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At least 235 records · Page 13Linked to original sources
USGS2015

A reply to Iversen et al.'s comment “Monitoring of animal abundance by environmental DNA - An increasingly obscure perspective”

We appreciate the conversation put forward by Iversen et al. (2015) in their response to our article “Quantification of eDNA shedding rates from invasive bighead carp Hypophthalmichthys nobilis and silver carp Hypophthalmichthys molitrix ” in the 2015 environmental DNA special issue of Biological Conservation. We agree with Iversen et al.'s concern about overly optimistic conclusions that could be drawn from the current eDNA literature. One hope for eDNA technology is that it can be used in estimating abundance or population density. Evidence suggests that eDNA measurements correlate with total biomass (Takahara et al., 2012) rather than abundance. We demonstrate a similar relationship between biomass and eDNA shedding rates. Nevertheless, without field testing of these methods and specific survey protocols, we cannot make strong conclusions regarding the technique's field applicability. In our manuscript, we attempted to point out areas in which more research is needed.

Biological Conservation↗
USGS2016

VNTR diversity in Yersinia pestis isolates from an animal challenge study reveals the potential for in vitro mutations during laboratory cultivation

Underlying mutation rates and other evolutionary forces shape the population structure of bacteria in nature. Although easily overlooked, similar forces are at work in the laboratory and may influence observed mutations. Here, we investigated tissue samples and Yersinia pestis isolates from a rodent laboratory challenge with strain CO92 using whole genome sequencing and multi-locus variable-number tandem repeat (VNTR) analysis (MLVA). We identified six VNTR mutations that were found to have occurred in vitro during laboratory cultivation rather than in vivo during the rodent challenge. In contrast, no single nucleotide polymorphism (SNP) mutations were observed, either in vivo or in vitro . These results were consistent with previously published mutation rates and the calculated number of Y. pestis generations that occurred during the in vitro versus the in vivo portions of the experiment. When genotyping disease outbreaks, the potential for in vitro mutations should be considered, particularly when highly variable genetic markers such as VNTRs are used.

Infection, Genetics and Evolution↗
USGS2002

Trophic strategies, animal diversity and body size

A primary difference between predators and parasites is the number of victims that an individual attacks throughout a life-history stage. A key division within natural enemies is whether a successful attack eliminates the fitness of the prey or the host. A third distinctive axis for parasites is whether the host must die to further parasite development. The presence or absence of intensity-dependent pathology is a fourth factor that separates macroparasites from microparasites; this also distinguishes between social and solitary predators. Combining these four dichotomies defines seven types of parasitism, seven corresponding parasites, three forms of predation and, when one considers obligate and facultative combinations of these forms, four types of predator. Here, we argue that the energetics underlying the relative and absolute sizes of natural enemies and their victims is the primary selective factor responsible for the evolution of these different trophic strategies.

