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.  

Accurate models are important to predict how global climate change will continue to alter plant phenology and near-term ecological forecasts can be used to iteratively improve models and evaluate predictions that are made a priori. The Ecological Forecasting Initiative's National Ecological Observatory Network (NEON) Forecasting Challenge, is an open challenge to the community to forecast daily greenness values, measured through digital images collected by the PhenoCam Network at NEON sites before the data are collected. For the first round of the challenge, which is presented here, we forecasted canopy greenness throughout the spring at eight deciduous broadleaf sites to investigate when, where, and for what model type phenology forecast skill is highest. A total of 192,536 predictions were submitted, representing eighteen models, including a persistence and a day of year mean null models. We found that overall forecast skill was highest when forecasting earlier in the greenup curve compared to the end, for shorter lead times, for sites that greened up earlier, and when submitting forecasts during times other than near budburst. The models based on day of year historical mean had the highest predictive skill across the challenge period. In this first round of the challenge, by synthesizing across forecasts, we started to elucidate what factors affect the predictive skill of near-term phenology forecasts.

Remotely sensed evapotranspiration (ET) data offer strong potential to support data-driven approaches for sustainable water management. However, practitioners require robust and rigorous accuracy assessments of such data. The OpenET system, which includes an ensemble of six remote sensing models, was developed to increase access to field-scale (30 m) ET data for the contiguous United States. Here we compare OpenET outputs against data from 152 in situ stations, primarily eddy covariance flux towers, deployed across the contiguous United States. Mean absolute error at cropland sites for the OpenET ensemble value is 15.8 mm per month (17% of mean observed ET), mean bias error is −5.3 mm per month (6%) and r2 is 0.9. Results for shrublands and forested sites show higher inter-model variability and lower accuracy relative to croplands. High accuracy and multi-model convergence across croplands demonstrate the utility of a model ensemble approach, and enhance confidence among ET data practitioners, including the agricultural water resource management community.

This report presents climate change-informed resource stewardship strategies for diverse Wrangell-St. Elias National Park and Preserve natural and cultural resources. The strategies were developed in early 2022 by park staff and other subject-matter experts in a scenario-based climate change adaptation planning process. Strategy development was facilitated by National Park Service (NPS) climate change adaptation specialists. Strategies address critical climate change implications for park resources identified in an immediately preceding (fall-2021) climate-resource scenario development process. The overall, nearly-year-long scenario- and strategy-development process was entirely virtual due  

Fire plays a critical role in forests of the western United States (US), but as wildfire and climate deviate from historical patterns, increasing fire activity may significantly alter forest ecosystems. To understand the impacts of changing climate and wildfire activity on conifer forests, we studied the impact of wildfire and annual post-fire climate on western larch (Larix occidentalis) regeneration. We destructively sampled 1651 seedlings from 57 sites within 32 fires that burned at moderate or high severity from 2000-2015 in the northwestern US. Using dendrochronological methods, we estimated germination years of seedlings to calculate annual recruitment rates. We used boosted regression trees to.03 model the annual probability of recruitment as a function of wildfire-related factors including distance-to-seed-source, satellite-derived fire severity, and time-since-fire, and using annual post-fire climate variables reflecting temperature and water availability. The majority of recruitment occurred within five years after fire, and at sites with northerly aspects that were within 25 m of mature pre-fire western larch. Wildfire-related factors had the highest relative influence on post-fire recruitment (87%), whereas post-fire climate had less influence (13%). Annual recruitment probability increased with growing season actual evapotranspiration, to a maximum c. 275 mm, and then decreased. Annual recruitment probability decreased as growing season climatic water deficit increased. These patterns are consistent with shade-intolerant traits and the temperature and moisture requirements of western larch. Our results suggest that climate warming has had variable, yet net-neutral, impacts on the climate suitability for post-fire western larch regeneration across its range – with suitability increasing modestly at ‘cooler and wetter’ sites and decreasing modestly at ‘warmer and drier’ sites. Overall, there is and has been broad climate suitability for post-fire regeneration across the distribution of western larch in the US. The strong influence of wildfire-related factors on post-fire regeneration highlights the important impact that management decisions can have in promoting western larch. For instance, facilitating prescribed or managed wildfire with moderate- to high-severity patches will generate conditions most suitable for natural regeneration, as long as a seed source remains nearby. Additionally, our findings support monitoring for natural regeneration or directing outcomes by planting within the first five years after fire, consistent with current management practices.

An estimated 50–80% of North America’s ducks use the millions of wetland basins in the Prairie Pothole Region as breeding habitat. The U.S. Fish and Wildlife Service (USFWS) National Wildlife Refuge System has conserved approximately 1.3 million hectares of grasslands and wetlands in the United States portion of the Prairie Pothole Region with the primary purpose to support breeding duck habitat. A major assumption inherent to the current conservation approach is that wetlands that have historically provided the highest value to breeding ducks will continue to do so into the future. The dynamic nature of climate in the Northern Great Plains and continued increases in air temperatures and precipitation variability have the potential to disrupt the desired outcomes of management agencies. The focus of this study is to better understand the sensitivity of prairie-pothole wetlands to climate change and help USFWS evaluate potential impacts to breeding ducks. We conducted virtual and in-person informational sessions with partners to inform them on the best practices of using downscaled global circulation models and approaches for climate scenario planning. We identified divergent future climate scenarios to consider important future climate uncertainties and simulated breeding duck pair responses to climate-driven impacts on wetland water levels. We have developed model estimates of future duck pair distribution under four climate scenarios for mid and end of century and currently are incorporating these estimates into the USFWS “predictive maps” that are used by refuge managers to prioritize wetland acquisition and management decisions. Additionally, our future duck-pair projections are being incorporated by another research team to develop economic optimization models to aid future conservation planning in the Prairie Pothole Region.