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At least 163 records · Page 9Linked to original sources
USGS2019

Epidemic growth rates and host movement patterns shape management performance for pathogen spillover at the wildlife-livestock interface

Managing pathogen spillover at the wildlife–livestock interface is a key step towards improving global animal health, food security and wildlife conservation. However, predicting the effectiveness of management actions across host–pathogen systems with different life histories is an on-going challenge since data on intervention effectiveness are expensive to collect and results are system-specific. We developed a simulation model to explore how the efficacies of different management strategies vary according to host movement patterns and epidemic growth rates. The model suggested that fast-growing, fast-moving epidemics like avian influenza were best-managed with actions like biosecurity or containment, which limited and localized overall spillover risk. For fast-growing, slower-moving diseases like foot-and-mouth disease, depopulation or prophylactic vaccination were competitive management options. Many actions performed competitively when epidemics grew slowly and host movements were limited, and how management efficacy related to epidemic growth rate or host movement propensity depended on what objective was used to evaluate management performance. This framework offers one means of classifying and prioritizing responses to novel pathogen spillover threats, and evaluating current management actions for pathogens emerging at the wildlife–livestock interface.

Philosophical Transactions of the Royal Society A:↗
USGS2024

Metagenomic sequencing sheds light on microbes putatively associated with pneumonia-related fatalities of white-tailed deer (Odocoileus virginianus)

With emerging infectious disease outbreaks in human, domestic and wild animal populations on the rise, improvements in pathogen characterization and surveillance are paramount for the protection of human and animal health, as well as the conservation of ecologically and economically important wildlife. Genomics offers a range of suitable tools to meet these goals, with metagenomic sequencing facilitating the characterization of whole microbial communities associated with emerging and endemic disease outbreaks. Here, we use metagenomic sequencing in a case-control study to identify microbes in lung tissue associated with newly observed pneumonia-related fatalities in 34 white-tailed deer ( Odocoileus virginianus ) in Wisconsin, USA. We identified 20 bacterial species that occurred in more than a single individual. Of these, only Clostridium novyi was found to substantially differ (in number of detections) between case and control sample groups; however, this difference was not statistically significant. We also detected several bacterial species associated with pneumonia and/or other diseases in ruminants ( Mycoplasma ovipneumoniae , Trueperella pyogenes , Pasteurella multocida , Anaplasma phagocytophilum , Fusobacterium necrophorum ); however, these species did not substantially differ between case and control sample groups. On average, we detected a larger number of bacterial species in case samples than controls, supporting the potential role of polymicrobial infections in this system. Importantly, we did not detect DNA of viruses or fungi, suggesting that they are not significantly associated with pneumonia in this system. Together, these results highlight the utility of metagenomic sequencing for identifying disease-associated microbes. This preliminary list of microbes will help inform future research on pneumonia-associated fatalities of white-tailed deer.

Microbial Genomics↗
USGS2007

Linking resources with demography to understand resource limitation for bears

1. Identifying the resources that limit growth of animal populations is essential for effective conservation; however, resource limitation is difficult to quantify. Recent advances in geographical information systems (GIS) and resource modelling can be combined with demographic modelling to yield insights into resource limitation. 2. Using long-term data on a population of black bears Ursus americanus, we evaluated competing hypotheses about whether availability of hard mast (acorns and nuts) or soft mast (fleshy fruits) limited bears in the southern Appalachians, USA, during 1981-2002. The effects of clearcutting on habitat quality were also evaluated. Annual survival, recruitment and population growth rate were estimated using capture-recapture data from 101 females. The availability of hard mast, soft mast and clearcuts was estimated with a GIS, as each changed through time as a result of harvest and succession, and then availabilities were incorporated as covariates for each demographic parameter. 3. The model with the additive availability of hard mast and soft mast across the landscape predicted survival and population growth rate. Availability of young clearcuts predicted recruitment, but not population growth or survival. 4. Availability of hard mast stands across the landscape and availability of soft mast across the landscape were more important than hard mast production and availability of soft mast in young clearcuts, respectively. 5. Synthesis and applications. Our results indicate that older stands, which support high levels of hard mast and moderate levels of soft mast, should be maintained to sustain population growth of bears in the southern Appalachians. Simultaneously, the acreage of intermediate aged stands (10-25 years), which support very low levels of both hard mast and soft mast, should be minimized. The approach used in this study has broad application for wildlife management and conservation. State and federal wildlife agencies often possess long-term data on both resource availability and capture-recapture for wild populations. Combined, these two data types can be used to estimate survival, recruitment, population growth, elasticities of vital rates and the effects of resource availability on demographic parameters. Hence data that are traditionally used to understand population trends can be used to evaluate how and why demography changes over time. ?? 2007 The Authors.

