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At least 1,711 records · Page 95Linked to original sources
USGS2008

Buruli ulcer disease prevalence in Benin, West Africa: Associations with land use/cover and the identification of disease clusters

Background: Buruli ulcer (BU) disease, caused by infection with the environmental mycobacterium M. ulcerans, is an emerging infectious disease in many tropical and sub-tropical countries. Although vectors and modes of transmission remain unknown, it is hypothesized that the transmission of BU disease is associated with human activities in or around aquatic environments, and that characteristics of the landscape (e.g., land use/cover) play a role in mediating BU disease. Several studies performed at relatively small spatial scales (e.g., within a single village or region of a country) support these hypotheses; however, if BU disease is associated with land use/cover characteristics, either through spatial constraints on vector-host dynamics or by mediating human activities, then large-scale (i.e., country-wide) associations should also emerge. The objectives of this study were to (1) investigate associations between BU disease prevalence in villages in Benin, West Africa and surrounding land use/cover patterns and other map-based characteristics, and (2) identify areas with greater and lower than expected prevalence rates (i.e., disease clusters) to assist with the development of prevention and control programs. Results: Our landscape-based models identified low elevation, rural villages surrounded by forest land cover, and located in drainage basins with variable wetness patterns as being associated with higher BU disease prevalence rates. We also identified five spatial disease clusters. Three of the five clusters contained villages with greater than expected prevalence rates and two clusters contained villages with lower than expected prevalence rates. Those villages with greater than expected BU disease prevalence rates spanned a fairly narrow region of south-central Benin. Conclusion: Our analyses suggest that interactions between natural land cover and human alterations to the landscape likely play a role in the dynamics of BU disease. For example, urbanization, potentially by providing access to protected water sources, may reduce the likelihood of becoming infected with BU disease. Villages located at low elevations may have higher BU disease prevalence rates due to their close spatial proximity to high risk environments. In addition, forest land cover and drainage basins with variable wetness patterns may be important for providing suitable growth conditions for M. ulcerans, influencing the distribution and abundance of vectors, or mediating vector-human interactions. The identification of disease clusters in this study provides direction for future research aimed at better understanding these and other environmental and social determinants involved in BU disease outbreaks. ?? 2008 Wagner et al; licensee BioMed Central Ltd.

International Journal of Health Geographics↗
USGS2017

Quantifying drivers of wild pig movement across multiple spatial and temporal scales

Background The movement behavior of an animal is determined by extrinsic and intrinsic factors that operate at multiple spatio-temporal scales, yet much of our knowledge of animal movement comes from studies that examine only one or two scales concurrently. Understanding the drivers of animal movement across multiple scales is crucial for understanding the fundamentals of movement ecology, predicting changes in distribution, describing disease dynamics, and identifying efficient methods of wildlife conservation and management. Methods We obtained over 400,000 GPS locations of wild pigs from 13 different studies spanning six states in southern U.S.A., and quantified movement rates and home range size within a single analytical framework. We used a generalized additive mixed model framework to quantify the effects of five broad predictor categories on movement: individual-level attributes, geographic factors, landscape attributes, meteorological conditions, and temporal variables. We examined effects of predictors across three temporal scales: daily, monthly, and using all data during the study period. We considered both local environmental factors such as daily weather data and distance to various resources on the landscape, as well as factors acting at a broader spatial scale such as ecoregion and season. Results We found meteorological variables (temperature and pressure), landscape features (distance to water sources), a broad-scale geographic factor (ecoregion), and individual-level characteristics (sex-age class), drove wild pig movement across all scales, but both the magnitude and shape of covariate relationships to movement differed across temporal scales. Conclusions The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

