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USGS2000

Wildlife tradeoffs based on landscape models of habitat

It is becoming increasingly clear that the spatial structure of landscapes affects the habitat choices and abundance of wildlife. In contrast to wildlife management based on preservation of critical habitat features such as nest sites on a beach or mast trees, it has not been obvious how to incorporate spatial structure into management plans. We present techniques to accomplish this goal. We used multiscale logistic regression models developed previously for neotropical migrant bird species habitat use in South Carolina (USA) as a basis for these techniques. Based on these models we used a spatial optimization technique to generate optimal maps (probability of occurrence, P = 1.0) for each of seven species. To emulate management of a forest for maximum species diversity, we defined the objective function of the algorithm as the sum of probabilities over the seven species, resulting in a complex map that allowed all seven species to coexist. The map that allowed for coexistence is not obvious, must be computed algorithmically, and would be difficult to realize using rules of thumb for habitat management. To assess how management of a forest for a single species of interest might affect other species, we analyzed tradeoffs by gradually increasing the weighting on a single species in the objective function over a series of simulations. We found that as habitat was increasingly modified to favor that species, the probability of presence for two of the other species was driven to zero. This shows that whereas it is not possible to simultaneously maximize the likelihood of presence for multiple species with divergent habitat preferences, compromise solutions are possible at less than maximal likelihood in many cases. Our approach suggests that efficiency of habitat management for species diversity can by maximized for even small landscapes by incorporating spatial context. The methods we present are suitable for wildlife management, endangered species conservation, and nature reserve design.

Conference Paper↗

USGS2021

Temporal dynamics of sagebrush songbird abundance in relation to energy development

Spatial aspects of wildlife responses to human-induced habitat change have been examined frequently, yet the temporal dynamics of responses remain less understood. We tested alternative hypotheses for how the abundance of a suite of declining songbirds in relation to energy development changed over time. We conducted point counts at two natural gas fields during two periods spanning a decade (2008–2009 and 2018–2019), and compared the abundance of sagebrush songbirds across a gradient of surface disturbance between study periods (trend-by-time). We also assessed changes in the abundance of birds between study periods relative to additional development that had occurred (trend-over-time). We predicted that abundance responses to surface disturbance would be more negative during the second period, regardless of additional disturbance that had occurred, because of previously observed inverse relationships between surface disturbance and nest survival at our sites. Contrary to our predictions, abundance responses attenuated by the second time period for two of three species, Brewer's sparrow and sage thrasher (the latter at one energy field only). Sagebrush sparrow abundance, however, consistently decreased with surface disturbance within and between periods. Sage thrasher abundance consistently decreased with surface disturbance at one of the gas fields, and the probability of colonization by thrashers between study periods was lower where additional surface disturbance had occurred. Our results highlight the importance of revisiting wildlife responses to anthropogenic habitat changes over time, to clarify the severity and longevity of effects.

Biological Conservation↗

USGS2015

Evaluating species richness: biased ecological inference results from spatial heterogeneity in species detection probabilities

Accurate estimates of species richness are necessary to test predictions of ecological theory and evaluate biodiversity for conservation purposes. However, species richness is difficult to measure in the field because some species will almost always be overlooked due to their cryptic nature or the observer's failure to perceive their cues. Common measures of species richness that assume consistent observability across species are inviting because they may require only single counts of species at survey sites. Single-visit estimation methods ignore spatial and temporal variation in species detection probabilities related to survey or site conditions that may confound estimates of species richness. We used simulated and empirical data to evaluate the bias and precision of raw species counts, the limiting forms of jackknife and Chao estimators, and multi-species occupancy models when estimating species richness to evaluate whether the choice of estimator can affect inferences about the relationships between environmental conditions and community size under variable detection processes. Four simulated scenarios with realistic and variable detection processes were considered. Results of simulations indicated that (1) raw species counts were always biased low, (2) single-visit jackknife and Chao estimators were significantly biased regardless of detection process, (3) multispecies occupancy models were more precise and generally less biased than the jackknife and Chao estimators, and (4) spatial heterogeneity resulting from the effects of a site covariate on species detection probabilities had significant impacts on the inferred relationships between species richness and a spatially explicit environmental condition. For a real dataset of bird observations in northwestern Alaska, the four estimation methods produced different estimates of local species richness, which severely affected inferences about the effects of shrubs on local avian richness. Overall, our results indicate that neglecting the effects of site covariates on species detection probabilities may lead to significant bias in estimation of species richness, as well as the inferred relationships between community size and environmental covariates.

