Publications

Objective Managing freshwater fisheries in warming lakes is challenging because climate change impacts anglers, fish, and their interactions.Methods We integrated recent models of current and future lake temperatures with recreational fisheries catch data from 587 lakes in three north-central U.S. states (Michigan, Minnesota, and Wisconsin) to evaluate how the thermal composition of...

Onsite wastewater treatment systems (OWTS) are a major source of excess nutrients and co-pollutants in watersheds across the United States. In Barnstable County (Cape Cod), Massachusetts, effluent from septic systems and cesspools contributes approximately 80% of the controllable reactive nitrogen (N) load to numerous impaired estuaries and degrades water quality in the region's sole...

Nest-site fidelity is a common strategy in birds and is believed to be adaptive due to familiarity with local conditions. Returning to previously successful nest sites (i.e., the win-stay lose-switch strategy) may be beneficial when habitat quality is spatially variable and temporally predictable; however, changes in environmental conditions may constrain dispersal decisions despite...

Coastal wetlands are hotspots of carbon sequestration, and their conservation and restoration can help to mitigate climate change. However, there remains uncertainty on when and where coastal wetland restoration can most effectively act as a Natural Climate Solution (NCS). Here, we synthesize current understanding to illustrate the requirements for coastal wetland restoration to benefit...

Accurate estimates of methylmercury (MeHg) exposure are valuable to actionably assess risk and protect wildlife and human health. MeHg trophic transfer is a critical driver of risk: MeHg is generally biomagnified by a factor of 8.3 ± 7.5 from one trophic level to the next, averaged across freshwater communities (mean ± standard deviation). This variability can produce disparate risks...

Stream salinization is a global issue, yet few models can provide reliable salinity estimates for unmonitored locations at the time scales required for ecological exposure assessments. Machine learning approaches are presented that use spatially limited high-frequency monitoring and spatially distributed discrete samples to estimate the daily stream-specific conductance across a...