40 research outputs found
Data and code associated with “Supporting Adaptive Management with Ecological Forecasting: Chronic Wasting Disease in the Jackson Elk Herd”
No full textFinal_Data.zip contains several spreadsheets representing data collected by both the Wyoming Game and Fish Department and the US Fish and Wildlife Service for elk management: Jackson feedground census, 1998-2016; Harvest data, 1997-2015; Hunt area census, 1998-2016; Chronic wasting disease test results, 1998-2015. Final_Code.zip contains several Program R scripts written for data analysis and model fitting as described in the full associated article.Adaptive management has emerged as the prevailing approach for combining environmental research and management to advance science and policy. Adaptive management, as originally formulated by Carl Walters in 1986, depends on the use of Bayesian models to provide a framework to accumulate knowledge. The emergence of ecological forecasting using the Bayesian framework has provided robust tools and supports a new approach to informing adaptive management, which can be particularly useful in developing policy for managing infectious disease in wildlife. We used the potential infection of elk populations with chronic wasting disease in the Jackson Valley of Wyoming and the National Elk Refuge as a model system to show how Bayesian forecasting can support adaptive management in anticipation of management challenges. The core of our approach resembles the sex- and age-structured, discrete time models used to support management decisions on elk harvest throughout western North America. Our model differs by including stages for CWD infected and unaffected animals. We used data on population counts, sex and age classification, and CWD testing, as well as results from prior research, in a Bayesian statistical framework to predict model parameters and the number of animals in each age, sex, and disease stage over time. Initial forecasts suggested CWD may reach a mean prevalence in the population of 12%, but uncertainty in this forecast is large and we cannot rule out a mean forecasted prevalence as high as 20%. Using recruitment rates observed during the last two decades, the model predicted that a CWD prevalence of 7% in females would cause the population growth rate (l) to drop below 1, resulting in population declines even when female harvest was zero. The primary value of this ecological forecasting approach is to provide a framework to assimilate data with understanding of disease processes to enable continuous improvement in understanding the ecology of CWD and its management.Data collection was funded as part of management efforts by the Wyoming Game and Fish Department and the US Fish and Wildlife Service. Data analysis and work for publication was funded by the US Fish and Wildlife Service and the National Park Service
Effects of resource availability and social aggregation on the species richness of raccoon endoparasite infracommunities
No full textEcological correlates of pneumonia epizootics in bighorn sheep herds
No full text Bighorn sheep (Ovis canadensis) populations commonly experience pneumonia outbreaks caused by Pasteurella spp. that result in a partial or complete dieoff. Although several factors can contribute to Pasteurella spp. transmission or infectivity in bighorn sheep, to date the importance of such factors in population declines has not been rigorously examined. We evaluated the relationship between pneumonia-induced dieoffs in bighorn sheep and environmental and biological factors by analyzing demographic information for 99 herds across the species' geographic range. Our analysis revealed that 88% of pneumonia-induced dieoffs occurred at or within 3 years of peak population numbers, which implies that density-dependent forces such as food shortage or stress contribute to bighorns' susceptibility to pneumonia. There were few differences in the growth rates of dieoff and non-dieoff populations, suggesting that pneumonia did not manifest itself demographically prior to an outbreak. On average, abundance of lambs was most dramatically reduced post outbreak (66%) relative to that of either rams (35%) or ewes (42%). Deviations in normal precipitation and temperature regimes were not associated with the onset of pneumonia outbreaks, but herds found in proximity to domestic sheep tended to be more susceptible to dieoff. Our results suggest that bighorn sheep herds are rendered vulnerable to pneumonia principally through density-dependent factors, as well as through horizontal transmission of Pasteurella spp. from domestic sheep serving as reservoir hosts. </jats:p
Factors associated with alien plant richness, cover and composition differ in tropical island forests
No full textGenetic variability and viral seroconversion in an outcrossing vertebrate population
No full textInverse correlations between genetic variability and parasitism are important concerns for conservation biologists. We examined correlations between neutral genetic variability and the presence of antibodies to canine distemper virus (CDV) and feline parvovirus (FPV) in a free-ranging population of raccoons. Over 3 years there was a strong relationship between age and seroprevalence rates. Most young animals were seronegative to CDV and FPV, but the oldest age class was greater than 80 per cent seropositive to both viruses. CDV-seropositive animals had greater heterozygosity and lower measures of inbreeding compared with CDV-seronegative animals. This relationship was strongest among the youngest animals and did not occur during a 1 year CDV epidemic. In contrast, FPV-seropositive animals only had significantly lower measures of inbreeding in 1 year, perhaps because FPV-associated mortality is relatively low or primarily occurs among very young individuals that were under-represented in our sampling. These results suggest that even in large outcrossing populations, animals with lower heterozygosity and higher measures of inbreeding are less likely to successfully mount an immune response when challenged by highly pathogenic parasites.</jats:p
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CreechTylerFisheriesWildlifeUsingNetworkTheory.pdf
No full textConnectivity models using empirically-derived
landscape resistance maps can predict potential
linkages among fragmented animal and plant populations.
