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At least 73 records · Page 4Linked to original sources

An integrated framework for ecological drought across riverscapes of North America

Climate change is increasing the severity and extent of extreme droughts events, posing a critical threat to freshwater ecosystems, particularly with increasing human demands for diminishing water supplies. Despite the importance of drought as a significant driver of ecological and evolutionary dynamics, current understanding of drought consequences for freshwater biodiversity is very limited. We describe key barriers that hinder integrative drought research and monitoring across riverscapes. The primary constraint limiting understanding of ecological drought is an existing monitoring framework focused on human water consumption and flood risk in mainstem rivers. This approach is misaligned with escalating needs for research and data collection that illuminate exposure, sensitivity, and adaptive capacity (i.e., vulnerability) of biota to drought across entire riverscapes. We present a hierarchical framework for integrated ecological drought monitoring and research that addresses drought vulnerability across riverscapes, and describe how this approach can directly inform natural-resource management.

BioScience

Macroecological patterns of sexual size dimorphism in turtles of the world

Sexual size dimorphism (SSD) is a well-documented phenomenon in both plants and animals; however, the ecological and evolutionary mechanisms that drive and maintain SSD patterns across geographic space at regional and global scales are understudied, especially for reptiles. Our goal was to examine geographic variation of turtle SSD and to explore ecological and environmental correlates using phylogenetic comparative methods. We use published body size data on 135 species from nine turtle families to examine how geographic patterns and the evolution of SSD are influenced by habitat specialization, climate (annual mean temperature and annual precipitation) and climate variability, latitude, or a combination of these predictor variables. We found that geographic variation, magnitude and direction of turtle SSD are best explained by habitat association, annual temperature variance and annual precipitation. Use of semi-aquatic and terrestrial habitats was associated with male-biased SSD, whereas use of aquatic habitat was associated with female-biased SSD. Our results also suggest that greater temperature variability is associated with female-biased SSD. In contrast, wetter climates are associated with male-biased SSD compared with arid climates that are associated with female-biased SSD. We also show support for a global latitudinal trend in SSD, with females being larger than males towards the poles, especially in the families Emydidae and Geoemydidae. Estimates of phylogenetic signal for both SSD and habitat type indicate that closely related species occupy similar habitats and exhibit similar direction and magnitude of SSD. These global patterns of SSD may arise from sex-specific reproductive behaviour, fecundity and sex-specific responses to environmental factors that differ among habitats and vary systematically across latitude. Thus, this study adds to our current understanding that while SSD can vary dramatically across and within turtle species under phylogenetic constraints, it may be driven, maintained and exaggerated by habitat type, climate and geographic location.

Journal of Evolutionary Biology

Bringing traits back in the equation: A roadmap to understand species redistribution

Ecological and evolutionary theories have proposed that species traits should be important in mediating species responses to contemporary climate change; yet, empirical evidence has so far provided mixed evidence for the role of behavioral, life history, or ecological characteristics in facilitating or hindering species range shifts. As such, the utility of trait-based approaches to predict species redistribution under climate change has been called into question. We develop the perspective, supported by evidence, that trait variation, if used carefully can have high potential utility, but that past analyses have in many cases failed to identify an explanatory value for traits by not fully embracing the complexity of species range shifts. First, we discuss the relevant theory linking species traits to range shift processes at the leading (expansion) and trailing (contraction) edges of species distributions and highlight the need to clarify the mechanistic basis of trait-based approaches. Second, we provide a brief overview of range shift–trait studies and identify new opportunities for trait integration that consider range-specific processes and intraspecific variability. Third, we explore the circumstances under which environmental and biotic context dependencies are likely to affect our ability to identify the contribution of species traits to range shift processes. Finally, we propose that revealing the role of traits in shaping species redistribution may likely require accounting for methodological variation arising from the range shift estimation process as well as addressing existing functional, geographical, and phylogenetic biases. We provide a series of considerations for more effectively integrating traits as well as extrinsic and methodological factors into species redistribution research. Together, these analytical approaches promise stronger mechanistic and predictive understanding that can help society mitigate and adapt to the effects of climate change on biodiversity.

