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At least 109 records · Page 6Linked to original sources
USGS2018

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↗
USGS2022

Invasive species control and management: The sea lamprey story

Control of invasive species is a critical component of conservation biology given the catastrophic damage that they can cause to the ecosystems they invade. This is particularly evident with sea lamprey ( Petromyzon marinus ) in the Laurentian Great Lakes. Native to the Atlantic Ocean, the sea lamprey's ability to osmoregulate in fresh water, its wide thermal tolerance, generalist diet, and high fecundity allowed it to rapidly reach pest proportions in the prey-rich Great Lakes once it gained access through shipping canals. The invasion exacerbated declines in Great Lakes fisheries caused by overharvest, culminating in the crash of lake trout ( Salvelinus namaycush ) and other fish populations. In the last 60 years, however, a highly successful sea lamprey control program has reduced sea lamprey to ∼10% of their peak abundance and has been instrumental in enabling the rehabilitation of the Great Lakes ecosystem. In this chapter, we: (1) discuss the likely vectors of the invasion and the physiological attributes of sea lamprey that enabled them to become established in the Great Lakes; (2) review the two cornerstones of the sea lamprey control program—which relies on a combination of pesticides to eradicate multiple generations of larval sea lamprey in their nursey streams, and in-stream barriers to restrict the upstream migration of spawning lamprey—both of which exploit unique physiological vulnerabilities of sea lamprey; (3) describe how sea lamprey control can adversely affect non-target species and how these can be mitigated; (4) show how physiology-based approaches are improving our understanding of the lethal and sublethal effects of sea lamprey on host fishes; and (5) discuss the future of conservation physiology in sea lamprey control. The prime challenge in the next several decades of the Anthropocene will be to further refine the specificity of control tools while maintaining their efficacy, and to adapt to a warming climate and other anthropogenic activities affecting the Great Lakes and their tributaries.

Lake Erie, Lake Huron, Lake Michigan, Lake Ontario↗
USGS2013

Mapping behavioral landscapes for animal movement: a finite mixture modeling approach

Because of its role in many ecological processes, movement of animals in response to landscape features is an important subject in ecology and conservation biology. In this paper, we develop models of animal movement in relation to objects or fields in a landscape. We take a finite mixture modeling approach in which the component densities are conceptually related to different choices for movement in response to a landscape feature, and the mixing proportions are related to the probability of selecting each response as a function of one or more covariates. We combine particle swarm optimization and an Expectation-Maximization (EM) algorithm to obtain maximum likelihood estimates of the model parameters. We use this approach to analyze data for movement of three bobcats in relation to urban areas in southern California, USA. A behavioral interpretation of the models revealed similarities and differences in bobcat movement response to urbanization. All three bobcats avoided urbanization by moving either parallel to urban boundaries or toward less urban areas as the proportion of urban land cover in the surrounding area increased. However, one bobcat, a male with a dispersal-like large-scale movement pattern, avoided urbanization at lower densities and responded strictly by moving parallel to the urban edge. The other two bobcats, which were both residents and occupied similar geographic areas, avoided urban areas using a combination of movements parallel to the urban edge and movement toward areas of less urbanization. However, the resident female appeared to exhibit greater repulsion at lower levels of urbanization than the resident male, consistent with empirical observations of bobcats in southern California. Using the parameterized finite mixture models, we mapped behavioral states to geographic space, creating a representation of a behavioral landscape. This approach can provide guidance for conservation planning based on analysis of animal movement data using statistical models, thereby linking connectivity evaluations to empirical data.

Ecological Applications↗
USGS2018

Occupancy modeling species–environment relationships with non‐ignorable survey designs

Statistical models supporting inferences about species occurrence patterns in relation to environmental gradients are fundamental to ecology and conservation biology. A common implicit assumption is that the sampling design is ignorable and does not need to be formally accounted for in analyses. The analyst assumes data are representative of the desired population and statistical modeling proceeds. However, if data sets from probability and non‐probability surveys are combined or unequal selection probabilities are used, the design may be non‐ignorable. We outline the use of pseudo‐maximum likelihood estimation for site‐occupancy models to account for such non‐ignorable survey designs. This estimation method accounts for the survey design by properly weighting the pseudo‐likelihood equation. In our empirical example, legacy and newer randomly selected locations were surveyed for bats to bridge a historic statewide effort with an ongoing nationwide program. We provide a worked example using bat acoustic detection/non‐detection data and show how analysts can diagnose whether their design is ignorable. Using simulations we assessed whether our approach is viable for modeling data sets composed of sites contributed outside of a probability design. Pseudo‐maximum likelihood estimates differed from the usual maximum likelihood occupancy estimates for some bat species. Using simulations we show the maximum likelihood estimator of species–environment relationships with non‐ignorable sampling designs was biased, whereas the pseudo‐likelihood estimator was design unbiased. However, in our simulation study the designs composed of a large proportion of legacy or non‐probability sites resulted in estimation issues for standard errors. These issues were likely a result of highly variable weights confounded by small sample sizes (5% or 10% sampling intensity and four revisits). Aggregating data sets from multiple sources logically supports larger sample sizes and potentially increases spatial extents for statistical inferences. Our results suggest that ignoring the mechanism for how locations were selected for data collection (e.g., the sampling design) could result in erroneous model‐based conclusions. Therefore, in order to ensure robust and defensible recommendations for evidence‐based conservation decision‐making, the survey design information in addition to the data themselves must be available for analysts. Details for constructing the weights used in estimation and code for implementation are provided.

