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At least 163 records · Page 9Linked to original sources
USGS2024

Predator-specific mortality of sage-grouse nests based on predator DNA on eggshells

Greater sage-grouse (hereafter sage-grouse; Centrocercus urophasianus ) populations have declined across their range. Increased nest predation as a result of anthropogenic land use is one mechanism proposed to explain these declines. However, sage-grouse contend with a diverse suite of nest predators that vary in functional traits (e.g., search tactics or hunting mode) and abundance. Consequently, generalizing about factors influencing nest fate is challenging. Identifying the explicit predator species responsible for nest predation events is, therefore, critical to understanding causal mechanisms linking land use to patterns of sage-grouse nest success. Cattle grazing is often assumed to adversely affect sage-grouse recruitment by reducing grass height (and hence cover), thereby facilitating nest detection by predators. However, recent evidence found little support for the hypothesized effect of grazing on nest fate at the pasture scale. Rather, nest success appears to be similar on pastures grazed at varying intensities. One possible explanation for the lack of observed effect involves a localized response by one or more nest predators. The presence of cattle may cause a temporary reduction in predator density and/or use within a pasture (the cattle avoidance hypothesis). The cattle avoidance hypothesis predicts a decreased probability of at least one sage-grouse nest predator predating sage-grouse nests in pastures with livestock relative to pastures without livestock present during the nesting season. To test the cattle avoidance hypothesis, we collected predator DNA from eggshells from predated nests and used genetic methods to identify the sage-grouse nest predator(s) responsible for the predation event. We evaluated the influence of habitat and grazing on predator-specific nest predation. We evaluated the efficacy of our genetic method by deploying artificial nests with trail cameras and compared the results of our genetic method to the species captured via trail camera. Our molecular methods identified at least one nest predator captured predating artificial nests via trail camera for 33 of 35 (94%) artificial nests. We detected nest predators via our molecular analysis at 76 of 114 (67%) predated sage-grouse nests. The primary predators detected at sage-grouse nests were coyotes ( Canis latrans ) and corvids ( Corvidea ). Grazing did not influence the probability of nest predation by either coyotes or corvids. Sagebrush canopy cover was negatively associated with the probability a coyote predated a nest, distance to water was positively associated with the probability a corvid predated a nest, and average minimum temperature was negatively associated with the probability that either a coyote or a corvid predated a nest. Our study provides a framework for implementing an effective, non-invasive method for identifying sage-grouse nest predators that can be used to better understand how management actions at local and regional scales may impact an important component of sage-grouse recruitment.

Idaho↗
USGS2001

Aeolian dust in Colorado Plateau soils: Nutrient inputs and recent change in source

Aeolian dust (windblown silt and clay) is an important component in arid-land ecosystems because it may contribute to soil formation and furnish essential nutrients. Few geologic surfaces, however, have been characterized with respect to dust-accumulation history and resultant nutrient enrichment. We have developed a combination of methods to identify the presence of aeolian dust in arid regions and to evaluate the roles of this dust in ecosystem processes. Unconsolidated sandy sediment on isolated surfaces in the Canyonlands region of the Colorado Plateau differs greatly in mineralogical and chemical composition from associated bedrock, mainly aeolian sandstone. Detrital magnetite in the surficial deposits produces moderately high values of magnetic susceptibility, but magnetite is absent in nearby bedrock. A component of the surficial deposits must be aeolian to account for the abundance of magnetite, which formed originally in far-distant igneous rocks. Particle-size analysis suggests that the aeolian dust component is typically as much as 20–30%. Dust inputs have enriched the sediments in many elements, including P, Mg, Na, K, and Mo, as well as Ca, at sites where bedrock lacks calcite cement. Soil-surface biologic crusts are effective dust traps that apparently record a change in dust sources over the past several decades. Some of the recently fallen dust may result from human disturbance of land surfaces that are far from the Canyonlands, such as the Mojave Desert. Some land-use practices in the study area have the potential to deplete soil fertility by means of wind-erosion removal of aeolian silt. Many studies have addressed the presence of aeolian dust in soils and surficial deposits in deserts to provide important geologic and ecologic information bearing on landscape dynamics (1–16). From this body of work, we have improved understanding about: ( i ) current and past sources and flux of dust, hence changing conditions of dust emission; ( ii ) the genesis of desert soils; ( iii ) the influences of aeolian silt and clay on water-infiltration rates in soil; ( iv ) the evolution of desert surfaces (such as desert pavement) relevant to surface stability, as well as the distribution of surface and subsurface water; and ( v ) interrelations among aeolian dust, distribution of plants and soil crust, rain-water runoff, and productivity. Nevertheless, we lack fundamental knowledge about the accumulation history of aeolian dust on most landscapes and about how to discriminate between contributions from parent material and aeolian dust to the biotic system. Although many different methods provide clear evidence for aeolian input into soils (4, 6, 8, 9, 11, 13, 17, 18), ecosystem studies would benefit from rapid assessment of aeolian components in soils. Here we demonstrate that magnetic methods, which characterize the type and distribution of iron oxide minerals, can be applied to detect the presence of aeolian dust in young surficial sediments and soils over large arid-land areas. The magnetic results, combined with geochemical and textural analyses, form a basis for understanding the influence of fine-grained aeolian inputs on soil fertility of the central Colorado Plateau, Utah.

