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At least 1,711 records · Page 95Linked to original sources
USGS2016

Use of Atlantic Forest protected areas by free-ranging dogs: estimating abundance and persistence of use

Worldwide, domestic dogs ( Canis familiaris ) are one of the most common carnivoran species in natural areas and their populations are still increasing. Dogs have been shown to impact wildlife populations negatively, and their occurrence can alter the abundance, behavior, and activity patterns of native species. However, little is known about abundance and density of the free-ranging dogs that use protected areas. Here, we used camera trap data with an open-robust design mark–recapture model to estimate the number of dogs that used protected areas in Brazilian Atlantic Forest. We estimated the time period these dogs used the protected areas, and explored factors that influenced the probability of continued use (e.g., season, mammal richness, proportion of forest), while accounting for variation in detection probability. Dogs in the studied system were categorized as rural free-ranging, and their abundance varied widely across protected areas (0–73 individuals). Dogs used protected areas near human houses for longer periods (e.g., >50% of sampling occasions) compared to more distant areas. We found no evidence that their probability of continued use varied with season or mammal richness. Dog detection probability decreased linearly among occasions, possibly due to the owners confining their dogs after becoming aware of our presence. Comparing our estimates to those for native carnivoran, we found that dogs were three to 85 times more abundant than ocelots ( Leopardus pardalis ), two to 25 times more abundant than puma ( Puma concolor ), and approximately five times more abundant than the crab-eating fox ( Cerdocyon thous ). Combining camera trapping data with modern mark–recapture methods provides important demographic information on free-ranging dogs that can guide management strategies to directly control dogs' abundance and ranging behavior.

Ecosphere↗
USGS2016

Shrinking windows of opportunity for oak seedling establishment in southern California mountains

Seedling establishment is a critical step that may ultimately govern tree species’ distribution shifts under environmental change. Annual variation in the location of seed rain and microclimates results in transient “windows of opportunity” for tree seedling establishment across the landscape. These establishment windows vary at fine spatiotemporal scales that are not considered in most assessments of climate change impacts on tree species range dynamics and habitat displacement. We integrate field seedling establishment trials conducted in the southern Sierra Nevada and western Tehachapi Mountains of southern California with spatially downscaled grids of modeled water-year climatic water deficit (CWD wy ) and mean August maximum daily temperature ( T max ) to map historical and projected future microclimates suitable for establishment windows of opportunity for Quercus douglasii , a dominant tree species of warm, dry foothill woodlands, and Q. kelloggii , a dominant of cooler, more mesic montane woodlands and forests. Based on quasi-binomial regression models, Q. douglasii seedling establishment is significantly associated with modeled CWD wy and to a lesser degree with modeled T max . Q. kelloggii seedling establishment is most strongly associated with T max and best predicted by a two-factor model including CWD wy and T max . Establishment niche models are applied to explore recruitment window dynamics in the western Tehachapi Mountains, where these species are currently widespread canopy dominants. Establishment windows are projected to decrease by 50–95%, shrinking locally to higher elevations and north-facing slopes by the end of this century depending on the species and climate scenario. These decreases in establishment windows suggest the potential for longer-term regional population declines of the species. While many additional processes regulate seedling establishment and growth, this study highlights the need to account for topoclimatic controls and interannual climatic variation when assessing how seedling establishment and colonization processes could be affected by climate change.

California↗
USGS2016

Spatial and ecological variation in dryland ecohydrological responses to climate change: implications for management

Ecohydrological responses to climate change will exhibit spatial variability and understanding the spatial pattern of ecological impacts is critical from a land management perspective. To quantify climate change impacts on spatial patterns of ecohydrology across shrub steppe ecosystems in North America, we asked the following question: How will climate change impacts on ecohydrology differ in magnitude and variability across climatic gradients, among three big sagebrush ecosystems (SB-Shrubland, SB-Steppe, SB-Montane), and among Sage-grouse Management Zones? We explored these potential changes for mid-century for RCP8.5 using a process-based water balance model (SOILWAT) for 898 big sagebrush sites using site- and scenario-specific inputs. We summarize changes in available soil water (ASW) and dry days, as these ecohydrological variables may be helpful in guiding land management decisions about where to geographically concentrate climate change mitigation and adaptation resources. Our results suggest that during spring, soils will be wetter in the future across the western United States, while soils will be drier in the summer. The magnitude of those predictions differed depending on geographic position and the ecosystem in question: Larger increases in mean daily spring ASW were expected for high-elevation SB-Montane sites and the eastern and central portions of our study area. The largest decreases in mean daily summer ASW were projected for warm, dry, mid-elevation SB-Montane sites in the central and west-central portions of our study area (decreases of up to 50%). Consistent with declining summer ASW, the number of dry days was projected to increase rangewide, but particularly for SB-Montane and SB-Steppe sites in the eastern and northern regions. Collectively, these results suggest that most sites will be drier in the future during the summer, but changes were especially large for mid- to high-elevation sites in the northern half of our study area. Drier summer conditions in high-elevation, SB-Montane sites may result in increased habitat suitability for big sagebrush, while those same changes will likely reduce habitat suitability for drier ecosystems. Our work has important implications for where land managers should prioritize resources for the conservation of North American shrub steppe plant communities and the species that depend on them.