Ecological Applications↗

USGS2012

A catalog of Louisiana's nesting seabird colonies

Summarizing his colonial nesting waterbird survey experiences along the northern coast of the Gulf of Mexico in a paper presented to the Colonial Waterbird Group of the Waterbird Society (Portnoy 1978), bird biologist John W. Portnoy stated, “This huge concentration of nesting waterbirds, restricted almost entirely to the wetlands and estuaries of southern Louisiana, is unmatched in all of North America; for example, a 1975 inventory of wading birds along the Atlantic Coast from Maine to Florida [Custer and Osborn, in press], tallied 250,000 breeding [waterbirds] of 14 species, in contrast with the 650,000 birds of 15 species just from Sabine Pass to Mobile Bay.” The “650,000 birds” to which Portnoy referred, were tallied by him in a 1976 survey of coastal Louisiana, Mississippi, and Alabama (see below, under “Major Surveys” section). According to the National Atlas of Coastal Waterbird Colonies in the Contiguous United States: 1976-82 (Spendelow and Patton 1988), the percentages of the total U.S. populations of Laughing Gull (11%), Forster's Tern (52%), Royal Tern (16%), Sandwich Tern (77%), and Black Skimmer (44%) which annually nest in Louisiana are significant – perhaps crucially so in the cases of Forster's Tern, Sandwich Tern, and Black Skimmer. Nearly three decades after Spendelow and Patton's determinations above, coastal Louisiana still stands out as the major center of colonial wading bird and seabird nesting in all of the United States. Within those three intervening decades, however, the collective habitats which comprise Louisiana's now fragile coastal zone have taken major hits from commercial/residential, oil & gas, and other industrial development, primarily in the form of coastal erosion exacerbated by these and other factors (Portnoy 1978, Spendelow and Patton 1988, Martin and Lester 1990, Green, et al. 2006). Moreover, during this same period, both geologic subsidence rates (Tornqvist et al. 2008) and mean sea-level (Tornqvist et al. 2002) have increased, along with significant tropical storm activity; all of which have combined to impact available marsh, barrier island, beach, and dredge spoil nesting habitat for waterbirds, especially seabirds, throughout the coastal zone of Louisiana. The primary objective of this publication is to detail those coastal Louisiana colonial seabird nesting sites for which we have reasonably accurate data, in a tabular, site-by-site format. All major survey (1976-2008) data of site-by-site seabird species counts, as well as several smaller data sets, referred to in the site history tables as “miscellaneous observations” obtained during the May-June seabird breeding period, are included. It is our hope that these data will provide a dependable foundation from which future colonial seabird nesting surveys might be planned and carried out, as well as showcase the importance of coastal Louisiana's seabird rookeries, and contribute to their conservation.

Louisiana↗

USGS2025

A monitoring framework to assess forest bird population response to landscape scale mosquito suppression using the Incompatible Insect Technique