Ecological Applications↗
USGS2023

Functional stability of vegetation following biocontrol of an invasive riparian shrub

Understanding plant community response to environmental change is a crucial aspect of biological conservation and restoration, but species-based approaches are limited in that they do not reveal the underlying mechanisms driving vegetation dynamics. An understanding of trait-environment relationships is particularly important in the case of invasive species which may alter abiotic conditions and available resources. This study is the first to measure the functional response of riparian plant communities to biocontrol of an invasive species. We focused on an invasive shrub, Tamarix (saltcedar), that is defoliated by a beetle that was released by the US Department of Agriculture along the Upper Colorado River (southwestern United States). We calculated community weighted means and functional dispersion of individual traits, multivariate functional dispersion and species diversity. We used linear mixed effect models (LME) to compare these metrics at paired vegetation patches dominated and not dominated by Tamarix during cycles of defoliation and refoliation over eight years. We found that community-weighted average trait values, species diversity and functional dispersion changed little in response to defoliation, and instead seemed to be responding to fluctuations in yearly precipitation. Average height and seed weight were greater in Tamarix -dominated patches relative to control patches. Functional dispersion followed a similar trajectory to species diversity, but was a more sensitive indicator of plant community change. We showed that riparian vegetation can be resilient to Tamarix biocontrol, and that defoliation might not necessarily always lead to substantial changes in ecosystem function.

Biological Invasions↗
USGS2022

Average kinship within bighorn sheep populations is associated with connectivity, augmentation, and bottlenecks

Understanding the influence of population attributes on genetic diversity is important to advancement of biological conservation. Because bighorn sheep ( Ovis canadensis ) populations vary in size and management history, the species provides a unique opportunity to observe the response of average pairwise kinship, inversely related to genetic diversity, to a spectrum of natural and management influences. We estimated average pairwise kinship of bighorn sheep herds and compared estimates with population origin (native/indigenous/extant or reintroduced), historical minimum count, connectivity, and augmentation history, to determine which predictors were the most important. We evaluated 488 bighorn sheep from 19 wild populations with past minimum counts of 16–562 animals, including native and reintroduced populations that received 0–165 animals in augmentations. Using the Illumina High Density Ovine array, we generated a dataset of 7728 single nucleotide polymorphisms and calculated average pairwise kinship for each population. Multiple linear regression analysis determined that connectivity between populations via dispersal, greater number of animals received in augmentations, and greater minimum count were correlated with lower average pairwise kinship at the population level, and whether the population was extant or reintroduced was less important. Thus, our results indicated that genetic isolation of populations can result in increased levels of inbreeding. By determining that natural and human-assisted gene flow were likely the most important influences of average pairwise kinship at the population level, this study can serve as a benchmark for future management of bighorn sheep populations and aid in identifying populations of genetic concern to define priorities for conservation of wild populations.

Montana, Wyoming↗
USGS2015

Nest predation research: Recent findings and future perspectives

Nest predation is a key source of selection for birds that has attracted increasing attention from ornithologists. The inclusion of new concepts applicable to nest predation that stem from social information, eavesdropping or physiology has expanded our knowledge considerably. Recent methodological advancements now allow focus on all three players within nest predation interactions: adults, offspring and predators. Indeed, the study of nest predation now forms a vital part of avian research in several fields, including animal behaviour, population ecology, evolution and conservation biology. However, within nest predation research there are important aspects that require further development, such as the comparison between ecological and evolutionary antipredator responses, and the role of anthropogenic change. We hope this review of recent findings and the presentation of new research avenues will encourage researchers to study this important and interesting selective pressure, and ultimately will help us to better understand the biology of birds.