Journal of Applied Ecology↗
USGS2005

Rocky Mountain Center for Conservation Genetics and Systematics

The use of molecular genetic tools has become increasingly important in addressing conservation issues pertaining to plants and animals. Genetic information can be used to augment studies of population dynamics and population viability, investigate systematic, refine taxonomic definitions, investigate population structure and gene flow, and document genetic diversity in a variety of plant and animal species. Further, genetic techniques are being used to investigate mating systems through paternity analysis, and analyze ancient DNA samples from museum specimens, and estimate population size and survival rates using DNA as a unique marker. Such information is essential for the sound management of small, isolated populations of concern and is currently being used by universities, zoos, the U.S. Fish and Wildlife Service, and numerous state fish and wildlife agencies.

Fact Sheet↗
USGS2018

Raptor nest-site use in relation to the proximity of coalbed methane development

Raptor nest–site use in relation to the proximity of coalbed–methane development. Energy development such as coalbed–methane (CBM) extraction is a major land use with largely unknown consequences for many animal species. Some raptor species may be especially vulnerable to habitat changes due to energy development given their ecological requirements and population trajectories. Using 12,977 observations of 3,074 nests of 12 raptor species across nine years (2003–2011) in the Powder River Basin, Wyoming, USA, we evaluated relationships between raptor nest–site use and CBM development. Our objectives were to determine temporal trends in nest–use rates, and whether nest–site use was related to the proximity of CBM development. Across the study area, nest–use rates varied across species and years in a non–linear fashion. We developed a novel randomization test to assess differences in use between nests at developed and undeveloped sites, while controlling for annual variation in nest–site use. Red–tailed hawks (Buteo jamaicensis), burrowing owls (Athene cunicularia), and long–eared owls (Asio otus) used nests in undeveloped areas more than nests in developed areas (i.e. nests near CBM development). Differences between development groups were equivocal for the remaining nine species; however, we caution that we likely had lower statistical power to detect differences for rarer species. Our findings suggest potential avoidance of nesting in areas near CBM development by some species and reveal that CBM effects may be fairly consistent across distances between 400–2,415 m from wells. Future work should consider habitat preferences and fitness outcomes, and control for other key factors such as local prey availability, raptor densities, and weather.

Wyoming↗
USGS1992

Application of DNA fingerprinting to the recovery program of the endangered Puerto Rican parrot

The Puerto Rican parrot was reduced to 13 animals in 1975 and as a conservation measure, a captive population was established from a few founders taken from the wild between 1973 and 1983. The number of successful breeding pairs in captivity has been !ow, and the captive breeding program has not been as productive as that of the closely related Hispaniolan parrot. Therefore, a genetic study was initiated to examine the relative levels of relatedness of the captive founders using levels of bandsharing in DNA fingerprints. Unrelated captive founder Puerto Rican parrots had the same average level of bandsharing (0.41) as second-degree relatives of the Hispaniolan parrot (0.38, P > 0,05), with an inbreeding coefficient of 0.04. High levels of bandsharing (>40%) between pairs of males and females correlated with reproductive failure, suggesting that inbreeding depression is partly responsible for the !ow number of' breeding pairs. Consequently, DNA profiling can be used to guide the captive breeding program for the Puerto Rican parrot, and other endangered species, by identifying pairs of males and females with low levels of bandsharing.