The Birds, Not Mosquitoes Monitoring and Support Science Working Group detailed methods for monitoring the population response of Hawaiian forest birds during implementation of the Incompatible Insect Technique (IIT) on the islands of Maui and Kauaʻi. The group prioritized methods for measuring the influence of mosquito suppression on populations within IIT treatment and control areas and identified focal species for IIT efficacy monitoring in birds. Three primary metrics were established to assess the impact of IIT on vulnerable species: population demography, density, and geographic range. Each metric can be evaluated using multiple methods. This report reviews those methods, with emphasis on approaches supported by pre-IIT baseline data and compatible with a before-after control-impact (BACI) study design for evaluating population responses over time. Focal avian species were selected based on population size estimates, fecundity, and disease susceptibility. We identified ʻākohekohe (Palmeria dolei), ʻiʻiwi (Drepanis coccinea), Maui ʻalauahio (Paroreomyza montana), Hawaiʻi ʻamakihi (Chlorodrepanis virens), Kauaʻi ʻamakihi (Chlorodrepanis stejnegeri), Kauaʻi ʻelepaio (Chasiempis sclateri), and ʻanianiau (Magumma parva) as focal species for monitoring population level response to disease suppression. Populations of kiwikiu (Pseudonestor xanthophrys), ʻakikiki (Oreomystis bairdi), akekeʻe (Loxops caeruleirostris), and the ʻiʻiwi population on Kauaʻi may be too small (e.g., <100 individuals) to effectively monitor, and it is unlikely that sufficient data can be collected from these birds to show IIT efficacy in a relatively short time frame (i.e., 5–10 years). Despite the logistical challenges to IIT implementation, there is potential to maintain disease-free status in individual populations of birds. Indeed, the continued existence of these critically endangered species in the wild within or near IIT treatment areas could be considered an accomplishment of IIT, given the current predictions for their extinction in the wild within 5–10 years. Demographic monitoring methods, including territory mapping, nest monitoring, mist-netting, and mark-recapture studies, provide direct evidence of survivorship and reproductive output. When combined with disease surveillance, these approaches could provide the most robust evidence of increased survivorship and productivity resulting from avian malaria suppression via IIT. However, demographic studies require several years of monitoring to achieve statistically robust BACI comparisons of survivorship and are more difficult to implement relative to other approaches. Given that these field efforts are labor-intensive and heavily reliant on personnel availability and funding, demographic monitoring could be conducted when adequate resources permit. On both Maui and Kauaʻi, passive acoustic monitoring (PAM) was identified as a priority method for monitoring the range, occupancy, and relative abundance of focal species. Autonomous recording units (ARUs) can record bird vocalizations in remote areas for several months. Innovative machine learning techniques permit rapid and semi-autonomous identification of most endemic honeycreepers on each island, maximizing sampling efficiencies and minimizing data processing costs. We predict mosquito suppression could support expansion of focal species into areas where disease transmission is currently excluding these species and expect acoustic monitoring data of focal species to reflect these spatial patterns. Additionally, the relative occupancy and call densities can be monitored temporally and spatially to assess the efficacy of IIT for supporting positive growth in vulnerable bird species. It is not yet clear if PAM is more effective than other methods, such as distance sampling, for detecting trends in the densities of rare species. However, the increased detections resulting from the larger sample size per observation point using ARUs will likely improve accuracy in detecting changes in species’ ranges. Collection of during and after treatment data within the BACI design could help to provide critical information to track avian population response, recovery, and potential range expansion related to IIT efforts. Point-transect distance sampling (point-counts) was prioritized as a method for monitoring population densities of focal species. Extensive historical sampling across focal species’ ranges provides a robust baseline for detecting change. These counts provide updated population densities and can be used to assess the distribution of focal species within IIT treatment areas. However, detecting subtle population changes with traditional distance sampling requires intensive spatial and temporal effort and may be less effective for rare species. To improve resolution, density surface modeling can integrate multiple data sources (e.g., point-counts, PAM, spot-mapping, and resightings) to estimate species-specific densities at finer spatial scales, including within and outside IIT treatment areas. This integrated modeling approach allows for detailed comparisons and may reveal early signs of recovery, including recolonization of formerly occupied sites. A coordinated monitoring strategy can allow managers to evaluate the success of mosquito suppression as a conservation intervention and support adaptive management in the face of emerging challenges.

Hawaii↗

USGS2017

Altitudinal migration and the future of an iconic Hawaiian honeycreeper in response to climate change and management

