Novel approaches for quantifying density and distributions could help biologists adaptively manage wildlife populations, particularly if methods are accurate, consistent, cost-effective, rapid, and sensitive to change. Such approaches may also improve research on interactions between density and processes of interest such as disease transmission across multiple populations. We assess how satellite imagery, unmanned aerial systems (UAS) imagery, and Global Positioning System (GPS) collar data vary in characterizing elk density, distribution and count patterns across times with and without supplemental feeding at the National Elk Refuge (NER), Wyoming, USA. We also present the first comparison of satellite imagery data with traditional counts for ungulates in a temperate system. We further evaluate 7 different aggregation metrics to identify the most consistent and sensitive metrics for comparing density and distribution across time and populations. All three data sources detected higher densities and aggregation locations of elk during supplemental feeding than non-feeding at the NER. Kernel density estimates (KDEs), KDE polygon areas, and the first quantile of inter-elk distances detected differences with the highest sensitivity and were most highly correlated across data sources. Both UAS and satellite imagery provide snapshots of density and distribution patterns of most animals in the area for lower costs than GPS collars. While satellite-based counts were lower than traditional counts, aggregation metrics matched those from UAS and GPS data sources when animals appeared in high contrast to the landscape, including brown elk against new snow in open areas. UAS counts of elk were similar to traditional ground-based counts on feed grounds and are the best data source for assessing changes in small spatial extents. Satellite, UAS, or GPS data can provide appropriate data for assessing density and changes in density from adaptive management actions. For the NER, where high elk densities are beneath controlled airspace, GPS collar data will be most useful for evaluating how management actions, including changes in the dates of supplemental feeding, influence elk density and aggregation across large spatial extents. Using consistent and sensitive measures of density may improve research on the drivers and effects of density within and across a wide range of species.
These model objects are the outputs of three Boosted Regression Tree models (for three different time periods) to explore the role of climate change and variability in driving ecological change and transformation. Response variables were the proportion of sites in each ecoregion with peak rates of change at 100-year time steps. Predictor variables included temperature anomaly, temperature trend, temperature variability, precipitation anomaly, precipitation trend, precipitation variability and ecoregion, also at 100-yr time steps. Models focused on the most distant time periods (0-21000 BP and 7500 - 21000 BP) show that rapid vegetation change was initiated across these landscapes once a 2 ℃ temperature increase (positive temperature anomaly, relative to 21,000 yr BP) was realized. The model focused on the more recent time periods, 0-7500 BP, shows that rapid vegetation change was initiated across these landscapes again recently with reduced rainfall.
These model objects are the outputs of two Bayesian hierarchical models (one for the Middle Rockies and one for the Southern Rockies) to explore the role of landscape characteristics in climate-driven ecological change and transformation. We used the rate of change for each site at 100-yr time steps as the response variable, and included elevation, CHILI, aspect, slope, and TPI as fixed effects in the models, run separately for each ecoregion. We included a random intercept of site to quantify the magnitude of site-level variation in rate-of-change that may be unaccounted for by our covariates.
This database integrates a list of vegetation transformations that occurred across the Southern and Middle Rockies since 21,000 years ago, the age of occurrence, the type of vegetation switch that occurred, whether the rates of vegetation change peaked at that time, and when applicable, the duration of peak rates of vegetation change.
This project investigated how climate change over the last 21,000 years, which was characterized by significant warming, influenced vegetation in the Southern and Middle Rockies. We found that rapid vegetation change was initiated across these landscapes once a 2 ℃ temperature increase was realized and again recently with reduced rainfall. Southwesterly slopes in the Southern Rockies were prone to rapid change, otherwise landscape features didn’t have a strong effect. We also examined vegetation transformations (e.g., sagebrush steppe switches to a lodgepole pine forest) and identified between one and four vegetation transformations at each site, for a total of 60 transformations, over half of which occurred rapidly. This work provides a novel understanding of vegetation change that integrates climate change and landscape context, and helps to anticipate when (once our climate warms by 2 ℃ (before 2050)) and where (southwesterly slopes in the Southern Rockies) rapid vegetation change and transformation will be likely. The following details describe the scripts for the paleoecological portion of the NC CASC project 'Risk of ecological transformation across the US West and Pinyon woodlands' which are located in GitLab.
