the Testing RICT predictions of expected values using an

Transcription

Testing RICT predictions
of expected values using an
independent RIVPACS model
and new RIVPACS test data
A Report to the
Environment Agency
J. Davy-Bowker
R.T. Clarke
November 2015
Research Contractor
This document was produced by the Freshwater Biological Association:
†
†
John Davy-Bowker and Ralph T. Clarke
†
The Freshwater Biological Association, River Laboratory, East Stoke, Wareham, Dorset,
BH20 6BB, United Kingdom.
Project Funders
This project was funded by the Environment Agency.
Disclaimer
Whilst this document is considered to represent the best available scientific information and expert
opinion available at the stage of completion of the report, it does not necessarily represent the final or
policy positions of the project funders or contractors.
Dissemination status
Unrestricted
Environment Agency Project Manager
Environment Agency’s project manager for this contract was:
John Murray-Bligh (EA)
FBA Project Manager
FBA’s project manager for this contract was:
John Davy-Bowker
FBA Project Code
S/0025/R
The Freshwater Biological Association
The Ferry Landing
Far Sawrey, Ambleside
Cumbria, LA22 0LP, United Kingdom
River Laboratory
East Stoke, Wareham
Dorset, BH20 6BB, United Kingdom
Web site: www.fba.org.uk
Email: [email protected]
Registered Charity No. 214440
Company Limited by Guarantee No. 263162, England
UKPRN No. 10018314
Registered Office: The Ferry Landing, Far Sawrey, Ambleside, Cumbria, LA22 0LP, United Kingdom
EXECUTIVE SUMMARY
Testing RICT predictions of expected values using an independent RIVPACS model and
new RIVPACS test data
Project funders: Environment Agency
Background to research
The environment agencies in the UK (the Environment Agency; Scottish Environment
Protection Agency; Natural Resources Wales and the Northern Ireland Environment Agency)
use the River Invertebrate Classification Tool (RICT) to classify the ecological quality of
rivers for Water Framework Directive compliance monitoring. The current system uses
RIVPACS observed (O) to expected (E) ratios (EQIs) of the two macroinvertebrate indices
WHPT NTAXA and WHPT ASPT.
Since the first launch of the RICT software a variety of research and development projects
on RIVPACS have been undertaken to further develop and enhance the models. Whilst not
all of these upgrades have been applied to the operational version of the RICT software,
many have and this has necessitated a series of software upgrades by SEPA appointed
programmers and SEPA in-house IT specialists.
It is now a fitting time to test the implementation of the various upgrades that have been
made by comparison to an independently coded version of the RIVPACS prediction model. It
is also appropriate to do this using new test data with a wide geographical spread of test
sites and range of environmental qualities. The derivation of new test data and the RICT
testing exercise are reported here.
Objectives of research
 To derive new RIVPACS/RICT test data for current (and future) RIVPACS/RICT testing
purposes.
 To test the current RICT software to see if its predictions of single season (Spring)
Expected values of the raw and reference quality-adjusted abundance-weighted WHPT
indices for the test sites match those of an independently constructed version of the same
RIVPACS IV prediction model and adjustment algorithms.
Key findings and recommendations
 Our independent calculation of each of the algorithm steps involved in derving RIVPACS
IV GB model predictions of the raw and adjusted Expected values of the WHPT indices
suggest that these are correctly coded and calculated within the RICT software (i.e. RICT
as of 13 March 2015). This is based on predictions of spring sample Expected values for
12 test sites.
 The RICT software correctly predicts the abundance-weighted WHPT indices based on
Taxonomic Level 2 data, but using the Composite families version of WHPT rather than
the Distinct families version. This should be made clear in the RICT software and manual,
and may need be rectified within RICT in due course.
 The RICT code to calculate the values of the numerous derived environmental variables
used in RICT predictions (notably Latitude, Longitude and mean and range of air
Temperature) agrees with our independent RIVPACS calculations and checks
 The RICT code to calculate probability of end-group agrees with our independent tests.
 The RICT code using the probabilities of end-group and end-group biotic index means to
calculate (unadjusted) Expected biotic index values agreed with our independent
calculations (when checked using the two abundance-weighted WHPT indices for spring
samples).
 The minor adjustments to WFD Reference state of the raw Expected values of WHPT
NTAXA and WHPT ASPT for the 12 test sites appears to have been coded correctly in
RICT, based on our independent code, but the RICT code could be tested further using
artificial more-widely varying adjustment factors.
Key words:
River Invertebrate Prediction and Classification System, RIVPACS, River
Invertebrate Classification Tool, RICT, Testing, Test Data.
Testing RICT predictions of expected values using an independent RIVPACS model and new RIVPACS test data
Table of Contents
1. BACKGROUND
2. DERIVING NEW RIVPACS/RICT TEST DATA
2.1 Geographical coverage throughout Great Britain
2.2 Range of Environmental Predictor Variables
2.3 Coverage of RIVPACS IV Biological End Groups
2.4 Reference and Degraded Samples
2.5 Environmental and Biological Test Data Files
3. RUNNING THE TEST DATA IN RICT
4. COMPARING RICT PREDICTIONS OUTPUT WITH INDEPENDENT CODE VALUES
FOR THE TEST DATA
4.1 RIVPACS derived Environmental variables for the predictions
4.2 Discriminant functions coefficients
4.3 End-group means for WHPT biotic indices
4.4 Mahalanobis distances and Probabilities of end-group for test sites
4.5 (Unadjusted) Expected values of the (WHPT) biotic indices
4.6 Adjustment of Expeced values for the quality of reference sites involved
4.7 Summary of testing of RICT predictions of Expected values of WHPT indices
5. REFERENCES
6. APPENDIX 1: FULL LIST OF THE RIVPACS/RICT BIOLOGICAL TEST DATASET
1
2
4
4
4
4
8
8
11
12
12
13
14
14
14
15
16
17
18
1. BACKGROUND
Since the original research projects that led to the development of the current RIVPACS IV
models in RICT and the subsequent launch of the first version of the RICT software (Clarke
et al., 2006; Davy-Bowker et al., 2007a, 2007b; 2008), a variety of further research and
development work has been carried out on the RIVPACS IV models and the RIVPACS
bioassessment methodologies. These are summarised below:
SNIFFER - project WFD100 (Davy-Bowker et al., 2010)
 Supplied new data files to support species-level taxonomic outputs from RICT.
 Allocated numerical abundance values to the RIVPACS database.
 Calculated a new range of species-level biotic indices in the RIVPACS database and
supplied the files necessary for RICT to predict expected values.
 Produced a list of new predictive variables to offset the loss of predictive power
associated with the future removal of variables affected by stress.
SNIFFER - project WFD119 (Clarke et al., 2011)
 Derived new alternative predictive variables that are not affected by stressors with
particular emphasis on hydrological/acidification metric predictors.
 Constructed several new RIVPACS models using stressor independent variables.
 Reviewed the performance of WFD reporting indices notably AWIC (species), LIFE
(species), PSI and WHPT.
Environment Agency - Deep Rivers (Jones et al., 2012; Davy-Bowker et al., 2014)
 Reviewed the results of previous deep-water methods comparison studies and made
recommendations on the preferred deep water sampling method(s) and the threshold
between methods for sampling wadeable and deep rivers.
 Examined the potential discontinuities in RIVPACS predictive models that might arise
from the methods used to collect reference samples.
 Identified existing RIVPACS sites that have been inappropriately sampled (given their
depth) and examined the distribution of deep water sites in the current model.
 Evaluated the suitability of the metrics EQR ASPT and NTAXA for deep rivers and
examined the potential need for additional environmental variables for deep rivers.
 Produced clear guidelines for sampling deep rivers for inclusion in future
Environment Agency sampling manuals.
 Undertook an ergonomic assessment of airlift sampling and provided a specification
for a ‘standard’ airlift sampling device.
SEPA - abundance weighted indices project (Clarke & Davy-Bowker, 2014)
 Develop algorithms and uncertainty parameter estimates for the incorporation of
abundance-weighted WHPT, LIFE and PSI into RICT.
 Estimated sampling uncertainty components in the abundance-weighted WHPT, LIFE
and PSI indices.
 Provided estimates of sampling variance for WHPT NTAXA, WHPT ASPT, LIFE and
PSI, together with detailed algorithms for incorporation into confidence of class
simulations.
 Analyzed a dataset of 427 samples to determine the biases (i.e. differences) between
the observed (pre-audit) sample value and the audit-corrected sample value of each
index.
 Provided algorithms to simulate the estimated sample processing biases in the
abundance-weighted WHPT indices.
 Provided a detailed algorithms section to enable the RICT software programmers to
encode these new methods and uncertainty parameter estimates for the abundanceweighted WHPT indices into the next version of RICT.
2
Scottish Executive - abstraction and sediment project (Davy-Bowker et al., In prep)
 Developed algorithms and uncertainty parameter estimates for the incorporation of
abundance-weighted classification indices WHPT, LIFE and PSI into RICT.
 Developed algorithms and parameter estimates for the incorporation of sample
biases of abundance-weighted indices LIFE and PSI, into RICT.
 Produced the basic statistical procedures needed classify by LIFE and PSI in RICT.
 Derived an initial set of statistically based WFD class boundaries for LIFE and PSI
taking into account of the range of pressures assessed by these metrics.
