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At least 271 records · Page 15Linked to original sources
USGS2024

Droughts reshape apex predator space use and intraguild overlap

1. Droughts are increasing in frequency and severity globally due to climate change, leading to changes in resource availability that may have cascading effects on animal ecology. Resource availability is a key driver of animal space use, which in turn influences interspecific interactions like intraguild competition. Understanding how climate-induced changes in resource availability influence animal space use, and how species-specific responses scale up to affect intraguild dynamics, is necessary for predicting broader community-level responses to climatic changes. 2. Although several studies have demonstrated the ecological impacts of drought, the behavioral responses of individuals that scale up to these broader-scale effects are not well known, particularly among animals in top trophic levels, such as large carnivores. Furthermore, we currently lack understanding of how the impacts of climate variability on individual carnivore behavior are linked to intraguild dynamics, in part because multi-species datasets collected at timescales relevant to climatic changes are rare. 3. Using 11 years of GPS data from four sympatric large carnivore species in southern Africa – lions ( Panthera leo ), leopards ( Panthera pardus ), African wild dogs ( Lycaon pictus) , and cheetahs ( Acinonyx jubatus ) – spanning 4 severe drought events, we test whether drought conditions impact 1) large carnivore space use, 2) broad-scale intraguild spatial overlap, and 3) fine-scale intraguild interactions. 4. Drought conditions expanded space use across species, with carnivores increasing their monthly home range sizes by 35% (wild dogs) to 66% (leopards). Drought conditions increased the amount of spatial overlap between lions and subordinate felids (cheetahs and leopards) by up to 119%, but only lion-cheetah encounter rates were affected by these changes, declining in response to drought. 5. Our findings reveal that drought has a clear signature on the space use of multiple sympatric large carnivore species, which can alter spatiotemporal partitioning between competing species. Our study thereby illuminates the links between environmental change, animal behavior, and intraguild dynamics. While fine-scale avoidance strategies may facilitate intraguild coexistence during periodic droughts, large carnivore conservation may require considerable expansion of protected areas or revised human-carnivore coexistence strategies to accommodate the likely long-term increased space demands of large carnivores under projected increases in drought intensity.

Okavango Delta↗
USGS2018

Designing a protected area to safeguard imperiled species from urbanization

Reserve design is a process that can address ecological, social, and political factors to identify parcels of land needed to sustain wildlife populations and other natural resources. Acquisition of parcels for a large terrestrial reserve is difficult because it typically occurs over a long timeframe and thus invokes consideration of future conditions such as climate and urbanization changes. In central Florida, a new protected area, the Everglades Headwaters National Wildlife Refuge, has been authorized by the United States Government. The new refuge will host important threatened and endangered species and habitats, as well as be located to allow for species adaptation from climate change impacts. For this study we combined habitat objectives defined by the U.S. Fish and Wildlife Service and projections from two urbanization models to provide guidance for Everglades Headwaters National Wildlife Refuge design. We used Marxan with Zones to find near-optimal solutions for protecting explicit amounts of five target habitats. We identified parcels for inclusion into the reserve design that the model allocated among two zones representing different methods of protection: fee-simple purchase (up to 20,234 hectares authorized by the United States government), and conservation easement agreements (up to 40,469 hectares authorized). As expected, for all scenarios we found an increase in costs as the proportion of fee-simple purchases was increased, reflecting the lesser cost of easements, but the number of parcels required for protection differed little among scenarios. The two urbanization models showed considerable agreement over which habitat patches were not forecast to be developed, and showed some agreement over which parcels might be developed. The U.S. Fish and Wildlife Service may benefit from focusing on parcels that are selected frequently by our analyses under both urban scenarios because these parcels are more likely to be in areas where urbanization threats and demand for land is reduced. The reserve designs we generated met U.S. Fish and Wildlife Service habitat goals within fee and easement zone restrictions, and we found reserve configurations that fell well below the mandated size limit.

Florida↗
USGS2019

Top-down effect of repatriating bald eagles hinder jointly recovering competitors

