Current and future hydrologic variability is a major driver underlying large-scale management and modification of inland waters and river systems. In a climate-altered future, identifying and implementing management actions that mitigate anticipated flow regime extremes will be an important component of climate adaptation strategies. These concerns will be particularly focused on extreme flows (floods and droughts) that have ecological, social, and economic importance, and whose impacts are inversely proportion to their frequency. Climate warming is expected to increase the frequency of extreme precipitation. It is critical for natural resources conservation that responses to these risks incorporate ‘green’ infrastructure which potentially benefit both ecosystems and human infrastructure

Climate change-driven shifts in distribution and abundance are documented in many species. However, in order to better predict species responses, managers are seeking to understand the mechanisms that are driving these changes, including any thresholds that might soon be crossed. We leveraged the research that has already been supported by the Northeast Climate Adaptation Science Center (NE CASC) and its partners and used the latest modeling techniques combined with robust field data to examine the impact of specific climate variables, land use change, and species interactions on the future distribution and abundance of species of conservation concern. Moreover, we documented biological thresholds related to climate variability and change for critical species in the Northeastern and Midwestern U.S. Our objectives were to identify the primary drivers (e.g

There is growing evidence that headwater stream ecosystems are especially vulnerable to changing climate and land use, but their conservation is challenged by the need to address the threats at a landscape scale, often through coordination with multiple management agencies and landowners. This project sought to provide an example of cooperative landscape decision-making by addressing the conservation of headwater stream ecosystems in the face of climate change at the watershed scale. Predictive models were built for critical resources to examine the effects of the potential alternative actions on the objectives, taking account of climate effects and examining whether there were key uncertainties that impede decision making.  Results provide decision analyses that are (1) relevant to the management partners in question; (2) emblematic of landscape-scale cooperative decisions; and (3) sensitive to the practical consequences of climate change