Proceedings of the National Academy of Sciences↗
USGS2004

Coping with unobservable and mis-classified states in capture-recapture studies

Multistate mark-recapture methods provide an excellent conceptual framework for considering estimation in studies of marked animals. Traditional methods include the assumptions that (1) each state an animal occupies is observable, and (2) state is assigned correctly at each point in time. Failure of either of these assumptions can lead to biased estimates of demographic parameters. I review design and analysis options for minimizing or eliminating these biases. Unobservable states can be adjusted for by including them in the state space of the statistical model, with zero capture probability, and incorporating the robust design, or observing animals in the unobservable state through telemetry, tag recoveries, or incidental observations. Mis-classification can be adjusted for by auxiliary data or incorporating the robust design, in order to estimate the probability of detecting the state an animal occupies. For both unobservable and mis-classified states, the key feature of the robust design is the assumption that the state of the animal is static for at least two sampling occasions.

Animal Biodiversity and Conservation↗
USGS2004

Demographic estimation methods for plants with dormancy

Demographic studies in plants appear simple because unlike animals, plants do not run away. Plant individuals can be marked with, e.g., plastic tags, but often the coordinates of an individual may be sufficient to identify it. Vascular plants in temperate latitudes have a pronounced seasonal life–cycle, so most plant demographers survey their study plots once a year often during or shortly after flowering. Life–states are pervasive in plants, hence the results of a demographic study for an individual can be summarized in a familiar encounter history, such as 0VFVVF000. A zero means that an individual was not seen in a year and a letter denotes its state for years when it was seen aboveground. V and F here stand for vegetative and flowering states, respectively. Probabilities of survival and state transitions can then be obtained by mere counting. Problems arise when there is an unobservable dormant state, i.e., when plants may stay belowground for one or more growing seasons. Encounter histories such as 0VF00F000 may then occur where the meaning of zeroes becomes ambiguous. A zero can either mean a dead or a dormant plant. Various ad hoc methods in wide use among plant ecologists have made strong assumptions about when a zero should be equated to a dormant individual. These methods have never been compared among each other. In our talk and in Kéry et al. (submitted), we show that these ad hoc estimators provide spurious estimates of survival and should not be used. In contrast, if detection probabilities for aboveground plants are known or can be estimated, capturerecapture (CR) models can be used to estimate probabilities of survival and state–transitions and the fraction of the population that is dormant. We have used this approach in two studies of terrestrial orchids, Cleistes bifaria (Kéry et al., submitted) and Cypripedium reginae (Kéry & Gregg, submitted) in West Virginia, U.S.A. For Cleistes, our data comprised one population with a total of 620 marked ramets over 10 years, and for Cypripedium , two populations with 98 and 258 marked ramets over 11 years. We chose the ramet (= single stem or shoot) as the demographic unit of our study since there was no way distinguishing among genets (genet = genetical individual, i.e., the “individual” that animal ecologists are mostly concerned with). This will introduce some non–independence into the data, which can nevertheless be dealt with easily by correcting variances for overdispersion. Using ramets instead of genets has the further advantage that individuals can be assigned to a state such as flowering or vegetative in an unambiguous manner. This is not possible when genets are the demographic units. In all three populations, auxiliary data was available to show that detection probability of aboveground plants was m 0.995 We fitted multistate models in program MARK by specifying three states (D, V, F), even though the dormant state D does not occur in the encounter histories. Detection probability is fixed at 1 for the vegetative (V) and the flowering state (F) and at zero for the dormant state (D). Rates of survival and of state transitions as well as slopes of covariate relationships can be estimated and LRT or the AIC machinery be used to select among models. To estimate the fraction of the population in the unobservable dormant state, the encounter histories are collapsed to 0 (plant not observed aboveground) and 1 (plant observed aboveground). The Cormack–Jolly–Seber model without constraints on detection probability is used to estimate detection probability, the complement of which is the estimated fraction of the population in the dormant state. Parameter identifiability is an important issue in multi state models. We used the Catchpole–Morgan–Freeman approach to determine which parameters are estimable in principle in our multi state models. Most of 15 tested models were indeed estimable with the notable exception of the most general model, which has fully interactive state- and time-dependent survival and state transition rates. This model would become identifiable if at least some plants would be excavated in years when they do not show up aboveground. Our analyses for three analyzed populations of Cleistes and Cypripedium yielded annual ramet survival rates ranging from 0.86–0.96. Estimates of the average fraction dormant ranged from 0.02–0.30, but with up to half a population in the dormant state in some years. Ultrastructural modeling enables interesting hypotheses to be tested about the relationships of demographic rates with climatic covariates for instance. Such covariate modeling makes the CR approach particularly interesting for evolutionary–ecological questions about, e.g., the adaptive significance of the dormant state.

