Caroline Dykstra thesis draft Sept 6 - The Atrium

 Nitrogen fixation dynamics of Brachiaria decumbens and four shrubby legumes in a pasture system in Northeastern Brazil by Caroline S. Dykstra A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science in Environmental Sciences Guelph, Ontario, Canada © Caroline S. Dykstra, September, 2013 ABSTRACT NITROGEN FIXATION DYNAMICS OF BRACHIARIA DECUMBENS AND FOUR SHRUBBY LEGUMES IN A PASTURE SYSTEM IN NORTHEASTERN BRAZIL Caroline S. Dykstra University of Guelph, 2013 Advisor: Dr. R. Paul Voroney Dr. J. Dubeux Nitrogen (N) fixation, herbage mass and botanical composition were measured in a silvopastoral system with shrubby legumes Bauhinia cheilantha, Gliricidia sepium, Leucena leucocephala and Mimosa caesalpiniifolia planted in grazed Brachiaria decumbens in Northeastern Brazil. A greenhouse study was conducted to determine the natural abundance δ15N of the legumes grown without soil N (B value), reported as 2.24‰ and 1.03‰ for G. sepium and L. leucocephala, respectively. In the field, G. sepium and M. caesalpiniifolia were significantly (p<0.05) larger then B. cheilantha and L. leucocephala and G. sepium and L. leucocephala fixed more N than the other legumes. Amount of fixed N in the grass ranged from 76.4% in the B. cheilantha paddocks to 58.2% in the M. caesalpiniifolia paddocks. The herbage mass of the B. decumbens pasture showed that control plots produced more grass in each time period then the legume-­‐grass plots due to competition and shading. ACKNOWLEDGEMENTS I’d briefly like to thank a number of people who helped me immensely with this project. Carolina Camara Lira, Felipe Cabral, Erick Rodrigo, Diego Coehlo, Socorro De Caldas Pinto and everyone else at the research station in Itambé. Also, my family there in Casa Verde – Cristina Camara, Maria Helena Lira and Carolina Camara Lira without whom I wouldn’t have survived a week! Muitobrigada for inviting me into your home and treating me like family – not to mention the food and fun. Thanks also for the patience you showed while I learned how to communicate, behave and live in Brazil. You taught me, and continue to teach me so much about life and culture. I’d also like to thank my support network in Canada – my friends and family who encouraged me, challenged me and loved me throughout this experience. Finally, I’d like to thank my advisors: Dr. Voroney, you have believed in me throughout this project and always had a word of encouragement when I needed it! Dr. Dubeux, thanks you for allowing me to come to Brazil and for helping me there with all those details small and large. Thank you also for your feedback throughout the process, your input has been hugely helpful. iv TABLE OF CONTENTS Chapter 1 Introduction and Literature Review..................................................................................2 1.1 Introduction .............................................................................................................................................................2 1.1.1 Research Context ...............................................................................................................................................2 1.1.1.1 Research aims ...........................................................................................................................................2 1.1.1.2 Research approach .................................................................................................................................2 1.1.1.3 Research relevance.................................................................................................................................3 1.2 Literature Review .................................................................................................................................................3 1.2.1 Pastures.................................................................................................................................................................3 1.2.1.1 Pasture degradation...............................................................................................................................3 1.2.1.2 Causes of degradation ...........................................................................................................................4 1.2.1.2.1 Poor soil................................................................................................................................................5 1.2.1.2.2 Overstocking.......................................................................................................................................5 1.2.1.2.3 Grass monocultures .........................................................................................................................6 1.2.1.3 Solutions to pasture degradation: legume-­‐grass intercropping .........................................7 1.2.1.3.1 Legume persistence and production .........................................................................................8 1.2.1.3.2 Competition and soil N availability ...........................................................................................8 1.2.1.3.3 Stress .....................................................................................................................................................9 1.2.1.3.4 Grazing pressure............................................................................................................................ 10 1.2.2 N-­transfer between grass and legumes.................................................................................................. 10 1.2.3 Tree legumes .................................................................................................................................................... 12 1.2.3.1 Bauhinia cheilantha............................................................................................................................. 13 1.2.3.2 Gliricidia sepium................................................................................................................................... 13 1.2.3.3 Leucaena leucocephala ...................................................................................................................... 15 1.2.3.4 Mimosa caesalpiniifolia ..................................................................................................................... 16 1.3 References .............................................................................................................................................................. 17 Chapter 2 Assessment of growth and 15N natural abundance of shrubby legumes grown in five soil-­sand combinations in a pot study.........................................................................................2 2.1 Introduction .......................................................................................................................................................... 25 2.2 Materials and Methods.................................................................................................................................... 26 2.2.1 Establishment .................................................................................................................................................. 27 2.2.2 Maintenance..................................................................................................................................................... 28 2.2.3 Sampling ............................................................................................................................................................ 29 2.2.5 Statistical analysis ......................................................................................................................................... 29 2.3 Results and Discussion.................................................................................................................................... 30 2.3.1 Soil fertility........................................................................................................................................................ 30 2.3.2 Plant production: height and biomass ................................................................................................... 31 2.3.3 Total N and δ15N natural abundance ..................................................................................................... 33 2.3.4 Percent Nitrogen derived from fixation (%Ndfa) .............................................................................. 35 2.4 Conclusions ............................................................................................................................................................ 37 2.5 References:............................................................................................................................................................. 37 Chapter 3 Herbage mass production and botanical composition of a B. decumbens silvopasture with four shrubby legumes.............................................................................................. 25 3.1 Introduction .......................................................................................................................................................... 42 v 3.1.1 Brachiaria grass ............................................................................................................................................. 42 3.1.1.1 Grazing effects........................................................................................................................................ 43 3.1.1.2 Compatibility with legumes ............................................................................................................. 43 3.1.1.3 Tolerance to shading........................................................................................................................... 44 3.1.1.4 Competition for water ........................................................................................................................ 45 3.3 Materials and Methods.................................................................................................................................... 46 3.3.1 Study site............................................................................................................................................................ 46 3.3.2 Experimental design...................................................................................................................................... 47 3.3.3 Plant Sampling ................................................................................................................................................ 50 3.3.4 Statistical analysis ......................................................................................................................................... 51 3.4 Results and Discussion.................................................................................................................................... 51 3.4.1 Height of legume shrubs .............................................................................................................................. 51 3.4.2 Botanical composition.................................................................................................................................. 52 3.4.2.1 Percent signal grass............................................................................................................................. 52 3.4.2.2 Percent bare soil ................................................................................................................................... 54 3.4.2.3 Percent other species.......................................................................................................................... 55 3.4.2.4 Unfertilized signal grass, fertilized signal grass and P5 ...................................................... 56 3.4.3 Productivity ...................................................................................................................................................... 57 3.4.3.1 Grass-­‐legume treatments.................................................................................................................. 57 3.4.3.2 Unfertilized signal grass, fertilized signal grass and P5 ...................................................... 60 3.5 Conclusions ............................................................................................................................................................ 61 3.6 References .............................................................................................................................................................. 61 Chapter 4 15N natural abundance of four shrubby legumes, B. decumbens, litter and soil in a grazed pasture system in Northeast Brazil.................................................................................. 65 4.1.1 Measuring N-­fixation: Natural abundance of 15N.............................................................................. 66 4.1.1.1 Reference species ................................................................................................................................. 67 4.1.1.2 Isotopic discrimination ...................................................................................................................... 67 4.1.1.3 B-­‐value ...................................................................................................................................................... 68 4.1.1.4 Fractionation .......................................................................................................................................... 68 4.1.2 Estimates of N fixation of legumes........................................................................................................... 69 4.1.3 Transfer of N from legumes........................................................................................................................ 69 4.1.4 Effects of grazing............................................................................................................................................ 70 4.2 Materials and Methods.................................................................................................................................... 70 4.2.1 Study site and experimental design......................................................................................................... 70 4.2.2 Sampling ............................................................................................................................................................ 70 4.2.4 Analysis............................................................................................................................................................... 71 4.2.4.3 Statistical analysis ................................................................................................................................ 71 4.3 Results and Discussion.................................................................................................................................... 72 4.3.1 Soil........................................................................................................................................................................ 72 4.3.1.1 Soil fertility.............................................................................................................................................. 72 4.3.1.2 Soil total N and δ15N natural abundance.................................................................................... 72 4.3.1.2.1 Grass-­legume paddocks............................................................................................................... 73 4.3.1.2.2 Fertilized and unfertilized signal grass................................................................................. 75 4.3.2 Litter total N and δ15N natural abundance.......................................................................................... 76 4.3.2.1 Grass-­‐legume paddocks..................................................................................................................... 76 4.3.2.2 Fertilized and unfertilized signal grass....................................................................................... 78 4.3.3 Legume total N and δ15N natural abundance ..................................................................................... 79 vi 4.3.4 Grass total N and δ15N natural abundance .......................................................................................... 81 4.3.4.1 Grass-­‐legume paddocks..................................................................................................................... 81 4.3.4.2 Fertilized and unfertilized signal grass....................................................................................... 83 4.3.5 Percent nitrogen derived from the atmosphere ................................................................................. 84 4.3.5.1 Percent nitrogen from fixation in legumes................................................................................ 84 4.3.5.2 Percent nitrogen from fixation in grass...................................................................................... 85 4.4 Conclusions ............................................................................................................................................................ 86 4.5 References .............................................................................................................................................................. 86 Chapter 5 Conclusions and Recommendations for Further Study............................................ 63 5.1 Conclusions and Recommendations for Further Study................................................................ 92 vii LIST OF TABLES Table 2.1. Species of plant and common name shown with corresponding strain of bacteria (Lira, personal communication, October 2012)...................................................................................................... 28 Table 2.2. Preparation of N-­‐free Hoagland’s solution (adapted from Hoagland and Arnon 1950).
.......................................................................................................................................................................................... 28 Table 2.3. Soil fertility data analyzed at UFRPE. Averages shown for each soil treatment with Type III variance analysis within rows. ..................................................................................................................... 31 Table 2.4. Mean plant height (cm) of three shrubby legumes with calculated LSD (P<0.05) for the interaction of species*soil treatment. ............................................................................................................. 32 Table 2.5. Mean plant height (cm) of three shrubby legumes with calculated LSD (P<0.05) for the interaction of species*cycle. ................................................................................................................................ 32 Table 2.6. Total N and δ15N of soil across four legumes and five soil treatments.................................. 33 Table 2.7. LSD of δ15N and total N of plant material across four legumes and five soil treatments. Letters represent statistical difference across rows................................................................................. 34 Table 2.8. Comparisons of percent nitrogen derived from the atmosphere (%Ndfa) of the legume Leucena using three ‘B’ values............................................................................................................................ 36 Table 2.9. Comparisons of percent nitrogen derived from the atmosphere (%Ndfa) of the legume Gliricidia using three ‘B’ values.......................................................................................................................... 36 Table 3.1. Experimental treatments shown by species ..................................................................................... 48 Table 3.2. Schedule of sampling cycles for Itambé field project 2010-­‐2011............................................ 49 Table 3.3. Position of quadrat points in relation to the legume hedgerow............................................... 50 Table 3.4. Average height (m) of legume shrubs in August 2010 to August 2011. ............................... 52 Table 3.5. Analysis of variance of three sources of variation in four legume-­‐grass plots. ................. 53 Table 3.6. LS Means of % signal grass for significant effects of four legume-­‐grass pastures It shows the cycle*point interaction for gliricidia and sabiá, point effect for mororó and cycle effect for leucena. Letters represent significant differences (P=0.05) within each legume species........................................................................................................................................................................... 53 Table 3.7. Type III test of fixed effects of % bare soil in legume-­‐grass pasture plots. ......................... 54 Table 3.8. LS Means of species*point*cycle interactions of % bare soil in four legume-­‐grass pastures. Letters represent significant differences (P=0.05). SE=0.07 ............................................ 55 Table 3.9. Type III test of fixed effect of % other species in legume-­‐grass pasture plots................... 55 Table 3.10. LS Means of % other species for species*point interactions in legume-­‐grass pastures.
.......................................................................................................................................................................................... 56 Table 3.11. LS Means of % other species for point*cycle interactions in legume-­‐grass pastures.. 56 Table 3.12. LS Means of herbage mass (Mg ha-­‐1) of pasture grass by legume-­‐species treatment. Estimates followed by the same letter are not different at P<0.05. ................................................... 57 Table 3.13. LS Means of herbage mass (Mg ha-­‐1) of pasture grass by cycle. Estimates followed by the same letter are not different at P<0.05. .................................................................................................. 58 Table 3.14. Type III Test of Fixed Effects for pasture productivity (Mg ha-­‐1 herbage mass) in cycle, point and cycle*point interactions for four treatments analyzed separately................................ 58 Table 3.15. LS Means of grass herbage mass (Mg ha-­‐1) in quadrats at points P1-­‐P5 away from the legume trees. Statistical comparisons are within columns.................................................................... 59 Table 3.16. Type III test of fixed effects for unfertilized signal grass, fertilized signal grass and P5 of legume treatments when herbage mass (Mg ha-­‐1) of grass was measured............................... 60 viii Table 4.1. P-­‐values (at type 3 error rate of 0.05) of soil fertility parameters across effects of a variance analysis. ..................................................................................................................................................... 72 Table 4.2. Type 3 fixed effects of soil δ15N and % total N values analyzed across 6 species, 2 cycles, 5 points and 3 depths............................................................................................................................... 73 Table 4.3. LS means of soil δ15N and % total N in four legume treatments measuring P1 and P5 across 3 depths.......................................................................................................................................................... 74 Table 4.4. Type 3 fixed effects of soil δ15N and % total soil N values analyzed in signal grass and fertilized signal grass plots, over 2 cycles, and at 3 depths. .................................................................. 75 Table 4.5. LS Means of soil δ15N species*depth interaction and % total N depth effect. .................... 75 Table 4.6. Type III variance analysis of litter showing δ15N and % total N. ............................................. 76 Table 4.7. LS means of legume cycle*species interaction for % total N of litter in four legume-­‐
grass paddocks. ......................................................................................................................................................... 77 Table 4.8. LS means of δ15N (‰) of litter in four legume-­‐grass paddocks............................................... 78 Table 4.9. Variance analysis of δ15N and total N of fertilized and unfertilized signal grass litter... 78 Table 4.10. LS means of litter δ15N (‰) and total N (%) for fertilized and unfertilized signal grass over 3 cycles. .............................................................................................................................................................. 79 Table 4.11. Variance analysis of δ15N and total N for 4 legumes................................................................... 79 Table 4.12. LSD of δ15N (%0) values of four legume trees over three cycles. .......................................... 80 Table 4.13. LSD of % total N values of four legume trees over three cycles for cycle*species interaction. .................................................................................................................................................................. 81 Table 4.14. Type III variance analysis of δ15N and total N of grass in four legume-­‐grass treatments over three cycles and five points....................................................................................................................... 81 Table 4.15. LS means of δ15N (%0) of pasture grass in four grass-­‐legume treatments over 3 cycles and five transect points. ........................................................................................................................................ 82 Table 4.16. LS Means of % total N of pasture grass in species*cycle interaction in four legume paddocks. ..................................................................................................................................................................... 83 Table 4.17. LS Means of % total N of pasture grass in species*point interaction in four grass-­‐
