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USGS2026

Critter Tales—Adventures in restoration activity book for kids

Product Information “Critter Tales: Adventures in Restoration Activity Book” is an interactive educational resource designed for children ages 5–9, produced by the U.S. Geological Survey in cooperation with the U.S. Department of the Interior, Office of Restoration and Damage Assessment. Through the journey of Lulu the loon and a cast of animal friends, young readers explore the importance of ecological restoration across diverse habitats—from sand dunes and wetlands to prairies and streams. The activity book blends storytelling, science, and hands-on activities to teach children how restoration efforts help wildlife thrive. Readers learn about native plants, animal life cycles, and the role of restoration in protecting habitats for birds, turtles, butterflies, mussels, and more. Engaging puzzles, coloring pages, and interactive challenges encourage kids to become nature’s helpers, fostering environmental stewardship and awareness. With vibrant illustrations and accessible language, the publication highlights practical actions—such as planting native milkweed, using lead-free fishing tackle, and supporting mussel restoration—that empower children to make a positive change in their own communities. The book also introduces basic ecological concepts and celebrates the interconnectedness of living things, making it an ideal resource for families, educators, and anyone interested in environmental education.

General Information Product↗
USGS2026

Simulation of the impacts of spring diversions on streamflow in the Strawberry Creek watershed, San Bernardino County, California, using an integrated hydrological model

The Strawberry Creek watershed, in the San Bernardino Mountains of southern California, features a group of natural springs known as Arrowhead Springs that have been augmented with diversions in the form of sub-horizontal borings and tunnels. Understanding the effects of these structures on streamflow through groundwater capture is crucial for managing surface-water resources in this watershed. In this study, we constructed the Strawberry Creek integrated hydrological model to increase this understanding. The Strawberry Creek integrated hydrological model is an integrated surface runoff and groundwater model, GSFLOW to simulate surface runoff and infiltration and groundwater flow. The model has 263 rows and 176 columns in each of its three layers. The model area includes the Strawberry Creek and four adjacent watersheds. The precipitation-runoff modeling system was calibrated using two streamflow gaging stations, and the groundwater and surface-water flow model was calibrated to the reported spring diversion discharge and a sparse number of groundwater-level measurements. The Strawberry Creek integrated hydrological model was run with and without diversions active, and simulated streamflow was compared, indicating that in the headwaters of Strawberry Creek, about 35 percent of the diversion flow was captured from base flow.

California↗
USGS2026

Tracing mercury from land to river: Global sources, retention, and implications for sustainability

Mercury (Hg) pollution in river systems is a global sustainability challenge. Yet the transport, transformation, and retention of Hg within global rivers remain poorly quantified, particularly in regions with sparse observations such as Southeast Asia and Africa, hindering effective pollution mitigation and reinforcing geographic inequities in scientific knowledge and environmental governance. Here, we present the first global, high-resolution simulation of riverine Hg dynamics using a process-based model that traces Hg from land-based sources through river networks to the ocean. Under a realistic scenario, we estimate that ∼1900 megagrams per year (Mg/yr) of Hg enters global rivers, including 1500 Mg/yr from human-induced sources and 400 Mg/yr from soil erosion. Nearly half of this flux (∼1000 Mg/yr) is retained in reservoirs and dams, which act as major sinks. While such retention limits downstream delivery to the oceans, it also heightens in-reservoir Hg methylation risks. By bridging the gap between Hg releases and observed riverine exports, our framework offers a scalable tool for data-limited regions, promotes data access, and supports global freshwater and pollution-management strategies.

Environmental Science & Technology↗
USGS2026

Co-producing coastal bird research on the Gulf Coast through structured decision making (SDM) and constructed value of information (CVoI)

Conservation practitioners face the complex challenge of addressing global biodiversity threats within social-ecological systems with multiple jurisdictions, numerous interest groups, and changing environmental conditions. Bridging the research-to-implementation gap between scientists and managers, which integrates diverse perspectives that represent the variety of considerations impacting management outcomes can help to inform efficient and effective conservation. Avian conservation programs along the U.S. Gulf Coast exemplify these challenges, as management decisions must address diverse threats to declining coastal bird populations across large breeding, wintering, and migratory ranges while facing uncertainty surrounding the efficacy of large-scale strategies. This provides opportunities for improving management through co-produced research with structured decision making (SDM). We present a case study that demonstrates the application of co-production principles and SDM to collaboratively develop high-priority research questions informing effective avian conservation and management. Additionally, we applied a constructed value of information (CVoI) framework to identify and prioritize which uncertainties to reduce and better understand how research questions impact management actions. The integration of SDM’s five-step decision making framework ensured key principles of co-production were met, while co-production enhanced SDM outcomes by incorporating diverse perspectives and knowledge bases. CVoI further allowed participants to collectively determine final high-priority research questions in the face of complexity and uncertainty. Together, these approaches supported co-produced knowledge-generation, strategic hypothesis prioritization, and identification of research questions most likely to improve conservation decisions. This case study from the U.S. Gulf Coast demonstrates how co-produced research through SDM offers a broadly applicable approach for navigating ecological complexity and bridging the research-to-implementation gap in avian conservation.