Utah↗
USGS2024

Treed Gaussian processes for animal movement modeling

Wildlife telemetry data may be used to answer a diverse range of questions relevant to wildlife ecology and management. One challenge to modeling telemetry data is that animal movement often varies greatly in pattern over time, and current continuous-time modeling approaches to handle such nonstationarity require bespoke and often complex models that may pose barriers to practitioner implementation. We demonstrate a novel application of treed Gaussian process (TGP) modeling, a Bayesian machine learning approach that automatically captures the nonstationarity and abrupt transitions present in animal movement. The machine learning formulation of TGPs enables modeling to be nearly automated, while their Bayesian formulation allows for the derivation of movement descriptors with associated uncertainty measures. We demonstrate the use of an existing R package to implement TGPs using the familiar Markov chain Monte Carlo algorithm. We then use estimated movement trajectories to derive movement descriptors that can be compared across individuals and populations. We applied the TGP model to a case study of lesser prairie-chickens ( Tympanuchus pallidicinctus ) to demonstrate the benefits of TGP modeling and compared distance traveled and residence times across lesser prairie-chicken individuals and populations. For broad usability, we outline all steps necessary for practitioners to specify relevant movement descriptors (e.g., turn angles, speed, contact points) and apply TGP modeling and trajectory comparison to their own telemetry datasets. Combining the predictive power of machine learning and the statistical inference of Bayesian methods to model movement trajectories allows for the estimation of statistically comparable movement descriptors from telemetry studies. Our use of an accessible R package allows practitioners to model trajectories and estimate movement descriptors, facilitating the use of telemetry data to answer applied management questions.

Ecology and Evolution↗
USGS2018

Dynamic occupancy modeling of temperate marine fish in area-based closures

Species distribution models (SDMs) are commonly used to model the spatial structure of species in the marine environment, however, most fail to account for detectability of the target species. This can result in underestimates of occupancy, where nondetection is conflated with absence. The site occupancy model (SOM) overcomes this failure by treating occupancy as a latent variable of the model and incorporates a detection submodel to account for variability in detection rates. These have rarely been applied in the context of marine fish and never for the multiseason dynamic occupancy model (DOM). In this study, a DOM is developed for a designated species of concern, cusk ( Brosme brosme ), over a four-season period. Making novel use of a high-resolution 3-dimensional hydrodynamic model, detectability of cusk is considered as a function of current speed and algae cover. Algal cover on the seabed is measured from video surveys to divide the study area into two distinct regions: those with canopy forming species of algae and those without (henceforth bottom types). Modeled estimates of the proportion of sites occupied in each season are 0.88, 0.45, 0.74, and 0.83. These are significantly greater than the proportion of occupied sites measured from underwater video observations which are 0.57, 0.28, 0.43, and 0.57. Individual fish are detected more frequently with increasing current speed in areas lacking canopy and less frequently with increasing current speed in areas with canopy. The results indicate that, where possible, SDM studies for all marine species should take account of detectability to avoid underestimating the proportion of sites occupied at a given study area. Sampling closed areas or areas of conservation often requires the use of nonphysical, low impact sampling methods like camera surveys. These methods inherently result in detection probabilities less than one, an issue compounded by time-varying features of the environment that are rarely accounted for marine studies. This work highlights the use of modeled hydrodynamics as a tool to correct some of this imbalance.

Gulf of Maine↗
USGS2018

An analytical framework for estimating aquatic species density from environmental DNA

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross-validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.