Movement Ecology↗
USGS2026

Size of modern megafire not unprecedented and a cumulative fire deficit persists

Background The area burned by wildfires in western North American forests has grown since the 1980s, largely driven by individual “megafires.” Despite breaking state records for fire size, it remains uncertain whether these large fires are unprecedented, owing to limited knowledge of the area burned during historical fire regimes (pre-1900). We used new methods and 14 tree-ring fire-scar sites to evaluate whether the area burned by Arizona’s largest fire on record – the 217,741 ha 2011 Wallow Fire – was unprecedented in a multi-century context. Using the 375-year reconstruction of annual area burned, we also assessed the departure of the modern fire regime by introducing cumulative fire deficit, calculated as the cumulative sum of 20-year area burned anomalies. Results The size of the Wallow Fire was exceptional in the modern era, but comparable to the extent of burning in 1748, 1847, and 1851 on the same landscape. Notably, years of extensive fire (50,000–100,000 ha) were common on this landscape prior to 1900. The average return interval for fires exceeding 100,000 ha was just 20 years. By contrast, the 2011 Wallow Fire was the only modern fire > 10,000 ha in our study area ( n = 129, 1970–2024), leading to an 85% reduction in average annual area burned. This exceptional departure from the historical fire regime generated a cumulative fire deficit exceeding 2.0 million hectares by 2011, which continues to increase despite the occurrence of the large Wallow Fire. Conclusions Although the modern wildfire crisis is characterized by large, severe wildfires, historical fire regimes also included extensive fires. On an Arizona landscape, the sizes of several historical fires were on par with the largest wildfire on record. Similar historical precedent of large fires is likely true elsewhere in dry conifer forests of western North America. These findings underscore that future wildfire events could be even larger, and likely more severe, as fuels accumulate and the climate grows warmer and drier. Forest restoration aimed at reestablishing characteristic disturbance regimes, including frequent, large, low-severity fires, could be used to assist recovery of these ecosystems resulting from the cumulative fire deficit.

Arizona↗
USGS2013

Spatial ecological processes and local factors predict the distribution and abundance of spawning by steelhead ( Oncorhynchus mykiss ) across a complex riverscape

Processes that influence habitat selection in landscapes involve the interaction of habitat composition and configuration and are particularly important for species with complex life cycles. We assessed the relative influence of landscape spatial processes and local habitat characteristics on patterns in the distribution and abundance of spawning steelhead (Oncorhynchus mykiss), a threatened salmonid fish, across ~15,000 stream km in the John Day River basin, Oregon, USA. We used hurdle regression and a multi-model information theoretic approach to identify the relative importance of covariates representing key aspects of the steelhead life cycle (e.g., site access, spawning habitat quality, juvenile survival) at two spatial scales: within 2-km long survey reaches (local sites) and ecological neighborhoods (5 km) surrounding the local sites. Based on Akaike’s Information Criterion, models that included covariates describing ecological neighborhoods provided the best description of the distribution and abundance of steelhead spawning given the data. Among these covariates, our representation of offspring survival (growing-season-degree-days, °C) had the strongest effect size (7x) relative to other predictors. Predictive performances of model-averaged composite and neighborhood-only models were better than a site-only model based on both occurrence (percentage of sites correctly classified = 0.80±0.03 SD, 0.78±0.02 vs. 0.62±0.05, respectively) and counts (root mean square error = 3.37, 3.93 vs. 5.57, respectively). The importance of both temperature and stream flow for steelhead spawning suggest this species may be highly sensitive to impacts of land and water uses, and to projected climate impacts in the region and that landscape context, complementation, and connectivity will drive how this species responds to future environments.

Oregon↗
USGS2014

Land cover and topography affect the land transformation caused by wind facilities

Land transformation (ha of surface disturbance/MW) associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only), sites (strings with roads connecting them, buried cables and other infrastructure), and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure). An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here.