legume paddocks...................................................................................................................................................... 83 Table 4.18. Percent Ndfa of four legumes over 3 cycles in a silvopastoral system planted with signal grass.................................................................................................................................................................. 84 Table 4.19. Percent Ndfa of grass in legume paddocks. .................................................................................... 85 Table 4.20. Percent Ndfa of grass in legume paddocks by transect point................................................. 85 ix LIST OF FIGURES Figure 1.1. Conceptual model of the major factors which interact to determine the level of nitrogen fixation in a pasture (Adapted from Ledgard and Steele 1992). .........................................8 Figure 3.1. Average annual precipitation (bars) and maximum and minimum temperatures (lines) per month 2002-­‐2012 for the Agricultural Research Station of Itambé (SINDA, Copyright 2009)........................................................................................................................................................ 47 Figure 3.2. Plan view of paddock showing 3 legume hedgerows, each with 2 rows of trees with 10 m of grass pasture between................................................................................................................................. 48 Figure 3.3. Plot design for legume plots showing 3 hedgerows. ................................................................... 49 Figure 3.4. Rise plate meter........................................................................................................................................... 50 Figure 4.1. Box chart showing mean δ15N (%0) of legume species when grown in paddocks with signal grass.................................................................................................................................................................. 80 x ________________________________________________________________________________________________________________ Chapter 1 Introduction and Literature Review 1.1 Introduction 1.1.1 Research Context Nitrogen (N) is a key nutrient affecting the health and sustainability of ecosystems (Brady and Weil 2002). With rising fuel costs and increased attention on environmental degradation, chemical fertilization is not always an economically feasible or ecologically sound farming practice (Fan et al. 2006). Natural methods of fertilization exist in which microorganisms that can convert dinitrogen (N2) to plant usable forms exist either as free-­‐living species or in association with plants (Hohnwald et al. 2006; Unkovich et al. 2010). These systems, used for centuries by farmers, are gaining new attention as environmental and economic concerns change the way we view conventional agriculture. A plethora of research exists regarding the use of legumes in agriculture and in degraded land rehabilitation. This research developed over a long period of time and many new techniques and theories have surfaced to spur faster, simpler and more economical methods of studying nitrogen fixation. However, management of the process is inherently complicated, and further understanding to aid farmers and researchers is required to ensure its success across a variety of systems. 1.1.1.1 Research aims The aim of this research was to provide information about N fixation in a degraded pasture ecosystem in northeastern Brazil. It used the natural abundance 15N technique to quantify the amounts of N fixed in a field and greenhouse setting. The goal of this research was to describe the N fixation abilities of a number of legumes and how this input of N affects the growth dynamics of associated grasses. The N derived from N2 fixation in the grasses was also measured. 1.1.1.2 Research approach The first chapter outlines the most pertinent research regarding pasture degradation in the tropics and the problems and promise surrounding legume-­‐grass intercropping in pastures. The 2 following three chapters each involve a finite but related research paper. The final chapter contains the recommendations for further research. 1.1.1.3 Research relevance This research contributes to a growing pool of knowledge regarding N fixation dynamics in grass-­‐
legume pastures. This information is important to understand and improve pasture management techniques in order to avoid land degradation. Silvopasture can provide multiple products and increase the quality of life of livestock and farmers, as well as contributing to enhanced soil and ecosystem quality. 1.2 Literature Review 1.2.1 Pastures Forest and natural grassland ecosystems are rapidly converted into agricultural lands in the tropics (Geissen et al. 2009). This is due to population pressures and poor management of existing agricultural lands (Barbier 2004). In many places, such as the Brazilian Amazon basin, the major conversion of land is to grazed pastures for cattle production (Luizao et al. 1992). A study by Amezquita et al. (2005) suggested that more than 77% of the agricultural land in tropical America, an area distinguished as Mexico, Central America, the Caribbean and South America excluding Argentina, Chile and Uruguay, is used for grazing. Of this, more than 60% is degraded (Amézquita et al. 2005). 1.2.1.1 Pasture degradation In 2009, Brazil had an estimated 209 million head of cattle fed on more than 196 million ha of cultivated pastures and rangelands (Dubeux et al. 2011; FAOSTAT 2011). This land exists specifically in the Cerrados, Atlantic Forest and Amazon ecoregions. Often, these pastures are not well managed and reach advanced states of degradation after 4-­‐10 years of production (Hohnwald et al. 2006; Lilienfein et al. 2003). In Brazil an estimated 50 million ha of degraded 3 pasture exist, 12.5 million ha in the Amazon alone (Hohnwald et al. 2006; Trannin et al. 2000). These pastures are able to support 1-­‐2 animal units per ha of land for the first few years but productivity soon declines, which allows for weed invasion, plant cover decreases and termite mounds appear. At this point the pastures can only support 0.5 animal units per ha (de Oliveira et al. 2004). When pastures become severely degraded, the land is no longer productive and is often abandoned (Bouman et al. 1999). This results in the need for new, undeveloped land to be used for pastureland, to compensate for the decreased productivity (de Oliveira et al. 2004, Barbier 2004). The new lands are often forestlands and result in deforestation (Barbier 2004). Barbier (2004) reported that annual clearing of land reached 15 million ha between 1980 and 1990 dropping to 12 million ha between 1990 and 2000. Over 50% of this deforestation was for direct conversion into agricultural land (Barbier 2004). Similarly, Geissen et al. (2009) in a historical comparison of land use in the Tabasco state of Mexico found that in 1940, 49% of the land area was forest and 21% was grassland, whereas in 2009 5.6% was forest and 53.8% was managed grassland. Deforestation causes greenhouse gas emissions and has a negative effect on biodiversity (Bouman et al. 1999, Carvalho 2009). Bouman et al. (1999) reported that deforestation has led to a net release of CO2 with annual emissions of 0.4-­‐1.6 x 109 ton carbon (C) per year in Costa Rica. Emissions of N2O and NO are also caused when forestland is converted due to both the burning of the forest biomass and the changes in the N and C cycles that ensue (Bouman et al. 1999; Luizao et al. 1992). Deforestation also increases habitat fragmentation, which Carvalho (2009) found to have a strongly negative effect on biodiversity. Conversion to pastureland also increases CH4 emissions from livestock (Bouman et al. 1999). 1.2.1.2 Causes of degradation A complex set of factors is involved in pasture degradation. The resulting decline in productivity and change in botanical composition are well documented (Myers and Robbins 1991), however, Kenichi et al. (2002) reported that there is a lack of knowledge on the causes of degradation. Moreover, Geissen et al. (2009) suggested that the information relating to soil quality that would 4 allow us to determine the causes of these problems are still deficient because the concepts and research were developed and performed in temperate climates and cannot be readily applied to the tropics. Poor soil, overstocking, and grass monocultures, some of the more prominent factors, are discussed below (Bouman et al. 1999). 1.2.1.2.1 Poor soil The Tropics are characterized by Ferralsolic soils, often with low pH and high Al availability (Kenichi et al. 2002; San José et al. 2003; Wilcke and Lilienfein 2004). These soils are generally highly weathered with low N and phosphorus (P) availability (Kenichi et al. 2002; Trannin et al. 2000). Due to socio-­‐economic factors, N and P fertilizers are often not applied to tropical pastures (Kenichi et al. 2002). The result is that N is removed from the soil at a faster rate then it is replenished, a state called N mining (Bouman et al. 1999). Bouman et al. (1999) estimated that N was mined from tropical pasture soils at annual rates as high as 65-­‐94 kg ha-­‐1. This nutrient supply problem has been shown to be the biggest cause of growth limitation in pastures (Boddey et al. 2004). 1.2.1.2.2 Overstocking Over-­‐stocking of pastures has been cited as a cause of pasture degradation in the tropics (Bouman et al. 1999). Grazing more animal units per ha on a paddock then is sustainable based on the limitations of the land for growing pasture forage is considered over-­‐stocking (de Oliveira et al. 2004). This exacerbates removal of nutrients where losses are much greater than inputs and soil nutrients are mined from the mobile soil pools (Bouman et al. 1999). Also, continual defoliation of plants, without rest periods, as often happens with overgrazing, will eventually kill the plants (Bushby 1992). Over-­‐stocking also tends to result in variable deposition of nutrients, with more nutrients being deposited in high traffic areas around water supplies or shaded areas (de Oliveira et al. 2004; Dubeux et al. 2007). These areas are more highly compacted then other areas, often with bulk density levels higher than the threshold value in which roots will grow (Geissen et al. 2009). As a result, fewer plants grow in the compacted areas causing a majority of the nutrients deposited 5 there to be lost by volatilization, leaching, erosion and runoff (de Oliveira et al. 2004). Bouman et al. (1999) suggested that if stocking rates were adapted to carrying capacity, then pastures could be productive over the long-­‐term. 1.2.1.2.3 Grass monocultures Degradation of pastures is further exacerbated by the planting of grass monocultures, a practice that is common throughout the tropics (Boddey et al. 2004). Brachiaria decumbens (signal grass) and two other species, Panicum maximum and Andropogon gayanus have been planted on more than 80 million ha of land in Brazil (Boddey et al. 2004; Bonfim-­‐Silva and Monteiro 2006) and account for more than 10% of the entire land area of the country (de Oliveira et al. 2004). These grasses are mostly species of African or Australian origin that have been adopted for use due to various morphological characteristics that make them well suited to the climate of tropical America (Boddey et al. 2004; Bonfim-­‐Silva and Monteiro 2006). This interest began in the 1960s with the discovery of the advantages of their adaptation to acid infertile soils (with pH < 5.5) (Louw-­‐Gaume et al. 2010). The planted grasses, however, are often less well adapted to conditions of low N availability and low soil water content then native grasses and forbs (Myers and Robbins 1991). While these imported C4 grass species are well adapted to acidic soil conditions, the subsequent accumulation of high C/N ratio litter and root material leads to an increase in net N immobilization rate by soil microorganisms (Andrade et al. 2010). This in turn decreases soil inorganic N availability which decreases grass productivity (Urquiaga et al. 1998). Cadisch et al. (1994) similarly suggested that monocultures of grasses lead to a reduction in N mineralization rate in the soil. Xavier et al. (2011) suggest this change in C/N ratio is the principal cause of pasture degradation in the tropics. Brachiaria decumbens (signal grass), one of the most commonly found grasses in Brazil, was introduced from Africa via Australia in the 1970s (Boddey et al. 2004; Louw-­‐Gaume et al. 2010). It is a C4 grass that grows well in nutrient poor sites in the tropics and can tolerate both 5 months of dry season and short-­‐term flooding (Cook et al. 2005). It is easily established by broadcast planting, spreads quickly to cover soil and is well adapted to heavy defoliation (Cook et al. 2005). 6 It has a moderately high palatability for animals and a good nutritive value, with between 50 and 80% digestibility (Cook et al. 2005). It responds well to N and P fertilizer with yields between 10 and 30 ton/ha/year dry matter under fertilization. It can result in animal production of 340 kg ha-­‐1 yr-­‐1 live weight gain in Brazil and 1290 kg live weight gain in Queensland, Australia (Cook et al. 2005). It is relatively free from diseases and pests, but is susceptible to spittlebugs of the genus Aeneolamia, Deois and Zulia (Cook et al. 2005). Despite the plethora of advantages of B. decumbens, there are more than 25 million ha of degraded pasture planted with this grass in Brazil (de Oliveira et al. 2004). 1.2.1.3 Solutions to pasture degradation: legume-­grass intercropping Research from a variety of sources over the past decades has investigated intercropping of multiple species in pastures. Specifically, many sources have found that intercropping legumes with grass in pastures can increase pasture sustainability and maintain productivity (Akinola 1981; Cadisch et al. 1994). Forage legumes are palatable to animals and use mostly atmospheric N2, as opposed to soil mineral N. This is thought to have a positive impact on sustainability by adding N to the pasture system over time (Miller and Stockwell 1991). Due to this N advantage, legumes can act to increase dry matter, total N, mineral content, and animal live weight gain in a pasture system (Akinola 1981). However, legumes vary greatly in adaptation and morphology; furthermore, competition with grass and low persistence in multi-­‐species systems can undermine any advantages if legumes are not properly selected (Miller and Stockwell 1991). Ledgard and Steele (1992) created a conceptual model (Figure 1.1) of the major factors that affect a pasture system and determine the level of N fixation possible. They suggested that legume persistence and productivity, competitiveness of associated grasses, stress level and soil N level affect legume N2 fixation in a pasture. 7 Figure 1.1. Conceptual model of the major factors which interact to determine the level of nitrogen fixation in a pasture (Adapted from Ledgard and Steele 1992). 1.2.1.3.1 Legume persistence and production Legume persistence is one of the biggest problems associated with legume-­‐grass pastures in the tropics (Miller and Stockwell 1991). Often legumes are the preferred plant for livestock consumption, causing the legumes to be defoliated more rapidly and frequently than other species in the pasture. Furthermore, legume production can vary greatly between species with different growth habits and soil requirements. The resulting competitive disadvantage tends to increase the spread of grass or weed species in the paddock and decreases legume productivity of the legume (Cadisch et al. 1994). To exacerbate the problem, establishment of legumes can be slow and costly (Miller and Stockwell 1991). Miller and Stockwell (1991) suggested that it can take 2-­‐8 years to fully establish a productive legume-­‐grass pasture. This large time frame may be a function of weather, time of sowing, vigour of the pasture, and species of legume planted (Miller and Stockwell 1991). Cadisch et al. (1994) suggest planting legumes with low palatability is a possible solution. 1.2.1.3.2 Competition and soil N availability Competition can also become a problem as grass-­‐legume mixtures can work in two ways: the legume can increase the available N in the soil or the legume can compete with the grass for soil 8 N (Vallis et al. 1977). Grass species often have a competitive advantage in terms of having larger, fibrous root systems, high N and P utilization efficiency, and tolerance to grazing (Trannin et al. 2000). Brachiaria species are particularly known for producing vigorous tillers, which often suppress legumes species (Ibrahim and Mannetje 1998). Competition has also been shown to increase N fixation as legumes with decreased access to soil N produce more fixed N (Forrester et al. 2007). As availability of other sources of N increase, legume fixation rates decrease. Allos and Bartholomew (1955) and Norman and Krampitz (1943) were among the first to report this fertilization effect, showing that N fertilization decreased but did not completely inhibit N fixation in legumes. Similarly, Salvagiotti et al. (2008) found a negative exponential relationship between fertilizer rate and N fixation in a review of soybean studies. 1.2.1.3.3 Stress Growth and fixation efficiency in legumes varies dramatically from close to zero to near 100% based on environmental and physiological factors (Ledgard and Steele 1992). These factors can affect both legume plants and their associated diazotrophic bacteria. Soil characteristics including acidity, temperature, salinity or alkalinity and mineral nutrition have specifically been found to change fixation efficiency (Graham 2005). In acid soils (pH < 5.0), three mechanisms of stress exist which affect legume growth and persistence. First, many rhizobial bacteria are sensitive to hydrogen ion concentrations causing a decreased rate of nodulation in legumes (Graham 2005). Second, acid soils often have toxic levels of aluminum and manganese, which limits root growth and nodulation in plants (Graham 2005). Lastly, high acidity in soils can induce deficiencies of elements essential in nodule formation and plant growth, specifically calcium, phosphorus and molybdenum (Brady and Weil 2002). Temperature tends to affect rhizobia more than legume plants, whereas soil salinity and alkalinity have more of an effect on legume plants than on rhizobia. Rhizobia are mesophiles and generally only grow at temperatures between 10 °C and 37 °C (Graham 2005). While high 9 salinity can directly effect and damage plant cells, alkalinity acts to reduce availability of iron, zinc, manganese and boron in the soil (Graham 2005). These stresses can limit N-­‐fixation in a pasture system. 1.2.1.3.4 Grazing pressure The introduction of cattle into pasture systems significantly changes grassland ecosystems. Cattle apply stress by defoliating plants, trampling soil and plants and redistributing nutrients. Cattle consume grass and legume material from a pasture and redeposit the nutrients in the form of urine and feces. Nitrogen loses of 4-­‐66% have been reported after urination events due to leaching or volatilization (Ryden 1986 in Dubeux et al. 2007). Loss of N, potassium (K) and sulfur (S) also result from feces (Haynes and Williams 1993). In tropical pastures, animal excreta are often distributed close to water supplies and shaded areas. Haynes and Williams (1993) measured excretal patches or hot spots and found they covered 30-­‐40% of total pasture area. This can cause an increased accumulation of P and N in these location and greater growth of plants, contributing up to 70% of plant production (Dubeux et al. 2006; Dubeux et al. 2007; Haynes and Williams 1993). Stocking rate and grazing method affect the amount of plant material consumed, amount of excreta deposited and distribution of excreta. Boddey et al. (2004) found high stocking rates as an indicator for grassland degradation due to greater losses of nutrients through excreta. Greater forage utilization could also affect soil nutrient dynamics and long-­‐term pasture productivity (Franzluebber et al. 2004). 1.2.2 N-­transfer between grass and legumes The transfer of fixed N between grass and legumes in pastures is an important interspecific facilitation and a potential measure of the sustainability of the pasture in the long-­‐term (Høgh-­‐
Jensen and Schjoerring 2000; Ledgard et al. 1985;). Estimates of N-­‐transfer, however, differ significantly due to species, environmental variability and measurement techniques. Høgh-­‐Jensen and Schjoerring (2000) used two techniques: a direct technique in which leaves were immersed in a 15NH4 solution and an indirect technique where 15N was applied to the soil of plots. They 10 found that transfer with the direct technique was more than double that with the indirect technique, suggesting that a direct method was more accurate (Høgh-­‐Jensen and Schjoerring 2000). Viera-­‐Vargas et al. (1995) suggested that over 30% of N in tropical grasses is derived from N2 fixation by legumes whereas Ledgard et al. (1985) suggested a number closer to 2.2%. Creating general estimates of transfer within a complex set of transfer mechanisms estimated using varying techniques is not an easy task. A number of different pathways of N-­‐transfer exist. Belowground transfers can occur from mineralization of decaying roots and nodules, root exudates or direct transfer via mycorrhizal hyphae (Pirhofer-­‐Walzl et al. 2012; Trannin et al. 2000). These transfers likely necessitate a close association between the grass and legume and a high ratio of legume to grass (Høgh-­‐Jensen and Schjoerring 2000). Aboveground transfers may occur via litter decomposition, however this is seen to be less significant then belowground mechanisms (Thomas and Asakawa 1993). N transfer is a bi-­‐directional process dependant on facilitation and competition between the legumes and grasses involved (Høgh-­‐Jensen and Schjoerring 2000). This means that N is transferred from legumes to grasses; however, N is also transferred from grasses to legumes (Pirhofer-­‐Walzl et al. 2012). This likely occurs by root exudation, dying roots and leaf leachates, which can be taken up by legumes or grass species (Dahlin and Stenberg 2010; Pirhofer-­‐Walzl et al. 2012). For example, as N is transferred to grass, the grass gains a competitive advantage and increases production. This larger plant then leads to an increase in root and shoot litter quantity and quality, increasing mineralization of N for uptake by legume or non-­‐legume species (Trannin et al. 2000). Haystead and Marriott (1979) found transfer only after the 4th harvest of pots containing white clover and perennial ryegrass. They suggest that the clover can re-­‐assimilate much of the senesced N after a harvest or that soil fauna assimilate the N into microbial biomass faster than the grass species can uptake the N (Haystead and Marriott 1979). Pot experiments, which work on the principle of having donor and receiver plants, are a popular method to measure N-­‐transfer between plant species (Moyer-­‐Henry et al. 2006). Many of these experiments use a fine mesh (25-­‐60 μm) screen inserted between the donor and receiver plants, which excludes plant roots but allows hyphae of arbuscular mycorrhizal fungi to growth between the plants. These studies indicate that mycorrhizal linkages increase N-­‐transfer and may even be 11 essential for transfer to occur (Bethlenfalvay et al. 1991; Frey and Schuepp 1992; Haystead et al. 1988). However, there is poor agreement on general transfer amounts, with some researchers finding <5% of N in receiver plants transferred from the legume (Frey and Schuepp 1992; Johansen and Jensen 1996; Martin et al. 1991) while others suggested transferred N can contribute 10-­‐20% (Bethlenfalvay et al. 1991; Haystead et al. 1988; Martins and Cruz 1998; Van Kessel et al. 1985). Field experiments, however, are less quantifiable and generally have examined growth and N yield of plants, which is then equated to N-­‐fixation without specifying a transfer mechanism (Høgh-­‐Jensen and Schjoerring 2000; Martin et al. 1991). Other researchers indicated different transfer mechanisms as being as important as fungal hyphae. Simpson (1976), for example, suggested that the majority of N transfer must occur after senescence, not necessarily through mycorrhizal fungi. Moyer-­‐Henry et al. (2006) studied N transfer to mycorrhizal and non-­‐mycorrhizal weeds in soybean and peanut (Arachis hypogaea L.) cropping systems. While most of their significant transfer events took place in systems where mycorrhizae were present, they found a 30% transfer from peanut to yellow nutsedge (Cyperus esculentus L.), a non-­‐mycorrhizal species. They suggest that this was likely due to N leakage or tissue senescence and subsequent mineralization of legume N (Moyer-­‐Henry et al. 2006). Trannin et al. (2000) also suggested this, finding that in a B. decumbens – S. guianensis experiment the main pathway to N transfer was decomposing roots. Ledgard et al. (1985) measured transfer of N during the growing season in a ryegrass (Lolium rigidum Gaud.) -­‐clover (Trifolium subterraneum L.) pasture. They used the isotope dilution technique in a pot experiment and found that 2.2% of the clover N was transferred to the grass after 29 days (Ledgard et al. 1985). Their longer experiment using mini-­‐plots, however, showed no significant transfer of N from legume to grass after 36 days. They suggested that the pot experiment would show a more significant effect because there was a greater concentration of roots in a restricted area and therefore whatever N the legume roots were secreting was taken-­‐