In each of these upgrades a contract report was produced that contained a mixture of either
new data, new code and/or new algorithms to permit the implementation of the work in RICT.
Whilst not all of these upgrades have been applied to the operational version of the RICT
software, this being dependent on the priorities of the UK Agencies, many have. These
upgrades to RICT have been carried out by SEPA appointed programmers and SEPA inhouse IT specialists:
It is now a fitting time to test the implementation of the various upgrades that have been
made to RICT by comparison to an independent stand-alone version of RIVPACS. An
independent version of RIVPACS can be constructed by virtue of the fact that all of the
necessary data, code and algorithms have always been published (see above). Ralph
Clarke (author) has extensive expertise in building RIVPACS models and wrote the software
for RIVPACS III+, the version immediately preceding the RIVPACS IV models currently
within RICT. Ralph also developed the the current RIVPACS IV statistical predictive models
and algorithms that were supplied to the SEPA-employed programmers in their development
of the original RICT software back in 2008.
Given the importance of the testing process it was considered appropriate to base these
tests on a new Great Britain-wide set of test data. Whilst various pieces of test data have
existed both now and in the past (e.g. the 3-site test data supplied with earlier pre-RICT
RIVPACS versions, and the current test data downloadable from the RICT website), these
have limited coverage of stream types and limited geographical spread . The opportunity
was therefore taken to devise a new set of test data with enhanced geographical spread,
better coverage of the range of environmental predictor variables, better coverage of
RIVPACS TWINSPAN biological end groups, and samples both in reference condition and
degraded status.
This research therefore had two objectives:
 To derive new RIVPACS/RICT test data for current (and future) RIVPACS/RICT testing
purposes.
 To test the current (Spring 2015) RICT software to see if its predictions match those of an
independently constructed version of the same RIVPACS IV model.
3
2. DERIVING NEW RIVPACS/RICT TEST DATA
A new set of test data was required with enhanced geographical spread, better coverage of
the range of environmental predictor variables, better coverage of RIVPACS IV TWINSPAN
biological end groups, and samples both in reference condition and degraded status.
Sites were drawn from the RIVPACS reference site database (Davy-Bowker et al., 2007a),
the dataset underpinning the development of all UK RIVPACS models.
Candidate RIVPACS reference sites were manually assessed for suitability using the
following overall considerations
1
2
3
Good geographical coverage (of Great Britain)
Good spread of environmental predictor variables compared to the full range of those
variables across the whole GB reference site dataset.
Good coverage across the RIVPACS IV biological TWINSPAN end groups
After examining various combinations of candidate sites, a group of twelve RIVPACS
reference sites were identified (Table 1) that had good geographical coverage, had a good
range of environmental variables, and were dispersed across all of the major TWINSPAN
biological end groups. The three considerations of geographical coverage, environmental
predictor variable range and coverage of biological end groups are discussed below.
2.1 Geographical coverage throughout Great Britain
The geographical coverage of the twelve RIVPACS reference sites is shown in Figure 1. The
sites are distributed across England (7 sites), Scotland (4 sites) and Wales (1 site) with the
number of sites in each country in approximate proportion to their relative land areas. The
sites cover a good north-south gradient (Shetland to the south west of England) and a good
east-west gradient (Islay to Suffolk). The sites are also quite well dispersed in relation to
each other, with only two sites (near Sheffield and Derby) in close proximity.
2.2 Range of Environmental Predictor Variables
The range of the eight user-supplied environmental variables used in RIVPACS predictions
for the twelve RIVPACS reference sites is shown in Figure 2. The open circles in Figure 2
represent the values of the environmental predictor variables for the twelve test sites.
Underlying these are frequency distributions of the same variables across 685 RIVPACS
reference sites. Figure 2 therefore shows the range of each variable that is likely to be
encountered in British streams and rivers and the representativeness of the test data across
those environmental gradients. For most of the variables the coverage is good, perhaps only
weakening towards sites that are at high altitudes, have high water depth, or very high width.
Overall the coverage was considered adequate.
2.3 Coverage of RIVPACS IV Biological End Groups
The construction of a RIVPACS model involves two main steps. Firstly a classification step
where the taxonomic data from all the reference samples is split successively into biological
end groups (typically using TWINSPAN), and secondly a Multiple Discriminant Analysis step
where equations are built that can discriminate the end groups from each other using the
physical predictor variables. Given that reference samples have been sought from all major
stream types that exist, the biological end groups therefore cover the majority of the range of
biological communities that are likely to occur. Designing the new test data to similarly cover
a wide range of different biological stream types was clearly desirable and assessing this by
virtue of their RIVPACS IV biological end groups was the simplest way to do this.
4
Table 1. The twelve RIVPACS reference sites identified for use in a new test dataset and their associated environmental variables.
Site ID
River
3101
Derwent
9581
Site
Langdale
End
Distance
Discharge
from
Grid Ref Easting Northing Latitude Longitude Altitude Slope Category Source Alkalinity
Mean Mean
Mean
Width Depth Substratum
SE942910 494200
491000
54.31
-0.55
60
2.7
2
10
101.4
6.4
21.7
-5.63776
SK220646 422000
364600
53.18
-1.67
142
5
4
6
194.6
6
10.7
-3.2125
8805
Lathkill
Alport
Coombevalley
Stream
Kilkhampton
SS246116 224600
111600
50.88
-4.49
100
40
1
1.7
50
1.4
7.8
-5.65594
2007
Blithe
SK048259 404800
325900
52.83
-1.93
97
1.8
3
27
164
10
8.7
-2.8
2307
Colne
Newton
Fordstreet
Bridge
TL921272 592100
227200
51.91
0.79
15
1.3
3
28
217.7
6.6
14.4
-3.37
7145
Ed
SU074105 407400
110500
50.89
-1.89
38
5.5
1
1.8
178
1.8
14.2
2.99505
6111
SEPA_
N06
SEPA_
W05
Pains Moor
Hilgay
Bridge
Ouse/Cam
TL604970 560400 297000
Shetland: Burn
of Laxdale
North Voxter HU437290 443700 1129000
Islay:
Duich/Torra
Torra Bridge NR344552 134400 655200
52.55
0.37
0
0.2
7
69
237.3
40
200
7.4375
60.044
-1.2154
5
11.5
1
6.6
17.5
3.6
12
-6.53
55.7173
-6.22961
46
11.4
3
8.5
3
4.53
20
-6.26
3785
Green Burn
Dalmary
NS515955 251500
695500
56.13
-4.39
30
45.7
1
4
9.5
3
17.5
-6.1375
NE01
Lossie
Cloddach
NJ203584 320300
858400
57.61
-3.33
44
8.3
4
27
23
15.1
25
-6.4
WE03
Afon Caseg
Braichmelyn
SH630663 263000
366300
53.18
-4.05
160
66.7
2
6.4
9.8
12
28
-6.985
5
Figure 1. Geographical distribution of the 12 RIVPACS test sites.
6
Figure 2. Environmental predictor variables of the 12 test sites (open circles) shown on top of frequency distributions of the same variables
across 685 RIVPACS reference sites.
7
Table 2 shows the RIVPACS IV biological end groups of the twelve reference samples.
There were 43 end groups in RIVPACS IV and the test samples have been evenly spread
across groups 1, 4, 8, 12, 16, 20, 24, 28, 32, 36, 40 and 43.
2.4 Reference and Degraded Samples
It was considered important that the test data set contained samples not only in reference
condition, but also examples of sites in degraded status. For example, it would not be
possible to use the test data in the future to examine the behaviour of RICT band limits if the
samples did not contain data that spanned a range of biological qualities.
Rather than adding another set of completely different samples of variously degrees of
environmental degradation to the twelve reference sites identified above, it was thought
useful to replicate the 12 reference samples, but this time with artificially simulated biological
quality as this would give greater control over the gradient of biological degradation in the
test data. Creating this second version of the twelve reference samples with simulated
degradation was achieved by making percentage reductions in the reference values of the
biotic indices. The simulated samples are therefore not ‘real’ in the sense that the indices are
not derived from actual taxonomic level data, and as such no actual taxonomic data could
necessarily create the particular set of observed biotic indices’ values that were made.
However, given that this test data is being developed to test the correct coding of the
classification steps in RICT, this is not a problem and the percentage reduction in indices
approach does give a better and more even range of environmental qualities to achieve this.
Table 2 summarises the final 24-site RIVPACS/RICT test data. In the first column are new
test data set samples codes. These have been renumbered from their original RIVPACS site
codes into a new structure where for example, in the case of sample TST-01-R, ‘TST’
indicates that this is a sample belonging to the RIVPACS/RICT test dataset, ‘01’ is a
sequential number between 01 and 12, and the suffix R means ‘reference quality’ (the
alternative ‘D’ indicating degraded quality). Table 2 also shows the two groups of reference
and degraded samples, which GB country they are within, their TWINSPAN end group, and
their original RIVPACS Site Code, River Name and Sample Name for cross referencing back
to the RIVPACS database.
2.5 Environmental and Biological Test Data Files
The final step in developing the new test data was to build RICT data input files for both the
environmental predictor variables and the biological indices WHPT NTAXA and WHPT ASPT
so that these data could be used for testing RICT. Note: the test dataset is also available as
RICT formatted Excel ® files and is downloadable from the FBA website www.fba.org.uk
(on the same webpage as this report).