PLoS ONE↗
USGS2014

Stream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale

We developed independent predictive disturbance models for a full regional data set and four individual ecoregions (Full Region vs. Individual Ecoregion models) to evaluate effects of spatial scale on the assessment of human landscape modification, on predicted response of stream biota, and the effect of other possible confounding factors, such as watershed size and elevation, on model performance. We selected macroinvertebrate sampling sites for model development (n = 591) and validation (n = 467) that met strict screening criteria from four proximal ecoregions in the northeastern U.S.: North Central Appalachians, Ridge and Valley, Northeastern Highlands, and Northern Piedmont. Models were developed using boosted regression tree (BRT) techniques for four macroinvertebrate metrics; results were compared among ecoregions and metrics. Comparing within a region but across the four macroinvertebrate metrics, the average richness of tolerant taxa (RichTOL) had the highest R 2 for BRT models. Across the four metrics, final BRT models had between four and seven explanatory variables and always included a variable related to urbanization (e.g., population density, percent urban, or percent manmade channels), and either a measure of hydrologic runoff (e.g., minimum April, average December, or maximum monthly runoff) and(or) a natural landscape factor (e.g., riparian slope, precipitation, and elevation), or a measure of riparian disturbance. Contrary to our expectations, Full Region models explained nearly as much variance in the macroinvertebrate data as Individual Ecoregion models, and taking into account watershed size or elevation did not appear to improve model performance. As a result, it may be advantageous for bioassessment programs to develop large regional models as a preliminary assessment of overall disturbance conditions as long as the range in natural landscape variability is not excessive.

North Central Appalachians;Northeastern Highlands;↗
USGS2017

Projected impacts of climate, urbanization, water management, and wetland restoration on waterbird habitat in California’s Central Valley

The Central Valley of California is one of the most important regions for wintering waterbirds in North America despite extensive anthropogenic landscape modification and decline of historical wetlands there. Like many other mediterranean-climate ecosystems across the globe, the Central Valley has been subject to a burgeoning human population and expansion and intensification of agricultural and urban development that have impacted wildlife habitats. Future effects of urban development, changes in water supply management, and precipitation and air temperature related to global climate change on area of waterbird habitat in the Central Valley are uncertain, yet potentially substantial. Therefore, we modeled area of waterbird habitats for 17 climate, urbanization, water supply management, and wetland restoration scenarios for years 2006–2099 using a water resources and scenario modeling framework. Planned wetland restoration largely compensated for adverse effects of climate, urbanization, and water supply management changes on habitat areas through 2065, but fell short thereafter for all except one scenario. Projected habitat reductions due to climate models were more frequent and greater than under the recent historical climate and their magnitude increased through time. After 2065, area of waterbird habitat in all scenarios that included severe warmer, drier climate was projected to be >15% less than in the “existing” landscape most years. The greatest reduction in waterbird habitat occurred in scenarios that combined warmer, drier climate and plausible water supply management options affecting priority and delivery of water available for waterbird habitats. This scenario modeling addresses the complexity and uncertainties in the Central Valley landscape, use and management of related water supplies, and climate to inform waterbird habitat conservation and other resource management planning. Results indicate that increased wetland restoration and additional conservation and climate change adaptation strategies may be warranted to maintain habitat adequate to support waterbirds in the Central Valley.

California↗
USGS2017

Evaluating the role of land cover and climate uncertainties in computing gross primary production in Hawaiian Island ecosystems

Gross primary production (GPP) is the Earth’s largest carbon flux into the terrestrial biosphere and plays a critical role in regulating atmospheric chemistry and global climate. The Moderate Resolution Imaging Spectrometer (MODIS)-MOD17 data product is a widely used remote sensing-based model that provides global estimates of spatiotemporal trends in GPP. When the MOD17 algorithm is applied to regional scale heterogeneous landscapes, input data from coarse resolution land cover and climate products may increase uncertainty in GPP estimates, especially in high productivity tropical ecosystems. We examined the influence of using locally specific land cover and high-resolution local climate input data on MOD17 estimates of GPP for the State of Hawaii, a heterogeneous and discontinuous tropical landscape. Replacing the global land cover data input product (MOD12Q1) with Hawaii-specific land cover data reduced statewide GPP estimates by ~8%, primarily because the Hawaii-specific land cover map had less vegetated land area compared to the global land cover product. Replacing coarse resolution GMAO climate data with Hawaii-specific high-resolution climate data also reduced statewide GPP estimates by ~8% because of the higher spatial variability of photosynthetically active radiation (PAR) in the Hawaii-specific climate data. The combined use of both Hawaii-specific land cover and high-resolution Hawaii climate data inputs reduced statewide GPP by ~16%, suggesting equal and independent influence on MOD17 GPP estimates. Our sensitivity analyses within a heterogeneous tropical landscape suggest that refined global land cover and climate data sets may contribute to an enhanced MOD17 product at a variety of spatial scales.

