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At least 127 records · Page 7Linked to original sources

The conservation genetics juggling act: Integrating genetics and ecology, science and policy

The field of conservation genetics, when properly implemented, is a constant juggling act integrating molecular genetics, ecology, and demography with applied aspects concerning managing declining species or implementing conservation laws and policies. This young field has grown substantially since the 1980’s following development of the polymerase chain reaction and now into the genomics era. Our lab has “grown up” with the field, having worked on these issues for over three decades. Our multi-disciplinary approach entails understanding the behavior and ecology of species as well as the underlying processes that contribute to genetic viability. Taking this holistic approach provides a comprehensive understanding of factors that influence species persistence and evolutionary potential while considering annual challenges that occur throughout their life cycle. As a federal lab, we are often addressing the needs of the U.S. Fish and Wildlife Service in their efforts to list, de-list or recover species. Nevertheless, there remains an overall communication gap between research geneticists and biologists who are charged with implementing their results. Therefore, we outline the need for a National Center for Small Population Biology to ameliorate this problem and provide organizations charged with making status decisions firmer ground from which to make their critical decisions.

Evolutionary Applications↗

A mosaic-based approach is needed to conserve biodiversity in disturbed freshwater ecosystems

Conserving native biodiversity in the face of human‐ and climate‐related impacts is a challenging and globally important ecological problem that requires an understanding of spatially connected, organismal‐habitat relationships. Globally, a suite of disturbances (e.g., agriculture, urbanization, climate change) degrades habitats and threatens biodiversity. A mosaic approach (in which connected, interacting collections of juxtaposed habitat patches are examined) provides a scientific foundation for addressing many disturbance‐related, ecologically based conservation problems. For example, if specific habitat types disproportionately increase biodiversity, these keystones should be incorporated into research and management plans. Our sampling of fish biodiversity and aquatic habitat along ten 3‐km sites within the Upper Neosho River subdrainage, KS, from June‐August 2013 yielded three generalizable ecological insights. First, specific types of mesohabitat patches (i.e., pool, riffle, run, and glide) were physically distinct and created unique mosaics of mesohabitats that varied across sites. Second, species richness was higher in riffle mesohabitats when mesohabitat size reflected field availability. Furthermore, habitat mosaics that included more riffles had greater habitat diversity and more fish species. Thus, riffles (<5% of sampled area) acted as keystone habitats. Third, additional conceptual development, which we initiate here, can broaden the identification of keystone habitats across ecosystems and further operationalize this concept for research and conservation. Thus, adopting a mosaic approach can increase scientific understanding of organismal‐habitat relationships, maintain natural biodiversity, advance spatial ecology, and facilitate effective conservation of native biodiversity in human‐altered ecosystems.

Kansas↗

Changing perspectives on pearly mussels, North America's most imperiled animals

Pearly mussels (Unionacea) are widespread, abundant, and important in freshwater ecosystems around the world. Catastrophic declines in pearly mussel populations in North America and other parts of the world have led to a flurry of research on mussel biology, ecology, and conservation. Recent research on mussel feeding, life history, spatial patterning, and declines has augmented, modified, or overturned long-held ideas about the ecology of these animals. Pearly mussel research has begun to benefit from and contribute to current ideas about suspension feeding, life-history theory, metapopulations, flow refuges, spatial patterning and its effects, and management of endangered species. At the same time, significant gaps in understanding and apparent paradoxes in pearly mussel ecology have been exposed. To conserve remaining mussel populations, scientists and managers must simultaneously and aggressively pursue both rigorous research and conservation actions.

BioScience↗

A review of supervised learning methods for classifying animal behavioural states from environmental features

Accurately predicting behavioural modes of animals in response to environmental features is important for ecology and conservation. Supervised learning (SL) methods are increasingly common in animal movement ecology for classifying behavioural modes. However, few examples exist of applying SL to classify polytomous animal behaviour from environmental features especially in the context of millions of animal observations. We review SL methods (weighted k -nearest neighbours; neural nets; random forests; and boosted classification trees with XGBoost) for classifying polytomous animal behaviour from environmental predictors. We also describe tuning parameter selection and assessment strategies, approaches for visualizing relationships between predictors and class outputs, and computational considerations. We demonstrate these methods by predicting three categories of risk to bald eagles from colliding with wind turbines using, as predictors, 12 environmental state features associated with 1.7 million GPS telemetry data points from 57 eagles. Of the SL methods we considered, XGBoost yielded the most accurate model with 86.2% classification accuracy and pairwise-averaged area under the ROC curve of 90.6. Computational time of XGBoost scaled better to large data than any other SL method. We also show how SHAP values integrated in the R package ( xgboost ) facilitate investigation of variable relationships and importance. For big data applications, XGBoost appears to provide superior classification accuracy and computational efficiency. Our results suggest XGBoost should be considered as an early modelling option in situations where the intent is to classify millions of animal behaviour observations from environmental predictors and to understand relationships between those predictors and movement behaviours. We also offer a tutorial to assist researchers in implementing this method.