Altitudinal movement by tropical birds to track seasonally variable resources can move them from protected areas to areas of increased vulnerability. In Hawaiʻi, historical reports suggest that many Hawaiian honeycreepers such as the ‘I‘iwi ( Drepanis coccinea ) once undertook seasonal migrations, but the existence of such movements today is unclear. Because Hawaiian honeycreepers are highly susceptible to avian malaria, currently minimal in high-elevation forests, understanding the degree to which honeycreepers visit lower elevation forests may be critical to predict the current impact of malaria on population dynamics and how susceptible bird populations may respond to climate change and mitigation scenarios. Using radio telemetry data, we demonstrate for the first time that a large fraction of breeding adult and juvenile ‘I‘iwi originating from an upper-elevation (1,920 m) population at Hakalau Forest National Wildlife Refuge exhibit post-breeding movements well below the upper elevational limit for mosquitoes. Bloom data suggest seasonal variation in floral resources is the primary driver of seasonal movement for ‘I‘iwi. To understand the demographic implications of such movement, we developed a spatial individual-based model calibrated using previously published and original data. ʻI‘iwi dynamics were simulated backward in time, to estimate population levels in the absence of avian malaria, and forward in time, to assess the impact of climate warming as well as two potential mitigation actions. Even in disease-free ‘refuge’ populations, we found that breeding densities failed to reach the estimated carrying capacity, suggesting the existence of a seasonal “migration load” as a result of travel to disease-prevalent areas. We predict that ‘I‘iwi may be on the verge of extinction in 2100, with the total number of pairs reaching only ~ 0.2–12.3% of the estimated pre-malaria density, based on an optimistic climate change scenario. The probability of extinction of ‘I‘iwi populations, as measured by population estimates for 2100, is strongly related to their estimated migration propensity. Long-term conservation strategies likely will require a multi-pronged response including a reduction of malaria threats, habitat restoration and continued landscape-level access to seasonally variable nectar resources.

Ecological Monographs↗

USGS2024

Contrasting migratory chronology and routes of Lesser Scaup: Implications of different migration strategies in a broadly distributed species

Migration allows birds to improve fitness by exploiting seasonal resource peaks and avoiding limitations. Migration strategies may differ among individuals within a species, but for all strategies, the benefit of increased fitness should outweigh the costs of migration. These costs can include increased mortality risk, time constraints in the annual cycle, and metabolic energy loss. We compared migratory chronology and routes of individuals from a broadly distributed species of waterfowl, the Lesser Scaup ( Aythya affinis ; hereafter Scaup), marked at the northern (66.51000° N, 145.98556° W) and southern (44.63778° N, 111.73694° W) extents of its breeding distribution in North America. Scaup breeding farther north in interior Alaska, USA migrated greater distances and had protracted migrations, especially in fall, compared to Scaup breeding farther south in southwest Montana, USA. During migration, Scaup breeding in Alaska used more staging and stopover areas compared to Scaup breeding in Montana. Scaup breeding in Alaska also spent less time at their breeding area and more time at their wintering areas compared to Scaup breeding in Montana. In addition, Scaup breeding in Alaska were largely absent from wintering areas in the Intermountain West that were used by Scaup breeding in Montana. These differences could have important effects on Scaup fitness and could contribute to differences in fecundity and recruitment observed across the Scaup’s broad latitudinal distribution. Understanding the fitness implications of intraspecific variation in migration strategies of broadly distributed species can assist resource managers by focusing conservation efforts on specific breeding populations, informing models of disease transmission, and improving projections of species’ responses to environmental change.

Journal of Field Ornithology↗

USGS2017

Full annual cycle climate change vulnerability assessment for migratory birds

Climate change is a serious challenge faced by all plant and animal species. Climate change vulnerability assessments (CCVAs) are one method to assess risk and are increasingly used as a tool to inform management plans. Migratory animals move across regions and continents during their annual cycles where they are exposed to diverse climatic conditions. Climate change during any period and in any region of the annual cycle could influence survival, reproduction, or the cues used to optimize timing of migration. Therefore, CCVAs for migratory animals best estimate risk when they include climate exposure during the entire annual cycle. We developed a CCVA incorporating the full annual cycle and applied this method to 46 species of migratory birds breeding in the Upper Midwest and Great Lakes (UMGL) region of the United States. Our methodology included background risk, climate change exposure × climate sensitivity, adaptive capacity to climate change, and indirect effects of climate change. We compiled information about migratory connectivity between breeding and stationary non-breeding areas using literature searches and U.S. Geological Survey banding and re-encounter data. Climate change exposure (temperature and moisture) was assessed using UMGL breeding season climate and winter climate from non-breeding regions for each species. Where possible, we focused on non-breeding regions known to be linked through migratory connectivity. We ranked 10 species as highly vulnerable to climate change and two as having low vulnerability. The remaining 34 species were ranked as moderately vulnerable. In general, including non-breeding data provided more robust results that were highly individualistic by species. Two species were found to be highly vulnerable throughout their annual cycle. Projected drying will have the greatest effect during the non-breeding season for species overwintering in Mexico and the Caribbean. Projected temperature increases will have the greatest effect during the breeding season in UMGL as well as during the non-breeding season for species overwintering in South America. We provide a model for adaptive management of migratory animals in the face of projected climate change, including identification of priority species, research needs, and regions within non-breeding ranges for potential conservation partnerships.