up directly by grass roots (Ledgard et al. 1985). However, this may mean that pot experiments are not indicative of transfer mechanisms in a field environment (Moyer-­‐Henry et al. 2006). 1.2.3 Tree legumes 12 Silvopasture is an agroforestry method in which trees, shrubs and forages are combined in a livestock system (Shrestha and Alavalapati 2004). The use of tree legumes in silvopasture has gained attention over the past two decades because legume trees are long-­‐lived and require low levels of maintenance (Gutteridge and Shelton 1994). They also provide a wide array of direct and indirect economic advantages for farmers (Gutteridge and Shelton 1994). Leguminous trees can be used as secondary marketable products (timber or fuel wood), as forage for grazing animals, to protect the soil from erosion, recycle nutrients from depth, prevent leaching losses, increase soil N through adding fixed N in litter, and long term accumulation of C and N in the soil (Nygren and Leblanc 2009; Peoples et al. 1996; Van Kessel et al. 1994). These advantages are enhanced in the tropics, where growth rates are higher and the rate of litter decomposition is very rapid (Van Kessel et al. 1994). Four tree legumes are discussed below. Gliricidia sepium and Leucaena leucocephala are two of the most commonly used legume tree species in the tropics, whereas Bauhinia cheilantha and Mimosa caesalpiniifolia are not often used in silvopastoral systems and therefore are not well studied. 1.2.3.1 Bauhinia cheilantha Bauhinia cheilantha, commonly known as mororó is a leguminous tree native to the northeastern Brazilian dry forest Caatinga ecosystem (Gutiérrez et al. 2011; Santiago de Freitas et al. 2010). It is used for fodder as well as is known to have traditional medicinal value (Gutiérrez et al. 2011). Few studies exist considering its suitability to silvopastoral systems. Santiago de Freitas et al. (2010) studied native plants in the Brazilian Caatinga in both undisturbed and disturbed sites. They found a δ15N signature of the leaves of mororó to range from 9.92±0.72 to 6.30±1.56 in undisturbed sites and 7.63 to 5.87±0.63 at disturbed sites in the Pernambuco and Paraiba states of northeastern Brazil (Santiago de Freitas et al. 2010). 1.2.3.2 Gliricidia sepium Gliricidia sepium (gliricidia), a native plant of Central America, is used throughout the tropics as a tree legume (Simons and Stewart 1994). It is commonly used as a shade tree for coffee 13 plantations as well as for fodder, fuel, green manure, live fences and soil stabilization (Simons and Stewart 1994). Gliricidia is considered a medium-­‐sized tree, growing up to 12 m tall and is well suited for a wide range of soil types, including acid, infertile soils (Simons and Stewart 1994). Gliricidia can be planted from cuttings, re-­‐grows quickly after cutting, and can tolerate frequent defoliation (Simons and Stewart 1994). It can produce between 2 and 20 t ha-­‐1 yr-­‐1 and has high nutritive value as fodder; however, it is not very palatable (Simons and Stewart 1994). It also nodulates freely with rhizobia of the ‘cowpea miscellany group’, according to Kadiata et al. (1996). Peoples et al. (1996) evaluated G. sepium grown with Panicum maximum (Guinea grass) in Queensland, Australia. The study took cuttings seven times during a 117-­‐week period and found that the trees had 52-­‐58 t dry matter ha-­‐1 with a cumulative N yield of 1678 kg N ha-­‐1 of which 1063 kg N ha-­‐1 was estimated to have been from N2 fixation (Peoples et al. 1996). Nygren and Leblanc (2009), in a study of cacao (Theobroma cacao) grown with legumes in lowland Costa Rica, found that 56-­‐74% of N in G. sepium was derived from N2 fixation, which was more active in the rainy season than in the dry season (Nygren and Leblanc 2009). Saginga et al. (1995) found the percent nitrogen derived from the atmosphere (%Ndfa) to be 35%, 24 weeks after planting, and 54%, 48 weeks after planting in a study in southwestern Nigeria. They examined δ15N in different plant parts and found that the difference between plant organs was small and therefore used stem estimates to complete the study (Nygren and Leblanc 2009). Studies using G. sepium indicated that it can transfer fixed N to forage crops (Jalonen et al. 2009a). Estimates using 15N natural abundance have shown 13-­‐42% in coffee (Coffea arabica L.) and 31-­‐35% in Dichanthium aristatum of N originated with fixation when these species were grown in association with G. sepium (Dulormne et al. 2003; Haggar et al. 1993; Sierra and Nygren 2006). These studies suggested that transfer of N occurred through the long-­‐term accumulation of legume residues (Jalonen et al. 2009b). A study by Jalonen et al. (2009b) found transfer between G. sepium and Dichanthium aristatum to be only about 0.8-­‐1.1% of the total N in the grass. The N exuded from the G. sepium roots was about 16% of grass total N content; however, the actual transfer seemed to need a direct connection between the two plants – either by roots or by mycorrhizal network (Jalonen et al. 2009b). The rest of the N exuded was thought to have 14 been immobilized by soil microorganisms (Jalonen et al. 2009a). This indicated that time frame of tree-­‐based intercropping is important. 1.2.3.3 Leucaena leucocephala Leucaena leucocephala (leucena) is the most widely used tree legume in the world (Van Kessel et al. 1994). It is known for its ability to grow rapidly after pruning, to provide good quality forage for animals, and its use as fuel wood (Högberg and Kvarnstdörm 1982; Peoples et al. 1996). Leucena can also be used for timber, human consumption, green manure, shade, and erosion control (Shelton and Brewbaker 1994). It is very drought tolerant and has deep roots, which can extend up to 5 m underground (Shelton and Brewbaker 1994). Leucena originated in Central America, but was quickly spread via the Spanish across most of South America, Asia, and later to Australia (Shelton and Brewbaker 1994). It was considered a ‘miracle tree’ in the 1970s and 1980s, however, it is sensitive to acidic soils and very susceptible to a psyllid insect (Heteropsylla cubana), decreasing its suitability in low-­‐input agriculture in the tropics (People et al. 1996). Also, leucena is very slow to establish taking up to 3 years to reach maturity (Shelton and Brewbaker 1994). According to Kadiata et al. (1996) leucena has a specific rhizobium symbiosis, creating problems for nodulation in soil that has not been inoculated. Kadiata et al. (1996) had a problem with growth of L. leucocephala in an acidic Ultisol due to nodulation problems. Inoculation of leucena generally improves growth, establishment and ensures effective nodulation (Shelton and Brewbaker 1994). Sanginga et al. (1989) found that inoculation increased nodulation, shoot dry matter and nitrogen content. Fertilization with phosphorus and calcium at planting is recommended, however, the addition of nitrogen fertilizer, has been shown to decrease N-­‐
fixation rates (Sanginga et al. 1989; Shelton and Brewbaker 1994). Sanginga et al. (1989) found that 40 kg N ha-­‐1 reduced N fixation by 43-­‐76%. Average annual aboveground biomass production of leucena can be very high, with high N yields (Shelton and Brewbaker 1994). Biomass production usually ranges from 1.6-­‐16.9 t ha-­‐1 yr-­‐1 (Lugo et al. 1990), but can be as high as 22 t ha-­‐1 yr-­‐1 in very good growing conditions (Van Kessel et al. 1994). It has also been shown to yield prunings with over 250 kg N ha-­‐1 yr-­‐1 (Guevarra 1976 15 in Kang and Gutteridge 1994). Nitrogen fixation rates of L. leucocephala have been shown as 110±30 kg N ha-­‐1 yr-­‐1 in Tanzania by Högberg and Kvarnström (1982) and 224-­‐274 kg N ha-­‐1 in six months by Saginga et al. (1986) in Nigeria. Sanginga et al. (1989), found a much lower quantity (134 kg and 98 kg ha-­‐1) in the same time period using the 15N dilution technique and two strains of rhizobium. They suggested this amount of N represents 34-­‐36% of the total N needed for plant growth. N-­‐transfer has also been found in leucena systems. Van Kessel et al. (1994) studied a L. leucocephala plantation on the island of Maui, Hawaii, U.S.A. harvested 6 years after planting and analysed parts of the trees and understory vegetation using the 15N natural abundance method. They found the understory vegetation to be significantly enriched in 15N compared to the leguminous trees in the first year of the study, but that the understory vegetation 15N enrichment declined steadily through the first 4 years of the study towards a value similar to that of leucena (Van Kessel et al. 1994). In the final harvest year the delta 15N values of the understory species and the leucena were not significantly different, indicating that they were deriving their N from the same N pool (Van Kessel et al. 1994). They suggested that the lower 15N enrichment of non-­‐
leguminous plants was due to a lowering of the 15N enrichment of the soil N pool brought about through the decomposition and recycling of legume plant litter (Van Kessel et al. 1994). Sandhu et al. (1990) found that the turnover time for all litter fractions of leucena was less than one year. They reported annual release of total N from above ground litter to be 208 kg ha-­‐1 (Sandhu et al. 1990). 1.2.3.4 Mimosa caesalpiniifolia Mimosa is a very diverse genera of over 500 species, many of which are native to South and Central America (Bueno dos Reis Jr. et al. 2010). The Brazilian ecoregions of the Cerrado and Caatinga are particularly rich in these species – many of which are endemic to their respective regions (Bueno dos Reis Jr. et al. 2010). Bueno dos Reis Jr. et al. (2010), studied Mimosa species in the Caatinga and found Mimosa caesalpiniifolia (sabiá) to be a nodulating species. 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63. Martins, M.A., and A.F. Cruz. 1998. The role of the external mycelial network of arbuscular mycorrhizal fungi: III. A study of nitrogen transfer between plants interconnected by common mycelium. Microbiological Reviews 29: 289-­‐294. Miller, C.P., and T.G.H. Stockwell. 1991. Sustaining productive pastures in the tropics 4. Augmenting native pastures with legumes. Tropical Grasslands 25: 104-­‐110. Moyer-­‐Henry, K.A., J.W. Burton, D.W. Israel, and T. W. Rufty. 2006. Nitrogen transfer between plants: a 15N natural abundance study with crop and weed species. Plant and Soil 282: 7-­‐20. Myers, R.J.K., and G.B. Robbins. 1991. Sustaining productive pastures in the tropics 5. Maintaining productive sown grass pastures. Tropical Grasslands 25: 104-­‐110. Norman, A.G., and L.O. Krampitz. 1945. The nitrogen nutrition of soybeans: II. Effect of available soil nitrogen on growth and nitrogen fixation. Soil Science Society of America Proceedings 10: 191-­‐196 (1946). Nygren, P., and H.A. Leblanc. 2009. Natural abundance of 15N in two cacao plantations with legume and non-­‐legume shade trees. Agroforestry Systems 76: 303-­‐315. Peoples, M.B., B. Palmer, D.M. Lilley, L.M. Duc, and D.F. Herridge. 1996. Application of N-­‐15 and xylem ureide methods for assessing N2 fixation of three shrub legumes periodically pruned for forage. Plant and Soil 182: 125-­‐137. Pirhofer-­‐Walzl, K., J. Rasmussen, H. Høgh-­‐Jensen, J. Eriksen, K. Søegaard, and J. Rasmussen. 2012. Nitrogen transfer from forage legumes to nine neighbouring plants in a multi-­‐species grassland. Plant and Soil 350: 71-­‐84. 21 Salvagiotti, F., K.G. Cassman, J.E. Specht, D.T. Walters, A. Weiss, and A. Dobermann. 2008. Nitrogen uptake, fixation and response to fertilizer N in soybeans: a review. Field Crops Research 108: 1-­‐
13. Sandhu J.M., M. Sinha, and R.S. Ambaht. 1990. Nitrogen release from decomposing litter of Leucaena leucocephala in the dry tropics. Soil Biology and Biochemistry 22: 859-­‐863. Sanginga, N., S.K. Danso, F. Zapata, and G.D. Bowen. 1995. Phosphorus requirements and nitrogen accumulation by N2-­‐fixing and non-­‐N2-­‐fixing leguminous trees growing in low P soils. Biology and Fertility of Soils 20: 205-­‐211. Sanginga, N., K. Mulongoy, and A. Ayanaba. 1986. Inoculation of Leucaena leucocephala (Lam.) de Wit with Rhizobium and its nitrogen contribution to a subsequent maize crop. Biology, Agriculture and Horticulture 3: 341-­‐347. Sanginga, N., K. Mulongoy, and A. Ayanaba. 1989. Nitrogen fixation of field-­‐inoculated Leucaena leucocephala (Lam.) de Wit estimated by the 15N and the difference methods. Plant and Soil 117: 269-­‐274. San José, J.J., R.A. Montes, and C. Rocha. 2003. Neotropical savanna converted to food cropping and cattle feeding systems: soil carbon and nitrogen changes over 30 years. Forest Ecology and Management 184: 17-­‐32. Santiago de Freitas, A.D., E.V. de Sá Barretto Sampaio, R.S.C. Menezes, and H. Tiessen. 2010. 15N natural abundance of non-­‐fixing woody species in the Brazilian dry forest (caatinga). Isotopes in Environmental and Health Studies DOI: 10.1080/10256016.2010.488805. Shelton, H.M., and J.L. Brewbaker. 1994. “Leucaena leucocephala – the most widely used forage tree legume” In: R.C. Gutteridge and H.M. Shelton (Eds.) Forage Tree Legumes in Tropical Agriculture pp. 15-­‐29. Wallingford, UK: CAB International. Shrestha T.R., and J.R.R. Alavalapati. 2004. Valuing environmental benefits of Silvopasture practice: a case study of the Lake Okeechobee watershed in Florida. Ecological Economics 49(3): 349-­‐359. Sierra, J., and P. Nygren. 2006. Transfer of N fixed by a legume tree to the associated grass in a tropical silvopastoral system. Soil Biology and Biochemistry 38(7): 1893-­‐1903. Simons, A.J., and J.L. Stewart. 1994. “Gliricidia sepium – A Multipurpose Forage Tree Legume” In: R.C. Gutteridge and H.M. Shelton (Eds.) Forage Tree Legumes in Tropical Agriculture pp. 30-­‐48. Wallingford, UK: CAB International. Thomas, R.J., and N.M. Asakawa. 1993. Decomposition of leaf litter from tropical forage grasses and legumes. Soil Biology and Biochemistry 25(10): 1351-­‐1361. Trannin, W.S., S. Urquiaga, G. Guerra, J. Ibijbijen, and G. Cadisch. 2000. Interspecies competition and N transfer in a tropical grass-­‐legume mixture. Biology and Fertility of Soils 32: 441-­‐448. 22 Unkovich, M.J., J. Baldock, and M.B. Peoples. 2010. Prospects and problems of simple linear models for estimating symbiotic N2 fixation by crop and pasture legumes. Plant and Soil 329: 75-­‐
89. Urquiaga, S., G. Cadisch, B.J.R. Alves, R.M. Boddey, and K.E. Giller. 1998. Influence of decomposition of roots of tropical forage species on the availability of soil nitrogen. Soil Biology and Biochemistry 30: 2099-­‐2106. Vallis, I., E.F. Henzeli, and T.R. Evans. 1977. Uptake of soil nitrogen by legumes in mixed swards. Australian Journal of Agricultural Research 28: 413-­‐425. Van Kessel, C., P.W. Singleton, and H.J. Hoben. 1985. Enhanced N-­‐transfer from a soybean to maize by vesicular arbuscular mycorrhizal (VAM) fungi. Plant Physiology 79: 562-­‐563. Van Kessel, C., R.E. Farrel, J.P. Roskoski, and K.M. Keane. 1994. Recycling of the naturally-­‐
occurring 15N in an established stand of Leucaena leucocephala. Soil Biology and Biochemistry 26: 757-­‐762. Viera-­‐Vargas, M.S., C.M. Souto, S. Urquiaga, and R.M. Boddey. 1995. Quantification of the contribution of N2 fixation to tropical forage legumes and transfer to associated grass. Soil Biology and Biochemistry 27: 1193-­‐1200. Wilcke, W., and J. Lilienfein. 2004. Element storage in native, agri-­‐, and silvicultural ecosystems of the Brazilian savanna. II. Metals. Plant and Soil 258: 31-­‐41. Xavier, D.F., F.J. da Silva Lédo, D.S. de Campos Paciullo, M de Fátima Ávila Pires, and R.M. Boddey. 2011. Dinâmica da serapilheira em pastagens braquiária em sistema silviopastoril e monocultura. Pesqisa Agropecuária Brasileira 46(10): 1214-­‐1219. 23 ________________________________________________________________________________________________________________ Chapter 2 Assessment of growth and 15N natural abundance of shrubby legumes grown in five soil-­sand combinations in a pot study 2.1 Introduction Ninety nine percent of the nitrogen (N) in the atmosphere is in the form of N2 – which is non-­‐
reactive and unavailable for plant use. Legumes and their associated diazotrophic bacteria are one of a few natural methods by which N2 is transformed into plant-­‐usable NH3, contributing more that 139 million Mg yr-­‐1 of N to the terrestrial environment (Brady and Weil 2002). Fixation efficiency of N2 in legumes, however, can vary dramatically based on environmental and physiological factors (Graham 2005). These factors can affect both legume plants and diazotrophic bacteria. Soil characteristics including acidity, temperature, salinity or alkalinity and mineral nutrition have specifically been found to change fixation efficiency (Graham 2005). Soil N availability has been found to affect certain species of legumes, with high soil inorganic N causing N2-­‐fixation to be reduced. Allos and Bartholomew (1955) reported this fertilization effect on fixation in seven leguminous plants (Soya max, Arachis hypogaea, Medicago sativa, Lespedeza stipulacea, Trifolium repens and Lotus corniculatus), suggesting that nitrogen fertilization decreases fixation but does not completely inhibit it. Earlier, Norman and Krampitz (1943) reported that N applied in large quantities reduced fixation to 30-­‐40% of total N utilized whereas N applied at 10-­‐15% of the normal rate resulted in fixation making up 80-­‐90% of the total N used. A more recent report by Salvagiotti et al. (2008), which reviewed approximately 50 studies of soybean production under different N fertilization regimes, found a negative exponential relationship between fertilizer rate and N2 fixation. A maximum nitrogen fixation of 337 kg ha-­‐1 was found when no N fertilizer was applied and a minimum of 17 kg N ha-­‐1 when 300 kg ha-­‐1 of N fertilizer was applied (Salvagiotti et al. 2008). Eaglesham et al. (1982a) showed that N fertilization of cowpeas (Vigna unguiculata) reduced nodulation and lowered N2-­‐fixation in a mineral-­‐N poor Alfisol, though N-­‐benefits were accrued from the no N fertilizer and 25 kg/ha N applications, but not from the 100 kg/ha N application (Eaglesham et al. 1982b). A similar decrease in N fixation was seen when N fertilizer was applied in a clover (Trifolium repens L.)/ryegrass (Lolium perenne L.) pasture grazed by dairy cows (Ledgard et al. 1999). 25 Shrubby legumes also have wide variations in N2 fixation among species. Jalonen et al. (2009) showed that between 30 and 90% of legume tree N was derived from fixation. While establishing shrubby legumes in pasture systems is difficult, these legumes have a number of direct and indirect uses that are highly advantageous to farmers (Shelton et al. 1991). Fodder and wood production, erosion and salinization control, shade for animals, and an increase in soil organic matter are some of the advantages of silvopastoral systems (Kadiata et al. 1996; Shelton et al. 1991). Less information, however, exists regarding the ‘fertilization effect’ for shrubby legumes. Soil type has been shown to affect N2 fixation in shrubby legumes. Kadiata et al. (1996) grew 10 species of shrubby legumes in two differing soil types (an Alfisol and an Ultisol) for a six-­‐month period and found that the N2 fixing potential and growth of the species was greater in the Alfisol than in the Ultisol. Growth of L. leucocephala was severely limited in the acidic Ultisol, possibly due to a lack of physiological tolerance and decreased nodulation (Kadiata et al. 1996). Specifically, a decrease of 22% in height and 15% in basal stem girth was reported in the acid Ultisol compared to the Alfisol (Kadiata et al. 1996). They also measured N2 fixation using an isotope dilution technique and found significant differences both between species and between soil types (Kadiata et al. 1996). Understanding legume N2 fixing efficiency under differing soil conditions is an important part of pasture management of mixed grass-­‐legume pastures. N fertilization has been shown to reduce N2-­‐fixation in legumes, however, it is not known how differing soil conditions affect N fixation. Therefore, this study focused on the N2 fixation efficiency of shrubby legumes in soil diluted with differing amounts of sand. Height, weight of dry matter, total N and natural abundance of 15N were measured for three shrubby legumes in soils varying in plant available inorganic N supply in a greenhouse pot experiment. The overall objective of this study was to determine productivity and N2 fixation of the legumes under varying soil inorganic N supply. 2.2 Materials and Methods This research was conducted in an open-­‐air greenhouse at the Department of Zootecnia at the Universidade Federal Rural de Pernambuco (UFRPE) in Recife, Pernambuco, Brazil between October 2010 and August 2011. The experiment was set out as a completely randomized design 26 (RCD) with five soil treatments, nine species treatments and four replicates per treatment x species. 2.2.1 Establishment Soil from a 15 year old low-­‐input Brachiaria decumbens pasture from the Agricultural Research Station of Itambé was collected, air-­‐dried and sieved to <2mm. The soil was designated as an Acrisol (Argisolo Vermelho-­‐Amarelo) and had 27.5% clay, 58.9% sand and 13.9% silt and a bulk density of 1.18 g/cm3 in the 0-­‐20 cm layer (Dubeux, unpublished results, February 2010; FAO 1998; Jacomine 1972). The soil was mixed with washed and sieved sand to create five soil-­‐sand mixtures: 100% soil, 50% soil, 25% soil, 12.5% soil and 0% soil. Five kilograms of a given soil mixture was added to a pot of approximately 30 cm diameter that was fashioned on the bottom with drainage tubes and a layer of crushed rocks. Nine species were planted into the pots on September 28: 8 legumes (A. pintoi, B. cheilantha, C. mucunoides, C. ternatea, G. sepium, L. leucocephala, M. caesalpiniifolia and S. capitata) and B. decumbens. All legume seeds were scarified with sand-­‐paper prior to planting. Seeds that did not germinate (specifically L. leucocephala, M. caesalpiniifolia, A. pintoi and C. ternatea) were replanted each week until germination was established. Three germinated seedlings were randomly chosen in each pot and any other plants were removed. This study will only report on the tree legumes that germinated well; specifically B. cheilantha (mororó), G. sepium (gliricidia) and L. leucocephala (leucena). M. caesalpiniifolia (sabiá), also a shrubby species, did not germinate well and was removed from the data set. Species were inoculated with live rhizobia bacteria at the 2-­‐leaflet stage as they germinated. One millilitre of inoculant was applied to the soil at the base of the germinated seedling using a pipette. The inoculants were grown in the lab of Dr. Mario Lira at UFRPE and were kept refrigerated until needed. Table 2.1 details the species-­‐specific strains of bacteria used in each inoculant. No known inoculate for B. cheilantha was available and therefore it was not inoculated. 27 Table 2.1. Species of plant and common name shown with corresponding strain of bacteria (Lira, personal communication, October 2012). Species A. pintoi B. cheilantha C. mucinoides C. ternatea G. sepium L. leucocephala M. caesilpiniifolia S. capitata Common Name Amendoim forrageiro Mororó Calopogonio Cunha Gliricidia Leucena Sabiá Stylosanthes Inoculant Strain SEMIA 6440 -­‐ SEMIA 6152 SEMIA 6411 SEMIA 6168 SEMIA 6070 SEMIA 6382 BR 502 2.2.2 Maintenance The greenhouse was open air and stayed at ambient temperature and humidity. The plants were watered, as needed, 2x per week with 400 ml of water, and then increased to 3x per week with 600 ml of water by January 2011. The pots were also fertilized with an N-­‐free Hoaglands solution (Table 2.2). The dosage was increased from 100 ml of solution every second week to 100 ml of solution every week after 10 week’s growth. Table 2.2. Preparation of N-­free Hoagland’s solution (adapted from Hoagland and Arnon 1950). Add to 1 L of water: Chemical 0.5 M K2SO4 1.0 M MgSO4 1.0 M KH2PO4 1.0 M CaCl2 Fe-­‐EDTA Micronutrients Ingredient dissolve 26.1g of EDTA in: 286 mL of NaOH 24.9 g FeSO4 7H2O dissolve in 1 L of water: 2.86 g H3BO3 1.81 g MnCl2 4H2O 0.22 g ZnSO4 7H2O 0.08 g CuSO4 5H2O 0.02 g H2MoO4 H2O Amount 5 mL 2 mL 1 mL 3 mL 1 mL 1 mL 28 2.2.3 Sampling Samples were taken on February 22, 2011, approximately 20 weeks after planting and again on July 27, 2011, approximately 42 weeks after planting. All leaves and petioles were removed from the shrubby legumes, but stems were left to continue growth. The plant material harvested from each pot, within each treatment was composited and weighed wet and after oven-­‐drying at 65°C for 48 h. Before removing the plant material, a height measurement was taken of each plant. Length and width measurements were also taken from three leaves of each plant. Plant material was weighed and dried (65° for 48h), then ground with a Wiley Mill to <0.5 mm. After importation to Guelph, Canada, the plant material was further ground to <250 µm using a ball mill and encapsulated for 15N natural abundance analysis. The samples were analyzed for 15N natural abundance and total N at the Stable Isotope Facility at the University of Saskatchewan, Saskatoon, Canada. Soil samples were also taken from center of the pots at the end of the experiment to a depth of 10 cm and a diameter of approximately 10 cm using a small trowel. The soil samples were air-­‐dried and analyzed for fertility [pH, phosphorus (P), sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), aluminum (Al), organic carbon (SOC) and organic matter (OM)] at the Universidade Federal Rural de Pernambuco soil chemistry lab in Recife, Brazil. Then, after importation to Canada, the soils were further ground, analyzed and quantified for 15N natural abundance according to Högberg (1997) and Sierra and Nygren (2006). 2.2.5 Statistical analysis The Statistical Analysis Software (v. 9.2, SAS Institute Inc., Cary, N.C.) program was used to perform variance analyses of the data. An analysis of the residuals indicated that no transformations were necessary to best meet the assumptions of the analysis for height data, but a log transformation was used for the leaf weight data. No transformations were necessary for the total N and 15N natural abundance data. 29 A variance analysis requires a linear additive model with errors that are homogenous, random, independent, normally distributed and equal to a mean of zero (Bowley 2008). A Shapiro-­‐Wilk test was used to determine normalcy followed by a Student’s t-­‐test to determine significance using a Type I error rate of 0.05. Least Significant Differences were used to compare values across soil treatments, harvest dates, species and the interactions. 2.3 Results and Discussion 2.3.1 Soil fertility Soil fertility parameters (Table 2.3) were significantly different within each variable (pH, P, Na, K+, Ca2++Mg2+, Ca2+, Al3+, H.Al. and O.C.) across the soil treatments. For example, soil pH increased from 5.3 in the 100% soil to 6.6 for the 0 soil treatment. The level of acidity in this field soil is typical of that associated with Ultisols (Loss et al. 2009). The pH remained relatively stable throughout the soil treatments but was significantly higher, at 6.6, in the 0 soil treatment. Although the concentration of Aluminum (both Al+3 and H.Al.) in the soil was relatively high in the 100 soil treatment, this would not likely cause toxicity to the plants given a soil pH above 5 (Brady and Weil 2002). The plant available P, K, Ca and Mg of the soil decreased with increasing sand addition, with the 0 soil treatment having the lowest levels in all nutrients. Soil organic C also decreased with increasing sand content. The existence of S.O.C. in the 0 soil treatment may be due to ungerminated seeds beginning to decompose by the end of the experiment. 30 Table 2.3. Soil fertility data analyzed at UFRPE. Averages shown for each soil treatment with Type III variance analysis within rows. Characteristic Soil Treatments (as % soil) 100 50 25 12.5 0 F value P>F 5.30 5.27 5.90 5.75 6.62 5.98* 0.0101 10.33 6.67 5.67 5.60 0.59 5.01* 0.0177 0.47 0.39 0.21 0.14 0.09 18.63* 0.0001 0.56 0.40 0.22 0.11 0.01 38.45* <0.0001 6.73 3.93 2.22 1.73 0.98 209.29* <0.0001 4.32 2.13 0.97 0.82 0.80 59.56* <0.0001 0.10 0 0 0 0 4.00* 0.0343 H + Al (cmolc/dm ) 6.21 4.27 2.87 2.66 2.28 90.38* <0.0001 S.O.C. (g/kg) 26.17 7.55 3.38 2.97 0.64 115.52* <0.0001 pH 3
