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At least 307 records · Page 17Linked to original sources
USGS2023

Estimating recruitment rate and population dynamics at a migratory stopover site using an integrated population model

Consideration of the full annual cycle population dynamics can provide useful insight for conservation efforts, but collecting data needed to estimate demographic parameters is often logistically difficult. For species that breed in remote areas, monitoring is often conducted during migratory stopover or at nonbreeding sites, and the recruitment rate of new breeding adults can be difficult to estimate directly. Here, we present an integrated population model that uses mark-resight and count data to estimate survival probability, population growth rate, and recruitment rate for an Arctic-breeding shorebird of conservation concern, the red knot ( Calidris canutus rufa ), from data collected during spring stopover in Delaware Bay, USA, from 2005 to 2018. At this site, red knots feed primarily on the eggs of spawning horseshoe crabs ( Limulus polyphemus ), a legally harvested species. We used this model to estimate the relationship between horseshoe crab abundance and red knot demographics, which informed a recent revision to the framework used to establish horseshoe crab harvest regulations. Our analysis indicates that the red knot population was most likely stable from 2005 to 2018 (average λ = 1.03, 95% credible interval [CRI]: 0.961, 1.15) despite low recruitment rates (average ρ = 0.088, 95% CRI: 0.012, 0.18). Adult survival probability was positively associated with horseshoe crab abundance in the same year (β = 0.35, 95% CRI: 0.09, 0.63), but we found no effect of horseshoe crab abundance two years previously on recruitment of new adults (β = −0.08, 95% CRI: −0.41, 0.38). Our approach demonstrates the utility of integrated population models for understanding population dynamics, even when data are only available from migratory stopover monitoring.

Delaware, New Jersey↗
USGS2023

Aquatic vegetation types identified during early and late phases of vegetation recovery in the Upper Mississippi River

Assemblage patterns and processes of aquatic vegetation in most large floodplain rivers are not well understood, particularly after plant recovery. Identifying vegetation types, which are recurring plant groupings based on species composition, diversity, and abundances, can describe plant assembly patterns and environmental drivers that aid conservation planning and management. We used a 22-year dataset ( n = 18,000 sampling plots) to identify aquatic vegetation types during an “early phase” and “late phase” of plant recovery at multiple spatial scales nested within a 500-km river reach of the Upper Mississippi River, USA. We hypothesized that vegetation types varied according to scale because of the stark environmental differences among riverine habitats and differing regional species pools along the river's latitudinal gradient, and that the late phase of recovery had developed several new vegetation types. We first used cluster analyses at multiple spatiotemporal scales to identify the number of vegetation types and their characteristics, such as indicator species, species compositions and abundances, and diversity index. Then we applied a multivariate regression to pinpoint environmental factors (such as hydrodynamics, system productivity, local habitat, and water quality) that structured those vegetation types. Clustering revealed that ~90% of plots irrespective of recovery phase were not classified into vegetation types, which indicated that most aquatic sampling plots are unique in species composition and unpredictable. However, impounded areas upriver from dams had matured five vegetation types: lotus ( Nelumbo lutea Willd.), submersed (a mix of 11 common submersed species), watercelery ( Vallisneria americana Michx.), arrowheads ( Sagittaria rigida Pursh and Sagittaria latifolia Willd.), and a diverse community (with high diversity indices and multiple life forms). The vegetation types were associated with three environmental gradients related to inundation depth and duration, system productivity, and water clarity. These five vegetation types are known to be of high ecological value to fish and wildlife and thus targets for restoration, for example, the watercelery community is principal forage for migrating canvasback ducks ( Aythya valisineria ) along the Mississippi River flyway. Our results provide insights on vegetation assembly during recovery and aid habitat conservation by providing quantitative, environmental targets for restoration.