Ecosphere↗
USGS2017

Alternative foraging strategies enable a mountain ungulate to persist after migration loss

The persistence of many migratory ungulate populations worldwide is threatened due to anthropogenic impacts to seasonal ranges and migration routes. While many studies have linked migratory ungulate declines to migration disruption or loss, very few have explored the underlying factors that determine whether a population perishes or persists. In some cases, populations undergo severe declines and extirpation after migration loss; however, others appear able to persist as residents. We predict that to persist, populations must replace the traditional benefits of migration by altering the foraging strategies they employ as residents within one seasonal range. We propose the alternative foraging strategies (AFS) hypothesis as a framework for identifying various behavioral strategies that populations may use to cope with migration loss. We tested the hypothesis using the formerly migratory Teton bighorn sheep population in northwest Wyoming, which ceased migrating over 60 yr ago, but has persisted as a resident population. We used global positioning system data to evaluate winter and summer habitat selection and seasonal elevational movements for 28 adult female bighorn sheep ( Ovis canadensis ) from 2008 to 2010. Resource selection functions revealed that bighorn sheep employ winter foraging strategies to survive as residents by seeking out rugged, high-elevation, windswept ridgelines. Seasonal movement analyses indicated that bighorn sheep undergo a newly documented “abbreviated migration” strategy that is closely synchronized with vegetation green-up patterns within their one range. Bighorn sheep descend 500 m in elevation and travel up to 10 km in spring, gaining access to newly emergent forage approximately 30 d before it appears on their high-elevation winter and summer ranges. Our findings indicate that the Teton bighorn sheep population has persisted due to its habitat selection, AFS, and unique movement patterns, which allow migration loss to be mediated to some extent. The identification of AFS and the habitats that support them can help reveal the underlying benefits of migration and conserve populations in the face of future migration loss.

Wyoming↗
USGS2017

Potential paths for male-mediated gene flow to and from an isolated grizzly bear population

For several decades, grizzly bear populations in the Greater Yellowstone Ecosystem (GYE) and the Northern Continental Divide Ecosystem (NCDE) have increased in numbers and range extent. The GYE population remains isolated and although effective population size has increased since the early 1980s, genetic connectivity between these populations remains a long-term management goal. With only ~110 km distance separating current estimates of occupied range for these populations, the potential for gene flow is likely greater now than it has been for many decades. We sought to delineate potential paths that would provide the opportunity for male-mediated gene flow between the two populations. We first developed step-selection functions to generate conductance layers using ecological, physical, and anthropogenic landscape features associated with non-stationary GPS locations of 124 male grizzly bears (199 bear-years). We then used a randomized shortest path (RSP) algorithm to estimate the average number of net passages for all grid cells in the study region, when moving from an origin to a destination node. Given habitat characteristics that were the basis for the conductance layer, movements follow certain grid cell sequences more than others and the resulting RSP values thus provide a measure of movement potential. Repeating this process for 100 pairs of random origin and destination nodes, we identified paths for three levels of random deviation (θ) from the least-cost path. We observed broad-scale concordance between model predictions for paths originating in the NCDE and those originating in the GYE for all three levels of movement exploration. Model predictions indicated that male grizzly bear movement between the ecosystems could involve a variety of routes, and verified observations of grizzly bears outside occupied range supported this finding. Where landscape features concentrated paths into corridors (e.g., because of anthropogenic influence), they typically followed neighboring mountain ranges, of which several could serve as pivotal stepping stones. The RSP layers provide detailed, spatially explicit information for land managers and organizations working with land owners to identify and prioritize conservation measures that maintain or enhance the integrity of potential areas conducive to male grizzly bear dispersal.