Methods in Ecology and Evolution↗

Forecasting sea otter recolonization: Insights from isotopic analysis of modern and zooarchaeological populations

Retrospective datasets offer essential context for conservation by revealing species’ ecological roles before industrial-era human impacts. We analysed isotopic compositions of pre-industrial and modern sea otters ( Enhydra lutris ) to reconstruct pre-extirpation ecology and offer insights for management. Our study focuses on southeast Alaska (SEAK), where sea otters are recolonizing, and northern Oregon, where translocations are being considered. We measured bulk bone collagen δ 13 C and δ 15 N values and essential amino acid δ 13 C values of extirpated sea otters from archaeological contexts, and bulk isotopic values from vibrissae of modern SEAK sea otters. We compare these results with published isotopic data of potential prey and additional archaeological datasets. In SEAK, our data show pre-industrial sea otter populations consumed infaunal bivalves and used soft-sediment (33%) and kelp forest habitats (67%), with sub-regional variation. We anticipate current populations will expand into this historical niche, and conflict with regional traditional/subsistence bivalve fisheries will persist. In northern Oregon, isotopic data from extirpated sea otters indicate past consumption of low trophic level invertebrates and a stronger reliance on kelp forests (88%) rather than soft-sediment habitats, highlighting the importance of kelp forests for future translocations. Our work exemplifies the value of historical ecology in informing conservation strategies for recovering species.

Alaska, Oregon↗

Fragmentation: Is the message clear?

In this paper, we briefly discuss some of the fundamental problems arising from the inherent complexity of larger-scale ecological systems. We examine the tenuous assumption of a direct correspondence between ecological data and theory, we comment on a recent report that evaluated the efficacy of fragmentation experiments, and we briefly assess its implications for ecological research and conservation practice on the landscape scale.

Ecology and Society↗

Monitoring for conservation

Human-mediated environmental changes have resulted in appropriate concern for the conservation of ecological systems and have led to the development of many ecological monitoring programs worldwide. Many programs that are identified with the purpose of `surveillance? represent an inefficient use of conservation funds and effort. Here, we revisit the 1964 paper by Platt and argue that his recommendations about the conduct of science are equally relevant to the conduct of ecological monitoring programs. In particular, we argue that monitoring should not be viewed as a stand-alone activity, but instead as a component of a larger process of either conservation-oriented science or management. Corresponding changes in monitoring focus and design would lead to substantial increases in the efficiency and usefulness of monitoring results in conservation.

Trends in Ecology and Evolution↗

Integrating human impacts and ecological integrity into a risk-based protocol for conservation planning

Conservation planning aims to protect biodiversity by sustainng the natural physical, chemical, and biological processes within representative ecosystems. Often data to measure these components are inadequate or unavailable. The impact of human activities on ecosystem processes complicates integrity assessments and might alter ecosystem organization at multiple spatial scales. Freshwater conservation targets, such as populations and communities, are influenced by both intrinsic aquatic properties and the surrounding landscape, and locally collected data might not accurately reflect potential impacts. We suggest that changes in five major biotic drivers—energy sources, physical habitat, flow regime, water quality, and biotic interactions—might be used as surrogates to inform conservation planners of the ecological integrity of freshwater ecosystems. Threats to freshwater systems might be evaluated based on their impact to these drivers to provide an overview of potential risk to conservation targets. We developed a risk-based protocol, the Ecological Risk Index (ERI), to identify watersheds with least/most risk to conservation targets. Our protocol combines risk-based components, specifically the frequency and severity of human-induced stressors, with biotic drivers and mappable land- and water-use data to provide a summary of relative risk to watersheds. We illustrate application of our protocol with a case study of the upper Tennessee River basin, USA. Differences in risk patterns among the major drainages in the basin reflect dominant land uses, such as mining and agriculture. A principal components analysis showed that localized, moderately severe threats accounted for most of the threat composition differences among our watersheds. We also found that the relative importance of threats is sensitive to the spatial grain of the analysis. Our case study demonstrates that the ERI is useful for evaluating the frequency and severity of ecosystemwide risk, which can inform local and regional conservation planning.