Gulf Coast↗
USGS2026

Biological, environmental, and geomorphological factors influencing reach-specific survival of spring Chinook Salmon smolts upstream of the Columbia–Snake River hydrosystem

Objective Pacific salmon Oncorhynchus spp. are exhibiting catastrophic declines throughout much of the Pacific Northwest, and juvenile mortality contributions are disproportionately high. Many Pacific salmon smolt populations are exhibiting high natal stream mortality; however, detailed natal stream reach-specific survival knowledge is lacking. Our objectives were to estimate natal stream reach-specific survival and identify influential covariates for spring Chinook Salmon O. tshawytscha smolts. An additional objective was to evaluate (i.e., estimate postrestoration cumulative survival) a novel and strategic large-scale river restoration approach (i.e., stream confluence restoration) in two Pacific Northwest spring Chinook Salmon natal streams. Methods Using radiotelemetry techniques during March–June (2011–2017), we estimated natal stream reach-specific survival for spring Chinook Salmon smolts in Catherine Creek and the Grande Ronde River, northeast Oregon. We examined the interrelated influences of temporal, biological, environmental, and geomorphological covariates on the behavior, travel time, and reach-specific survival of spring Chinook Salmon smolts that were emigrating through two hydrologically altered natal streams in the interior Columbia River basin. For each natal stream smolt tag-group, Cormack–Jolly–Seber reach-specific survival estimates that were adjusted for premature tag failure (i.e., bias-corrected) were generated. Subsequently, smolt effects were estimated using reach-specific travel times and survival estimates coupled with individual time-varying covariates from radio-tagged smolts and occupied reaches using an existing predator–prey model (i.e., mean free-path length [ XT ] model). Complementary population-specific principal coordinate analyses (PCoAs) were conducted to facilitate visualization of multicovariate resemblances in ordination space. Last, we employed our best-fitting XT model to model cumulative changes in smolt survival that were associated with a large-scale stream channel restoration scenario (i.e., restoration of the historical Catherine Creek and Grande Ronde River confluence). Results In aggregate, Catherine Creek smolts exhibited high mortality throughout Catherine Creek but near-100% survival upon entering the Grande Ronde River. In contrast, Grande Ronde River smolts generally exhibited low mortality upstream from the Grande Ronde Valley and high mortality throughout the Grande Ronde Valley. Our best-fitting XT model indicated that smolt survival was positively correlated with discharge, body size, and current velocity but negatively correlated with avian predation. Natural-origin smolts from Catherine Creek displayed higher λ-values (i.e., distance between predator–prey encounters) than their significantly larger and faster emigrating hatchery conspecifics, indicating that hatchery smolts may be more susceptible to predation. Our population-specific PCoAs further revealed that novel water (i.e., unique water chemistry) and emigration rate were the strongest predictors of reach occupancy in multivariate ordination space. Under a stream restoration scenario of restoring the historical hydrological template (i.e., restored channel configuration), our best-fitting XT model predicted changes in population-specific cumulative survivals to the lower Grande Ronde Valley (Imbler, Oregon) ranging from −38.4% to 69.0% for Grande Ronde River and Catherine Creek spring Chinook Salmon smolts, respectively. Conclusions Our best-fitting XT model and PCoAs identified the relative importance of biological, environmental, and geomorphological factors to both natural- and hatchery-origin Chinook Salmon smolt survival in two neighboring interior natal streams in the Columbia River basin. Our research indicates that concurrent habitat restoration and fish management strategies, including focused attention on smolt-rearing nursery habitat restoration, piscivorous avian control plans, adaptive management strategies for hatchery smolt releases, and discharge and novel water regime restoration projects, may yield survival benefits to “in-basin” Chinook Salmon smolts. Our research can inform origin-type-specific Chinook Salmon smolt management, habitat restoration, and future research decisions throughout the upper Grande Ronde River subbasin and potentially the Pacific Northwest.