Montana↗
USGS2017

Co-producing simulation models to inform resource management: a case study from southwest South Dakota

Simulation models can represent complexities of the real world and serve as virtual laboratories for asking “what if…?” questions about how systems might respond to different scenarios. However, simulation models have limited relevance to real-world applications when designed without input from people who could use the simulated scenarios to inform their decisions. Here, we report on a state-and-transition simulation model of vegetation dynamics that was coupled to a scenario planning process and co-produced by researchers, resource managers, local subject-matter experts, and climate change adaptation specialists to explore potential effects of climate scenarios and management alternatives on key resources in southwest South Dakota. Input from management partners and local experts was critical for representing key vegetation types, bison and cattle grazing, exotic plants, fire, and the effects of climate change and management on rangeland productivity and composition given the paucity of published data on many of these topics. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted important tradeoffs between grazer density and vegetation composition, as well as between the short- and long-term costs of invasive species management. It also pointed to impactful uncertainties related to the effects of fire and grazing on vegetation. More broadly, a scenario-based approach to model co-production bracketed the uncertainty associated with climate change and ensured that the most important (and impactful) uncertainties related to resource management were addressed. This cooperative study demonstrates six opportunities for scientists to engage users throughout the modeling process to improve model utility and relevance: (1) identifying focal dynamics and variables, (2) developing conceptual model(s), (3) parameterizing the simulation, (4) identifying relevant climate scenarios and management alternatives, (5) evaluating and refining the simulation, and (6) interpreting the results. We also reflect on lessons learned and offer several recommendations for future co-production efforts, with the aim of advancing the pursuit of usable science.

South Dakota↗
USGS2018

Effects of environmental variables on invasive amphibian activity: Using model selection on quantiles for counts

Many different factors influence animal activity. Often, the value of an environmental variable may influence significantly the upper or lower tails of the activity distribution. For describing relationships with heterogeneous boundaries, quantile regressions predict a quantile of the conditional distribution of the dependent variable. A quantile count model extends linear quantile regression methods to discrete response variables, and is useful if activity is quantified by trapping, where there may be many tied (equal) values in the activity distribution, over a small range of discrete values. Additionally, different environmental variables in combination may have synergistic or antagonistic effects on activity, so examining their effects together, in a modeling framework, is a useful approach. Thus, model selection on quantile counts can be used to determine the relative importance of different variables in determining activity, across the entire distribution of capture results. We conducted model selection on quantile count models to describe the factors affecting activity (numbers of captures) of cane toads ( Rhinella marina ) in response to several environmental variables (humidity, temperature, rainfall, wind speed, and moon luminosity) over eleven months of trapping. Environmental effects on activity are understudied in this pest animal. In the dry season, model selection on quantile count models suggested that rainfall positively affected activity, especially near the lower tails of the activity distribution. In the wet season, wind speed limited activity near the maximum of the distribution, while minimum activity increased with minimum temperature. This statistical methodology allowed us to explore, in depth, how environmental factors influenced activity across the entire distribution, and is applicable to any survey or trapping regime, in which environmental variables affect activity.

Ecosphere↗
USGS2018

Seasonal streamflow extremes are key drivers of Brook Trout young‐of‐the‐year abundance

To manage ecosystems in the context of climate change, we need to understand the relationship between extreme events and population dynamics. Floods and droughts are projected to occur more frequently, but how aquatic species will respond to these extreme events remains uncertain. Based on counts of Brook Trout ( Salvelinus fontinalis ) collected over 28 yr at 115 sites in Shenandoah National Park, we developed mixed‐effects models to (1) assess how well extreme streamflow, as compared to mean flows and total precipitation, can explain young‐of‐the‐year (YOY) abundance, (2) identify potential nonlinear relationships between seasonal environmental covariates and abundance using nonlinear generalized additive mixed models, and (3) explore likely impacts of expected future weather and streamflow conditions. We found that (1) using covariates of streamflow extremes improved prediction of YOY abundance compared to use of mean seasonal flow values or precipitation as a proxy, (2) warmer maximum daily spring temperatures were associated with increased YOY abundance up to about 1.5 standard deviations, above which abundance declined, and (3) a strong negative effect of extreme winter streamflow, unlikely to be offset by possibly positive effects from other seasons, is expected to have a detrimental impact on Brook Trout populations given predicted increases in winter precipitation. Because YOY abundance is a strong determinant of population dynamics for these short‐lived species, extreme events will have the potential to exert a strong influence on population persistence of Brook Trout in a changing climate. Management actions that maximize resiliency of populations in response to extreme events, such as restoration of habitat connectivity, should be prioritized to buffer negative impacts.

