This project examines how leadership within organizations (e.g., C-suite executives) influences organizational and sectoral responses to climate change. This includes prioritization of climate change responses within and beyond organizational boundaries, climate-oriented organizational leadership within and across sectors (e.g., public health, higher education), and the role of institutional leaders in driving change

Global mean sea level rise of ~3 mm/year during the last decade was likely the highest rate since 1900, and continues to accelerate. It is therefore critical that coastal communities begin to develop adaptive responses to changing shorelines. We will update local sea level rise projections along the Northeast US coastline using a probabilistic model of future sea level distribution, combined with analysis of local trends and extreme sea level events from tide gauge records, to create regionally-appropriate projections. A similar approach has already been successfully implemented for the state of Massachusetts. This project builds on previous work to improve the scale and continuity of the ice-sheet analysis, and spatially extending the framework to assess the vulnerability of the entire Northeast coastline

The forests of the Northeastern United States are home to some of the greatest diversity of nesting songbirds in the country. Climate change, shifts in natural disturbance regimes, and invasive species pose threats to forest habitats and bird species in the northeastern United States and represent major challenges to natural resource managers.   Although broad adaptation approaches have been suggested for sustaining forested habitats under global change, it is unclear how effective the implementation of these strategies at local and regional scales will be for maintaining habitat conditions for a broad suite of forest-dependent bird species over time. Moreover, given the diversity in forest stakeholders across the Northeast region, it is unclear if the adaptation science needs for these stakeholders are fully captured by existing adaptation recommendations

The northeastern U.S. is highly exposed to climate change; in fact, the rate of change is higher than most places on earth (Karmalkar and Bradley 2017). The forests of the Northeast CASC region, and the wildlife that inhabit them, are highly vulnerable to the effects of climate change.  In particular, the boreal forests, a biome that reaches from Alaska to the Northeast, and the northern hardwoods, including sugar maple and paper birch, are expected to be intolerant of climate warming. Likewise, many of the birds, mammals, amphibians, fish, and insects that inhabit these forest ecosystems are at their southern range edges here and are considered sensitive to climate change. Furthermore, local species’ adaptive capacity is limited by habitat fragmentation, high rates of invasive species, and other stressors. There is considerable uncertainty with respect to the magnitude and direction of future changes, particularly with respect to interactions with changes in land use and land management, as well as novel interactions amongst co-occurring species. Thus, a focus on climate adaptation in northern forest ecosystems, including evaluations of the impacts of particular actions, is critical. 

Downscaling is the process of making a coarse-scale global climate model into a finer resolution in order to capture some of the localized detail that the coarse global models cannot resolve. There are two general approaches of downscaling: dynamical and statistical. Within those, many dynamical models have been developed by different institutions, and there are a number of statistical algorithms that have been developed over the years. Many past studies have evaluated the performance of these two broad approaches of downscaling with respect to climate variables (e.g., temperature, precipitation), but few have translated these evaluations to ecological metrics that managers use to make decisions in planning for climate change. This study uses maple syrup production as a case study for evaluating how these two downscaling techniques perform in terms of projecting changes in the tapping season

WICCI is a grassroots effort to consolidate information about climate change impacts in Wisconsin.  Its first report, released in 2010, has played a critical role in elevating climate change within dialogue about environmental management across the state, and serves as the go-to resource for agencies, NGOs, and the public.  We are now working to update that document, focusing on new research in aquatic and other ecosystems, as well as case studies of impacts on Wisconsin's ecosystem services. The goals of this project are in part to 1) Compile a synthesis of climate change impacts on people and natural resources of Wisconsin.  2) Provide public education about the seriousness of climate change impacts.  3) Establish accessible and credible reference for policy makers

The first phase of this project developed an online platform to enable rapid sharing and cataloging of silviculture case studies documenting adaptive forest management approaches across MI, MN, Ontario, and WI.  The goal was to create a clearinghouse of information for forest managers across the region to disseminate ideas on addressing emerging issues and tracking effectiveness of a given approach.  The Prescription Library serves as the basis for regional continuing education offerings for natural resource professionals throughout Michigan, Minnesota, Ontario, and Wisconsin. The project initiated in late March 2014 and now shares over 120 case studies in adaptive silviculture through the Prescription Library platform. These case studies cover Minnesota, Ontario, and Wisconsin and demonstrate a range of silvicultural approaches to address current and emerging issues related to the sustainable management of forests in the Great Lakes region.

A reconnaissance study distinguishes coastal areas of the northeastern U.S. (approx. Virginia to Maine) that will experience an inundation-dominated response to sea-level rise from those that will respond dynamically due to physical and bio-physical sedimentation and erosion processes. Areas that will be dominated by inundation include urban regions of intense development and/or coastal engineering, as well as bedrock coasts. Areas that will respond dynamically include beaches, unconsolidated cliffs, barrier islands, and wetlands. Distinguishing which processes are relevant to sea-level rise impacts in these areas aids prioritization of scientific research and decision support efforts. Also see Dr. Robert Thieler's A Research and Decision Support Framework to Evaluate Sea-level Rise Impacts in the Northeastern U.S. Tools and Products Sea Level Rise Viewer https://coast.noaa.gov/digitalcoast/tools/slr

Using Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP3 data, we are developing a range of projections for the Eastern U.S.  We are also developing extreme event projections for stakeholder-relevant metrics (e.g., days over 90 °F, days below 32 °F, and days with over 1 inch of precipitation) based on CMIP5 models and North American Regional Climate Change Assessment Program (NARCCAP) dynamical downscaling.  We are also evaluating the performance of these models over historical time periods. Current research thrusts include emphasis on extreme heat stress (heat plus humidity) events and the relationship between extreme minimum temperatures and Southern Pine Beetle range expansion in the Northeast U.S.   We are finding that small changes in average conditions are associate with large changes in the frequency and intensity of extreme events

Historical climate data for the Midwestern U.S. show substantial regional variability in the occurrence of extreme rainfall events.  Climate projections for the region based on both statistically downscaled General Circulation Models and Regional Climate Models show significant inter-model variability in the magnitude and frequency of extreme rainfall events.  As a result, these climate projections cannot be used alone to adaptively manage water resources in a changing climate.  We believe that storm transposition provides an effective way to evaluate the vulnerability from extreme rainfall and flooding. We have reconstructed the 2008 storm that caused catastrophic damage across parts of south-central Iowa and Wisconsin.  We are currently using an existing hydrodynamic model of the Yahara Lakes (http://infosyahara.org/) to estimate the extent of damage that would have occurred had the storm been centered over the lakes