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At least 37 records · Page 2Linked to original sources
USGS2016

DNA and dispersal models highlight constrained connectivity in a migratory marine megavertebrate

Population structure and spatial distribution are fundamentally important fields within ecology, evolution, and conservation biology. To investigate pan-Atlantic connectivity of globally endangered green turtles ( Chelonia mydas ) from two National Parks in Florida, USA, we applied a multidisciplinary approach comparing genetic analysis and ocean circulation modeling. The Everglades (EP) is a juvenile feeding ground, whereas the Dry Tortugas (DT) is used for courtship, breeding, and feeding by adults and juveniles. We sequenced two mitochondrial segments from 138 turtles sampled there from 2006-2015, and simulated oceanic transport to estimate their origins. Genetic and ocean connectivity data revealed northwestern Atlantic rookeries as the major natal sources, while southern and eastern Atlantic contributions were negligible. However, specific rookery estimates differed between genetic and ocean transport models. The combined analyses suggest that post-hatchling drift via ocean currents poorly explains the distribution of neritic juveniles and adults, but juvenile natal homing and population history likely play important roles. DT and EP were genetically similar to feeding grounds along the southern US coast, but highly differentiated from most other Atlantic groups. Despite expanded mitogenomic analysis and correspondingly increased ability to detect genetic variation, no significant differentiation between DT and EP, or among years, sexes or stages was observed. This first genetic analysis of a North Atlantic green turtle courtship area provides rare data supporting local movements and male philopatry. The study highlights the applications of multidisciplinary approaches for ecological research and conservation.

Florida↗
USGS2016

Biogeography of boreal passerine range dynamics in western North America: past, present, and future

Many of the Neotropical migrant bird species that breed throughout the Canadian boreal region are not found in the Alaskan boreal region, separated by the northwestern cordilleran mountains, despite the presence of climatically suitable habitat. We asked whether biological or climatic factors constrain certain species from crossing this geographic barrier. Analyzing a comprehensive dataset for 80 boreal passerine species, we used phylogenetic logistic regression to evaluate the relative importance of physical, migratory and competition metrics versus current and paleoclimatic suitability factors. Controlling for current climatic suitability within boreal Alaska, we found that species with the greatest climatic suitability across the northwestern cordillera, presently and also during the mid-Holocene period, were most likely to be regular breeders in the Alaskan boreal region. Migratory strategy also played a role, but could not be disentangled from its strong phylogenetic basis. Our analysis suggests that the perceived barrier of the northwestern cordillera may be easily weakened as climate change improves conditions there for many forest species. The weakening of this barrier may lead to relatively rapid range expansions and the reshuffling of species communities. Species’ realized distributional shifts will be a function of the interplay between a changing climate and static topographic features.

Ecography: Pattern and Diversity in Ecology↗
USGS2017

Estimating the per-capita contribution of habitats and pathways in a migratory network: A modelling approach

Every year, migratory species undertake seasonal movements along different pathways between discrete regions and habitats. The ability to assess the relative demographic contributions of these different habitats and pathways to the species’ overall population dynamics is critical for understanding the ecology of migratory species, and also has practical applications for management and conservation. Metrics for assessing habitat contributions have been well-developed for metapopulations, but an equivalent metric is not currently available for migratory populations. Here, we develop a framework for estimating the demographic contributions of the discrete habitats and pathways used by migratory species throughout the annual cycle by estimating the per capita contribution of cohorts using these locations. Our framework accounts for seasonal movements between multiple breeding and non-breeding habitats and for both resident and migratory cohorts. We illustrate our framework using a hypothetical migratory network of four habitats, which allows us to better understand how variations in habitat quality affect per capita contributions. Results indicate that per capita contributions for any habitat or pathway are dependent on habitat-specific survival probabilities in all other areas used as part of the migratory circuit, and that contribution metrics are spatially linked (e.g. reduced survival in one habitat also decreases the contribution metric for other habitats). Our framework expands existing theory on the dynamics of spatiotemporally structured populations by developing a generalized approach to estimate the habitat- and pathway-specific contributions of species migrating between multiple breeding and multiple non-breeding habitats for a range of life histories or migratory strategies. Most importantly, it provides a means of prioritizing conservation efforts towards those migratory pathways and habitats that are most critical for the population viability of migratory species.