Ecological Applications↗

USGS2004

Evaluation of ultrastructure and random effects band recovery models for estimating relationships between survival and harvest rates in exploited populations

Increased population survival rate after an episode of seasonal exploitation is considered a type of compensatory population response. Lack of an increase is interpreted as evidence that exploitation results in added annual mortality in the population. Despite its importance to management of exploited species, there are limited statistical techniques for comparing relative support for these two alternative models. For exploited bird species, the most common technique is to use a fixed effect, deterministic ultrastructure model incorporated into band recovery models to estimate the relationship between harvest and survival rate. We present a new likelihood-based technique within a framework that assumes that survival and harvest are random effects that covary through time. We conducted a Monte Carlo simulation study under this framework to evaluate the performance of these two techniques. The ultrastructure models performed poorly in all simulated scenarios, due mainly to pathological distributional properties. The random effects estimators and their associated estimators of precision had relatively small negative bias under most scenarios, and profile likelihood intervals achieved nominal coverage. We suggest that the random effects estimation method approach has many advantages compared to the ultrastructure models, and that evaluation of robustness and generalization to more complex population structures are topics for additional research. ?? 2004 Museu de Cie??ncies Naturals.

Animal Biodiversity and Conservation↗

USGS2014

Carryover effects and climatic conditions influence the postfledging survival of greater sage-grouse

Prebreeding survival is an important life history component that affects both parental fitness and population persistence. In birds, prebreeding can be separated into pre- and postfledging periods; carryover effects from the prefledging period may influence postfledging survival. We investigated effects of body condition at fledging, and climatic variation, on postfledging survival of radio-marked greater sage-grouse ( Centrocercus urophasianus ) in the Great Basin Desert of the western United States. We hypothesized that body condition would influence postfledging survival as a carryover effect from the prefledging period, and we predicted that climatic variation may mediate this carryover effect or, alternatively, would act directly on survival during the postfledging period. Individual body condition had a strong positive effect on postfledging survival of juvenile females, suggesting carryover effects from the prefledging period. Females in the upper 25th percentile of body condition scores had a postfledging survival probability more than twice that (Φ = 0.51 ± 0.06 SE) of females in the bottom 25th percentile (Φ = 0.21 ± 0.05 SE). A similar effect could not be detected for males. We also found evidence for temperature and precipitation effects on monthly survival rates of both sexes. After controlling for site-level variation, postfledging survival was nearly twice as great following the coolest and wettest growing season (Φ = 0.77 ± 0.05 SE) compared with the hottest and driest growing season (Φ = 0.39 ± 0.05 SE). We found no relationships between individual body condition and temperature or precipitation, suggesting that carryover effects operated independently of background climatic variation. The temperature and precipitation effects we observed likely produced a direct effect on mortality risk during the postfledging period. Conservation actions that focus on improving prefledging habitat for sage-grouse may have indirect benefits to survival during postfledging, due to carryover effects between the two life phases.

Ecology and Evolution↗

USGS2017

Modeling nonbreeding distributions of shorebirds and waterfowl in response to climate change

To identify areas on the landscape that may contribute to a robust network of conservation areas, we modeled the probabilities of occurrence of several en route migratory shorebirds and wintering waterfowl in the southern Great Plains of North America, including responses to changing climate. We predominantly used data from the eBird citizen-science project to model probabilities of occurrence relative to land-use patterns, spatial distribution of wetlands, and climate. We projected models to potential future climate conditions using five representative general circulation models of the Coupled Model Intercomparison Project 5 (CMIP5). We used Random Forests to model probabilities of occurrence and compared the time periods 1981–2010 (hindcast) and 2041–2070 (forecast) in “model space.” Projected changes in shorebird probabilities of occurrence varied with species-specific general distribution pattern, migration distance, and spatial extent. Species using the western and northern portion of the study area exhibited the greatest likelihoods of decline, whereas species with more easterly occurrences, mostly long-distance migrants, had the greatest projected increases in probability of occurrence. At an ecoregional extent, differences in probabilities of shorebird occurrence ranged from −0.015 to 0.045 when averaged across climate models, with the largest increases occurring early in migration. Spatial shifts are predicted for several shorebird species. Probabilities of occurrence of wintering Mallards and Northern Pintail are predicted to increase by 0.046 and 0.061, respectively, with northward shifts projected for both species. When incorporated into partner land management decision tools, results at ecoregional extents can be used to identify wetland complexes with the greatest potential to support birds in the nonbreeding season under a wide range of future climate scenarios.