1. The recovery of piscivorous birds around the world is touted as one of the great conservation successes of the 21st century, but for some species, this success was short-lived. Bald eagles, ospreys, and great blue herons began repatriating Voyageurs National Park, USA, in the mid-20th century. However, after 1990, only eagles continued their recovery, while osprey and heron recovery failed for unknown reasons. 2. We aimed to evaluate whether top-down effects of bald eagles, and bottom-up effects of inclement weather, habitat quality, and fish resources contributed to the failed recovery of ospreys and herons in a protected area. 3. We quantified the relative influence of top-down and bottom-up factors on nest colonization, persistence (i.e., nest reuse) and success for ospreys, and occurrence and size of heronries using 26 years (1986-2012) of spatially-explicit monitoring data coupled with multi-response hierarchical models and Bayesian variable selection approaches. 4. Bald eagles were previously shown to recover faster due to intensive nest protection and management. Increased numbers of eagles were associated with a reduction in the numbers of osprey nests, their nesting success, and heronry size; while higher local densities of nesting eagles deterred heronries nearby. We found little evidence of bottom-up limitations on the failed recovery of herons and ospreys. 5. We present a conservation conundrum: bald eagles are top predators and a flagship species of conservation that have benefited from intensive protection, but this likely hindered the recovery of ospreys and herons. Returning top predators, or rewilding, is widely promoted as a conservation strategy for top-down ecosystem recovery, but managing top predators in isolation of jointly recovering species can halt or reverse ecosystem recovery. Previous studies warn of the potential consequences of ignoring biotic interactions amongst recovering species, but we go further by quantifying how these interactions contributed to failed recoveries via impacts on the nesting demography of jointly recovering species. Multi-species management is paramount to realizing the ecosystem benefits of top predator recovery.

Minnesota↗
USGS2023

Support for management actions to protect night sky quality: Insights from visitors to state and national park units in the U.S.

Light pollution is a global phenomenon where anthropogenic light sources continue to grow unabated, affecting both social and ecological systems. This is leaving parks and protected areas as some of the last vestiges of naturally dark environments for protecting views of the night sky. Yet, even parks and protected areas have outdoor lighting. Alternative lighting practices are needed to reduce or prevent light pollution from within parks. However, making parks darker may not be desirable for some visitors if they believe it will reduce navigability, safety, or restrict how they recreate (e.g., requiring the use of red-light flashlights after dark and before dawn). How visitors will respond to alternative lighting practices that park managers can implement is still unknown. We used an on-site intercept survey at nine state and national park units in Utah, U.S. , to investigate nighttime visitors' support or opposition to management actions to protect night sky quality and their interest in learning about topics related to night skies. Further, this study also segmented visitors into two groups: those ‘dependent’ on the dark sky as a resource and those whose activities did not depend on a dark sky. Defining what a ‘dark sky dependent’ visitor is, which has yet to be done in the literature, is a fundamental step to furthering night sky research and management efforts. Across nine parks and protected areas, 62% of nighttime visitors participated in dark sky dependent activities. Findings indicate broad support for management actions designed to improve night sky quality, with between 74% and 89% of all visitors supporting seven different management actions. There was stronger support from dark sky dependent visitors for some elements of alternative lighting practices, but there was still strong support for those who do not participate in dark sky dependent outdoor recreation. Additionally, between 57% and 75% of visitors were interested in learning more about topics related to night skies. This research indicates most visitors would welcome actions to preserve the quality of the rapidly dwindling naturally dark experiences offered by parks and protected areas.

Utah↗
USGS2025

Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA

Forecasting water levels in complex ecosystems like wetlands can support effective water resource management, ecological conservation, and understanding surface and groundwater hydrology. Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.

Florida↗
USGS2021

Using fecal DNA and closed-capture models to estimate feral horse population size

Accurate population estimates provide the foundation for managing feral horses ( Equus caballus ferus ) across the western United States. Certain feral horse populations are protected by the Wild and Free-Roaming Horses and Burros Act of 1971 and managed by the Bureau of Land Management (BLM) or the United States Forest Service on designated herd management areas (HMAs) or wild horse territories, respectively. Horses are managed to achieve an appropriate management level (AML), which represents the number of horses determined by BLM to contribute to a thriving natural ecological balance and avoid deterioration of the range. To achieve AML for each HMA, BLM resource managers need accurate and precise population estimates. We tested the use of non-invasive fecal samples in a genetic capture-recapture framework to estimate population size in a closed horse population at the Little Book Cliffs HMA, Colorado, USA, with a known size of 153 individuals. We collected 1,957 samples over 3 independent sampling periods in 2014 and amplified them at 8 microsatellite loci. We applied mark-recapture models to determine population size using 954 samples that amplified at all 8 loci. We subsampled and reanalyzed our dataset to simulate different data collection protocols and evaluated effects on accuracy and precision of estimates using N-mixture modeling, full likelihood closed-capture modeling, and capwire single-occasion modeling that used data from all 3 sampling periods. Our model results were accurate and precise for analyses that used data from all 3 occasions; however, capwire single-occasion modeling was not accurate when we analyzed each sampling period separately. For all subsampling analysis scenarios, reducing sample size decreased precision, whether by reducing number of field staff, field days, or geographic areas surveyed on each period. Reducing spatial coverage of the survey area did not result in accurate population estimates and only marginally lowered the number of samples that would need to be collected to maintain accuracy. Because laboratory analysis contributes the greatest expense for this method ($80 U.S./sample), reducing fecal sample size is advantageous. Our results demonstrate that non-invasive sampling combined with good survey design and careful genetic and capture-recapture analyses can provide an alternative method to estimate the number of feral horses in a closed population. This method may be especially appropriate in situations where aerial inventories are not practical or accurate because of low sighting conditions. But the higher costs associated with laboratory sample analyses may reduce the method's feasibility compared to helicopter surveys.

