Droughts are disproportionately impacting global dryland regions where ecosystem health and function are tightly coupled to moisture availability. Drought severity is commonly estimated using algorithms such as the standardized precipitation-evapotranspiration index (SPEI), which can estimate climatic water balance impacts at various hydrologic scales by varying computational length. However, the performance of these metrics as indicators of soil moisture dynamics at ecologically relevant scales, across soil depths, and in consideration of broader scale ecohydrological processes, requires more attention. In this study, we tested components of climatic water balance, including SPEI and SPEI computation lengths, to recreate multi-decadal and periodic soil-moisture patterns across soil profiles at 866 sites in the western United States. Modeling results show that SPEI calculated over the prior 12-months was the most predictive computation length and could recreate changes in moisture availability within the soil profile over longer periods of time and for annual recharge of deeper soil moisture stores. SPEI was slightly less successful with recreating spring surface-soil moisture availability, which is key to dryland ecosystems dominated by winter precipitation. Meteorological drought indices like SPEI are intended to be convenient and generalized indicators of meteorological water deficit. However, the inconsistent ability of SPEI to recreate ecologically relevant patterns of soil moisture at regional scales suggests that process-based models, and the larger data requirements they involve, remain an important tool for dryland ecohydrology.

Amphibians are a group of animals facing especially severe declines due to many factors including climate change and a common pathogen, the amphibian chytrid fungus. To make informed decisions about amphibians, wildlife managers need to identify species facing the greatest threats and the actions that will most effectively minimize impacts of those threats. Although some amphibian species are relatively well-studied, for most, data to inform management decisions are lacking. Therefore, tools to assist managers must be applicable to amphibian species across a range of data availability and susceptibility to climate change and other threats. In this project, researchers will determine which amphibians in the North Central region of the United States are at the greatest risk from the anticipated effects of climate change and other threats, such as disease. They will develop a decision framework for weighing tradeoffs among potential management actions and the anticipated impacts of those actions using both a data-deficient species and a species that is relatively data-rich, the Boreal Toad. This project will then use long-term monitoring information to develop a web application to guide management decisions for Boreal Toads, which are susceptible to amphibian chytrid fungus, likely to be affected by climate change, and are a species of concern for several states in the region. By coordinating with wildlife managers early in the development process, researchers will incorporate feedback from those who will actually use the products of this research and evaluate the effects of potential actions on amphibian populations. Thus, the results of this research will equip managers to make the most informed decisions for amphibian conservation across the North Central region of the United States.

These data represent projections of peak instantaneous rate of green-up date (PIRGd) and spring scale across Wyoming from 2000-2099. Annual data is provided in gridded time series at ~4 km spatial resolution. Projections were generated by applying linear mixed models to contemporary remote sensing data, and applying model parameters to future climate projection data from the MACA dataset. Projections were generated for 5 global climate models (GCMs) and 2 representative concentration pathway (RCP) scenarios: RCP 4.5 and RCP 8.5. Data starting in 2000 are provided to help assess accuracy of model projections against contemporary datasets, and provide a platform for comparison to projections for future years. These data were used to assess future changes to forage phenology greenscapes along mule deer migration routes in Wyoming, and are available to assess the impacts of future climate on a wide variety of ecological processes.

These GeoTIFF data were compiled to investigate how a new multivariate matching algorithm transfers simulated plant functional biomass of big sagebrush plant communities from 200 sites to a gridded product with 30-arcsec spatial resolution. Objectives of our study were to (1) describe how climate change will alter the biomass and composition of key plant functional types; (2) quantify the impacts of climate change on future functional type biomass and composition along climatic gradients; (3) identify if and which geographic locations will be relatively unaffected by climate change while others experience large effects; and (4) determine if there is consistency in climate change impacts on plant communities among a representative set of climate scenarios. These data represent geographic patterns in simulated plant functional biomass of big sagebrush plant communities (cheatgrass, perennial forbs, C3 perennial grasses, C4 perennial grasses, perennial grasses, big sagebrush) as across-year averages of under historical ("current"; years 1980-2010) climate and differences ("change") between projected future climates (years 2030-2060 and 2070-2100) derived as medians across 13 Global Climate Models (GCMs) that participated in CMIP5 for representative concentration pathways RCP4.5 and RCP8.5 and historical values. These data were created in 2020 and 2021 for the area of the sagebrush region in the western United States to describe geographic patterns in simulated plant functional biomass of big sagebrush plant communities under historical and projected future climate conditions at a 30-arcsec spatial resolution. These data can be used to confirm the results of the study identified as the ‘Larger Work Citation’ including the high resolution matching of projected declines in big sagebrush, perennial C3 grass and perennial forb biomass in warm, dry sites; no projected change or increases in functional type biomass in cold, moist sites; and widespread projected increases in perennial C4 grasses across sagebrush plant communities in the sagebrush region of the western United States as defined by Palmquist et al. (2021) and within the scope as defined by the study. These data may also be used to evaluate the potential impact of changing climate conditions on geographic patterns in simulated plant functional biomass of big sagebrush plant communities within the scope defined by the study. In particular, these data can be useful for informing the design of long-term landscape conservation efforts to maintain and expand wildlife habitat across the sagebrush biome.

Natural and cultural resource managers are increasingly working with the scientific community to create information on how best to adapt to the current and projected impacts of climate change. Engaging with these managers is a strategy that researchers can use to ensure that scientific outputs and findings are actionable (or useful and usable). In this article, the authors adapt Davidson’s wheel of participation to characterize and describe common stakeholder engagement strategies across the spectrum of Inform, Consult, Participate, and Empower. This adapted framework provides researchers with a standardized vocabulary for describing their engagement approach, guidance on how to select an approach, methods for implementing engagement, and potential barriers to overcome. While there is often no one “best” approach to engaging with stakeholders, researchers can use the objectives of their project and the decision context in which their stakeholders operate to guide their selection. Researchers can also revisit this framework over time as their project objectives shift and their stakeholder relationships evolve.