Tennessee↗

The migratory bird treaty and a century of waterfowl conservation

In the final decades of the nineteenth century, concern was building about the status of migratory bird populations in North America. In this literature review, we describe how that concern led to a landmark conservation agreement in 1916, between the United States and Great Britain (on behalf of Canada) to conserve migratory birds shared by Canada and the United States. Drawing on published literature and our personal experience, we describe how subsequent enabling acts in both countries gave rise to efforts to better estimate population sizes and distributions, assess harvest rates and demographic impacts, design and fund landscape-level habitat conservation initiatives, and organize necessary political and regulatory processes. Executing these steps required large-scale thinking, unprecedented regional and international cooperation, ingenuity, and a commitment to scientific rigor and adaptive management. We applaud the conservation efforts begun 100 years ago with the Migratory Bird Treaty Convention. The agreement helped build the field of wildlife ecology and conservation in the twentieth century but only partially prepares us for the ecological and social challenges ahead.

Journal of Wildlife Management↗

Cerulean Warbler Technical Group: Coordinating international research and conservation

Effective conservation for species of concern requires interchange and collaboration among conservationists and stakeholders. The Cerulean Warbler Technical Group (CWTG) is a consortium of biologists and managers from government agencies, non-governmental organizations, academia, and industry, who are dedicated to finding pro-active, science-based solutions for conservation of the Cerulean Warbler (Setophaga cerulea). Formed in the United States in 2001, CWTG’s scope soon broadened to address the species’ ecology and conservation on both the breeding and non-breeding ranges, in partnership with biologists from South and Central America. In 2004, CWTG launched the Cerulean Warbler Conservation Initiative, a set of activities aimed at addressing information and conservation needs for the species. These include (1) studies in the core breeding range to assess Cerulean Warbler response to forest management practices and to identify mined lands that could be reforested to benefit the species, (2) ecological and demographic studies on the winter range, and (3) surveys of Cerulean Warbler distribution on the breeding and winter ranges and during migration. A rangewide conservation action plan has been completed, along with a more detailed conservation plan for the non-breeding range. CWTG and partners now move forward with on-the-ground conservation, while still addressing unmet information needs.

Ornitologia Neotropical↗

Linking animals aloft with the terrestrial landscape

Despite using the aerosphere for many facets of their life, most flying animals (i.e., birds, bats, some insects) are still bound to terrestrial habitats for resting, feeding, and reproduction. Comprehensive broad-scale observations by weather surveillance radars of animals as they leave terrestrial habitats for migration or feeding flights can be used to map their terrestrial distributions either as point locations (e.g., communal roosts) or as continuous surface layers (e.g., animal densities in habitats across a landscape). We discuss some of the technical challenges to reducing measurement biases related to how radars sample the aerosphere and the flight behavior of animals. We highlight a recently developed methodological approach that precisely and quantitatively links the horizontal spatial structure of birds aloft to their terrestrial distributions and provides novel insights into avian ecology and conservation across broad landscapes. Specifically, we present case studies that (1) elucidate how migrating birds contend with crossing ecological barriers and extreme weather events, (2) identify important stopover areas and habitat use patterns of birds along their migration routes, and (3) assess waterfowl response to wetland habitat management and restoration. These studies aid our understanding of how anthropogenic modification of the terrestrial landscape (e.g., urbanization, habitat management), natural geographic features, and weather (e.g., hurricanes) can affect the terrestrial distributions of flying animals.

Book chapter↗

Representation of ecological systems within the protected areas network of the continental United States

If conservation of biodiversity is the goal, then the protected areas network of the continental US may be one of our best conservation tools for safeguarding ecological systems (i.e., vegetation communities). We evaluated representation of ecological systems in the current protected areas network and found insufficient representation at three vegetation community levels within lower elevations and moderate to high productivity soils. We used national-level data for ecological systems and a protected areas database to explore alternative ways we might be able to increase representation of ecological systems within the continental US. By following one or more of these alternatives it may be possible to increase the representation of ecological systems in the protected areas network both quantitatively (from 10% up to 39%) and geographically and come closer to meeting the suggested Convention on Biological Diversity target of 17% for terrestrial areas. We used the Landscape Conservation Cooperative framework for regional analysis and found that increased conservation on some private and public lands may be important to the conservation of ecological systems in Western US, while increased public-private partnerships may be important in the conservation of ecological systems in Eastern US. We have not assessed the pros and cons of following the national or regional alternatives, but rather present them as possibilities that may be considered and evaluated as decisions are made to increase the representation of ecological systems in the protected areas network across their range of ecological, geographical, and geophysical occurrence in the continental US into the future.