Illinois, Iowa, Minnesota, Wisconsin↗
USGS2023

Drought survival strategies differ between coastal and montane conifers in northern California

Increasingly severe and prolonged droughts are contributing to tree stress and forest mortality across western North America. However, in many cases, we currently have poor information concerning how drought responses in forests vary in relation to competition, climate, and site and tree characteristics. We used annual tree ring evidence of 13 C discrimination (Δ 13 C) and growth metrics to assess drought resistance and resilience for six conifer species at the intersection of several bioregions in northern California. Within each species' range in northern California, we collected competition and tree characteristics from 270 focal trees across sites that varied from wetter to drier habitat conditions (54 sites). Across sites, all six conifer species weathered the severe 2013–2015 drought with reasonably high resistance and post-drought resilience. However, we found important differences in drought responses between coastal and montane species based on annual growth and Δ 13 C metrics. Broadly, the two coastal species showed consistent declines in drought resistance across successive drought years, whereas the four montane species maintained high drought resistance across drought years. More specifically, we found lower Δ 13 C and growth during drought years in coastal species, suggesting stomatal closure during drought with the potential for vulnerability to carbon depletion during long-term drought. Conversely, Δ 13 C and growth were stable in montane species throughout the drought, which may contribute to hydraulic failure under increased drought frequency and/or severity. We also evaluated environmental factors that affect Δ 13 C using data from before and during the drought. These physiological models were consistent for the two coastal species, with a positive relationship between annual precipitation and Δ 13 C and a negative relationship between tree density and Δ 13 C. Conversely, the four montane models illustrated a greater importance of site conditions on drought responses for these species. Our findings show differential risk for drought stress across diverse conifers during severe drought. This work highlights the importance of site and tree characteristics in determining drought responses across cool, annually humid coastal habitats to seasonally dry montane habitats.

California↗
USGS2023

Quantifying uncertainty in coastal salinity regime for biological application using quantile regression

Salinity regimes in coastal ecosystems are highly dynamic and driven by complex geomorphic and hydrological processes. Estuarine biota are generally adapted to salinity fluctuation, but are vulnerable to salinity extremes. Characterizing coastal salinity regime for ecological studies therefore requires representing extremes of salinity ranges at time scales relevant to ecology (e.g., daily, monthly, and seasonally). Here, we propose a framework for modeling coastal salinity with these overall goals: (1) quantify uncertainty in salinity associated with important terrestrial and oceanographic drivers, (2) examine time scales of salinity response to river streamflow events, and (3) predict salinity continuously over space at key time scales. Salinity is modeled as quantile surfaces related to river discharge, tidal dynamics, wind, and spatial location, applied to Suwannee Sound estuary, FL, USA, where salinity has been monitored spatially since 1981. Each quantile level is regressed independently, and together they comprise a distribution of salinity uncertainty across space, with upper and lower quantiles describing salinity extremes. Effects of physical drivers on salinity are compared through four base models with various combinations of tide and wind variables, each including spatial coordinates and a single streamflow metric (in cubic meters per second). Multiple time scales of streamflow are considered by taking means across various periods, from 1 to 12 days, and at various lagged intervals prior to salinity sample, totaling 144 streamflow metrics. We found that the Suwannee coastal salinity regime is dynamic at multiple time scales and varies nonlinearly across space from the river effluence outward. Salinity increases nonlinearly with decreasing river flow rates below 200 m 3 /s, most prominently in the lower quantiles of salinity (τ = 0.05–0.25). Wind appears to have a stronger influence on salinity than astronomic tides for this estuary. The regression approach developed here can be applied to any coastal system that has sufficient spatial and temporal monitoring coverage to capture multiple flood and drought events. It is implemented with a simple R routine, and is less computationally-intensive than finite difference hydrodynamic modeling. The characterizations of salinity uncertainty developed in these analyses can be directly applied to future studies of fish and wildlife responses to changes in watershed management.

Florida↗
USGS2023

Reproductive response of the Samoan swallowtail butterfly to variability in host plant and habitat characteristics