P (mg/dm ) 3
Na (cmolc/dm ) +
3
K (cmolc/dm ) +2
+2
3
Ca + Mg (cmolc/dm ) +2
3
+3
3
Ca (cmolc/dm ) Al (cmolc/dm ) 3
*indicates values significant at P<0.05 2.3.2 Plant production: height and biomass Species, soil treatments and harvest differences were significantly different and the interactions of soil treatment by species and species by harvest were also significantly different when considering plant height. Soil by harvest interaction and the three-­‐way interaction of species by soil by harvest were not significant. Table 2.4 shows species by soil interactions using a Least Square Difference method. The values show that height of mororó and leucena were more affected by the change in soil characteristics then was gliricidia. In particular, leucena represented the greatest difference between the 0 and 100 soil treatments, with an average 50.8 cm difference. Mororó showed a similar trend with 12.5 and 0 treatments being more similar and lower in value than the 100, 50 and 25 treatments, with a difference between the 0 and 100 treatments of 21.3 cm. Within the treatments for gliricidia, less of a difference was seen, with an 8.2 cm change between the 0 and 100 treatments. 31 Table 2.4. Mean plant height (cm) of three shrubby legumes with calculated LSD (P<0.05) for the interaction of species*soil treatment. Species 0 12.5 Soil Treatment (as % soil) 25 Plant height (cm) 50 100 Mororó 19.0 (5.7)Da 25.0 (5.4)Cb 34.7( 5.4)ABb 39.6 (5.4)Ab 40.3 (5.4)Ab Gliricidia 30.2 (5.4)ABa 34.3 (5.4)ABab 37.5 (5.4)Ab 38.1 (5.4)Ab 38.4 (5.4)Ab Leucena 22.5 (5.7)Da 38.2 (5.4)CDb 53.4 (5.4)ABCa 57.4 (5.4)Aba 73.3 (5.4)Aa Standard errors are given in parentheses (n=24). Values followed by the same upper case letters, comparing differences between soil treatments for each species, are not significantly different at P<0.05. Values followed by the same lower case letters, comparing differences between species for each soil treatments, are not significantly different at P<0.05. No change was seen from harvest 1 to 2 for mororó or gliricidia (Table 2.5). Leucena plant heights were significantly different between the two harvest times. This may indicate that the leucena responded better to the defoliation then did either mororó or gliricidia. Table 2.5. Mean plant height (cm) of three shrubby legumes with calculated LSD (P<0.05) for the interaction of species*cycle. Species Mororo Gliricidia Leucena Plant height (cm) 1 32.3 (2.5)Ba 37.1 (2.5)ABa 40.7 (2.5)Ab 2 31.2 (3.8)Ba 34.3 (3.5)Ba 57.2 (3.9)Aa Standard errors are given in parentheses (n=26). Values followed by the same upper case letters, comparing differences between species for each cycle, are not significantly different at P<0.05. Values followed by the same lower case letters, comparing differences between cycles for each species, are not significantly different at P<0.05. Cycle When species was analyzed, a significant difference was seen between mororó and the other species. Mororó was an average of 8.50 cm shorter than gliricidia and 7.95 cm shorter than leucena. This would be expected due to growth habit differences, and the greater difficulty in the germination of the mororó, which had to be planted a second time whereas the gliricidia and leucena germinated well (inoculated 28/09/10 and 13/10/10, respectively). Furthermore, mororó was not inoculated because it does not have a known diazotrophic association. Data for plant biomass as dry weight (in grams) for all leaves and petioles per pot showed no significant differences among soil treatments, plant species, harvest dates or overall soil by species interactions (data not shown). Plant height and dry matter weight showed very different results for the shrubby legumes studied. While significant differences were seen between the treatments for height for all species, no significant differences were seen for weight. Height did 32 not change between harvest periods for two of the three legumes, which may indicate lack of growth of the plants, and relate to an observed decease in biomass production. 2.3.3 Total N and δ15N natural abundance The total N of the soil decreased as the amount of soil in the soil-­‐sand mixtures decreased (Table 2.6). The total N of the 100 % soil treatment was 0.1647% ± 0.0084 and in the sand (0 % soil) treatment was 0.0039% ± 0.0007. The δ15N of the soil was relatively stable throughout the soil treatments and across the legume species. The δ15N for the 100 treatment was 6.31‰ ± 0.061 and for the 0 treatment was 6.87‰ ± 0.358. The total N and δ15N value of the soil in the 100 soil treatment growing the Brachiaria decumbens (signal grass) were similar to the legume treatments at 0.1740% and 6.04‰. Table 2.6. Total N and δ15N of soil across four legumes and five soil treatments. Species Mororó Gliricidia Leucena Sabiá Variable Total N (%) 15
δ N (‰) Total N (%) 15
δ N (‰) Total N (%) 15
δ N (‰) Total N (%) 15
δ N (‰) 100 0.1756 6.24 0.1653 6.36 0.1554 6.28 0.1627 6.37 Soil Treatment (as % soil) 50 25 0.0866 0.0375 6.03 5.27 0.0861 0.0495 5.70 5.42 0.0886 0.0378 5.90 5.39 0.0864 0.0341 5.72 5.81 12.5 0.0242 5.43 0.0137 5.52 0.0250 5.33 0.0211 5.68 0 0.0044 7.13 0.0039 10.65 0.0029 6.62 0.0042 9.88 The δ15N of the plant material from the first harvest (Table 2.7) increased significantly with soil treatment for gliricidia and leucena but not for mororó, the species that was not inoculated with rhizobia. Mororó δ15N did not differ significantly for any treatment and had a mean of 8.85‰ ± 0.43, which was in the range of δ15N (9.92‰ ± 0.72 to 6.30‰ ± 1.56) found by Santiago de Freitas et al. (2010) in undisturbed sites in the Pernambuco and Paraíba states of Brazil. The total N for mororó did change between the 0, 25 and 100 soil treatments. Signal grass was also measured for the 100 soil treatment and found to have a δ15N of 9.21‰ ± 0.75. This was similar to a study by Boddey et al. (2001) which found Brachiaria mutica weeds had δ15N of 9.31‰ ± 0.21 in sugarcane fields in Timbaúba, Pernambuco. Gliricidia and leucena δ15N values were significantly lower in all the soil dilutions (1.02‰ ± 0.89 to 2.66‰ ± 0.86 and 2.44‰ ± 0 to 33 7.86‰ ± 1.38 respectively) compared to the 100 soil treatment (4.60‰ ± 1.38 and 9.24‰ ± 1.26 respectively). This indicates that more fixation was occurring in the sand-­‐diluted soil treatments due to a paucity of soil mineral N and the lack of significant difference in the total N values of the plants. Sabiá values were not statistically analyzed due to germination problems which reduced the number of replications. Table 2.7. LSD of δ15N and total N of plant material across four legumes and five soil treatments. Letters represent statistical difference across rows. Soil Treatment 0 12.5 25 50 100 15
δ N (‰) 8.52 (0.36)A Mororó 8.75 (0.36)A 8.45 (0.36)A 9.03 (0.36)A 9.52 (0.36)A Total N (%) 2.133 (0.075)B 2.008 (0.075)BC 1.759 (0.075)C 1.836 (0.075)BC 2.541 (0.075)A 15
δ N (‰) 1.03 (0.42)BC Gliricidia 0.84 (0.42)C 1.06 (0.42)BC 2.66 (0.42)B 4.60 (0.42)A Total N (%) 3.794 (0.149)A 3.753 (0.149)A 3.380 (0.149)A 3.495 (0.149)A 3.607 (0.149)A 15
δ N (‰) 2.24 (1.69)B Leucena 3.74 (0.99)B 6.36 (0.87)AB 7.86 (0.87)AB 9.24 (0.87)A Total N (%) 3.117 (0.398)A 3.645 (0.281)A 3.254 (0.281)A 3.521 (0.281)A 3.299 (0.281)A 15
δ
N (
‰) Sabiá 4.27 6.44 Total N (%) 2.053 2.239 Standard errors are given in parentheses (n=12). Values followed by the same upper case letters, comparing differences between soil treatments within rows, are not significantly different at P<0.05. Leucena and gliricidia were more enriched in δ15N then other studies have shown. Unpublished data from Australia and Indonesia (Boddey et al. 2000; Unkovich et al. 2008) reported mean values of -­‐1.28‰ for gliricidia and -­‐0.34‰ for leucena grown in a sand substrate without soil N. Similarly, mean δ15N for sabiá was found to be -­‐1.24 ± 0.22‰ for aerial plant parts in an undisturbed Caatinga ecosystem (Bueno dos Reis Jr. et al. 2010). Unkovich et al. (2008) suggested that for woody legumes, pot experiments should be at least one year in length to be comparable to field studies. Shoot δ15N is enriched in seedlings and will decrease with time as seed N reserves are diluted by N fixed from the atmosphere. Boddey et al. (2000) suggested that the δ15N of the seed should be measured and subtracted from the ‘B’ value before %Ndfa is calculated, but that this can be forgotten if seed N is small compared to total plant N. Seed N was not measured in this study and could, therefore, have been the cause of the enrichment of the values compared to past studies. Usually non-­‐fixing species have a δ15N similar to that of the soil. In this study, however, the δ15N of signal grass grown in the 100 soil treatment and the mororó in all treatments was higher then 34 the soil δ15N. It has been reported that in arid environments non-­‐fixing plant pools are often higher then the corresponding soil δ15N (Fry 1991; Shearer et al. 1983; Turner et al. 1987). Shearer et al. (1983) found that the non-­‐fixing woody species Atriplex polycarpa (saltbrush) had a higher δ15N then soil in its foliage, but a lower δ15N in the woody material. Fry (1991) reported a similar finding, suggesting that samples from arid grasslands and deserts had the highest δ15N values, with non-­‐fixing species at times having higher δ15N then soil δ15N. Even though the experiment was watered regularly, mororó is a species native to the semi-­‐arid Caatinga ecosystem and may exhibit a similar δ15N pattern as other plants from an arid environment. This may be due to the presence of non-­‐symbiotic N fixation occurring in the system. Also, only leaf and petioles material was collected for mororó samples, which may explain their high δ15N values. 2.3.4 Percent Nitrogen derived from fixation (%Ndfa) Percent nitrogen fixed by the legumes was calculated using Equation 2.2. One reference value and three ‘B’ values, as seen in Table 2.8 and 2.9, were used to compare %Ndfa results. The reference value used was 9.21‰, which was the average δ15N of the signal grass grown in the 100 soil treatment. This value was very similar to the values of mororó in the soil treatments (average 8.94‰). A ‘B’ value is a discrimination factor measured as the δ15N in the legume when it is grown with no available soil N (Högberg 1997). This value is theoretically estimated when the plant is grown in sand and provided an N-­‐free media, presumably taking up atmospheric N as its sole N source. The ‘B’ value represents the maximum amount of fixation possible by a specific legume and should be similar to the δ15N of the atmosphere. Zero was used as the first ‘B’ value comparison. Due to fractionation, however, the value of ‘B’ is usually slightly enriched or depleted compared to the atmosphere. Mean ‘B’ values compiled by Boddey et al. (2000) and Unkovich et al. (2008) were -­‐1.28‰ for gliricidia and -­‐0.34‰ for leucena. These were used as the second ‘B’ value in Table 2.8 and 2.9. In this experiment the δ15N values of the legumes grown in the 0 soil treatment were 2.24‰ for the leucena and 1.03‰ for the gliricidia. These results were enriched in 15N compared to values in the literature, and were used as the third ‘B’ value. 35 Table 2.8. Comparisons of percent nitrogen derived from the atmosphere (%Ndfa) of the legume Leucena using three ‘B’ values. Soil treatment Material analyzed 15
δ N Reference Estimate of %Ndfa ‘B’=0‰ ‘B’= -­‐0.34‰ (Unkovich et ‘B’= 2.24‰ (from (Unkovich et al. 2008) experiment) al. 2008) (‰) (‰) % % % 100 9.24 9.21 0.33 0* 0* 50 7.86 9.21 14.66 14.14 19.37 25 9.16 9.21 0.54 0.52 0.72 12.5 3.74 9.21 59.39 57.28 78.48 *designated 0% although using Equation 2.2 would generate a physiologically impossible estimate of %Ndfa < 0% The %Ndfa for leucena ranged from 0 in the 100 soil treatment to 78.86% in the 12.5 soil treatment with the ‘B’ value of 0. Using these criteria, nitrogen fixation was contributing to plant N in the 50 and 12.5 soil treatments with little to no contribution in the 100 and 25 soil treatments. Sanginga et al. (1990) found a range of 37 to 74% Ndfa for leucena plants grown in a 1:1 mixture of soil and sand and harvested 12 weeks after planting. Nitrogen derived from fixation was present in all soil treatments with the 100 soil treatment having the least and the 12.5 soil treatment having the most for gliricidia (Table 2.9). The %Ndfa for gliricidia ranged from 43.95% in the 100 soil treatment with ‘B’ value of -­‐1.28 to 100% in the 12.5 soil treatment using the 1.03‰ ‘B’ value. Sanginga et al. (1991) found 26 to 68% of N was derived from the atmosphere in gliricidia plants grown in a 1:1 ratio of sand to soil in a greenhouse for 12 weeks. Table 2.9. Comparisons of percent nitrogen derived from the atmosphere (%Ndfa) of the legume Gliricidia using three ‘B’ values. Soil treatment Material analyzed 15
δ N Reference Estimate of %Ndfa ‘B’=0‰ ‘B’= -­‐1.28‰ (Unkovich et ‘B’= 1.03‰ (from (Unkovich et al. 2008) experiment) al. 2008) (‰) (‰) % % % 100 4.60 9.21 50.05 43.95 56.36 50 2.66 9.21 71.12 62.44 80.07 25 1.06 9.21 88.49 77.69 99.63 12.5 0.84 9.21 90.88 79.79 100* *designated 100% although using Equation 2.2 would generate a physiologically impossible estimate of %Ndfa > 100% A higher reference value will report higher levels of nitrogen fixation. The reference value of 9.21‰ was lower then the mororó values for the 100 soil treatment and this resulted in lower 36 %Ndfa for this reference in this treatment (data not shown). The effect of ‘B’ value on the %Ndfa was small at high δ15N but became more significant as the δ15N decreased. At a δ15N of 9.24, the range of %Ndfa was 0.33% to 0% whereas at a δ15N of 3.74 the range was 59.39% to 78.48%, using the 9.21‰ reference. Unkovich et al. (2008) suggest that at %Ndfa of <50%, the choice of ‘B’ value will have little effect on the value. 2.4 Conclusions This study used a greenhouse experiment designed with five soil-­‐sand mixtures to explore growth and fixation efficiency at low levels of plant available soil N. The leguminous seedlings of gliricidia and leucena showed significant N2 fixation 20 weeks after planting. As the proportion of soil in the soil treatment decreased, %Ndfa increased in gliricidia and leucena. The total N did not change significantly across the treatments. Growth of the plants decreased significantly between the first and second harvest periods, suggesting a negative effect of defoliation. The growth of the plants was negatively affected by lower soil content suggesting that while the plants increased their proportions of N derived from N2 fixation, other factors such as water retention or pH may have limited their growth. 2.5 References: Allos, H. F., and W.V. Bartholomew. 1954. Effect of available nitrogen on symbiotic fixation. Soil Science Society Proceedings (1955). Div. III of the Soil Science Society of America, St. Paul, Minn. Nov. 9, 1954. Boddey, R.M., J.C. Polidoro, A.S. Resende, B.J.R. Alves, and S. Urquiaga. 2001. Use of the 15N natural abundance technique for the quantification of the contribution of N2 fixation to sugar cane and other grasses. Australian Journal of Plant Physiology 28: 889-­‐895. Boddey, R.M., M.B. Peoples, B. Palmer, and P.J. Dart. 2000. Use of the 15N natural abundance technique to quantify biological nitrogen fixation by woody perennials. Nutrient Cycling in Agroecosystems 57: 235-­‐270. Bowley, S.R. 2008. A Hitchhiker’s Guide to Statistics in Plant Biology. 2nd Edition. Any Old Subject Books, Guelph, ON. 37 Brady N.C., and R.R. Weil. 2002. The Nature and Properties of Soils: 13th Edition. Pearson Education, Inc., Upper Saddle River, New Jersey. Bueno dos Reis Jr., F., M.F. Simon, E. Gross, R.M. Boddey, G.N. Elliot, N.E. Neto, M. de Fatima Loureiro, L.P. de Queiroz, M.R. Scotti, W.M. Chen, A. Norén, M.C. Rubio, S.M. de Faria, C. Bontemps, S.R. Goi, J.P.W. Young, J.I. Sprent, and E.K. James. 2010. Nodulation and nitrogen fixation by Mimosa spp. in the Cerrado and Caatinga biomes of Brazil. New Phytologist 186: 934-­‐946. Eaglesham, A.R.J., A. Ayanaba, V. Ranga Rao, and D. L. Eskew. 1982a. Mineral N effects on cowpea and soybean crops in a Nigerian soil I. Development, nodulation, acetylene reduction and grain yield. Plant and Soil 68: 171-­‐181. Eaglesham, A.R.J., A. Ayanaba, V. Ranga Rao, and D. L. Eskew. 1982b. Mineral N effects on cowpea and soybean crops in a Nigerian soil II. Amount of N fixed and accrual to the soil. Plant and Soil 68: 183-­‐192. Food and Agriculture Organization of the United Nations. 1998. World reference base for soil resources. ISBN 92-­‐5-­‐104141-­‐5. Accessed online at http://www.fao.org/docrep/W8594E/w859 4e00.htm#. Fry, B. 1991. Stable isotope diagrams of freshwater food webs. Ecology 72(6): 2293-­‐2297. Graham, P.H. 2005. “Biological Dinitrogen Fixation: Symbiotic” In: D.M. Sylvia, P.G. Hartel, J.J. Fuhrmann and D.A. Zuberer Principles and Application of Soil Microbiology: Second Edition pp. 373-­‐404. Upper Saddle River, NJ: Pearson Education Inc. Hoagland, D.R., and D.I. Arnon. 1950. The water-­‐cultured method for growing plants without soil. California Agricultural Experiment Station Circular 347: 1-­‐32. Högberg, P. 1997. Tansley review no. 95. The New Phytologist, 137(2): 179-­‐203. Jacomine, P.K.T., A.C. Cavalcanti, N. Burgos, S.C.P. Pessoa, and C.O. Silveira. 1973. Levantamento exploratório-­‐reconhecimento de solos do estado de Pernambuco. Recife, Minisério da Agricultura/ Superintendência do Desenvolvimento do Nordeste v.1 359p. (Boletim Técnico 26; Série Pedológica, 14). Jacomine, P.K.T. 1972. Levantamento exploratório – reconhecimento de solos do Estado de Pernambuco, descrição de perfis de solos e analyses. Recife: MA – DNPEA/SUDENE/DRN. v. 1 (MA-­‐DNPEA. Boletim Técnico, 26). Jalonen, R., P. Nygren, and J. Sierra. 2009. Transfer of nitrogen from a tropical legume tree to an associated fodder grass via root exudation and common mycelial networks. Plant, Cell and Environment 32: 1366-­‐1376. Kadiata, B.D., K. Mulongoy, N.O. Isirimah, and M.A. Amakiri. 1996. Screening woody and shrub legumes for growth, nodulation and nitrogen-­‐fixation potential in two contrasting soils. Agroforestry Systems 33: 137-­‐152. 38 Ledgard, S.F., J.W. Penno, and M.S. Sprosen. 1999. Nitrogen inputs and losses from clover/grass pastures grazed by dairy cows, as affected by nitrogen fertilizer application. Journal of Agricultural Science 132: 215-­‐225. Loss, A., M.G. Pereira, N. Shultz, L.H.C. dos Anjos, and E.M.R. da Silva. 2009. Atributos quimicos e físicos de um Argissolo Vermelho-­‐Amarelo em sistema integrado de produção agroecológica. Pesquisa Agropecuária Brasiliera 44(1): 68-­‐75. Norman, A.G., and L.O. Krampitz. 1945. The nitrogen nutrition of soybeans: II. Effect of available soil nitrogen on growth and nitrogen fixation. Soil Science Society of America Proceedings 10: 191-­‐196 (1946). Salvagiotti, F., K.G. Cassman, J.E. Specht, D.T. Walters, A. Weiss, and A. Dobermann. 2008. Nitrogen uptake, fixation and response to fertilizer N in soybeans: A review. Field Crops Research 108: 1-­‐
13. Sanginga, N., G.D. Bowen, and SK.A. Danso. 1990. Assessment of genetic variability for N2 fixation between and within provenances of Leucaena leucocephala and Acacia albida estimated by 15N labeling techniques. Plant and Soil 127: 169-­‐178. Sanginga, N., K. Manrique, and G. Hardarson. 1991. Variation in nodulation and N2 fixation by the Gliricidia sepium/Rhizobium spp. symbiosis in a calcareous soil. Biology and Fertility of Soils 11: 273-­‐278. Santiago de Freitas, A.D., E.V. de Sá Barretto Sampaio, R.S.C. Menezes, and H. Tiessen. 2010. 15N natural abundance of non-­‐fixing woody species in the Brazilian dry forest (caatinga). Isotopes in Environmental and Health Studies DOI: 10.1080/10256016.2010.488805. Shearer, G., D.H. Kohl, R.A. Virginia, B.A. Bryan, J.L. Skeeter, E.T. Nilson, M.R. Sharifi, and P.W. Rundel. 1983. Estimates of N2-­‐fixation from variation in the natural abundance of 15N in Sonoran Desert ecosystems. Oecologia 56: 365-­‐373. Shelton, H.M., J.B. Lowry, R.C. Gutteridge, R.A. Bray, and J.H. Wildin. 1991. Sustaining productive pasture in the tropics 7. Tree and shrub legumes in improved pastures. Tropical Grasslands 25: 119-­‐128. Sierra, J., and Nygren, P. 2006. Transfer of N fixed by a legume tree to the associated grass in a tropical silvopastoral system. Soil Biology and Biochemistry 38(7): 1893-­‐1903. Turner, G.L., R.R. Gault, L. Morthorpe, D.L. Chase, and F.J. Bergersen. 1987. Differences in the natural abundance of 15N in the extractable mineral nitrogen of cropped and fallowed surface soils. Australian Journal of Agricultural Research 38:15-­‐25. Unkovich, M., D. Herridge, M. Peoples, G. Cadisch, B. Boddey, K. Giller, B. Alves, and P. Chalk. 2008. Measuring plant-­‐associated nitrogen fixation in agricultural systems. ACIAR Monograph No. 136, 258 pp. 39 Yoneyama, T., T. Muraoka, T. Murakami, and N. Boonkerd. 1993. Natural abundance of 15N in tropical plants with emphasis on tree legumes. Plant and Soil 153: 295-­‐304. 40 ________________________________________________________________________________________________________________ Chapter 3 Herbage mass production and botanical composition of a B. decumbens silvopasture with four shrubby legumes 3.1 Introduction There is renewed interest in silvopastoral systems in the tropics due to pressure to preserve native ecosystems and create sustainable agricultural production systems while maintaining current levels of agricultural productivity (Andrade et al. 2010). These systems introduce trees or shrubs into conventional pastures and often involve more complex management than monocultures. The trees perform multiple functions in the system, producing secondary marketable products in wood, creating shade and producing forage for animals, and increase soil organic matter pools. In addition, if the trees are leguminous, the high quality litter produced can maintain the fertility of the soil. Since degradation of tropical pastures is an ongoing problem, affecting more than 50 million hectares in Brazil alone, understanding the role of these leguminous species is particularly important (Boddey et al. 2004; Hohnwald et al. 2006). 3.1.1 Brachiaria grass Fonseca et al. (2006) estimated that Brazil has over 100 million ha of cultivated grassland, of which 85% is occupied by a single genus of graminoid: Brachiaria. Brachiaria grasses were introduced from Africa via Australia in the 1970s (Boddey et al. 2004; Louw-­‐Gaume et al. 2010). They are C4 grasses that grow well in nutrient poor sites in the tropics and can tolerate 5 months of dry season and short periods of flooding (Cook et al. 2005). Loch (1977) estimated that Brachiaria could withstand up to 7 months of dry season and as little as 1300 mm yr-­‐1 of rainfall. Brachiaria decumbens (signal grass, braquiária) is the most common Brachiaria grass found in Brazil, making up 55% of the Brachiaria planted (Fonseca et al. 2006). It is easily established by broadcast planting, spreads quickly to cover soil and is well adapted to heavy defoliation (Cook et al. 2005). It has a moderately high palatability for animals and a good nutritive value, with between 50-­‐80% digestibility (Cook et al. 2005). It responds well to N and P fertilizer with dry matter yields ranging between 10 to 30 ton ha-­‐1 year-­‐1 under fertilization. This can correspond to an animal production of 340 kg ha-­‐1 yr-­‐1 live weight gain in Brazil (Cook et al. 2005). It is relatively free from diseases and pests, but is susceptible to spittlebugs of the genus Aeneolamia, Deois and Zulia (Cook et al. 2005). Despite the advantages of B. decumbens, in Brazil more than 25 million ha planted with this grass is degraded pasture (de Oliveira et al. 2004). 