Intercalibration of RIVPACS for
the Irish Ecoregion
WFD16
April 2005
EXECUTIVE SUMMARY
RIVPACS (River Invertebrate Prediction and Classification system) is a
software package devised by scientists at the Centre for Ecology and
Hydrology (CEH, Dorset) formerly the Institute of Freshwater Ecology.
The system produces a site-specific prediction of the macroinvertebrate
fauna to be expected in the absence of environmental stress based on a
combination of geographical, physical and chemical features for that
site.
RIVPACS III was developed in 1995 and included a 614 reference site
database for Great Britain and 70 reference sites for Northern Ireland.
This was further expanded to include an additional 40 Northern Ireland
sites resulting in the final Northern Ireland RIVPACS classification
consisting of 110 sites (Wright et al., 1995).
Recent research at University College Dublin (UCD) assessed a wide
array of reference sites with detailed macroinvertebrate inventories
which have the potential to develop a predictive system conceptually
similar to RIVPACS. The main objective of this study was to produce a
collated macroinvertebrate species database for the entire island and
investigate whether the development of a single prototype system which
uses RIVPACS protocols could be used for WFD reporting for the Irish
Ecoregion.
Macroinvertebrate family and presence/absence data for three seasons
spring, summer and autumn for the 110 Northern Ireland sites were
supplied by J. Davy-Bowker (CEH). The environmental dataset was
supplied by Imelda O’Neill (EHS) and Chris Burns (EHS). The
macroinvertebrate data for the 97 Republic of Ireland sites were
supplied by Catherine Bradley and Mary Kelly-Quinn (UCD). The
environmental data were also supplied by Catherine Bradley and Martin
McGarrigle (EPA).
A total of 519 macroinvertebrate taxa representing 106 families were
recorded in the combined dataset. Representative taxa from all of the
major aquatic macroinvertebrate groups were present in each of the
datasets. Over 300 of the taxa identified to species/genus level
occurred in less than 5% (10 sites) of the total sites indicating the
presence of a complex noisy dataset.
Differences were evident at the species/genus level between the two
datasets. In particular, the three stoneflies Protonemura meyeri
(Pictet), Leuctra hippopus (Kempny) and Siphlonoperla torrentium
(Pictet) which occurred in over 90% of the ROI sites had much lower
occurrences in the Northern Ireland dataset. Perla bipunctata Pictet
and the trichopteran Odontocerum albicorne (Scopoli) occurred in less
than 5% of the Northern Ireland sites but occurred in over 50% of the
ROI sites.
This research project highlighted several issues that need to be
addressed before the development of a predictive model for the entire island could be
realised. The absence of normal distributions within several of the
environmental variables within the presently available dataset
confounded their potential use in any development of a predictive model
at this time.
TWINSPAN was used to generate a site classification using the
macroinvertebrate dataset. Two separate classification procedures were
carried out using the sum-option data consisting of the standardised
species data plus the family log category abundance data and the
max-option procedure consisting of the standardised species data plus
the maximum family categorical data for the combined spring and autumn
seasons.
Classification of the sum-option dataset resulted in the generation of
fourteen endgroups after four TWINSPAN divisions ranging in size from
one to 55 sites per group. High heterogeneity within each of the
endgroups however was apparent. The max-option classification which
emphasized the maximum seasonal family log category observed, generated
16 groupings ranging in size from 2 to 34 sites per group after four
division levels. Heterogeneity within the endgroups again was generally
high. The high number of endgroups produced in order to reach an
acceptable level of heterogeneity in both analyses is not preferable
when trying to
develop a predictive system. The small size of some of these endgroups
is also undesirable.
Multiple Discriminant Analysis was then performed to find combinations
of environmental variables that would best predict the defined site
groupings. Several problems occurred when the assumption of homogeneity
of covariance matrices between groups was not met. Five of the
environmental variables could not be normalised rendering them
inadequate for analysis. Variables that were highly correlated were
also removed.
The remaining environmental variables were not very successful in
predicting the membership of the sites to the groups within the
classifications. The issue of normality needs to be addressed for any
future development of a predictive system. The addition of more sites
in future analyses would be beneficial.
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N.B.
The report is available for download from the SNIFFER Website