High-Quality, Chromosome-Level Reference Genomes of the Viviparous Caribbean Skinks Spondylurus nitidus and S. culebrae.

New World mabuyine skinks are a diverse radiation of morphologically cryptic lizards with unique reproductive biologies. Recent studies examining population-level data (morphological, ecological, and genomic) have uncovered novel biodiversity and phenotypes, including the description of dozens of new species and insights into the evolution of their highly complex placental structures. Beyond the potential for this diverse group to serve as a model for the evolution of viviparity in lizards, much of the taxonomic diversity is concentrated in regions experiencing increasing environmental instability from climate and anthropogenic change. Consequently, a better understanding of genome structure and diversity will be an important tool in the adaptive management and conservation of this group. Skinks endemic to Caribbean islands are particularly vulnerable to global change with several species already considered likely extinct and several remaining species either endangered or threatened. Combining PacBio long-read sequencing, Hi-C, and RNAseq data, here we present the first genomic resources for this group by describing new chromosome-level reference genomes for the Puerto Rican Skink Spondylurus nitidus and the Culebra Skink S. culebrae. Results indicate two high quality genomes, both ∼1.4 Gb, assembled nearly telomere to telomere with complete mitochondrion assembly and annotation.

Cumulative effects of piscivorous colonial waterbirds on juvenile salmonids: A multi predator-prey species evaluation.

We investigated the cumulative effects of predation by piscivorous colonial waterbirds on the survival of multiple salmonid (Oncorhynchus spp.) populations listed under the U.S. Endangered Species Act (ESA) and determined what proportion of all sources of fish mortality (1 -survival) were due to birds in the Columbia River basin, USA. Anadromous juvenile salmonids (smolts) were exposed to predation by Caspian terns (Hydroprogne caspia), double-crested cormorants (Nannopterum auritum), California gulls (Larus californicus), and ring-billed gulls (L. delawarensis), birds known to consume both live and dead fish. Avian consumption and survival probabilities (proportion of available fish consumed or alive) were estimated for steelhead trout (O. mykiss), yearling Chinook salmon (O. tshawytscha), sub-yearling Chinook salmon, and sockeye salmon (O. nerka) during out-migration from the lower Snake River to the Pacific Ocean during an 11-year study period (2008-2018). Results indicated that probabilities of avian consumption varied greatly across salmonid populations, bird species, colony location, river reach, and year. Cumulative consumption probabilities (consumption by birds from all colonies combined) were consistently the highest for steelhead, with annual estimates ranging from 0.22 (95% credible interval = 0.20-0.26) to 0.51 (0.43-0.60) of available smolts. The cumulative effects of avian consumption were significantly lower for yearling and sub-yearling Chinook salmon, with consumption probabilities ranging annually from 0.04 (0.02-0.07) to 0.10 (0.07-0.15) and from 0.06 (0.3-0.09) to 0.15 (0.10-0.23), respectively. Avian consumption probabilities for sockeye salmon smolts was generally higher than for Chinook salmon smolts, but lower than for steelhead smolts, ranging annually from 0.08 (0.03-0.22) to 0.25 (0.14-0.44). Although annual consumption probabilities for birds from certain colonies were more than 0.20 of available smolts, probabilities from other colonies were less than 0.01 of available smolts, indicating that not all colonies of birds posed a substantial risk to smolt mortality. Consumption probabilities were lowest for small colonies and for colonies located a considerable distance from the Snake and Columbia rivers. Total mortality attributed to avian consumption was relatively small for Chinook salmon (less than 10%) but was the single greatest source of mortality for steelhead (greater than 50%) in all years evaluated. Results suggest that the potential benefits to salmonid populations of managing birds to reduce smolt mortality would vary widely depending on the salmonid population, the species of bird, and the size and location of the breeding colony.

Modeling spatiotemporal abundance and movement dynamics using an integrated spatial capture-recapture movement model.