42 3.1.1.1 Grazing effects Cattle grazing results in defoliation and trampling of pasture plants. Choosing plants that are morphologically adapted to these pressures is important in pasture management. In general, grasses of African origin are seen as very tolerant to grazing due to the historic existence of large herbivores in Africa (Klink 1994). Grazing-­‐tolerant grasses are often stoloniferous, tillering, with meristems at the base of the plant and a prostrate growth habit (Klink 1994). These adaptations allow for frequent defoliation without killing the plant. However, plant die-­‐off can still occur if grazing pressure is too great. B. decumbens is considered a grass that can withstand high grazing pressure (Harding 1972; Rika et al. 1991). It has been shown to re-­‐grow rapidly and persists well under frequent defoliation (Fisher and Kerridge 1996). In a study of beef cattle grazing by Chen et al. (1983), B. decumbens persisted longer under heavy grazing then the other grass species (Panicum maximum and Digitaria milanjiana), which were invaded by weeds. The B. decumbens maintained a high ground cover until it could not recover under prolonged, heavy grazing of 10 head ha-­‐1. This tolerance is due to its ability to regenerate well when defoliated and trampled (Klink 1994; Shelton 2000). 3.1.1.2 Compatibility with legumes Brachiaria species are considered to be highly aggressive, and are often used as a soil cover for plantation crops such as rubber, coconut and oil palm (Loch 1977). Loch (1977) reported that it was difficult to find legumes that were compatible with Brachiaria due to its aggressiveness. Even weeds are not usually a problem with Brachiaria unless the grass is mismanaged by overgrazing (Loch 1977). Since B. decumbens can undergo frequent and heavy defoliation, a legume with similar attributes would be needed for long-­‐term persistence; however, most legumes do not persist well under these circumstances. Success has been shown with some species of herbaceous legumes, including Arachis pintoi, Pueraria phaseoloides, and Stylosanthes capitata (Fisher and Kerridge 1996). Lascano and Estrada (1989) found that a B. decumbens-­P. phaseoloides pastures persisted for more than 10 years on a clay loam soil. Fisher and Kerridge (1996) reported that S. capitata had persisted in association with B. decumbens in a sandy soil in 43 Carimagua, Colombia. A. pintoi has also been shown to persist well which may be due to its prostrate growth habit and low growth points (Ayarza et al. 1994). Ayarza et al. (1994) found that while root biomass of A. pintoi decreased when in association with B. decumbens, the total shoot biomass increased significantly, resulting in an increase of the total productivity from 4831 kg ha-­‐1 for the B. decumbens alone and 5844 kg ha-­‐1 for the A. pintoi alone to 7186 kg ha-­‐1 for the mixed pasture. Associations with shrubby legumes rely less on the persistence and aggressiveness of the legumes and more on the water competition and shading tolerance and of the B. decumbens (Paciullo et al. 2011). 3.1.1.3 Tolerance to shading While silvopastoral systems have many advantages over grass-­‐only systems, the presence of trees in a pasture reduces light availability to grass and can have a major effect on productivity. The response of a grass to light varies due to morphogenic properties of the forage species, level of shading and soil fertility (Paciullo et al. 2011). Under moderate shading (<50%) most species show a reduction in root biomass, an increase in leaf area, elongated leaves and reduced tillering rates (Lambers et al. 1998; Paciullo et al. 2011). Height of grass plants usually increases with moderate shade due to the lengthening of stems and leaves which seek sun exposure (Martuscello et al. 2009). In ecosystems with a distinct dry period, moisture levels are higher in shaded areas causing increased litter decomposition and thereby mineralizing N more rapidly then areas with no shade, during the dry season. If the ecosystem is N-­‐poor, this increase in mineralization may result in an increase in grass productivity (Shelton et al. 1991). However, when shading intercepts more then 50% of incident radiation, most species show a reduction in forage production. During the dry season, competition for water by the tree and grass may reduce the moisture under the tree. B. decumbens has been rated as moderately tolerant to shading in a number of publications (Carrilho et al. 2012; Gobbi 2007; Lambers et al. 1998; Paciullo et al. 2011). Carrilho et al. (2012) found that root growth decreased, leaves became longer and thinner, and dry mass of tissues was lower as shade was increased from 0% to 50% in B. decumbens pastures. The height of the plants 44 increased between these two treatments, however tuft density (measured as number/m2) decreased (Gobbi 2007; Carrilho et al. 2012). With over 50% of incident radiation intercepted, the productivity of B. decumbens decreased (Martuscello et al. 2009; Paciullo et al. 2011). Martuscello et al. (2009) showed a marked decrease in productivity between a 50% shade treatment and a 70% shade treatment. Similarly, Paciullo et al. (2011), who compared three Brachiaria species (B. brizantha, B. decumbens, B. ruziziensis), found that tiller density of B. decumbens was not affected at 36% shade but decreased significantly in the 54% shade treatment. The other two species of Brachiaria were affected at both levels. Thermal comfort of cattle is highly dependant on access to shade in tropical climates (Pires et al. 2008). Cattle spend much of their time grazing and laying in shaded areas during the hotter periods of the day. This allows for lowered temperature and increased comfort for the animals but increased plant stress by trampling and defoliation (Pires et al. 2008). 3.1.1.4 Competition for water A major interaction between herbaceous and shrubby plants in silvopastoral systems is competition for water. While trees often have deeper roots then grasses, they also have a higher density of fine roots that compete directly with grass roots in the 0-­‐30 cm depth of soil (Batish et al. ….). The trees often have the competitive advantage for soil water, however this advantage decreases with distance from the tree (Rao et al. 1998). Few studies have rated the performance of pasture grass under legume trees. Because our understanding how these two components interact is paramount to creating sustainable pasturelands, this study undertook to determine changes in dry matter production and botanical composition over time and across transects in grass-­‐legume pastures. The objectives were to: •
Measure dry matter production of grass in transects in 4 legume grass pastures during 4 distinct times in a year •
Use a rank method to measure botanical composition at the beginning and end of a year •
Measure botanical composition and production at 5 distances from legume rows in 4 different legume grass pastures 45 3.3 Materials and Methods 3.3.1 Study site The field research was completed at the Agricultural Research Station of Itambé, an experimental farm managed by the Instituto Agronômico de Pernambuco, which is a state-­‐funded organization of Pernambuco, Brazil. The site was located approximately 10 km east of the town of Itambé near the border between the state of Pernambuco and the state of Paraíba. The study area is located at latitude 7°25’ (S) and longitude 35°06’ (SW) and 190 m above sea level. The ecoregion is considered ‘Mata Seca’, or Dry Forest, as it is located in the transition zone between the warm, wet Tropical Atlantic Rainforest ecological zone and the drier Caatinga zone (CPRH 2003). The climate is wet and cool in the winter, with an average temperature of 23.4°C, and dry and hot in the summer, with an average temperature of 26.6°C (CPRH 2003). Average annual precipitation is 1200 mm (SINDA 2009). Figure 3.1 shows the month-­‐by-­‐month annual temperature variation and precipitation trends taken at a weather station located at the research station. 46 Figure 3.1. Average annual precipitation (bars) and maximum and minimum temperatures (lines) per month 2002-­2012 for the Agricultural Research Station of Itambé (SINDA, Copyright 2009). The area surrounding the research station is predominately used for sugarcane (Saccharum officinarum L.) production or is under pasture. The soils in the area are classified as Acrisols (Argisolo Vermelho-­‐Amarelo) (FAO 1998; Jacomine 1972). 3.3.2 Experimental design The experiment consisted of a silvopastoral system established into an existing (approximately 20 year old) B. decumbens pasture in 2008. The experimental design was a randomized complete block design (RCBD) with four blocks and six treatments per block (Table 3.1). One of the control treatments received two applications of fertilizer N at a rate of 60 kg ha-­‐1 in March and April of 2008, and the other was left unfertilized. 47 Table 3.1. Experimental treatments shown by species Treatment Control 1 Control 2 Mororó Gliricidia Leucena Sabiá Species B. decumbens, unfertilized B. decumbens, fertilized B. decumbens + B. cheilantha B. decumbens + G. sepium B. decumbens + L. leucocephala B. decumbens + M. caesilpiniifolia The legume treatments were planted with 2-­‐month-­‐old legume seedlings on July 21, 2008. Each legume treatment (gliricidia, leucena, mororó, sabiá) had three 1-­‐ m wide strips cultivated into the grass pasture at 10 m intervals to allow planting of three hedgerows of legume seedlings, two rows per hedgerow, spaced 1 m apart. The legume shrubs were spaced 0.5 m apart in the rows. Figure 3.2 shows a plan view of the three hedgerows in the legume treatments. Each plot was 660 m2 (33 m x 20 m) as seen in Figure 3.3. Figure 3.2. Plan view of paddock showing 3 legume hedgerows, each with 2 rows of trees with 10 m of grass pasture between. 48 Figure 3.3. Plot design for legume plots showing 3 hedgerows. Grazing began in 2009 and continued monthly until August 2010 when a one month rest period was imposed due to evidence of heavy grazing pressure on the grass and legumes (Dubeux, personal communication, August 2010). The experiment described below was carried out from September 2010 to August 2011. During this period, grazing took place over a three-­‐day period every four weeks, with two cows grazing each paddock in the wet season and one cattle per paddock in the dry season. Table 3.2 shows the schedule for the grazing and sampling periods. Table 3.2. Schedule of sampling cycles for Itambé field project 2010-­2011. Cycle 1 2 3 4 5 6 7 8 9 10 11 12 Date 20/08/2010 – 25/08/2010 24/09/2010 – 29/09/2010 29/10/2010 – 03/11/2010 03/12/2010 – 08/12/2010 07/01/2011 – 12/01/2011 11/02/2011 – 16/02/2011 18/03/2011 – 23/03/2010 22/04/2011 – 27/04/2011 27/05/2011 – 01/06/2011 01/07/2011 – 06/07/2011 05/08/2011 – 10/08/2011 09/09/2011 – 14/09/2011 Number of cattle 2 2 2 2 1 1 1 2 2 2 2 2 49 3.3.3 Plant Sampling In each of the legume treatments six transects were created which started in the legume hedgerow (P1) and continued to the middle of the grass pasture (P5) (Table 3.3). Samples were taken at four week intervals, referred to as cycles, starting one day prior to and ending two days after animals had grazed the paddocks. Table 3.3. Position of quadrat points in relation to the legume hedgerow. Point P1 P2 P3 P4 P5 Quadrat Distance from Legume Row (m) 0.00 1.25 2.50 3.75 5.00 Prior to grazing, plant height in quadrats was measured using a rise plate meter (Figure 3.4; Sollenberger and Burns 2001). Plant material was cut at approximately 5 cm from ground height. Fresh sample weight was taken, and the harvested plant material was composited between transects into points (P1-­‐P5). Material was re-­‐weighed, oven dried at 65°C for 48 h, and weighed for determination of plant material water content at harvesting. Figure 3.4. Rise plate meter. 50 Botanical composition was recorded prior to cutting in cycle 2 (C2) and cycle 11 (C11) using a variation of the dry-­‐weight ranked method developed by Mannetje and Haydock (1963). This method relies on using quadrats and an estimator. The species estimated are divided into three columns: 70%, 21% and 9%. The dry weight ranked method indicates that only the first three species should be recorded, one in each column. However, combining this method with a direct estimation method allowed for more species to be recorded. Myers and Robbins (1991) suggest that this combination method, in which more than one species can be placed in each column, is particularly beneficial when there is one dominant species in the grassland and a number of minor species present in many of the sites. This was the case here, where B. decumbens dominated with more than 90% coverage in many quadrats. However, a number of minor species were consistently present and the combination method allows these species to be better represented. 3.3.4 Statistical analysis The Statistical Analysis Software (v. 9.2, SAS Institute Inc., Cary, N.C.) program was used to perform a variance analysis of the botanical composition data and the pasture dry matter production. Both sets of data met the assumption of the variance analysis, which requires a linear additive model with errors that are homogenous, random, independent, normally distributed and equal to a mean of zero (Bowley 2008). 3.4 Results and Discussion 3.4.1 Height of legume shrubs A large discrepancy in growth existed between the legume shrubs (Table 3.4). The gliricidia and sabiá grew well and had an average height of 3.7 m. The leucena and mororó did not grow well, with an average height of 1.1 m. According to Shelton et al. (1991), establishment of leucena is often a problem. Grazing before a shrub is well established could have caused harm to the leucena. Also, the leucena was very palatable to the livestock, and was completely defoliated during each grazing period. While the mororó was less palatable then the leucena, it did not grow 51 well in the experiment. The gliricidia and sabiá established well and the grass was the preferred forage in these legume paddocks. Table 3.4. Average height (m) of legume shrubs in August 2010 to August 2011. Legume Gliricidia Leucena Mororó Sabiá August 2010 2.40 1.30 0.64 3.05 Height (m) August 2011 3.80 1.90 0.90 5.05 3.4.2 Botanical composition All quadrats measured were dominated by signal grass. Weed invasion by herbaceous and shrubby species, both leguminous and non-­‐leguminous, however, was evident in many of the paddocks. The most common weeds were Desmodium canum, Brachiaria humidicola, Stylosanthes capitata, and seedlings of the planted legumes. Patches of bare soil were also visible, particularly close to the large shrubs in the shaded area. The percent of signal grass, bare soil and other species will be further analyzed below. 3.4.2.1 Percent signal grass The percent signal grass in the leucena (86.7%) and mororó (87.8%) paddocks were significantly different from that in the sabiá (53.0%) paddocks (P=0.05). The gliricidia (67.4) paddocks were not significantly different from any of the other species (data not shown). An analysis of variance of the percentage of signal grass in each grass-­‐legume treatment (Table 3.5) showed that point, cycle and the point*cycle interaction were significant for gliricidia (P<0.05), while only point was significant for mororó and only cycle was significant for leucena. Sabiá showed significant differences in point and point*cycle interactions. 52 Table 3.5. Analysis of variance of three sources of variation in four legume-­grass plots. Treatment Effect Num DF Gliricidia Cycle 1 Point 4 Cycle*Point 4 Leucena Cycle 1 Point 4 Cycle*Point 4 Mororó Cycle 1 Point 4 Cycle*Point 4 Sabiá Cycle 1 Point 4 Cycle*Point 4 *indicates values significant at P<0.05 Den DF 3 12 12 3 12 12 3 12 12 3 12 12 F Value 14.90* 32.96* 3.92* 11.10* 0.97 1.14 6.17 3.46* 0.28 0.36 32.85* 3.96* Pr>F 0.0307 <0.0001 0.0292 0.0447 0.4585 0.3839 0.089 0.0422 0.8837 0.5926 <0.0001 0.0282 Least significant differences were analyzed for % signal grass data in Table 3.6. Average % signal grass ranged from 2.7% (gliricidia P1, C11) to 96.2% (leucena P2, C11). The amount of signal grass in the quadrats changed significantly for gliricidia and sabiá paddocks where P1 and P2 in both cycles had significantly lower amounts of signal grass then P3, P4, and P5. The cycle effect in the mororó paddocks showed that P1 and P2 were significantly different, but were not different from P3, P4 and P5. Percent signal grass increased significantly between C2 and C11 in the leucena paddocks. Similarly, there was a marked decrease in % signal grass between C2 and C11 for gliricidia and sabiá in P1 and P2, but not for leucena and mororó. Table 3.6. LS Means of % signal grass for significant effects of four legume-­grass pastures It shows the cycle*point interaction for gliricidia and sabiá, point effect for mororó and cycle effect for leucena. Letters represent significant differences (P=0.05) within each legume species. Treatment Cycle Point P1 P2 P3 P4 P5 Gliricidia 2 31.5 (0.1)b 83.3 (0.1)a 89.8 (0.1)a 90.2 (0.1)a 88.7 (0.1)a 11 2.7 (0.1)b 33.2 (0.1)b 78.3 (0.1)a 83.2 (0.1)a 93.3 (0.1)a Sabiá 2 22.6 (0.1)cd 48.0 (0.1)abcd 71.7 (0.1)ab 65.0 (0.1)ab 74.0 (0.1)ab 11 11.8 (0.1)d 24.0 (0.1)bcd 54.6 (0.1)abc 80.8 (0.1)a 88.7 (0.1)a Mororó 73.6 (0.1)b 90.3 (0.1)a 88.4 (0.1)ab 88.4 (0.1)ab 88.3 (0.1)ab Leucena 2 80.6 (0.1)b 11 92.7 (0.1)a Standard errors are given in parentheses. Values followed by the same lower case letters, comparing differences between species, are not significantly different at P<0.05. 53 Gliricidia and sabiá grew taller and produced more forage. The significant decrease in % signal grass from P1 to P5 may indicate a shading effect in these plots. The difference between cycles for gliricidia and sabiá at P1 may have been due to problems with growth of the signal grass in full shade, causing the plants not to recover from defoliation. Wendling (2011) found that a signal grass monoculture accumulated more forage and had higher tillering rates then when signal grass was intercropped with Eucalyptus grandis or Acacia mangium trees. In addition, an increased competition for water in the quadrats closest to the trees may have caused a reduction in the amount of grass. Both C2 and C11 are at the beginning of the dry season when competition for water between the grass and the tree would potentially start to cause a decrease in grass production. 3.4.2.2 Percent bare soil The percent of bare soil in the legume-­‐grass plots changed based on species, point, cycle and species by point, species by cycle and species by point by cycle interactions (Table 3.7). However point by cycle was not a significant interaction. Table 3.7. Type III test of fixed effects of % bare soil in legume-­grass pasture plots. Sources of Variation Num DF Den DF Species 3 9 Point 4 12 Cycle 1 3 Species*Point 12 36 Species*Cycle 3 9 Point*Cycle 4 12 Species*Point*Cycle 12 36 *indicates values significant at P=0.05 F value 26.73* 51.68* 13.94* 28.24* 11.7* 2.75 3.21* Pr>F <0.0001 <0.0001 0.0335 <0.0001 0.0018 0.0777 0.0033 Sabiá had the largest % bare soil at an average of 97.8% at P1 in C11, whereas leucena and mororó both had 0% bare soil in multiple quadrats. The least significant difference estimates show that leucena and mororó had less bare soil at P1, P2, and P3 then gliricidia and sabiá (Table 3.8). At P1 all species except mororó showed an increase in % bare soil from C2 to C11. In P4 and P5, sabiá had significantly more bare soil then the other species. 54 Table 3.8. LS Means of species*point*cycle interactions of % bare soil in four legume-­grass pastures. Letters represent significant differences (P=0.05). SE=0.07 Species Cycle Point P1 P2 P3 P4 P5 Gliricidia 2 64.3 (0.1)Aa 12.0 (0.1)Bcd 1.6 (0.1)Bb 0.2 (0.1)Ba 0.4 (0.1)Ba 11 96.4 (0.1)Aa 63.2 (0.1)Aab 14.1 (0.1)Bab 4.9 (0.1)Ba 1.1 (0.1)Ba Leucena 2 6.2 (0.0)Ab 1.4 (0.0)ABcd 0.0 (0.0)Bb 0.6 (0.0)ABa 0.4 (0.0)ABa 11 1.7 (0.0)ABb 0.0 (0.0)Bd 0.1 (0.0)Bb 0.0 (0.0)Ba 0.3 (0.0)Ba Mororó 2 10.0 (0.0)Ab 0.5 (0.0)Acd 0.0 (0.0)Ab 0.0 (0.0)Aa 0.0 (0.0)Aa 11 4.0 (0.0)Ab 0.3 (0.0)Acd 0.4 (0.0)Ab 0.2 (0.0)Aa 0.6 (0.0)Aa Sabiá 2 73.1 (0.1)ABa 40.8 (0.1)BCDbc 13.6 (0.1)CDEab 9.0C (0.1)DEa 3.9 (0.1)EFa 11 97.8 (0.1)Aa 70.9 (0.1)ABa 39.2 (0.1)BCEa 10.7 (0.1)CDEa 4.3 (0.1)DFa Standard errors are given in parentheses. Values followed by the same upper case letters, comparing differences between points for each species, are not significantly different at P<0.05. Values followed by the same lower case letters, comparing differences between species for each point, are not significantly different at P<0.05. 3.4.2.3 Percent other species Table 3.9 show the percent of other species found in the legume-­‐grass plots. Cycle, species by point and point by cycle were significant. All other effects and interactions were not considered significant at P=0.05. Table 3.9. Type III test of fixed effect of % other species in legume-­grass pasture plots. Sources of Variation Num DF Den DF Species 3 9 Point 4 12 Cycle 1 3 Species*Point 12 36 Species*Cycle 3 9 Point*Cycle 4 12 Species*Point*Cycle 12 36 *indicates values significant at P=0.05 F value 0.91 1.87 11.25* 2.24* 3.19 3.58* 0.74 Pr>F 0.4736 0.1799 0.0439 0.031 0.077 0.0382 0.7018 The % other species generally increased from P1 to P5 in the gliricidia and sabiá plots and decreased from P1 to P5 in the leucena and mororó plots (Table 3.10). However, there were no significant differences between points for any species. 55 Table 3.10. LS Means of % other species for species*point interactions in legume-­grass pastures. Species Point 1 2 3 4 5 Gliricidia 2.5 (0.0)Aa 4.2 (0.0)Aa 7.5 (0.0)Aa 7.5 (0.0)Aa 8.2 (0.0)Aa Leucena 15.3 (0.1)Aa 7.7 (0.1)Aa 9.4 (0.1)Aa 8.8 (0.1)Aa 10.6 (0.1)Aa Mororó 13.4 (0.1)Aa 4.4 (0.1)Ba 7.5 (0.1)ABa 6.8 (0.1)ABa 7.8 (0.1)ABa Sabiá 2.0 (0.1)Aa 4.5 (0.1)Aa 5.5 (0.1)Aa 6.4 (0.1)Aa 6.8 (0.1)Aa Standard errors are given in parentheses. Values followed by the same upper case letters, comparing differences between points for each species, are not significantly different at P<0.05. Values followed by the same lower case letters, comparing differences between species for each point, are not significantly different at P<0.05. A decrease in % bare soil was seen at P1 between cycle 2 and cycle 11 (Table 3.11). There was not a significant difference between the cycles at P2, P3, P4 or P5. Table 3.11. LS Means of % other species for point*cycle interactions in legume-­grass pastures. Cycle Point 1 2 3 4 5 2 13.1 (0.0)Aa 6.5 (0.0)Ba 8.9 (0.0)ABa 9.0 (0.0)ABa 11.0 (0.0)ABa 11 3.5 (0.0)Aa 3.9 (0.0)Aa 6.0 (0.0)Aa 5.8 (0.0)Aa 5.8 (0.0)Aa Standard errors are given in parentheses. Values followed by the same upper case letters, comparing differences between points for each cycle, are not significantly different at P<0.05. Values followed by the same lower case letters, comparing differences between cycles for each point, are not significantly different at P<0.05. 3.4.2.4 Unfertilized signal grass, fertilized signal grass and P5 The two control treatments -­‐ unfertilized signal grass and fertilized signal grass -­‐ did not differ significantly in the % signal grass, % bare soil or % other species in the quadrats measured for any of the cycles (data not shown). When they were compared to P5 in the legume plots, no differences were found in the botanical composition measures between the controls and any of the treatment P5 quadrats. This may indicate that the amount of sunlight and competition for water were more influential than legume species at P5, causing it to react similarly. 56 3.4.3 Productivity 3.4.3.1 Grass-­legume treatments Average dry matter production was between 0.79 Mg ha-­‐1 cycle-­‐1 for sabiá to 1.21 Mg ha-­‐1 cycle-­‐1 for mororó. Table 3.12 indicates that the herbage mass in the paddocks with gliricidia and sabiá were significantly lower then in the leucena and mororó paddocks. While gliricidia and sabiá grew well and were not the animals’ first choice of forage during the grazing periods, the leucena and mororó were almost fully defoliated by the end of each grazing period, causing a large disparity between the tall legumes and the small legumes. This may have been the result of increased competition for sunlight and water in the gliricidia and sabiá plots, as well as to an increase in the amount of grass defoliated by the cattle in these paddocks. Table 3.12. LS Means of herbage mass (Mg ha-­1) of pasture grass by legume-­species treatment. Estimates followed by the same letter are not different at P<0.05. -­‐1
Treatment Herbage Mass (Mg ha ) Gliricidia 0.91 (2.43)b Leucena 1.13 (2.43)a Mororó 1.21 (2.43)a Sabiá 0.79 (2.43)b Standard errors are given in parentheses. Values followed by the same lower case letters, comparing differences between species, are not significantly different at P<0.05. The herbage mass of the pasture changed between cycles. Table 3.13 shows that the grass production was greatest in C2, then decreased through C5 and C7 and increased in C11. Data from the weather station at Itambé (SINDO) indicates that more precipitation falls in the winter and spring months (May -­‐ October) then in the summer and fall (November -­‐ April). Cycles 2 and 11 fell within this wetter time, while C5 and C7 were in the dry period. Cycle 7 is further into the dry period and would be expected to have the lowest productivity, with less residual moisture being left in the top 20 cm of the pasture for grass growth. 57 Table 3.13. LS Means of herbage mass (Mg ha-­1) of pasture grass by cycle. Estimates followed by the same letter are not different at P<0.05. -­‐1