Trees are bioindicators of global climate change and regional urbanization, but available monitoring tools are ineffective for fine-scale observation of many species. Using six accelerometers mounted on two urban ash trees (Fraxinus americana), we looked at high-frequency tree vibrations, or change in periodicity of tree sway as a proxy for mass changes, to infer seasonal patterns of flowering and foliage (phenophases). We compared accelerometer-estimated phenophases to those derived from digital repeat photography using Green Chromatic Coordinates (GCC) and visual observation of phenophases defined by the USA National Phenology Network (NPN). We also drew comparisons between two commercial accelerometers and assessed how placement height influenced the ability to extract seasonal transition dates. Most notably, tree sway data showed a greenness signal in an urban environment and produced a clear flowering time-series and peak flowering signal (PF), marking the first observations of a flower phenophase using accelerometer data. Estimated start of spring (SOS) from accelerometers and time-lapse GCC were more similar than start of autumn (SOA); accelerometers lagged behind the time-lapse camera dates by three and four days for SOS and 13 and 14 days for SOA for each tree. Estimates for SOS and SOA from accelerometers and time-lapse cameras aligned closely with different NPN phenophases. The two commercial accelerometers produced similar season onset: a difference of 2.4 to 3.8 days for SOS, 2.1 days for SOA, and 0.5 to 2.0 days for PF. Accelerometers placed at the main crown branch point versus higher in the canopy showed a difference of 0.2 to 4.9 days for SOS and -1.5 to 1.7 days for PF. Our results suggest accelerometers present a novel opportunity to objectively monitor reproductive tree biology and fill gaps in phenology observations. Furthermore, widely available accelerometers show promise for scaling up from individual trees to the landscape level to aid forest management and assessing climate change impacts to tree phenology.
Recent fires have fueled concerns that regional and global warming trends are leading to more extreme burning. We found compelling evidence that average fire events in regions of the United States are up to four times the size, triple the frequency, and more widespread in the 2000s than in the previous two decades. Moreover, the most extreme fires are also larger, more common, and more likely to co-occur with other extreme fires. This documented shift in burning patterns across most of the country aligns with the palpable change in fire dynamics noted by the media, public, and fire-fighting officials.
Ungulate populations across the West have adapted to specific patterns in forage quantity, quality, and timing that ultimately influence the number of animals. We assessed potential for climate change to affect forage quality and availability for ungulates in the West. First, we evaluated multiple satellite remote sensing datasets and found that in some parts of the western U.S., growing season dates have shifted by over 30 days. We found agreement in the direction of recent trends in growing season dates across ~60% of the West. Substantial shifts in vegetation timing can have outsized effects on the wildlife that depend on matching migration timing to spring green up. For example, migrating mule deer follow the pattern of vegetation as it greens up in the spring when it is most nutritious. We assessed how green-up will change and how changes may affect mule deer migration in Wyoming. We projected that green-up of vegetation will generally occur earlier, particularly in drier years. We found future green-up along deer migration paths will be shuffled and of shorter duration, potentially decreasing the availability of high quality forage. This reduction in the benefit of migration could reduce the number of migrating deer. If local forage resources limit resident population size, mule deer abundance could decline. We provide baseline information on recent changes in the timing of forage, a framework to assess climate effects on forage, information on the quality of remote sensing data sources used for this research, improved understanding of the connections between climate and vegetation timing, and maps of projected future green-up. These products will be useful for biologists as they plan habitat treatments, consider effects of energy developments, and manage big game populations.
States in the North Central (NC) region have already been invaded by grass speciescapable of altering fire regimes and creating self-perpetuating 'grass-fire cycles'. Under climatechange, these grasses may interact with drought and fire to burn more and exclude native species. Managers can plan for these interactions and create collaborative communities to address thesecomplex challenges.
The National Park Service (NPS) is responsible for managing livestock grazing in nearly 100 parks, and several park grazing management planning efforts are currently underway. However, there is a recognized need to update grazing management practices to be responsive and adaptive to future climate change. As a step toward developing a process to address this need, this project worked with Dinosaur National Monument to consider climate change in its grazing management planning process. In this project, we convened researchers, managers, subject-matter experts, and climate change adaptation specialists through a participatory climate change scenario planning workshop to develop and apply a small set of challenging, plausible, relevant, and divergent scenarios that qualitatively assessed how grazing resources and management may be affected under climate change.