Great Plains Landscape Conservation Cooperative↗

USGS2023

Application of habitat association models across regions: Useful explanatory power retained in wetland bird case study

Species often exhibit regionally specific habitat associations, so habitat association models developed in one region might not be accurate or even appropriate for other regions. Three programs to survey wetland-breeding birds covering (respectively) Great Lakes coastal wetlands, inland Great Lakes wetlands, and the Prairie Pothole Region offer an opportunity to test whether regionally specific models of habitat use by wetland-obligate breeding birds are transferrable across regions. We first developed independent, regional population density models for four species of wetland-obligate birds: Pied-billed Grebe ( Podilymbus podiceps ), Virginia Rail ( Rallus limicola ), Sora ( Porzana carolina ), and American Bittern ( Botaurus lentiginosus ). We then used adjusted pseudo- R 2 values to compare the amount of variation explained by each model when applied to data collected in each of the three regions. Although certain habitat characteristics, such as emergent vegetation and wetland area, were consistently important across regions, models for each species differed by region—both in variables selected for inclusion and often in the directionality of relationships for common variables—indicating that habitat associations for these species are regionally specific. When we applied a model developed in one region to data collected in another region, we found that explanatory power was reduced in most (71%) models. Therefore, we suggest that ecological analyses should emphasize regionally specific habitat association models whenever possible. Nonetheless, models created from inland Great Lakes wetland data had higher median explanatory power when applied to other regions, and the amount of explanatory power lost by other transferred models was relatively small. Thus, while regionally specific habitat association models are preferable, in the absence of reliable regional data, habitat association models developed in one region may be applied to another region, but the results need to be cautiously interpreted. Additionally, we found that median explanatory power was higher when local-scale habitat characteristics were included in the models, indicating that regionally specific models should ideally be based on a combination of local- and landscape-scale habitat characteristics. Conservation practitioners can leverage such regionally specific models and associated monitoring data to help prioritize areas for management activities that contribute to regional conservation efforts.

Illinois, Indiana, Michigan, Minnesota, New York, ↗

USGS2007

Selenium and Mercury Concentrations in Fish, Wolford Mountain Reservoir, Colorado, 2005

A reconnaissance investigation of selenium and total mercury in fish in Wolford Mountain Reservoir, Colorado, was conducted by the U.S. Geological Survey in June 2005, in cooperation with the Colorado River Water Conservation District. A total of 32 game and nongame fish were collected from three sites in the reservoir for analysis of selenium and total mercury. Five species of fish were sampled: white sucker (Catostomus commersonii, n=17), brown trout (Salmo trutta, n=5), rainbow trout (Oncorhynchus mykiss, n=5), cutthroat trout (Oncorhynchus clarkii, n=3), and splake (Salvelinus fontinalis x Salvelinus namaycush, n=2). Selenium concentrations ranged from 1.05 to 11.7 micrograms per gram (equivalent to parts per million or ppm) dry weight, whole body. Almost 22 percent (7 of 32) of fish samples had selenium concentrations greater than 7.91 micrograms per gram dry weight, the U.S. Environmental Protection Agency 2004 draft freshwater chronic criterion for selenium in whole-body fish tissue. Total mercury concentrations in muscle plug samples ranged from 0.012 to 0.320 microgram per gram wet weight. Concentrations of mercury in muscle plug samples are comparable to concentrations in fillet samples, and only one fish sample, a nongame white sucker, had a total mercury concentration greater than the U.S. Environmental Protection Agency water-quality criterion for the protection of human health of 0.3 microgram per gram wet weight in fillets. Converting muscle plug or fillet concentrations of mercury to whole-body concentrations, four fish samples (12.5 percent) had estimated whole-body total mercury concentrations greater than 0.1 microgram per gram wet weight concentration in whole-body fish tissue, the U.S. Fish and Wildlife Service criterion for protection of fish-eating birds and wildlife. Water-quality data for dissolved selenium and total mercury in two tributaries and three reservoir sites were compiled and compared. Dissolved concentrations of selenium in one tributary and one reservoir site (prior to 1998) were greater than 4.6 micrograms per liter, the State of Colorado chronic water-quality standard for dissolved selenium for protection of aquatic life. Total mercury concentrations in most water samples from two tributaries and three reservoir sites were less than or equal to 0.01 microgram per liter, the State of Colorado chronic water-quality standard for total mercury for protection of aquatic life. Selenium and mercury in fish in Wolford Mountain Reservoir most likely are not directly related to selenium and mercury concentrations in reservoir water, as most selenium and mercury in fish tissue results from the presence of selenium and mercury in the diet rather than through gill uptake from water. Results of this reconnaissance investigation of selenium and total mercury in fish in Wolford Mountain Reservoir indicate that concentrations of selenium were elevated in some fish. Most total mercury concentrations in fish were less than criteria levels.