Ecology and Evolution↗
USGS2022

Errors in aerial survey count data: Identifying pitfalls and solutions

Accurate estimates of animal abundance are essential for guiding effective management, and poor survey data can produce misleading inferences. Aerial surveys are an efficient survey platform, capable of collecting wildlife data across large spatial extents in short timeframes. However, these surveys can yield unreliable data if not carefully executed. Despite a long history of aerial survey use in ecological research, problems common to aerial surveys have not yet been adequately resolved. Through an extensive review of the aerial survey literature over the last 50 years, we evaluated how common problems encountered in the data (including nondetection, counting error, and species misidentification) can manifest, the potential difficulties conferred, and the history of how these challenges have been addressed. Additionally, we used a double-observer case study focused on waterbird data collected via aerial surveys and an online group (flock) counting quiz to explore the potential extent of each challenge and possible resolutions. We found that nearly three quarters of the aerial survey methodology literature focused on accounting for nondetection errors, while issues of counting error and misidentification were less commonly addressed. Through our case study, we demonstrated how these challenges can prove problematic by detailing the extent and magnitude of potential errors. Using our online quiz, we showed that aerial observers typically undercount group size and that the magnitude of counting errors increases with group size. Our results illustrate how each issue can act to bias inferences, highlighting the importance of considering individual methods for mitigating potential problems separately during survey design and analysis. We synthesized the information gained from our analyses to evaluate strategies for overcoming the challenges of using aerial survey data to estimate wildlife abundance, such as digital data collection methods, pooling species records by family, and ordinal modeling using binned data. Recognizing conditions that can lead to data collection errors and having reasonable solutions for addressing errors can allow researchers to allocate resources effectively to mitigate the most significant challenges for obtaining reliable aerial survey data.

Alabama, Florida, Louisiana, Mississippi, Texas↗
USGS2015

Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation

Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low-quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision-making framework will result in better-informed, more robust decisions.

Florida↗
USGS2020

Calibrating environmental DNA metabarcoding to conventional surveys for measuring fish species richness

The ability to properly identify species present in a landscape is foundational to ecology and essential for natural resource management and conservation. However, many species are often unaccounted for due to ineffective direct capture and visual surveys, especially in aquatic environments. Environmental DNA metabarcoding is an approach that overcomes low detection probabilities and should consequently enhance estimates of biodiversity and its proxy, species richness. Here, we synthesize 37 studies in natural aquatic systems to compare species richness estimates for bony fish between eDNA metabarcoding and conventional methods, such as nets, visual census, and electrofishing. In freshwater systems with fewer than 100 species, we found eDNA metabarcoding detected more species than conventional methods. Using multiple genetic markers further increased species richness estimates with eDNA metabarcoding. For more diverse freshwater systems and across marine systems, eDNA metabarcoding reported similar values of species richness to conventional methods; however, more studies are needed in these environments to better evaluate relative performance. In systems with greater biodiversity, eDNA metabarcoding will require more populated reference databases, increased sampling effort, and multi-marker assays to ensure robust species richness estimates to further validate the approach. eDNA metabarcoding is reliable and provides a path for broader biodiversity assessments that can outperform conventional methods for estimating species richness.

Frontiers in Ecology and Evolution↗
USGS2019

Genomic pedigree reconstruction identifies predictors of mating and reproductive success in an invasive vertebrate

The persistence of an invasive species is influenced by its reproductive ecology, and a successful control program must operate on this premise. However, the reproductive ecology of invasive species may be enigmatic due to factors that also limit their management, such as cryptic coloration and behavior. We explored the mating and reproductive ecology of the invasive Brown Treesnake (BTS : Boiga irregularis ) by reconstructing a multigenerational genomic pedigree based on 654 single nucleotide polymorphisms for a geographically closed population established in 2004 on Guam ( N = 426). The pedigree allowed annual estimates of individual mating and reproductive success to be inferred for snakes in the study population over a 14‐year period. We then employed generalized linear mixed models to gauge how well phenotypic and genomic data could predict sex‐specific annual mating and reproductive success. Average snout–vent length (SVL), average body condition index (BCI), and trappability were significantly related to annual mating success for males, with average SVL also related to annual mating success for females. Male and female annual reproductive success was positively affected by SVL, BCI, and trappability. Surprisingly, the degree to which individuals were inbred had no effect on annual mating or reproductive success. When juxtaposed with current control methods, these results indicate that baited traps, a common interdiction tool, may target fecund BTS in some regards but not others. Our study emphasizes the importance of reproductive ecology as a focus for improving BTS control and promotes genomic pedigree reconstruction for such an endeavor in this invasive species and others.