Trends in Ecology and Evolution↗
USGS2004

Gold concentrations in abiotic materials, plants, and animals: A synoptic review

Gold (Au) is ubiquitous in the environment and mined commercially at numerous locations worldwide. It is also an allergen that induces dermatitis in sensitive individuals. Gold concentrations were comparatively elevated in samples collected near gold mining and processing facilities, although no data were found for birds and non-human mammals. Maximum gold concentrations reported in abiotic materials were 0.001 μg L -1 in rainwater; 0.0015 μgL -1 in seawater near hydrothermal vents vs. <0.00004–0.0007 μg L -1 elsewhere; 5.0 μg kg -1 dry weight (DW) in the Earth's crust; 19.0 μg L -1 in a freshwater stream near a gold mining site; 440 μg kg -1 DW in atmospheric dust near a high traffic road; 843 μg kg -1 DW in alluvial soil near a Nevada gold mine vs. <29 μg kg -1 DW premining; 2.53 mg kg -1 DW in snow near a Russian smelter vs. <0.35 mg kg -1 DW at a reference site; 4.5 mg kg -1 DW in sewage sludge; 28.7 mg kg -1 DW in polymetallic sulfides from the ocean floor; and 256.0 mg kg -1 DW in freshwater sediments near a gold mine tailings pile vs. <5 μg kg -1 DW prior to mining. In plants, elevated concentrations of 19 μg Au kg -1 DW were reported in terrestrial vegetation near gold mining operations vs. <4 μg kg -1 DW at a reference site; 37 μg kg -1 DW in aquatic bryophytes downstream from a gold mine; 150 μg Au kg -1 DW in leaves of beans grown in soil containing 170 μg kg -1 DW; up to 1.06 mg kg -1 DW in algal mats of rivers receiving gold mine wastes; and 0.1–100 mg kg -1 DW in selected gold accumulator plants. Fish and aquatic invertebrates contained 0.1–38.0 μg Au kg -1 DW. In humans, gold concentrations up to 1.1 μg L -1 were documented in urine of dental technicians vs. 0.002–0.85 μg L -1 in reference populations; 2.1 μg L -1 in breast milk, attributed to gold dental fillings and jewelry of mothers; 1.4 mg kg -1 DW in hair of goldsmiths vs. a normal range of 6–880 μg kg -1 DW; 2.39 mg L -1 in whole blood of rheumatoid arthritis patients receiving gold thiol drugs to reduce inflammation (chrysotherapy) vs. a normal range of 0.2–2.0 μg L -1 ; and 60.0 to 233.0 mg kg -1 fresh weight (FW) in kidneys of rheumatoid arthritis patients undergoing active chrysotherapy vs. <42.0 mg kg -1 FW kidney 140 months posttreatment.

Environmental Monitoring and Assessment↗
USGS2021

Monitoring abundance of aggregated animals (Florida manatees) using an unmanned aerial system (UAS)

Imperfect detection is an important problem when counting wildlife, but new technologies such as unmanned aerial systems (UAS) can help overcome this obstacle. We used data collected by a UAS and a Bayesian closed capture-mark-recapture model to estimate abundance and distribution while accounting for imperfect detection of aggregated Florida manatees ( Trichechus manatus latirostris ) at thermal refuges to assess use of current and new warmwater sources in winter. Our UAS hovered for 10 min and recorded 4 K video over sites in Collier County, FL. Open-source software was used to create recapture histories for 10- and 6-min time periods. Mean estimates of probability of detection for 1-min intervals at each canal varied by survey and ranged between 0.05 and 0.92. Overall, detection probability for sites varied between 0.62 and 1.00 across surveys and length of video (6 and 10 min). Abundance varied by survey and location, and estimates indicated that distribution changed over time, with use of the novel source of warmwater increasing over time. The highest cumulative estimate occurred in the coldest winter, 2018 (N = 158, CI 141–190). Methods here reduced survey costs, increased safety and obtained rigorous abundance estimates at aggregation sites previously too difficult to monitor.

Florida↗
USGS2009

COMDYN: Software to study the dynamics of animal communities using a capture-recapture approach

COMDYN is a set of programs developed for estimation of parameters associated with community dynamics using count data from two locations or time periods. It is Internet-based, allowing remote users either to input their own data, or to use data from the North American Breeding Bird Survey for analysis. COMDYN allows probability of detection to vary among species and among locations and time periods. The basic estimator for species richness underlying all estimators is the jackknife estimator proposed by Burnham and Overton. Estimators are presented for quantities associated with temporal change in species richness, including rate of change in species richness over time, local extinction probability, local species turnover and number of local colonizing species. Estimators are also presented for quantities associated with spatial variation in species richness, including relative richness at two locations and proportion of species present in one location that are also present at a second location. Application of the estimators to species richness estimation has been previously described and justified. The potential applications of these programs are discussed.

Bird Study↗
USGS1995

Survival estimation and the effects of dependency among animals

Survival models assume that fates of individuals are independent, yet the robustness of this assumption has been poorly quantified. We examine how empirically derived estimates of the variance of survival rates are affected by dependency in survival probability among individuals. We used Monte Carlo simulations to generate known amounts of dependency among pairs of individuals and analyzed these data with Kaplan-Meier and Cormack-Jolly-Seber models. Dependency significantly increased these empirical variances as compared to theoretically derived estimates of variance from the same populations. Using resighting data from 168 pairs of black brant, we used a resampling procedure and program RELEASE to estimate empirical and mean theoretical variances. We estimated that the relationship between paired individuals caused the empirical variance of the survival rate to be 155% larger than the empirical variance for unpaired individuals. Monte Carlo simulations and use of this resampling strategy can provide investigators with information on how robust their data are to this common assumption of independent survival probabilities.