Virginia↗
USGS2018

The relationship between invader abundance and impact

The impacts of invasive species generally increase with their abundance, but the form of invader abundance–impact relationships remain poorly described. We highlight the utility of abundance–impact curves for three questions. First, abundance–impact relationships can clarify whether prevention and management should focus on the species likely to become abundant or those likely to cause large impacts per individual. Second, comparing abundance–impact relationships between native and exotic species can reveal any systematic differences in their effects on ecological systems. Third, identifying any thresholds in the relationship between invader impact and abundance can be used to select management targets and design invasive species control strategies. With increasing extent and resolution of datasets of invasive organisms worldwide, we now have the opportunity to explore in detail the form and context dependence of the abundance–impact relationship. Doing so provides opportunities to improve the prediction of invader impact, to better understand the differences between exotic and resident organisms, and to scale the impacts of invasive species from localities to ranges.

Ecosphere↗
USGS2019

Simulating demography, genetics, and spatially explicit processes to inform reintroduction of a threatened char

The success of species reintroductions can depend on a combination of environmental, demographic, and genetic factors. Although the importance of these factors in the success of reintroductions is well‐accepted, they are typically evaluated independently, which can miss important interactions. For species that persist in metapopulations, movement through and interaction with the landscape is predicted to be a vital component of persistence. Simulation‐based approaches are a promising technique for evaluating the independent and combined effects of these factors on the outcome of various reintroduction and associated management actions. We report results from a simulation study of bull trout ( Salvelinus confluentus ) reintroduction to three watersheds of the Pend Oreille River system in northeastern Washington State, USA. We used an individual‐based, spatially explicit simulation model to evaluate how reintroduction strategies, life history variation, and riverscape structure (e.g., network topology) interact to influence the demographic and genetic characteristics of reintroduced bull trout populations in three watersheds. Simulation scenarios included a range of initial genetic stocks (informed by empirical bull trout genetic data), variation in migratory tendency and life history, and two landscape connectivity alternatives representing a connected network (isolation‐by‐distance) and a fragmented network (isolation‐by‐barrier, using the known existing barriers). A novel feature of these simulations was the ability to consider the interaction of both demographic and genetic (i.e., demogenetic) factors in riverscapes with implicit asymmetric movement probabilities across the barriers. We found that connectivity (presence or absence of barriers) had the largest effect on demographic and genetic outcomes over 200 yr, with a greater effect than both initial genetic diversity and life history variation. We also identified regions of the study system in which bull trout populations persisted across a wide range of demographic, life history, and environmental connectivity parameters. Finally, we found no evidence that initial neutral genetic diversity influenced genetic diversity and structure after 200 yr; instead, genetic drift due to stray rate and population isolation dominated and erased any initial differences in genetic diversity. Our results highlight the utility of spatially explicit demogenetic approaches in exploring and understanding population dynamics—and their implications for management strategies—in fresh waters.

Washington↗
USGS2019

Knowing your limits: Estimating range boundaries and co-occurrence zones for two competing plethodontid salamanders

Understanding threats to species persistence requires knowledge of where species currently occur. We explore methods for estimating two important facets of species distributions, namely where the range limit occurs and how species interactions structure distributions. Accurate understanding of range limits is crucial for predicting range dynamics and shifts in response to interspecific interactions and climate change. Additionally, species interactions are increasingly recognized as an important but not well‐understood predictor of range shifts. Our objective was to predict range limits and contact zones for two plethodontid salamanders, the highly range‐restricted Shenandoah salamander ( Plethodon shenandoah ) and the wide‐ranging red‐backed salamander ( Plethodon cinereus ). Using detection/non‐detection data, we assess four methodological decisions when estimating species’ distributions: (1) accounting for imperfect detection, (2) covariates to predict species occurrences, (3) accounting for species interactions, and (4) the inclusion of spatial autocorrelation. We found that Shenandoah salamander and red‐backed salamander co‐occurrence would have been underestimated and the range edge misidentified had we not accounted for incomplete detection. Covariates related to habitat were not sufficient to explain species’ range boundaries. Models that included spatial autocorrelation (i.e., a conditional autoregressive random effect) performed better than models that included just species interactions (i.e., detection and occurrence were conditional on the other species being present) and models that included both spatial autocorrelation and species interactions. Further, we found that the breadth of primary contact zones was typically 60–170 m, which is greater on average than previous estimates. In addition, we frequently observed secondary, disjunct contact zones along the range boundary. Understanding the extent to which species co‐occur and how the range boundaries are shaped is crucial to conservation efforts. Our work indicates that accounting for detection is crucial for accurately characterizing range edges and that spatial models may be especially effective in modeling distributions at the boundary.