Hawaii↗
USGS2024

Predicting future grizzly bear habitat use in the Bitterroot Ecosystem under recolonization and reintroduction scenarios

Many conservation actions must be implemented with limited data. This is especially true when planning recovery efforts for extirpated populations, such as grizzly bears ( Ursus arctos ) within the Bitterroot Ecosystem (BE), where strategies for reestablishing a resident population are being evaluated. Here, we applied individual-based movement models developed for a nearby grizzly bear population to predict habitat use in and near the BE, under scenarios of natural recolonization, reintroduction, and a combination. All simulations predicted that habitat use by grizzly bears would be higher in the northern half of the study area. Under the natural recolonization scenario, use was concentrated in Montana, but became more uniform across the northern BE in Idaho over time. Use was more concentrated in east-central Idaho under the reintroduction scenario. Assuming that natural recolonization continues even if bears are reintroduced, use remained widespread across the northern half of the BE and surrounding areas. Predicted habitat maps for the natural recolonization scenario aligned well with outlier and GPS collar data available for grizzly bears in the study area, with Spearman rank correlations of ≥0.93 and mean class values of ≥9.1 (where class 10 was the highest relative predicted use; each class 1–10 represented 10% of the landscape). In total, 52.4% of outlier locations and 79% of GPS collar locations were in class 10 in our predicted habitat maps for natural recolonization. Simulated grizzly bears selected habitats over a much larger landscape than the BE itself under all scenarios, including multiple-use and private lands, similar to existing populations that have expanded beyond recovery zones. This highlights the importance of recognizing and planning for the role of private lands in recovery efforts, including understanding resources needed to prevent and respond to human-grizzly bear conflict and maintain public acceptance of grizzly bears over a large landscape.

Idaho, Montana↗
USGS2024

Quantification of threats to bats at localized spatial scales for conservation and management

In a rapidly changing world, where species conservation needs vary by local habitat, concentrated conservation efforts at small spatial scales can be critical. Bats provide an array of value to the ecosystems they inhabit; many bat species are also of conservation concern. San Diego County, California, contains 22 of the 41 bat species that occur in the United States, 16 of which are on conservation watchlists. Thus, management of bat communities in San Diego County is a pressing need. Because bats exploit vast areas of the landscape and historical sampling strategies have shifted over time, a standardized way of prioritizing areas of the landscape for management would provide an integral asset to bat conservation. We leveraged long-term bat community survey data from sampling areas across San Diego County to prioritize areas with the most management need. We calculated two types of scores: species scores and threat scores. Species scores incorporated richness and conservation status, and threat scores included landscape level threats that bats could encounter. We found that urbanization, the presence of artificial lights, and areas sampled on unconserved land were all significantly associated with decreases in species richness. Further, using species and threat scores, each sampling area was placed into one of four conservation categories, in order from greatest to least conservation need, ranging from highest priority (high species score, high threat score) to lowest (low species score, low threat score). Additionally, we focused on sampling areas in which Townsend’s big-eared bat ( Corynorhinus townsendii ) and/or pallid bat ( Antrozous pallidus ) occurred. These two species are of exceptional conservation concern in San Diego County and across the western United States. We identified urbanization, the presence of artificial lights, and areas sampled on unconserved land as threats that were all significantly associated with the absence of Townsend’s big-eared bat, but not pallid bat. The strategy, methodology, and solutions proposed in our study should assist bat conservation and management efforts wherever bats occur, and can be extended to other species that require conservation attention.