Oregon, Washington↗
USGS2026

Genomic structural variation rescues a classic biological invader from a population bottleneck

Invasion genetics presents a classic paradox: How do species successfully spread despite severe population bottlenecks? The brown treesnake ( Boiga irregularis ) in Guam represents a notable example of this phenomenon, having been introduced with only a handful of individuals. We show that the population endured an extreme bottleneck, with roughly half of the genome exhibiting runs of homozygosity, comparable to species of conservation concern. Despite this, we uncovered extensive diversity in the form of nearly 19,000 genomic structural variants, which affect almost eight times more of the genome than single-nucleotide variants and provide material for “rescuing” the population from inbreeding-driven declines. Structural variant density was highest in gene promoters, where recombination and DNA repair often occur, providing a mechanism for rapid evolution of gene-linked diversity. This diversity is enriched in genes vital for adaptive immunity and olfaction, suggesting genomic diversity in key chromosomal regions can rescue populations from inbreeding. This work has critical implications for invasion biology and conservation genetics practitioners.

Guam↗
USGS2026

Tracking decadal changes in frequent fire activity across the southeastern U.S. (2000-2019): Insights from Southeast FireMap

Background The dominant natural habitats in the southeastern United States depend on frequent fire ignited by humans or lightning. However, fire activity has sharply declined in the region since the early 1900s, and reduced fire activity has degraded natural habitats and increased wildfire risk. Identifying changes in fire use during recent decades is necessary to guide the conservation of fire-dependent wildlife, management of hazardous fuels, and identify areas where increased fire use could improve ecosystem resilience. To address this need, we created the Southeast FireMap dataset by fine-tuning the United States Geological Survey’s Landsat Burned Area product to track burned area, and provide a fire history across the southeastern United States. We used the Southeast FireMap data to quantify changes in areas frequently burned, as measured by areas with multiple burns within a decade. We compared the periods 2000–2009 and 2010–2019 to identify where frequently burned area is increasing or declining. We examined patterns of change across ownership, land cover, and soil orders to provide geographic context, and we considered future implications of these changes for land use categories of ecological interest. Results Frequently burned area increased between decades across the region. This increase occurred on both private and public lands, in upland vegetation types, and on upland soils, though these increases were moderately offset by decreased wetland burning and its associated soil orders. However, changes varied among states, with burned area decreasing in some states. Conclusions The overall increase in frequently burned area across the region reflects a summation of positive and negative shifts associated with specific combinations of physiography, ownership class, and government jurisdiction. Southeast FireMap marks a significant advancement in our ability to identify changes in prescribed burning within the geographic and cultural contexts that will likely influence the complex future of fire in the region.

southeastern United States↗
USGS2026

Streamflow characterization and effects of Interstate 26 highway construction on water-quality and channel morphology conditions of the French Broad River in Buncombe and Henderson Counties, North Carolina, 2019–22

The North Carolina Department of Transportation began a series of highway construction projects to upgrade Interstate 26 (I–26) in Buncombe and Henderson Counties, North Carolina, starting in early 2020. The North Carolina Department of Transportation and the U.S. Geological Survey partnered in 2019 to monitor and assess water-quality and geomorphic conditions throughout the French Broad River corridor in areas near Interstate 26 highway construction activities. This report summarizes findings from multi-year water-quality and channel morphology monitoring from 2019 through 2022 in the French Broad River corridor near ongoing highway construction activities. Dissolved oxygen, pH, specific conductance, turbidity, and water temperature were monitored at six gaging locations, three of which were near highway sections undergoing construction during the study period from June 1, 2019, through December 31, 2022. Water quality was compared across three monitoring locations before and during construction using Brunner-Dette-Munk statistical tests, a nonparametric form of analysis of variance used for unbalanced datasets. Most Brunner-Dette-Munk test results detected insignificant effects of highway construction on water-quality conditions when controlling for monitoring location, except for the test of daily maximum specific conductance values. However, the effects of highway construction could not be isolated from other external factors that may have affected specific conductance, including an extended period of low streamflow and possible road salt application after winter storms. Additional Brunner-Dette-Munk tests, controlling for flow magnitude (streamflow quantiles) or hydrograph position (“rising limb,” “falling limb,” or “base flow”), did not suggest that highway construction affected water-quality conditions in the study area. Geomorphic surveys of the streambed and streambanks were performed in a 1-kilometer reach from 2019 through 2022 to assess geomorphic changes during the reconstruction of a bridge spanning the French Broad River. Bathymetric surveys of the streambed and light detection and ranging (lidar) scans of the streambanks were collected from a canoe using motion-compensated, real-time positioning solutions. Initial geomorphic surveys were used as a baseline to which subsequent repeat surveys were compared using geomorphic change detection analysis. Detectable elevation changes were determined using statistically robust thresholds, ensuring only changes exceeding measurement uncertainty were considered for interpretive analyses. Change detection results identified that 16.4 percent of the reach experienced detectable geomorphic change during the study period, with inter-survey changes ranging from 3.5 to 12.4 percent of the total reach. Most detectable change is attributed to the installation and reconfiguration of temporary construction pads; other changes are attributed to enlargement of a scour hole and upstream deposition near the bridge. Although anthropogenic activities and changes in streamflow regime contributed to these observations, the approach used in this study provides confidence that reported values reflect real geomorphic changes and not noise.