PLoS ONE↗

Solar energy development selectively filters avian taxonomic and functional diversity across a perennial agricultural landscape

Solar energy is rapidly expanding across agricultural landscapes, yet its consequences for avian communities remain poorly understood, particularly among heterogeneous land-use matrices. In 2024 and 2025, we surveyed birds across 107 sites in New York State, including conventional solar arrays with mowing or sheep grazing to manage vegetation, solar-adjacent working lands (e.g. hayfields, pastures) and reference working lands independently located from solar arrays. We integrated diversity metrics across four trait dimensions—taxonomic, morphological, ecological and conservation status—and examined interactions between species-level abundance and traits to understand avian community responses to solar energy development. Avian species in solar sites tended to be common, non-migratory (in behaviour and wing morphology) and associated with shrubland or forest. Compared to reference working lands, bird communities in solar and solar-adjacent sites were less taxonomically diverse and were composed of fewer declining and range-restricted species. However, solar and solar-adjacent sites retained comparable diversity of intrinsic traits, suggesting that ecological function may persist despite apparent species filtering and functional reshuffling. While solar energy development can support avian communities with unique functional signatures, our findings suggest that conventional solar arrays sited on agricultural working lands in New York maintain low bird diversity and are unlikely to support conservation-priority species—such as grassland birds characterized by declining populations, migratory tendencies and open-habitat dependence. Synthesis and applications . Our study provides a pathway to leverage functional diversity to quantitatively characterize solar-associated avian communities and the ecological mechanisms that shape them. Our results suggest that meeting biodiversity conservation goals while achieving solar energy targets requires ecologically informed siting and processes, particularly across regions in which co-prioritization of conservation, agriculture and energy presents sustainability trade-offs.

New York↗

A comparative analysis of common methods to identify waterbird hotspots

1. Hotspot analysis is a commonly used method in ecology and conservation to identify areas of high biodiversity or conservation concern. However, delineating and mapping hotspots is subjective and various approaches can lead to different conclusions with regard to the classification of particular areas as hotspots, complicating long-term conservation planning and implementation efforts. 2. We present a comparative analysis of recent approaches for identifying waterbird hotspots, with the goal of developing insights about the appropriate use of these methods. We selected four commonly used measures to identify persistent areas of high use: kernel density estimation, Getis-Ord Gi*, hotspot persistence, and hotspots conditional on presence, which represent the range of quantitative hotspot estimation approaches used in waterbird analyses. We applied each of the methods to aerial survey waterbird count data collected in the Great Lakes from 2012-2014 using a 5 km2 grid. For each approach, we identified areas of high use for seven species/species groups and then compared the results across all methods. 3. Our results indicate that formal hotspot analysis frameworks do not always lead to the same conclusions. The kernel density and Getis-Ord Gi* methods yielded the most similar results across all species analyzed. We found that these two models can differ substantially from the hotspot persistence and hotspots conditional on presence estimation approaches, which were not consistently similar to one another. The hotspot persistence approach differed most significantly from the other methods but is the only method to explicitly account for temporal variation. 4. We recommend considering the ecological question and scale of any conservation or management activities prior to designing survey methodologies. Deciding the appropriate definition and scale for analysis is critical for interpretation of hotspot analysis results. Combining methods using an integrative approach, either within a single analysis or post-hoc, could lead to greater consistency in the identification of waterbird hotspots.

Lake Erie, Lake Huron, Lake Michigan↗

Study of biological communities subject to imperfect detection: Bias and precision of community N -mixture abundance models in small-sample situations

Community N -mixture abundance models for replicated counts provide a powerful and novel framework for drawing inferences related to species abundance within communities subject to imperfect detection. To assess the performance of these models, and to compare them to related community occupancy models in situations with marginal information, we used simulation to examine the effects of mean abundance ( &lambda; &macr; : 0.1, 0.5, 1, 5), detection probability ( p &macr; : 0.1, 0.2, 0.5), and number of sampling sites ( n site : 10, 20, 40) and visits ( n visit : 2, 3, 4) on the bias and precision of species-level parameters (mean abundance and covariate effect) and a community-level parameter (species richness). Bias and imprecision of estimates decreased when any of the four variables ( &lambda; &macr; , p &macr; , n site , n visit ) increased. Detection probability p &macr; was most important for the estimates of mean abundance, while &lambda; &macr; was most influential for covariate effect and species richness estimates. For all parameters, increasing n site was more beneficial than increasing n visit . Minimal conditions for obtaining adequate performance of community abundance models were n site &ge; 20, p&macr; &ge; 0.2, and &lambda; &macr; &ge; 0.5. At lower abundance, the performance of community abundance and community occupancy models as species richness estimators were comparable. We then used additive partitioning analysis to reveal that raw species counts can overestimate &beta; diversity both of species richness and the Shannon index, while community abundance models yielded better estimates. Community N -mixture abundance models thus have great potential for use with community ecology or conservation applications provided that replicated counts are available.