Animal movement is a fundamental ecological process affecting the survival and reproduction of individuals, the structure of populations, and the dynamics of communities. Methods to quantify animal movement and spatiotemporal abundances, however, are generally separate and therefore omit linkages between individual-level and population-level processes. We describe an integrated spatial capture-recapture (SCR) movement model to jointly estimate (1) the number and distribution of individuals in a defined spatial region and (2) movement of those individuals through time. We applied our model to a study of polar bears (Ursus maritimus) in a 28,125 km2 survey area of the eastern Chukchi Sea, USA in 2015 that incorporated capture-recapture and telemetry data. In simulation studies, the model provided unbiased estimates of movement, abundance, and detection parameters using a bivariate normal random walk and correlated random walk movement process. Our case study provided detailed evidence of directional movement persistence for both male and female bears, where individuals regularly traversed areas larger than the survey area during the 36-day study period. Scaling from individual- to population-level inferences, we found that densities varied from <0.75 bears/625 km2 grid cell/day in nearshore cells to 1.6-2.5 bears/grid cell/day for cells surrounded by sea ice. Daily abundance estimates ranged from 53 to 69 bears, with no trend across days. The cumulative number of unique bears that used the survey area increased through time due to movements into and out of the area, resulting in an estimated 171 individuals using the survey area during the study (95% credible interval 124-250). Abundance estimates were similar to a previous multiyear integrated population model using capture-recapture and telemetry data (2008-2016; Regehr et al., Scientific Reports 8:16780, 2018). Overall, the SCR-movement model successfully quantified both individual- and population-level space use, including the effects of landscape characteristics on movement, abundance, and detection, while linking the movement and abundance processes to directly estimate density within a prescribed spatial region and temporal period. Integrated SCR-movement models provide a generalizable approach to incorporate greater movement realism into population dynamics and link movement to emergent properties including spatiotemporal densities and abundances.

Integrated animal movement and spatial capture-recapture models: Simulation, implementation, and inference.

Over the last decade, spatial capture-recapture (SCR) models have become widespread for estimating demographic parameters in ecological studies. However, the underlying assumptions about animal movement and space use are often not realistic. This is a missed opportunity because interesting ecological questions related to animal space use, habitat selection, and behavior cannot be addressed with most SCR models, despite the fact that the data collected in SCR studies - individual animals observed at specific locations and times - can provide a rich source of information about these processes and how they relate to demographic rates. We developed SCR models that integrated more complex movement processes that are typically inferred from telemetry data, including a simple random walk, correlated random walk (i.e., short-term directional persistence), and habitat-driven Langevin diffusion. We demonstrated how to formulate, simulate from, and fit these models with standard SCR data using data-augmented Bayesian analysis methods. We evaluated their performance through a simulation study, in which we varied the detection, movement, and resource selection parameters. We also examined different numbers of sampling occasions and assessed performance gains when including auxiliary location data collected from telemetered individuals. Across all scenarios, the integrated SCR movement models performed well in terms of abundance, detection, and movement parameter estimation. We found little difference in bias for the simple random walk model when reducing the number of sampling occasions from T = 25 to T = 15. We found some bias in movement parameter estimates under several of the correlated random walk scenarios, but incorporating auxiliary location data improved parameter estimates and significantly improved mixing during model fitting. The Langevin movement model was able to recover resource selection parameters from standard SCR data, which is particularly appealing because it explicitly links the individual-level movement process with habitat selection and population density. We focused on closed population models, but the movement models developed here can be extended to open SCR models. The movement process models could also be easily extended to accommodate additional "building blocks" of random walks, such as central tendency (e.g., territoriality) or multiple movement behavior states, thereby providing a flexible and coherent framework for linking animal movement behavior to population dynamics, density, and distribution.

An integrated path for spatial capture-recapture and animal movement modeling.