Colorado↗
USGS2018

Lesser prairie-chicken space use among landscapes in relation to anthropogenic structures

The Southern Great Plains has been altered by conversion of native grassland to row‐crop agriculture, which is considered the primary cause of declining lesser prairie‐chicken ( Tympanuchus pallidicinctus ) populations. However, recent analyses indicate that direct loss of grassland has slowed while lesser prairie‐chicken populations continue to decline, suggesting that remaining grasslands potentially suffer from degradation by various land uses (e.g., increased anthropogenic disturbance). Understanding the spatial ecology of lesser prairie‐chickens relative to anthropogenic structures is important for conservation planning, habitat management, and infrastructure mitigation. We investigated effects of proximity to anthropogenic structures on home range and nest placement (second‐order selection) and within home range space use (third‐order selection) of radio‐marked lesser prairie‐chickens ( n = 285) at 2 scales of selection using resource utilization functions and resource selection functions. We collected data from birds marked in the Mixed‐Grass Prairie and Short‐Grass Prairie ecoregions of Kansas, USA, from 15 March 2013 to 14 March 2016. Home range placement did not vary by region or season, and lesser prairie‐chickens placed home ranges farther from powerlines and roads than would be expected at random. As distance increased from 0 to 3 km away from roads and powerlines, the relative probability of home range placement increased 1.66 and 1.54 times, respectively. Distance to powerline was the single most consistent variable negatively affecting nest placement. As the distance from powerline increased from 0 to 3 km, the relative probability of nest placement increased 2.19 times. Distance to oil well did not influence placement of home ranges or nests. When pooled across regions, lesser prairie‐chickens exhibited behavioral avoidance of powerlines, roads, and oil wells within their home range. Lesser prairie‐chickens, on average, used space at greater intensities within their home range farther from wells, powerlines, and roads than available. Across breeding season phases, we found no evidence of increased behavioral avoidance of anthropogenic structures during the nesting or brooding phases compared to the lekking or post‐breeding phases. Within home range space use during the brooding phase was not related to powerlines, wells, or roads. Our results indicate that avoidance of anthropogenic structures may result in functional habitat loss and continued fragmentation of remaining grassland habitat. Reduction or elimination of anthropogenic development in quality lesser prairie‐chicken habitat and concentrating new development in already altered areas that are avoided by lesser prairie‐chickens and no longer considered available habitat may reduce continued habitat degradation throughout the species’ range and aid in population persistence.

Journal of Wildlife Management↗
USGS2016

Northern bobwhite breeding season ecology on a reclaimed surface mine

Surface coal mining and subsequent reclamation of surface mines have converted large forest areas into early successional vegetative communities in the eastern United States. This reclamation can provide a novel opportunity to conserve northern bobwhite ( Colinus virginianus ). We evaluated the influence of habitat management activities on nest survival, nest-site selection, and brood resource selection on managed and unmanaged units of a reclaimed surface mine, Peabody Wildlife Management Area (Peabody), in west-central Kentucky, USA, from 2010 to 2013. We compared resource selection, using discrete-choice analysis, and nest survival, using the nest survival model in Program MARK, between managed and unmanaged units of Peabody at 2 spatial scales: the composition and configuration of vegetation types (i.e., macrohabitat) and vegetation characteristics at nest sites and brood locations (i.e., microhabitat). On managed sites, we also investigated resource selection relative to a number of different treatments (e.g., herbicide, disking, prescribed fire). We found no evidence that nest-site selection was influenced by macrohabitat variables, but bobwhite selected nest sites in areas with greater litter depth than was available at random sites. On managed units, bobwhite were more likely to nest where herbicide was applied to reduce sericea lespedeza ( Lespedeza cuneata ) compared with areas untreated with herbicide. Daily nest survival was not influenced by habitat characteristics or by habitat management but was influenced by nest age and the interaction of nest initiation date and nest age. Daily nest survival was greater for older nests occurring early in the breeding season (0.99, SE < 0.01) but was lower for older nests occurring later in the season (0.08, SE = 0.13). Brood resource selection was not influenced by macrohabitat or microhabitat variables we measured, but broods on managed units selected areas treated with herbicide to control sericea lespedeza and were located closer to firebreaks and disked native-warm season grass stands than would be expected at random. Our results suggest the vegetation at Peabody was sufficient without manipulation to support nesting and brood-rearing northern bobwhite at a low level, but habitat management practices improved vegetation for nesting and brood-rearing resource selection. Reproductive rates (e.g., nest survival and re-nesting rates) at Peabody were lower than reported in other studies, which may be related to nutritional deficiencies caused by the abundance of sericea lespedeza. On reclaimed mine lands dominated by sericea lespedeza, we suggest continuing practices such as disking and herbicide application that are targeted at reducing sericea lespedeza to improve the vegetation for nesting and brood-rearing bobwhite.