The Samoan swallowtail butterfly ( Papilio godeffroyi ) has become restricted to Tutuila Island, American Samoa. Factors driving its extirpation on other islands may be partly due to the availability and suitability of habitat, given the singular association we observed of P. godeffroyi with its host plant, Micromelum minutum. We expected that as a host plant specialist, P. godeffroyi might respond to variation in the physical traits and habitat context of M. minutum , which could help identify conservation opportunities throughout its present and former range. Because the ecology of P. godeffroyi is largely unknown, we conducted systematic surveys during 15 months in 2013 and 2014 on Tutuila to investigate its reproductive response to the physical and phenological variability of individual host trees and to the structural and geographical variability of the stands in which they occurred. We searched foliage for eggs, larvae, and pupae and monitored seasonal trends in herbivory and production of leaves, flowers, and fruits on 117 host trees in 8 rainforest stands, mostly within the National Park of American Samoa (NPSA), starting in March 2013 and ending in August 2014. We observed high variability in butterfly reproductive output between individual trees and stands, due largely to a strong negative relationship between leaf biomass (at both tree and stand levels) and oviposition density (number of eggs per foliar biomass) and frequency (number of eggs per survey). Distribution patterns of larvae and pupae were less distinct but generally followed trends in oviposition. Our findings indicate that the butterfly is reproducing widely across Tutuila and is likely to respond positively to management to increase the availability of small host trees in low-density stands. Thus, the species is a good candidate for conservation management focusing on habitat.

Tutuila Island↗
USGS2023

Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment

High interannual variability of forage production in semiarid grasslands leads to uncertainties when livestock producers make decisions, such as buying additional feed, relocating animals, or using flexible stocking. Within-season predictions of annual forage production (i.e., yearly production) can provide specific boundaries for producers to make these decisions with more information and possibly with higher confidence. In this study, we use a recently developed forage production model, ForageAhead, that uses environmental and seasonal climate variables to estimate the annual forage production as approximated by remotely sensed vegetation data. Because, among other variables, this model uses observed summer climate data, the model output cannot be produced early enough in the year (e.g., spring months) to inform within-season management decisions. To address this issue, we developed summer climate scenarios (e.g., extremely warm and dry and moderately cool and wet) that serve as an input in the model in combination with observed winter and spring climate data from a particular year. The summer climate scenarios used historical summer precipitation and temperature data (1950–2018) categorized into three, five, and seven percentile categories. These percentile values were then combined to represent summer climate scenarios, which were further used as the ForageAhead model input. We tested the optimal number of percentile categories to be used as the model input to obtain accurate prediction of forage production while also minimizing the number of possible temperature and precipitation combinations, which increases with the number of percentile categories. For the 19-year period analysis (2000–2018), we also determined the most and least common scenarios that occurred in the western United States. When using five percentile categories for summer precipitation and temperature, we were able to capture the interannual variability in the spatial extent of abnormally low and high biomass production. The ForageAhead predictions captured similar spatial patterns of forage anomalies as another similar model (Grass-Cast). This method can be made available in a user-friendly automated system that can be used by livestock producers and rangeland managers to inform within-season management decisions. This method can be especially valuable for flexible stocking as it provides a range of possible annual forage production scenarios by the end of May.

Ecosphere↗
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, ↗
USGS2023

Diverse migratory portfolios drive inter-annual switching behavior of elk across the Greater Yellowstone Ecosystem

A growing body of evidence shows that some ungulates alternate between migratory and nonmigratory behaviors over time. Yet it remains unclear whether such short-term behavioral changes can help explain reported declines in ungulate migration worldwide, as opposed to long-term demographic changes. Furthermore, advances in tracking technology reveal that a simple distinction between migration and nonmigration may not sufficiently describe all individual behaviors. To better understand the dynamics and drivers of ungulate switching behavior, we investigated 14 years of movement data from 361 elk in 20 herds across the Greater Yellowstone Ecosystem (GYE). First, we categorized yearly individual behaviors using a clustering algorithm that identified similar migratory tactics across a continuum of behaviors. Then, we tested seven hypotheses to explain why some ungulates switch behaviors, and we evaluated how behavioral changes affected the proportions of different behaviors across the system. We identified four distinct behavioral tactics: residents (4.8% of elk-years), short-distance migrants (53.7%), elevational migrants (21.9%) and long-distance migrants (19.6%). Of the 20 herds, 18 were partially migratory, and 5 had all four movement tactics present. We observed switches between migratory tactics in all sets of consecutive years during our study period, with an average of 22.5% of individual elk changing movement tactics from one year to the next. Elk in herds with higher movement tactic diversity were significantly more likely to switch tactics and often responded more effectively to adverse environmental conditions, compared to those in herds with low movement tactic diversity. During our study period, switching increased the prevalence of both short- and long-distance migrants, decreased the prevalence of elevational migrants, and had no effect on the prevalence of residents. Our findings suggest that rather than contributing to the declining migratory behavior found in the GYE, switching behavior may enable greater resiliency to continuously changing environmental and anthropogenic conditions.

