Abstract (from ESA Journals): Climate change is a well-documented driver and threat multiplier of infectious disease in wildlife populations. However, wildlife disease management and climate-change adaptation have largely operated in isolation. To improve conservation outcomes, we consider the role of climate adaptation in initiating or exacerbating the transmission and spread of wildlife disease and the deleterious effects thereof, as illustrated through several case studies. We offer insights into best practices for disease-smart adaptation, including a checklist of key factors for assessing disease risks early in the climate adaptation process. By assessing risk, incorporating uncertainty, planning for change, and monitoring outcomes, natural resource managers and conservation practitioners can better prepare for and respond to wildlife disease threats in a changing climate.

Under climate change, ecosystems are experiencing novel drought regimes, often in combination with stressors that reduce resilience and amplify drought’s impacts. Consequently, drought appears increasingly likely to push systems beyond important physiological and ecological thresholds, resulting in substantial changes in ecosystem characteristics persisting long after drought ends (i.e., ecological transformation). In the present article, we clarify how drought can lead to transformation across a wide variety of ecosystems including forests, woodlands, and grasslands. Specifically, we describe how climate change alters drought regimes and how this translates to impacts on plant population growth, either directly or through drought's interactions with factors such as land management, biotic interactions, and other disturbances. We emphasize how interactions among mechanisms can inhibit postdrought recovery and can shift trajectories toward alternate states. Providing a holistic picture of how drought initiates long-term change supports the development of risk assessments, predictive models, and management strategies, enhancing preparedness for a complex and growing challenge.

Grassland birds in North America have declined sharply over the last 60 years, driven by the widespread loss and degradation of grassland habitats. Climate change is occurring more rapidly in grasslands relative to some other ecosystems, and exposure to extreme and novel climate conditions may affect grassland bird ecology and demographics. To determine the potential effects of weather and climate variability on grassland birds, we conducted a systematic review of relationships between temperature and precipitation and demographic responses in grassland bird species of North America. Based on 124 independent studies, we used a vote-counting approach to quantify the frequency and direction of significant effects of weather and climate variability on grassland birds. Grassland birds tended to experience positive and negative effects of higher temperatures and altered precipitation. Moderate, sustained increases in mean temperature and precipitation benefitted some species, but extreme heat, drought, and heavy rainfall often reduced abundance and nest success. These patterns varied among climate regions, temporal scales of temperature and precipitation (<1 or ≥1 month), and taxa. The sensitivity of grassland bird populations to extreme weather and altered climate variability will likely be mediated by regional climates, interaction with other stressors, life-history strategies of various species, and species’ tolerances for novel climate conditions.

This dataset represents a climate-informed management alternative for maintaining whitebark pine (Pinus albicaulis) in the Greater Yellowstone Ecosystem. This data was developed for use in a landscape simulation modeling study aimed at evaluating how well alternative management strategies maintain whitebark pine populations under historical climate and future climate conditions. For the study, we developed three spatial management alternatives for whitebark pine in the Greater Yellowstone Ecosystem representing no active management, current management, and climate-informed management. These management alternatives were implemented in the simulaton model FireBGCv2 under historical climate and three future climate change scenarios - the HadGEM-ES, CESM1-CAM5, and CNRM-CM5 Global Circulation Models under the RCP 8.5 emissions scenario. We worked with the Greater Yellowstone Coordinating Committee's (GYCC) Whitebark Pine Subcommittee to develop this spatial representation of their current management strategy. The treatments mapped represent a set of the treatments recommended in the GYCC Whitebark Pine 2011 Strategy document and include planting blister-rust resistant whitebark pine seedlings, competition removal thinning, wildland fire use and prescribed fire, and protection from mountain pine beetles using verbenone and carbaryl. We used historical and future projections of climate suitability based on species distribution models for whitebark pine (Chang et al. 2014) to map zones of core, deteriorating, and future whitebark pine habitat. Core zones were those areas that are currently suitable for whitebark and remain suitable in the future. Deteriorating zones were where the climatic conditions for whitebark pine are expected to decline. Future zones were areas that are projected to become newly suitable for whitebark pine. We then overlaid our climate zones for whitebark pine with similar projections of future climate suitability for all of whitebark pine’s competitors - Engelmann spruce, subalpine fir, lodgepole pine, and Douglas-fir (Piekielek et al. 2015. We discussed the different combinations of climate suitability zones (core, deteriorating, future) and potential future level of competition (low or high) from other species with the GYCC Whitebark Pine Subcommittee to determine which management activities should be prioritized within each management zone. The result is a map of management zones where different activities are prioritized to meet the goal of maintaining whitebark pine populations. This was used to determine which treatments would be implemented spatially during the simulation modeling, dependent upon additional criteria related to simulated stand-level conditions.