Kentucky↗
USGS2026

When best intentions are not enough - A collaboration between scientists, policymakers, and an agricultural community

Rocky Mountain National Park is a Congressionally mandated Clean Air Act Class I Area, but years of research have documented evidence of biogeochemical and ecological change caused by atmospheric deposition of nitrogen. A coalition of government agencies—National Park Service, the Environmental Protection Agency Region 8, and the State of Colorado—developed the 2007 Nitrogen Deposition Reduction Plan to reduce wet nitrogen deposition to the park from the baseline in 2006 by 50% by 2032. Fifty-four percent of wet nitrogen deposition is ammonium, primarily sourced from industrial cattle and dairy operations east of the park. An Agriculture Subcommittee, meeting with regulatory and management agencies and scientists since 2006, has explored voluntary options to reduce ammonia emissions. Ammonia emissions are unregulated in the U.S. Despite sustained efforts, neither ammonium deposition nor total inorganic nitrogen deposition have declined at the rate determined to reach the targeted value by 2032. In fact, ammonia is increasing over the Front Range agricultural area. Wet nitrogen deposition in 2024 was 2.81 kg N ha −1 yr −1 , 0.61 kg N ha −1 yr −1 higher than targeted in the Nitrogen Deposition Reduction Plan. The collaborative approach between agricultural producers, regulatory entities, and resource managers is not working, but not for lack of effort by all parties. Cattle process nitrogen inefficiently, and while management practices can somewhat reduce the proportion of ammonia emitted from feedlots, with more than one million head of cattle east of Rocky Mountain National Park, large-scale reductions are unlikely. New programs to reduce emissions of nitrogen oxides (46% of wet nitrogen deposition) may reduce nitrogen deposition that is changing park ecosystems. Improved integration of crop and livestock agriculture and valuation of the ecosystem services and economy of Rocky Mountain National Park alongside agricultural value are topics for further discussion. Implications : Nitrogen deposition in precipitation to Rocky Mountain National Park has changed natural ecosystems. To protect its Clean Air Act Class I status a 2007 Nitrogen Deposition Reduction Plan agreed upon by state and federal agencies set a goal to reduce wet nitrogen deposition to the Park by half by 2032. Industrial livestock operations are a large source of nitrogen; an Agriculture Subcommittee explored voluntary options to reduce emissions from cattle. Despite sustained efforts nitrogen deposition has not declined. Further reductions in industry and transportation emissions will be needed reduce nitrogen deposition to Rocky Mountain National Park.

Colorado↗
USGS2013

Estimating animal resource selection from telemetry data using point process models

Analyses of animal resource selection functions (RSF) using data collected from relocations of individuals via remote telemetry devices have become commonplace. Increasing technological advances, however, have produced statistical challenges in analysing such highly autocorrelated data. Weighted distribution methods have been proposed for analysing RSFs with telemetry data. However, they can be computationally challenging due to an intractable normalizing constant and cannot be aggregated (i.e. collapsed) over time to make space-only inference. In this study, we take a conceptually different approach to modelling animal telemetry data for making RSF inference. We consider the telemetry data to be a realization of a space–time point process. Under the point process paradigm, the times of the relocations are also considered to be random rather than fixed. We show the point process models we propose are a generalization of the weighted distribution telemetry models. By generalizing the weighted model, we can access several numerical techniques for evaluating point process likelihoods that make use of common statistical software. Thus, the analysis methods can be readily implemented by animal ecologists. In addition to ease of computation, the point process models can be aggregated over time by marginalizing over the temporal component of the model. This allows a full range of models to be constructed for RSF analysis at the individual movement level up to the study area level. To demonstrate the analysis of telemetry data with the point process approach, we analysed a data set of telemetry locations from northern fur seals (Callorhinus ursinus) in the Pribilof Islands, Alaska. Both a space–time and an aggregated space-only model were fitted. At the individual level, the space–time analysis showed little selection relative to the habitat covariates. However, at the study area level, the space-only model showed strong selection relative to the covariates.

