Conservation synthesis case study: Cusuco

Conservation synthesis case study:
Cusuco National Park, Honduras
Dr Peter Long
[email protected]
Lecture outline
-
Cusuco National Park introduction
Stakeholders, Key biodiversity features
Monitoring theory… BACI, ED etc.
Sampling design
Monitoring, Indicators, Management plan
Modelling
- species distribution models (with extensions)
- land cover change and scenarios
- ecosystem services
- Social science conservation interventions -WCPs
Cusuco National Park, Honduras
One of the few remaining areas of cloud forest
in Honduras.
Despite National Park status, illegal logging and
hunting threaten the persistence of the forest
ecosystem.
Local people…
- unaware of park regulations
- don’t benefit financially from park
Insufficient government resources to manage
the park, monitor biodiversity.
Honduras
Cusuco National Park
Biogeography
• Central America is a land bridge formed about 5m years ago.
• Laurasian taxa moved south, Gondwanan taxa moved north.
• Meso-America is a CI biodiversity hotspot
Quercus
Podocarpus
Pinus
http://www.biodiversityhotspots.org/xp/hotspots/mesoamerica/Pages/default.aspx
Opposums
Cusuco has incredible biodiversity
An incredibly complex landscape
• Cusuco National Park is in the Merendon mountains
• Elevation from 0m to 2200m
Major natural habitats
Broadleaf moist forest
(considerable changes
over elevation gradient)
Pine
Dwarf forest
(Bosque enano)
Modified habitats
Recently cleared forest
Bare soil
following landslides
Coffee
Diverse land-covers and a dynamic system
Pink - Soil
Yellow –
Guamil
(recent
2ndary
growth)
Turquoise - Pasture
Dark green – Broadleaf moist forest
Light green - Pine
Key features
• Baird’s tapir
• Bosque enano
• 7 species of park endemic
frogs
• Invertebrate assemblage
• Montane birds (goldencheeked warbler, quetzal etc).
• Overall functioning of the
system and provision of
ecosystem services such as
water flow, carbon storage,
erosion protection.
• Medicinal plants, orchids
Threats
• Livelihoods dependent on exploitation forest resources (firewood
collection, hunting mammals, exploitation or orchids)
• Persecution of snakes/bats etc).
• Agriculture (land cover change, fragmentation, pollution)
• Invasive species
• Climate change
Potential management actions
-
Monitor biodiversity, land cover, economic indicators
Demonstrate value of the park (ecosystem services)
Apply to GEF to resource park management
Consult local people, provide alternative incomes:
- eg. Coffee co-operative, ESAC+OpWall
- Communicate to all stakeholders
- Advocate on environmental policy to government:
result: the park is now staffed
Role of OpWall, a vNGO
Vicious circle
The vNGO model:
There is a management plan…
But it was written in 1994 and it’s not very good:
- Out of date concerning features, threats and actions
- Stakeholders weren’t consulted
- It lacks an aim, objectives, actions etc.
We’re writing a new one, but it’s a long process.
Spatial sampling framework
- 7 camps
- 25 sample routes (~3km)
- 152 sample sites
Monitoring methods
-
Habitat characteristics at sample sites
(Botany plots)
Dung beetle pitfall trapping
Jewel scarab beetle light traps
Herp sample route walks, (opportunistic search, pitfalls)
Bird point counts (mist netting)
Small mammal trapping
Bat mist netting
Large mammal sample route walks
Remote sensing and GIS
Textual analysis, interviews, questionnaires, focus groups
Biodiversity database
Park GIS
Landsat footprints
Pressure-state-response monitoring
Pressure indicators
• Population size of each settlement
• Number of households
• Hunting take in BA - estimated numbers of each species (anonymous)
• Infrastructure development (park cost-distance histogram)
• Fertiliser consumption
• Prevalence and/or distribution of Chytrid
• Numbers/distribution of invasive plants
State indicators
Remote sensing
• Land cover (disaggregated by village hinterlands)
• Forest fragmentation
Habitats
• Biomass (at sample sites)
• Number of dead trees (at sample sites)
• Volume of deadwood (at sample sites)
• Sapling density (at sample sites)
Water quality
• Biotic indicator in development
Ecosystem services
• Flow in streams
• Erosion hazard
• Carbon storage
Monitoring land cover change
…
Satellite
image
t1
t2
t3
Time
tn
Derive indicator
Landscape
Indicator
Trend
Eg.
Forest area
Time
t1
t2
t3
…
tn
Change detection (delta classification)
1987
1994
2000
2006
State indicators
Biodiversity
• Dung beetle community indicators (at sample sites)
• Relative abundance of reptiles – by guild (at transects)
• Relative abundance of amphibians – by guild (at transects)
• Relative abundance of small mammals - by 3 species (at transect level)
• Relative abundance of bat guilds – by guild (at nets)
• CPUE of large mammal signs (at transects)
• Population trends of several bird species, Distance-Occupancy (park)
-by guilds:
- large ground birds
- cavity nesters
- hummingbirds
- montane forest specialists
- lowland forest specialists
- birds of disturbed habitats/forest edges
Linkage between database and indicators
Survey
Eg. bird
point
counts
t1
…
t2
t3
Time
tn
Database
Query
Analysis
Indicator ± error
Biodiversity
Indicator
Trend
Eg.