Ecology and Evolution↗
USGS2023

Hidden Markov movement models reveal diverse seasonal movement patterns in two North American ungulates

Animal movement is the mechanism connecting landscapes to fitness, and understanding variation in seasonal animal movements has benefited from the analysis and categorization of animal displacement. However, seasonal movement patterns can defy classification when movements are highly variable. Hidden Markov movement models (HMMs) are a class of latent-state models well-suited to modeling movement data. Here, we used HMMs to assess seasonal patterns of variation in the movement of pronghorn ( Antilocapra americana ), a species known for variable seasonal movements that challenge analytical approaches, while using a population of mule deer ( Odocoileus hemionus ), for whom seasonal movements are well-documented, as a comparison. We used population-level HMMs in a Bayesian framework to estimate a seasonal trend in the daily probability of transitioning between a short-distance local movement state and a long-distance movement state. The estimated seasonal patterns of movements in mule deer closely aligned with prior work based on indices of animal displacement: a short period of long-distance movements in the fall season and again in the spring, consistent with migrations to and from seasonal ranges. We found seasonal movement patterns for pronghorn were more variable, as a period of long-distance movements in the fall was followed by a winter period in which pronghorn were much more likely to further initiate and remain in a long-distance movement pattern compared with the movement patterns of mule deer. Overall, pronghorn were simply more likely to be in a long-distance movement pattern throughout the year. Hidden Markov movement models provide inference on seasonal movements similar to other methods, while providing a robust framework to understand movement patterns on shorter timescales and for more challenging movement patterns. Hidden Markov movement models can allow a rigorous assessment of the drivers of changes in movement patterns such as extreme weather events and land development, important for management and conservation.

Wyoming↗
USGS2025

SiMPL wildlife magnets: A camera trap tool for detecting all creatures great and small

We created the SiMPL wildlife magnet—a baited camera trap design that allows passive monitoring of wildlife, particularly small- to medium-sized mammals. The SiMPL wildlife magnet is inexpensive and easy to construct. To evaluate its effectiveness, we conducted a two-year case study using 9 camera stations along an elevation gradient in the White Mountains of the northeastern United States. We examined how the detection probability of mammal species changed with the inclusion of a SiMPL wildlife magnet using data from pre-and post-establishment. We found a significant increase in community-level detection probability with the use of SiMPL wildlife magnets and for individual species, including red squirrels ( Tamiasciurus hudsonicus ), American marten ( Martes americana ), and fisher ( Pekania pennanti ). Moreover, we were able to capture more species with SiMPL wildlife magnets than without, including flying squirrels ( Glaucomys spp.), various rodents ( Cricetidae spp.), black bears ( Ursus americanus ), moose ( Alces alces ), owls, and other birds. The SiMPL wildlife magnet is an effective, low-cost method for surveying wildlife communities, especially rodents and mesocarnivores. It addresses the limited field of view presented by other techniques for capturing small mammals on camera traps and enables efficient collection of phenology data, including vegetation and snowpack. This tool has several applications, including monitoring species' responses to management practices and global change.

Ecology and Evolution↗
USGS2011

Evaluating the demographic buffering hypothesis with vital rates estimated for Weddell seals from 30years of mark-recapture data

1. Life‐history theory predicts that those vital rates that make larger contributions to population growth rate ought to be more strongly buffered against environmental variability than are those that are less important. Despite the importance of the theory for predicting demographic responses to changes in the environment, it is not yet known how pervasive demographic buffering is in animal populations because the validity of most existing studies has been called into question because of methodological deficiencies. 2. We tested for demographic buffering in the southern‐most breeding mammal population in the world using data collected from 5558 known‐age female Weddell seals over 30 years. We first estimated all vital rates simultaneously with mark–recapture analysis and then estimated process variance and covariance in those rates using a hierarchical Bayesian approach. We next calculated the population growth rate’s sensitivity to changes in each of the vital rates and tested for evidence of demographic buffering by comparing properly scaled values of sensitivity and process variance in vital rates. 3. We found evidence of positive process covariance between vital rates, which indicates that all vital rates are affected in the same direction by changes in annual environment. Despite the positive correlations, we found strong evidence that demographic buffering occurred through reductions in variation in the vital rates to which population growth rate was most sensitive. Process variation in vital rates was inversely related to sensitivity measures such that variation was greatest in breeding probabilities, intermediate for survival rates of young animals and lowest for survival rates of older animals. 4. Our work contributes to a small but growing set of studies that have used rigorous methods on long‐term, detailed data to investigate demographic responses to environmental variation. The information from these studies improves our understanding of life‐history evolution in stochastic environments and provides useful information for predicting population responses to future environmental change. Our results for an Antarctic apex predator also provide useful baselines from a marine ecosystem when its top‐ and middle‐trophic levels were not substantially impacted by human activity.

