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Linking watershed and microhabitat characteristics: effects on production of A tlantic salmonids ( S almo salar and S almo trutta )
Author(s) -
Foldvik Anders,
Einum Sigurd,
Finstad Anders G.,
Ugedal Ola
Publication year - 2017
Publication title -
ecology of freshwater fish
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.667
H-Index - 55
eISSN - 1600-0633
pISSN - 0906-6691
DOI - 10.1111/eff.12272
Subject(s) - salmo , electrofishing , productivity , biomass (ecology) , environmental science , drainage basin , population , brown trout , habitat , ecology , trout , spatial variability , watershed , hydrology (agriculture) , geography , fishery , biology , fish <actinopterygii> , statistics , mathematics , cartography , demography , macroeconomics , sociology , economics , geotechnical engineering , machine learning , computer science , engineering
Abstract The spatial scale of environmental factors influencing population dynamics ranges from microhabitat to continental or even global scales. Integration of multiple spatial scales is important in order to understand links between environmental variation and population processes. In the present study, we investigate how multiscale drivers influence the production of stream‐rearing A tlantic salmonids ( A tlantic salmon, S almo salar L. and brown trout, S almo trutta L.) measured in terms of abundance. Variation in juvenile production was studied using data from single‐pass electrofishing surveys (measured as biomass per m 2 ) from nine rivers. These data were combined with habitat data ranging from an important in‐stream microhabitat variable (shelter availability) to properties of the catchment. Variation in productivity within and among rivers was affected by both properties of in‐stream habitat and catchment properties. Shelter availability and the proportion of the catchment consisting of cultivated land and lakes influenced biomass positively, while catchment area had the opposite effect. For a different set of rivers ( N = 20), river gradient and catchment area were shown to positively affect the amount of shelter. Finally, the variables identified in the two preceding analysis were included in the analysis of population productivity using catch statistics from 160 rivers. The proportion of cultivated land and lakes, estimated shelter availability were found to have positive effects. In addition, temperature had a positive effect, while river width had a negative effect. This study shows that combining multiple‐scale environmental factors can explain a substantial proportion of variation in population productivity among and within the populations of A tlantic salmonids.