Ecography↗
USGS2017

Local and cross-seasonal associations of climate and land use with abundance of monarch butterflies Danaus plexippus

Quantifying how climate and land use factors drive population dynamics at regional scales is complex because it depends on the extent of spatial and temporal synchrony among local populations, and the integration of population processes throughout a species’ annual cycle. We modeled weekly, site-specific summer abundance (1994–2013) of monarch butterflies Danaus plexippus at sites across Illinois, USA to assess relative associations of monarch abundance with climate and land use variables during the winter, spring, and summer stages of their annual cycle. We developed negative binomial regression models to estimate monarch abundance during recruitment in Illinois as a function of local climate, site-specific crop cover, and county-level herbicide (glyphosate) application. We also incorporated cross-seasonal covariates, including annual abundance of wintering monarchs in Mexico and climate conditions during spring migration and breeding in Texas, USA. We provide the first empirical evidence of a negative association between county-level glyphosate application and local abundance of adult monarchs, particularly in areas of concentrated agriculture. However, this association was only evident during the initial years of the adoption of herbicide-resistant crops (1994–2003). We also found that wetter and, to a lesser degree, cooler springs in Texas were associated with higher summer abundances in Illinois, as were relatively cool local summer temperatures in Illinois. Site-specific abundance of monarchs averaged approximately one fewer per site from 2004–2013 than during the previous decade, suggesting a recent decline in local abundance of monarch butterflies on their summer breeding grounds in Illinois. Our results demonstrate that seasonal climate and land use are associated with trends in adult monarch abundance, and our approach highlights the value of considering fine-resolution temporal fluctuations in population-level responses to environmental conditions when inferring the dynamics of migratory species.

Illinois↗
USGS2016

Competitive exclusion over broad spatial extents is a slow process: Evidence and implications for species distribution modeling

There is considerable debate about the role of competition in shaping species distributions over broad spatial extents. This debate has practical implications because predicting changes in species' geographic ranges in response to ongoing environmental change would be simpler if competition could be ignored. While this debate has been the subject of many reviews, recent literature has not addressed the rates of relevant processes. This omission is surprising in that ecologists hypothesized decades ago that regional competitive exclusion is a slow process. The goal of this review is to reassess the debate under the hypothesis that competitive exclusion over broad spatial extents is a slow process. Available evidence, including simulations presented for the first time here, suggests that competitive exclusion over broad spatial extents occurs slowly over temporal extents of many decades to millennia. Ecologists arguing against an important role for competition frequently study modern patterns and/or range dynamics over periods of decades, while much of the evidence for competition shaping geographic ranges at broad spatial extents comes from paleoecological studies over time scales of centuries or longer. If competition is slow, as evidence suggests, the geographic distributions of some, perhaps many species, would continue to change over time scales of decades to millennia, even if environmental conditions did not continue to change. If the distributions of competing species are at equilibrium it is possible to predict species distributions based on observed species–environment relationships. However, disequilibrium is widespread as a result of competition and many other processes. Studies whose goal is accurate predictions over intermediate time scales (decades to centuries) should focus on factors associated with range expansion (colonization) and loss (local extinction), as opposed to current patterns. In general, understanding of modern range dynamics would be enhanced by considering the rates of relevant processes.