Wyoming↗
USGS2023

Marmots do not drink coffee: Human urine contributions to the nitrogen budget of a popular national park destination

Reactive nitrogen (Nr) concentrations are higher than expected for mountain lakes in Rocky Mountain National Park, and for many years, high Nr concentrations have been attributed to atmospheric Nr deposition from regional and more distant emission sources, including combustion of fossil fuels and agricultural activities. Here, we estimated the contribution from a very local source, that of human urine, related to intensive use by visitors in Loch Vale Watershed (LVWS). Not only does urine convey hormones, pharmaceuticals, antibiotic-resistant bacteria, and antibiotic-resistant genes to the environment, but it also contributes Nr, which contributes to loss of biodiversity and eutrophication. Using caffeine as a specific marker for human urine, we compared the calculated maximum potential input of urine with that from wet atmospheric Nr deposition. The maximum potential input is a worst-case scenario. Nearly 30,000 and 45,000 people hiked the 4.0 km to the Loch, the lowest lake in LVWS, in June–September 2019 and 2020, respectively. Informal trails and informal latrine sites were mapped, and the contribution of human urine was calculated based on several assumptions, including that each visitor voided their bladder on the ground once per visit somewhere in Loch Vale. The resulting Nr input from urine in Loch Vale for the summer months of June through September was 0.02 kg Nr ha −1 , and prorated to a full year, the 2019 potential contribution of human waste was 0.06 kg ha −1 year −1 . These values are compared with June–September 1.2 kg Nr ha −1 from wet atmospheric deposition or annual measured 2019 deposition of 2.5 kg Nr ha −1 year −1 , to indicate a contribution of 2% Nr to the waters of Loch Vale from local human urine. Most Nr in this alpine and subalpine watershed is still attributable to emissions and subsequent wet atmospheric deposition, but a 2% contribution from human waste is not insignificant. In the very broadest sense, our results document an ecological disturbance from an unprecedented level of human activity in a protected and designated wilderness area. Local solutions to this local problem could include greater outreach to visitors of public lands about the consequences of their activities and installation of latrines.

Colorado↗
USGS2023

Coral restoration for coastal resilience: Integrating ecology, hydrodynamics, and engineering at multiple scales

The loss of functional and accreting coral reefs reduces coastal protection and resilience for tropical coastlines. Coral restoration has potential for recovering healthy reefs that can mitigate risks from coastal hazards and increase sustainability. However, scaling up restoration to the large extent needed for coastal protection requires integrated application of principles from coastal engineering, hydrodynamics, and ecology across multiple spatial scales, as well as filling missing knowledge gaps across disciplines. This synthesis aims to identify how scientific understanding of multidisciplinary processes at interconnected scales can advance coral reef restoration. The work is placed within the context of a decision support framework to evaluate the design and effectiveness of coral restoration for coastal resilience. Successfully linking multidisciplinary science with restoration practice will ensure that future large-scale coral reef restorations maximize protection for at-risk coastal communities.

Ecosphere↗
USGS2023

Conspecific density and habitat quality affect breeding habitat selection: Support for the social attraction hypothesis

Breeding habitat selection is a critical component of the annual cycle because of its effect on fitness. Multiple theories of habitat selection can be differentiated by their responses to the quantity of habitat, conspecific density, and habitat quality. Here, we use network analysis to understand the characteristics of fine-scale breeding habitat selected by both immigrant and returning adult piping plovers ( Charadrius melodus ) to test five hypotheses of habitat selection. Between 2014 and 2019, we recorded 2034 uniquely marked adults breeding at 326 breeding locations with 1240 successive breeding events. Among adults, immigration events (i.e., individuals that moved to a new breeding location) were detected as often as fidelity to the same breeding location. We found support for the social attraction hypothesis for both immigrants and returners, indicating that adult plovers use social cues for settlement decisions. Adult plovers selected habitats with intermediate levels of conspecific density and high habitat quality, as assessed by con- and heterospecific nest survival, with no effect from the amount of available habitat. We also simulated the loss of breeding habitat and identified highly connected breeding locations, which occurred mostly on the riverine habitat type, which have important implications for habitat conservation for this listed species. Our results highlight the role of conspecifics at identifying high-quality breeding habitat regardless of whether individuals return to the same breeding site or immigrate to new areas.