Ecosphere↗
USGS2019

The importance of simulation assumptions when evaluating detectability in population models

Population monitoring is important for investigating a variety of ecological questions, and N-mixture models are increasingly used to model population size (N) and trends (lambda) while estimating detectability (p) from repeated counts within primary periods (when populations are closed to changes). Extending these models to dynamic processes with serial dependence across primary periods may relax the closure assumption, but simulations to evaluate models and inform effort (e.g., number of repeated counts) typically assume p is constant or random across sites and years. Thus, it is unknown how these models perform under scenarios where trends in p confound inferences on N and lambda, and conclusions regarding effort may be overoptimistic. Here, we used global positioning system (GPS) data from greater sage-grouse (Centrocercus urophasianus) to inform simulations of the detection process for lek counts of this species, and we created scenarios with and without linear annual trends in p. We then compared estimates of N and lambda from hierarchical population models either fit with single maximum counts or with detectability estimated from repeated counts (dynamic N-mixture models). We also explored using auxiliary data to correct counts for variation in detectability. Uncorrected count models consistently underestimated N by >50% whereas N-mixture models without auxiliary data underestimated N to a lesser degree due to unmodeled heterogeneity in p such as age. Nevertheless, estimates of lambda from both types of models were unbiased and similar for scenarios without trends in p. When p declined systematically across years, uncorrected count models underestimated lambda whereas N-mixture models estimated lambda with little bias when all sites were counted repeatedly. Auxiliary data also reduced bias in parameter estimates. Evaluating population models using scenarios with systematic variation in p may better reveal potential biases and inform effort than simulations that assume p is constant or random. Dynamic N-mixture models can distinguish between trends in p and N, but also require repeated counts within primary periods for accurate estimates. Auxiliary data may be useful when researchers lack repeated counts, wish to monitor more sites less intensively, or require unbiased estimates of N.

Ecosphere↗
USGS2020

Is your ad hoc model selection strategy affecting your multimodel inference?

(Yackulic) 1. Ecologists routinely fit complex models with multiple parameters of interest, where hundreds or more competing models are plausible. To limit the number of fitted models, ecologists often define a model selection strategy composed of a series of stages in which certain features of a model are compared while other features are held constant. Defining these multi-stage strategies requires making a series of decisions, which may potentially impact inferences, but have not been critically evaluated. 2. We begin by identifying key features of strategies, introducing descriptive terms when they did not already exist in the literature. Strategies differ in how they define and order model building stages. Sequential-by-sub-model strategies focus on one sub-model (parameter) at a time with modeling of subsequent sub-models dependent on the selected model structures from the previous stages. Secondary candidate set strategies model sub-models independently and combine the top set of models from each sub-model for selection in a final stage. Build-up approaches define stages across sub-models and increase in complexity at each stage. Strategies also differ in how the top set of models is selected in each stage and whether they use null or more complex model structures for non-target sub-models. 3. We tested the performance of different model selection strategies using four datasets and three model types. For each dataset, we determined the “true” distribution of AIC weights by fitting all plausible models. Then, we calculated the number of models that would have been fitted and the portion of “true” AIC weight we recovered under different model selection strategies. 4. Sequential-by-sub-model strategies often performed poorly. Build-up or secondary candidate sets were more reliable, provided all models within 5 AIC of the top model were carried forward to subsequent stages. The structure of non-target sub-models was less important. 5. Multi-stage approaches cannot compensate for a lack of critical thought in selecting covariates and building models to represent competing a priori hypotheses. However, even when competing hypotheses for different sub-models are limited, thousands or more models may be possible so strategies to explore candidate model space reliably and efficiently will be necessary.