Journal of Animal Ecology↗
USGS2017

Do you hear what I see? Vocalization relative to visual detection rates of Hawaiian hoary bats (Lasiurus cinereus semotus)

B ats vocalize during flight as part of the sensory modality called echolocation, but very little is known about whether flying bats consistently call. Occasional vocal silence during flight when bats approach prey or conspecifics has been documented for relatively few species and situations. Bats flying alone in clutter-free airspace are not known to forgo vocalization, yet prior observations suggested possible silent behavior in certain, unexpected situations. Determining when, why, and where silent behavior occurs in bats will help evaluate major assumptions of a primary monitoring method for bats used in ecological research, management, and conservation. In this study, we recorded flight activity of Hawaiian hoary bats ( Lasiurus cinereus semotus ) under seminatural conditions using both thermal video cameras and acoustic detectors. Simultaneous video and audio recordings from 20 nights of observation at 10 sites were analyzed for correspondence between detection methods, with a focus on video observations in three distance categories for which accompanying vocalizations were detected. Comparison of video and audio detections revealed that a high proportion of Hawaiian hoary bats “seen” on video were not simultaneously “heard.” On average, only about one in three visual detections within a night had an accompanying call detection, but this varied greatly among nights. Bats flying on curved flight paths and individuals nearer the cameras were more likely to be detected by both methods. Feeding and social calls were detected, but no clear pattern emerged from the small number of observations involving closely interacting bats. These results may indicate that flying Hawaiian hoary bats often forgo echolocation, or do not always vocalize in a way that is detectable with common sampling and monitoring methods. Possible reasons for the low correspondence between visual and acoustic detections range from methodological to biological and include a number of biases associated with the propagation and detection of sound, cryptic foraging strategies, or conspecific presence. Silent flight behavior may be more prevalent in echolocating bats than previously appreciated, has profound implications for ecological research, and deserves further characterization and study.

Hawai'i↗
USGS2020

Are environmental DNA methods ready for aquatic invasive species management?

Multiple studies have demonstrated environmental (e)DNA detections of rare, invasive species. However, invasive species managers struggle with using eDNA results because detections might not indicate species presence. We evaluated if eDNA methods have matured to a point where they can be widely applied to aquatic invasive species management. We found that eDNA methods meet legal standards for being admissible as evidence in most courts, suggesting that eDNA method reliability is not the problem. Rather, we suggest that the interface between results and management needs attention since there are few tools for integrating uncertainty into decision-making. Solutions include decision support trees based on molecular best practices that integrate the temporal and spatial trends in eDNA positives relative to human risk tolerance.

Trends in Ecology and Evolution↗
USGS2025

Different data for different goals: Exploring trade-offs and synergies in the use of spatial data inputs to optimize conservation action in sagebrush ecosystems

Ecosystems worldwide continue to experience rapid rates of habitat and species loss. Management actions to conserve and restore functional habitats are needed to reduce these declines, but funding and resources for such actions are limited. Spatial conservation prioritization (SCP) can facilitate strategic decision-making for targeted conservation planning and delivery, but complexities arise when management objectives include multiple wildlife species and ecological or management constraints, all of which can be further complicated by data uncertainty and existing conservation plans. The Prioritizing Restoration of Sagebrush Ecosystems Tool (PReSET), an R package-based decision-support tool, supports strategic ecosystem management planning across the sagebrush biome by using SCP. We adapted PReSET to better address the needs of multiple wildlife species, evaluate the effects of different ecological or management constraints on conservation outcomes, assess the influence of data uncertainty, and integrate existing conservation plans. Specifically, we developed optimization problems to identify priority sagebrush protection and restoration across the state of Wyoming, USA, and evaluated the efficacy and trade-offs of various approaches to problem design. We evaluated trade-offs in targeting multiple species compared to a single species, including using greater sage-grouse as a potential umbrella species to benefit other sagebrush-dependent wildlife. We then evaluated multi-species protection and restoration problems aimed at minimizing the risks of inadequate connectivity, climate change, and restoration failure, and accounted for data uncertainty to assess relationships between risk aversion of managers and conservation outcomes. We also developed optimization problems within conservation areas identified by an existing sagebrush conservation plan to evaluate the efficacy of guiding local-scale conservation delivery within more broadly defined conservation areas. Our results demonstrate how SCP methods can leverage novel spatial data to develop targeted decision-support resources that can facilitate landscape conservation planning and improve management outcomes across a wide array of systems and species.