RICT currently performs WFD status classifications based on the indices WHPT NTAXA and
WHPT ASPT and typically on a combination of spring and autumn samples. These were the
combinations that this contract specification therefore requested for testing and comparison
with an independently derived RIVPACS model. The environmental and biological data for
these commonly used indices and seasons are given in Table 3 and Table 4.
Given that RICT previously classified sites based on BMWP NTAXA and BMWP ASPT, and
also that the LIFE and PSI indices may soon be added to RICT for similar purposes, it was
considered useful to provide a more comprehensive list of biological index test data for indices
other than just the two WHPT indices, and for all three seasons These are provided in
Appendix 1. When combined with the Table 3 environmental data the Appendix 1 biological
data will permit the future testing of RICT in terms of a much wider range of index-by-season
combinations with a reduced likelihood of having to create another new set of test data.
8
Table 2. The 12 sites were used to make 24 test samples in both reference state, and simulated degraded status with new site codes ‘TST-01R’ to ‘TST-12-R’ (where R denotes reference condition), and ‘TST-01-D’ to ‘TST-12-D’ (where D denotes simulated degraded)
Test Data
Site Number
TST-01-R
TST-02-R
TST-03-R
TST-04-R
TST-05-R
TST-06-R
TST-07-R
TST-08-R
TST-09-R
TST-10-R
TST-11-R
TST-12-R
TST-01-D
TST-02-D
TST-03-D
TST-04-D
TST-05-D
TST-06-D
TST-07-D
TST-08-D
TST-09-D
TST-10-D
TST-11-D
TST-12-D
Reference/simulated
degraded
Reference
Reference
Reference
Reference
Reference
Reference
Reference
Reference
Reference
Reference
Reference
Reference
Degraded
Degraded
Degraded
Degraded
Degraded
Degraded
Degraded
Degraded
Degraded
Degraded
Degraded
Degraded
England/
Scotland/
Wales*
Eng.
Eng.
Eng.
Eng.
Eng.
Eng.
Eng.
Scot.
Scot.
Scot.
Scot.
Wales
Eng.
Eng.
Eng.
Eng.
Eng.
Eng.
Eng.
Scot.
Scot.
Scot.
Scot.
Wales
TWINSPAN
End Group
(1-43)
20
24
28
32
36
40
43
1
4
8
12
16
20
24
28
32
36
40
43
1
4
8
12
16
Site Code
3101
9581
8805
2007
2307
7145
6111
SEPA_N06
SEPA_W05
3785
NE01
WE03
3101
9581
8805
2007
2307
7145
6111
SEPA_N06
SEPA_W05
3785
NE01
WE03
River Name
Derwent
Lathkill
Coombevalley Stream
Blithe
Colne
Ed
Ouse/Cam
Shetland: Burn of Laxdale
Islay: Duich/Torra
Green Burn
Lossie
Afon Caseg
Derwent
Lathkill
Coombevalley Stream
Blithe
Colne
Ed
Ouse/Cam
Shetland: Burn of Laxdale
Islay: Duich/Torra
Green Burn
Lossie
Afon Caseg
*the number of samples was distributed proportionally across England, Scotland and Wales by land area.
9
Site Name
Langdale End
Alport
Kilkhampton
Newton
Fordstreet Bridge
Pains Moor
Hilgay Bridge
North Voxter
Torra Bridge
Dalmary
Cloddach
Braichmelyn
Langdale End
Alport
Kilkhampton
Newton
Fordstreet Bridge
Pains Moor
Hilgay Bridge
North Voxter
Torra Bridge
Dalmary
Cloddach
Braichmelyn
PEBBLES_GRAVEL
SAND
SILT_CLAY
2
4
1
3
3
1
7
1
3
1
4
2
2
4
1
3
3
1
7
1
3
1
4
2
BOULDER_COBBLES
2.7
5
40
1.8
1.3
5.5
0.2
11.5
11.4
45.7
8.3
66.7
2.7
5
40
1.8
1.3
5.5
0.2
11.5
11.4
45.7
8.3
66.7
ALKALINITY
DISCHARGE
60
142
100
97
15
38
1
5
46
30
44
160
60
142
100
97
15
38
1
5
46
30
44
160
MEAN_DEPTH
SLOPE
91000
64600
11600
25900
27200
10500
97000
29000
55200
95500
58400
66300
91000
64600
11600
25900
27200
10500
97000
29000
55200
95500
58400
66300
MEAN_WIDTH
ALTITUDE
94200
22000
24600
04800
92100
07400
60400
43700
34400
51500
20300
63000
94200
22000
24600
04800
92100
07400
60400
43700
34400
51500
20300
63000
DIST_FROM_SOURCE
Northing
SE
SK
SS
SK
TL
SU
TL
HU
NR
NS
NJ
SH
SE
SK
SS
SK
TL
SU
TL
HU
NR
NS
NJ
SH
VELOCITY
Easting
SITE
TST-01-R
TST-02-R
TST-03-R
TST-04-R
TST-05-R
TST-06-R
TST-07-R
TST-08-R
TST-09-R
TST-10-R
TST-11-R
TST-12-R
TST-01-D
TST-02-D
TST-03-D
TST-04-D
TST-05-D
TST-06-D
TST-07-D
TST-08-D
TST-09-D
TST-10-D
TST-11-D
TST-12-D
NGR
Table 3. RIVPACS/RICT environmental test data.
10
6
1.7
27
28
1.8
69
6.6
8.5
4
27
6.4
10
6
1.7
27
28
1.8
69
6.6
8.5
4
27
6.4
6.4
6
1.4
10
6.6
1.8
40
3.6
4.53
3
15.1
12
6.4
6
1.4
10
6.6
1.8
40
3.6
4.53
3
15.1
12
21.7
10.7
7.8
8.7
14.4
14.2
200
12
20
17.5
25
28
21.7
10.7
7.8
8.7
14.4
14.2
200
12
20
17.5
25
28
101.4
194.6
50
164
217.7
178
237.3
17.5
3
9.5
23
9.8
101.4
194.6
50
164
217.7
178
237.3
17.5
3
9.5
23
9.8
58
30
65
25
12
0
1
73
67
70
70
83
58
30
65
25
12
0
1
73
67
70
70
83
36
47
30
53
80
38
2
27
33
25
30
17
36
47
30
53
80
38
2
27
33
25
30
17
3
20
3
15
8
13
3
0
0
5
0
0
3
20
3
15
8
13
3
0
0
5
0
0
1
3
3
7
0
50
94
0
0
0
0
0
1
3
3
7
0
50
94
0
0
0
0
0
Site
TST-01-R
TST-02-R
TST-03-R
TST-04-R
TST-05-R
TST-06-R
TST-07-R
TST-08-R
TST-09-R
TST-10-R
TST-11-R
TST-12-R
TST-01-D
TST-02-D
TST-03-D
TST-04-D
TST-05-D
TST-06-D
TST-07-D
TST-08-D
TST-09-D
TST-10-D
TST-11-D
TST-12-D
WHPT
NTAXA
Abund
24
25
28
31
24
31
35
11
18
15
22
27
23
20
18
16
8
6
33
9
12
8
8
5
WHPT
ASPT
Abund
6.512
6.476
6.739
6.587
4.908
5.503
4.017
5.436
7.767
7.033
7.636
7.604
5.783
5.650
5.778
5.125
3.625
2.833
3.636
4.667
6.417
5.250
5.250
4.200
Season_ID
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
WHPT
NTAXA
Abund
WHPT
ASPT
Abund
Site
TST-01-R
TST-02-R
TST-03-R
TST-04-R
TST-05-R
TST-06-R
TST-07-R
TST-08-R
TST-09-R
TST-10-R
TST-11-R
TST-12-R
TST-01-D
TST-02-D
TST-03-D
TST-04-D
TST-05-D
TST-06-D
TST-07-D
TST-08-D
TST-09-D
TST-10-D
TST-11-D
TST-12-D
Season_ID
Table 4. RIVPACS/RICT Spring (left) and Autumn (right) WHPT ASPT and WHPT NTAXA
biological test data (the same data are coloured blue and green respectively in Appendix 1).
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
6.348
5.892
6.132
6.648
4.881
5.452
3.959
5.845
8.018
7.146
7.617
7.048
5.615
5.150
5.222
5.125
3.455
2.667
3.500
5.000
6.818
5.286
5.750
3.286
27
25
28
31
31
29
27
11
17
13
24
33
26
20
18
16
11
6
26
9
11
7
8
7
10
These
environmental and
biological
RIVPACS/RICT test
data files are
available to
download as RICT
formatted Excel ®
files from the FBA
website
www.fba.org.uk
and are stored on
the same webpage
as this report.
This is the simplest
way to access and
use the test dataset
with RICT.
3. RUNNING THE TEST DATA IN RICT
The first step in making a comparison between the predictions generated by RICT, and
those generated by an independent version of the same RIVPACS IV model, was to obtain
the RICT classification results.
An initial exploratory RICT run was performed first to ensure that the test data were correctly
formatted for RICT (e.g. columns correctly labelled and in the correct sequence and site
names in the environmental file and biological files matched each other). This was also an
opportunity to perform a visual check of the grid references by comparing the map in Figure
1 with the map produced inside RICT.
