Peter C. Esselman
Catherine M. Riseng
Ashley K. Elgin
Mark D. Rowe
Jennifer M. Morrison
2024
<p><span>Invasive dreissenid mussels (</span><i>Dreissena polymorpha</i><span> and </span><i>Dreissena rostriformis bugensis</i><span>) have altered Great Lakes ecosystems through a multitude of effects on benthic habitats, food web structure, and nutrient cycling. This study explores whether spatially continuous geographic data of environmental factors can be utilized to predict </span><i>Dreissena</i><span> spp. spatial distributions on a lake-wide scale. Categorical variables were also assessed for significant relationships with </span><i>Dreissena</i><span> spp. biomass. Point observations from the 2017 Lake Huron benthic survey under the Cooperative Science and Monitoring Initiative (CSMI) were utilized for in situ measurements of dreissenid presence and biomass at 119 sites across Lake Huron. Basin, bathymetric zone, and tributary influence were found to have statistically significant relationships to dreissenid biomass. A boosted regression tree (BRT) model (ROC score 0.707) was developed to spatially predict dreissenid presence probability across Lake Huron from six environmental explanatory variables: April, May, and October chlorophyll, June dissolved organic carbon, January bottom temperature, and May bottom temperature. The importance of food availability and bottom temperature illuminated relationships between dreissenid mussels and periods of benthic-pelagic mixing in the spring and fall seasons. Future models could be improved through advancements in survey technology for improved geographic characterization of mussel habitat characteristics and environmental constraints.</span></p>
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10.1016/j.jglr.2024.102369
en
Elsevier
Predicting Lake Huron Dreissena spp. spatial distribution patterns from environmental characteristics
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