Global Change Biology

Multiple hypotheses testing of fish incidence patterns in an urbanized ecosystem

Ecological and evolutionary theories have focused traditionally on natural processes with little attempt to incorporate anthropogenic influences despite the fact that humans are such an integral part of virtually all ecosystems. A series of alternate models that incorporated anthropogenic factors and traditional ecological mechanisms of invasion to account for fish incidence patterns in urban lakes was tested. The models were based on fish biology, human intervention, and habitat characteristics. However, the only models to account for empirical patterns were those that included fish invasiveness, which incorporated species-specific information about overall tolerance and fecundity. This suggests that species-specific characteristics are more important in general distributional patterns than human-mediated dispersal. Better information of illegal stocking activities is needed to improve human-mediated models, and more insight into basic life history of ubiquitous species is needed to truly understand underlying mechanisms of biotic homogenization. ?? Springer 2005.

Aquatic Ecology

Using stable isotopes to investigate individual diet specialization in California sea otters (Enhydra lutris nereis)

Differences in diet composition among conspecifics (dietary specialization) have been documented across a broad range of taxonomic groups and habitats, and such variation at the individual level is increasingly recognized as an important component of diversity in trophic interactions. Accurate identification of individual dietary specialization, however, requires longitudinal dietary records that are labor-intensive and cost-prohibitive to obtain for many species. Here we explore the use of stable isotopes (δ 13 C and δ 15 N) as a promising technique for detecting and quantifying patterns of individual dietary specialization. Southern sea otters ( Enhydra lutris nereis ) offer a unique opportunity for testing this approach because (1) they consume a wide variety of prey that span multiple trophic levels, habitats, and ecologically defined functional groups; and (2) individual diet specialization can be validated with existing observational data. We analyzed the isotopic composition of sea otter vibrissae ( n = 31) in order to characterize inter- and intra-individual variation in sea otter diets at Monterey Bay, California, USA. At the population level, sea otters showed substantial variation in both δ 13 C and δ 15 N values, occupying nearly all of the “isotopic space” created by the diversity of isotopic signatures of potential prey taxa. Most of the variation in sea otter vibrissae was accounted for by differences between individuals, with much less contributed by within-individual variation. A majority of sea otters (∼80%) showed relatively little temporal variability in isotopic composition, suggesting that the proportional composition of most individuals' diets is relatively constant over time; a few individuals (∼20%) exhibited a high degree of intra-vibrissa isotopic variability, suggesting seasonal shifts in diet composition. These results and our interpretation of them were supported by long-term observational data on the diets of radio-tagged sea otters from the same population ( n = 23). Our results demonstrate that stable isotopes can provide an efficient tool for measuring individual- and population-level dietary breadth and may be useful for studying populations where longitudinal data on individuals would otherwise be impossible to acquire. This will be critical for examining the causes and consequences of dietary variation within and among consumer populations, thereby improving our understanding of these important ecological and evolutionary processes at the community level.

Ecology

Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations

Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R 2 values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.

Ecology and Evolution

Isolation and characterization of novel waterfowl microsatellite loci: Cross-species comparisons and research applications

Waterfowl constitute an ecologically diverse group which are the subject of extensive research (e.g. see reviews in Batt et al . 1992), and are intensively managed (Nichols et al .1995). Genetic studies utilizing allozyme electrophoresis and mitochondrial (mt)DNA have provided valuable information on waterfowl ecology and evolutionary history (Cooke & Buckley 1987). However, highly variable molecular genetic markers (e.g. multilocus minisatellites; Triggs et al. 1992) have not generally been identified for this group.

Molecular Ecology

Tick-, mosquito-, and rodent-borne parasite sampling designs for the National Ecological Observatory Network

Parasites and pathogens are increasingly recognized as significant drivers of ecological and evolutionary change in natural ecosystems. Concurrently, transmission of infectious agents among human, livestock, and wildlife populations represents a growing threat to veterinary and human health. In light of these trends and the scarcity of long-term time series data on infection rates among vectors and reservoirs, the National Ecological Observatory Network (NEON) will collect measurements and samples of a suite of tick-, mosquito-, and rodent-borne parasites through a continental-scale surveillance program. Here, we describe the sampling designs for these efforts, highlighting sampling priorities, field and analytical methods, and the data as well as archived samples to be made available to the research community. Insights generated by this sampling will advance current understanding of and ability to predict changes in infection and disease dynamics in novel, interdisciplinary, and collaborative ways.