Ecological Research↗

Assessing conservation relevance of organism-environment relations using predicted changes in response variables

1. Organism–environment models are used widely in conservation. The degree to which they are useful for informing conservation decisions – the conservation relevance of these relations – is important because lack of relevance may lead to misapplication of scarce conservation resources or failure to resolve important conservation dilemmas. Even when models perform well based on model fit and predictive ability, conservation relevance of associations may not be clear without also knowing the magnitude and variability of predicted changes in response variables. 2. We introduce a method for evaluating the conservation relevance of organism–environment relations that employs confidence intervals for predicted changes in response variables. The confidence intervals are compared to a preselected magnitude of change that marks a threshold (trigger) for conservation action. To demonstrate the approach, we used a case study from the Chihuahuan Desert involving relations between avian richness and broad-scale patterns of shrubland. We considered relations for three winters and two spatial extents (1- and 2-km-radius areas) and compared predicted changes in richness to three thresholds (10%, 20% and 30% change). For each threshold, we examined 48 relations. 3. The method identified seven, four and zero conservation-relevant changes in mean richness for the 10%, 20% and 30% thresholds respectively. These changes were associated with major (20%) changes in shrubland cover, mean patch size, the coefficient of variation for patch size, or edge density but not with major changes in shrubland patch density. The relative rarity of conservation-relevant changes indicated that, overall, the relations had little practical value for informing conservation decisions about avian richness. 4. The approach we illustrate is appropriate for various response and predictor variables measured at any temporal or spatial scale. The method is broadly applicable across ecological environments, conservation objectives, types of statistical predictive models and levels of biological organization. By focusing on magnitudes of change that have practical significance, and by using the span of confidence intervals to incorporate uncertainty of predicted changes, the method can be used to help improve the effectiveness of conservation efforts.

Methods in Ecology and Evolution↗

Accounting for location uncertainty in azimuthaltelemetry data improves ecological inference

Background Characterizing animal space use is critical for understanding ecological relationships. Animal telemetry technology has revolutionized the fields of ecology and conservation biology by providing high quality spatial data on animal movement. Radio-telemetry with very high frequency (VHF) radio signals continues to be a useful technology because of its low cost, miniaturization, and low battery requirements. Despite a number of statistical developments synthetically integrating animal location estimation and uncertainty with spatial process models using satellite telemetry data, we are unaware of similar developments for azimuthal telemetry data. As such, there are few statistical options to handle these unique data and no synthetic framework for modeling animal location uncertainty and accounting for it in ecological models. We developed a hierarchical modeling framework to provide robust animal location estimates from one or more intersecting or non-intersecting azimuths. We used our azimuthal telemetry model (ATM) to account for azimuthal uncertainty with covariates and propagate location uncertainty into spatial ecological models. We evaluate the ATM with commonly used estimators (Lenth (1981) maximum likelihood and M-Estimators) using simulation. We also provide illustrative empirical examples, demonstrating the impact of ignoring location uncertainty within home range and resource selection analyses. We further use simulation to better understand the relationship among location uncertainty, spatial covariate autocorrelation, and resource selection inference. Results We found the ATM to have good performance in estimating locations and the only model that has appropriate measures of coverage. Ignoring animal location uncertainty when estimating resource selection or home ranges can have pernicious effects on ecological inference. Home range estimates can be overly confident and conservative when ignoring location uncertainty and resource selection coefficients can lead to incorrect inference and over confidence in the magnitude of selection. Furthermore, our simulation study clarified that incorporating location uncertainty helps reduce bias in resource selection coefficients across all levels of covariate spatial autocorrelation. Conclusion The ATM can accommodate one or more azimuths when estimating animal locations, regardless of how they intersect; this ensures that all data collected are used for ecological inference. Our findings and model development have important implications for interpreting historical analyses using this type of data and the future design of radio-telemetry studies.

Movement Ecology↗