North Carolina↗
USGS2026

The use of fluorite geochemistry and machine learning to identify critical mineral systems

Fluorite (CaF 2 ) is a potential pathfinder to critical mineral and rare earth element (REE) deposits but its application has been limited to a narrow range of mineralization types. I show that fluorite is a robust recorder of mineralization fertility by applying statistical and machine-learning methods to a new global fluorite geochemical database. Distinct median rare earth and trace element patterns are observed among deposit types and genetic environments. Fluorite associated with carbonatites and REE deposits are relatively enriched in Sr and have minimal Eu anomalies. These characteristics define new bivariate discrimination diagrams that correctly identify 78% of carbonatite-related fluorite and 88% of fluorite from REE deposits. Random forest classifiers were developed for a wide range of mineralization types and genetic settings. Trained solely on rare earth element patterns, these models achieve accuracies of 77–79%. Higher classification accuracies (up to 88–96%) are obtained when including elements such as Sr, highlighting the significance of trace elements for optimal fluorite classification. The recognition of diagnostic fluorite compositional fingerprints, particularly in REE-fertile systems, underscores its potential as a pathfinder and indicator for critical mineral exploration in F-bearing environments.

Mineralium Deposita↗
USGS2026

Topography-aware registration refinement of Landsat 8/9 L1TP products with Sentinel-2 L1C and NAIP orthoimages

Satellite orthoimage products are widely available, yet residual geometric misregistration across independently processed products remains common, limiting their direct interoperability for multi-source and multi-temporal analysis. This paper introduces a residual Multi-Layer Perceptron (MLP)–based, topography-aware framework to further increase the registration quality of existing orthoimages based on dense matching without requiring any sensor-specific metadata or physical imaging parameters. We evaluate our approach by precisely co-registering 26 Landsat 8/9 Collection 2 Level-1 Terrain Precision (L1TP) scenes across Indiana (USA) and Berlin (Germany) with Sentinel-2 L1C and National Agriculture Imagery Program (NAIP) orthoimages. The baseline Landsat misregistration to Sentinel-2 or NAIP typically ranges from 3 to 10 m, which is reduced to 2–4 m after applying our MLP-based refinement, outperforming conventional polynomial and Rational Polynomial Coefficient (RPC) models. Further empirical evaluation demonstrates that consistent registration precision can be achieved across various terrain datasets; specifically, 30 m global digital elevation models (DEMs) yield comparable performance to that of high resolution (1–10 m) national or regional DEMs. The developed MLP approach provides a precise and reliable framework that transcends Landsat-specific tasks. It is readily adaptable to other registration applications requiring high-fidelity geometric alignment and consistent integration of heterogeneous image sources.

Indiana↗
USGS2026

Predicting reach-scale macroinvertebrate community changes due to declining flows in an aridland river

Understanding the connection between streamflow and macroinvertebrate community structure is critical for managing river ecosystems under scenarios of change caused by human activities and drought. Streamflow influences physical habitat characteristics, including depth, water velocity, and substrate composition, which structure macroinvertebrate communities. Although strong empirical evidence has linked macroinvertebrates to these variables, most studies are correlative, and predictive approaches that link altered streamflow to changes in habitat availability and community structure remain limited. To address this gap, we coupled benthic macroinvertebrate surveys with reach-scale, 2-dimensional hydraulic models to quantify changes in community structure in response to altered streamflows. We characterized macroinvertebrate communities and physical habitat conditions in riffle, run, and pool mesohabitats across 3 reaches of a free-flowing section of the Verde River (Arizona, USA) over 3 y and developed hydraulic models using overflight data, ground surveys, and streamflow monitoring. Macroinvertebrate communities differed among mesohabitats, with riffles supporting higher macroinvertebrate densities and pools exhibiting higher taxonomic richness. The 2-dimensional hydraulic models indicated that declining streamflows could reduce the area of suitable habitat in riffles and runs relative to pools, potentially shifting the distribution of mesohabitats and altering community composition. These changes may lead to declines in overall macroinvertebrate diversity and abundance under reduced flow conditions. By explicitly linking streamflow to habitat availability and community structure, this study demonstrates how integrating hydraulic modeling with biological surveys can improve predictions of ecological response to flow alteration. This framework provides a basis for flow management strategies aimed at maintaining habitat heterogeneity and supporting biodiversity in river networks.