Journal of Applied Statistics↗
USGS1978

Estimation of the size of a closed population when capture probabilities vary among animals

A model which allows capture probabilities to vary by individuals is introduced for multiple recapture studies n closed populations. The set of individual capture probabilities is modelled as a random sample from an arbitrary probability distribution over the unit interval. We show that the capture frequencies are a sufficient statistic. A nonparametric estimator of population size is developed based on the generalized jackknife; this estimator is found to be a linear combination of the capture frequencies. Finally, tests of underlying assumptions are presented.

Biometrika↗
USGS2021

Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distribution

Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSFs) or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual- and population-level inference with flexible non-linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from golden eagles Aquila chrysaetos from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k -fold cross-validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of individual variation in response to land cover variables during winter months, with most individuals more closely adhering to the population-level trend. During the summer months, eagles exhibited more substantial individual variation in shape and smoothness of the functional relationships, suggesting some need to account for individual variation in eagle habitat use for both inferential and predictive purposes, during this time of year. Because they allow users to blend flexible functions with random effects structures and are well-supported by a variety of software platforms, we believe that HGAMs provide a useful addition to the suite of analyses used for modeling habitat associations or predicting species distributions.

Ecography↗
USGS1985

The representative research animal: Why rainbow trout (Salmo gairdneri Rich.)?

In laboratory research, the rainbow trout has become a counterpart to the white rat, because that fish is an adaptable species available in much of the developed world and stocks from egg through adult are available throughout the year. Moreover, many strains are recognized, and their propagation and laboratory maintenance are not particularly demanding. Also, knowledge of rainbow trout nutrition, husbandry, diseases, immune responses, toxicology, and carcinogenesis exceeds that of any other salmonid or coldwater teleost. The rainbow trout is the logical surrogate species in many studies of other salmonids.

Journal of Applied Ichthyology↗
USGS2012

Program SPACECAP: software for estimating animal density using spatially explicit capture-recapture models

1. The advent of spatially explicit capture-recapture models is changing the way ecologists analyse capture-recapture data. However, the advantages offered by these new models are not fully exploited because they can be difficult to implement. 2. To address this need, we developed a user-friendly software package, created within the R programming environment, called SPACECAP. This package implements Bayesian spatially explicit hierarchical models to analyse spatial capture-recapture data. 3. Given that a large number of field biologists prefer software with graphical user interfaces for analysing their data, SPACECAP is particularly useful as a tool to increase the adoption of Bayesian spatially explicit capture-recapture methods in practice.

Methods in Ecology and Evolution↗
USGS2018

Is ungulate migration culturally transmitted? Evidence of social learning from translocated animals

Ungulate migrations are assumed to stem from learning and cultural transmission of information regarding seasonal distribution of forage, but this hypothesis has not been tested empirically. We compared the migratory propensities of bighorn sheep and moose translocated into novel habitats with those of historical populations that had persisted for hundreds of years. Whereas individuals from historical populations were largely migratory, translocated individuals initially were not. After multiple decades, however, translocated populations gained knowledge about surfing green waves of forage (tracking plant phenology) and increased their propensity to migrate. Our findings indicate that learning and cultural transmission are the primary mechanisms by which ungulate migrations evolve. Loss of migration will therefore expunge generations of knowledge about the locations of high-quality forage and likely suppress population abundance.