Alaska↗
USGS2018

Integrating encounter theory with decision analysis to evaluate collision risk and determine optimal protection zones for wildlife

1.Better understanding human‐wildlife interactions and their links with management can help improve the design of wildlife protection zones. One example is the problem of wildlife collisions with vehicles or human‐built structures (e.g. power lines, wind farms). In fact, collisions between marine wildlife and watercraft are among the major threats faced by several endangered species of marine mammals. Natural resource managers are therefore interested in finding cost‐effective solutions to mitigate these threats. 2.We combined abundance estimators with encounter rate theory to estimate relative lethal collision risk of the Florida manatee ( Trichechus manatus latirostris ) from watercraft. We first modeled seasonal abundance of watercraft and manatees using a Bayesian analysis of aerial survey count data. We then modeled relative lethal collision risk in space and across seasons. Finally, we applied decision analysis and Linear Integer Programming to determine the optimal design of speed zones in terms of relative risk to manatees and costs to waterway users. We used a Pareto efficient frontier approach to evaluate the performance of alternative zones, which included additional practical considerations (e.g. spatial aggregation of speed zones) in relation to the optimal zone configurations. 3.Under the various relationships for probability of death given strike speed that we considered, the current speed zones reduced the relative lethal collision risk by an average of 51.5% to 70% compared to the scenario in which all speed regulations were removed (i.e. the no‐protection scenario). We identified optimal zones and near‐optimal zones with additional management considerations that improved upon the current zones in terms of cost or relative risk. 4.Policy Implications : Our analytical framework combines encounter rate theory and decision analysis to quantify the effectiveness of speed zones protecting manatees while accounting for uncertainty. Our approach can be used to optimize the design of protection zones intended to reduce conflicts between human waterborne activity and marine mammals. This framework could be extended to address many other problems of human‐wildlife interactions, such as the optimal placement of wind farms to minimize collisions with wildlife or the optimal allocation of ranger effort to mitigate poaching threats.

Journal of Applied Ecology↗
USGS2022

Seasonal resource selection and movement ecology of free-ranging horses in the western United States

Understanding factors driving resource selection and habitat use of different species is an important component of management and conservation. Feral horses ( Equus caballus ) are free ranging across various vegetation types in the western United States, yet few studies have quantified their resource selection and seasonal use. We conducted a study to determine effects of vegetation community, distance to water, and topographic variables on seasonal resource selection in 2 feral horse populations in Great Basin sagebrush ( Artemisia spp.) ecosystems of west-central Utah, USA: Conger Herd Management Area (HMA) and Frisco HMA. We deployed global positioning system (GPS) radio-collars on 38 female horses and GPS-transmitters braided and glued into the tail hair of 14 males, collecting locations every 2 hours for 1–4 years between 2016 and 2020. We calculated home range size and core use area of social groups (harems) and bachelor males using auto-correlated kernel density estimators for each biologically defined season (breeding, fall, and winter) per study year. We examined seasonal home range size and overlap of harem groups and bachelor males and compared movement speed of bachelors and harems among seasons. We determined seasonal resource selection in a use-availability framework using resource selection functions. We hypothesized that horses would select for areas of high herbaceous vegetation, that water would be a key variable in resource selection models like other equids, and home range size in winter would be largest because horses can eat snow for hydration and could therefore roam farther from surface water. Mean annual home range size was 103.12 ± 37.38 km 2 (SD) for Conger harems and 117.47 ± 32.75 km 2 for Frisco harems. At Conger there was no difference in home range size between harem groups and bachelor males, but home range size was smaller in winter than other seasons, whereas winter home range size at Frisco was larger than other seasons. Bachelor males moved at higher speeds than harems during all seasons, and harem groups from both populations had lower movement speeds in winter. Harem groups had distinct winter ranges with little overlap on breeding season ranges. In both populations, all horses selected for herbaceous vegetation types and avoided forest relative to shrubland throughout the year. Harems at Frisco were consistently located closer to water sources, whereas selection for water sources by Conger harems varied seasonally, with winter having the lowest selection. Harem groups at Conger had an average of 10.6% of their home ranges outside the HMA boundary and Frisco harems had up to 66.8% outside, likely because of the horseshoe shape of Frisco HMA in which shrub meadows (foraging areas) comprise the horseshoe center, which is outside the HMA. Our results highlight the importance of water sources, which were a key predictor of horse movement patterns in our study. We emphasize the utility of telemetry devices to understand resource selection of feral horses at a fine scale, enabling management to be more targeted and facilitate planning.

