Studying the impacts of climate on important ecological responses is a recent priority of monitoring programs throughout the Northeast. Established sampling protocols for data collection, whether to inform estimates of species abundance or occupancy, were designed to evaluate the effects of non-climate stressors (e.g., habitat conversion) and related management actions. Traditional modeling approaches may not accurately identify important relationships between species and climate nor elicit useful information on how these species will be impacted by climate change. Management decisions based on these traditional modeling approaches could have negative and unintended consequences on species and habitat conservation.
The goal of this project is to develop statistical methods to enhance the ability of monitoring programs to understand climate effects on fish and wildlife. Focusing on riverine smallmouth bass and streamside forest bird communities in the Northeast, this project will:
(1) develop statistical models that account for and quantify the impacts of sampling design on understanding the relationship between climate and species abundance or occupancy, and
(2) develop an optimal sampling design that enables monitoring programs to track climate change impacts and provide early indicators for fish and wildlife responses.
With partners at both state and federal agencies, these approaches can be extended to support existing monitoring programs of other fish, wildlife, and habitats in making informed management decisions in the face of climate change. Project results will augment monitoring programs that are collecting critical data used to directly inform regulatory and policy decisions.