Ecography↗
USGS2017

Spatial ecology and movement of reintroduced Canada lynx

Understanding movement behavior and identifying areas of landscape connectivity is critical for the conservation of many species. However, collecting fine‐scale movement data can be prohibitively time consuming and costly, especially for rare or endangered species, whereas existing data sets may provide the best available information on animal movement. Contemporary movement models may not be an option for modeling existing data due to low temporal resolution and large or unusual error structures, but inference can still be obtained using a functional movement modeling approach. We use a functional movement model to perform a population‐level analysis of telemetry data collected during the reintroduction of Canada lynx to Colorado. Little is known about southern lynx populations compared to those in Canada and Alaska, and inference is often limited to a few individuals due to their low densities. Our analysis of a population of Canada lynx fills significant gaps in the knowledge of Canada lynx behavior at the southern edge of its historical range. We analyzed functions of individual‐level movement paths, such as speed, residence time, and tortuosity, and identified a region of connectivity that extended north from the San Juan Mountains, along the continental divide, and terminated in Wyoming at the northern edge of the Southern Rocky Mountains. Individuals were able to traverse large distances across non‐boreal habitat, including exploratory movements to the Greater Yellowstone area and beyond. We found evidence for an effect of seasonality and breeding status on many of the movement quantities and documented a potential reintroduction effect. Our findings provide the first analysis of Canada lynx movement in Colorado and substantially augment the information available for conservation and management decisions. The functional movement framework can be extended to other species and demonstrates that information on movement behavior can be obtained using existing data sets.

Wyoming↗
USGS2017

Used-habitat calibration plots: A new procedure for validating species distribution, resource selection, and step-selection models

“Species distribution modeling” was recently ranked as one of the top five “research fronts” in ecology and the environmental sciences by ISI's Essential Science Indicators (Renner and Warton 2013), reflecting the importance of predicting how species distributions will respond to anthropogenic change. Unfortunately, species distribution models (SDMs) often perform poorly when applied to novel environments. Compounding on this problem is the shortage of methods for evaluating SDMs (hence, we may be getting our predictions wrong and not even know it). Traditional methods for validating SDMs quantify a model's ability to classify locations as used or unused. Instead, we propose to focus on how well SDMs can predict the characteristics of used locations. This subtle shift in viewpoint leads to a more natural and informative evaluation and validation of models across the entire spectrum of SDMs. Through a series of examples, we show how simple graphical methods can help with three fundamental challenges of habitat modeling: identifying missing covariates, non-linearity, and multicollinearity. Identifying habitat characteristics that are not well-predicted by the model can provide insights into variables affecting the distribution of species, suggest appropriate model modifications, and ultimately improve the reliability and generality of conservation and management recommendations.

Ecography↗
USGS2017

Unifying population and landscape ecology with spatial capture-recapture

Spatial heterogeneity in the environment induces variation in population demographic rates and dispersal patterns, which result in spatio‐temporal variation in density and gene flow. Unfortunately, applying theory to learn about the role of spatial structure on populations has been hindered by the lack of mechanistic spatial models and inability to make precise observations of population state and structure. Spatial capture–recapture (SCR) represents an individual‐based analytic framework for overcoming this fundamental obstacle that has limited the utility of ecological theory. SCR methods make explicit use of spatial encounter information on individuals in order to model density and other spatial aspects of animal population structure, and they have been widely adopted in the last decade. We review the historical context and emerging developments in SCR models that enable the integration of explicit ecological hypotheses about landscape connectivity, movement, resource selection, and spatial variation in density, directly with individual encounter history data obtained by new technologies (e.g. camera trapping, non‐invasive DNA sampling). We describe ways in which SCR methods stand to advance the study of animal population ecology.

Ecography↗
USGS2018

Phylogeny and species traits predict bird detectability

Avian acoustic communication has resulted from evolutionary pressures and ecological constraints. We therefore expect that auditory detectability in birds might be predictable by species traits and phylogenetic relatedness. We evaluated the relationship between phylogeny, species traits, and field‐based estimates of the two processes that determine species detectability (singing rate and detection distance) for 141 bird species breeding in boreal North America. We used phylogenetic mixed models and cross‐validation to compare the relative merits of using trait data only, phylogeny only, or the combination of both to predict detectability. We found a strong phylogenetic signal in both singing rates and detection distances; however the strength of phylogenetic effects was less than expected under Brownian motion evolution. The evolution of behavioural traits that determine singing rates was found to be more labile, leaving more room for species to evolve independently, whereas detection distance was mostly determined by anatomy (i.e. body size) and thus the laws of physics. Our findings can help in disentangling how complex ecological and evolutionary mechanisms have shaped different aspects of detectability in boreal birds. Such information can greatly inform single‐ and multi‐species models but more work is required to better understand how to best correct possible biases in phylogenetic diversity and other community metrics.