Utah↗
USGS2021

Species mixture effects and climate influence growth, recruitment and mortality in Interior West USA Populus tremuloides-conifer communities

Tree-species mixture effects (e.g. complementarity and facilitation) have been found to increase individual-tree productivity, lessen mortality and improve recruitment in forests worldwide. By promoting more efficient and complete resource use, mixture effects may also lessen individual-tree-level water stress, thus improving drought resistance. We investigated the influence of mixture effects on tree productivity, mortality and recruitment across broad compositional and moisture gradients in high-elevation Interior West US mixed-conifer communities, where Populus tremuloides (trembling aspen) is the major contributor to functional diversity. Our goal was to provide a more complete scientific foundation for managing these drought-prone, fire-excluded systems under an uncertain climate. We used landscape-scale national forest inventory data to examine mixture effects on P. tremuloides and the major associated conifer species, Pseudotsuga menziesii , Pinus contorta , Abies lasiocarpa and Picea engelmannii . Using generalized linear mixed modelling, we isolated the influences of P. tremuloides relative density and climate on tree-level (stems ≥ 12.7 cm DBH) growth, mortality and stand-level recruitment (presence/absence of new trees). Cold-season precipitation (PPT) and warm-season vapour pressure deficit (VPD) served to represent soil moisture supply and demand, respectively. Populus tremuloides growth declined as interspecific density increased. In contrast, Pinus contorta and A. lasiocarpa growth increased with P. tremuloides density. For all species except A. lasiocarpa and P. menziesii, growth increased under higher PPT and VPD. Populus tremuloides mortality increased under high VPD but not with interspecific relative density. We found limited evidence that A. lasiocarpa mortality decreased as P. tremuloides density increased. Populus tremuloides recruitment declined steeply above 25% interspecific relative density. We found a decline in conifer recruitment odds as P. tremuloides density increased, ranging from strong in P. contorta to insubstantial in P. engelmannii . Synthesis . Our findings have implications for sustaining mixed-conifer communities impacted by climate change and historical fire exclusion. Mixtures of P. tremuloides and conifers may improve conifer growth while adversely impacting P. tremuloides growth relative to pure stands. Higher conifer productivity combined with lower P. tremuloides recruitment at high conifer relative density may accelerate succession.

Journal of Ecology↗
USGS2015

Tidal marsh susceptibility to sea-level rise: importance of local-scale models

Increasing concern over sea-level rise impacts to coastal tidal marsh ecosystems has led to modeling efforts to anticipate outcomes for resource management decision making. Few studies on the Pacific coast of North America have modeled sea-level rise marsh susceptibility at a scale relevant to local wildlife populations and plant communities. Here, we use a novel approach in developing an empirical sea-level rise ecological response model that can be applied to key management questions. Calculated elevation change over 13 y for a 324-ha portion of San Pablo Bay National Wildlife Refuge, California, USA, was used to represent local accretion and subsidence processes. Next, we coupled detailed plant community and elevation surveys with measured rates of inundation frequency to model marsh state changes to 2100. By grouping plant communities into low, mid, and high marsh habitats, we were able to assess wildlife species vulnerability and to better understand outcomes for habitat resiliency. Starting study-site conditions were comprised of 78% (253-ha) high marsh, 7% (30-ha) mid marsh, and 4% (18-ha) low marsh habitats, dominated by pickleweed Sarcocornia pacifica and cordgrass Spartina spp. Only under the low sea-level rise scenario (44 cm by 2100) did our models show persistence of some marsh habitats to 2100, with the area dominated by low marsh habitats. Under mid (93 cm by 2100) and high sea-level rise scenarios (166 cm by 2100), most mid and high marsh habitat was lost by 2070, with only 15% (65 ha) remaining, and a complete loss of these habitats by 2080. Low marsh habitat increased temporarily under all three sea-level rise scenarios, with the peak (286 ha) in 2070, adding habitat for the endemic endangered California Ridgway&rsquo;s rail Rallus obsoletus obsoletus . Under mid and high sea-level rise scenarios, an almost complete conversion to mudflat occurred, with most of the area below mean sea level. Our modeling assumed no marsh migration upslope due to human levee and infrastructure preventing these types of processes. Other modeling efforts done for this area have projected marsh persistence to 2100, but our modeling effort with site-specific datasets allowed us to model at a finer resolution with much higher local confidence, resulting in different results for management. Our results suggest that projected sea-level rise will have significant impacts on marsh plant communities and obligate wildlife, including those already under federal and state protection. Comprehensive modeling as done here improves the potential to implement adaptive management strategies and prevent marsh habitat and wildlife loss in the future.