Animal Biodiversity and Conservation↗
USGS2004

Individual heterogeneity and identifiability in capture-recapture models

Individual heterogeneity in detection probabilities is a far more serious problem for capture-recapture modeling than has previously been recognized. In this note, I illustrate that population size is not an identifiable parameter under the general closed population mark-recapture model Mh. The problem of identifiability is obvious if the population includes individuals with pi = 0, but persists even when it is assumed that individual detection probabilities are bounded away from zero. Identifiability may be attained within parametric families of distributions for pi , but not among parametric families of distributions. Consequently, in the presence of individual heterogeneity in detection probability, capture-recapture analysis is strongly model dependent.

Animal Biodiversity and Conservation↗
USGS2004

Computing and software

The reality is that the statistical methods used for analysis of data depend upon the availability of software. Analysis of marked animal data is no different than the rest of the statistical field. The methods used for analysis are those that are available in reliable software packages. Thus, the critical importance of having reliable, up–to–date software available to biologists is obvious. Statisticians have continued to develop more robust models, ever expanding the suite of potential analysis methods available. But without software to implement these newer methods, they will languish in the abstract, and not be applied to the problems deserving them. In the Computers and Software Session, two new software packages are described, a comparison of implementation of methods for the estimation of nest survival is provided, and a more speculative paper about how the next generation of software might be structured is presented. Rotella et al. (2004) compare nest survival estimation with different software packages: SAS logistic regression, SAS non–linear mixed models, and Program MARK. Nests are assumed to be visited at various, possibly infrequent, intervals. All of the approaches described compute nest survival with the same likelihood, and require that the age of the nest is known to account for nests that eventually hatch. However, each approach offers advantages and disadvantages, explored by Rotella et al. (2004). Efford et al. (2004) present a new software package called DENSITY. The package computes population abundance and density from trapping arrays and other detection methods with a new and unique approach. DENSITY represents the first major addition to the analysis of trapping arrays in 20 years. Barker & White (2004) discuss how existing software such as Program MARK require that each new model’s likelihood must be programmed specifically for that model. They wishfully think that future software might allow the user to combine pieces of likelihood functions together to generate estimates. The idea is interesting, and maybe some bright young statistician can work out the specifics to implement the procedure. Choquet et al. (2004) describe MSURGE, a software package that implements the multistate capture–recapture models. The unique feature of MSURGE is that the design matrix is constructed with an interpreted language called GEMACO. Because MSURGE is limited to just multistate models, the special requirements of these likelihoods can be provided. The software and methods presented in these papers gives biologists and wildlife managers an expanding range of possibilities for data analysis. Although ease–of–use is generally getting better, it does not replace the need for understanding of the requirements and structure of the models being computed. The internet provides access to many free software packages as well as user–discussion groups to share knowledge and ideas. (A starting point for wildlife–related applications is (http://www.phidot.org).

Animal Biodiversity and Conservation↗
USGS2004

Evolution of quantitative methods for the study and management of avian populations: on the importance of individual contributions

The EURING meetings and the scientists who have attended them have contributed substantially to the growth of knowledge in the field of estimating parameters of animal populations. The contributions of David R. Anderson to process modeling, parameter estimation and decision analysis are briefly reviewed. Metrics are considered for assessing individual contributions to a field of inquiry, and it is concluded that Anderson’s contributions have been substantial. Important characteristics of Anderson and his career are the ability to identify and focus on important topics, the premium placed on dissemination of new methods to prospective users, the ability to assemble teams of complementary researchers, and the innovation and vision that characterized so much of his work. The paper concludes with a list of interesting current research topics for consideration by EURING participants.