Idaho, Wyoming↗
USGS2009

Animal species endangerment: The role of environmental pollution

Multiple factors contribute to the decline of species. Habitat destruction is the primary factor that threatens species. affecting 73 % of endangered species. The second major factor causing species decline is the introduction of nonnative species. affecting 68% of endangered species. Pollution and overharvesting were identified as impacting, respectively, 38 and 15% of endangered species. Other factors affecting species decline include hybridization, competition, disease, and other interspecific interactions. Once a species is reduced to a remnant of its former population size and distribution, its vulnerability to catastrophic pollution events increases, frequently exceeding or replacing the factors responsible for the initial decline. Small, isolated populations are particularly vulnerable to catastrophic loss by an acute event. such as a chemical spill or pesticide application. However, when it comes to surviving a single disaster, widespread subpopulations of a species are far more resilient and ensure genetic survival. Hypothesizing theoretical concerns of potential factors that could affect an endangered species could predispose the scientific and political communities to jeopardizing threats. The user of recovery plans as a data source must be aware of the bias within the data set. These data should be used with the caveat that the source of information in recovery plans is not always based on scientific research and rigorous data collection. Over 58% of the information identifying species threats is based on estimates or personal communication. while only 42% is based on peer reviewed literature, academic research. or government reports. Many recovery plans were written when a species was initially listed in the 1970s or 1980s. Politics, human disturbance, and habitat demand issues evolve over a 20- to 30-year period. leaving much of the threats facing endangered species outdated and inadequate. These data are most valuable when used to facilitate reviews of Section 7 consultations and environmental impact statements, review permit applications, conduct environmental risk assessments, prioritize research needs. and identify limiting factors affecting species health. These data are also useful in identifying potential threats to species' health. Without properly identifying threats to endangered species based on sound. scientific research. there is little hope to successfully recover an endangered species.

Book chapter↗
USGS2022

Bayesian inverse reinforcement learning for collective animal movement

Agent-based methods allow for defining simple rules that generate complex group behaviors. The governing rules of such models are typically set a priori, and parameters are tuned from observed behavior trajectories. Instead of making simplifying assumptions across all anticipated scenarios, inverse reinforcement learning provides inference on the short-term (local) rules governing long-term behavior policies by using properties of a Markov decision process. We use the computationally efficient linearly-solvable Markov decision process to learn the local rules governing collective movement for a simulation of the selfpropelled-particle (SPP) model and a data application for a captive guppy population. The estimation of the behavioral decision costs is done in a Bayesian framework with basis function smoothing. We recover the true costs in the SPP simulation and find the guppies value collective movement more than targeted movement toward shelter.

Annals of Applied Statistics↗
USGS1993

Survival in pond water of four reoviruses isolated from aquatic animals

The viabilities of golden shiner virus (GSV), chum salmon virus (CSV), oyster reovirus 13P2 (13P2). and catfish reovirus (CRV) were compared following viruses incubation in pond water samples held at 4°. 20°, 25°, and 30°C for one month. At the three higher temperatures tested, viral infectivity was lost by day 15 for GSV, day 20 for CSV, and day 10 for CRV and 13P2. At 4°C. no infectious GSV was detected at day 15, while the other viruses showed little or no loss of infectivity during the 30-day incubation period. The survival of these viruses in natural waters appears to be sufficient to sustain fish-to-fish transmission.

Journal of Applied Aquaculture↗
USGS2011

Challenges in identifying sites climatically matched to the native ranges of animal invaders

Background: Species distribution models are often used to characterize a species' native range climate, so as to identify sites elsewhere in the world that may be climatically similar and therefore at risk of invasion by the species. This endeavor provoked intense public controversy over recent attempts to model areas at risk of invasion by the Indian Python (Python molurus). We evaluated a number of MaxEnt models on this species to assess MaxEnt's utility for vertebrate climate matching. Methodology/Principal Findings: Overall, we found MaxEnt models to be very sensitive to modeling choices and selection of input localities and background regions. As used, MaxEnt invoked minimal protections against data dredging, multi-collinearity of explanatory axes, and overfitting. As used, MaxEnt endeavored to identify a single ideal climate, whereas different climatic considerations may determine range boundaries in different parts of the native range. MaxEnt was extremely sensitive to both the choice of background locations for the python, and to selection of presence points: inclusion of just four erroneous localities was responsible for Pyron et al.'s conclusion that no additional portions of the U.S. mainland were at risk of python invasion. When used with default settings, MaxEnt overfit the realized climate space, identifying models with about 60 parameters, about five times the number of parameters justifiable when optimized on the basis of Akaike's Information Criterion. Conclusions/Significance: When used with default settings, MaxEnt may not be an appropriate vehicle for identifying all sites at risk of colonization. Model instability and dearth of protections against overfitting, multi-collinearity, and data dredging may combine with a failure to distinguish fundamental from realized climate envelopes to produce models of limited utility. A priori identification of biologically realistic model structure, combined with computational protections against these statistical problems, may produce more robust models of invasion risk.

PLoS ONE↗