Ecologists and conservation biologists increasingly rely on spatial capture-recapture (SCR) and movement modeling to study animal populations. Historically, SCR has focused on population-level processes (e.g., vital rates, abundance, density, and distribution), whereas animal movement modeling has focused on the behavior of individuals (e.g., activity budgets, resource selection, migration). Even though animal movement is clearly a driver of population-level patterns and dynamics, technical and conceptual developments to date have not forged a firm link between the two fields. Instead, movement modeling has typically focused on the individual level without providing a coherent scaling from individual- to population-level processes, whereas SCR has typically focused on the population level while greatly simplifying the movement processes that give rise to the observations underlying these models. In our view, the integration of SCR and animal movement modeling has tremendous potential for allowing ecologists to scale up from individuals to populations and advancing the types of inferences that can be made at the intersection of population, movement, and landscape ecology. Properly accounting for complex animal movement processes can also potentially reduce bias in estimators of population-level parameters, thereby improving inferences that are critical for species conservation and management. This introductory article to the Special Feature reviews recent advances in SCR and animal movement modeling, establishes a common notation, highlights potential advantages of linking individual-level (Lagrangian) movements to population-level (Eulerian) processes, and outlines a general conceptual framework for the integration of movement and SCR models. We then identify important avenues for future research, including key challenges and potential pitfalls in the developments and applications that lie ahead.

Demographic risk assessment for a harvested species threatened by climate change: polar bears in the Chukchi Sea.

Climate change threatens global biodiversity. Many species vulnerable to climate change are important to humans for nutritional, cultural, and economic reasons. Polar bears Ursus maritimus are threatened by sea-ice loss and represent a subsistence resource for Indigenous people. We applied a novel population modeling-management framework that is based on species life history and accounts for habitat loss to evaluate subsistence harvest for the Chukchi Sea (CS) polar bear subpopulation. Harvest strategies followed a state-dependent approach under which new data were used to update the harvest on a predetermined management interval. We found that a harvest strategy with a starting total harvest rate of 2.7% (˜85 bears/yr at current abundance), a 2:1 male-to-female ratio, and a 10-yr management interval would likely maintain subpopulation abundance above maximum net productivity level for the next 35 yr (approximately three polar bear generations), our primary criterion for sustainability. Plausible bounds on starting total harvest rate were 1.7-3.9%, where the range reflects uncertainty due to sampling variation, environmental variation, model selection, and differing levels of risk tolerance. The risk of undesired demographic outcomes (e.g., overharvest) was positively related to harvest rate, management interval, and projected declines in environmental carrying capacity; and negatively related to precision in population data. Results reflect several lines of evidence that the CS subpopulation has been productive in recent years, although it is uncertain how long this will last as sea-ice loss continues. Our methods provide a template for balancing trade-offs among protection, use, research investment, and other factors. Demographic risk assessment and state-dependent management will become increasingly important for harvested species, like polar bears, that exhibit spatiotemporal variation in their response to climate change.

Age-structured Jolly-Seber model expands inference and improves parameter estimation from capture-recapture data.

Understanding the influence of individual attributes on demographic processes is a key objective of wildlife population studies. Capture-recapture and age data are commonly collected to investigate hypotheses about survival, reproduction, and viability. We present a novel age-structured Jolly-Seber model that incorporates age and capture-recapture data to provide comprehensive information on population dynamics, including abundance, age-dependent survival, recruitment, age structure, and population growth rates. We applied our model to a multi-year capture-recapture study of polar bears (Ursus maritimus) in western Hudson Bay, Canada (2012-2018), where management and conservation require a detailed understanding of how polar bears respond to climate change and other factors. In simulation studies, the age-structured Jolly-Seber model improved precision of survival, recruitment, and annual abundance estimates relative to standard Jolly-Seber models that omit age information. Furthermore, incorporating age information improved precision of population growth rates, increased power to detect trends in abundance, and allowed direct estimation of age-dependent survival and changes in annual age structure. Our case study provided detailed evidence for senescence in polar bear survival. Median survival estimates were lower (<0.95) for individuals aged <5 years, remained high (>0.95) for individuals aged 7-22 years, and subsequently declined to near zero for individuals >30 years. We also detected cascading effects of large recruitment classes on population age structure, which created major shifts in age structure when these classes entered the population and then again when they reached prime breeding ages (10-15 years old). Overall, age-structured Jolly-Seber models provide a flexible means to investigate ecological and evolutionary processes that shape populations (e.g., via senescence, life expectancy, and lifetime reproductive success) while improving our ability to investigate population dynamics and forecast population changes from capture-recapture data.

