TY - JOUR
T1 - Applications of extensive survey techniques to describe freshwater pearl mussel distribution and macrohabitat in the River Spey, Scotland
AU - Hastie, L. C.
AU - Cooksley, S. L.
AU - Scougall, F.
AU - Young, M. R.
AU - Boon, P. J.
AU - Gaywood, M. J.
PY - 2004/12/15
Y1 - 2004/12/15
N2 - The spatial distribution and associated physical habitat of endangered freshwater pearl mussels (Margaritifera margaritifera) in a 145 km stretch of the River Spey, northeast Scotland, were investigated. The overall size of the Spey M. margaritifera population was estimated to be in the order of 10 million. Mussel distributions were compared with River Corridor Survey (RCS) macrohabitat data and found to be positively associated with coarse riverbed substrata, 'fast-flowing' waters, riparian woodland, and river bends; and negatively associated with shingle bars, flood barriers, 'slow-flowing' waters, eroding cliffs and aquatic macrophytes. Significant positive relationships between mussel density and channel slope, width and bank height, were also observed. Binary logistic regression models (based on four to six features) were used to predict the presence/absence of mussels or the occurrence of 'optimal' mussel habitat (i.e. mussel density > 1 m-2) at any given site. Overall predictive success rates of 79% and 78% were achieved, respectively. Discriminant function models (based on five variables) were also used, with predictive success rates of 78% and 88%, respectively.
AB - The spatial distribution and associated physical habitat of endangered freshwater pearl mussels (Margaritifera margaritifera) in a 145 km stretch of the River Spey, northeast Scotland, were investigated. The overall size of the Spey M. margaritifera population was estimated to be in the order of 10 million. Mussel distributions were compared with River Corridor Survey (RCS) macrohabitat data and found to be positively associated with coarse riverbed substrata, 'fast-flowing' waters, riparian woodland, and river bends; and negatively associated with shingle bars, flood barriers, 'slow-flowing' waters, eroding cliffs and aquatic macrophytes. Significant positive relationships between mussel density and channel slope, width and bank height, were also observed. Binary logistic regression models (based on four to six features) were used to predict the presence/absence of mussels or the occurrence of 'optimal' mussel habitat (i.e. mussel density > 1 m-2) at any given site. Overall predictive success rates of 79% and 78% were achieved, respectively. Discriminant function models (based on five variables) were also used, with predictive success rates of 78% and 88%, respectively.
KW - Macrohabitat
KW - Margaritifera
KW - Population
KW - River corridor survey
UR - http://www.scopus.com/inward/record.url?scp=11844259489&partnerID=8YFLogxK
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U2 - 10.1002/rra.808
DO - 10.1002/rra.808
M3 - Article
AN - SCOPUS:11844259489
SN - 1535-1459
VL - 20
SP - 1001
EP - 1013
JO - River Research and Applications
JF - River Research and Applications
IS - 8
ER -