North Dakota, South Dakota↗
USGS2023

Dynamic spatiotemporal modeling of a habitat-defining plant species to support wildlife management at regional scales

Sagebrush ( Artemisia spp.) ecosystems provide critical habitat for the Greater sage-grouse ( Centrocercus urophasianus ), a species of conservation concern. Thus, future loss of sagebrush habitat because of land use change and global climate change is of concern. Here, we use a dynamic additive spatiotemporal model to estimate the effects of climate on sagebrush cover dynamics at 32 sage-grouse management (core) areas in Wyoming. We use the fitted models to quantify the sensitivity of each management area to precipitation and temperature, and to make probabilistic projections of sagebrush cover from present to 2100 under three climate change scenarios. Global circulation models predict an increase in temperature and no change in precipitation for Wyoming. Sensitivity to climate varied among management areas, but the most common response (70% of management areas) was a positive effect of temperature on sagebrush performance. The combination of positive sensitivity to temperature and the predicted increase in temperature under all climate change scenarios resulted in projections of increased sagebrush cover for most management areas. We characterized management areas as “optimal” or “suboptimal” based on the percentage of grid cells in each management area with sagebrush cover exceeding a nesting habitat target value. Only 18% of management areas are projected to switch from being currently optimal to suboptimal in the future. Thirty-five percent of management areas are projected to switch from being suboptimal to optimal. The most common outcome (47%) was for currently suboptimal management areas to remain suboptimal, even though average cover tended to increase in those areas. The direct effects of climate change appear to favor sagebrush performance in the future for most sage-grouse core areas in Wyoming. Our approach is broadly applicable to quantitative climate change assessments where remotely sensed estimates of habitat-defining vegetation are available.

Wyoming↗
USGS2023

Geographic isolation reduces genetic diversity of a wide-ranging terrestrial vertebrate, Canis lupus

Genetic diversity is theorized to decrease in populations closer to a species' range edge, where habitat may be suboptimal. Generalist species capable of long-range dispersal may maintain sufficient gene flow to counteract this, though the presence of significant barriers to dispersal (e.g., large water bodies, human-dominated landscapes) may still lead to, and exacerbate, the edge effect. We used microsatellite data for 2421 gray wolves ( Canis lupus ) from 24 subpopulations (groups) to model how allelic richness and expected heterozygosity varied with mainland–island position and two measures of range edge (latitude and distance from range center) across >7.3 million km 2 of northern North America. We expected low genetic diversity both at high latitudes, due to harsh environmental conditions, and on islands, but no change in diversity with distance to the range center due to the species' exceptional dispersal ability and favorable conditions in far eastern and western habitats. We found that allelic richness and expected heterozygosity of island groups were measurably less than that of mainland groups, and that these differences increased with the island's distance to the species' range center in the study area. Our results demonstrate how multiple axes of geographic isolation (distance from range center and island habitation) can act synergistically to erode the genetic diversity of wide-ranging terrestrial vertebrate populations despite the counteracting influence of long-range dispersal ability. These findings emphasize how geographic isolation is a potential threat to the genetic diversity and viability of terrestrial vertebrate populations even among species capable of long-range dispersal.