RICT currently has the ability to produce both single season results (runs where prediction
and classification results are derived from just one season of biological data) or combined
season runs (runs where two separate single season runs are integrated within the software
into an overall combined seasons classification). In the second case, RICT automatically
produces single season ‘child’ runs before subsequently combining them into the overall
classification.
It was useful to take the opportunity to verify that the results of separate season runs were in
agreement with those of the child components of combined season runs (as far as the basic
Face Value Bias Uncorrected EQI values at least – testing further than this was beyond the
scope of this project).
Testing confirmed that the Face Value Bias Uncorrected EQI values produced in single
season runs and the EQIs produced in combined season child runs were in mutual
agreement. This simplified the subsequent comparison of RICT with the independently
generated RIVPACS model by making it only necessary to compare single season runs.
The newly developed RIVPACS/RICT test data were therefore put through RICT as two
separate season classification runs, one for spring and one for autumn using:


Environmental data and Spring WHPT NTAXA & ASPT biological data
Environmental data and Autumn WHPT NTAXA & ASPT biological data
The output files from these two runs were downloaded from the RICT software and saved.
The results of these two RICT classification runs were then extracted into a more convenient
spreadsheet format ready for comparison with the independently derived RIVPACS IV
prediction model.
11
4. COMPARING RICT PREDICTIONS OUTPUT WITH INDEPENDENT CODE VALUES
FOR THE TEST DATA
Because of a limited budget and hence time for this testing work, it was agreed with John
Murray-Bligh (Environment Agency) that the testing would concentrate on making
predictions of the expected values of the abundance-weighted WHPT NTAXA and WHPT
ASPT indices for spring samples, both as raw un-adjusted expected values and as adjusted
expected vaues (i.e. adjusted for the quality of the RIVPACS reference sites actively
involved in the prediction for any specific test site).
All of the statistical algorithms used to provide the RIVPACS IV model predictions of
expected values of biotic indices in the original (and current) RICT software were developed
by Ralph Clarke and supplied in complete detail in the SNIFFER project WFD72C final
report (Davy-Bowker et al 2008) upon which the RICT software was orginallly developed.
Back in 2007-08, Ralph Clarke originally developed and assessed the RIVPACS IV models
involved in RICT using a mixture of statistical software and his own MINITAB statistical
software macro codes. For this RICT-testing project, Ralph adapted parts of this code to
make independent calculations of the predictions for the 12 sites in the new Test Data
described in sections 2 and 3 above.
4.1 RIVPACS derived Environmental variables for the predictions
RIVPACS predictions of the probability of RIVPACS TWINSPAN end-groups membership for
any river site are based on previously-derived multivariate discriminant analyses (MDA) of
the RIVPACS Reference sites. These MDA discriminant functions are applied to a specific
set of environmental variables, most of which are derivatives of the original environmental
variables supplied by the User as input to the RICT software. Specifically the derived
variables are:
Latitiude and Longitude - derived from site National Grid reference
Air Temperature Mean and Range - derived from site National Grid reference
Mean substratum composition (in phi units) - derived from percentage cover of each of
boulders/cobbles, pebbles/gravel, sand and silt/clay
and also the logarithm (to base 10) of:
stream distance from source (DFS)
stream width and depth
altitude and slope at site
alkalinity (log alkalinity and alkalinity are both used in the predictive equatons)
The precise order of all of the MDA environmental variables and their values for the 12 test
data sites are given in Table 5.
Within the RICT software the NGR of a site is used to derive its Latitude and Longitude and
estimates of the Mean and Range of Air Temperature of the site. These derived variables
are based on a complex set of trigonometric and geographic interpolation equations and
background temperature map data, which were all supplied to the RICT programmers within
the WFD72C project and final report. To check these have been coded correctly within the
RICT software, we compared the values of these variables output from RICT (RICT output
file ‘PEV.XML’) with those previously derived by us (prior to RICT) using the RIVPACS III+
(RPBATCH) software. There were no differences in values (to 2 decimal places) between
the RICT and former RPBATCH derived values for any of these variables or for Mean
12
substratum composition. The log (to base 10) transformation of the appropriate
environmental variables was also checked and found to be correct for the 12 test sites.
SITE
LATITUDE
LONGITUDE
MEAN AIR TEMP
AIR TEMP RANGE
DISCHARGE CATEGORY
ALKALINITY
MEAN SUBSTRATUM
LOG ALTITUDE
LOG DISTANCE FROM SOURCE
LOG WIDTH
LOG DEPTH
LOG ALKALINITY
LOG SLOPE
Table 5. RIVPACS/RICT MDA environmental predictor variables’ values for the test data
(derived variables displayed to three decimal places); variables are in the correct order for
input to RICT
TST-01-R
54.306
-0.552
9.486
11.953
2
101.4
-5.638
1.778
1.000
0.806
1.336
2.006
0.431
TST-02-R
53.178
-1.671
9.750
12.562
4
194.6
-3.213
2.152
0.778
0.778
1.029
2.289
0.699
TST-03-R
50.877
-4.493
10.761
9.848
1
50.0
-5.656
2.000
0.230
0.146
0.892
1.699
1.602
TST-04-R
52.830
-1.929
9.590
12.650
3
164.0
-2.800
1.987
1.431
1.000
0.940
2.215
0.255
TST-05-R
51.910
0.793
10.098
13.670
3
217.7
-3.370
1.176
1.447
0.820
1.158
2.338
0.114
TST-06-R
50.893
-1.895
10.558
12.496
1
178.0
2.995
1.580
0.255
0.255
1.152
2.250
TST-07-R
52.547
0.366
9.645
13.584
7
237.3
7.438
0.000
1.839
1.602
2.301
2.375
0.740
0.699
TST-08-R
60.044
-1.215
7.530
8.880
1
17.5
-6.535
0.699
0.820
0.556
1.079
1.243
1.061
TST-09-R
55.717
-6.230
9.427
9.091
3
3.0
-6.265
1.663
0.929
0.656
1.301
0.477
1.057
TST-10-R
56.129
-4.390
8.757
12.242
1
9.5
-6.138
1.477
0.602
0.477
1.243
0.978
1.660
TST-11-R
57.609
-3.334
8.567
11.206
4
23.0
-6.400
1.643
1.431
1.179
1.398
1.362
0.919
TST-12-R
53.176
-4.050
10.224
10.298
2
9.8
-6.985
2.204
0.806
1.079
1.447
0.991
1.824
Summary: the RICT code to calculate the values of the numerous derived
environmental variables used in RICT predictions agrees with our independent
RIVPACS calculations and checks.
4.2 Discriminant functions coefficients
In the independent check of the RICT software it was assumed that the coefficients of the 13
MDA discriminant functions used in the RIVPACS predictions were those supplied from the
WFD72C project as file:
'DFCOEFF_GB685_sent101207.DAT'
The 13 MDA discriminant functions mean values for the reference sites in each of the 43
TWINSPAN end-groups were extracted from the RICT software and supplied by David
Colvill (SEPA). These were used in the independent RICT calculations testing.
13
4.3 End-group means for WHPT biotic indices
The RIVPACs IV model TWINSPAN end-group mean values of each of a wide range of
biotic indices are available form the RIVPACS Reference sites main database available from
the FBA (www.fba.org.uk) and other sources.
On checking, we eventually determined that the form of abundance-weighted WHPT NTAXA
and WHPT ASPT currently used in RICT are derived from the end-group means of the two
WHPT indices based on Taxonomic Level 2 data, but using the BMWP Composite taxa
version of the WHPT indices rather than the Distinct families version (both versions were
supplied by us in 2008 for the original version of RICT). This is important as some Agency
staff may have thought that this set of RICT predictions were for abundance-weighted WHPT
NTAXA and WHPT ASPT based on the use of Distinct families taxonomic data and
consequently would have incorrectly compare observed index values for Users’ sites based
on Distinct family data values with expected values based on Composite values. WHPT
NTAXA for distinct families can only be as great or greater than WHPT NTAXA for
Composite families; when greater there would be some over-estimation of EQI NTAXA.
RICT software and User documentation needs to:
(i)
make clear that the abundance-weighted WHPT indices are currently
based on BMWP Composite families data
(ii)
be updated to include the ability to make predictions for the abundanceweighted WHPT indices based on Distinct families taxonomic data.
4.4 Mahalanobis distances and Probabilities of end-group for test sites
RIVPACS (and thus RICT) predictions of the end-group probabilities of any site involve
calculating the Mahalanobis distances (in MDA multivariate space) of the test site to each
end-group. These Mahalanobis distances can be extracted from RICT output files. The
distance for each of the 12 test sites to each of the 43 GB model end-groups agree with our
independent calculations (all differences in distances were less than 0.0001).
The RICT output of its calculations of the probability of belonging to each of the 43 endgroups for each of the 12 test sites agreed with our independent calculations (all differences
in probabilities were less than 0.0001).
For any fixed set of values of the environmental variables for a site, the probability of
belonging to each end-group is fixed in that it does not depend on either the seasons and/or
years samples to be assssed or on the biotic indices to be used in the assessment or on
their observed values.