Arizona↗
USGS2026

Detecting earthquakes in noisy real-time GNSS data with deep learning for improved PGD magnitude estimation

To disseminate accurate and useful warnings, earthquake early warning (EEW) systems must quickly determine the size and location of an earthquake to estimate expected shaking. Traditional seismic‐based algorithms tend to underestimate the true magnitudes of large earthquakes, a phenomenon known as magnitude saturation. This limitation motivated the recent inclusion of Global Navigation Satellite Systems (GNSS) data into the U.S. Geological Survey’s ShakeAlert EEW system with the Geodetic First Approximation of Size and Time (GFAST) algorithm because GNSS data do not saturate with large ground motions. However, the noise levels of GNSS data are very high compared with traditional seismic data, which obscures P ‐wave arrivals and can result in less accurate magnitude estimations if displacement amplitudes are low, such as for lower magnitude earthquakes or large source–station distances. In this study, we develop a deep‐learning model that detects earthquakes in GNSS data and use the Ridgecrest, California, earthquake sequence as a case study to demonstrate how the model could act as a filter to reduce the amount of low‐quality data that enters an algorithm like GFAST. To preserve our limited real earthquake data for model inference, we generated a training dataset composed of >700,000 synthetic displacement waveforms. We combined the synthetic waveforms with real‐time GNSS noise to produce realistically noisy training waveforms and then tested our model on additional synthetic data and performed inference using the real data that were held back. We discuss the performance of our trained model on both the unseen synthetic data and real inference data. Our model can be used to selectively filter only high‐quality data where an earthquake signal is observed for input into an algorithm like GFAST (outperforming a simple signal‐to‐noise ratio–based filter) to reduce the error in GFAST’s real‐time earthquake magnitude estimations.

California↗
USGS2026

Coal beneath Federal lands in the United States—Mines, reserves, and resources

The U.S. Geological Survey (USGS) compiled a list of coal mines and tabulated the coal reserves and available coal resources beneath Federal lands in the conterminous United States. Coal resources beneath Federal lands in Alaska are also discussed in this report. In 2024, the 34 coal mines on Federal lands produced more than 261 million short tons of coal. Surface mining is used at 23 of the coal mines, and underground mining is used at 11. These 34 coal mines control more than 4.2 billion short tons of reported coal reserves. Most of the coal mines (31) and more than 98 percent of the reported coal reserves are on Federal lands west of the Mississippi River. Of all the States, Wyoming has the most coal mines on Federal lands (14) and produces the most coal from Federal lands. The Powder River Basin has the most coal mines per basin or coal field operating on Federal lands (12 in Wyoming, 2 in Montana). Most of the available coal resources in the conterminous United States are also west of the Mississippi River. There are five basins or coal fields in the West that each contain available coal resources of more than 25 billion short tons. The USGS estimates that more than 355 billion short tons of available coal resources remain beneath Federal lands in the conterminous United States. Alaska contains substantial quantities of coal resources. The USGS estimates that Alaska has at least 140 billion short tons of identified available coal resources but may ultimately have as much as 5.5 trillion short tons of coal resources.

Circular↗
USGS2026

Global performance of remote sensing-based and reanalysis-driven models to estimate open water evaporation

Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, we analyze the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. We compare 3 remote sensing-based models, 1 reanalysis-driven model and 1 ensemble approach, using in situ observations from 27 lakes representing a diverse range of geographic and climatic regions. Our results demonstrate that, overall, the ensemble outperformed any individual model in terms of accuracy, with a RMSE and a bias of 1.3 and 0.3 mm day −1 , respectively. These findings highlight the benefits of using an ensemble approach to estimate open water evaporation with satellite-based models at the global scale, leveraging the unique strengths of each model. For the individual models, differences in the representation of heat storage changes and advection effects led to lower values of RMSE and bias, depending on the location and depth of the lakes. This study sets the path for future improvement of open water evaporation algorithms globally, while remote sensing techniques are proven satisfactory to monitoring of water loss in lakes globally, an essential step toward effective large-scale water resources management.