Alaska↗
USGS2023

Biotic and abiotic factors shaping bat activity in Maryland soybean fields

Bats are important pest control agents in agriculture. Yet, the underlying fine-scale biotic and abiotic mechanisms that drive their foraging behaviors and responses to insect outbreaks are unclear. Herbivore-induced plant volatiles (HIPVs) can attract both invertebrate and vertebrate natural enemies that use the chemical plant cues to locate insect prey. The ability of HIPVs to attract multiple species raises the question of whether they may also be a biotic factor influencing insectivorous bat activity. Additionally, abiotic factors, such as weather conditions, can affect bat activity in agricultural settings, but little is known about how bats respond to shifting environmental conditions on short timescales in this landscape context. Using a model crop system, soybean ( Glycine max ), our study asked three questions: (1) Which bat species are active in eastern Maryland soybean fields? (2) Is insectivorous bat activity affected by naturally occurring soybean HIPVs and/or synthetic soybean HIPVs (indole or farnesene)? (3) How is insectivorous bat activity affected by hourly weather conditions in this landscape? In soybean fields in eastern Maryland, we created paired treatment plots: HIPV plots (damaged plants or synthetic HIPV dispensers) and control plots (undamaged plants or empty dispensers). We measured bat activity using ultrasonic recorders, summarizing hourly and nightly activity, and detected 10 total species. The most abundant species were big brown/silver-haired bats ( Eptesicus fuscus / Lasionycteris noctivagans ). Bat activity did not significantly differ between control and HIPV plots in any of the three experiments. Thus, our results do not support our expectation that bats in eastern Maryland use soybean HIPVs to locate insect prey. However, bat activity did increase with increasing average hourly temperature and wind speed. This initial study of bats and HIPVs, as well as the fine-scale examination of weather conditions on bat activity, may serve as a guide for future research on bat–plant interactions that can support the development of new strategies for sustainable pest management.

Maryland↗
USGS2023

Integrating community science and agency-collected monitoring data to expand monitoring capacity at large spatial scales

Monitoring species to better understand their status, ecology, and management needs is a major expense for agencies tasked with biodiversity conservation. Community science data have the potential to improve monitoring for minimal cost, given appropriate analytical frameworks. We describe a framework for integrating data from the eBird community science platform with agency-collected monitoring data using a multistate occupancy model. Our model accounts for the structural differences across datasets and allows for estimation of both occupancy and breeding probabilities. The framework was applied to Common Loons ( Gavia immer ) in Washington State. A total of 766 sites had observation effort, of which 713 sites had only eBird effort, 26 sites had only Washington Department of Fish and Wildlife (WDFW) effort, and 27 sites had both. We predicted that the probability of occupancy was only 0.07 (95% Bayesian credible interval, BCI = 0.02–0.51) at the 2324 sites in our sampling frame, though the probability that Common Loons were breeding at occupied sites was 0.95 (95% BCI = 0.71–1.00). We found that probability of occupancy was positively related to waterbody size (probability of a positive effect = 0.88) and negatively related to an index of human influence (probability of a negative effect = 0.94). We found that probability of breeding at occupied sites was positively related to tree canopy cover (0.86), negatively related to elevation (0.99), and negatively related to barren, scrub/shrub, and herbaceous land cover (0.98). We found that state agency biologists were 16 times more likely to detect breeding Common Loons at a site than were eBird users (0.94, 95% BCI = 0.78–0.99 for agency biologists vs. 0.08, 95% BCI = 0.06–0.10 for eBird users). However, the amount of effort expended by eBird users meant that they confirmed Common Loons at 94 sites while agency biologists confirmed them at just 24 sites, although evidence of reproduction was only contributed by agency biologists. Our results provide a better understanding of the distribution of Common Loons in Washington, while further demonstrating that community science data can be a valuable complement to agency-collected data, if appropriate frameworks are developed to integrate these data sources.

Ecosphere↗
USGS2023

Historical fire regimes and contemporary fire effects within sagebrush habitats of Gunnison Sage-grouse

The historical role of fire in sagebrush ( Artemisia tridentata ) landscapes remains poorly understood, yet is important to inform management and conservation of obligate species such as the threatened Gunnison Sage-grouse (GUSG; Centrocercus minimus ). We reconstructed fire histories from tree-ring fire scars at sagebrush–forest ecotones (10 sites, 111 trees) to better understand the role of fire in sagebrush landscapes of the Upper Gunnison Basin (UGB), Colorado, and how fire may have changed following Euro-American settlement. We assessed likely influences of historical fire by surveying plant composition and structure at 100 sagebrush sites with and without recent (2001–2020) fires. Tree-ring fire scars revealed a history of repeated low-severity fire at sagebrush–forest ecotones until 1892, followed by over a century without fire. Between 1684 and 1892, the mean fire interval (MFI) among sites averaged 49.6 years (ranging from 18.2 to 119 years). Fire over this period occurred synchronously at two or more sites on average every 23.6 years, potentially indicative of spread between sites. Most (70%) of the historical fires burned in the early growing season, consistent with times of strong wind. Recent burns exhibited reductions in sagebrush cover (5% vs. 25% in unburned sites) and concomitant increases in herbaceous cover (55% vs. 40%). These differences declined over time but persisted for at least two decades. Burned sites were dominated by native perennial grasses, forbs, and resprouting shrub species. Historically, such openings may have served as seasonal GUSG habitat. Our results indicate that parts of the UGB sagebrush landscapes were characterized historically by frequent fire and dynamic vegetation mosaics that included open, grassy patches. These findings support the use of prescribed fire to restore and maintain this ecological process and vegetation heterogeneity. However, the contemporary context for fire has changed and now includes substantially reduced, Endangered Species Act (ESA)-listed GUSG populations, increased risk of non-native plant invasion, and climate warming. These circumstances highlight new risks, information needs, and opportunities for key knowledge co-production via management–research partnerships.