California↗
USGS2018

A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform

Mapping high resolution (30-m or better) cropland extent over very large areas such as continents or large countries or regions accurately, precisely, repeatedly, and rapidly is of great importance for addressing the global food and water security challenges. Such cropland extent products capture individual farm fields, small or large, and are crucial for developing accurate higher-level cropland products such as cropping intensities, crop types, crop watering methods (irrigated or rainfed), crop productivity, and crop water productivity. It also brings many challenges that include handling massively large data volumes, computing power, and collecting resource intensive reference training and validation data over complex geographic and political boundaries. Thereby, this study developed a precise and accurate Landsat 30-m derived cropland extent product for two very important, distinct, diverse, and large countries: Australia and China. The study used of eight bands (blue, green, red, NIR, SWIR1, SWIR2, TIR1, and NDVI) of Landsat-8 every 16-day Operational Land Imager (OLI) data for the years 2013–2015. The classification was performed by using a pixel-based supervised random forest (RF) machine learning algorithm (MLA) executed on the Google Earth Engine (GEE) cloud computing platform. Each band was time-composited over 4–6 time-periods over a year using median value for various agro-ecological zones (AEZs) of Australia and China. This resulted in a 32–48-layer mega-file data-cube (MFDC) for each of the AEZs. Reference training and validation data were gathered from: (a) field visits, (b) sub-meter to 5-m very high spatial resolution imagery (VHRI) data, and (c) ancillary sources such as from the National agriculture bureaus. Croplands versus non-croplands knowledge base for training the RF algorithm were derived from MFDC using 958 reference-training samples for Australia and 2130 reference-training samples for China. The resulting 30-m cropland extent product was assessed for accuracies using independent validation samples: 900 for Australia and 1972 for China. The 30-m cropland extent product of Australia showed an overall accuracy of 97.6% with a producer’s accuracy of 98.8% (errors of omissions = 1.2%), and user’s accuracy of 79% (errors of commissions = 21%) for the cropland class. For China, overall accuracies were 94% with a producer’s accuracy of 80% (errors of omissions = 20%), and user’s accuracy of 84.2% (errors of commissions = 15.8%) for cropland class. Total cropland areas of Australia were estimated as 35.1 million hectares and 165.2 million hectares for China. These estimates were higher by 8.6% for Australia and 3.9% for China when compared with the traditionally derived national statistics. The cropland extent product further demonstrated the ability to estimate sub-national cropland areas accurately by providing an R 2 value of 0.85 when compared with province-wise cropland areas of China. The study provides a paradigm-shift on how cropland maps are produced using multi-date remote sensing. These products can be browsed at www.croplands.org and made available for download at NASA’s Land Processes Distributed Active Archive Center (LP DAAC) https://www.lpdaac.usgs.gov/node/1282 .

ISPRS Journal of Photogrammetry and Remote Sensing↗
USGS2021

Conservation implications of spatiotemporal variation in the terrestrial ecology of Western spadefoots

Conservation of species reliant on ephemeral resources can be especially challenging in the face of a changing climate. Western spadefoots ( Spea hammondii ) are small burrowing anurans that breed in ephemeral pools, but adults spend the majority of their lives underground in adjacent terrestrial habitat. Western spadefoots are of conservation concern throughout their range because of habitat loss, but little is known about the activity patterns and ecology of their terrestrial life stage. We conducted a radio-telemetry study of adult western spadefoots at 2 sites in southern California, USA, from December 2018 to November 2019 to characterize their survival, behavior, and movements from breeding through aestivation to refine conservation and management for the species. Western spadefoot survival varied seasonally, with risk of mortality higher in the active season than during aestivation. The probability of movement between successive observations was higher during the winter and spring and when atmospheric moisture was high and soil water content at 10-cm depth was low. The amount of rain between observations had the strongest effect on the probability of movement between observations; for every 20 mm of rainfall between observations, western spadefoots were 2.4 times more likely to move. When movements occurred, movement rates were highest when both relative humidity and soil water content at 10-cm depth were high. The conditions under which western spadefoots were likely active on the surface, likely to have moved, and moved at the highest rates are conditions that reduce the risk of desiccation of surface-active spadefoots. Western spadefoot home range areas varied between study sites and were mostly <1 ha, although 1 individual's home range area was >6 ha. Western spadefoots rapidly dispersed from the breeding pools, and asymptotic distances from the breeding pool were generally reached by June. The asymptotic distance from the breeding pool varied between sites, with the 95th percentile of the posterior predictive distribution reaching 486 m at 1 site and 187 m at the other. Western spadefoots did not select most habitat components disproportionately to their availability, but at Crystal Cove State Park, they avoided most evaluated vegetation types (graminoids, forbs, and shrubs). Spatial variation was evident in most evaluated western spadefoot behaviors; context-dependent behavior suggests that site-specific management is likely necessary for western spadefoots. Furthermore, comparison with an earlier study of western spadefoots at Crystal Cove State Park indicated substantial temporal variation in western spadefoot behavior. Therefore, basing management decisions on short-term studies might fail to meet conservation objectives. Better understanding the influences of spatial context and climatic variation on western spadefoot behavior will improve conservation efforts for this species.