Summary: the RICT code to calculate the probabilities of end-group for each test site
agrees with our independent calculations.
4.5 (Unadjusted) Expected values of the (WHPT) biotic indices
In this testing study, the requirement was check the accuracy of the RICT calculation of the
raw (i.e. unadjusted) Expected values of the two currently used biotic indices, namely
abundance-weighted WHPT NTAXA and WHPT ASPT. In section 4.3 of this report, we have
already deduced that the current RICT software predictions were based on the Composite
family form of these indices (rather than the Distinct family form). In our independent
calculation checking we therefore used the same end-group means of the Composite family
forms of the two abundance-weighted WHPT indices.
14
Our checks were based on comparing predictions for spring samples only.
The RICT output agreed with our independent calcuations of the (unadjusted) expected
spring sample values of WHPT NTAXA (all differences were less than 0.007) and WHPT
ASPT (all differences were less than 0.002). The same RICT code is almost certainly used
for other season(s) samples, so the only remaining cause of error in this stage of the
predictions is that the wrong season(s) end-group means for the required biotic indices are
selected.
Summary: the RICT code using the probabilities of end-group and end-group biotic
index means to calculate (unadjusted) Expected biotic index values agreed with our
independent calculations - when checked using the two abundance-weighted WHPT
indices for spring samples.
4.6 Adjustment of Expeced values for the quality of reference sites involved
The RICT predicted Expected index values for any site is subsequently adjusted using the
algorithms developed by Ralph Clarke and detailed in the Work Element 4.5 section of the
WFD72C final report. These algorithms were converted into independent code by Ralph
Clarke and used to provide an independent check of the RICT software code calculations of
adjustment of raw Expected values to WFD Reference Expected values for the same 12 test
sites.
The RICT output of the adjusted Expected spring sample values agreed with our
independent calcuations for WHPT NTAXA (all differences were less than 0.008) and WHPT
ASPT (all differences were less than 0.002).
However, because the adjustment factors (Q1,Q2, Q3 ,Q4, Q5) for both of these indices are
are either 1.0 or quite close (Table 6), it is not necessarily a very sensitive check of the RICT
code. At the next stage of the RICT checking project, it would be better if these true values
of the adjustment factors were temporarily replaced with more extreme values (e.g. 1.0, 0.9,
0.8, 0.6, 0.4) in both RICT and our independent code and the adjusted Expected values recalculated and compared (the adjustment factors in RICT should of course be reset back to
their true values after any such test). Further testing in a follow on project would also provide
the opportunity for us to verify that RICT is using up-to date versions of the Adjustment
Factors that reflect the latest work done on intercalibration by John Murray-Bligh.
Table 6. Adjustment factors for reference site quality (Q1, Q2, Q3, Q4, Q5) for abundanceweighted WHPT NTAXA and WHPT ASPT
Index
WHPT NTAXA
WHPT ASPT
Q1
1
1
Q2
1
1
Q3
1
1
Q4
0.967
0.977
Q5
0.926
0.945
Summary: The minor adjustments to WFD Reference state of the raw Expected values
of WHPT NTAXA and WHPT ASPT for the 12 test sites appears to have been coded
correctly in RICT, based on our independent code, but the RICT code could be tested
further using artificial more-widely varying adjustment factors.
15
4.7 Summary of testing of RICT predictions of Expected values of WHPT indices
Our independent calculation of each of the algorithm steps involved in derving RIVPACS IV
GB model predictions of the raw and adjusted Expected values of the WHPT indices suggest
that these are correctly coded and calculated within the RICT software (i.e. RICT as of 13
March 2015).
This initial testing project has also highlighted the need for the RICT software and website to
include clear software version numbering and a user-accessible log of updates and changes,
along with the dates that these alterations were made.
16
5. REFERENCES
Clarke R.T. & Davy-Bowker J. (2006). Development of the scientific rationale and formulae
for altering RIVPACS predicted indices for WFD reference condition. Scotland &
Northern Ireland Forum for Environmental Research. Edinburgh, Scotland, UK.
(SNIFFER project WFD72B).
Clarke R.T. & Davy-Bowker J. (2014) River Invertebrate Classification Tool Science
Development Project: Modifications for WHPT and other abundance-weighted indices.
A report to the Scottish Environment Protection Agency.
Clarke R. T., Davy-Bowker J., Dunbar M., Laize C., Scarlett P.M. & Murphy J.F. (2011)
Enhancement of the River Invertebrate Classification Tool (RICT). Scotland & Northern
Ireland Forum for Environmental Research. Edinburgh, Scotland, UK. (SNIFFER
project WFD119).
Davy-Bowker J., Arnott S., Close R., Dobson M., Dunbar M., Jofre G., Morton D.,
Murphy J., Wareham W., Smith S. & Gordon V. (2010) Further Development of
River Invertebrate Classification Tool. Scotland & Northern Ireland Forum for
Environmental Research. Edinburgh, Scotland, UK. (SNIFFER project WFD100).
Davy-Bowker J., Clarke R., Corbin T., Vincent H., Pretty J., Hawczak A., Blackburn J.,
Murphy J. & Jones I. (2008). River Invertebrate Classification Tool. Scotland &
Northern Ireland Forum for Environmental Research. Edinburgh, Scotland, UK.
(SNIFFER project WFD72C).
Davy-Bowker J., Clarke R., Furse M., Davies C., Corbin T., Murphy J. & Kneebone N.
(2007a) RIVPACS Database Documentation. Scotland & Northern Ireland Forum for
Davy-Bowker J., Clarke R., Furse M., Davies C., Corbin T., Murphy J. & Kneebone N.
(2007b) RIVPACS Pressure Data Analysis. Scotland & Northern Ireland Forum for
Davy-Bowker J., Clarke R.T., Jones J.I. & Murphy J.F. (In prep) River Invertebrate
Classification Tool Science Development Project: Describing the impact of abstraction
and fine sediment pressures on the biological communities in Scottish rivers. A report
to the Scottish Government.
Davy-Bowker J., Jones J.I. & Murphy J.F. (2014) Standardisation of RIVPACS for deep
rivers: Phase I - deriving a standard approach to deep river sampling. Environment
Agency, Bristol.
Jones J.I. & Davy-Bowker J. (2012) Standardisation of RIVPACS for deep rivers: Phase I review of techniques for sampling benthic macro-invertebrates in deep rivers.
Environment Agency, Bristol.
17
TL1 BMWP
TL2 WHPT Score
(nonAb,DistFam)
TL2 WHPT NTAXA