However, such models have rarely been used to
guide systematic decision-making, such as identifying
the most important habitat patches and dispersal corridors
to protect or restore in order to maximize regional
connectivity. Combining resistance models with network
theory offers one means of prioritizing management
for connectivity, and we applied this approach to a
metapopulation of desert bighorn sheep (Ovis canadensis
nelsoni) in the Mojave Desert of the southwestern
United States. We used a genetic-based landscape
resistance model to construct network models of genetic
connectivity (potential for gene flow) and demographic connectivity (potential for colonization of empty habitat
patches), which may differ because of sex-biased
dispersal in bighorn sheep. We identified high-priority
habitat patches and corridors and found that the type of
connectivity and the network metric used to quantify
connectivity had substantial effects on prioritization
results, although some features ranked highly across all
combinations. Rankings were also sensitive to our
empirically-derived estimates of maximum effective
dispersal distance, highlighting the importance of this
often-ignored parameter. Patch-based analogs of our
network metrics predicted both neutral and mitochondrial
genetic diversity of 25 populations within the study
area. This study demonstrates that network theory can
enhance the utility of landscape resistance models as
tools for conservation, but it is critical to consider the
implications of sex-biased dispersal, the biological
relevance of network metrics, and the uncertainty
associated with dispersal range and behavior when
using this approach.Keywords: Graph theory, Gene flow, Dispersal, Connectivity, Colonization, Extinction, Habitat patch, Landscape resistance, Fragmented populatio
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Predicting diet quality and genetic diversity of a desert-adapted ungulate with NDVI
No full textDiet quality influences ungulate population dynamics but is difficult to measure at fine temporal or spatial resolution using field-intensive methods such as fecal nitrogen (FN). Increasingly, the remotely sensed vegetation index NDVI is used to represent potential ungulate diet quality, but NDVI's relationship with diet quality has yet to be examined for herbivores in desert environments. We evaluated how strongly NDVI was associated with diet quality of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert using FN data from multiple years and populations. We considered effects of temporal resolution, geographic variability, and NDVI spatial summary statistic on the NDVI-diet quality relationship. NDVI was more reliably associated with diet quality over the entire growing season than with instantaneous diet quality for a population. NDVI was also positively associated with population genetic diversity, a proxy for long-term, population-level effects of diet quality. We conclude that NDVI is a useful diet quality indicator for Mojave Desert bighorn sheep and potentially other desert ungulates. However, it may not reliably track diet quality if NDVI data are too spatially coarse to detect microhabitats providing high-quality forage, or if diet is strongly influenced by forage items that are weakly correlated with landscape greenness.Keywords: Mojave Desert, Forage, Bighorn sheep, Fecal nitroge
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CreechPredictingDietQualityAppendixA.pdf
No full textDiet quality influences ungulate population dynamics but is difficult to measure at fine temporal or spatial resolution using field-intensive methods such as fecal nitrogen (FN). Increasingly, the remotely sensed vegetation index NDVI is used to represent potential ungulate diet quality, but NDVI's relationship with diet quality has yet to be examined for herbivores in desert environments. We evaluated how strongly NDVI was associated with diet quality of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert using FN data from multiple years and populations. We considered effects of temporal resolution, geographic variability, and NDVI spatial summary statistic on the NDVI-diet quality relationship. NDVI was more reliably associated with diet quality over the entire growing season than with instantaneous diet quality for a population. NDVI was also positively associated with population genetic diversity, a proxy for long-term, population-level effects of diet quality. We conclude that NDVI is a useful diet quality indicator for Mojave Desert bighorn sheep and potentially other desert ungulates. However, it may not reliably track diet quality if NDVI data are too spatially coarse to detect microhabitats providing high-quality forage, or if diet is strongly influenced by forage items that are weakly correlated with landscape greenness.Keywords: Bighorn sheep, Mojave Desert, Fecal nitrogen, ForageKeywords: Bighorn sheep, Mojave Desert, Fecal nitrogen, Forag
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Using network theory to prioritize management in a desert bighorn sheep metapopulation
No full textConnectivity models using empirically-derived landscape resistance maps can predict potential linkages among fragmented animal and plant populations. However, such models have rarely been used to guide systematic decision-making, such as identifying the most important habitat patches and dispersal corridors to protect or restore in order to maximize regional connectivity. Combining resistance models with network theory offers one means of prioritizing management for connectivity, and we applied this approach to a metapopulation of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert of the southwestern United States. We used a genetic-based landscape resistance model to construct network models of genetic connectivity (potential for gene flow) and demographic connectivity (potential for colonization of empty habitat patches), which may differ because of sex-biased dispersal in bighorn sheep. We identified high-priority habitat patches and corridors and found that the type of connectivity and the network metric used to quantify connectivity had substantial effects on prioritization results, although some features ranked highly across all combinations. Rankings were also sensitive to our empirically-derived estimates of maximum effective dispersal distance, highlighting the importance of this often-ignored parameter. Patch-based analogs of our network metrics predicted both neutral and mitochondrial genetic diversity of 25 populations within the study area. This study demonstrates that network theory can enhance the utility of landscape resistance models as tools for conservation, but it is critical to consider the implications of sex-biased dispersal, the biological relevance of network metrics, and the uncertainty associated with dispersal range and behavior when using this approach.Keywords: Gene flow, Colonization, Connectivity, Dispersal, Graph theory, Extinction, Habitat patch, Fragmented population, Landscape resistanc