Ecography↗
USGS2018

Using spatially‐explicit capture–recapture models to explain variation in seasonal density patterns of sympatric ursids

Understanding how environmental factors interact to determine the abundance and distribution of animals is a primary goal of ecology, and fundamental to the conservation of wildlife populations. Studies of these relationships, however, often assume static environmental conditions, and rarely consider effects of competition with ecologically similar species. In many parts of their shared ranges, grizzly bears Ursus arctos and American black bears U. americanus have nearly complete dietary overlap and share similar life history traits. We therefore tested the hypothesis that density patterns of both bear species would reflect seasonal variation in available resources, with areas of higher primary productivity supporting higher densities of both species. We also hypothesized that interspecific competition would influence seasonal density patterns. Specifically, we predicted that grizzly bear density would be locally reduced due to the ability of black bears to more efficiently exploit patchy food resources such as seasonally abundant fruits. To test our hypotheses, we used detections of 309 grizzly and 597 black bears from two independent genetic sampling methods in spatially‐explicit capture–recapture (SECR) models. Our results suggest grizzly bear density was lower in areas of high black bear density during spring and summer, although intraspecific densities were also important, particularly during the breeding season. Black bears had lower densities in areas of high grizzly bear density in spring; however, density of black bears in early and late summer was best explained by primary productivity. Our results are consistent with the hypothesis that smaller‐bodied, more abundant black bears may influence the density patterns of behaviorally‐dominant grizzly bears through exploitative competition. We also suggest that seasonal variation in resource availability be considered in efforts to relate environmental conditions to animal density.

Montana↗
USGS2018

Gaps in kelp cover may threaten the recovery of California sea otters

Despite more than a century of federal protection, the California sea otter Enhydra lutris nereis remains threatened under the U.S. Endangered Species Act (ESA), and the population has not appreciably expanded its range in two decades. Here, we examine a novel dataset of 725 sea otter live strandings from 1984–2015 to gain insights into demographic and environmental factors underlying threats to sea otter recovery. Using multinomial logistic regression to evaluate spatiotemporal patterns of stranding causes, we demonstrate that increases in stranding rates, particularly outside the range center, are related to a substantial increase in shark bites. By contrast, trauma linked to human activities has declined dramatically, and now accounts for less than 5% of stranding cases. Within the range core, where the sea otter population seems regulated by prey availability, symptoms of energetic stress represent more than 63% of all strandings and are strongly associated with high sea otter density. Conversely, in range peripheries, the majority of strandings are caused by shark bite and neurological disease. Notably, these threats are virtually absent where nearshore habitat is characterized by at least 10% kelp canopy cover. Our analyses reveal that declining kelp cover may therefore constrain the population's spatial expansion and recovery in two key ways. Absence of kelp intensifies density‐independent threats in the range peripheries, and likely limits dispersal of reproductive females, which depend on kelp canopy for nursery habitat. These results highlight the significance of both top‐down and bottom‐up processes in population dynamics, and inform an ecosystem‐based approach to conservation planning.