(nonAb,DistFam)
TL2 WHPT ASPT
(nonAb,DistFam)
TL2 WHPT Score
(nonAb,CompFam)
TL2 WHPT NTAXA
(nonAb,CompFam)
TL2 WHPT ASPT
(nonAb,CompFam)
TL2 WHPT Score
(AbW,DistFam)
TL2 WHPT NTAXA
(AbW,DistFam)
TL2 WHPT ASPT
(AbW,DistFam)
TL2 WHPT Score
(AbW,CompFam)
TL2 WHPT NTAXA
(AbW,CompFam)
TL2 WHPT ASPT
(AbW,CompFam)
TST-01-R
1
132
22
6.000
157.7
24
6.571
156.0
24
6.500
156.3
24
6.512
154.6
24
6.442
TST-02-R
1
140
21
6.667
163.4
25
6.536
163.3
25
6.532
161.9
25
6.476
161.8
25
6.472
TST-03-R
1
164
26
6.308
194.2
28
6.936
192.8
28
6.886
188.7
28
6.739
187.2
28
6.686
TST-04-R
1
165
26
6.346
206.0
31
6.645
198.4
30
6.613
204.2
31
6.587
196.4
30
6.547
TST-05-R
1
107
22
4.864
119.5
24
4.979
116.1
23
5.048
117.8
24
4.908
114.6
23
4.983
TST-06-R
1
144
28
5.143
168.5
31
5.435
168.7
31
5.442
170.6
31
5.503
170.6
31
5.503
TST-07-R
1
146
31
4.710
152.7
35
4.363
147.0
32
4.594
140.6
35
4.017
135.6
32
4.238
TST-08-R
1
43
9
4.778
63.6
11
5.782
62.2
11
5.655
59.8
11
5.436
58.4
11
5.309
TST-09-R
1
119
17
7.000
137.3
18
7.628
135.8
18
7.544
139.8
18
7.767
138.3
18
7.683
TST-10-R
1
76
13
5.846
101.3
15
6.753
93.8
14
6.700
105.5
15
7.033
95.9
14
6.850
TST-11-R
1
134
20
6.700
160.4
22
7.291
152.6
21
7.267
168.0
22
7.636
160.1
21
7.624
TST-12-R
1
171
25
6.840
202.6
27
7.504
193.6
26
7.446
205.3
27
7.604
197.1
26
7.581
TST-01-D
1
112
21
5.333
134
23
5.826
133
23
5.783
133
23
5.783
131
23
5.696
TST-02-D
1
98
17
5.765
114
20
5.700
114
20
5.700
113
20
5.650
113
20
5.650
TST-03-D
1
90
17
5.294
107
18
5.944
106
18
5.889
104
18
5.778
103
18
5.722
TST-04-D
1
66
13
5.077
82
16
5.125
79
15
5.267
82
16
5.125
79
15
5.267
TST-05-D
1
27
8
3.375
30
8
3.750
29
8
3.625
29
8
3.625
29
8
3.625
TST-06-D
1
14
6
2.333
17
6
2.833
17
6
2.833
17
6
2.833
17
6
2.833
TST-07-D
1
124
29
4.276
130
33
3.939
125
30
4.167
120
33
3.636
115
30
3.833
TST-08-D
1
30
7
4.286
45
9
5.000
44
9
4.889
42
9
4.667
41
9
4.556
TST-09-D
1
65
11
5.909
76
12
6.333
75
12
6.250
77
12
6.417
76
12
6.333
TST-10-D
1
30
7
4.286
41
8
5.125
38
7
5.429
42
8
5.250
38
7
5.429
TST-11-D
1
34
7
4.857
40
8
5.000
38
7
5.429
42
8
5.250
40
7
5.714
TST-12-D
1
17
5
3.400
20
5
4.000
19
5
3.800
21
5
4.200
20
5
4.000
TST-01-R
2
154
24
6.417
176.2
27
6.526
168.6
26
6.485
179.9
27
6.663
172.7
26
6.642
TST-02-R
2
116
17
6.824
123.6
18
6.867
124.7
18
6.928
122.6
18
6.811
123.5
18
6.861
TST-03-R
2
141
24
5.875
174.1
28
6.218
166.7
27
6.174
167.7
28
5.989
160.3
27
5.937
TST-04-R
2
154
26
5.923
171.0
29
5.897
171.3
29
5.907
172.1
29
5.934
172.5
29
5.948
TST-05-R
2
100
20
5.000
115.0
22
5.227
115.7
22
5.259
117.7
22
5.350
118.4
22
5.382
TST-06-R
2
119
23
5.174
131.4
25
5.256
131.7
25
5.268
122.0
25
4.880
122.1
25
4.884
TST-07-R
2
142
29
4.897
147.1
34
4.326
140.0
31
4.516
132.4
34
3.894
126.0
31
4.065
TST-08-R
2
35
9
3.889
52.6
10
5.260
50.9
10
5.090
55.3
10
5.530
53.6
10
5.360
TST-09-R
2
120
18
6.667
138.1
19
7.268
136.4
19
7.179
132.7
19
6.984
131.0
19
6.895
TST-10-R
2
null
null
null
null
null
null
TST-11-R
2
122
19
6.421
147.0
21
7.000
139.2
20
6.960
150.9
21
7.186
142.1
20
7.105
TST-12-R
2
148
22
6.727
168.0
24
7.000
159.0
23
6.913
162.7
24
6.779
153.6
23
6.678
TST-01-D
2
131
23
5.696
150
26
5.769
143
25
5.720
153
26
5.885
147
25
5.880
TST-02-D
2
81
14
5.786
87
14
6.214
87
14
6.214
86
14
6.143
86
14
6.143
TST-03-D
2
78
16
4.875
96
18
5.333
92
18
5.111
92
18
5.111
88
18
4.889
TST-04-D
2
62
13
4.769
68
15
4.533
69
15
4.600
69
15
4.600
69
15
4.600
TST-05-D
2
25
7
3.571
29
8
3.625
29
8
3.625
29
8
3.625
30
8
3.750
TST-06-D
2
12
5
2.400
13
5
2.600
13
5
2.600
12
5
2.400
12
5
2.400
TST-07-D
2
121
28
4.321
125
32
3.906
119
29
4.103
113
32
3.531
107
29
3.690
TST-08-D
2
25
7
3.571
37
8
4.625
36
8
4.500
39
8
4.875
38
8
4.750
TST-09-D
2
66
12
5.500
76
12
6.333
75
12
6.250
73
12
6.083
72
12
6.000
TST-10-D
2
TST-11-D
2
31
7
4.429
37
7
5.286
35
7
5.000
38
7
5.429
36
7
5.143
TST-12-D
2
15
4
3.750
17
5
3.400
16
5
3.200
16
5
3.200
15
5
3.000
TL1 ASPT
Site ID
TL1 NTAXA
Season Code
6. APPENDIX 1: Full List of the RIVPACS/RICT Biological Test Dataset
Spring
Reference
Degraded
Summer
Reference
null
null
null
null
null
null
null
null
null
Degraded
null
null
null
null
null
null
null
18
null
null
null
null
null
null
null
null
TL2 WHPT ASPT
(nonAb,DistFam)
TL2 WHPT Score
(nonAb,CompFam)
TL2 WHPT NTAXA
(nonAb,CompFam)
TL2 WHPT ASPT
(nonAb,CompFam)
TL2 WHPT Score
(AbW,DistFam)
TL2 WHPT NTAXA
(AbW,DistFam)
TL2 WHPT ASPT
(AbW,DistFam)
TL2 WHPT Score
(AbW,CompFam)
157
26 6.038
168.3
27
6.233
167.0
27
6.185
171.4
27
6.348
170.1
27 6.300
3
129
21 6.143
150.4
25
6.016
150.7
25
6.028
147.3
25
5.892
147.6
25 5.904
TST-03-R
3
149
25 5.960
176.7
28
6.311
175.3
28
6.261
171.7
28
6.132
170.1
28 6.075
TST-04-R
3
184
28 6.571
206.4
31
6.658
206.5
31
6.661
206.1
31
6.648
206.1
31 6.648
TST-05-R
3
123
25 4.920
151.1
31
4.874
144.1
29
4.969
151.3
31
4.881
143.8
29 4.959
TST-06-R
3
143
26 5.500
164.3
29
5.666
164.7
29
5.679
158.1
29
5.452
158.4
29 5.462
TST-07-R
3
123
26 4.731
116.5
27
4.315
120.0
27
4.444
106.9
27
3.959
111.8
27 4.141
TST-08-R
3
56
11 5.091
65.7
11
5.973
64.1
11
5.827
64.3
11
5.845
62.7
11 5.700
TST-09-R
3
110
16 6.875
134.4
17
7.906
134.2
17
7.894
136.3
17
8.018
136.1
17 8.006
TST-10-R
3
81
13 6.231
92.8
13
7.138
91.3
13
7.023
92.9
13
7.146
91.4
13 7.031
TST-11-R
3
151
22 6.864
181.5
24
7.562
173.7
23
7.552
182.8
24
7.617
174.9
23 7.604
TST-12-R
3
171
27 6.333
230.0
33
6.970
221.0
32
6.906
232.6
33
7.048
223.3
32 6.978
TST-01-D
3
133
25 5.320
143
26
5.500
142
26
5.462
146
26
5.615
145
26 5.577
TST-02-D
3
90
17 5.294
105
20
5.250
105
20
5.250
103
20
5.150
103
20 5.150
TST-03-D
3
82
16 5.125
97
18
5.389
96
18
5.333
94
18
5.222
94
18 5.222
TST-04-D
3
74
14 5.286
83
16
5.188
83
16
5.188
82
16
5.125
82
16 5.125
TST-05-D
3
31
9 3.444
38
11
3.455
36
10
3.600
38
11
3.455
36
10 3.600
TST-06-D
3
14
5 2.800
16
6
2.667
16
6
2.667
16
6
2.667
16
6 2.667
TST-07-D
3
105
25 4.200
99
26
3.808
102
26
3.923
91
26
3.500
95
26 3.654
TST-08-D
3
39
9 4.333
46
9
5.111
45
9
5.000
45
9
5.000
44
9 4.889
TST-09-D
3
61
10 6.100
74
11
6.727
74
11
6.727
75
11
6.818
75
11 6.818
TST-10-D
3
32
7 4.571
37
7
5.286
37
7
5.286
37
7
5.286
37
7 5.286
TST-11-D
3
38
8 4.750
45
8
5.625
43
8
5.375
46
8
5.750
44
8 5.500
TST-12-D
3
17
5 3.400
23
7
3.286
22
6
3.667
23
7
3.286
22
6 3.667
TL2 WHPT ASPT
(AbW,CompFam)
TL2 WHPT NTAXA
(nonAb,DistFam)
TL2 WHPT NTAXA
(AbW,CompFam)
TL2 WHPT Score
(nonAb,DistFam)
3
TST-02-R
TL1 ASPT
TL1 BMWP
TST-01-R
Site ID
TL1 NTAXA
Season Code
Appendix 2: continued...
Autumn
Reference
Degraded
Footnote: Reference biotic indices (Site ID suffixed ‘R’) were the biotic indices of the
RIVPACS reference samples. Degraded biotic indices (Site ID suffixed ‘D’) were simulated.