Scientific Investigations Report↗

USGS2025

Fine-grained temporal population monitoring of a declining, critically endangered Hawaiian honeycreeper

Annual point counts are commonly used to monitor birds to track population densities across space and time. Palila ( Loxioides bailleui ) are surveyed annually in the first quarter, but we recently instituted quarterly sampling that offers a unique opportunity to improve estimator precision. We conducted point-transect distance sampling point counts during the first quarter of 2020 through 2024, and the second through fourth quarters in 2022 and 2023, and the second quarter in 2024. The reduced sampling intensity during the quarterly counts, however, requires model-based methods to estimate abundance to the entire sampling frame. We modeled spatial and temporal correlation using a soap film smoother within a generalized additive modeling framework, a density surface model, fitted to palila counts each quarter for the five-year timeseries to track changes in population abundances. Our results indicate that palila maintained a high-density hotspot throughout the five-year timeseries; however, the extent of the hotspot declined substantially over the timeseries while densities within the hotspot declined from about 3 birds/ha in 2020 to about 1 bird/ha in 2024, which resulted in a 66% decline in palila abundances over 5 years. Density surface model estimates give on average a confidence interval width that was 74.7% shorter than the associated distance sampling confidence interval widths. Our results indicate that palila may benefit most if management actions were applied within the remaining hotspot. Additionally, this temporally fine-grained sampling provides information on seasonal movement patterns and resource tracking, and population response to management and conservation actions. Our spatially explicit, model-based approach is applicable to a wide range of monitoring programs, particularly those with inconsistent, opportunistic spatial coverage.

Hawaii↗

USGS2025

Rallus elegans (King Rail) occupancy is stable, but habitat is in short supply in the Arkansas Delta

Secretive marsh birds experienced precipitous declines due to losses in wetland habitat across North America. However, from 1998 to 2004, wetland area increased, and between 2009 and 2019, the extent of emergent wetlands did not significantly decrease. This raises the question: how did secretive marsh birds, which are tied to emergent wetlands, respond to this period of relative stability in wetland area? Here, we use Rallus elegans (King Rail) occurrence data collected in 2005, 2006, 2012, and 2017 in the Arkansas Delta in the United States to test the hypothesis that a period of stability in wetland vegetation is linked to stable Rallus elegans occupancy. Specifically, we sought to (1) quantify relationships between R. elegans occupancy and land cover, (2) quantify temporal trends in R. elegans occupancy, and (3) characterize changes in land cover types linked to R. elegans occupancy. We developed spatial multi-season occupancy models, and our top model contained the categorical year effect but showed no trend in R. elegans occupancy between 2005 and 2017, instead showing high interannual variation in occupancy. We found strong associations between R. elegans occupancy and emergent wetlands (positive) and elevation (negative). From 2005 to 2017 in the ∼3.7 million ha Arkansas Delta, rice crop cover decreased by 294,750 ha, emergent wetlands increased by 6,719 ha, and all other cover types increased or decreased by < 7,500 ha. Thus, although emergent wetlands did increase, the total area of emergent wetlands in 2016 (22,262 ha) comprised <1% of the Arkansas Delta. Our results support the hypothesis that R. elegans occupancy stabilized during a time when the main habitat type R. elegans depend on, emergent wetlands, also stabilized in spatial extent. There is an opportunity to turn the tide in R. elegans declines by conserving extant emergent wetlands and creating new emergent wetlands.