California↗
USGS2019

Perspectives and challenges for the use of radar in biological conservation

Radar is at the forefront for the study of broad‐scale aerial movements of birds, bats and insects and related issues in biological conservation. Radar techniques are especially useful for investigating species which fly at high altitudes, in darkness, or which are too small for applying electronic tags. Here, we present an overview of radar applications in biological conservation and highlight its future possibilities. Depending on the type of radar, information can be gathered on local‐ to continental‐scale movements of airborne organisms and their behaviour. Such data can quantify flyway usage, biomass and nutrient transport (bioflow), population sizes, dynamics and distributions, times and dimensions of movements, areas and times of mass emergence and swarming, habitat use and activity ranges. Radar also captures behavioural responses to anthropogenic disturbances, artificial light and man‐made structures. Weather surveillance and other long‐range radar networks allow spatially broad overviews of important stopover areas, songbird mass roosts and emergences from bat caves. Mobile radars, including repurposed marine radars and commercially dedicated ‘bird radars’, offer the ability to track and monitor the local movements of individuals or groups of flying animals. Harmonic radar techniques have been used for tracking short‐range movements of insects and other small animals of conservation interest. However, a major challenge in aeroecology is determining the taxonomic identity of the targets, which often requires ancillary data obtained from other methods. Radar data have become a global source of information on ecosystem structure, composition, services and function and will play an increasing role in the monitoring and conservation of flying animals and threatened habitats worldwide.

Ecography↗
USGS2018

Consequences of ignoring spatial variation in population trend when conducting a power analysis

Long-term, large-scale monitoring programs are becoming increasingly common to document status and trends of wild populations. A successful program for monitoring population trend hinges on the ability to detect the trend of interest. Power analyses are useful for quantifying the sample size needed for trend detection, given expected variation in the population. Four components of variation (within-year variation at a given site, interannual variation within a site, variation among sites in the interannual variation, and variation among sites in mean abundance or density) are commonly considered in power analyses for population trend, but a fifth is not: variation among sites in the local trend. Spatial variation in trend is expected to reduce statistical power, but the magnitude of this reduction has not been fully explored. We used computer simulations to evaluate the consequences of ignoring spatial variation in trend under a variety of sampling designs and wide ranges of other components of variation. The effect of spatial variation in trend on power was minor when other input parameters took extreme values that made the trend either very difficult or very easy to detect. However, at moderate values of the other parameters, spatial variation in trend had a strong effect, reducing statistical power by up to 60%. In some cases, ignoring spatial variation in trend resulted in an 80% probability of a Type I error (falsely detecting a trend in a stable population). Spatial variation in trend is therefore an important consideration when designing a long-term monitoring program for many species, especially those affected by local conditions at sites that are repeatedly surveyed. If variation in trend is ignored, as in most previous power analyses, the recommended sampling design will likely be insufficient to detect the trend of interest and lead to potentially false conclusions of a stable population.

Ecography↗
USGS2019

Integrated modeling reveals shifts in waterfowl population dynamics under climate change

1. Climate change has been identified as one of the most important drivers of wildlife populations. The development of appropriate conservation strategies relies on reliable predictions of population responses to climate change, which require in-depth understanding of the complex relationships between climate and population dynamics through density dependent demographic processes. Integrated population models (IPMs) are a type of modeling approach that unify the analyses of demography and abundance data, providing opportunities to understand and predict population demography and dynamics under climate change. 2. In this study we developed dynamic N-mixture models for large scale population estimates, which became an important component of the IPM we used in data analysis. We then analyzed four decades (1974-2014) of Mallard ( Anas platyrhynchos ) breeding population survey, band-recovery, and climate data covering a large spatial extent from North American prairies through boreal habitat to Alaska. Our goals were to examine the complex relationships among climate, density dependent processes, waterfowl population demography and dynamics, identify the key demographic parameters that are sensitive to climate change and are influential to population growth, and forecast population responses to climate change. 3. Our results revealed the interactive effects of temperature and density dependent processes on Mallard recruitment and to a less extent apparent survival. We also found that recruitment explained more variance of population growth than apparent survival. We then forecasted a decrease in Mallard breeding population density in the Northern Prairie Potholes and an increase in Mallard breeding population density in the northern part of our study area, indicating potential shifts in Mallard population dynamics under future climate change. 4. Synthesis and applications Different strategies need to be considered across regions to conserve waterfowl populations under climate change. Strategies that facilitate recruitment are essential for high-density populations that are relatively vulnerable to climate change. By contrast, low-density populations are relatively resilient to climate change and their habitats may serve as future climate refugia. Adaptive management is essential for evaluating management consequences. Our modelling framework approach can be easily adapted for other species and thus has wide applications in ecology and conservation.