Animal Biodiversity and Conservation↗
USGS2004

DENSITY: software for analysing capture-recapture data from passive detector arrays

A general computer-intensive method is described for fitting spatial detection functions to capture-recapture data from arrays of passive detectors such as live traps and mist nets. The method is used to estimate the population density of 10 species of breeding birds sampled by mist-netting in deciduous forest at Patuxent Research Refuge, Laurel, Maryland, U.S.A., from 1961 to 1972. Total density (9.9 ? 0.6 ha-1 mean ? SE) appeared to decline over time (slope -0.41 ? 0.15 ha-1y-1). The mean precision of annual estimates for all 10 species pooled was acceptable (CV(D) = 14%). Spatial analysis of closed-population capture-recapture data highlighted deficiencies in non-spatial methodologies. For example, effective trapping area cannot be assumed constant when detection probability is variable. Simulation may be used to evaluate alternative designs for mist net arrays where density estimation is a study goal.

Animal Biodiversity and Conservation↗
USGS2004

Generalized estimators of avian abundance from count survey data

I consider modeling avian abundance from spatially referenced bird count data collected according to common protocols such as capture?recapture, multiple observer, removal sampling and simple point counts. Small sample sizes and large numbers of parameters have motivated many analyses that disregard the spatial indexing of the data, and thus do not provide an adequate treatment of spatial structure. I describe a general framework for modeling spatially replicated data that regards local abundance as a random process, motivated by the view that the set of spatially referenced local populations (at the sample locations) constitute a metapopulation. Under this view, attention can be focused on developing a model for the variation in local abundance independent of the sampling protocol being considered. The metapopulation model structure, when combined with the data generating model, define a simple hierarchical model that can be analyzed using conventional methods. The proposed modeling framework is completely general in the sense that broad classes of metapopulation models may be considered, site level covariates on detection and abundance may be considered, and estimates of abundance and related quantities may be obtained for sample locations, groups of locations, unsampled locations. Two brief examples are given, the first involving simple point counts, and the second based on temporary removal counts. Extension of these models to open systems is briefly discussed.

Animal Biodiversity and Conservation↗
USGS2004

Hierarchial mark-recapture models: a framework for inference about demographic processes

The development of sophisticated mark-recapture models over the last four decades has provided fundamental tools for the study of wildlife populations, allowing reliable inference about population sizes and demographic rates based on clearly formulated models for the sampling processes. Mark-recapture models are now routinely described by large numbers of parameters. These large models provide the next challenge to wildlife modelers: the extraction of signal from noise in large collections of parameters. Pattern among parameters can be described by strong, deterministic relations (as in ultrastructural models) but is more flexibly and credibly modeled using weaker, stochastic relations. Trend in survival rates is not likely to be manifest by a sequence of values falling precisely on a given parametric curve; rather, if we could somehow know the true values, we might anticipate a regression relation between parameters and explanatory variables, in which true value equals signal plus noise. Hierarchical models provide a useful framework for inference about collections of related parameters. Instead of regarding parameters as fixed but unknown quantities, we regard them as realizations of stochastic processes governed by hyperparameters. Inference about demographic processes is based on investigation of these hyperparameters. We advocate the Bayesian paradigm as a natural, mathematically and scientifically sound basis for inference about hierarchical models. We describe analysis of capture-recapture data from an open population based on hierarchical extensions of the Cormack-Jolly-Seber model. In addition to recaptures of marked animals, we model first captures of animals and losses on capture, and are thus able to estimate survival probabilities w (i.e., the complement of death or permanent emigration) and per capita growth rates f (i.e., the sum of recruitment and immigration rates). Covariation in these rates, a feature of demographic interest, is explicitly described in the model.