California↗
USGS2003

Geographic analysis and monitoring at the United States Geological Survey

The Geographic Analysis and Monitoring (GAM) Program of the U.S. Geological Survey assesses the Nation's land surface at a variety of spatial and temporal scales to understand the rates, causes, and consequences of natural and human-induced processes and their interactions that affect the landscape over time. The program plays an important role in developing National Map tools and application. The GAM is a science and synthesis program that not only assesses the rates of changes to the Earth's land surface, but also provides reports on the status and trends of the Nation's land resources on a periodic basis, produces a land-use and land- cover database for the periodically updated map and data set-the Geographic Face of the Nation, and conducts research leading to improved understanding and knowledge about geographic processes. Scientific investigations provide comprehensive information needed to understand the environmental, resource, and economic consequences of landscape change. These analyses responds to the needs of resource managers and offers the American public baseline information to help them understand the dynamic nature of our national landscape and to anticipate the opportunities and consequences of our actions.

Cartography and Geographic Information Science↗
USGS2017

Competitive Interactions of Garlic Mustard ( Alliaria petiolata ) and Damesrocket ( Hesperis matronalis )

Competitive interactions between native plants and nonnative, invasive plant species have been extensively studied; however, within degraded landscapes, the effect of interspecific interactions among invasive plants is less explored. We investigated a competitive interaction between two sympatric, invasive mustard species that have similar life history strategies and growth forms: garlic mustard and damesrocket. Greenhouse experiments using a full range of reciprocal density ratios were conducted to investigate interspecific competition. Garlic mustard had a negative effect on the final biomass, number of leaves, and relative growth rate in height of damesrocket. Survival of damesrocket was not negatively affected by interspecific competition with garlic mustard; however, garlic mustard showed higher mortality because of intraspecific competition. These results indicated that although garlic mustard has been observed to be the dominant species in this landscape, it may not completely outcompete damesrocket in all situations. Studies of invasive species in competition are important in degraded landscapes because this is the common situation in many natural areas.

Invasive Plant Science and Management↗
USGS2020

Looking at the bigger picture: How abundance of nesting and brooding habitat influences lek-site selection by Lesser Prairie-Chickens

Lesser Prairie-Chicken ( Tympanuchus pallidicinctus ) populations have declined throughout most of their distribution since the mid-1980s. These declines are largely attributed to loss of habitat through the conversion and expansion of cropland, construction of oil wells and other anthropogenic features on the landscape, and grazing intensification. Changes in habitat availability and quality are seemingly having a disproportionate effect on the reproductive habitat of Lesser Prairie-Chickens, as some populations continue to decline. Nest and brood survival are crucial to population growth of Lesser Prairie-Chickens, with adequate reproductive habitat vital to population persistence. To better understand the influence of reproductive habitat availability on populations, we quantified the composition of reproductive habitat in lek landscapes across the northern extent of the Lesser Prairie-Chicken range. We measured vegetation at six study sites in Kansas and Colorado from 2013–2016. We sought to quantify available nest and brooding habitat adjacent to leks, investigate the relationship between reproductive habitat availability and lek attendance by males at several spatial scales, and examine vegetation characteristics that influence lek attendance. Within 5 km of a lek, 25% (2546/10,320 points) and 26% (2682/10,320 points) of random locations provided nesting and brooding habitat, respectively. Changes to reproductive habitat at both scales affected male attendance at leks. Visual obstruction of vegetation was the main predictor of male lek attendance at both spatial scales and limited the amount of reproductive habitat in lek landscapes. Accordingly, management should increase visual obstruction throughout the Lesser Prairie-Chicken range to increase reproductive success and improve populations to facilitate achieving the conservation goal set by the Western Association of Fish and Wildlife Agencies of a 10 y average Lesser Prairie-Chicken population of 67,000 birds.

