Great Lakes coastal fish habitat classification and assessment

Journal of Great Lakes Research(2018)

Cited 17|Views14
No score
Abstract
Basin-scale assessment of fish habitat in Great Lakes coastal ecosystems would increase our ability to prioritize fish habitat management and restoration actions. As a first step in this direction, we identified key habitat factors associated with highest probability of occurrence for several societally and ecologically important coastal fish species as well as community metrics, using data from the Great Lakes Aquatic Habitat Framework (GLAHF), Great Lakes Environmental Indicators (GLEI) and Coastal Wetland Monitoring Program (CWMP). Secondly, we assessed whether species-specific habitat was threatened by watershed-level anthropogenic stressors. In the southern Great Lakes, key habitat factors for determining presence/absence of several species of coastal fish were chlorophyll concentrations, turbidity, and wave height, whereas in the northern ecoprovince temperature was the major habitat driver for most of the species modeled. Habitat factors best explaining fish richness and diversity were bottom slope and chlorophyll a. These models could likely be further improved with addition of high-resolution submerged macrophyte complexity data which are currently unavailable at the basin-wide scale. Proportion of invasive species was correlated primarily with increasing maximum observed inorganic turbidity and chlorophyll a. We also demonstrate that preferred habitat for several coastal species and high-diversity areas overlap with areas of high watershed stress. Great Lakes coastal wetland fish are a large contributor to ecosystem services as well as commercial and recreational fishery harvest, and scalable basin-wide habitat models developed in this study may be useful for informing management actions targeting specific species or overall coastal fish biodiversity.
More
Translated text
Key words
Coastal wetlands,Invasive fish habitat models,Fish biodiversity models,Anthropogenic threats,Habitat variability,Random Forests
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined