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USGS2025

Detection of deer at remote camera sites in relation to snow conditions

In the rain-snow transition zone of the Pacific Northwest, climate change is expected to alter the incidence of rain-on-snow and freeze-thaw events, which will change snow density and hardness dynamics. In winter, the ability of economically and ecologically important wildlife species, such as deer ( Odocoileus spp.), to efficiently move through the landscape and access forage is mediated by snow conditions. Therefore, snow properties such as density and hardness can directly affect how energetically costly it is for these animals to survive. However, little is known about whether and how ungulates use habitats based on snow density and hardness. We deployed a stratified network of remote camera stations in complex forested terrain in Latah County, Idaho, USA, to remotely measure snow depth and detect deer. We also collected snow density and hardness measurements throughout the winter. We used these data to determine the degree to which the probability of deer presence at cameras could be explained by snow conditions and air temperature. Snow depth and density had negative relationships with the probability of deer presence, while ram resistance (a proxy for snow hardness) had a marginal positive effect. We were able to estimate snow conditions important to deer in winter 2020–2021 primarily using data obtained from cameras. This provides an important proof-of-concept that can be applied at different sites and climate conditions to gain a deeper understanding of how deer are affected by snowpack properties. These methods can be used by managers to determine how ungulates are affected by snow depth, density, and hardness collectively and subsequently inform ungulate management in a changing climate.

Idaho↗

USGS2024

Applying mark-resight, count, and telemetry data to estimate effective sampling area and fish density with stationary underwater cameras

Accurate estimates of abundance and density for geographically open populations must account for the effective sampling area (ESA) of sampling gears. We describe a Marked N-Mixture model to estimate ESA and density (number of individuals/unit area) from repeated counts of unmarked and marked individuals, integrating mark-resight, camera counts, and telemetry data of red snapper ( Lutjanus campechanus ) at a 1.6 km 2 reef off North Carolina, USA. Cameras recorded observations of unmarked and marked individuals, whereas telemetry data indicated the number of tagged fish present on the reef. We estimated density (95 individuals/km 2 , 95%CI: 58–149), ESA (which was lower when current direction was towards the camera), detection probability (0.06, 95%CI: 0.03–0.09), and covariate relationships. Simulation studies under different scenarios of data quality and space use identified positive bias in density estimates from N-mixture models due to fish movement. In contrast, the Marked N-Mixture model returned unbiased estimates of density, ESA, and detection parameters, and appears to be a more robust method for modeling density given the data available for this analysis. This approach can be applied to other populations where count and telemetry data overlap in space and time.

North Carolina↗

USGS2026

Biocrust and seed placement influence emergence rates of perennial grass Elymus elymoides across five North American deserts

1. Dryland vascular plant emergence is often limited by water availability especially with projected climate and precipitation changes. Biological soil crusts (biocrusts) can promote water retention and nutrient availability that benefit germination, and emergence yet can also act as a surface barrier preventing critical seed soil contact and hindering emergence. Alongside these factors, dryland fire frequency has increased with the inclusion of invasive species and vegetation structural changes. With enhanced continuous fine fuel distribution there is a high potential to disrupt biocrust-plant interactions and influence associated management actions. 2. This study explores the dynamic relationship between biocrusts and fire-related heating effects on seedling emergence across five North American deserts: the Chihuahuan Desert, Colorado Plateau, Great Basin, Mojave Desert and Sonoran Desert. We conducted a greenhouse-based seedling emergence experiment using Elymus elymoides (bottlebrush squirreltail), a common perennial grass, with biocrust and bare soil mesocosms in which half were heated to mimic the effects of wildfire temperature. 3. The variables that had the greatest influence on germination rate and germination timing were the presence of biocrust and seed placement (on top of vs within the biocrust/soil matrix). Emergence rate was greatest atop bare soil followed by seeds inserted into biocrust. Emergence timing was faster with biocrust present, but only when seeds were inserted into it. Desert origin of biocrust and soil collection also influenced germination where the probability of any one seed emerging was highest in the Chihuahuan and Mojave desert sites relative to the Sonoran desert site which showed the lowest probability. Heating had mixed effects whereby it increased the likelihood of emergence but did not affect the overall rate or timing. 4. Synthesis and applications . This study underscores the importance of healthy and impaired biocrusts in dryland systems and suggests ways in which the combination of biocrust and seed placement can influence plant establishment, in addition to providing insight into seeding strategies for managers and restoration practitioners working in dryland sites.

Arizona, California, Colorado, Nevada, New Mexico↗

USGS2003

Population dynamics of hispid cotton rats (Sigmodon hispidus) across a nitrogen-amended landscape

We conducted a mark-recapture experiment to examine the population dynamics of hispid cotton rats (Sigmodon hispidus) in response to low-level nitrogen amendments (16.4 kg nitrogen/ha per year) and exclosure fencing in an old-field grassland. The experimental design consisted of sixteen 0.16-ha plots with 4 replicates of each treatment combination. We predicted that densities, reproductive success, movement probabilities, and survival rates of cotton rats would be greater on nitrogen-amended plots because of greater aboveground biomass and canopy cover. Population densities of cotton rats tended to be highest on fenced nitrogen plots, but densities on unfenced nitrogen plots were similar to those on control and fenced plots. We observed no distinct patterns in survival rates, reproductive success, or movement probabilities with regard to nitrogen treatments. However, survival rates and reproductive success tended to be higher for cotton rats on fenced plots than for those on unfenced plots and this was likely attributable to decreased predation on fenced plots. As low-level nitrogen amendments continue to be applied, we predict that survival, reproduction, and population-growth rates of cotton rats on control plots, especially fenced plots with no nitrogen amendment, will eventually exceed those on nitrogen-amended plots as a result of higher plant-species diversity, greater food availability, and better quality cover.

Canadian Journal of Zoology↗

USGS1977

Relation of surflcial erosion on hillslopes to profile geometry

Differences in erosion rates in relation to the geometry of hillslope profiles were hypothesized by R. E. Horton in 1945. Experimental testing of this hypothesis is described for natural hillslopes in western Colorado using a rainfall simulator to apply five "storms" each having an intensity of 1.85 inches per hour (47 millimeters per hour). Erosion from straight hillslope segments was about twice the amount from convex and concave segments along nine hillslope transects. Standard deviations of erosion measurements for each segment show that the greatest variation occurs in concave slope segments. This is probably because the concave segment is the only place on the profile where deposition occurs. Analysis of variance indicates that the amount of erosion is significant at the 1-percent level of confidence between convex and straight slope segments and at the 5-percent level of confidence between straight and convex slope segments.

Colorado↗

USGS2006

Survey design for detecting rare freshwater mussels

A common objective when surveying freshwater mussels is to detect the presence of rare populations. In certain situations, such as when endangered or threatened species are potentially in the area of a proposed impact, the survey should be designed to ensure a high probability of detecting species presence. Linking survey design to probability of detecting species presence has been done for quantitative surveys, but commonly applied designs that are based on timed searches have not made that connection. I propose a semiquantitative survey design that links search area and search efficiency to probability of detecting species presence. The survey can be designed to protect against failing to detect populations above a threshold abundance (or density). I illustrate the design for surveys to detect clubshell (Pluerobema clava) and northern riffleshell (Epioblasma torulosa rangiana) in the Allegheny River. Monte Carlo simulation indicated that the proposed survey design performs well under a range of spatial distributions and low densities (<0.05 m2) where search area is sufficient to ensure that the probability of detecting species presence is predicted to be ???0.85. ?? 2006 by The North American Benthological Society.

Journal of the North American Benthological Societ↗

USGS2018

Broad‐scale occurrence of a subsidized avian predator: reducing impacts of ravens on sage‐grouse and other sensitive prey

Expanding human enterprise across remote environments impacts numerous wildlife species. Anthropogenic resources provide subsidies for generalist predators that can lead to cascading effects on prey species at lower trophic levels. A fundamental challenge for applied ecologists is to disentangle natural and anthropogenic influences on species occurrence, and subsequently develop spatially explicit models to help inform management and conservation decisions. Using Bayesian hierarchical occupancy models, we mapped the broad‐scale occurrence of common ravens Corvus corax as a function of natural and anthropogenic landscape covariates using >15,000 point count surveys performed during 2007–2016 within the Great Basin region, USA. Raven abundance and distribution is substantially increasing across the American west due to unintended anthropogenic resource subsidies. Importantly, ravens prey on eggs and chicks of numerous species including greater sage‐grouse Centrocercus urophasianus , an indicator species whose decline is at the centre of national conservation strategies and land use policies.Anthropogenic factors that contributed to greater raven occurrence were: increased road density, presence of transmission lines, agricultural activity, and presence of roadside rest areas. Natural landscape characteristics included lower elevations with greener vegetation (NDVI), greater stream and habitat edge densities, and lower percentages of big sagebrush A. tridentata spp . Interactions between anthropogenic sources of nesting substrate and food subsidies suggested that raven occurrence increased multiplicatively when these resource subsidies co‐occurred. Overall, the average probability of raven occurrence estimated within sagebrush ecosystems of the study area was ~0.83. Synthesis and applications . We demonstrate how anthropogenic factors can be disentangled from natural effects when making spatially‐explicit predictions of subsidized predators occurring across expansive landscapes. This approach can guide management decisions where subsidized predators overlap sensitive prey habitats. For example, we identify areas where elevated raven occurrence coincides with breeding sage‐grouse concentration areas and appears to be largely driven by anthropogenic factors. Management applications could focus on reducing raven access to anthropogenic subsidies in these areas, while prioritizing habitat improvements for sage‐grouse elsewhere. Our approach is applicable to other species where widespread survey data are available.

Journal of Applied Ecology↗

USGS2014

Sampling characteristics and calibration of snorkel counts to estimate stream fish populations

Snorkeling is a versatile technique for estimating lotic fish population characteristics; however, few investigators have evaluated its accuracy at population or assemblage levels. We evaluated the accuracy of snorkeling using prepositioned areal electrofishing (PAE) for estimating fish populations in a medium-sized Appalachian Mountain river during fall 2008 and summer 2009. Strip-transect snorkel counts were calibrated with PAE counts in identical locations among macrohabitats, fish species or taxa, and seasons. Mean snorkeling efficiency (i.e., the proportion of individuals counted from the true population) among all taxa and seasons was 14.7% (SE, 2.5%), and the highest efficiencies were for River Chub Nocomis micropogon at 21.1% (SE, 5.9%), Central Stoneroller Campostoma anomalum at 20.3% (SE, 9.6%), and darters (Percidae) at 17.1% (SE, 3.7%), whereas efficiencies were lower for shiners ( Notropis spp., Cyprinella spp., Luxilus spp.) at 8.2% (SE, 2.2%) and suckers (Catostomidae) at 6.6% (SE, 3.2%). Macrohabitat type, fish taxon, or sampling season did not significantly explain variance in snorkeling efficiency. Mean snorkeling detection probability (i.e., probability of detecting at least one individual of a taxon) among fish taxa and seasons was 58.4% (SE, 6.1%). We applied the efficiencies from our calibration study to adjust snorkel counts from an intensive snorkeling survey conducted in a nearby reach. Total fish density estimates from strip-transect counts adjusted for snorkeling efficiency were 7,288 fish/ha (SE, 1,564) during summer and 15,805 fish/ha (SE, 4,947) during fall. Precision of fish density estimates is influenced by variation in snorkeling efficiency and sample size and may be increased with additional sampling effort. These results demonstrate the sampling properties and utility of snorkeling to characterize lotic fish assemblages with acceptable efficiency and detection probability, less effort, and no mortality, compared with traditional sampling methods.

North American Journal of Fisheries Management↗

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↗

USGS2021

Adaptive monitoring in action: Reconsidering design-based estimators reveals underestimation of whitebark pine disease prevalence in the Greater Yellowstone Ecosystem

Identifying and understanding status and trends in ecological indicators motivates continual monitoring over decades. Many programs rely on probability surveys and their companion design-based estimators for status assessments (e.g. Horvitz–Thompson). Design-based estimators do not easily extend to trend estimation nor situations with observation errors. Field-based monitoring efforts inevitably have turnover of field crew members which may affect consistency and accuracy of data collection over time. Additionally, design-based estimators ignore the complexities of spatial and temporal heterogeneity in an ecological indicator and how this variability may be linked to environmental or biological dynamics. We propose monitoring programs should re-evaluate their prescribed statistical methods, consider model-based approaches and adapt their sampling designs as needed to improve inferences. The Greater Yellowstone Ecosystem, home to two of the most iconic U.S. National Parks, has experienced significant declines in whitebark pine Pinus albicaulis communities due to forest pathogens, insect outbreaks, wildland fires and drought. Whitebark pine is a keystone species found in mountainous environments throughout the Western U.S. and Canada. We assessed the design-based ratio estimator originally recommended for estimating prevalence of white pine blister rust Cronartium ribicola . We compared the design-based estimator to a model-based approach that accounts for the sampling design, imperfect detection and allows for infection probabilities to vary over space and time. Ignoring observation errors led to lower estimated prevalence of white pine blister rust in the general population. Using model-based approaches, we found that the probability of infection has increased since 2004. However, overall prevalence likely has not changed because of the mountain pine beetle Dendroctonus ponderosae -induced shift towards smaller diameter trees that have a lower probability of infection compared to their larger cohorts. Synthesis and Applications . Using a design-based approach to detect change in ecological indicators falls short because of the inability to account for observation errors or to explore environmental or biological factors explaining temporal dynamics. Inherently understanding the mechanisms leading to changes in an ecological indicator over time informs potential management actions. Our assessment underscores the need for continued evaluation and updating of a monitoring program's sampling design and analytical procedures to maintain relevancy.

Wyoming↗

USGS2011

Recent changes in burbot growth in Lake Erie

Recruitment of burbot Lota lota in eastern Lake Erie, estimated by catches of age-4 burbot, was high during 1997–2001 and then abruptly declined to low levels during 2002–2007. The invasive round goby Neogobius melanostomus , a benthic species, was first collected in trawl assessments in eastern Lake Erie in 1999, and was first found in stomachs of burbot in 2001. By 2003, round goby became an important prey in the diet of burbot. We hypothesized that the combined effects of low recruitment and consumption of round goby would result in increased size-at-age in burbot. We reasoned that: (i) decreased competition for resources among juveniles should result in larger adults, and (ii) consumption of a benthic prey by a bottom-dwelling predator such as burbot should require less foraging in the water column, and thus less energetic expenditure. We divided our data into two temporal periods: one in which burbot belonged to strong year classes and ate few, if any round goby (i.e., year classes 1989–1997 collected during 1997–2001) and one in which burbot belonged to weak year classes and probably ate round gobies by age 4 (year classes 1998–2003 collected during 2002–2007). Mass and total lengths at ages 4–7 were generally higher during the second period. However, the rates of growth between ages 4 and 7 were not different for the two periods. The results indicate that greater growth at ages 0–4 resulted in larger size at ages 4–7 in the latter period. More information on juvenile diet and growth in burbot is needed for effective conservation of burbot stocks.

Journal of Applied Ichthyology↗

USGS2026

Evaluating alternative methods for modeling trap efficiencies of out-migrating juvenile salmonids

Objective We aimed to compare two machine learning approaches—boosted beta regression (BBR) and beta mixed model forest (BMF)—to a Bayesian mixed-effects beta regression (BME) for the prediction of rotary screw trap (RST) efficiency for out-migrating juvenile salmonids from environmental covariates. Methods We identified two machine learning approaches that shared the ability to model overdispersed probabilities. We compared the BBR and BMF machine learning models to a BME model to evaluate precision in detection probability prediction and model performance on bias in parameter estimation. We tested our three candidate models using a simulation study to understand the specific advantages and disadvantages of each when the data set was increasingly sparse and the capture probabilities were realistically small. We then applied the models to a case study of RST data from the Klamath River in California, United States. Results The BME and BMF outperformed BBR in all simulated scenarios, although the BMF displayed poor explanatory power. In the case study, the BME and BMF identified environmental covariates that predicted RST efficiency. Conclusions Using the BME as a benchmark for comparing machine learning approaches to trap efficiency modeling, our simulations and case study demonstrated that the BMF performed well and is a viable modeling approach with strong predictive power. The BME model would be the preferred modeling approach when its strong explanatory power is desired.

North American Journal of Fisheries Management↗

USGS1978

Accuracy of flood mapping

Information taken directly from published and unpublished reports was used to appraise the accuracy and the limitations of the three general flood-mapping methods: detailed, historical, and physiographic. In the appraisal, the probable nationwide average standard error of estimate for water depth and elevation in percentage of depth and in meters was determined for 100-year flood boundaries. Bias errors, users' errors, and certain time-variant errors were not. considered. The probable standard error for the detailed method is 23 percent. Based on 3.9 m as the national average 100-yr depth, the probable standard error of estimate is 0.9 m. The detailed method is applicable to a wide range of hydraulic and topographic conditions; it is the only method tested that is directly applicable to floodways analysis. The method requires detailed data and time-consuming analyses, however, and it has only limited application for determining flood elevations for sheet flow and for flow in channels having readily movable boundaries. The probable standard error for the historical method is 23 percent. Based on the 3.9-m average 100-yr depth, the standard error is 0.9 m. The historical method is applicable to a wide range of hydraulic and topographic conditions if specific data are available. The method is not applicable to floodways analysis, and it has only limited application for flow in moveable-boundary channels. The standard error for the physiographic method is 27 percent. In meters, the error is 1.1. .The physiographic method is simpler to apply than the other methods; however, it can be used only in natural channels having rigid boundaries. It is not applicable to sheet flow and to floodways analysis.

Journal of Research of the U.S. Geological Survey↗

USGS2012

Tectonic stresses in the lithosphere: constraints provided by the experimental deformation of rocks.

The strengths of rocks clearly place an upper limit on the stress that can be sustained by the upper half of the lithosphere. Laboratory data on rock rheology are generally lacking at intermediate temperatures and pressures on the important rock types expected in the lithosphere, so a definitive accounting of the strength distribution with depth in the upper lithosphere is presently unattainable. Analogies are drawn between the fragmentary strength data on silicates at intermediate temperature and the more extensive experimental data on marble and limestone, and several tentative conclusions are drawn: First, brittle processes, such as faulting and cataclasis, are expected to control rock strength at low pressures and temperatures. The strengths associated with these brittle mechanisms increase rapidly with increasing effective pressure and are relatively insensitive to temperature and strain rate. Second, the transitions between brittle and ductile processes occur at critical values of the least principal stress σ 3 . I suggest that the concept of the deformation mechanism map of Ashby (1972) be extended to brittle-ductile transitions by normalizing the applied differential stress σ by σ 3 , i.e., the transitions occur at critical values of σ/σ 3 . Third, the high temperature flow law of olivine, widely applied to problems involving flow in the asthenosphere, is inappropriate to the conditions of temperature found in the lithosphere, because different dislocation flow mechanisms dominate at low to intermediate temperatures. The fragmentary rheological data suggest the following rheological structure of the lithosphere where it is inelastically deforming: A rapid pressure-driven increase in rock strength with depth culminates with a shear strength maximum of up to 8 kbar at depths that depend on the state of stress and on the temperature distribution. A review of the mechanisms of weakening associated with water suggests that water weakening effects are probably not important in the oceanic lithosphere but are likely to be controlling in the continental crust.

Journal of Geophysical Research Solid Earth↗

USGS2016

Overwintering strategies of migratory birds: a novel approach for estimating seasonal movement patterns of residents and transients

Our understanding of movement patterns in wildlife populations has played an important role in current ecological knowledge and can inform landscape conservation decisions. Direct measures of movement can be obtained using marked individuals, but this requires tracking individuals across a landscape or multiple sites. We demonstrate how movements can be estimated indirectly using single-site, capture–mark–recapture (CMR) data with a multi-state open robust design with state uncertainty model (MSORD-SU). We treat residence and transience as two phenotypic states of overwintering migrants and use time- and state-dependent probabilities of site entry and persistence as indirect measures of movement. We applied the MSORD-SU to data on eight species of overwintering Neotropical birds collected in 14 countries between 2002 and 2011. In addition to entry and persistence probabilities, we estimated the proportions of residents at a study site and mean residence times. We identified overwintering movement patterns and residence times that contrasted with prior categorizations of territoriality. Most species showed an evidence of residents entering sites at multiple time intervals, with transients tending to enter between peak resident movement times. Persistence and the proportion of residents varied by latitude, but were not always positively correlated for a given species. Synthesis and applications . Our results suggest that migratory songbirds commonly move among habitats during the overwintering period. Substantial proportions of populations appear to be comprised of transient individuals, and residents tend to persist at specific sites for relatively short periods of time. This information on persistence and movement patterns should be explored for specific habitats to guide landscape management on the wintering grounds, such as determining which habitats are conserved or restored as part of certification programmes of tropical agroforestry crops. We suggest that research and conservation efforts on Neotropical migrant songbirds focus on identifying landscape configurations and regional habitat networks that support these diverse overwintering strategies to secure full life cycle conservation.

Journal of Applied Ecology↗

USGS2007

Concerns regarding a call for pluralism of information theory and hypothesis testing

1. Stephens et al. (2005) argue for 'pluralism' in statistical analysis, combining null hypothesis testing and information-theoretic (I-T) methods. We show that I-T methods are more informative even in single variable problems and we provide an ecological example. 2. I-T methods allow inferences to be made from multiple models simultaneously. We believe multimodel inference is the future of data analysis, which cannot be achieved with null hypothesis-testing approaches. 3. We argue for a stronger emphasis on critical thinking in science in general and less reliance on exploratory data analysis and data dredging. Deriving alternative hypotheses is central to science; deriving a single interesting science hypothesis and then comparing it to a default null hypothesis (e.g. 'no difference') is not an efficient strategy for gaining knowledge. We think this single-hypothesis strategy has been relied upon too often in the past. 4. We clarify misconceptions presented by Stephens et al. (2005) . 5. We think inference should be made about models, directly linked to scientific hypotheses, and their parameters conditioned on data, Prob(Hj| data). I-T methods provide a basis for this inference. Null hypothesis testing merely provides a probability statement about the data conditioned on a null model, Prob(data |H0). 6. Synthesis and applications . I-T methods provide a more informative approach to inference. I-T methods provide a direct measure of evidence for or against hypotheses and a means to consider simultaneously multiple hypotheses as a basis for rigorous inference. Progress in our science can be accelerated if modern methods can be used intelligently; this includes various I-T and Bayesian methods.

Journal of Applied Ecology↗

USGS2024

Simulation modeling to assess line transect distance sampling under a range of translocation scenarios

The accuracy of posttranslocation population monitoring methods is critical to assessing long-term success in translocation programs. Translocation can produce unique challenges to monitoring efforts; therefore, it is important to understand the flexibility and robustness of commonly used monitoring methods. In Florida, USA, thousands of gopher tortoises Gopherus polyphemus have been, and continue to be, translocated from development sites to permitted recipient sites. These recipient sites create a broad range of potential monitoring scenarios due to variability in soft-release strategies, habitat conditions, and population demographics. Line transect distance sampling is an effective method for monitoring natural tortoise populations, but it is currently untested for translocated populations. We therefore produced 3,024 individual-based, spatially explicit scenarios of translocated tortoise populations that differed in recipient site and tortoise population properties, based on real-world examples, literature review, and expert opinion. We virtually sampled simulated tortoise populations by using line transect distance sampling methods and built a Bayesian hierarchical model to estimate the population density for each simulation, which incorporated individual-level covariates (i.e., burrow width and burrow occupancy). Line transect distance sampling was largely appropriate for the conditions that typify gopher tortoise recipient sites, particularly when detection probability on the transect lines was greater than or equal to 0.85. Designing the layout of transects relative to the orientation of soft-release pens, to avoid possible sampling biases that lead to extreme outliers in estimates of tortoise densities, resulted in more accurate population estimates. We also suggest that use of individual-level covariates, applied using a Bayesian framework as demonstrated in our study, may improve the applicability of line transect distance sampling surveys in a variety of contexts and that simulation can be a powerful tool for assessing survey design in complex sampling situations.

Florida↗

USGS2023

Combining expert knowledge of a threatened trout distribution with sparse occupancy data for climate-related projection

Objective To evaluate the vulnerability of Bull Trout Salvelinus confluentus to potential climate changes across its range in Oregon, we compiled disparate expert knowledge of the distribution of spawning and rearing and combined these probabilistic statements as data along with documented records of breeding and rearing in a joint occupancy model. Methods The joint expert knowledge–occupancy model, which was based on discrete patches of cold water (≤13°C) suitable for spawning and rearing, permitted the association of true occupancy with climate and other explanatory variables while accounting for variation in detection probability. We then applied estimated relationships of patch occupancy with explanatory variables to projected coldwater patch configurations in the years 2040 and 2080. Result Projections of the kilometers of occupied coldwater patch in future decades suggest precipitous declines if current relationships of occupancy with environmental variables are maintained. Impacts of climate changes in future decades manifest directly through the outright loss of coldwater patches and increases in winter high flows but also indirectly by increased isolation. Conclusion Combining probabilistic statements of species distributions from knowledgeable experts with sparse occupancy data may be a robust and timely alternative when large numbers of repeated occupancy surveys are infeasible.

Oregon↗