19
TL4 AWIC(Sp)
Murphy
TL5 AWIC(Sp)
Murphy
TL4 SEPA % Acid
Sensitive Taxa
TL5 SEPA % Acid
Sensitive Taxa
TL1/2 LIFE(Fam)
(CompFam)
TL2 LIFE(Fam)
(DistFam)
TL3 LIFE(Fam)
(DistFam)
TL4 LIFE(Sp)
TL5 LIFE(Sp)
TL3 PSI(Fam)
TL4 PSI(Sp)
TL5 PSI(Sp)
1
4.636
5.875
5.875
7.812
7.812
11.982
11.982
7.100
7.100
7.100
8.000
8.000
53.659
69.565
72.093
TST-02-R
1
4.500
7.333
7.333
10.167
10.167
54.198
54.198
7.526
7.526
7.526
8.600
8.600
75.676
88.636
88.372
TST-03-R
1
4.360
6.316
6.316
8.789
8.789
54.099
53.051
7.625
7.625
7.625
8.419
8.667
66.667
69.118
72.131
TST-04-R
1
4.800
7.312
7.267
10.312
10.333
10.385
10.385
7.542
7.600
7.600
8.552
8.846
63.636
74.699
76.190
TST-05-R
1
5.100
7.200
7.200
10.100
10.100
2.844
2.844
6.550
6.524
6.524
7.200
7.455
29.545
43.860
45.455
TST-06-R
1
5.500
6.571
6.571
9.857
9.857
28.318
27.773
6.704
6.704
6.704
7.000
7.346
44.068
34.667
40.625
TST-07-R
1
5.519
9.000
9.000
14.000
14.000
2.065
2.064
5.759
5.656
5.656
5.667
5.761
13.699
6.140
6.140
TST-08-R
1
4.444
6.667
6.667
8.000
8.000
2.445
2.309
7.429
7.429
7.429
8.400
8.500
63.158
57.143
53.846
TST-09-R
1
3.882
5.875
5.875
7.312
7.312
5.234
5.234
8.200
8.200
8.200
8.667
8.667
82.353
94.286
94.286
TST-10-R
1
3.846
5.000
5.000
6.700
6.700
9.635
9.635
6.818
6.667
6.667
7.588
7.750
44.444
54.545
54.545
TST-11-R
1
4.300
7.000
7.000
9.333
9.333
46.679
46.679
8.222
8.263
8.263
9.087
9.091
76.364
90.000
88.679
TST-12-R
1
4.440
7.074
7.074
9.259
9.259
45.600
45.509
7.957
7.917
7.917
8.727
8.750
74.000
90.769
93.333
TST-01-D
1
3.941
4.994
4.994
6.640
6.640
10.185
10.185
6.035
6.035
6.035
6.800
6.800
45.610
59.130
61.279
TST-02-D
1
3.150
5.133
5.133
7.117
7.117
37.939
37.939
5.268
5.268
5.268
6.020
6.020
52.973
62.045
61.860
TST-03-D
1
2.398
3.474
3.474
4.834
4.834
29.754
29.178
4.194
4.194
4.194
4.630
4.767
36.667
38.015
39.672
TST-04-D
1
1.920
2.925
2.907
4.125
4.133
4.154
4.154
3.017
3.040
3.040
3.421
3.538
25.454
29.880
30.476
TST-05-D
1
1.275
1.800
1.800
2.525
2.525
0.711
0.711
1.638
1.631
1.631
1.800
1.864
7.386
10.965
11.364
TST-06-D
1
0.550
0.657
0.657
0.986
0.986
2.832
2.777
0.670
0.670
0.670
0.700
0.735
4.407
3.467
4.063
TST-07-D
1
4.691
7.650
7.650
11.900
11.900
1.755
1.754
4.895
4.808
4.808
4.817
4.897
11.644
5.219
5.219
TST-08-D
1
3.111
4.667
4.667
5.600
5.600
1.712
1.616
5.200
5.200
5.200
5.880
5.950
44.211
40.000
37.692
TST-09-D
1
2.135
3.231
3.231
4.022
4.022
2.879
2.879
4.510
4.510
4.510
4.767
4.767
45.294
51.857
51.857
TST-10-D
1
1.538
2.000
2.000
2.680
2.680
3.854
3.854
2.727
2.667
2.667
3.035
3.100
17.778
21.818
21.818
TST-11-D
1
1.075
1.750
1.750
2.333
2.333
11.670
11.670
2.056
2.066
2.066
2.272
2.273
19.091
22.500
22.170
TST-12-D
1
0.444
0.707
0.707
0.926
0.926
4.560
4.551
0.796
0.792
0.792
0.873
0.875
7.400
9.077
9.333
TST-01-R
2
4.833
6.769
6.769
9.077
9.077
49.341
49.232
7.409
7.348
7.348
8.333
8.333
58.000
73.077
69.231
TST-02-R
2
4.500
7.500
7.500
10.125
10.125
79.587
79.587
7.625
7.625
7.625
8.294
8.294
80.769
73.333
73.333
TST-03-R
2
4.792
6.692
6.692
9.231
9.231
51.297
51.240
7.409
7.348
7.348
8.125
8.333
53.968
60.000
65.217
TST-04-R
2
5.000
7.333
7.333
10.250
10.250
23.996
23.996
7.167
7.167
7.167
7.844
7.931
54.902
61.842
60.317
TST-05-R
2
5.105
6.800
6.800
10.000
10.000
7.073
7.073
7.278
7.278
7.278
7.955
8.471
58.333
63.333
65.957
TST-06-R
2
5.143
6.333
6.333
9.667
9.667
22.732
22.312
6.591
6.591
6.591
6.704
6.952
31.148
25.714
28.814
TST-07-R
2
5.560
9.000
9.000
13.500
13.500
4.528
4.601
5.643
5.516
5.516
5.415
5.439
18.182
6.034
6.034
TST-08-R
2
5.222
7.000
7.000
9.667
9.667
66.531
62.595
7.286
7.286
7.286
8.500
8.400
65.000
84.615
63.636
TST-09-R
2
4.444
6.455
6.455
8.455
8.455
0.818
0.818
7.750
7.750
7.750
8.400
8.429
81.818
87.500
87.097
TST-10-R
2
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
TST-11-R
2
4.684
7.688
7.667
11.062
11.133
42.052
42.210
8.118
8.167
8.167
9.167
9.217
79.592
86.957
89.231
TST-12-R
2
4.636
7.765
7.765
10.176
10.176
25.000
25.000
7.750
7.762
7.762
8.217
8.217
74.359
91.892
91.429
TST-01-D
2
4.108
5.754
5.754
7.715
7.715
41.940
41.847
6.298
6.246
6.246
7.083
7.083
49.300
62.115
58.846
TST-02-D
2
3.150
5.250
5.250
7.088
7.088
55.711
55.711
5.338
5.338
5.338
5.806
5.806
56.538
51.333
51.333
TST-03-D
2
2.636
3.681
3.681
5.077
5.077
28.213
28.182
4.075
4.041
4.041
4.469
4.583
29.682
33.000
35.869
TST-04-D
2
2.000
2.933
2.933
4.100
4.100
9.598
9.598
2.867
2.867
2.867
3.138
3.172
21.961
24.737
24.127
TST-05-D
2
1.276
1.700
1.700
2.500
2.500
1.768
1.768
1.820
1.820
1.820
1.989
2.118
14.583
15.833
16.489
TST-06-D
2
0.514
0.633
0.633
0.967
0.967
2.273
2.231
0.659
0.659
0.659
0.670
0.695
3.115
2.571
2.881
TST-07-D
2
4.726
7.650
7.650
11.475
11.475
3.849
3.911
4.797
4.689
4.689
4.603
4.623
15.455
5.129
5.129
TST-08-D
2
3.655
4.900
4.900
6.767
6.767
46.572
43.817
5.100
5.100
5.100
5.950
5.880
45.500
59.231
44.545
TST-09-D
2
2.444
3.550
3.550
4.650
4.650
0.450
0.450
4.263
4.263
4.263
4.620
4.636
45.000
48.125
47.903
TST-10-D
2
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
TST-11-D
2
1.171
1.922
1.917
2.766
2.783
10.513
10.553
2.030
2.042
2.042
2.292
2.304
19.898
21.739
22.308
TST-12-D
2
0.464
0.776
0.776
1.018
1.018
2.500
2.500
0.775
0.776
0.776
0.822
0.822
7.436
9.189
9.143
TL5 WFD
AWIC(Sp)
McFarland
TL1 AWIC(Fam)
TST-01-R
Site ID
TL4 WFD
AWIC(Sp)
McFarland
Season Code
Spring
Reference
Degraded
Summer
Reference
Degraded
20
TL5 PSI(Sp)
TL4 PSI(Sp)
TL3 PSI(Fam)
TL5 LIFE(Sp)
TL4 LIFE(Sp)
TL3 LIFE(Fam)
(DistFam)
TL2 LIFE(Fam)
(DistFam)
TL1/2 LIFE(Fam)
(CompFam)
TL5 SEPA % Acid
Sensitive Taxa
TL4 SEPA % Acid
Sensitive Taxa
TL5 WFD
AWIC(Sp)
McFarland
TL4 WFD
AWIC(Sp)
McFarland
TL5 AWIC(Sp)
Murphy
TL4 AWIC(Sp)
Murphy
TL1 AWIC(Fam)
Site ID
Season Code
Autumn
Reference
TST-01-R
3
4.923 6.846 6.846
9.538
9.538
21.145 21.145
7.333 7.333 7.333 8.400 8.375
62.264 85.185 79.167
TST-02-R
3
5.000 7.500 7.500
10.875
10.875
82.877 82.877
6.895 6.895 6.895 8.227 8.600
49.020 56.364 67.391