Ecography↗
USGS2019

oSCR: A spatial capture–recapture R package for inference about spatial ecological processes

Spatial capture–recapture (SCR) methods have become widely applied in ecology. The immediate adoption of SCR is due to the fact that it resolves some major criticisms of traditional capture–recapture methods related to heterogeneity in detectabililty, and the emergence of new technologies (e.g. camera traps, non‐invasive genetics) that have vastly improved our ability to collection spatially explicit observation data on individuals. However, the utility of SCR methods reaches far beyond simply convenience and data availability. SCR presents a formal statistical framework that can be used to test explicit hypotheses about core elements of population and landscape ecology, and has profound implications for how we study animal populations. In this software note, we describe the technical basis and analytical workflow of oSCR, an R package for analyzing spatial encounter history data using a multi‐session sex‐structured likelihood. The impetus for developing oSCR was to create an accessible and transparent analysis tool that allows users to conveniently and intuitively formulate statistical models that map directly to fundamental processes of interest in spatial population ecology (e.g. space use, resource selection, density and connectivity). We have placed an emphasis on creating a transparent and accessible code base that is coupled with a logical workflow that we hope stimulates active participation in further technical developments.

Ecography↗
USGS2020

The historical context of contemporary climatic adaptation: A case study in the climatically dynamic and environmentally complex southwestern United States

The process of adaptation can be highly dependent upon historical and contemporary factors, especially in environmentally and topographically complex regions affected by Pleistocene glaciations. Here, we investigate Hilaria jamesii (Poaceae), a dryland C 4 graminoid, to test how patterns of adaptive genetic variation are linked to its glacial and post‐glacial history. We show that the species persisted in a single, southern refugium during the last glacial period and subsequently migrated throughout its current distribution concurrent with post‐glacial warming. The species’ putative adaptive genetic variation correlates with climatic gradients (e.g. monsoon precipitation and mean diurnal temperature range) that covary with the species’ probable route of demographic expansion. The short timescale and multiple climatic dimensions of adaptation imply that natural selection acted primarily upon standing genetic variation. These findings suggest that restoration and conservation practices should prioritize the maintenance of standing genetic variation to ensure that species have the capacity to respond to future environmental changes.

Arizona, California Colorado, Nevada, New Mexico, ↗
USGS2019

Aridity drives spatiotemporal patterns of masting across the latitudinal range of a dryland conifer

Masting, or the synchronous and irregular production of seed crops, is controlled by environmental conditions and resource budgets. Increasing temperatures and shifting precipitation regimes may alter the frequency and magnitude of masting, especially in species that experience chronic resource stress. Yet the effects of a changing climate on seed production are unlikely to be uniform across populations, particularly those that span broad abiotic gradients. In this study, we assessed the spatiotemporal patterns of masting across the latitudinal distribution of a widely distributed dryland conifer species, piñon pine Pinus edulis . We quantified seed cone production from 2004 to 2017 using cone abscission scars in 187 trees from 28 sites along an 1100 km latitudinal gradient to investigate the spatiotemporal drivers of seed cone production and synchrony across populations. Populations from chronically hot and dry areas (greater climatic water deficits and less monsoonal precipitation) tended to have greater interannual variability in seed cone production and smaller crop sizes. Mast years generally followed years with low vapor pressure deficits and high precipitation during key periods of the reproductive process, but the strength of these relationships varied across the region. Populations that received greater monsoonal precipitation were less sensitive to late summer vapor pressure deficits during seed cone initiation yet more sensitive to spring vapor pressure deficits during pollination. Spatially correlated patterns of vapor pressure deficit better predicted synchrony in seed cone production than geographic distance, and these patterns were conserved at distances up to 500 km. These results demonstrate that aridity drives spatiotemporal variability in seed cone production. As a result, projected increases in aridity are likely to decrease the frequency and magnitude of masting in these dry forests and woodlands. Declines in seed production may compound climatic limitations to recruitment and impede tree regeneration, with cascading effects for numerous wildlife species.

Ecography↗