Animal Biodiversity and Conservation↗
USGS2004

Occupancy as a surrogate for abundance estimation

In many monitoring programmes it may be prohibitively expensive to estimate the actual abundance of a bird species in a defined area, particularly at large spatial scales, or where birds occur at very low densities. Often it may be appropriate to consider the proportion of area occupied by the species as an alternative state variable. However, as with abundance estimation, issues of detectability must be taken into account in order to make accurate inferences: the non?detection of the species does not imply the species is genuinely absent. Here we review some recent modelling developments that permit unbiased estimation of the proportion of area occupied, colonization and local extinction probabilities. These methods allow for unequal sampling effort and enable covariate information on sampling locations to be incorporated. We also describe how these models could be extended to incorporate information from marked individuals, which would enable finer questions of population dynamics (such as turnover rate of nest sites by specific breeding pairs) to be addressed. We believe these models may be applicable to a wide range of bird species and may be useful for investigating various questions of ecological interest. For example, with respect to habitat quality, we might predict that a species is more likely to have higher local extinction probabilities, or higher turnover rates of specific breeding pairs, in poor quality habitats.

Animal Biodiversity and Conservation↗
USGS2004

Evaluation of ultrastructure and random effects band recovery models for estimating relationships between survival and harvest rates in exploited populations

Increased population survival rate after an episode of seasonal exploitation is considered a type of compensatory population response. Lack of an increase is interpreted as evidence that exploitation results in added annual mortality in the population. Despite its importance to management of exploited species, there are limited statistical techniques for comparing relative support for these two alternative models. For exploited bird species, the most common technique is to use a fixed effect, deterministic ultrastructure model incorporated into band recovery models to estimate the relationship between harvest and survival rate. We present a new likelihood-based technique within a framework that assumes that survival and harvest are random effects that covary through time. We conducted a Monte Carlo simulation study under this framework to evaluate the performance of these two techniques. The ultrastructure models performed poorly in all simulated scenarios, due mainly to pathological distributional properties. The random effects estimators and their associated estimators of precision had relatively small negative bias under most scenarios, and profile likelihood intervals achieved nominal coverage. We suggest that the random effects estimation method approach has many advantages compared to the ultrastructure models, and that evaluation of robustness and generalization to more complex population structures are topics for additional research. ?? 2004 Museu de Cie??ncies Naturals.

Animal Biodiversity and Conservation↗
USGS2004

Multi-state analysis of the impacts of avian pox on a population of Serins (Serinus serinus): The importance of estimating recapture rates

Disease is one of the evolutionary forces shaping populations. Recent studies have shown that epidemics like avian pox, malaria, or mycoplasmosis have affected passerine population dynamics, being responsible for the decline of some populations or disproportionately killing males and larger individuals and thus selecting for specific morphotypes. However, few studies have estimated the effects of an epidemic by following individual birds using the capture-recapture approach. Because avian pox can be diagnosed by direct examination of the birds, we are here able to analyze, using multistate models, the development and consequences of an avian pox epidemic affecting in 1996, a population of Serins (Serinus serinus) in northeastern Spain. The epidemics lasted from June to the end of November of 1996, with a maximum apparent prevalence rate > 30% in October. However, recapture rate of sick birds was very high (0.81, range 0.37-0.93) compared to that of healthy birds (0.21, range 0.020-32), which highly inflated apparent prevalence rate. This was additionally supported by the low predicted transition from the state of being uninfected to the state of being infected (0.03, SE 0.03). Once infected, Serin avian pox was very virulent with (15-day) survival rate of infected birds being of only 0.46 (SE 0.17) compared to that of healthy ones (0.87, SE 0.03). Probability of recovery from disease, provided that the bird survived the first two weeks, however, was very high (0.65, SE 0.25). The use of these estimates together with a simple model, allowed us to predict an asymptotic increase to prevalence of about 4% by the end of the outbreak period, followed by a sharp decline, with the only remaining infestations being infected birds that had not yet recovered. This is in contrast to the apparent prevalence of pox and stresses the need to estimate recapture rates when estimating population dynamics parameters. ?? 2004 Museu de Cie??ncies Naturals.

Animal Biodiversity and Conservation↗