TST-03-R
3
4.583 6.615 6.615
9.000
9.000
43.691 43.275
7.304 7.304 7.304 7.889 8.083
58.065 65.517 68.627
TST-04-R
3
4.962 7.200 7.143
10.067
10.000
20.841 20.841
7.769 7.769 7.769 8.059 8.367
66.071 70.130 75.862
TST-05-R
3
5.174 7.200 7.200
10.600
10.600
14.317 14.305
6.957 6.840 6.840 7.382 7.633
39.062 49.451 49.367
TST-06-R
3
5.120 6.889 6.889
10.111
10.111
34.361 34.134
6.680 6.680 6.680 7.222 7.565
33.871 33.803 37.705
TST-07-R
3
5.609 9.000 9.000
13.000
13.000
0.896
5.800 5.560 5.560 5.485 5.548
16.418
TST-08-R
3
4.727 5.800 5.800
7.000
7.000
14.511 14.286
7.778 7.778 7.778 8.714 8.833
68.182 77.778 68.421
TST-09-R
3
4.000 5.789 5.789
7.526
7.526
16.491 16.491
TST-10-R
3
3.750 5.857 5.857
7.571
7.571
TST-11-R
3
4.045 6.720 6.667
9.080
TST-12-R
3
4.481 6.826 6.826
TST-01-D
3
TST-02-D
3
TST-03-D
0.895
4.819
3.659
7.867 7.867 7.867 8.682 8.714
83.333 97.727 97.674
1.132
7.091 7.091 7.091 8.417 8.455
73.077 85.000 84.211
9.042
34.455 34.439
8.100 8.143 8.143 8.968 9.000
75.439 89.873 91.549
9.043
9.043
37.400 37.400
7.560 7.577 7.577 8.586 8.607
71.154 90.323 92.308
4.185 5.819 5.819
8.107
8.107
17.973 17.973
6.233 6.233 6.233 7.140 7.119
52.924 72.407 67.292
3.500 5.250 5.250
7.613
7.613
58.014 58.014
4.827 4.827 4.827 5.759 6.020
34.314 39.455 47.174
3
2.521 3.638 3.638
4.950
4.950
24.030 23.801
4.017 4.017 4.017 4.339 4.446
31.936 36.034 37.745
TST-04-D
3
1.985 2.880 2.857
4.027
4.000
8.336
8.336
3.108 3.108 3.108 3.224 3.347
26.428 28.052 30.345
TST-05-D
3
1.294 1.800 1.800
2.650
2.650
3.579
3.576
1.739 1.710 1.710 1.846 1.908
9.766 12.363 12.342
TST-06-D
3
0.512 0.689 0.689
1.011
1.011
3.436
3.413
0.668 0.668 0.668 0.722 0.757
3.387
3.380
3.771
TST-07-D
3
4.768 7.650 7.650
11.050
11.050
0.761
0.762
4.930 4.726 4.726 4.662 4.716
13.955
4.096
3.110
TST-08-D
3
3.309 4.060 4.060
4.900
4.900
10.158 10.000
5.445 5.445 5.445 6.100 6.183
47.727 54.445 47.895
TST-09-D
3
2.200 3.184 3.184
4.139
4.139
9.070
9.070
4.327 4.327 4.327 4.775 4.793
45.833 53.750 53.721
TST-10-D
3
1.500 2.343 2.343
3.028
3.028
0.472
0.453
2.836 2.836 2.836 3.367 3.382
29.231 34.000 33.684
TST-11-D
3
1.011 1.680 1.667
2.270
2.261
8.614
8.610
2.025 2.036 2.036 2.242 2.250
18.860 22.468 22.887
TST-12-D
3
0.448 0.683 0.683
0.904
0.904
3.740
3.740
0.756 0.758 0.758 0.859 0.861
1.181
Degraded
21
7.115
9.032
9.231
Season Code
TL2 SPEAR(Fam)
%
TL4 SPEAR(Sp) %
TL5 SPEAR(Sp) %
TL4 CCI
TL5 CCI
TST-01-R
1
50.826
44.352
53.455
17.818
17.818
TST-02-R
1
55.179
56.564
59.371
16.800
16.800
TST-03-R
1
37.100
32.760
44.640
6.000
5.739
TST-04-R
1
47.228
42.921
51.305
12.115
11.591
TST-05-R
1
22.700
21.223
28.413
8.600
8.409
TST-06-R
1
28.756
33.532
38.908
13.323
12.542
TST-07-R
1
18.182
21.216
24.801
16.234
16.022
TST-08-R
1
28.478
41.777
54.572
1.200
1.200
TST-09-R
1
66.144
60.177
60.750
9.375
9.375
TST-10-R
1
37.404
23.368
27.622
5.471
5.250
TST-11-R
1
62.106
52.891
60.615
11.000
6.158
TST-12-R
1
61.869
63.781
64.359
11.000
11.000
TST-01-D
1
43.202
37.699
45.437
15.145
15.145
TST-02-D
1
38.625
39.595
41.560
11.760
11.760
TST-03-D
1
20.405
18.018
24.552
3.300
3.156
TST-04-D
1
18.891
17.168
20.522
4.846
4.636
TST-05-D
1
5.675
5.306
7.103
2.150
2.102
TST-06-D
1
2.876
3.353
3.891
1.332
1.254
TST-07-D
1
15.455
18.034
21.081
13.799
13.619
TST-08-D
1
19.935
29.244
38.200
0.840
0.840
TST-09-D
1
36.379
33.097
33.413
5.156
5.156
TST-10-D
1
14.962
9.347
11.049
2.188
2.100
TST-11-D
1
15.527
13.223
15.154
2.750
1.540
TST-12-D
1
6.187
6.378
6.436
1.100
1.100
TST-01-R
2
59.967
54.503
61.544
12.200
11.667
TST-02-R
2
44.442
41.212
40.980
17.733
17.733
TST-03-R
2
33.121
25.082
34.113
4.950
4.833
TST-04-R
2
39.479
39.002
45.536
11.129
11.071
TST-05-R
2
25.408
22.551
25.239
5.714
5.250
TST-06-R
2
15.538
15.729
20.289
4.957
4.579
TST-07-R
2
18.785
17.464
20.442
12.950
13.103
TST-08-R
2
29.634
23.498
33.328
1.000
1.000
TST-09-R
2
48.336
40.523
46.377
9.286
9.286
TST-10-R
2
null
null
null
null
null
TST-11-R
2
58.874
56.473
58.750
5.842
5.842
TST-12-R
2
46.875
44.212
48.465
9.500
9.500
TST-01-D
2
50.972
46.328
52.312
10.370
9.917
TST-02-D
2
31.109
28.848
28.686
12.413
12.413
TST-03-D
2
18.217
13.795
18.762
2.723
2.658
TST-04-D
2
15.792
15.601
18.214
4.452
4.428
TST-05-D
2
6.352
5.638
6.310
1.429
1.313
TST-06-D
2
1.554
1.573
2.029
0.496
0.458
TST-07-D
2
15.967
14.844
17.376
11.008
11.138
TST-08-D
2
20.744
16.449
23.330
0.700
0.700
TST-09-D
2
26.585
22.288
25.507
5.107
5.107
TST-10-D
2
0.000
0.000
0.000
0.000
0.000
TST-11-D
2
14.719
14.118
14.688
1.461
1.461
TST-12-D
2
4.688
4.421
4.847
0.950
0.950
Site ID
Spring
Reference
Degraded
Summer
Reference
Degraded
22
TL4 CCI
47.239
10.435
9.773
45.915 39.175
43.239
20.000
20.632
TST-03-R
3
32.553 25.090
31.237
14.609
14.667
TST-04-R
3
40.109 34.659
43.678
10.806
10.000
TST-05-R
3
19.186 21.716
24.746
8.971
8.448
TST-06-R
3
27.263 28.993
29.615
9.800
9.773
TST-07-R
3
22.353 21.769
24.459
14.875
14.933
TST-08-R
3
46.580 43.844
52.606
1.000
1.000
TST-09-R
3
69.892 68.249
71.528
11.053
11.053
TST-10-R
3
54.503 50.644
52.618
14.000
14.000
TST-11-R
3
58.180 54.263
58.103
11.923
11.923
TST-12-R
3
59.933 57.354
58.728
11.800
11.250
TST-01-D
3
41.429 34.857
40.153
8.870
8.307
TST-02-D
3
32.141 27.423
30.267
14.000
14.442
TST-03-D
3
17.904 13.800
17.180
8.035
8.067
TST-04-D
3
16.044 13.864
17.471
4.322
4.000
TST-05-D
3
4.797
5.429
6.187
2.243
2.112
TST-06-D
3
2.726
2.899
2.962
0.980
0.977
TST-07-D
3
19.000 18.504
20.790
12.644
12.693
TST-08-D
3
32.606 30.691
36.824
0.700
0.700
TST-09-D
3
38.441 37.537
39.340
6.079
6.079
TST-10-D
3
21.801 20.258
21.047
5.600
5.600
TST-11-D
3
14.545 13.566
14.526
2.981
2.981
TST-12-D
3
5.873
1.180
1.125
TL5 CCI
TL5 SPEAR(Sp) %
48.740 41.008
3
TL2 SPEAR(Fam)
%
3
TST-02-R
Season Code
TST-01-R
Site ID
Autumn
TL4 SPEAR(Sp) %
Reference
Degraded
5.993
5.735
23
24

the Testing RICT predictions of expected values using an

Transcription

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