Cycle Herbage Mass (Mg ha ) 2 1.12 (2.15)a 5 1.00 (2.15)ab 7 0.86 (2.15)b 11 1.07 (2.15)a Standard errors are given in parentheses. Values followed by the same lower case letters, comparing differences between cycles, are not significantly different at P<0.05. An analysis of variance of cycle, point and cycle by point interactions was performed for each species separately. The results in Table 3.14 show that cycle was significant for leucena while point was significant across all species and cycle by point interaction were significant for gliricidia and sabiá only. Table 3.14. Type III Test of Fixed Effects for pasture productivity (Mg ha-­1 herbage mass) in cycle, point and cycle*point interactions for four treatments analyzed separately. Treatment Gliricidia Leucena Mororó Sabiá Effect Cycle Point Cycle*Point Cycle Point Cycle*Point Cycle Point Cycle*Point Cycle Point Cycle*Point Num DF 3 4 12 3 4 12 3 4 12 3 4 12 Den DF 9 12 36 9 12 36 9 12 36 9 12 36 F Value 2.17 59.27* 4.50* 7.13* 6.29* 1.43 6.15 7.18* 0.65 0.91 25.1* 4.71* Pr>F 0.1614 <.0001 0.0002 0.0094 0.0057 0.1969 0.0146 0.0034 0.7858 0.4738 <.0001 0.0001 *indicates values significant at P<0.05 Little difference was seen between cycles when the species were analyzed separately. Grazing time and number of cattle were reduced during the dry season (C5 and C7) which would have decreased the total amount of herbage removed by grazing, however, with very little re-­‐growth occurring between grazing periods a decrease in herbage mass would still be expected. Sollenberger and Burns (2001), in a study on grass-­‐legume swards in Colombia found that cattle preferences changed with the season, consuming more grass during the wet season and more legume during the dry season. They suggest this is because legumes stay green longer during the 58 dry period. The cattle consuming more legume and less grass may have been the cause of the similarity between the dry weight herbage mass between the time periods. The herbage mass in the quadrats across the paddocks increased with distance from the legume row for all treatments. Gliricidia increased the most from 0.63 Mg ha-­‐1 in P1 to 1.11 Mg ha-­‐1 in P5 (Table 3.15). Table 3.15. LS Means of grass herbage mass (Mg ha-­1) in quadrats at points P1-­P5 away from the legume trees. Statistical comparisons are within columns. Point Gliricidia Leucena Mororó Sabiá P1 0.63 (3.70)d 1.06 (2.52)bc 1.08 (2.49)b 0.57 (2.18)d P2 0.84 (3.70)c 1.03 (2.52)c 1.16 (2.49)ab 0.70 (2.18)cd P3 0.94 (3.70)bc 1.16 (2.52)abc 1.29 (2.49)a 0.79 (2.18)bc P4 1.02 (3.70)ab 1.18 (2.52)ab 1.29 (2.49)a 0.92 (2.18)ab P5 1.11 (3.70)a 1.21 (2.52)a 1.30 (2.49)a 0.99 (2.18)b Standard errors are given in parentheses. Values followed by the same lower case letters, comparing differences between points for each species, are not significantly different at P<0.05. Increased herbage yield with increasing distance from legume rows was expected for gliricidia and sabiá, where a lot of shading would have been occurring and botanical composition analysis indicated there was a lot of bare soil close to the legume. Carrilho et al. (2012) found that Brachiaria genus had a significantly lower herbage yield at 30 and 50% shade then at 0%. Brachiaria decumbens, which is considered to be a moderately shade tolerant species, showed a decrease in tillering at 54% shade, whereas other species showed a decrease at 36% shade (Paciullo et al. 2011). Shaded areas maintain higher soil humidity levels for longer then non-­‐shaded areas. Paciullo et al. (2011) showed that soil moisture content and microbial activity affecting N mineralization were both higher in shaded areas. This might counteract the effect of less photosynthetic activity, especially in the dry season. However, in this study the opposite effect was seen, where pasture grass production decreased more dramatically in the shaded areas of the large legumes compared to those of the small legumes. This may have been due to the competition for moisture between the grass and legume that would have been strongest close to the legumes. 59 3.4.3.2 Unfertilized signal grass, fertilized signal grass and P5 Comparison of dry matter production in quadrats of unfertilized signal grass and fertilized signal grass showed no significant differences for cycle, species or cycle by species interactions (data not shown). When these plots were compared against the P5 values of the legume paddocks, species and cycle had significant effects (Table 3.16). Table 3.16. Type III test of fixed effects for unfertilized signal grass, fertilized signal grass and P5 of legume treatments when herbage mass (Mg ha-­1) of grass was measured. Sources of Variation Num DF Den DF F value P >F Species 5 15 7.27* 0.0012 Cycle 3 9 6.87* 0.0105 Species by Cycle 15 45 1.44 0.1697 LS Means: Species Estimate Unfertilized signal grass 0.70a Fertilized signal grass 0.66ab Gliricidia P5 0.55bc Leucena P5 0.60abc Mororó P5 0.65ab Sabiá P5 0.50c SE=2.924 LS Means: Cycle Estimate C2 0.67a C5 0.59ab C7 0.53b C11 0.65a SE=2.515 *indicates values significant at P=0.05. Standard errors are given in parentheses. Values followed by the same lower case letters, comparing differences between species or cycles, are not significantly different at P<0.05. Unfertilized signal grass and fertilized signal grass produced more herbage mass then the P5 quadrats of the legume plots. Both the fertilized and unfertilized signal grass plots were invaded with weedy species, many of them leguminous. This may have been one reason for the increased herbage mass in these paddocks. The mororó and leucena P5 quadrats did not differ significantly from the signal grass and fertilized signal grass plots. Sabiá was significantly different, producing the least dry matter at (0.50 Mg ha-­‐1). Significantly less herbage mass was produced during C7 then in C2 or C11 when unfertilized signal grass, fertilized signal grass and P5 were compared (Table 3.16). This follows the same trend as the legume treatments, due to climatic conditions. 60 3.5 Conclusions The overall growth of the grass was better in the paddocks without shrubby legumes (unfertilized signal grass and fertilized signal grass) and during the rainy season. This was likely due to the presence of weedy herbaceous legumes that grew into the plots in the years leading up to the experiment. Productivity of grass in the legume paddocks as measured by % ground cover and dry weight was more affected by transect point then by time period. The difference between the larger and smaller legumes was very apparent, suggesting that shading and water stress were likely the most important factors effecting grass performance in the experiment. 3.6 References Andrade, C.M.S., J.F. Valentim, J.B.M. Pereira, and A.S. Ferreira. 2010. Yield and botanical composition of a mixed grass-­‐legume pasture in response to maintenance fertilization. Revista Brasileira de Zootecnia 39(8): 1633-­‐1640. Ayarza, M.A., I.M. Rao, R.J. Thomas, M.J. Fisher, C.E. Lascano, and P. Herrera. 1994. Standing root biomass and root distribution in Brachiaria decumbens-­Arachis pintoi pastures under grazing. In: Proceedings of the XVII International Grassland Congress, Vol. 3. pg. 1921. Palmerston North, New Zealand. Boddey, R.M., R. Macedo, R.M. Tarré, E. Ferreira, O.C. de Oliveira, C. de P. Rezende, et al. 2004. Nitrogen cycling in brachiaria pastures: The key to understanding the process of pasture decline. Agriculture, Ecosystems and Environment 103(2): 389-­‐403. Bowley, S.R. 2008. A Hitchhiker’s Guide to Statistics in Plant Biology. 2nd Edition. Any Old Subject Books, Guelph, ON. Carrilho, P.H.M., J. Alonso, L.D.T. Santos, and R.A. Sampaio. 2012. Vegetative and reproductive behavior of Brachiaria decumbens cv. Basilisk under different shade levels. Cuban Journal of Agricultural Science 46(1): 85-­‐90. Chen, C.P., and J.K. Bong. 1983. Performance of tropical forages under the closed canopy of oil palm. 1. Grasses. MARDI Research Bulletin 11: 248-­‐263. Cook, B.G., Pengelly, B.C., Brown, S.D., Donnelly, J.L., Eagles, D.A., Franco, M.A., Hanson, J., Mullen, B.F., Partridge, I.J., Peters, M., and Schultze-­‐Kraft, R. 2005. Tropical forages: an interactive selection tool, website, CSIRO, DPI&F(Qld), CIAT and ILRI, Brisbane, Australia. 61 CPRH – Companhia Pernambucana do Meio Ambiente. 2003. Diagnóstico sócio ambiental do Litoral Norte de Pernambuco. Recife, 214p. de Oliveira, O.C., I.P. de Oliveira, B.J.R. Alves, S. Urquiaga, and R.M. Boddey. 2004. Chemical and biological indicators of decline/degradation of brachiaria pastures in the Brazilian Cerrado. Agriculture, Ecosystems and Environment 103(2): 289-­‐300. Fisher, M.J., and P.C. Kerridge. 1996. “Chapter 3: The Agronomy and Physiology of Brachiaria Species”.. In: V. Kumble (ed), Brachiaria: Biology, Agronomy and Improvement. pp. 43-­‐52. Cali Columbia: CIAT. Fonseca, D.M., J.A. Martuscello, and D.J.G. Faria. 2006. Adubação em gramíneas do gênero Brachairia: mitos e realidades. Simpósio sobre manejo estratégico das pastagens. Universidade Federal de Viçosa, Brazil. pp. 153-­‐182. Food and Agriculture Organization of the United Nations. 1998. World reference base for soil resources. ISBN 92-­‐5-­‐104141-­‐5. Accessed online at http://www.fao.org/docrep/W8594E/w859 4e00.htm#. Gobbi, K.F. 2007. Características morfoanatômicas, nutricionais e produtividade de forrageiras tropicais submetidas ao sombreamento. PhD Thesis. Universidade Federal de Viçosa. Brazil. p. 82. Harding, W.A.T. 1972. The contribution of plant introduction to pasture development in the wet tropics of Queensland. Tropical Grasslands 6(3): 191-­‐199. Hohnwald, S., B. Rischkowsky, A.P. Camarao, R. Schultze-­‐Kraft, J.A. Rodrigues Filho, and J.M. King. 2006. Integrating cattle into the slash-­‐and-­‐burn cycle on smallholdings in the Eastern Amazon, using grass-­‐capoeira or grass-­‐legume pastures. Agriculture, Ecosystems and Environment, 117(4), 266-­‐276. Jacomine, P.K.T. 1972. Levantamento exploratório – reconhecimento de solos do Estado de Pernambuco, descrição de perfis de solos e analyses. Recife: MA – DNPEA/SUDENE/DRN. v. 1 (MA-­‐DNPEA. Boletim Técnico, 26). Jose, S., S.C. Allen, and P.K.R. Nair. 2008. “Chapter 2: Tree-­‐crop interactions: lessons from temperate alley-­‐cropping systems” In:D.R. Batish et al. (Eds.) Ecological Basis of Agroforestry pp. 15-­‐37. Boca Raton, USA: Taylor and Francis Group. Klink, C.A. 1994. Effects of clipping on size and tillering of native and African grasses of the Brazilian savannas (the cerrado). Oikos 70: 365-­‐376. Lambers, H., F.S. Chapim III, and T.L. Pons. 1998. Plant physiological ecology. Springer, New York. 540pp. Lascano C.E., and J. Estrada. 1989. Long-­‐term productivity of legume-­‐based and pure grass pastures in the Eastern Plains of Colombia. In: XVI International Grassland Congress, pg. 1179-­‐
1180. Nice, France. 62 Loch, D. S. 1977. Brachiaria decumbens (signal grass): a review with particular reference to Australia. Tropical Grasslands 11(2): 141-­‐157. Louw-­‐Gaume, A.E., I.M. Rao, A.J. Gaume, and E. Frossard. 2010. A comparative study on plant growth and root plasticity responses of two Brachiaria forage grasses grown in nutrient solution at low and high phosphorus supply. Plant and Soil 328: 155-­‐164. Mannetje, L., and K.P. Haydock. 1963. The dry-­‐weight-­‐rank method for the botanical analysis of pasture. Grass and Forage Science, 18: 268–275. Martuscello, J.A., L. Jank, M.M.G. Neto, V.A. Laura, and D.N.F.V. da Cunha. 2009. Produção de gramíneas do gênero Brachiaria sob níveis de sombreamento. Revista Brasileira de Zootecnia 38(7): 1183-­‐1190. Myers, R.J.K., and G.B. Robbins. 1991. Sustaining productive pastures in the tropics 5. Maintaining productive sown grass pastures. Tropical Grasslands 25: 104-­‐110. Paciullo, D.S.C., P.B. Fernandes, C.A.M. Gomide, C.R.T. Castro, F. de Souza Sobrinho, and C.A.B. de Carvalho. 2011. The growth dynamics in Brachiaria species according to nitrogen dose and shade. Revista Brasileira de Zootecnia 40(2): 270-­‐276. Pires, M.F.A, L.E. Salla, C.R.T. Castro, D.S.C. Paciullo, M.G.C.D. Peixoto, R.L. Teodoro, L.J.M. Aroeira, and F.J.N. Costa. 2008. Physiological and behavioural parameters of crossbred heifers in single Brachiaria decumbens pasture and in silvopastoral system. In: Proceedings of the International Conference on Livestock and Global Cimate Change. Editors P. Rowlinson, M. Steele and A. Nefzaoui. May 17-­‐20, 2008, Hammamet, Tunisia. Rao M.R., P.K. Nair, and C.K. Ong. 1998. Biophysical interactions in tropical agroforestry systems. Agroforesty Systems 38: 3-­‐50. Rika, I.K., I.K. Mendra, M. Gusti Oka, and M.G. Oka Nurjaya. 1991. New forage species for coconut plantations in Bali. In: Shelton, H.M and W.W. Stür (eds). Forages for plantation crops: proceedings of a workshop, Sanur Beach, Bali, Indonesia 27-­‐29 June 1990. ACIAR proceedings no. 32. ACIAR, Canberra, A.C.T. Australia p. 41-­‐44. Shelton, H.M., J.B. Loway, R.C. Gutteridge, R.A. Bray, and J.H. Wildin. 1991. Sustaining productive pastures in the tropics 7. Tree and shrub legumes in improved pastures. Tropical Grasslands, 25: 119-­‐128. Shelton, M. 2000. Brachiaria decumbens. In: Grassland Species Profiles. CIAT/FAO collaboration on Tropical Forages. Accessed online at http://www.fao.org/ag/AGP /AGPC/doc/Gbase/Default.htm. SINDA – Sistema Nacional de Dados Ambientais. 2009. Brasil Secretaria de Ciência e Tecnologia. Accessed online at: http://sinda.crn2.inpe.br/PCD/metadados.jsp?uf=16&id=31752&tipo=MET. 63 Sollenberger, L.E., and J.C. Burns. 2001. Canopy characteristics, ingestive behaviour and herbage intake in cultivated tropical grasslands. In: International Grassland Congress Vol. 19, pg. 321-­‐327. Piracicaba: Fealq. Wendling, I. J. Ph.D. Thesis. Universidade Federal de Viçosa, October 2011. Productivity and nutritive value of signalgrass silvopastoral systems with eucalyptus and acacia trees fertilized with nitrogen. Adviser: Rasmos Garcia. Co-­‐Advisers: Júlio César Lima Neves and Dimermando Miranda da Fonseca. 64 ________________________________________________________________________________________________________________ Chapter 4 15N natural abundance of four shrubby legumes, B. decumbens, litter and soil in a grazed pasture system in Northeast Brazil 4.1 Introduction Nitrogen deficiencies often develop in tropical pasture systems due to low inputs and poor existing soil conditions (Kenichi et al. 2002). Planting mixed grass-­‐legume pastures can combat this N shortage; however, herbaceous legumes usually create management complexity for farmers. Silvopastural systems which include leguminous trees or shrubs in grass pastures, provide an alternative to herbaceous mixed pastures that offer added benefits to farmers including shade for animals, secondary income in timber and fence posts and increased forage during dry seasons (Gutteridge and Shelton 1994). Estimating N-­‐fixation in silvopastoral systems, however, can be challenging due to the complex interactions and nutrient cycling that occurs between soil, shrubs, grasses and animals (Gathumbi et al. 2002). 4.1.1 Measuring N-­fixation: Natural abundance of 15N A method used to measure N-­‐fixation and transfer is the 15N natural abundance method. The natural abundance of 15N method is based on a ratio of the two stable isotopes of nitrogen, 14N and 15N. 14N is the lighter isotope and makes up 99.6337% of the N2 found in the atmosphere and 15N, the heavier isotope, makes up 0.3663% of the atmospheric nitrogen (Zuberer 2005). Due to the mass difference of the two isotopes, N pools in the environment have differential uptake rates. The ratios of 15N to 14N are measured in plant and soil samples as ‘isotopic signatures’ of N – written as δ 15N (Högberg 1997). Since atmospheric N has a lower δ15N then soil N pools, plants that fix atmospheric N2 will have a lower δ15N then plants which obtain all of their N from the soil (Sprent et al. 1996). Percent nitrogen derived from the atmosphere (%Ndfa) is calculated by first computing δ 15N (Equation 4.1), then applying it in Equation 4.2: Equation 4.1 and 66 %Ndfa =
(δ 15N ref −δ 15N fix )
× 100 (δ 15N ref − B)
Equation 4.2 €
(Höberg 1997; Sierra and Nygren 2006) Where, in Equation 4.1, ‘R’ is the ratio of 15N:14N and, in Equations 4.2, ‘ref’ is a non-­‐fixing reference species, ‘fix’ is the legume and ‘B’ is the 15N:14N ratio of the legume when grown without soil N (Sierra and Nygren 2006). 4.1.1.1 Reference species Nitrogen fixation determination using the natural abundance method requires the use of a non-­‐N fixing reference species to be measured alongside sample species. The best reference species have similar root systems, growth behaviour, temporal N uptake patterns and preferences for mineral N acquisition as the sample species (Högberg 1997; Wanek and Arndt 2002). Suitable reference species are often difficult to find, creating a source of error in the determination of N fixation, however, when acceptable species are found, it allows for more accuracy and precision in estimated values (Wanek and Arndt 2002). 4.1.1.2 Isotopic discrimination Mineralization, immobilization, nitrification and other soil N transformations all undergo isotopic discrimination (Wanek and Arndt 2002). According to Boddey et al. (2000), mineralization and immobilization have lower isotopic discrimination factors than nitrification. These factors are expressed by a ratio of 2 constants (14k/15k), which is termed β (Boddey et al. 2000). Different values of β have been estimated including 1.005 and 1.0046 for immobilization, 1.025 and 1.0176 for nitrification and 1.0046 for ammonification (Herman and Rundel 1989; Shearer et al. 1974;). Shearer et al. (1974) suggest that given these β values, if ammonification and nitrification are occurring at the same time, NO3-­‐ will be depleted in 15N and the immobilized N will be enriched in 15N. It is for this reason that over a long period of time (decades) the organic N pool in the soil becomes enriched with 15N. 67 This trend is then transferred to the plants growing in the soil. Plants using NO3-­‐ as a source of N will likewise be depleted in 15N compared to the soil N pool (Högberg et al. 1996). Boddey et al. (2000) suggest that pioneer species mostly use nitrate N, these species are then recycled into litter and the litter is mineralized into usable forms of N, which are quickly incorporated into plant material. This is a mechanism by which plants continue to be relatively depleted in 15N, even when soil is enriched (Boddey et al. 2000). 4.1.1.3 B-­value A B-­‐value is the 15N abundance of plant tissue when grown without soil N, and therefore assumed to be obtaining all of it’s N from fixation (Boddey et al. 2000). This is usually measured by growing a species in an N-­‐free medium or hydroponically. Most estimates for B range between -­‐
2.0 and +1.0‰ (Ledgard 1989). Many sources of error exist in the determination of B-­‐values. One potential error is that natural systems are usually associated with more than one symbiotic association, whereas with planted systems, one inoculate is chosen. A number of researchers including Bergersen et al. (1986) and Yoneyama et al. (1986) found significant differences in B value depending on the rhizobium strain used. Error can also occur when using N-­‐free mediums. For example, vermiculite, which is often used as a growth medium, has been shown to retain ammonium ions in unexpanded layers of the 2:1 lattice (Giller et al. 1986). Another difficulty is in growing plants for B-­‐value that are the same age as the plants for sampling, since δ15N declines in the shoot with age (Boddey et al. 2000). Volatilization of ammonia has been shown to occur in the older leaves of plants, causing possible errors because volatilized N is likely depleted in 15N (Boddey et al. 2000; Turner et al. 1983). 4.1.1.4 Fractionation Fractionation during N2 fixation is thought to be small, however fractionation during transport of N into various parts of the plant can be significant (Shearer and Kohl 1986; Van Kessel et al. 68 1994;). Shearer and Kohl (1986) found δ15N values of stem tissues to be slightly lower than that of foliar tissues. Nygren and Leblanc (2009) examined fractionation in the legume tree Gliricidia sepium, finding values of 0.13 (SE 0.127) in young leaves, 0.31‰ (SE 0.181) in mature leaves, -­‐
0.60‰ (SE 0.304) in branches, -­‐0.53‰ (SE 0.113) in stems and -­‐0.05‰ (SE 0.157) in coarse roots. They indicate that fractionation was not significant based on these values. Van Kessel et al. (1994) suggest that researchers use similar tissues from all the plants to be compared to avoid differences due to fractionation. 4.1.2 Estimates of N fixation of legumes Due to the complications in estimating N-­‐fixation, there is a large range for estimates of N-­‐
fixation in legume shrubs, depending on climate, soil, season and management practices. Gliricidia sepium (gliricidia) was found to derive 35% of its N from fixation 24 weeks after planting and 54% 48 weeks after planting (Sanginga et al. 1995). Leucaena leucocephala (leucena) values ranged from 98 to 274 kg N ha-­‐1 in a six-­‐month period in studies in Nigeria and Tanzania, respectively (Högberg and Kvarnström 1982; Sanginga et al. 1986, 1989). 4.1.3 Transfer of N from legumes The transfer of N from fixing to non-­‐fixing components of pasture systems is not well understood. A number of different pathways of N-­‐transfer are thought to exist including belowground transfer via mineralization of roots and by mycorhizae hyphae (Pirhofer-­‐Walzl et al. 2012; Trannin et al. 2000). Aboveground transfers may occur via litter and animal excrement decomposition (Thomas and Asakawa 1993). Numerous studies of gliricidia have shown transfer of fixed N to coffee in the range of 13 to 42% and to grass in the range of 31 to 35% (Dulormne et al. 2003; Haggar et al. 1993; Sierra and Nygren 2006). These studies all were within systems were there was direct contact between the roots of the leguminous and non-­‐leguminous plants. Other studies, where the transfer would be indirect, have shown 0.8 to 1.1% of total N in grass as originating from fixation (Jalonen et al. 2009). Studies of leucena have also shown variable amounts of N transferred to associated non-­‐
leguminous plants (Van Kessel et al. 1994). 69 4.1.4 Effects of grazing Estimating N-­‐fixation in a pasture ecosystem is further complicated by animal grazing. Cattle redistribute nutrients across pasture systems through urine and feces. This is often done in a non-­‐uniform manner since cattle tend to spend more time in shaded areas and close to water supplies than elsewhere (Haynes and Williams 1993). Little research measuring N-­‐fixation in these systems exists to date. Determining N-­‐fixation in different legumes and the associated grass in paddocks of a functioning pasture system is an important step to assessing legume suitability in specific systems. This study analyzed the N-­‐fixation capability of four shrubby legumes: B. cheilantha, G. sepium, L. leucocephala, and M. caesalpiniifolia in a pasture system planted with B. decumbens. Further, N-­‐
fixation in B. decumbens was measured to preliminarily assess transfer of N from the legumes to the grass. 4.2 Materials and Methods 4.2.1 Study site and experimental design The study site and experimental design are outlined in Chapter 3 of this document. 4.2.2 Sampling Plant material was cut at approximately 5 cm in each transect point. The samples were weighed fresh and then composited between transects into points (P1-­‐P5), resulting in 5 samples per paddock treatment. The composited sample was weighed fresh, dried (65°C for 48 h) and weighed dry. Litter samples were collected in cycle (C) 4, C5, and C7-­‐ C12. These samples were weighed, composited, dried and re-­‐weighed in the same manner as the live plant material. Soils were sampled using a 6 cm diameter soil core during C2 and C11. Three soil cores were taken at random in each quadrat and divided into 0-­‐10 cm, 10-­‐20 cm and 20-­‐40 cm segments. 70 The soil was air dried, sieved to <2 mm and composited in the same way as the plant and litter material. 4.2.4 Analysis A 100 g sample of each soil was submitted to the Universidade Federal Rural de Pernambuco Departmento de Agronomia, Laboratório de Fertilidade do Solo, Recife, Brazil to determine pH (water–1:2.5), Mehlich-­‐I phosphorus, sodium, calcium, magnesium, aluminum, organic carbon and organic matter content (EMBRAPA 1979). Dried and sieved (2 mm) soil samples were ground using a shaker-­‐ball mill to a fine powder (~250 μm). The plant samples were coarse ground with a Wiley Mill and then in a shaker-­‐ball mill to a fine powder (~250 μm). The samples were encapsulated into tin capsules (6 mm x 4 mm for plant samples and 8 mm x 5 mm for soil samples). Total N and δ15N were measured using a mass spectrometer at the Stable Isotope Facility of the University of Saskatchewan, Saskatoon, Canada. 4.2.4.3 Statistical analysis All data were analyzed using the Statistical Analysis Software package (v. 9.3, SAS Institute Inc., Cary, N.C.) with a variance analysis in the ‘proc mixed’ coding. It was determined that the original scale of the data best met the assumption of a variance analysis, which required a linear additive model with errors that are homogenous, random, independent, normally distributed and equal to a mean of zero (Bowley 2008). The variance analysis was partitioned into fixed (cycle, species, point, and depth) and random (block) effects. A p-­‐value of 0.05 was used. 71 4.3 Results and Discussion 4.3.1 Soil 4.3.1.1 Soil fertility No significant differences were seen in pH when looking at Type 3 fixed effects at an error rate of 0.05 for cycle, species, point, depth and the interactions of these effects (Table 4.1). Cycle by species had a significant interaction for P, Na, CaMg, Ca, Al, HAl, and organic carbon (O.C.). Other significant interactions for P were cycle by species by point, species by point and depth. No effects were significant for K. Species by point and depth were significant for CaMg while only depth was further significant for Ca. Cycle by species by point and depth were also significant for HAl but not for Al. Cycle by species by point was significant for soil organic carbon. Table 4.1. P-­values (at type 3 error rate of 0.05) of soil fertility parameters across effects of a variance analysis. Effect Cycle cycle*species cycle*species*point cycle*species*depth cycle*point*depth cycl*spec*point*depth Species species*point species*point*depth Point point*depth Depth Soil Fertility Parameter pH P Na 0.7238 0.8753 0.1664 0.9782 <.0001 <.0001 0.3769 0.0019 0.1238 0.5959 0.9965 0.8232 0.2867 0.9762 0.9743 0.5091 0.9999 0.6292 0.957 0.6383 0.4585 0.2958 0.0032 0.815 0.4289 1 0.7457 0.3539 0.3401 0.15 0.3226 0.9995 0.8323 0.6275 0.022 0.3317 K 0.5599 0.9514 0.2531 0.6182 0.9149 0.3488 0.2966 0.306 0.1807 0.574 0.9166 0.085 CaMg 0.4095 <.0001 0.6448 0.9064 0.6739 0.8355 0.1848 0.0007 0.6444 0.607 0.3372 0.0013 Ca 0.7919 <.0001 0.6532 0.9759 0.6875 0.542 0.8248 0.6843 0.7614 0.7958 0.2279 <.0001 Al 0.4881 0.016 0.1595 0.9574 0.4971 0.0829 0.4307 0.1224 0.4426 0.602 0.5834 0.3921 HAl 0.2306 <.0001 0.0051 0.903 0.7723 0.9977 0.7017 0.6586 0.816 0.3038 0.8394 0.0006 O.C. 0.2903 0.0107 0.0243 0.997 0.9978 0.9996 0.9874 0.7766 0.9888 0.914 0.8969 0.8716 4.3.1.2 Soil total N and δ15N natural abundance Soil δ15N values for the field experiment ranged from 5.22‰ to 7.92‰ and were similar to values found in a review of pasture studies by Hobbie and Ouimette (2009). The variance analysis of soil δ15N for the whole experiment showed no significant effects when species, cycle, point, depth and their interactions were analyzed at P>0.05. Table 4.2 shows F and P values for 72 these effects and interactions. Percent total N values ranged from 0.0015 to 0.2218. Percent N values were significant (P>0.05) for cycle by species interaction and depth. Table 4.2. Type 3 fixed effects of soil δ15N and % total N values analyzed across 6 species, 2 cycles, 5 points and 3 depths. Effect Num DF Cycle 1 Species 5 Point 4 Depth 2 Cycle*Species 5 Cycle*Point 4 Cycle*Depth 2 Species*Point 12 Species*Depth 10 Point*Depth 5 Cycle*Species*Point 12 Cycle*Species*Depth 10 Cycle*Point*Depth 5 Species*Point*Depth 15 Cycle*Species*Point*Depth 15 *indicates values significant at P>0.05 Den DF 3 15 12 6 205 205 205 205 205 205 205 205 205 205 205 15