Colorado, Kansas↗
USGS2006

Mixed-grass prairie passerines exhibit weak and variable responses to patch size

Much of our current understanding of the demographic effects of habitat fragmentation on bird populations is derived from studies of passerines in forests and tallgrass prairie surrounded by woody vegetation. We quantified grassland bird density, nest survival, and productivity in 41 native mixed-grass prairie pastures during 1997-2000 in southern Saskatchewan, Canada. Pastures ranged in size from 18 ha to 11,600 ha and were typically surrounded by agriculture (i.e., ranching and annual cropping). Grassland passerines did not respond strongly or uniformly to patch size. Sprague's Pipit ( Anthus spragueii ) was the only species whose density increased with pasture size. Patch size had minimal influence on nest survival of Sprague's Pipit or Clay-colored Sparrow ( Spizella pallida ); whereas nest survival increased with patch size for Savannah Sparrow ( Passerculus sandwichensis ) and declined for Baird's Sparrow ( Ammodramus bairdii ), Chestnut-collared Longspur ( Calcarius ornatus ), and Western Meadowlark ( Sturnella neglecta ). Time-specific factors (i.e., nest age, date, and year) were more important predictors of nest survival than patch size. Exploratory analyses indicated that effects of edge distance, pasture shape, or landscape on nest survival were just as likely as patch-size effects. However, effects of edge on Chestnut-collared Longspurs may be governed by landscape-level factors, because nest survival decreased with distance to edge in landscapes with increased amounts of cropland. Our results indicate that mixed-grass prairie parcels ≥18 ha play a role in the conservation of several grassland passerine species currently in decline, but the conservation of Sprague's Pipit likely depends on maintaining larger tracts of native prairie.

The Auk↗
USGS2017

Logistic quantile regression provides improved estimates for bounded avian counts: A case study of California Spotted Owl fledgling production

Counts of avian fledglings, nestlings, or clutch size that are bounded below by zero and above by some small integer form a discrete random variable distribution that is not approximated well by conventional parametric count distributions such as the Poisson or negative binomial. We developed a logistic quantile regression model to provide estimates of the empirical conditional distribution of a bounded discrete random variable. The logistic quantile regression model requires that counts are randomly jittered to a continuous random variable, logit transformed to bound them between specified lower and upper values, then estimated in conventional linear quantile regression, repeating the 3 steps and averaging estimates. Back-transformation to the original discrete scale relies on the fact that quantiles are equivariant to monotonic transformations. We demonstrate this statistical procedure by modeling 20 years of California Spotted Owl fledgling production (0−3 per territory) on the Lassen National Forest, California, USA, as related to climate, demographic, and landscape habitat characteristics at territories. Spotted Owl fledgling counts increased nonlinearly with decreasing precipitation in the early nesting period, in the winter prior to nesting, and in the prior growing season; with increasing minimum temperatures in the early nesting period; with adult compared to subadult parents; when there was no fledgling production in the prior year; and when percentage of the landscape surrounding nesting sites (202 ha) with trees ≥25 m height increased. Changes in production were primarily driven by changes in the proportion of territories with 2 or 3 fledglings. Average variances of the discrete cumulative distributions of the estimated fledgling counts indicated that temporal changes in climate and parent age class explained 18% of the annual variance in owl fledgling production, which was 34% of the total variance. Prior fledgling production explained as much of the variance in the fledgling counts as climate, parent age class, and landscape habitat predictors. Our logistic quantile regression model can be used for any discrete response variables with fixed upper and lower bounds.

The Auk↗
USGS2014

A multiscale assessment of tree avoidance by prairie birds

In North America, grassland bird abundances have declined, likely as a result of loss and degradation of prairie habitat. Given the expense and limited opportunity to procure new grasslands, managers are increasingly focusing on ways to improve existing habitat for grassland birds, using techniques such as tree removal. To examine the potential for tree removal to benefit grassland birds, we conducted 446 point counts on 35 grassland habitat patches in the highly fragmented landscape of west-central Minnesota during 2009–2011. We modeled density of four grassland bird species in relation to habitat composition at multiple scales, focusing on covariates that described grass, woody vegetation (trees and large shrubs), or combinations of grass and woody vegetation. The best-supported models for all four grassland bird species incorporated variables measured at multiple scales, including local features such as grass height, litter depth, and local tree abundance, as well as landscape-level measures of grass and tree cover. Savannah Sparrows ( Passerculus sandwichensis ), Sedge Wrens ( Cistothorus platensis ), and Bobolinks ( Dolichonyx oryzivorus ) responded consistently and negatively to woody vegetation, but response to litter depth, grass height, and grassland extent were mixed among species. Our results suggest that reducing shrub and tree cover is more likely to increase the density of grassland birds than are attempts to improve grass quality or quantity. In particular, tree removal is more likely to increase density of Savannah Sparrows and Sedge Wrens than any reasonable changes in grass quality or quantity. Yet tree removal may not result in increased abundance of grassland birds if habitat composition is not considered at multiple scales. Managers will need to either manage at large scales (80–300 ha) or focus their efforts on removing trees in landscapes that contain some grasslands but few nearby wooded areas.