Ecosphere

Spatially explicit management of genetic diversity using ancestry probability surfaces

1. Ecological restoration and conservation efforts are increasing worldwide and the management of intraspecific genetic variation in plants and animals, an important component of biodiversity, is increasingly valued. As a result, tailorable, spatially explicit approaches to map genetic variation are needed to support decision-making and management frameworks related to the recovery of threatened and endangered species and the maintenance of genetic resources in species utilized by humans, such as for restoration or agricultural purposes. 2. Here, we describe and demonstrate a workflow to spatially interpolate patterns of genetic differentiation using novel functions in the R package POPMAPS ( Pop ulation M anagement using A ncestry P robability S urfaces). Our approach uses empirical genetic data to estimate ancestry coefficients across a user-defined landscape correlated with patterns of differentiation in the focal species. The resulting surface, which we term the ancestry probability surface, includes two components: hard population boundaries and estimations of uncertainty that represent confidence in population assignments (i.e., ancestry probabilities). 3. An ancestry probability surface developed for Hilaria jamesii , an important graminoid utilized in restoration across the western United States, demonstrates the functionality of POPMAPS . Genetic distances among empirical sites correlated better with least-cost distances across suitable habitat than with geographic distances, informing the surface over which the interpolation was conducted (i.e., a model indicating habitat suitability). A jackknifing procedure identified parameter values resulting in robust population assignments across the species’ range, which were utilized in downstream analyses to estimate ancestry coefficients from empirical data. Ancestry coefficients were translated into ancestry probabilities, which tended to be low for cells that were intermediate in distance between empirical sampling locations representing different populations or when influenced by empirical sampling locations with mixed genetic ancestry. 4. POPMAPS allows users to tailor parameter values and analytical approaches and thereby incorporate species-specific biological characteristics and desired levels of uncertainty into maps illustrating patterns of genetic differentiation. Ancestry probability surfaces may be used to guide management or investigate further ecological or evolutionary hypotheses. We discuss how maps produced by POPMAPS can inform multiple management challenges including species recovery planning and the utilization of commonly used species in restoration.

Methods in Ecology and Evolution

The bee microbiome: Impact on bee health and model for evolution and ecology of host-microbe interactions

As pollinators, bees are cornerstones for terrestrial ecosystem stability and key components in agricultural productivity. All animals, including bees, are associated with a diverse community of microbes, commonly referred to as the microbiome. The bee microbiome is likely to be a crucial factor affecting host health. However, with the exception of a few pathogens, the impacts of most members of the bee microbiome on host health are poorly understood. Further, the evolutionary and ecological forces that shape and change the microbiome are unclear. Here, we discuss recent progress in our understanding of the bee microbiome, and we present challenges associated with its investigation. We conclude that global coordination of research efforts is needed to fully understand the complex and highly dynamic nature of the interplay between the bee microbiome, its host, and the environment. High-throughput sequencing technologies are ideal for exploring complex biological systems, including host-microbe interactions. To maximize their value and to improve assessment of the factors affecting bee health, sequence data should be archived, curated, and analyzed in ways that promote the synthesis of different studies. To this end, the BeeBiome consortium aims to develop an online database which would provide reference sequences, archive metadata, and host analytical resources. The goal would be to support applied and fundamental research on bees and their associated microbes and to provide a collaborative framework for sharing primary data from different research programs, thus furthering our understanding of the bee microbiome and its impact on pollinator health.

mBio

Population ecology of Roosevelt elk: Conservation and management in Redwood National and State Parks. Butch Weckerly. 2017. University of Nevada Press, Reno, Nevada, USA. 224 pp. $54.95 hardback. ISBN 978- 1943859504.

Long-term research on large ungulate populations typically conjures perceptions of extensive (and expensive) animal capture and telemetry work, and subsequent advanced modeling of resource selection and population dynamics that inform management decisions. In contrast, studies lacking a telemetry component are often limited to animal behavior or natural history. Although compelling from a standpoint of advancing understanding of ecological and evolutionary processes, results from the latter can be unfairly labeled as esoteric because they are not easily transferable to resource managers or may not provide exceptional interest to a general public drawn to these charismatic megafuana. Such dichotomies are not predetermined, however, because study conditions exist where dedicated academic researchers on tight budgets can achieve results relevant to ecology and management.