California↗
USGS2019

Phenological mismatch between season advancement and migration timing alters Arctic plant traits

1. Climate change is creating phenological mismatches between herbivores and their plant resources throughout the Arctic. While advancing growing seasons and changing arrival times of migratory herbivores has been shown to have consequences for herbivores and forage quality, developing mismatches are also likely to influence other traits of plants, such as above- and belowground biomass and the type of reproduction, that are often not investigated. 2. In coastal western Alaska, we conducted a three-year factorial experiment that simulated scenarios of phenological mismatch by manipulating the start of the growing season (ca. 3-weeks early and ambient) and grazing times (3-weeks early, typical, 3-weeks late, or no-grazing) of Pacific black brant (Branta bernicla nigricans), to examine how the timing of these events influence a primary goose forage species, Carex subspathacea. 3. After three years, an advanced growing season compared to a typical growing season increased stem heights, standing dead biomass, and the number of inflorescences. Early season grazing compared to typical season grazing reduced above- and belowground biomass, stem height, and the number of tillers; while late season grazing increased the number of inflorescences and standing dead biomass by year 3. Therefore, an advanced growing season and late grazing had comparable directional effects on most plant traits, but a 3-week delay in grazing had an impact on vegetation traits 3 to 5 times greater than a similar shift in advancement of spring conditions. In addition, changes in response to treatments for some variables, such as the number of inflorescences, were not measurable until the second year of the experiment, while other variables, such as root productivity and number of tillers, changed the direction of their responses to treatments over time. 4. Synthesis: Factors influencing the timing of migration have a larger influence on an important forage species than earlier springs in the breeding and rearing habitats of Pacific black brant. The phenological mismatch prediction for this site of earlier springs and later goose arrival will likely increase above- and belowground biomass and sexual reproduction of C. subspathacea. Implications for mismatch may be difficult to predict because some variables required successive years of mismatch to respond.

Journal of Ecology↗
USGS2022

Upper Rio Grande Basin water-resource status and trends: Focus area study review and synthesis

The Upper Rio Grande Basin (URGB) is a critical international water resource under pressure from a myriad of climatic, ecological, infrastructural, water-use, and legal constraints. The objective of this study is to provide a comprehensive assessment of the spatial distribution and temporal trends of selected water-budget components (snow processes, evapotranspiration (ET), streamflow processes, and groundwater storage) using integrated analyses, such as watershed modeling and water availability and use data in the URGB over the past three decades. A spatially distributed snow evolution modeling system simulated snowpack processes over 34 years (1984–2017). It highlighted snow water equivalent declines from -35 to -77 mm/decade with widespread variability across elevation zones and land cover types. Gridded actual ET data from the SSEBop model were developed and tested for the URGB and demonstrated that all land-cover types had significant decreasing trends (1986-2015) ranging from -14 to -80 mm/decade. Conductivity-mass-balance (CMB) hydrograph separation results found that baseflow forms a large component of total streamflow, ranging from 29 to 69% (49% average) of total streamflow at 17 URGB sites upstream of Albuquerque, NM. Three of 4 graphical hydrograph separation methods in the U.S. Geological Survey Groundwater Toolbox were found to be inappropriate for estimating baseflow in the URGB; the most promising method, baseflow index (BFI) Standard, was optimized using CMB data and tested at three URGB sites, with resulting overestimation of 0 to 47%. Simulated changes in groundwater storage were extracted from historical and recent groundwater-flow models of select alluvial basins (San Luis, Española, Middle Rio Grande, and Tularosa-Hueco). In general, decreases in groundwater storage were observed from 1903 to 2013 except for the San Luis alluvial basin (Colorado), where periods of recovery are observed. The PRMS hydrologic model was successfully calibrated for 9 near-native subbasins (Nash-Sutcliffe efficiency 0.47 to 0.85) and parameters translated to the remaining subbasins; compared to simulated near-native flows (with minimal influence of reservoirs or diversions), observed Rio Grande streamgage flows demonstrated reductions of 40% or more for New Mexico and Texas areas of the basin. Significant decreasing trends (1980-2015) in precipitation, snowmelt rate, streamflow, and baseflow were observed at many of the 12 streamgage basins studied, which suggests that the decreasing trends for actual ET may be related to overall decreasing water availability in the basin, with negative implications for agricultural production and groundwater abstraction. Water security concerns arise from our findings of higher fraction precipitation as rain, slower snowmelt rates leading to decreasing streamflow production, and an increasing fraction of baseflow, all of which will affect the timing and magnitude of water available for human needs in the basin.

Upper Rio Grande Basin↗