Zooplankton-phytoplankton biomass and diversity relationships in the Great Lakes.

Quantifying the relationship between phytoplankton and zooplankton may offer insight into zooplankton sensitivity to shifting phytoplankton assemblages and the potential impacts of producer-consumer decoupling on the rest of the food web. We analyzed 18 years (2001-2018) of paired phytoplankton and zooplankton samples collected as part of the United States Environmental Protection Agency (U.S. EPA) Great Lakes Biology Monitoring Program to examine both the long-term and seasonal relationships between zooplankton and phytoplankton across all five Laurentian Great Lakes. We also analyzed effects of phytoplankton diversity on zooplankton biomass, diversity, and predator-prey (zooplanktivore/grazer) ratios. Across the Great Lakes, there was a weak positive correlation between total algal biovolume and zooplankton biomass in both spring and summer. The relationship was weaker and not consistently positive within individual lakes. These trends were consistent over time, providing no evidence of increasing decoupling over the study period. Zooplankton biomass was weakly negatively correlated with algal diversity across lakes, whereas zooplankton diversity was unaffected. These relationships did not change when we considered only the edible phytoplankton fraction, possibly due to the high correlation between total and edible phytoplankton biovolume in most of these lakes. Lack of strong coupling between these producer and consumer assemblages may be related to lagging responses by the consumers, top-down effects from higher-level consumers, or other confounding factors. These results underscore the difficulty in predicting higher trophic level responses, including zooplankton, from changes in phytoplankton assemblages.

Guiding riparian management in a transboundary watershed through high resolution spatial statistical network models.

The United States Environmental Protection Agency and the Houlton Band of Maliseet Indians (HBMI) built a stream temperature spatial statistical network (SSN) model for the Meduxnekeag Watershed. The headwaters of the Meduxnekeag Watershed are in Maine, United States of America and the outlet is in New Brunswick, Canada, creating an additional challenge because many datasets are constrained to political boundaries. The release of the High-Resolution National Hydrology Dataset Plus included transboundary watersheds and enabled creation of fine resolution (1:24,000) SSN temperature models consistent with management scales for riparian buffers. SSN models were developed for July, August, and September median stream temperatures and the growing season maximum (GSM). Fitted SSN models had relatively high R2 values (0.88-0.96) and all final models included significant parameters for shade-attenuated solar radiation, reference flow, air temperature, and bankfull depth or width. Fitted models predicted stream temperatures during a dry (2010) and wet (2011) year. Monthly models predicted the fewest cold water (<19.0 °C) reaches in July with 28% in the dry and 68% in the wet year. September had >99% cold water reaches, and August results were intermediate between July and September. GSM predictions found 81% of stream reaches could not support salmonid survival (>27.0 °C) in the dry year and 59% of the reaches were warmwater (22.5-27.0 °C) in the wet year. The model was used to predict stream temperatures following restoration scenarios of a forested 30-m or 90-m buffer of stream segments bordered by agricultural or developed land. The restoration scenarios expanded cold water habitat based on monthly median temperatures and decreased the habitat area with GSM above survival thresholds, with little difference in effectiveness of the two buffer widths. These results will guide riparian restoration projects by the HBMI to expand habitat for cold water fishes.