Journal of Wildlife Management

Marine latitudinal diversity gradients, niche conservatism and out of the tropics and Arctic: Climatic sensitivity of small organisms

Aim The latitudinal diversity gradient (LDG) is a consequence of evolutionary and ecological mechanisms acting over long history, and thus is best investigated with organisms that have rich fossil records. However, combined neontological‐palaeontological investigations are mostly limited to large, shelled invertebrates, which keeps our mechanistic understanding of LDGs in its infancy. This paper aims to describe the modern meiobenthic ostracod LDG and to explore the possible controlling factors and the evolutionary mechanisms of this large‐scale biodiversity pattern. Location Present‐day Western North Atlantic. Taxon Ostracoda. Methods We compiled ostracod census data from shallow‐marine environments of the western North Atlantic Ocean. Using these data, we documented the marine LDG with multiple metrics of alpha, beta (nestedness and turnover) and gamma diversity, and we tested whether macroecological patterns could be governed by different environmental factors, including temperature, salinity, dissolved oxygen, pH and primary productivity. We also explored the geologic age distribution of ostracod genera to investigate the evolutionary mechanisms underpinning the LDG. Results Our results show that temperature and climatic niche conservatism are important in setting LDGs of these small, poorly dispersing organisms. We also found evidence for some dispersal‐driven spatial dynamics in the ostracod LDG. Compared to patterns observed in marine bivalves, however, dispersal dynamics were weaker and they were bi‐directional, rather than following the ‘out‐of‐the‐tropics’ model. Main conclusions Our detailed analyses revealed that meiobenthic organisms, which comprise two‐thirds of marine diversity, do not always follow the same rules as larger, better‐studied organisms. Our findings suggest that the understudied majority of biodiversity may be more sensitive to climate than well‐studied, large organisms. This implies that the impacts of ongoing Anthropocene climatic change on marine ecosystems may be much more serious than presently thought.

Journal of Biogeography

A multiscale natural community and species-level vulnerability assessment of the Gulf Coast, USA

Vulnerability assessments combine quantitative and qualitative evaluations of the exposure, sensitivity, and adaptive capacity of species or natural communities to current and future threats. When combined with the economic, ecological or evolutionary value of the species, vulnerability assessments quantify the relative risk to regional species and natural communities and can enable informed prioritization of conservation efforts. Vulnerability assessments are common practice in conservation biology, including the potential impacts of future climate scenarios. However, geographic variation in scenarios and vulnerabilities is rarely quantified. This gap is particularly limiting for informing ecosystem management given that conservation practices typically vary by sociopolitical boundaries rather than by ecological boundaries. To support prioritization of conservation actions across a range of spatial scales, we conducted the Gulf Coast Vulnerability Assessment (GCVA) for four natural communities and eleven focal species around the Gulf of Mexico based on current and future threats from climate change and land-use practices out to 2060. We used the Standardized Index of Vulnerability and Value (SIVVA) tool to assess both natural community and species vulnerabilities. We observed greater variation across ecologically delineated subregions within the Gulf Coast of the U.S. than across climate scenarios. This novel finding suggests that future vulnerability assessments incorporate regional variation and that conservation prioritization may vary across ecological subregions. Across subregions and climate scenarios the most prominent threats were legacy effects, primarily from habitat loss and degradation, that compromised the adaptive capacity of species and natural communities. The second most important threats were future threats from sea-level rise. Our results suggest that the substantial threats species and natural communities face from climate change and sea-level rise would be within their adaptive capacity were it not for historic habitat loss, fragmentation, and degradation.

Alabama, Florida, Georgia, Louisiana, Mississippi,

The expectations and challenges of wildlife disease research in the era of genomics: Forecasting with a horizon scan-like exercise

The outbreak and transmission of disease-causing pathogens are contributing to the unprecedented rate of biodiversity decline. Recent advances in genomics have coalesced into powerful tools to monitor, detect, and reconstruct the role of pathogens impacting wildlife populations. Wildlife researchers are thus uniquely positioned to merge ecological and evolutionary studies with genomic technologies to exploit unprecedented ‘Big Data’ tools in disease research; however, many researchers lack the training and expertise required to use these computationally intensive methodologies. To address this disparity, the inaugural ‘Genomics of Disease in Wildlife’ workshop assembled early to mid-career professionals with expertise across scientific disciplines (e.g., genomics, wildlife biology, veterinary sciences, and conservation management) for training in the application of genomic tools to wildlife disease research. A horizon scanning-like exercise, an activity to identify forthcoming trends and challenges, performed by the workshop participants identified and discussed five themes considered to be the most pressing to the application of genomics in wildlife disease research: i) “Improving Communication”, ii) “Methodological and Analytical Advancements”, iii) “Translation into Practice”, iv) “Integrating Landscape Ecology and Genomics”, and v) “Emerging New Questions”. Wide-ranging solutions from the horizon scan were international in scope, itemized both deficiencies and strengths in wildlife genomic initiatives, promoted the use of genomic technologies to unite wildlife and human disease research, and advocated best practices for optimal use of genomic tools in wildlife disease projects. The results offer a glimpse of the potential revolution in human and wildlife disease research possible through multi-disciplinary collaborations at local, regional, and global scales.