Arkansas↗

USGS2024

Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways

The Central Valley of California (CVC) and Mid-Atlantic (MA) in the U.S. are both critical sites for nationwide food security, and many waterfowl species annually, especially during the winter, providing feeding and roosting locations for a variety of species. Mapping waterfowl distributions, using NEXRAD, may aid in the adaptive management of important waterfowl habitat and allow various government agencies to better understand the interface between wild and domestic birds and commercial agricultural practices. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl relative abundance in the CVC and MA as a function of weather, temporal period, environmental conditions, and landcover characteristics using boosted regression tree modelling. We were able to quantify the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide waterfowl management and host a high density of nationally important commercial agriculture. In general, weather, geographic (distance to features), and landcover condition (wetness index) predictors had the strongest relative effect on predicting wintering waterfowl relative abundance in both regions, while effects of land cover composition were more regionally and temporally specific. Increased daily mean temperature was a major predictor of increasing relative waterfowl abundance in both regions throughout the winter. Increasing precipitation had differing effects within regions, increasing relative waterfowl abundance in the MA, while decreasing in general within the CVC. Increasing relative waterfowl abundance in the CVC are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl relative abundance in the MA was generally higher nearer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote a better understanding of spatial associations of waterfowl to landscape features and may aid in conservation and biosecurity management protocols.

California, Delaware, Maryland, New Jersey, North ↗

USGS2024

Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways

The Central Valley of California (CVC) and Mid-Atlantic (MA) in the U.S. are both critical sites for nationwide food security (California Poultry Federation 2016, Prosser et al. 2017), and many waterfowl species annually, especially during the winter, providing feeding and roosting locations for a variety of species. Mapping waterfowl distributions, using NEXRAD, may aid in the adaptive management of important waterfowl habitat and allow various government agencies to better understand the interface between wild and domestic birds and commercial agricultural practices. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl relative abundance in the CVC and MA as a function of weather, temporal period, environmental conditions, and landcover characteristics using Boosted Regression Tree modelling. We were able to quantify the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide waterfowl management and host a high density of nationally important commercial agriculture. In general, weather, geographic (distance to features), and landcover condition (wetness index) predictors had the strongest relative effect on predicting wintering waterfowl relative abundance in both regions, while effects of land cover composition were more regionally and temporally specific. Increased daily mean temperature was a major predictor of increasing relative waterfowl abundance in both regions throughout the winter. Increasing precipitation had differing effects within regions, increasing relative waterfowl abundance in the MA, while decreasing in general within the CVC. Increasing relative waterfowl abundance in the CVC are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl relative abundance in the MA was generally higher nearer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote a better understanding of spatial associations of waterfowl to landscape features and may aid in conservation and biosecurity management protocols.

Authorea↗

USGS2012

Drought and cooler temperatures are associated with higher nest survival in Mountain Plovers

Native grasslands have been altered to a greater extent than any other biome in North America. The habitats and resources needed to support breeding performance of grassland birds endemic to prairie ecosystems are currently threatened by land management practices and impending climate change. Climate models for the Great Plains prairie region predict a future of hotter and drier summers with strong multiyear droughts and more frequent and severe precipitation events. We examined how fluctuations in weather conditions in eastern Colorado influenced nest survival of an avian species that has experienced recent population declines, the Mountain Plover (Charadrius montanus). Nest survival averaged 27.2% over a 7-yr period (n = 936 nests) and declined as the breeding season progressed. Nest survival was favored by dry conditions and cooler temperatures. Projected changes in regional precipitation patterns will likely influence nest survival, with positive influences of predicted declines in summer rainfall yet negative effects of more intense rain events. The interplay of climate change and land use practices within prairie ecosystems may result in Mountain Plovers shifting their distribution, changing local abundance, and adjusting fecundity to adapt to their changing environment.

Avian Conservation and Ecology↗