F Value* 3.49 0.43 0.67 4.52 0.47 1.00 0.26 0.89 0.28 0.76 0.94 0.32 0.53 0.70 0.68 δ N Pr>F 0.1584 0.8197 0.6282 0.0634 0.7986 0.4076 0.7714 0.5567 0.9857 0.5795 0.5092 0.9766 0.75 0.7875 0.8048 F Value* 8.34 2.05 1.85 22.69* 3.44* 0.85 0.81 0.99 1.42 1.02 0.78 0.81 0.71 0.34 0.34 % Total N Pr>F 0.0631 0.1294 0.1839 0.0016 0.0052 0.4976 0.4479 0.4549 0.1723 0.4096 0.6668 0.6217 0.6202 0.9896 0.9896 4.3.1.2.1 Grass-­legume paddocks In the plots with legume shrubs, surface soil was significantly depleted in δ15N compared to soil at a depth of 20-­‐40 cm (Table 4.3). Soil δ15N increased with depth from 6.01‰ (SE=0.070) and 5.82‰ (SE=0.067) in the 0-­‐10 cm layer of soil to 6.42‰ (SE=0.066) and 6.47‰ (SE=0.069) in the 20-­‐40 cm layer of soil. An increase in δ15N with depth is common in forest and grassland soil as 15N-­‐depleted litter is deposited on the surface (Högberg 1997). This more labile pool of organic matter also undergoes N transformations and movement more quickly than organic matter at depth and these differences may be reflected in the δ15N of the soil (Hobbie and Ouimette 2009). 73 Table 4.3. LS means of soil δ15N and % total N in four legume treatments measuring P1 and P5 across 3 depths. 15
Point Depth (cm) δ N (%0) % Total N (%) 1 0-­‐10 6.01 (0.07)b 0.146 (0.010)ab 10-­‐20 6.38 (0.07)a 0.146 (0.010)ab 20-­‐40 6.42 (0.07)a 0.123 (0.009)bc 5 0-­‐10 5.82 (0.07)b 0.150 (0.010)a 10-­‐20 6.43 (0.07)a 0.142 (0.009)ab 20-­‐40 6.47 (0.07)a 0.115 (0.010)c Standard errors are given in parentheses. Values followed by the same lower case letters, comparing differences between points and depths, are not significantly different at P<0.05. No significant differences were seen in δ15N between P1 and P5 indicating that distance from the legume tree did not play a significant role in soil δ15N. Sierra and Nygren (2006) also found relative homogeneity of soil δ15N across plots in a five-­‐year experiment. Their experiment removed legume tree prunings from a pasture system periodically to determine the effect of root litter on δ15N. Their results indicated that soil δ15N could not be correlated with current tree root density since it may take soil isotopic signatures four to six years to stabilize after the introduction of tree legumes (Sierra and Nygren 2006). In addition, the δ15N of the total soil N pool will change more slowly than the more labile soil mineral N. Turner et al. (1983) found that while the δ15N of the total soil was stable in an experiment that looked at fallow land and oat crops, the δ15N of the mineral N was changing significantly from season to season. This may indicate that the soil δ15N of the current experiment had not stabilized at the time of sampling and while changes may have been apparent in the mineral N pool, the total N pool was not changing rapidly enough to measure. The results may further be homogenized by grazing, which may acts to distribute legume nutrients across the paddock through urine and manure patches. No significant differences were seen in P1 between the depths for total N values (Table 4.3), however, a significant decrease in total N was seen in P5 between the 0-­‐10 (0.146%) and the 20-­‐
40 (0.123%) depth. This may be an indication of the presence of more legume root litter at P1, increasing the total N to depth. Similarly Sierra and Nygren (2006) concluded that soil N content increased more in areas closer to legume trees than in open grassland over 12 years. The presence of grazing cattle may be the reason that the 0-­‐10 cm layer did not change over distance. 74 4.3.1.2.2 Fertilized and unfertilized signal grass When a variance analysis of the fertilized and unfertilized signal grass treatment soils was performed, depth, cycle by depth, treatment by depth and cycle by treatment by depth were significant for δ15N while only treatment by depth was significant for total N (Table 4.4). Table 4.4. Type 3 fixed effects of soil δ15N and % total soil N values analyzed in signal grass and fertilized signal grass plots, over 2 cycles, and at 3 depths. 15
Effect Num DF Den DF Cycle 1 3 Species 1 3 Depth 2 6 Cycle*Species 1 15 Cycle*Depth 2 15 Species*Depth 2 15 Cycle*Species*Depth 2 15 *indicates values significant at P=0.05 δ N F Value* Pr>F F Value* 0.74 0.4542 0.14 1.11 0.3699 0 10.18* 0.0118 3.53 3.84 0.0688 0.75 9.36* 0.0023 0.28 5.65* 0.0148 5.57* 21.78* <.0001 0.82 % Total N Pr>F 0.7373 0.9871 0.0969 0.4006 0.757 0.0155 0.4598 In the fertilized signal grass treatment, δ15N in 10-­‐20 cm depth (6.16‰) was the most depleted and was significantly different (P=0.05) then the 20-­‐40 cm depth (6.55‰) (Table 4.5). The total N values show the same trend, with the 10-­‐20 cm layer having significantly more N than the 20-­‐
40 cm layer. In the unfertilized treatment the 0-­‐10 cm depth was significantly depleted in 15N compared to the deeper samples, showing a similar pattern to the grass-­‐legume paddocks. This profile, where 15N is enriched with depth, is common in natural and agro ecosystems where 15N-­‐
depleted plant litter is deposited on the soil surface (Högberg 1997). There were not significant differences between the depths for total N of the unfertilized treatment. Also, no significant differences in soil δ15N or %N were observed between the two treatments at any depth. Table 4.5. LS Means of soil δ15N species*depth interaction and % total N depth effect. 15
δ N (%0) % Total N (%) Treatment Depth (cm) Cycle 2 Cycle 11 Fertilized 0-­‐10 5.89 (0.14)e 6.76 (0.14)ac 0.123 (0.008)ab 10-­‐20 6.36 (0.14)abce 5.97 (0.18)bde 0.140 (0.010)a 20-­‐40 6.76 (0.14)ab 6.34 (0.15)abce 0.097 (0.009)b Unfertilized 0-­‐10 6.00 (0.14)cdef 6.07 (0.14)bef 0.134 (0.008)ab 10-­‐20 6.31 (0.14)abce 6.41 (0.15)abce 0.108 (0.009)ab 20-­‐40 6.16 (0.14)cdef 6.76 (0.18)acd 0.119 (0.010)ab Standard errors are given in parentheses. Values followed by the same lower case letters, comparing differences between treatment and depth, are not significantly different at P<0.05. 75 The differences in the soil δ15N and % total N were based on soil depth, not species or transect distance. This was expected since the experiment was not long enough to measure changes in soil characteristics in the total soil N pool. A 15N-­‐depleted surface layer, as found in the unfertilized treatment and the grass-­‐legume paddocks, is common of forest soils where mixing of 15N-­‐
depleted litter material is slow. Piccolo et al. (1996) found that surface soils of old pastures can be even more depleted in δ15N than younger pastures or forest soils due to increased N fixation by free-­‐living diazotrophs associated with pasture grasses. Agricultural fields that incorporate plant residue via ploughing often have a 15N inversion where the top layer of soil is more enriched in 15N than the lower layers (Högberg 1997). This type of inversion was observed in the fertilized signal grass and may have been the result of past ploughing. The cycle*depth interaction showed that the 15N-­‐depleted surface layer was less pronounce in cycle 11 then in cycle 2. 4.3.2 Litter total N and δ15N natural abundance 4.3.2.1 Grass-­legume paddocks Litter δ15N values ranged from 5.61‰ to -­‐1.15‰. Cycle and species by point were significant for litter δ15N (Table 4.6). The total N in the litter ranged from 2.115% to 0.299%. All the effects tested for % total N except for cycle by point and cycle by species by point were significant at P=0.05 error rate in a type III test of fixed effects. Table 4.6. Type III variance analysis of litter showing δ15N and % total N. 15
δ N Effect Num DF Den DF F Value Cycle 2 162 18.88* Species 3 162 1.32 Point 4 162 1.86 Cycle*Species 6 162 1.35 Cycle*Point 8 162 1.33 Species*Point 12 162 1.93* Cycle*Species*Point 24 162 1.16 *indicates values significant at P=0.05 Pr > F <.0001 0.2707 0.1202 0.24 0.2302 0.0347 0.2912 % Total N F Value 80.94* 62.99* 10.76* 12.1* 1.57 1.01 0.88 Pr > F <.0001 <.0001 <.0001 <.0001 0.1362 0.4347 0.6233 76 The data suggest spatial and temporal variability of % total N in litter. Both surface and subsurface litter represent a relatively labile source of organic material. Litter consists of newly fallen and slightly decomposed plant material, still containing distinguishable plant parts. C11 had the highest total N content in the litter with an estimate of 1.599% in gliricidia, while C5 had less at 1.014% in sabiá and C7 had the lowest level at 0.825% in gliricidia (Table 4.7). These differences suggest that the quality of litter changed seasonally because C5 was at the end of the wet season, C11 was during the wet season and C7 was during the dry season. Yavitt et al. (2004) found a similar trend in a forest in Panama where foliar tree litter had higher N concentrations during the wet season and lower N concentrations during the dry season. The δ15N of the litter also changed over the cycles, with C5 (0.94‰) and C7 (1.11‰) being significantly depleted in δ15N compared to C11 (2.52‰). An explanation for this, suggested by Garten et al. (2011), was nitrate leached from litter during heavy rainfall caused the δ15N of the litter to increase because isotopically depleted nitrate-­‐N is leached out. Table 4.7. LS means of legume cycle*species interaction for % total N of litter in four legume-­grass paddocks. Treatment Cycle % Total N Gliricidia 5 0.990 (0.048)bc 7 0.825 (0.050)bcd 11 1.599 (0.054)a Leucena 5 0.868 (0.052)bcd 7 0.697 (0.048)d 11 0.779 (0.054)bcd Mororó 5 0.670 (0.059)de 7 0.460 (0.048)e 11 0.771 (0.050)cd Sabiá 5 1.014 (0.048)b 7 0.752 (0.048)d 11 1.416 (0.053)a Standard errors are given in parentheses. Values followed by the same lower case letters, comparing differences between treatment and cycle, are not significantly different at P<0.05. Species by point interaction was significant for δ15N of litter (Table 4.8). Litter in the leucena paddocks was more enriched in δ15N closer to the legume, with δ15N values falling towards P5. Sabiá showed the opposite trend with P1 having a significantly depleted δ15N compared to P2-­‐P5. Differences between the litter changed with distance from the legume row. At P1 leucena litter was significantly more enriched in δ15N than that of sabiá whereas in P3 and P4 leucena and 77 mororó litter showed depleted δ15N compared to gliricidia and sabiá. By P5 no significant differences in litter were seen between any of the legume plots. Table 4.8. LS means of δ15N (‰) of litter in four legume-­grass paddocks. Point Species Gliricidia Leucena Mororó Sabiá 1 1.34 (0.26)Aab 1.70 (0.27)Aa 1.42 (0.23)Aab 0.97 (0.17) Bb 2 1.16 (0.26)Aa 1.25 (0.27)Aba 1.04 (0.23)Aa 1.45 (0.17)Aba 3 1.49 (0.26)Aa 0.71 (0.27)Bb 0.73 (0.23)Ab 1.51 (0.17)Aa 4 1.64 (0.26)Aa 0.57 (0.27)Ba 0.66 (0.23)Aa 1.47 (0.17)Aa 5 1.56 (0.26)Aa 0.72 (0.27)Ba 0.71 (0.23)Aa 1.42 (0.17)Aba Standard errors are given in parentheses. Values followed by the same upper case letters, comparing differences between points for each species, are not significantly different at P<0.05. Values followed by the same lower case letters, comparing differences between species for each point, are not significantly different at P<0.05. 4.3.2.2 Fertilized and unfertilized signal grass Total N values for the fertilized and unfertilized signal grass litter ranged from 0.299% to 0.832%. A variance analysis indicated that cycle was the only significant effect (Table 4.9). The litter δ15N values ranged from -­‐0.68‰ to 1.38‰ and cycle was the only significant effect. Table 4.9. Variance analysis of δ15N and total N of fertilized and unfertilized signal grass litter. 15
δ N % Total N Effect Num DF Den DF F Value Pr > F F Value Pr > F cycle 2 17 7.9* 0.0038 10.5* 0.0011 treatment 1 17 0.71 0.4104 2.69 0.1196 cycle*treatment 2 17 1.02 0.3802 0.37 0.6953 * indicates significance at P>0.05 The seasonality of the signal grass followed the same trend as in the legume plots (Table 4.10). The δ15N of the litter was significantly less depleted in C11 then in C5 and C7. The % total N was highest in C11 and C5 and significantly lower in C7. 78 Table 4.10. LS means of litter δ15N (‰) and total N (%) for fertilized and unfertilized signal grass over 3 cycles. 15
Cycle δ N (‰) % Total N 5 0.16 (0.18)b 0.623 (0.036)a 7 0.22 (0.18)b 0.456 (0.036)b 11 1.09 (0.19)a 0.690 (0.039)a Standard errors are given in parentheses. Values followed by the same lower case letters, comparing differences between cycles for each variable, are not significantly different at P<0.05. 4.3.3 Legume total N and δ15N natural abundance Legume δ15N ranged between -­‐0.61‰ in leucena to 3.20‰ in mororó with corresponding % total N values of 4.9% and 1.9%. A variance analysis showed that species and cycle*species were significant effects for both δ15N and % total N (Table 4.11). Table 4.11. Variance analysis of δ15N and total N for 4 legumes. Source of Variation Num DF Cycle 2 Species 3 Cycle*Species 6 * indicates significance at P>0.05 Den DF 5 9 13 15
δ N F Value 1.02 48.16* 4.44* Pr>F 0.4238 <0.0001 0.0116 % Total N F Value 0.36 224.55* 29.10* Pr>F 0.7155 <0.0001 <0.0001 Mean δ15N for gliricidia was 1.19 ± 0.660‰ and for leucena was -­‐0.36 ± 0.777‰. The average for mororó was 3.11 ± 0.346‰ and for sabiá was 1.69± 0.719‰ (Figure 4.1). The values for leucena are similar to the mean of -­‐0.34‰ compiled from studies across Australia and Indonesia by Boddey et al. (2000) and Unkovich et al. (2008). Values for gliricidia and sabiá were higher than those cited in the literature, specifically -­‐1.28‰ and -­‐1.24‰, respectively (Boddey et al. 2000; Bueno dos Reis Jr. et al. 2010). Values for δ15N of mororó were much lower in the current study than those found (9.03 ± 1.18‰) in Caatinga sites around the town of Caruaru (Freitas et al. 2010). Teixeira et al. (2006) also found higher δ15N for mororó of 11.4‰ in the wet season and 13.2‰ in the dry season. Both these studies used wild mororó as a reference species. 79 Figure 4.1. Box chart showing mean δ15N (%0) of legume species when grown in paddocks with signal grass. Mororó was more enriched in δ15N in all cycles compared to the other species. In C7 all of the δ15N values were significantly different (P=0.05). For gliricidia and mororó, no differences were seen between the cycles, however for leucena a significant difference was seen between C5 and C11 and for sabiá between C5 and C7 (Table 4.12). Table 4.12. LSD of δ15N (%0) values of four legume trees over three cycles. Cycle Gliricidia Leucena Mororó Sabiá 5 1.22 (0.35)Ba 0.53 (0.27)Ba 3.14 (0.15)Aa 1.32(0.36)Bb 7 0.95 (0.35)Ca -­‐0.61 (0.23)Dab 3.29 (0.15)Aa 2.20 (0.36)Ba 11 1.48 (0.40)Aa -­‐0.96 (0.27)Bb 2.70 (0.21)Aa 1.51 (0.38)Aab Standard errors are given in parentheses. Values followed by the same upper case letters, comparing differences between species for each cycle, are not significantly different at P<0.05. Values followed by the same lower case letters, comparing differences between cycles for each species, are not significantly different at P<0.05. The % total N of the four species differed significantly with mororó and sabiá having a lower %N in all cycles than the gliricidia and leucena. Differences between cycles were not seen for gliricidia or mororó, however leucena and sabiá had significantly less total N in C5 (Table 4.13). 80 Table 4.13. LSD of % total N values of four legume trees over three cycles for cycle*species interaction. Cycle Gliricidia Leucena Mororó Sabiá 5 4.047 (0.081)Ba 4.931 (0.940)Aa 1.943 (0.081)Ca 2.191 (0.081)Cb 7 3.864 (0.101)Aa 4.224 (0.101)Ab 2.028 (0.101)Ca 3.005 (0.101)Ba 11 3.679 (0.088)Ba 4.061 (0.088)Ab 2.111 (0.108)Ca 3.095 (0.088)Ba Standard errors are given in parentheses. Values followed by the same upper case letters, comparing differences between species for each cycle, are not significantly different at P<0.05. Values followed by the same lower case letters, comparing differences between cycles for each species, are not significantly different at P<0.05. 4.3.4 Grass total N and δ15N natural abundance 4.3.4.1 Grass-­legume paddocks A Type III variance analysis showed that all sources of variation were significant for δ15N of the grass while only species, point, cycle*species and species*point were significant for % total N (Table 4.14). Table 4.14. Type III variance analysis of δ15N and total N of grass in four legume-­grass treatments over three cycles and five points. 15
δ N % Total N Source of Variation Num DF Den DF F Value* Pr>F F Value* Pr>F Cycle 2 6 12.56* 0.0072 4.85 Species 3 9 36.23* <.0001 21.39* Point 4 12 11.02* 0.0005 9.75* Cycle*Species 6 125 9.68* <.0001 2.61* Cycle*Point 8 125 3.22* 0.0023 0.58 Species*Point 12 125 3.83* <.0001 2.82* Cycle*Species*Point 24 125 3.83* <.0001 1.02 * indicates significance at P>0.05 0.0558 0.0002 0.0009 0.0203 0.7891 0.0019 0.444 The δ15N of the signal grass ranged from 5.87‰ for sabia in P1 to 0.61‰ in mororó P5. In general δ15N decreased from P1 to P5 in all legume paddocks (Table 4.15). Significant differences were not seen between cycles for any legume and point combination. Yoneyama et al. (1997) examined neighbouring plants to sugarcane plantations in a number of states in Brazil and found that Brachiaria species had a δ15N in the range of 5.2‰ to 1.2‰. This range is similar to that found in the current study. 81 Table 4.15. LS means of δ15N (%0) of pasture grass in four grass-­legume treatments over 3 cycles and five transect points. Species Cycle Point 1 2 3 4 5 5 3.42 (0.37)ABab 3.40 (0.10)ABab 2.99 (0.21)ABabc 2.61 (0.21)Babcd 2.59 (0.27)Ba 7 3.27 (0.32)ABab 3.16 (0.10)ABabc 3.17 (0.25)ABabc 2.91 (0.24)ABabcd 2.65 (0.27)Ba 11 2.90 (0.45)ABab 3.40 (0.10)ABab 4.22 (0.21)Aa 4.28 (0.21)Aa 3.41 (0.27)ABa 5 3.06 (0.37)Aab 2.38 (0.10)Abc 2.16 (0.25)Acd 1.90 (0.21)Acd 1.98 (0.31)Aa Leucena 7 3.00 (0.32)Aab 2.19 (0.10)Abc 2.35 (0.21)Acd 1.82 (0.21)Ad 1.92 (0.27)Aa 11 2.94 (0.31)Aab 2.39 (0.10)Abc 2.68 (0.21)Abcd 2.20 (0.24)Aabcd 2.40 (0.27)Aa 5 2.98 (0.37)ABab 2.62 (0.12)ABbc 2.20 (0.21)ABcd 2.35 (0.24)ABbcd 1.56 (0.27)Ba Mororó 7 3.87 (0.37)Aab 2.15 (0.12)ABbc 1.44 (0.25)Bd 1.77 (0.21)Bd 1.40 (0.27)Ba 11 2.86 (0.32)ABab 2.01 (0.10)ABc 2.76 (0.21)ABbcd 2.23 (0.21)ABbcd 2.45A (0.27)Ba 5 2.78 (0.37)ABCb 3.40 (0.14)ABCab 2.93 (0.21)ABCabcd 2.23 (0.21)Cbcd 2.34 (0.27)BCa Sabiá 7 3.92 (0.37)ABCab 4.19 (0.10)ABCa 3.94 (0.21)ABCab 3.55 (0.21)ABCabc 2.90 (0.38)ABCa 11 4.56 (0.45)Aa 4.21 (0.12)ABCa 4.43 (0.25)ABa 3.95 (0.24)ABCab Standard errors are given in parentheses. Values followed by the same upper case letters, comparing differences between species for each cycle by point, are not significantly different at P<0.05. Values followed by the same lower case letters, comparing differences between point for each species by cycle, are not significantly different at P<0.05. Gliricidia The δ15N of the signal grass in the paddocks had increased with proximity to the legume hedgerows, particularly from the large legumes – gliricidia and sabiá. This was not in agreement with the data reported by Sierra and Nygren (2006) who found no correlation between δ15N of Dichanthium aristatum and distance from legume tree rows. However, Daudin and Sierra (2008), using the same experiment, found that the δ15N of the grass decreased with distance from legume rows before the trees were pruned. After the pruning, the δ15N of the grass increased continuously with distance from the legume row. They suggest that pruning causes rapid decomposition of tree nodules and roots, which have a higher δ15N then root exudates, causing an increase in δ15N in grass in areas with the highest tree-­‐root density (Daudin and Sierra 2008). In the current study, grazing cattle may have acted as “pruning” agents each cycle, causing the δ15N of the grass closest to the legume rows to increase more than that further from the trees. The % total N of the signal grass ranged from 2.564% for gliricidia P1 to 0.778% in mororó P3. The % total N of the grass increased from C5 to C11 for all species (Table 4.16). Leucena and mororó had significantly less % total N then gliricidia and sabiá. 82 Table 4.16. LS Means of % total N of pasture grass in species*cycle interaction in four legume paddocks. Species Cycle 5 7 11 Gliricidia 1.852(0.192)Aa 1.940 (0.202)Aa 2.374 (0.222)Aa Leucena 1.143 (0.073)Aab 1.207 (0.073)Ab 1.318 (0.073)Aab Mororó 1.097 (0.045)ABb 1.043 (0.044)Bb 1.212 (0.044)Ab Sabiá 2.008 (0.222)Bab 2.028 (0.225)ABa 2.544 (0.244)Aab Standard errors are given in parentheses. Values followed by the same upper case letters, comparing differences between cycles for each species, are not significantly different at P<0.05. Values followed by the same lower case letters, comparing differences between species for each cycle, are not significantly different at P<0.05. In general % total N in litter decreased from P1 to P5 for gliricidia and sabiá and remained constant across the transects for leucena and mororó (Table 4.17). Table 4.17. LS Means of % total N of pasture grass in species*point interaction in four grass-­legume paddocks. Species Point 1 2 3 4 5 Gliricidia 2.592 (0.217)Aa 1.963 (0.113)Aab 2.195 (0.134)Aab 1.690 (0.137)Aab 1.836 (0.418)Ab Leucena 1.271 (0.218)Ba 1.245 (0.113)Ba 1.162 (0.134)BCa 1.363 (0,137)ABa 1.072 (0.440)Aa Mororó 1.220 (0.209)Ba 1.142 (0.117)Bab 1.066 (0.127)Cab 1.123 (0.137)Bab 1.036 (0.418)Ab Sabiá 2.946 (0.256)Aa 2.688 (0.129)Aab 1.848 (0.140)ABb 1.736 (0.137)Ab 1.747 (0.480)Ab Standard errors are given in parentheses. Values followed by the same upper case letters, comparing differences between species for each point, are not significantly different at P<0.05. Values followed by the same lower case letters, comparing differences between points for each species, are not significantly different at P<0.05. Grass % total N was higher closer to the trees and decreased with distance from the legume rows. This was also reported by Dulormne et al. (2003) in a long-­‐term study of silvopastoral systems in Guadaloupe. They suggested that it may be due to higher shoot N/root N ratio in grass under trees due to shading, which increased N mineralization in shaded soils (Dulormne et al. 2003). 4.3.4.2 Fertilized and unfertilized signal grass There were no differences in %N and δ15N for fertilized and unfertilized signal grass. Average percent N was 1.201 ± 0.5852% and 15N natural abundance was 2.45 ± 1.440‰. This lack of difference between the two control treatments may have been due to not enough distance between the legume plots and the control plots. Sierra and Nygren (2006) found that fine tree 83 roots caused a lowering of δ15N in control plots because the plots were not sufficiently separated to be free of tree roots, and this may have occurred in the current study. 