This dataset represents current management alternatives for maintaining whitebark pine (Pinus albicaulis) in the Greater Yellowstone Ecosystem. This data was developed for use in a landscape simulation modeling study aimed at evaluating how well alternative management strategies maintain whitebark pine populations under historical climate and future climate conditions. For the study, we developed three spatial management alternatives for whitebark pine in the Greater Yellowstone Ecosystem representing no active management, current management, and climate-informed management. These management alternatives were implemented in the simulaton model FireBGCv2 under historical climate and three future climate change scenarios - the HadGEM-ES, CESM1-CAM5, and CNRM-CM5 Global Circulation Models under the RCP 8.5 emissions scenario. We worked with the Greater Yellowstone Coordinating Committee's (GYCC) Whitebark Pine Subcommittee to develop this spatial representation of their current management strategy. The treatments mapped represent a set of the treatments recommended in the GYCC Whitebark Pine 2011 Strategy document and include planting blister-rust resistant whitebark pine seedlings, competition removal thinning, wildland fire use and prescribed fire, and protection from mountain pine beetles using verbenone and carbaryl. For the current management strategy, we relied on differences in land allocation classes and proximity to roads and trails to determine where treatments would occur. Land allocations were derived from a federal land ownership layer (https://catalog.data.gov/harvest/object/6bec8d3c-fff4-4037-8028-9b1d7ff64814/html/original). We mapped the proximity to roads/trails by buffering all roads/trails as mapped by the GYCC Whitebark Pine Subcommittee.The types of treatments that can be implemented in the current strategy are constrained by access, logistics, and management constraints among different jurisdictions. Through discussions with the GYCC Whitebark pine Subcommittee we mapped available treatments based on land allocation and proximity to roads in the following zones: Zone 1: Multiple use forest (non-Wilderness & inventoried roadless areas on USFS/BLM lands) farther than 1-mile from roads/trails. Available treatments: thinning, prescribed fire, wildland use fire, 80% fire suppression. Zone 2: Multiple use forest (non-Wilderness & inventoried roadless areas on USFS/BLM lands) within 1-mile from roads/trails. Available treatments: planting, thinning, prescribed fire, wildland use fire, 80% fire suppression. Zone 3: NPS non-wilderness lands farther than 1 mile from roads/trails. Available treatments: thinning, prescribed fire, wildland use fire, 20% fire suppression. Zone 4: NPS, non-wilderness lands within 1 mile from roads/trails. Available treatments: planting, thinning, prescribed fire, wildland use fire, 20% fire suppression. Zone 5: Non-federal lands (private, state, Native American lands, but we do include USFWS lands here). Available treatments: none, full fire suppression. Zone 6: Wilderness lands (designated, proposed and wilderness study areas) administered by NPS. Available treatments: wildland fire use, 20% fire suppression Zone 7: Wilderness lands (designated, proposed and wilderness study areas) administered by USFS/BLM. Available treatments: wildland fire use, 20% fire suppression

Note: this data release has been deprecated. Find the new version here: https://doi.org/10.5066/P9QCLGKM. This NetCDF represents the monthly inputs and outputs from a United States Geological Survey water-balance model (McCabe and Wolock, 2011) for the conterminous United States for the period 1895-01-01 to 2020-12-31. The source data used to run the water balance model is based on the National Oceanic and Atmospheric Administration's(NOAA, 2020) ClimGrid data for precipitation and temperature. This NetCDF contains the following monthly inputs: temperature (degrees Celsius) and precipitation (millimeters, mm) and the following outputs (all in mm): runoff, soil moisture storage, actual evapotranspiration, potential evapotranspiration, snow water equivalent, and snowfall. The spatial reference for this data set is ESPG 4326.