Movement-assisted localization from acoustic telemetry data.

BACKGROUND: Acoustic telemetry technologies are being increasingly deployed to study a variety of aquatic taxa including fishes, reptiles, and marine mammals. Large cooperative telemetry networks produce vast quantities of data useful in the study of movement, resource selection and species distribution. Efficient use of acoustic telemetry data requires estimation of acoustic source locations from detections at receivers (i.e., "localization"). Multiple processes provide information for localization estimation including detection/non-detection data at receivers, information on signal rate, and an underlying movement model describing how individuals move and utilize space. Frequently, however, localization methods only integrate a subset of these processes and do not utilize the full spatial encounter history information available from receiver arrays. METHODS: In this paper we draw analogies between the challenges of acoustic telemetry localization and newly developed methods of spatial capture-recapture (SCR). We develop a framework for localization that integrates explicit sub-models for movement, signal (or cue) rate, and detection probability, based on acoustic telemetry spatial encounter history data. This method, which we call movement-assisted localization, makes efficient use of the full encounter history data available from acoustic receiver arrays, provides localizations with fewer than three detections, and even allows for predictions to be made of the position of an individual when it was not detected at all. We demonstrate these concepts by developing generalizable Bayesian formulations of the SCR movement-assisted localization model to address study-specific challenges common in acoustic telemetry studies. RESULTS: Simulation studies show that movement-assisted localization models improve point-wise RMSE of localization estimates by >50% and greatly increased the precision of estimated trajectories compared to localization using only the detection history of a given signal. Additionally, integrating a signal rate sub-model reduced biases in the estimation of movement, signal rate, and detection parameters observed in independent localization models. CONCLUSIONS: Movement-assisted localization provides a flexible framework to maximize the use of acoustic telemetry data. Conceptualizing localization within an SCR framework allows extensions to a variety of data collection protocols, improves the efficiency of studies interested in movement, resource selection, and space-use, and provides a unifying framework for modeling acoustic data.

Measuring the additive effects of predation on prey survival across spatial scales.

The degree to which predation is an additive vs. compensatory source of mortality is fundamental to understanding the effects of predation on prey populations and evaluating the efficacy of predator management actions. In the Columbia River basin, USA, predation by Caspian Terns (Hydroprogne caspia) on U.S. Endangered Species Act (ESA)-listed juvenile salmonids (smolts; Oncorhynchus spp.) has led to predator management actions to reduce predation; however, the assumption that reduced predation translates into greater salmonid survival, either within the life stage where predation occurs or across their lifetime, has remained untested. To address this critical uncertainty, we analyzed a long-term (2008-2018) mark-recapture-recovery data set of ESA-listed steelhead trout (O. mykiss) that were tagged (n = 78,409) and subsequently exposed to predation during smolt out-migration through multiple river reaches (spatial scales), jointly estimating weekly probabilities of steelhead survival, mortality due to bird predation, and mortality due to other causes. This concurrent estimation across time-stratified cohorts allowed for the direct measurement of the strength, magnitude, and direction of relationships between survival and Caspian Tern predation. Estimates of Tern predation on steelhead were substantial in most years, with cumulative annual estimates ranging from 0.075 (95% creditable interval = 0.058-0.099) to 0.375 (0.290-0.461). Increases in Tern predation probabilities were associated with statistically significant decreases in steelhead survival probabilities in all evaluated years and salmonid life stages (smolt out-migration and smolt-to-adult returns). Results provide novel evidence that predation by Caspian Terns may have been a super-additive source of mortality during the smolt life stage and a partially additive source of mortality to the adult life stage. Annual estimates of the difference between observed survival and baseline survival (i.e., in the absence of Tern predation) ranged from 0.052 (0.017-0.103) to 0.314 (0.172-0.459) during the steelhead smolt life stage and from 0.011 (0.001-0.029) to 0.049 (0.025-0.078) to the adult life stage. The estimated levels of compensation have important implications for predator management actions aimed at increasing the survival of endangered salmonids, and the modeling approach developed herein provides a framework to directly quantify the impacts of source-specific mortality factors on prey populations.