Journal of Heredity

The airspace is habitat

A preconception concerning habitat persists and has gone unrecognized since use of the term first entered the lexicon of ecological and evolutionary biology many decades ago. Specifically, land and water are considered habitats, while the airspace is not. This might at first seem a reasonable, if unintended, demarcation, since years of education and personal experience as well as limits to perception predispose a traditional view of habitat. Nevertheless, the airspace satisfies the definition and functional role of a habitat, and its recognition as habitat may have implications for policy where expanding anthropogenic development of airspace could impact the conservation of species and subject parts of the airspace to formalized legal protection.

Trends in Ecology and Evolution

Development of high-throughput genomic resources to inform white-tailed deer population and disease management

White-tailed deer ( Odocoileus virginianus ) are the most abundant and widespread cervid in North America. Genetic data are used as a tool to monitor populations and make management decisions for this game species. However, the development and use of genomic tools that can generate a set of markers suitable for longitudinal genomic data collection, whether for management purposes or to study the demographic and evolutionary processes of widely distributed species, have been challenging. This is mainly due to the cost required to fully implement and interpret the data produced. Here, we generated whole genome resequencing data for 44 free-ranging deer from three regions in their central and eastern North American range and identified over 89 million single nucleotide polymorphisms (SNPs). We used a subset of these SNPs to develop two nested SNP tools, a high-density array (702,183 SNPs) and a medium-density array (72,723 SNPs) to support deer and chronic wasting disease (CWD) management and research. SNPs were selected to ensure an even distribution across scaffolds of the reference genome and include SNPs associated with CWD susceptibility. Using genotyping results for 469 deer from 15 states in the US and Mexico generated by the high-density array and 1335 deer from 18 states generated by the medium-density array, we assessed genotyping success across different populations and explored some insights into population structure. These genomic tools offer a standard set of markers that will enable researchers and managers to address important questions related to white-tailed deer and CWD management. Our SNP arrays also offer the opportunity to examine aspects of white-tailed deer ecology and evolutionary history that were previously difficult to address.

Molecular Ecology Resources

Ten best practices for effective phenological research

The number and diversity of phenological studies has increased rapidly in recent years. Innovative experiments, field studies, citizen science projects, and analyses of newly available historical data are contributing insights that advance our understanding of ecological and evolutionary responses to the environment, particularly climate change. However, many phenological data sets have peculiarities that are not immediately obvious and can lead to mistakes in analyses and interpretation of results. This paper aims to help researchers, especially those new to the field of phenology, understand challenges and practices that are crucial for effective studies. For example, researchers may fail to account for sampling biases in phenological data, struggle to choose or design a volunteer data collection strategy that adequately fits their project’s needs, or combine data sets in inappropriate ways. We describe ten best practices for designing studies of plant and animal phenology, evaluating data quality, and analyzing data. Practices include accounting for common biases in data, using effective citizen or community science methods, and employing appropriate data when investigating phenological mismatches. We present these best practices to help researchers entering the field take full advantage of the wealth of available data and approaches to advance our understanding of phenology and its implications for ecology.

International Journal of Biometeorology

Interaction assessment: Rationale and a test using plants

A non-manipulative method for deriving empirical expressions of population growth parameters from simple field data is presented. The derived expressions can be used to assess the intensity and form of density dependence and interspecies interactions, and have potential for parameterizing more mechanistic models of population dynamics and for use in applied ecology, e.g. land management or environmental risk assessment. The method is based on an assertion of invariant expected fitness across occupied microhabitats. Hence, its success depends upon the degree to which that assertion holds. The assertion, as used here, is broadly applicable. Thus, the method can be expected to yield reliable results even in nonequilibrium communities. Here, we apply the method to data on six desert plant species. Expressions generated from data in one stand, in one year, successfully predict plant cover values in other stands and years. The predicted patterns of plant species interactions are discussed in the light of current knowledge and theorics of desert succession.

Evolutionary Ecology