Minnesota↗
USGS2017

Refined conservation strategies for Golden-winged Warblers in the West Virginia highlands with implications for the broader avian community

Golden-winged Warbler ( Vermivora chrysoptera ) populations in the Appalachian Mountains region of North America are imperiled, warranting species-specific conservation. However, management for Golden-winged Warblers can affect both early-successional and forest species, many of which are also declining in the region. We conducted point counts in sites representing a range of successional stages within the Golden-winged Warbler's breeding range in West Virginia, USA, during 2008–2015. We identified plausible models of Golden-winged Warbler density using covariates at 4 spatial scales representing annual dispersal (5-km radius), extraterritorial movement (1.5-km radius), intraterritorial movement (100-m radius), and local resource utilization (11.3-m radius). Golden-winged Warbler density peaked at an intermediate elevation at the 1.5-km radius scale, but was negatively associated with 100-m radius minimum elevation. Density was positively associated with 100-m radius shrubland cover. Southerly latitudes were associated with higher densities when modeled alone, but there was no association when controlling for other covariates. We then examined the relationship between covariates from these plausible models and avian community structure using canonical correspondence analysis to assess the value of Golden-winged Warbler conservation for the broader avian community. We identified 5 species likely to benefit from management for Golden-winged Warblers and 21 species likely to be affected positively or negatively to varying degrees depending on their affinity for early-successional vegetation communities. Golden-winged Warblers were plotted higher along the 100-m shrubland cover gradient than any other bird species, suggesting that they may be the most shrubland area–sensitive songbird in our study area. However, the species also requires heavily forested landscapes. Therefore, a species-specific conservation strategy that balances shrubland (patches of 9–13 ha in size, comprising 15% of the landscape) and contiguous forest area (≥75% of the landscape) could concurrently meet the needs of Golden-winged Warblers and the 26 other species identified.

West Virginia↗
USGS2018

Opportunistically collected data reveal habitat selection by migrating Whooping Cranes in the U.S. Northern Plains

The Whooping Crane ( Grus americana ) is a federally endangered species in the United States and Canada that relies on wetland, grassland, and cropland habitat during its long migration between wintering grounds in coastal Texas, USA, and breeding sites in Alberta and Northwest Territories, Canada. We combined opportunistic Whooping Crane sightings with landscape data to identify correlates of Whooping Crane occurrence along the migration corridor in North Dakota and South Dakota, USA. Whooping Cranes selected landscapes characterized by diverse wetland communities and upland foraging opportunities. Model performance substantially improved when variables related to detection were included, emphasizing the importance of accounting for biases associated with detection and reporting of birds in opportunistic datasets. We created a predictive map showing relative probability of occurrence across the study region by applying our model to GIS data layers; validation using independent, unbiased locations from birds equipped with platform transmitting terminals indicated that our final model adequately predicted habitat use by migrant Whooping Cranes. The probability map demonstrated that existing conservation efforts have protected much top-tier Whooping Crane habitat, especially in the portions of North Dakota and South Dakota that lie east of the Missouri River. Our results can support species recovery by informing prioritization for acquisition and restoration of landscapes that provide safe roosting and foraging habitats. Our results can also guide the siting of structures such as wind towers and electrical transmission and distribution lines, which pose a strike and mortality risk to migrating Whooping Cranes.

North Dakota, South Dakota↗