4.3.5 Percent nitrogen derived from the atmosphere 4.3.5.1 Percent nitrogen from fixation in legumes Legume percent nitrogen derived from the atmosphere (%Ndfa) was determined using Equation 4.2 with a B-­‐value of -­‐1.28‰ and -­‐0.34‰ for gliricidia and leucena, respectively, taken from Unkovich et al. 2008. The B-­‐value for sabiá was -­‐1.24‰ from a study by Buenos dos Reis et al. (2010). No literature B-­‐value for mororó was found so a value of 0 was assigned (Unkovich et al. 2008). The reference value used was the highest value of the mororó in the field study. The value was 3.65‰ and was similar to the mean value of 4.5‰ reported for agroforestry experiments in South America (Boddey et al. 2000). Högberg (1997) suggests that the reference value should be at least 5‰ different then B-­‐values to gain good estimations of %Ndfa. None of the values in this study meets this criterion, although gliricidia and leucena are very close at 4.93‰ and 4.89‰. Percent N derived from fixation ranged from 10% in mororó to 100% in leucena (Table 4.18). Average values were low for gliricidia (47%) mororó (14%) and sabiá (40%) and were very high for leucena (100%). The very low B-­‐values in the literature for gliricidia and sabiá would have affected these estimation values. Because the mororó value was used for a reference, the %Ndfa was expected to be low. Table 4.18. Percent Ndfa of four legumes over 3 cycles in a silvopastoral system planted with signal grass. Cycle Gliricidia Leucena Mororó Sabiá 5 49.3 (6.0)ABa 78.1 (7.0)Ab 14.1 (6.0)Ca 47.6 (6.0)Ba 7 54.8 (6.0)Ba 100* (6.0)Aab 9.9 (6.0)Ca 29.7 (6.0)Cb 11 41.4 (7.3)Ba 100* (7.3)Aa 27.1 (8.9)Ba 40.4 (7.3)Bab Standard errors are given in parentheses. Values followed by the same upper case letters, comparing differences between species for each cycle, are not significantly different at P<0.05. Values followed by the same lower case letters, comparing differences between cycles for each species, are not significantly different at P<0.05. *designated 100% although using Equation 2.2 would generate a physiologically impossible estimate of %Ndfa > 0% 84 4.3.5.2 Percent nitrogen from fixation in grass For the grass, reference values were taken from the greenhouse experiment and the B-­‐value of the associated legume was used (Sierra and Nygren 2006). The percent N fixed in the grass of the gliricidia and sabiá paddocks was significantly lower than that of the leucena and mororó (Table 4.19). Table 4.19. Percent Ndfa of grass in legume paddocks. Grass Paddock Gliricidia Leucena Mororó Estimate 59.6 (1.24)b 73.6 (1.24)a 76.4 (1.24)a Sabiá 58.2 (1.24)b Standard errors are given in parentheses. Values followed by the same lower case letters, comparing differences between species, are not significantly different at P<0.05. No differences were seen between transect points for gliricidia, leucena or mororó (Table 4.20). The %Ndfa was significantly lower in P1-­‐P3 than P4 and P5 for the grass in the sabiá paddocks. The differences between legume paddocks seen in Table 4.19 were also apparent when looking at the paddock transects. Table 4.20. Percent Ndfa of grass in legume paddocks by transect point. Point Treatment Gliricida Leucena Mororó Sabiá 1 60.2 (2.96)Aab 68.1 (2.96)Aa 67.5 (2.96)Aa 52.2 (2.96)Bb 2 56.2 (2.10)Ab 74.8 (2.10)Aa 77.8 (2.10)Aa 50.5 (2.10)Bb 3 57.4 (2.89)Ab 71.4 (2.89)Aa 79.0 (2.89)Aa 56.0 (2.89)Bb 4 61.3 (2.92)Ab 79.4 (2.92)Aa 77.0 (2.92)Aa 60.7 (2.92)Ab 5 63.0 (3.17)Ab 74.5 (3.17)Aab 80.5 (3.17)Aa 71.4 (3.17)Aab Standard errors are given in parentheses. Values followed by the same upper case letters, comparing differences between species for each point, are not significantly different at P<0.05. Values followed by the same lower case letters, comparing differences between points for each species, are not significantly different at P<0.05. The above results suggest that large amounts of N were being transferred from legume shrubs to the signal grass in this experiment. However, other research has provided evidence of diazotrophic association with pasture grasses. Boddey and Victoria (1986) suggested that Brachiaria grasses can obtain between 30-­‐40% of their nitrogen from endophytic associations. 85 This is further indicated by the lack of a significant difference between the δ15N of the legume plots versus the control plots (fertilized and unfertilized signal grass plots). However, Sierra and Nygren (2006) suggest that this could also be explained by the existence of legume fine roots throughout the entire experiment. In addition, herbaceous legumes from the region were present in all the paddocks. These spontaneous occurrences may have further confounded the δ15N of the grass. 4.4 Conclusions The components of the nitrogen cycle in a grazed silvopastoral system are complex. There was generally a depletion of δ15N with distance from the legume row in the soil, litter and grass of the system. This was not expected as δ15N depleted above and below ground litter from legume shrubs would be expected to have a spatial distribution. A further complexity in the current study was the grazing cattle. The cattle may have acted to prune legume shrubs, causing decomposition of root nodules enriched with δ15N, and redistributing δ15N depleted legume foliage throughout the plots as urine and feces. Nitrogen fixation was greater in the leucena and gliricidia then in the mororó and sabiá. However, the grass in the mororó and leucena paddocks had more fixed N then in the gliricidia and sabiá. This disparity is likely the result of shading and moisture competition being greater in the paddocks with the larger legumes (gliricidia and sabiá) where grass and spontaneous herbaceous legumes grew better throughout. 4.5 References Bergersen, F.J., G.L. Turner, N. Amarger, F. Mariotti, and A. Mariotti. 1986. Strain of Rhizobium lupini determines natural abundance of 15N in the root nodules of Lupinus spp. Soil Biology and Biochemistry 18: 97-­‐101. Boddey, R.M., M.B. Peoples, B. Palmer, and P.J. Dart. 2000. 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1993. Thomas, R.J., and N.M. Asakawa. 1993. Decomposition of leaf litter from tropical forage grasses and legumes. Soil Biology and Biochemistry 25(10): 1351-­‐1361. Trannin, W.S., S. Urquiaga, G. Guerra, J. Ibijbijen, and G. Cadisch. 2000. Interspecies competition and N transfer in a tropical grass-­‐legume mixture. Biology and Fertility of Soils 32: 441-­‐448. Turner, G.L., F.J. Bergersen, and H. Tantala. 1983. Natural enrichment of 15N during decomposition of plant material in soil. Soil Biology and Biochemistry 15: 495-­‐497. Unkovich, D. Herridge, M. Peoples, G. Cadish, B. Boddey, and K. Giller. 2008. Measuring plant-­‐
associated nitrogen fixation in agricultural systems. ACIAR Monograph No. 136, 258 pg. Van Kessel, C., R.E. Farrel, J.P. Roskoski, and K.M. Keane. 1994. Recycling of the naturally-­‐
occurring 15N in an established stand of Leucaena leucocephala. Soil Biology and Biochemistry 26: 757-­‐762. Wanek, W., and S.K. Arndt. 2002. Difference in δ15N signature between nodulated roots and shoots of soybean is indicative of the contribution of symbiotic N2 fixation to plant N. Journal of Experimental Botany 53(371): 1109-­‐1118. Yavitt, J.B., S.J. Wright, and R.K. Wieder. 2004. Seasonal drought and dry-­‐season irrigation influence leaf-­‐litter nutrients and soil enzymes in a moist, lowland forest in Panama. Austral Ecology 29: 177-­‐188. Yoneyama, T., K. Fujita, T, Yoshida, T. Matsumoto, and I. Kambayashi. 1986. Variation in natural abundance of 15N among plant parts and in 15N/14N fractionation during N2 fixation in the legumes rhizobia symbiotic system. Plant and Cell Physiology 27: 791-­‐799. Yoneyama, T., T. Muraoka, T.H. Kim, E.V. Dacanay, and Y. Nakanishi. 1997. The natural 15N abundance of sugarcane and neighbouring plants in Brazil, the Philippines and Miyako (Japan). Plant and Soil 189: 239-­‐244. 89 Zuberer D.A. 2005. “Biological Dinitrogen Fixation: Introduction and Nonsymbiotic” In: D.M. Sylvia, P.G. Hartel, J.J. Fuhrmann and D.A. Zuberer Principles and Application of Soil Microbiology: Second Edition pp. 373-­‐404. Upper Saddle River, NJ: Pearson Education Inc. 90 Chapter 5 Conclusions and Recommendations for Further Study 5.1 Conclusions and Recommendations for Further Study With growing population around the world and interest in environmental preservation on the rise, increasing agricultural productivity in an environmental and economically sensitive manner is becoming more important. Silvopastoral systems are seen as a management approach for increasing the environmental sustainability and economic benefits of beef production. Silvopastoral systems that include leguminous shrubs or trees into grass pasture have multiple secondary benefits including marketable products, greater forage in dry seasons, shade for cattle, and an increased nitrogen economy. Because of these benefits, silvopastoral systems are gaining renewed interest throughout the tropics. The research outlined in this report evaluated the growth and N interactions in a silvopastoral system of Northeastern Brazil – from a field and a greenhouse perspective. The legumes grown in the greenhouse were significantly younger than those in the field, causing a potential disparity in δ15N. Also, complete defoliation of the greenhouse legumes at 20 weeks after germination was problematic, with none of the legumes growing well afterwards. While the complexities of working under field conditions in a grazed pasture created many challenges and complexities to the data, a number of items were clear. The legumes grown in the field provided two distinct cases: small trees that did not grow well under consistent defoliation (L. leucocephala and B. cheilantha) and large trees that grew very well and were less palatable to the cattle (G. sepium and M. caeselpiinfolia). The differences in the grass pasture (growth, δ15N, botanical composition) were based on legume size more than on legume species. Recommendations for improvements upon the current study would include: •
Allowing for a greater length of time for the greenhouse study to determine more accurate B values for the legumes •
Observing animal behaviour and legume palatability in the plots •
Measuring nodulation of the legumes, particularly B. cheilantha to ascertain its usability as a reference plant for natural abundance δ15N measurements 92 Further studies that could build on these findings would include: •
A study on larger paddock sizes where the cattle can be grazed for longer periods of time – this would allow for the added component of animal nutrition, where feces and urine could be analyzed to determine the amount of legume being consumed by the animals •
A study that measures δ15N of inorganic N in soil would allow for greater accuracy in %Ndfa measurements •
Measuring δ15N in a similar experiment where leguminous weeds have not invaded the B. decumbens to obtain a better determination of transfer of fixed N from legumes to grass 93 Appendix A A Review of Biological Nitrogen Fixation in the Context of The Nitrogen Cycle 6.1 The Nitrogen Cycle Nitrogen is an essential macronutrient for plant growth and is often the limiting factor to growth in terrestrial ecosystems (Brady and Weil 2002). It is occurs mainly as an organic form in soil, as anionic forms in plants, and as diatomic forms in the atmosphere (Brady and Weil 2002). The most abundant form of N is dinitrogen gas (N2), which comprises approximately 78% of the atmosphere. Dinitrogen cannot be used directly by most plants but must be transformed into inorganic forms to be usable for growth and production of proteins (Robertson and Groffman 2007). The terrestrial N cycle is a complicated system of losses, additions, and transformations. The main processes by which N is transformed are: mineralization and immobilization, which change organic N into inorganic N and vice versa, and nitrification and denitrification, which is the oxidation and reduction of inorganic N by microbial activity (Robertson and Groffman 2007). The process by which N2 is converted to plant-­‐usable N is called nitrogen fixation, and when this is preformed in natural environments by nitrogen-­‐fixing bacteria it is called biological nitrogen fixation (BNF). The following sections expand on these processes. 6.1.1Mineralization and immobilization The process by which organic N is transformed into inorganic N (mineralization) and the opposite process by which inorganic N is converted into organic N (immobilization) are two important processes of the N cycle. Mineralization allows complex organic N compounds to be converted into simpler forms of N that are usable for plants and microbes. It occurs when a wide array of microbes (such as fungi, aerobes, anaerobes or bacteria) which consume biomass for use as energy release excess N, making it available for plants and other microbes (Robertson and Groffman 2007). Immobilization occurs when the detritus material is incorporated into the microbes and transformed into a more complex form that is not plant available. Mineralization and immobilization occur simultaneously in the soil because decomposable materials, microbes and the soil environment are spatially variable and very heterogeneous. Net N Mineralization (NNM) is the balance between the gross N mineralized by microorganisms and the opposing amount immobilized (Robertson and Groffman 2007). 95 Brady and Weil (2002) suggest that 1.5-­‐3.5% of the organic N in soil mineralizes annually. Soil temperature, soil water content, amount of detritus and quality of detritus control the rate of mineralization. High temperatures and moderate soil water contents increase the rate of activities of the soil microbes and therefore increase mineralization and immobilization processes. The most important factor affecting the rate is the amount and quality of soil organic matter. If the detritus material is low in N, the microbes must scavenge more N from other sources and no N is released, therefore increasing immobilization. But if the organic material is high in N, some is released in a mineralized form. A general rule is that materials with a C:N ratio of >25:1 stimulate immobilization whereas a C:N of <25:1 stimulates mineralization (Robertson and Groffman 2007). 6.1.2 Nitrification and denitrification Nitrification is the oxidation of ammonium (NH4+) to NO2-­‐ and then to NO3-­‐ and is usually performed by autotrophic nitrifying bacteria. These autotrophs obtain energy by oxidizing ammonium ions instead of from organic materials (Brady and Weil 2002). The nitrification reaction occurs in two steps where the first step (NH4+ to NO2-­‐) is performed by Nitrosomonas bacteria. The second step (NO2-­‐ to NO3-­‐), which occurs immediately after the first step, is performed by a group of autotrophs called Nitrobacter (Robertson and Groffman 2007). The main factors affecting nitrification rate is the supply of ammonium ions in the soil. If N mineralization rates are low, ammonium supply in the soil is low and nitrification rates will be low. Bare soil fallows and soil disturbances such as tillage, fire, clear-­‐cutting or fertilization act to increase NH4+ availability and will therefore increase nitrification (Brady and Weil 2002). Since all known nitrifying bacteria are obligate aerobes, oxygen levels also affect nitrification. The bacteria perform best in well drained soils where approximately 60% of pores space is water filled and the temperature is 20-­‐30°C. Soils with high amounts of Ca2+ and Mg2+ also favour nitrification (Myrold 2005). Nitrification occurs very rapidly and therefore nitrate is usually the main inorganic form of N in the soil. Many environmental conditions cause flushes of nitrate such as spring thawing of frozen 96 soil, tillage, and rainfalls after periods of drought (Brady and Weil 2002). These conditions have long-­‐term negative effects because nitrification can contributes to soil acidity by producing H+ ions (Brady and Weil 2002). Also, because nitrate is an anion it readily leaches from the soil and causes contamination problems in groundwater and surface water systems. Denitrification is the reduction of soil nitrate to N gases such as NO, N2O and N2. It is carried out by anaerobic bacteria, which can be either autotrophic or heterotrophic, using organic materials to generate energy. The process requires low oxygen conditions at the microsites in the soil (Myrold 2005). Denitrification can occur between 5 and 50°C, while times of heavy rainfall where soils are near saturation tend to favour it (Robertson and Groffman 2007). 6.1.3 Biological nitrogen fixation Considered to be second only to photosynthesis as the most important biochemical reaction for life on earth, biological nitrogen fixation (BNF) is of the utmost importance to terrestrial ecosystems (Brady and Weil 2002). This is the process by which microbes transform unreactive atmospheric N2 into plant usable forms of N. Since the triple N bond of the N2 is broken during fixation it is an energy intensive reaction. The microbes involved are prokaryotes, specifically certain species of bacteria, cyanobacteria and actinomycetes (Bottomley and Myrold 2007). These organisms can be free-­‐living or have symbiotic relationships with other organisms. ‘Diazotroph’ is the term for an organism that uses N2 as its sole source of N. The process by which N2 is fixed always involves the enzyme complex nitrogenase. It is made up of the proteins dinitrogenase and nitrogenase reductase and different forms need one of molybdenum, vanadium or iron as the element on the catalytic sites (Bottomley and Myrold 2007). Two molecules of ATP are necessary to transfer one electron from nitrogenase reductase to dinitrogenase. In order for one molecule of N2 to be fixed, 16 ATP molecules are needed which provide 6 electrons. This is because the process is both energetically expensive and inefficient, with approximately 25% of the energy lost in the reduction of 2H+ to H2 (Brady and Weil 2002). The process (Figure X) starts with the protein dinitrogen reductase accepting an electron from ferredoxin, flavodoxin or a similar low-­‐redox donor. This allows 2 MgATP to be bound to the 97 enzyme. Using the ATP, one electron at a time is transferred to the dinitrogenase protein and the proteins form a complex which hydrolyzes the ATP to ADP+P, than dissociate (Zuberer 2005). The process is repeated approximately 6 times, until enough electrons have been collected by the dinitrogenase at which point a molecule of N2 is bound, reduced and released as ammonia (NH3+). This process can also reduce other small, triple bonded molecules such as acetylene (CH2) to ethylene (C2H4) (Bottomley and Myrold 2007). Figure 6.1. Process by which the nitrogenase complex converts N2 to NH3 (Zuberer 2005). Factors that affect nitrogenase activity include temperature and the availability of necessary elements of the process. Nitrogenase is temperature sensitive, acting only between 5 and 40°C. Most of the organisms that are responsible for this reaction are mesophiles and are not well adapted to extremes of temperature. Nitrogenase is also sensitive to irreversible denaturation by oxygen. Many diazotrophs have developed special mechanisms to protect themselves from this, such as thick cell walls, leghemoglobin production, heterocysts, and temporal separation between when O2 is produced and N2 fixation (Brady and Weil 2002). Mo, Fe, or Va and the presence of sufficient sources of ATP are also necessary for nitrogenase to be active (Bottomley and Myrold 2007). 98 The three main forms of N2-­‐fixing microbes are free-­‐living organisms, plant-­‐associative organisms and plant symbiotic organisms. Free-­‐living heterotrophs, including azotobacter and cyanobacteria, are thought to have limited N2-­‐fixing ability because they require labile C to be present to fix N (Bottomley and Myrold 2007). They have been shown to fix between <1 and 10 kg N ha-­‐1, but quantifying their fixation rates continues to be difficult (Bottomley and Myrold 2007). ‘Plant associative’ indicates species that live in the rhizosphere, intercellular spaces of the root cortex or in the phyllosphere, where secretions of organic C are high but there are no morphological or genetic interactions between the plant and the microbe (Bottomley and Myrold 2007). Sugar cane has been found to have an associative bacteria (Gluconacetobacter diazotrophicus), that can provide the plant with up to 60% of its N-­‐requirements (Urquiaga et al. 1992). Also, flooded areas where rice is grown are known to support a variety of associative diazotrophs, including the fern Azolla with its associated cyanobacteria Anabaena, which are able to provide 30-­‐50 kg N ha-­‐1 yr-­‐1 to the rice crop (Zuberer 2005). Though sugar cane and rice associated microbes provide more significant quantities of N for the crops, Zuberer (2005) suggests that generally between 5 and 30%, or 5 to 25 kg N ha-­‐1 yr-­‐1 of the N used by plants can be provided by plant associative N2 fixation. While this amount is relatively low in conventional row crop agriculture systems, it can play a significant role in N supply of grasslands and low-­‐
input agricultural systems. Symbiotic N2 fixing relationships account for 50% of the N used in agriculture (Bottomley and Myrold 2007). The relationships between N2-­‐fixing bacteria and a eukaryotic host are generally mutualistic, where the host gains usable forms of N for growth and development and the bacteria gains energy in the form of C complexes from the host (Bottomley and Myrold 2007). These relationships involve the creation of a special structure to house the microbe, called a nodule. The most common form of this relationship is between legumes and rhizobia bacteria. There are 5 stages by which rhizobia infect and establish themselves in legumes (Graham 2005). The first stage is the infection by which the bacteria penetrate the legume roots through a root hair or at a site of lateral root emergence. The bacteria attaches itself to the cell wall of the root 99 hair triggering a series of morphological responses in which the hair curls back upon itself and encloses the bacteria. In the second stage the rhizobia moves down the root hairs in an infection tube and branches, causing visible changes to the root due to growth of host cells in the root cortex and division of cortical cells. During stage three, cortical cell walls dissolve to allow rhizobia to be delivered into the nodule cell by endocytosis. Stage four occurs when rhizobia are released from the infection tube and enclosed within a peribacteroid membrane to become physically isolated from the host cell cytoplasm. Also, the nodule structure is formed and vascular strands from the plant extend into it, becoming the site of nutrient exchange. Finally, in stage five the symbiosome (which is the peribacteroid membrane enclosed bacterium) matures, limiting O2 and producing leghemoglobin, and begins to actively fix N2 (Graham 2005). The nodules take N2 and H2 from the air and respire CO2. The plant sends in photosynthates and the diazotrophs send out C-­‐N compounds to the plants such as ureides and basic amino acids. NH4+ is not directly transferred to the plant, but converted into compounds with low C:N for efficient transport (Bottomley and Myrold 2007; Graham 2005). Nodules can be determinate or indeterminate (Graham 2005). Determinate nodules are round and have no pronounced meristematic region. Examples of plants with determinate nodules are Glycine and Phaseolus species (Graham 2005). Indeterminate nodules have three distinct regions: an elongated meristematic region, an active N2 fixation region, and a region of senescence. The three areas can often be distinguished by colour (Graham 2005). Alfalfa, peas and clover are all plants that have indeterminate nodules. Several factors can affect the functioning of the symbiosis in legumes, including legume growth factors and symbiosome growth factors. Acidity can affect formation and activity of nodules because some strains of rhizobium are acid sensitive. Also, high acidity can cause Al and Mn toxicity problems for plants and deficiencies of Ca, P and Mo (Graham 2005). Temperature is also important for the plants and the bacteria, as both are mesophiles. Rhizobia bacteria do not growth well in extremes beyond 10-­‐37°C; the optimal temperature for N2-­‐fixation is at 25°C (Graham 2005). Soil fertility and mineral nutrition status of the plant have a significant affect on N2 fixation. Legumes often have a higher need for P because nodules are a P sink due to high ATP 100 requirements. Other important nutrients are Mo, which is necessary for nitrogenase, and Fe, which is needed for leghemoglobin production (Graham 2005). Salinity and alkalinity also tend to decrease N2-­‐fixation by limiting the growth of the plant. Alkalinity can limit the availability of Fe, Zn, Mn, and Bo (Graham 2005). 6.1.3.1 Amount of BNF in the global N budget There have been several estimates of the contributions of BNF to the global N budget (Boyer et al. 2004; Burns and Hardy 1975; Delwiche 1970; Galloway et al. 1995; Herridge et al. 2008; Smil 1999; Vitousek et al. 1997,). Delwiche (1970) reported 100 million tons as the global, annual amount of N2 fixed by BNF. Five years later, Burns and Hardy (1975) estimated 122 million tons of BNF, globally. Herridge et al. (2008) suggest that these estimates are necessarily poor due to an inability to estimate BNF in natural systems, where variability is very high and there is a lack of scientific literature. The most accurate information is available for field crops, which have been extensively studied and less accurate information exists for forage crops, where variability is higher (Cleveland et al. 1999; Herridge et al. 2008). Another problem concerning estimates of global BNF inputs is a lack of data on inputs from underground portions of leguminous plants – nodules and roots (Herridge et al. 2008; Unkovich et al. 2010). Herridge et al. (2008) created a new estimate for the global inputs of N by BNF in agricultural systems. To compensate for the lack of data on underground plant portions, Herridge et al. (2008) used a multiplication factor of two to account for underground portions of forage, pasture, and major crop legumes. The estimate for forage and fodder legumes is 25 million tons of N fixed annually (Herridge et al. 2008). This value is double that of an estimate made by Smil (1999), which Herridge et al. (2008) suggest is due to having disregarded the input of underground plant components. The estimate for major crops and oilseed legumes also differs significantly between the two studies. Smil (1999) suggests 10 million tons fixed annually whereas Herridge et al. (2008) suggests 21.5 million. The differences here are due to differences in the two authors’ estimates of the amount of N fixed by soybean and pea crops. The amount of N fixed by these crops differs widely between locations, for example in Brazil the percent nitrogen in a soybean plant that is derived from atmospheric N is approximately 80%, whereas in China and Japan this value can be as low as 50% (Herridge et al. 2008; Yoneyama et al. 2003). 101 6.2 References Brady N.C., and R.R. Weil. 2002. The Nature and Properties of Soils: 13th Edition. Pearson Education, Inc., Upper Saddle River, New Jersey. Bottomley P.J., and D.D. Myrold. 2007. “Biological N Inputs” In: E.A. 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