Ecosphere↗
USGS2020

Distance effects of gas field infrastructure on pygmy rabbits in southwestern Wyoming

As domestic energy development activity continues in the western United States, wildlife conservation planning in affected regions is increasingly important. The geologic basins where oil and gas energy exploration is occurring are primarily sagebrush steppe rangelands. Sagebrush steppe habitats may support more than 20 vertebrate species of conservation concern, and for many of these species, information is lacking on the effects of gas energy development. In earlier work, we demonstrated a negative relationship among development density of gas field infrastructure and pygmy rabbits ( Brachylagus idahoensis ). We now examine the spatial relationship among gas field infrastructure, pygmy rabbits, and their habitat on four major gas fields in southwest Wyoming. Using data collected from 120 plots over three years (2011–2013) and 2012 National Agriculture Imagery Program (NAIP) imagery, we evaluated (1) whether well pads are more likely to be located in areas of pygmy rabbit habitat, (2) whether the presence and abundance of pygmy rabbits are related to distance from infrastructure, and, if so, (3) how much of the total surface area on a gas field is affected. Well pads on three gas fields occurred in higher quality pygmy rabbit habitat than did a set of randomly generated points, and the abundance and probability of pygmy rabbits being present were lower within approximately 0.5–1.5 km of the nearest road and 2 km of well pads and utilities. Buffering a digital layer of roads and well pads on one gas field revealed that nearly 82% of the (4417 km 2 ) surface area was within 1 km of infrastructure, and over 95% of the gas field surface area was within 2 km. This need not be the case on future gas fields. Directional and horizontal well drilling technologies now make it possible for gas to be recovered from a greater area per well pad, enabling future gas field developments that require fewer well pads, roads, and pipeline corridors. Such changes would enable increased well pad spacing and provide the opportunity to locate gas field infrastructure in areas of poor quality wildlife habitat, avoid high priority habitat, and conserve a greater amount of on‐field wildlife habitat overall.

Wyoming↗
USGS2020

Rockhopper Penguin–Imperial Cormorant mixed colonies in the Falkland Islands: A stroke of luck for late breeders

Mixed-species colonies occur frequently, especially among seabirds, and may provide mutual benefits among associated species including antipredator advantages. The “protector” species in such associations may provide early warning signals or by aggressively defending their own nests, may expel predators from the area. We explored costs and benefits to Rockhopper Penguins ( Eudyptes chrysocome ) in relation to offspring production in both monospecific colonies and those mixed with Imperial Cormorants ( Phalacrocorax atriceps ) at Saunders Island (Falkland Islands), emphasizing differences in predation pressure. We considered behavioral responses of chicks (in crèches), as well as differences in their nutritional condition, morphometric measurements, and survival compared among different breeding colonies. Our study revealed a paradox: High-quality adult penguins, those arriving early and occupying lower-elevation sites closer to the coast, produced better-nourished chicks earlier in the season. However, they averaged half the number of chicks fledged, compared to breeders that arrived later in the season. Late breeders were forced by unavailability of optimal habitat to nest in more elevated areas, forming mixed colonies with cormorants, which, in turn, provided them with protection from nest predators. This study provides an example of the role of luck in nature, and how it may compensate for differences in individual fitness.

Ecosphere↗
USGS2021

Piping plovers demonstrate regional differences in nesting habitat selection patterns along the U.S. Atlantic coast

Habitat studies that encompass a large portion of a species’ geographic distribution can explain characteristics that are either consistent or variable, further informing inference from more localized studies and improving management successes throughout the range. We identified landscape characteristics at Piping Plover nests at 21 sites distributed from Massachusetts to North Carolina and compared habitat selection patterns among the three designated U.S. recovery units (New England, New York–New Jersey, and Southern). Geomorphic setting, substrate type, and vegetation type and density were determined in situ at 928 Piping Plover nests (hereafter, used resource units) and 641 random points (available resource units). Elevation, beach width, Euclidean distance to ocean shoreline, and least-cost path distance to low-energy shorelines with moist substrates (commonly used as foraging habitat) were associated with used and available resource units using remotely sensed spatial data. We evaluated multivariate differences in habitat selection patterns by comparing recovery unit-specific Bayesian networks. We then further explored individual variables that drove disparities among Bayesian networks using resource selection ratios for categorical variables and Welch’s unequal variances t-tests for continuous variables. We found that relationships among variables and their connections to habitat selection were similar among recovery units, as seen in commonalities in Bayesian network structures. Furthermore, nesting Piping Plovers consistently selected mixed sand and shell, gravel, or cobble substrates as well as areas with sparse or no vegetation, irrespective of recovery unit. However, we observed significant differences among recovery units in the elevations, distances to ocean, and distances to low-energy shorelines of used resource units. Birds also exhibited increased selectivity for overwash habitats and for areas with access to low-energy shorelines along a latitudinal gradient from north to south. These results have important implications for conservation and management, including assessment of shoreline stabilization and habitat restoration planning as well as forecasting effects of climate change.