Colorado↗
USGS2023

Mammalian resistance to megafire in western U.S. woodland savannas

Increasingly frequent megafires are dramatically altering landscapes and critical habitats around the world. Across the western United States, megafires have become an almost annual occurrence, but the implication of these fires for the conservation of native wildlife remains relatively unknown. Woodland savannas are among the world's most biodiverse ecosystems and provide important food and structural resources to a variety of wildlife, but they are threatened by megafires. Despite this, the great majority of fire impact studies have only been conducted in coniferous forests. Understanding the resistance and resilience of wildlife assemblages following these extreme perturbations can help inform future management interventions that limit biodiversity loss due to megafire. We assessed the resistance of a woodland savanna mammal community to the short-term impacts of megafire using camera trap data collected before, during, and after the fire. Specifically, we utilized a 5-year camera trap data set (2016–2020) from the Hopland Research and Extension Center to examine the impacts of the 2018 Mendocino Complex Fire, California's largest recorded wildfire at the time, on the distributions of eight observed mammal species. We used a multispecies occupancy model to quantify the effects of megafire on species' space use, to assess the impact on species size and diet groups, and to create robust estimates of fire's impacts on species diversity across space and time. Megafire had a negative effect on the detection of certain mammal species, but overall, most species showed high resistance to the disturbance and returned to detection and site use levels comparable to unburned sites by the end of the study period. Following megafire, species richness was higher in burned areas that retained higher canopy cover relative to unburned and burned sites with low canopy cover. Fire management that prevents large-scale canopy loss is critical to providing refugia for vulnerable species immediately following fire in oak woodlands, and likely other mixed-forest landscapes.

California↗
USGS2023

BioLake: A first assessment of lake temperature-derived bioclimatic predictors for aquatic invasive species

Aquatic invasive species (AIS) present major ecological and economic challenges globally, endangering ecosystems and human livelihoods. Managers and policy makers thus need tools to predict invasion risk and prioritize species and areas of concern, and they often use native range climate matching to determine whether a species could persist in a new location. However, climate matching for AIS often relies on air temperature rather than water temperature due to a lack of global water temperature data layers, and predictive power of models is seldom evaluated. We developed 12 global lake (water) temperature-derived “BioLake” bioclimatic layers for distribution modeling of aquatic species and compared “climatch” climate matching predictions (from climatchR package) from BioLake with those based on BioClim temperature layers and with a null model. We did this for 73 established AIS in the United States, training the models on their ranges outside of the United States and Canada. Models using either set of climate layers outperformed the null expectation by a similar (but modest) amount on average, but some species were occasionally found in locations with low climatch scores. Mean US climatch scores were higher for most species when using air temperature. Including additional climate layers in models reduced mean climatch scores, indicating that commonly used climatch score thresholds are not absolute but can be context specific and may require calibration based upon climate data used. Although finer resolution global lake temperature data would likely improve predictions, our BioLake layers provide a starting point for aquatic species distribution modeling. Climate matching was most effective for some species that originated at low latitudes or had small ranges. Climatch scores remain useful but limited for predicting AIS risk, perhaps because current ranges seldom fully reflect climatic tolerances (fundamental niches). Managers could consider climate matching as one of a suite of tools that can be used in AIS prioritization.

Ecosphere↗