The USGS National Climate Adaptation Science Center (NCASC) is currently engaged in an Ecological Drought initiative, focused on understanding the impacts of drought on natural ecosystems across the country. This project supported the Ecological Drought initiative by creating an Intermountain West Drought Social Science Synthesis Working Group. The goal of this working group was to investigate human dimensions of ecological drought across the intermountain west from a comparative, regional perspective. Throughout the Intermountain West, there has been significant investment in understanding how social factors influence manager and citizen experiences of drought in particular locations. Yet there is still a gap in knowledge of how human dimensions of drought impacts, planning, and resilience are similar and different across cases and regions. The working group engaged social scientists from federal agencies and universities to identify common trends in drought management across the Intermountain West to inform more effective drought preparedness and response across the region. Project outputs included two conference sessions, a typology manuscript to be submitted by the end of FY19, and the conceptual framing of a rapid assessment methodology that was subsequently developed into a standalone project.  

Drought is an inescapable reality in many regions, including much of the western United States. With climate change, droughts are predicted to intensify and occur more frequently, making the imperative for drought management even greater. Many diverse actors – including private landowners, business owners, scientists, non-governmental organizations (NGOs), and managers and policymakers within tribal, local, state, and federal government agencies – play multiple, often overlapping roles in preparing for and responding to drought. Managing water is, of course, one of the most important roles that humans play in both mitigating and responding to droughts; but, focusing only on “water managers” or “water management” fails to capture key elements related to the broader category of drought management. The respective roles played by those managing drought (as distinct from water managers), the interactions among them, and the consequences in particular contexts, are not well understood. Our team synthesized insights from 10 in-depth case studies to understand key facets of decision making about drought preparedness and response. We present a typology with four elements that collectively describe how decisions about drought preparedness and response are made (context and objective for a decision; actors responsible; choice being made or action taken; and how decisions interact with and influence other decisions). The typology provides a framework for system-level understanding of how and by whom complex decisions about drought management are made. Greater system-level understanding helps decision makers, program and research funders, and scientists to identify constraints to and opportunities for action, to learn from the past, and to integrate ecological impacts, thereby facilitating social learning among diverse participants in drought preparedness and response.

In 1969, researchers developed the first global circulation model (Ruttiman 2006); however, it was not until 2014 that modelers first attempted a global ecosystem and biodiversity model that included human pressures (i.e., the Madingley Model) (Harfoot et al. 2014). Other large-scale models of biodiversity exist, such as GLOBIO (Alkemade et al. 2009), but to date there are no well accepted global biodiversity models similar to global circulation models that can help guide global biodiversity policy development and targets. The lack of global biodiversity models compared to the extensive array of general circulation models provides a unique opportunity for climate, ecosystem, and biodiversity modeling experts to determine similarities and differences in modeling approaches to inform development of integrated global biodiversity modeling approaches. More accurate and comprehensive biodiversity models are needed to understand how countries individually and as a whole are progressing towards the internationally defined targets (e.g., Aichi Biodiversity Targets and Sustainable Development Goals) to inform global biodiversity conservation, monitoring, and sustainable use (Tittensor 2014). In addition, the scenarios and modeling summary from the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) identified a need for better assessment of biodiversity models and progress towards more global models. Collaborative approaches between the biodiversity and global climate modeling communities can provide information to advance biodiversity models and improve each community’s approaches to forecasting change. Collaboration can also help tighten the linkages between biodiversity and climate and land-use models as climate change and other anthropogenic stressors continue to threaten biodiversity and its ecosystem services. To address the need for improved large-scale biodiversity models, experts in biodiversity and climate modeling and remote sensing fields came together via a series of in-person workshops and virtual discussions. Our goals were to 1) identify strategies (both qualitative and quantitative) from climate models to be applied to large-scale biodiversity models, 2) to explore NASA and other remote sensing products to assist in global biodiversity modeling efforts and 3) to address and build on gaps and data needs to inform development of GEOBON Essential Biodiversity Variables (EBV) and tracking and development of the next generation of Aichi Biodiversity Targets and Sustainable Development Goals. The first in-person meeting was held in June 2017 with 20 in-person and remote participants in Reston, VA and a second in-person meeting in February 2018 with 18 in-person and remote participants in Tucson, AZ to address these objectives. Participants came from national and international academic institutions, government agencies, and non-governmental organizations and were from various stages in their careers. The workshop series resulted in three main outcomes, including a list of lessons learned and recommendations from those with expertise in climate modeling to address goal 1 above, a framework for assessment and refinement of diverse biodiversity models using remote sensing tools to address goal 1, 2, and 3 above, and lastly the development of a meta-conceptual biodiversity model to inform future model development and needs. Below is a detailed overview highlighting recommendations and outcomes of the workshop series.