Connecticut, Delaware, Maryland, Massachusetts, ne↗
USGS2021

Hippopotamus movements structure the spatiotemporal dynamics of an active anthrax outbreak

Globally, anthrax outbreaks pose a serious threat to people, livestock, and wildlife. Furthermore, environmental change can exacerbate these outbreak dynamics by altering the host–pathogen relationship. However, little is known about how the quantitative spatial dynamics of host movement and environmental change may affect the spread of Bacillus anthracis , the causative agent of anthrax. Here, we use real-time observations and high-resolution tracking data from a population of common hippopotamus ( Hippopotamus amphibius ) in Tanzania to explore the relationship between river hydrology, H. amphibius movement, and the spatiotemporal dynamics of an active anthrax outbreak. We found that extreme river drying, a consequence of anthropogenic disturbances to our study river, indirectly facilitated the spread of B. anthracis by modulating H. amphibius movements. Our findings reveal that anthrax spread upstream in the Great Ruaha River (~3.5 km over a 9-day period), which followed the movement patterns of infected H. amphibius , who moved upstream as the river dried in search of remaining aquatic refugia. These upstream movements can result in large aggregations of H. amphibius . However, despite these aggregations, the density of H. amphibius in river pools did not influence the number of B. anthracis -induced mortalities. Moreover, infection by B. anthracis did not appear to influence H. amphibius movement behaviors, which suggests that infected individuals can vector B. anthracis over large distances right up until their death. Finally, we show that contact rates between H. amphibius- and B. anthracis- infected river pools are highly variable and the frequency and duration of contacts could potentially increase the probability of mortality. While difficult to obtain, the quantitative insights that we gathered during a real-time anthrax outbreak are critical to better understand, predict, and manage future outbreaks.

Ruaha National Park↗
USGS2021

Understanding the future of big sagebrush regeneration: challenges of projecting complex ecological processes

Regeneration is an essential demographic step that affects plant population persistence, recovery after disturbances, and potential migration to track suitable climate conditions. Challenges of restoring big sagebrush ( Artemisia tridentata ) after disturbances including fire-invasive annual grass interactions exemplify the need to understand the complex regeneration processes of this long-lived, woody species that is widespread across the semiarid western U.S. Projected 21st century climate change is expected to increase drought risks and intensify restoration challenges. A detailed understanding of regeneration will be crucial for developing management frameworks for the big sagebrush region in the 21st century. Here, we used two complementary models to explore spatial and temporal relationships in the potential of big sagebrush regeneration representing (1) range-wide big sagebrush regeneration responses in natural vegetation (process-based model) and (2) big sagebrush restoration seeding outcomes following fire in the Great Basin and the Snake River Plains (regression-based model). The process-based model suggested substantial geographic variation in long-term regeneration trajectories with central and northern areas of the big sagebrush region remaining climatically suitable, whereas marginal and southern areas are becoming less suitable. The regression-based model suggested, however, that restoration seeding may become increasingly more difficult, illustrating the particularly difficult challenge of promoting sagebrush establishment after wildfire in invaded landscapes. These results suggest that sustaining big sagebrush on the landscape throughout the 21st century may climatically be feasible for many areas and that uncertainty about the long-term sustainability of big sagebrush may be driven more by dynamics of biological invasions and wildfire than by uncertainty in climate change projections. Divergent projections of the two models under 21st century climate conditions encourage further study to evaluate potential benefits of re-creating conditions of uninvaded, unburned natural big sagebrush vegetation for post-fire restoration seeding, such as seeding in multiple years and, for at least much of the northern Great Basin and Snake River Plains, the control of the fire-invasive annual grass cycle.

Ecosphere↗