Journal of Ornithology↗
USGS2017

Using silver and bighead carp cell lines for the identification of a unique metabolite fingerprint from thiram-specific chemical exposure

Conservation biology often requires the control of invasive species. One method is the development and use of biocides. Identifying new chemicals as part of the biocide registration approval process can require screening millions of compounds. Traditionally, screening new chemicals has been done in vivo using test organisms. Using in vitro (e.g., cell lines) and in silico (e.g., computer models) methods decrease test organism requirements and increase screening speed and efficiency. These methods, however, would be greatly improved by better understanding how individual fish species metabolize selected compounds. We combined cell assays and metabolomics to create a powerful tool to facilitate the identification of new control chemicals. Specifically, we exposed cell lines established from bighead carp and silver carp larvae to thiram (7 concentrations) then completed metabolite profiling to assess the dose-response of the bighead carp and silver carp metabolome to thiram. Forty one of the 700 metabolomic markers identified in bighead carp exhibited a dose-response to thiram exposure compared to silver carp in which 205 of 1590 metabolomic markers exhibited a dose-response. Additionally, we identified 11 statistically significant metabolomic markers based upon volcano plot analysis common between both species. This smaller subset of metabolites formed a thiram-specific metabolomic fingerprint which allowed for the creation of a toxicant specific, rather than a species-specific, metabolomic fingerprint. Metabolomic fingerprints may be used in biocide development and improve our understanding of ecologically significant events, such as mass fish kills.

Chemosphere↗
USGS2010

Landscape-level impact of tropical forest loss and fragmentation on bird occurrence in eastern Guatemala

Tropical forest destruction and fragmentation of habitat patches may reduce population persistence at the landscape level. Given the complex nature of simultaneously evaluating the effects of these factors on biotic populations, statistical presence/absence modelling has become an important tool in conservation biology. This study uses logistic regression to evaluate the independent effects of tropical forest cover and fragmentation on bird occurrence in eastern Guatemala. Logistic regression models were constructed for 10 species with varying response to habitat alteration. Predictive variables quantified forest cover, fragmentation and their interaction at three different radii (200, 500 and 1000 m scales) of 112 points where presence of target species was determined. Most species elicited a response to the 1000 m scale, which was greater than most species’ reported territory size. Thus, their presence at the landscape scale is probably regulated by extra-territorial phenomena, such as dispersal. Although proportion of forest cover was the most important predictor of species’ presence, there was strong evidence of area-independent and -dependent fragmentation effects on species presence, results that contrast with other studies from northernmost latitudes. Species’ habitat breadth was positively correlated with AIC model values, indicating a better fit for species more restricted to tropical forest. Species with a narrower habitat breadth also elicited stronger negative responses to forest loss. Habitat breadth is thus a simple measure that can be directly related to species’ vulnerability to landscape modification. Model predictive accuracy was acceptable for 4 of 10 species, which were in turn those with narrower habitat breadths.

Cerro San Gil Watershed Protection Reserve↗
USGS2018

The confluences of ideas leading to, and the flow of ideas emerging from, individual-based modeling of riverine fishes

In this review article, we trace the history of events leading to the development of individual-based models (IBMs) to represent aquatic organisms in rivers and streams. As a metaphor, we present this history as a series of confluences between individual scientists (tributaries) sharing ideas. We describe contributions of these models to science and management. One iconic feature of river IBMs is the linkage between flow and the physical habitat experienced by individual animals, and the first model that focused on this linkage is briefly described. We continue by reviewing the contributions of riverine IBMs to eight broad areas of scientific inquiry. The first four areas include research to understand 1) the effects of flow regimes on fish populations, 2) species interactions (e.g., size-mediated competition and predation), 3) fish movement and habitat selection, and 4) contaminant and water quality impacts on populations. Next, we review research using IBMs 5) to guide conservation biology of imperiled taxa through population viability analysis, including research 6) to understand river fragmentation by dams and reconnection, 7) to understand genetic outcomes for riverine metapopulations, and 8) to anticipate the future effects of temperature and climate change. This rich body of literature has contributed to both theoretical insights (e.g., about animal behavior and life history) and applied insights (e.g., population-level effects of flow regimes, temperature, and the effects of hydropower and other industries that share rivers with aquatic biota). We finish by exploring promising branches that lie ahead in the braided, downstream channel that represents future river modeling research.