Toucan
density
t1
t2
t3
…
Time
tn
Logic behind model-based monitoring
• Having designed an efficient monitoring programme and collected and
managed the data, you need to evaluate the data and make decisions about
implications for management.
• ANOVA and BACI designs
• Regression designs
Take care of themselves, because
significance of effects or trends is a
function of statistical power (sample size
and variability in the data)
• Reference-condition based monitoring designs
Harder. Need a different framework.
Ecological distance (dissimilarity)
Community composition
an example of an ED-based indicator
Species distribution models (tree fern)
Species distribution models as a monitoring tool
• Distribution modelling (and validation) is the process of
selecting a correct hypothesis: ie. parameter estimates
associated with environment.
• Even better if you simultaneously estimate
- detectability,
- occupancy of landscape units ~ environmental covariates
- density.
• The map is just one result, but not the only possible result.
• Distribution models can be coupled with RS monitoring data or
scenario data in order to model species distributions/population
size etc.
Response indicators
• Park budget
• Number of Park staff
• Money spent by OpWall in Honduras
• Official area of PA (core and buffer) according to Honduran government
• Number of tourist visits
• Media coverage
• Peer-reviewed publications
• Revenue per unit mass of coffee produced in the buffer zone
Lessons learned from the monitoring…
• Habitat structure, Birds and Dung beetles easy to do and informative
(Gardner 2008)
• Herps very important in Cusuco, but hard to monitor well
• Small mammals, bats and large mammal monitoring has been a nightmare
• Remote sensing also very useful
• Social indicators much harder than we though they would be.
What makes a good biodiversity indicator?
•
•
•
•
•
•
•
•
•
•
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Highly diversified taxonomically and ecologically
High ecological fidelity
Relatively sedentary
Species are endemic or locally/regionally differentiated
Taxonomically well-known
Well studied biology and ecology
Abundant and apparent
Present the majority of the time (Damped fluctuations)
Large samples easy to obtain in order to look at variation
Functional role in Ecosystem
Predictable, rapid and linear response to disturbance that can be
analysed
• Other species and ecosystem resources associated closely with the
indicator
Wildlife Conservation Products
Expediciones y Servicios Ambientales
de Cusuco (ESAC)
Wildlife Conservation Product scheme
for local shade-grown coffee
Investigation of other suitable crops
to be sold as wildlife conservation
products
Not Fairtrade.
Better in many ways.
Further reading
Elzinga CL, Salzer DW, Willoughby JW,
Gibbs JP (2001)
Monitoring plant and animal communities:
a handbook for field biologists. Blackwell
Clear section on
monitoring communities
and ecological dissimilarity
This book is very
good at explaining
how to actually
make many types
of ecological and
landscape models
Wainwright J, Mulligan M
(2004) Environmental
modelling: finding
simplicity in complexity.
Wiley
Strand, H., Höft, R., Strittholt, J., Miles, L.,
Horning, N., Fosnight, E., Turner, W., eds.
(2007). Sourcebook on Remote Sensing and
Biodiversity Indicators. Secretariat of the
Convention on Biological Diversity,
Montreal, Technical Series no. 32
Available from:
www.cbd.int/doc/publications/cbd-ts-32.pdf
How to use remote sensing to
develop indicators. Very good
case studies.
Further reading
Very good on methods
for community ecology
McCune B, Grace J, Urban DL (2002)
Analysis of ecological communities.
MJM software design
Why is it so hard to
get conservation
projects to work?
McShane TO, Wells MP
(2004) Getting
biodiversity conservation
projects to work.
Columbia University
Press
Social science techniques can
be complemented by remote
sensing, which is especially
good for detecting land-cover
change
Fox J, Rindfuss RR, Walsh SJ, Mishra V
(2003) People and the environment:
approaches for linking household and
community surveys to remote sensing
and GIS. Kluwer
References
Mesoamerica
* http://www.biodiversityhotspots.org/xp/hotspots/mesoamerica/Pages/default.aspx
Monitoring
Danielson F, Burgess ND, Balmford A et al. (2009) Local participation in nautral resource
monitoring: a characterisation of approaches. Conservation Biology 23: 31-42
*Gardner TA, Barlow J, Araujo IS et al. (2008) The cost-effectiveness of biodiversity surveys
in tropical forests. Ecology Letters 11: 139-150
Change detection
Coppin P, Jonckheere I, Nackaerts K, Muys B, Lambin E (2004) Digital change detection
methods in ecosystem monitoring: a review. International Journal of Remote Sensing 25:
1565-1596
Chytrid
Kolby JE, Padget-Flohr GE, Field R (2009) Amphibian chytrid fungus Batrachochytrium
dendrobatitdis in Cusuco National Park Honduras. Dieases of Aquatic Organisms
doi: 10.3354/dao02055