Wyoming↗
USGS2024

Development and validation of a GT-seq panel for genetic monitoring in a threatened species using minimally invasive sampling

Minimally invasive samples are often the best option for collecting genetic material from species of conservation concern, but they perform poorly in many genomic sequencing methods due to their tendency to yield low DNA quality and quantity. Genotyping-in-thousands by sequencing (GT-seq) is a powerful amplicon sequencing method that can genotype large numbers of variable-quality samples at a standardized set of single nucleotide polymorphism (SNP) loci. Here, we develop, optimize, and validate a GT-seq panel for the federally threatened northern Idaho ground squirrel ( Urocitellus brunneus ) to provide a standardized approach for future genetic monitoring and assessment of recovery goals using minimally invasive samples. The optimized panel consists of 224 neutral and 81 putatively adaptive SNPs. DNA collected from buccal swabs from 2016 to 2020 had 73% genotyping success, while samples collected from hair from 2002 to 2006 had little to no DNA remaining and did not genotype successfully. We evaluated our GT-seq panel by measuring genotype discordance rates compared to RADseq and whole-genome sequencing. GT-seq and other sequencing methods had similar population diversity and F ST estimates, but GT-seq consistently called more heterozygotes than expected, resulting in negative F IS values at the population level. Genetic ancestry assignment was consistent when estimated with different sequencing methods and numbers of loci. Our GT-seq panel is an effective and efficient genotyping tool that will aid in the monitoring and recovery of this threatened species, and our results provide insights for applying GT-seq for minimally invasive DNA sampling techniques in other rare animals.

Ecology and Evolution↗
USGS2015

Testing taxon tenacity of tortoises: evidence for a geographical selection gradient at a secondary contact zone

We examined a secondary contact zone between two species of desert tortoise, Gopherus agassizii and G. morafkai . The taxa were isolated from a common ancestor during the formation of the Colorado River (4-8 mya) and are a classic example of allopatric speciation. However, an anomalous population of G. agassizii comes into secondary contact with G. morafkai east of the Colorado River in the Black Mountains of Arizona and provides an opportunity to examine reinforcement of species' boundaries under natural conditions. We sampled 234 tortoises representing G. agassizii in California ( n = 103), G. morafkai in Arizona ( n = 78), and 53 individuals of undetermined assignment in the contact zone including and surrounding the Black Mountains. We genotyped individuals for 25 STR loci and determined maternal lineage using mtDNA sequence data. We performed multilocus genetic clustering analyses and used multiple statistical methods to detect levels of hybridization. We tested hypotheses about habitat use between G. agassizii and G. morafkai in the region where they co-occur using habitat suitability models. Gopherus agassizii and G. morafkai maintain independent taxonomic identities likely due to ecological niche partitioning, and the maintenance of the hybrid zone is best described by a geographical selection gradient model.

Ecology and Evolution↗
USGS2023

Four conservation challenges and a synthesis

Conservation and management of biological systems involves decision-making over time, with a generic goal of sustaining systems and their capacity to function in the future. We address four persistent and difficult conservation challenges: (1) prediction of future consequences of management, (2) uncertainty about the system's structure, (3) inability to observe ecological systems fully, and (4) nonstationary system dynamics. We describe these challenges in terms of dynamic systems subject to different sources of uncertainty, and we present a basic Markovian framework that can encompass approaches to all four challenges. Finding optimal conservation strategies for each challenge requires issue-specific structural features, including adaptations of state transition models, uncertainty metrics, valuation of accumulated returns, and solution methods. Strategy valuation exhibits not only some remarkable similarities among approaches but also some important operational differences. Technical linkages among the models highlight synergies in solution approaches, as well as possibilities for combining them in particular conservation problems. As methodology and computing software advance, such an integrated conservation framework offers the potential to improve conservation outcomes with strategies to allocate management resources efficiently and avoid negative consequences.

Ecology and Evolution↗