Ecological Modelling↗
USGS2015

Global land cover mapping using Earth observation satellite data: Recent progresses and challenges

Land cover is an important variable for many studies involving the Earth surface, such as climate, food security, hydrology, soil erosion, atmospheric quality, conservation biology, and plant functioning. Land cover not only changes with human caused land use changes, but also changes with nature. Therefore, the state of land cover is highly dynamic. In winter snow shields underneath various other land cover types in higher latitudes. Floods may persist for a long period in a year over low land areas in the tropical and subtropical regions. Forest maybe burnt or clear cut in a few days and changes to bare land. Within several months, the coverage of crops may vary from bare land to nearly 100% crops and then back to bare land following harvest. The highly dynamic nature of land cover creates a challenge in mapping and monitoring which remains to be adequately addressed. As economic globalization continues to intensify, there is an increasing trend of land cover/land use change, environmental pollution, land degradation, biodiversity loss at the global scale, timely and reliable information on global land cover and its changes is urgently needed to mitigate the negative impact of global environment change.

ISPRS Journal of Photogrammetry and Remote Sensing↗
USGS2011

Multimodel inference and adaptive management

Ecology is an inherently complex science coping with correlated variables, nonlinear interactions and multiple scales of pattern and process, making it difficult for experiments to result in clear, strong inference. Natural resource managers, policy makers, and stakeholders rely on science to provide timely and accurate management recommendations. However, the time necessary to untangle the complexities of interactions within ecosystems is often far greater than the time available to make management decisions. One method of coping with this problem is multimodel inference. Multimodel inference assesses uncertainty by calculating likelihoods among multiple competing hypotheses, but multimodel inference results are often equivocal. Despite this, there may be pressure for ecologists to provide management recommendations regardless of the strength of their study’s inference. We reviewed papers in the Journal of Wildlife Management (JWM) and the journal Conservation Biology (CB) to quantify the prevalence of multimodel inference approaches, the resulting inference (weak versus strong), and how authors dealt with the uncertainty. Thirty-eight percent and 14%, respectively, of articles in the JWM and CB used multimodel inference approaches. Strong inference was rarely observed, with only 7% of JWM and 20% of CB articles resulting in strong inference. We found the majority of weak inference papers in both journals (59%) gave specific management recommendations. Model selection uncertainty was ignored in most recommendations for management. We suggest that adaptive management is an ideal method to resolve uncertainty when research results in weak inference.

Journal of Environmental Management↗
USGS2005

Fire as a global ‘herbivore’: the ecology and evolution of flammable ecosystems

It is difficult to find references to fire in general textbooks on ecology, conservation biology or biogeography, in spite of the fact that large parts of the world burn on a regular basis, and that there is a considerable literature on the ecology of fire and its use for managing ecosystems. Fire has been burning ecosystems for hundreds of millions of years, helping to shape global biome distribution and to maintain the structure and function of fire-prone communities. Fire is also a significant evolutionary force, and is one of the first tools that humans used to re-shape their world. Here, we review the recent literature, drawing parallels between fire and herbivores as alternative consumers of vegetation. We point to the common questions, and some surprisingly different answers, that emerge from viewing fire as a globally significant consumer that is analogous to herbivory.

Trends in Ecology and Evolution↗
USGS2000

Geographic analysis of species richness and community attributes of forest birds from survey data in the mid-Atlantic integrated assessment region

Species richness of local communities is a state variable commonly used in community ecology and conservation biology. Investigation of spatial and temporal variations in richness and identification of factors associated with these variations form a basis for specifying management plans, evaluating these plans, and for testing hypotheses of theoretical interest. However, estimation of species richness is not trivial: species can be missed by investigators during sampling sessions. Sampling artifacts can lead to erroneous conclusions on spatial and temporal variation in species richness. Here we use data from the North American Breeding Bird Survey to estimate parameters describing the state of bird communities in the Mid-Atlantic Assessment (MAIA) region: species richness, extinction probability, turnover and relative species richness. We use a recently developed approach to estimation of species richness and related parameters that does not require the assumption that all the species are detected during sampling efforts. The information presented here is intended to visualize the state of bird communities in the MAIA region. We provide information on 1975 and 1990. We also quantified the changes between these years. We summarized and mapped the community attributes at a scale of management interest (watershed units).