Water Resources Research↗
USGS2026

Brown bullhead catfish melanoma represents a novel transmissible cancer

Since 2012, brown bullhead catfish ( Ameiurus nebulosus ) in a lake that spans Vermont, USA, and Quebec, Canada, have shown a high rate of melanomas, suggesting a causal contaminant or contagion 1 . We tested the hypothesis that this affliction represents a clonally transmissible cancer, a rare phenomenon in which cancer cells themselves spread between individuals, behaving more like parasites than conventional tumours 2 . Whole-genome sequencing of tumour and matched non-tumour host tissues revealed that tumour mitochondrial and nuclear genomes are more closely related to each other than to their hosts or unaffected fish. Hundreds of thousands of genetic variants are shared among tumour samples but are absent from host fish, vastly exceeding levels seen in conventional cancers 3 . These findings indicate that melanoma in these brown bullheads represents the fourth documented type of naturally occurring transmissible cancer in animals, after dogs 4 , Tasmanian devils 5 and several bivalve species 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 . This raises important questions about the cancer’s origin, the mode of transmission and the long-term impact on fish populations.

Quebec, Vermont↗
USGS2026

Predicting disease spread from host movement data: Chronic wasting disease in North America as a case study

1. Rare long-distance movements can increase the spatial spread of invasive species and shifts in species ranges. However, in the context of wildlife disease spread, seasonal migrations only matter if they lead to transmission beyond an individual’s initial set of contacts, and the importance of juvenile dispersal depends on whether those juveniles become infected before they disperse. 2. High resolution animal movement data are increasing, but it is unclear how to leverage these data to improve predictions future disease spread particularly in regions without pre-existing movement data. 3. We predicted the speed of chronic wasting disease (CWD) spread based on movement metrics of mule deer ( Odocoileus hemionus ) and white-tailed deer ( Odocoileus virginianus ) and compared our predictions to observed spreading rates in North America from 2005 to 2022. We hypothesized that CWD should spread faster in regions with long-distance migratory mule deer, but this hypothesis was only partially supported. 4. Observed rates of CWD spread were faster in western epicenters with more mobile mule deer than in epicenters with only white-tailed deer (14-18 km/yr compared to 5-7 km/yr, respectively). However, the observed speed of CWD spread did not align well with migration distances. Deer movements in the Canadian Prairie Provinces (CPP) were far shorter than those in Colorado and Wyoming, yet had faster CWD spread much of which was open prairies where deer movements tend to be along riverine corridors rather than the longer elevational migrations in more montane regions. 5. Generally, our predicted rates of CWD spread from three different models were far slower than the observed rates regardless of whether the model included dispersal or migration. Understanding of these discrepancies is needed before high-resolution animal movement data can be used to predict broad-scale patterns of disease invasion. 6. Anthropogenic movements likely explain longer-distance movements of CWD across North America, but it remains unclear whether human-mediated movements or alternative analytical methods and deer movement metrics can explain the faster than predicted local CWD spread.

Journal of Animal Ecology↗
USGS2026

Connecting and coordinating conservation action across landscapes through regional planning processes and syntheses

Modern threats to conservation are often global; however, relevant conservation decisions and actions typically occur within local jurisdictions. The socio-ecological complexity of these problems requires collaboration across large landscapes, diverse community interests, and geopolitical boundaries, yet a lack of interoperability of planning products among decision makers, jurisdictions, and objectives impedes collaboration. Here, we provide a working model for the collaborative, iterative development of a landscape conservation design (LCD) in the Midwest region of the United States, the Midwest Conservation Blueprint, and demonstrate its applicability to the coordination of voluntary conservation actions and investments across jurisdictional boundaries. We used spatial prioritization software to synthesize over 20 datasets to develop a basemap of priority lands and waters for conservation across a diverse set of societal and ecological values (e.g., water quality, biodiversity, recreation). The Midwest Conservation Blueprint is a living plan, updated annually based on improvements in underlying data, understanding of local conditions, and public input. Landscape-scale planning is not designed to replace local knowledge or supersede decision-making authorities. However, by synthesizing existing data that represent diverse socio-ecological values and planning at a broader scale, the Midwest Conservation Blueprint documents where there are shared priorities and opportunities for collaborative landscape conservation.

Midwest↗