TY - JOUR
T1 - Characterization of freshwater pearl mussel (Margaritifera margaritifera) riverine habitat using River Habitat Survey data
AU - Hastie, L. C.
AU - Cooksley, S. L.
AU - Scougall, F.
AU - Young, M. R.
AU - Boon, P. J.
AU - Gaywood, M. J.
PY - 2003/5
Y1 - 2003/5
N2 - 1. The feasibility of using River Habitat Survey (RHS) data to describe freshwater pearl mussel (Margaritifera margaritifera) macrohabitat in the River Spey, north-east Scotland, was investigated. 2. Mussels were found to be positively associated with a number of RHS variables. These included: boulder/cobble river bed substrates, broken/unbroken standing waves (channel flow types), aquatic liverworts/mosses/lichens and broadleaf/mixed woodland/bankside tree cover. Negative associations with gravel-pebble/silt substrates and emergent reeds/sedges/herbs were also found. 3. Two binary logistic regression models, based on seven and four variables, respectively, were constructed in order to predict the presence/absence of mussels at any given site. Predictive success rates of 83% and 78% were achieved. 4. Another binary logistic regression model, based on four variables, was constructed in order to predict the occurrence of 'optimal' M. margaritifera habitat (overall mussel densities ≥ 1 m-2). A predictive success rate of 83% was achieved. 5. The results indicate two potentially important applications of RHS for the conservation management of M. margaritifera: (1) for monitoring the effects of physical changes on extant mussel beds (and predicting their effects on mussel populations), and (2) for determining the habitat suitability of historically occupied sites for re-introductions.
AB - 1. The feasibility of using River Habitat Survey (RHS) data to describe freshwater pearl mussel (Margaritifera margaritifera) macrohabitat in the River Spey, north-east Scotland, was investigated. 2. Mussels were found to be positively associated with a number of RHS variables. These included: boulder/cobble river bed substrates, broken/unbroken standing waves (channel flow types), aquatic liverworts/mosses/lichens and broadleaf/mixed woodland/bankside tree cover. Negative associations with gravel-pebble/silt substrates and emergent reeds/sedges/herbs were also found. 3. Two binary logistic regression models, based on seven and four variables, respectively, were constructed in order to predict the presence/absence of mussels at any given site. Predictive success rates of 83% and 78% were achieved. 4. Another binary logistic regression model, based on four variables, was constructed in order to predict the occurrence of 'optimal' M. margaritifera habitat (overall mussel densities ≥ 1 m-2). A predictive success rate of 83% was achieved. 5. The results indicate two potentially important applications of RHS for the conservation management of M. margaritifera: (1) for monitoring the effects of physical changes on extant mussel beds (and predicting their effects on mussel populations), and (2) for determining the habitat suitability of historically occupied sites for re-introductions.
KW - Conservation
KW - Distribution
KW - Freshwater pearl mussel
KW - Macrohabitat
KW - River Habitat Survey
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U2 - 10.1002/aqc.560
DO - 10.1002/aqc.560
M3 - Article
AN - SCOPUS:0037910403
SN - 1052-7613
VL - 13
SP - 213
EP - 224
JO - Aquatic Conservation: Marine and Freshwater Ecosystems
JF - Aquatic Conservation: Marine and Freshwater Ecosystems
IS - 3
ER -