Delaware, Maryland, Pennsylvania, Virginia, West V↗
USGS2003

Population dynamics of Microtus pennsylvanicus in corridor-linked patches

Corridors have become a key issue in the discussion of conservation planning: however, few empirical data exist on the use of corridors and their effects on population dynamics. The objective of this replicated, population level, capture-re-capture experiment on meadow voles was to estimate and compare population characteristics of voles between (1) corridor-linked fragments, (2) isolated or non-linked fragments, and (3) unfragmented areas. We conducted two field experiments involving 22600 captures of 5700 individuals. In the first, the maintained corridor study, corridors were maintained at the time of fragmentation, and in the second, the constructed corridor study, we constructed corridors between patches that had been fragmented for some period of time. We applied multistate capture-recapture models with the robust design to estimate adult movement and survival rates, population size, temporal variation in population size, recruitment, and juvenile survival rates. Movement rates increased to a greater extent on constructed corridor-linked grids than on the unfragmented or non-linked fragmented grids between the pre- and post-treatment periods. We found significant differences in local survival on the treated (corridor-linked) grids compared to survival on the fragmented and unfragmented grids between the pre- and post-treatment periods. We found no clear pattern of treatment effects on population size or recruitment in either study. However, in both studies, we found that unfragmented grids were more stable than the fragmented grids based on lower temporal variability in population size. To our knowledge, this is the first experimental study demonstrating that corridors constructed between existing fragmented populations can indeed cause increases in movement and associated changes in demography, supporting the use of constructed corridors for this purpose in conservation biology.

Maryland↗
USGS2016

Revisiting Paine’s 1966 sea star removal experiment, the most-cited empirical article in the American Naturalist

“Food Web Complexity and Species Diversity” (Paine 1966) is the most-cited empirical article published in the American Naturalist . In short, Paine removed predatory sea stars ( Pisaster ochraceus ) from the rocky intertidal and watched the key prey species, mussels ( Mytilus californianus ), crowd out seven subordinate primary space-holding species. However, because these mussels are a foundational species, they provide three-dimensional habitat for over 300 associated species inhabiting the mussel beds; thus, removing sea stars significantly increases community-wide diversity. In any case, most ecologists cite Paine (1966) to support a statement that predators increase diversity by interfering with competition. Although detractors remained skeptical of top-down effects and keystone concepts, the paradigm that predation increases diversity spread. By 1991, “Food Web Complexity and Species Diversity” was considered a classic ecological paper, and after 50 years it continues to influence ecological theory and conservation biology.

American Naturalist↗
USGS2001

Some considerations on the use of ecological models to predict species' geographic distributions

Peterson (2001) used Genetic Algorithm for Rule-set Prediction (GARP) models to predict distribution patterns from Breeding Bird Survey (BBS) data. Evaluations of these models should consider inherent limitations of BBS data: (1) BBS methods may not sample species and habitats equally; (2) using BBS data for both model development and testing may overlook poor fit of some models; and (3) BBS data may not provide the desired spatial resolution or capture temporal changes in species distributions. The predictive value of GARP models requires additional study, especially comparisons with distribution patterns from independent data sets. When employed at appropriate temporal and geographic scales, GARP models show considerable promise for conservation biology applications but provide limited inferences concerning processes responsible for the observed patterns.

Condor↗
USGS2019

Cohesive framework for modeling plant cover class data

The study of plant distribution and abundance is a fundamental pursuit in ecology and conservation biology. Measuring plant abundance by visually assessing percent cover and recording a cover class is a common field method that yields ordinal data. Statistical models for ordinal data exist but entail cumbersome interpretations and sometimes restrictive assumptions. We propose a Bayesian hierarchical framework for analysing cover class data that allows for linking ordinal observations to a latent beta distribution and accounts for zero inflation. Harnessing a latent beta distribution supports interpreting changes in abundance in terms of mean percent cover rather than odds ratios of cumulative cover classes as for cumulative link models. The zero augmentation allows for simultaneous inferences on both occurrence (distribution) and abundance. We show how our model can account for true and false zeros, misclassification of cover classes, multiple species and hierarchical sampling designs, using empirical examples and simulations. Simulated observation errors, when ignored, led to models overestimating abundance and underestimating occurrence. Based on simulations, we found no substantial difference between mean percent cover estimates when analyzing ordinal cover classes versus continuous percent cover as the response. Our empirical datasets displayed high probability of detection (>0.85 on average for all species), likely due to the sampling design used and training of observers. Probability of occurrence was slightly underestimated for bare ground, Artemisia tridentata , Elycap medusae , and Poa secunda using a model that ignored imperfect detection. Estimated mean percent cover was not substantially impacted by ignoring measurement error for five plant species and bare ground. Our modelling framework for cover class data allows for an explicit separation of distribution from abundance and, importantly, allows for interpreting species–environment relationships in terms of variation in mean percent cover as compared to cumulative odds ratios. The beta distribution inherently accommodates heteroscedasticity and skewness, statistical properties that are a consequence of spatially aggregated patterns common to plant survey data. Recording cover classes provides a reliable, efficient way to measure plants and our simulations suggest little loss of information compared to assuming continuous percent cover. We provide JAGS and Stan model code for implementation.

Methods in Ecology and Evolution↗