Integrated Population Modeling Provides the First Empirical Estimates of Vital Rates and Abundance for Polar Bears in the Chukchi Sea.

Large carnivores are imperiled globally, and characteristics making them vulnerable to extinction (e.g., low densities and expansive ranges) also make it difficult to estimate demographic parameters needed for management. Here we develop an integrated population model to analyze capture-recapture, radiotelemetry, and count data for the Chukchi Sea subpopulation of polar bears (Ursus maritimus), 2008-2016. Our model addressed several challenges in capture-recapture studies for polar bears by including a multievent structure reflecting location and life history states, while accommodating state uncertainty. Female breeding probability was 0.83 (95% credible interval [CRI] = 0.71-0.90), with litter sizes of 2.18 (95% CRI = 1.71-2.82) for age-zero and 1.61 (95% CRI = 1.46-1.80) for age-one cubs. Total adult survival was 0.90 (95% CRI = 0.86-0.92) for females and 0.89 (95% CRI = 0.83-0.93) for males. Spring on-ice densities west of Alaska were 0.0030 bears/km2 (95% CRI = 0.0016-0.0060), similar to 1980s-era density estimates although methodological differences complicate comparison. Abundance of the Chukchi Sea subpopulation, derived by extrapolating density from the study area using a spatially-explicit habitat metric, was 2,937 bears (95% CRI = 1,552-5,944). Our findings are consistent with other lines of evidence suggesting the Chukchi Sea subpopulation has been productive in recent years, although it is uncertain how long this will continue given sea-ice loss due to climate change.

Transcription profiling in environmental diagnostics: health assessments in Columbia River basin steelhead (Oncorhynchus mykiss).

The health condition of out-migrating juvenile salmonids can influence migration success. Physical damage, pathogenic infection, contaminant exposure, and immune system status can affect survival probability. The present study is part of a wider investigation of out-migration success in juvenile steelhead (Oncorhynchus mykiss) and focuses on the application of molecular profiling to assess sublethal effects of environmental stressors in field-collected fish. We used a suite of genes in O. mykiss to specifically assess responses that could be directly related to steelhead health condition during out-migration. These biomarkers were used on juvenile steelhead captured in the Snake River, a tributary of the Columbia River, in Washington, USA, and were applied on gill and anterior head kidney tissue to assess immune system responses, pathogen-defense (NRAMP, Mx, CXC), general stress (HSP70), metal-binding (metallothionein-A), and xenobiotic metabolism (Cyp1a1) utilizing quantitative polymerase chain reaction (PCR) technology. Upon capture, fish were ranked according to visual external physical conditions into good, fair, poor, and bad categories; gills and kidney tissues were then dissected and preserved for gene analyses. Transcription responses were tissue-specific for gill and anterior head kidney with less significant responses in gill tissue than in kidney. Significant differences between the condition ranks were attributed to NRAMP, MX, CXC, and Cyp1a1 responses. Gene profiling correlated gene expression with pathogen presence, and results indicated that gene profiling can be a useful tool for identifying specific pathogen types responsible for disease. Principal component analysis (PCA) further correlated these responses with specific health condition categories, strongly differentiating good, poor, and bad condition ranks. We conclude that molecular profiling is an informative and useful tool that could be applied to indicate and monitor numerous population-level parameters of management interest.