In ecosystems characterized by flowing water, such as rivers and streams, the dynamics of how the water moves - how deep it is, how fast it flows, how often it floods - have direct effects on the health, diversity, and sustainability of underlying communities. Yet increasingly, climate extremes like droughts and floods are disrupting fragile stream ecosystems by specifically changing their internal aquatic flows. Human infrastructure, such as irrigation and dams, further disrupt these dynamics. These changes in climate and land use are leading to teh fragmentation of aquatic habtiat, degraded water quality, altered sediment transport processes, variation in the timing and duration of floodplain inundation, shifts in stream and lake temperatures, and the conversion of flowing streams to lakes and wetlands. This project, termed the “Future of Aquatic Flows,” has three primary components: 1) Regional projects focused on key research questions related to the future of aquatic flows in a changing climate at each CASC region around the country;  2) A national synthesis component which will synthesize the state of the science on how aquatic changes will be impacted by climate change, and implications for ecosystems and human communities; 3) A training component for the post-doctoral researchers who participate in this cohort of the CAP Fellows program "Future of Aquatic Flows: Towards a National Synthesis" is the umbrella project for the 2022-2024 Climate Adaptation Postdoctoral (CAP) Fellows cohort. Fellows situated at each of the nine regional CASCs will work with USGS, university, and regional partners to conduct research directly applicable to regional management priorities relating to aquatic flows, and will also work with each other on a national synthesis project on the topic. More information about the Future of Aquatic Flows CAP Fellowship can be found here: https://www.usgs.gov/programs/climate-adaptation-science-centers/science/2022-24-future-aquatic-flows 

We mapped potential climate change refugia for riparian areas in the central and western USA for 2040-2069 and 2070-2099. Riparian refugia are existing riparian areas that are projected to maintain riparian vegetation and associated ecological function under plausible future climates. Four input variables were included in the riparian refugia index: two landscape variables that represent where existing riparian areas may be more resilient to climatic changes (riparian connectedness and landscape diversity) and two climate variables that reflect projected exposure to climate change (runoff and warm days). For the climate variables, we considered two global circulation models: moderately hot and wet (CNRM-CM5) and hot and dry (IPSL-CM5A-MR) under RCP 8.5. The climate variables represented the projected change from a historical baseline (1971-2000) for two future 30-year time periods, mid-century (2040-2069) and late century (2070-2099). The four input variables of uniform pixel size were assigned equal weights and layered together using ArcGIS Pro’s Suitability Modeler to create an index for riparian refugial quality. Here we provide raster layers for the riparian refugia index and three of the four input variables including riparian connectedness, runoff, and warm days. The fourth input variable, landscape diversity, was produced by The Nature Conservancy and is available online at The Nature Conservancy’s Resilient and Connected Network. The four climate scenarios (CNRM-CM5 2040-2069, CNRM-CM5 2070-2099, IPSL-CM5A-MR 2040-2069, and IPSL-CM5A-MR 2070-209) are included as individual rasters for the riparian refugia index, runoff, and warm days, and are zipped into each base folder. We also provide a geodatabase that contains all the data (riparian refugia index, riparian connectedness, runoff, and warm days).

Ecological drought impacts ecosystems across the U.S. that support a wide array of economic activity and ecosystem services. Managing drought-vulnerable natural resources is a growing challenge for federal, state and Tribal land managers.  Plant communities and animal populations are strongly linked to patterns of drought and soil moisture availability.  As a result, ecosystems may be heavily altered by future changes in precipitation and soil moisture that are driven by climate change.  Although this vulnerability is well recognized, developing accurate information about the potential consequences of climate change for ecological drought is difficult because the soil moisture conditions that plants experience are shaped by complex interactions among weather, atmospheric CO2, plants and soils. There are currently very few ecologically appropriate datasets about future drought with widespread distribution at resolutions suitable for informing natural resource decision making.  This project will meet some of those needs by simulating complex interactions that affect soil moisture availability to plants and generating user-relevant soil moisture projections.  Results will include detailed and synthesized drought information for the 21st century across the entire contiguous U.S. that are delivered via the Climate Toolbox, an established source for long-term climate projections. Data provided by this project will be useful for a wide variety of applications including scenario planning, species distribution models, and ecological drought and habitat vulnerability assessments.