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ABSTRACT: Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.
PLoS ONE 01/2013; 8(2):e55097. · 4.09 Impact Factor
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ABSTRACT: Twelve species of North American sea ducks (Tribe Mergini) winter off the eastern coast of the United States and Canada. Yet,
despite their seasonal proximity to urbanized areas in this region, there is limited information on patterns of wintering
sea duck habitat use. It is difficult to gather information on sea ducks because of the relative inaccessibility of their
offshore locations, their high degree of mobility, and their aggregated distributions. To characterize environmental conditions
that affect wintering distributions, as well as their geographic ranges, we analyzed count data on five species of sea ducks
(black scoters Melanitta nigra americana, surf scoters M. perspicillata, white-winged scoters M. fusca, common eiders Somateria mollissima, and long-tailed ducks Clangula hyemalis) that were collected during the Atlantic Flyway Sea Duck Survey for tenyears starting in the early 1990s. We modeled count
data for each species within ten-nautical-mile linear survey segments using a zero-inflated negative binomial model that included
four local-scale habitat covariates (sea surface temperature, mean bottom depth, maximum bottom slope, and a variable to indicate
if the segment was in a bay or not), one broad-scale covariate (the North Atlantic Oscillation), and a temporal correlation
component. Our results indicate that species distributions have strong latitudinal gradients and consistency in local habitat
use. The North Atlantic Oscillation was the only environmental covariate that had a significant (but variable) effect on the
expected count for all five species, suggesting that broad-scale climatic conditions may be directly or indirectly important
to the distributions of wintering sea ducks. Our results provide critical information on species–habitat associations, elucidate
the complicated relationship between the North Atlantic Oscillation, sea surface temperature, and local sea duck abundances,
and should be useful in assessing the impacts of climate change on seabirds.
KeywordsBayesian analysis-Climate change-Negative binomial model
Oecologia 04/2012; 163(4):893-902. · 3.41 Impact Factor
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ABSTRACT: Summary1. For wildlife researchers, disease specialists and policy analysts unfamiliar with the mathematical/statistical language of disease models, translation of probability statements into meaningful terms for disease research and control may be challenging. Markov chain models are powerful tools, applicable to the study of disease dynamics that allow straightforward calculations of easily interpretable metrics of interest including probabilities of infection/recovery, expected times to initial infection, duration of illness and life expectancies for susceptible and infected individuals.2. We present the basic principles and assumptions behind Markov chain modelling with an intuitive interpretation of parameter estimates and a step-by-step guide (including software code) for implementing this approach in the study of wildlife diseases. We also include an explanation of the estimation process necessary to implement Markov chain modelling (i.e. estimating the probability of state transitions between consecutive time steps) from typical survey data.3. We demonstrate the usefulness and ease of calculation of Markov chains through an example using a house finch Carpodacus mexicanus–Mycoplasma gallisepticum (MG) system. Our results show how semi-weekly transition estimates of susceptible and infected individuals can be used to estimate a wide array of seasonal disease-associated metrics.4. Markov chain modelling can provide a basic understanding of parameters estimated from wildlife disease studies, and can aid in understanding the implications of disease on wildlife populations and in evaluation of control measures. We envision this paper serving as an entry point into the extensive literature and potential applications of Markov chains in epidemiological modelling.
Methods in Ecology and Evolution 05/2010; 1(2):192 - 198. · 5.09 Impact Factor
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ABSTRACT: Twelve species of North American sea ducks (Tribe Mergini) winter off the eastern coast of the United States and Canada. Yet, despite their seasonal proximity to urbanized areas in this region, there is limited information on patterns of wintering sea duck habitat use. It is difficult to gather information on sea ducks because of the relative inaccessibility of their offshore locations, their high degree of mobility, and their aggregated distributions. To characterize environmental conditions that affect wintering distributions, as well as their geographic ranges, we analyzed count data on five species of sea ducks (black scoters Melanitta nigra americana, surf scoters M. perspicillata, white-winged scoters M. fusca, common eiders Somateria mollissima, and long-tailed ducks Clangula hyemalis) that were collected during the Atlantic Flyway Sea Duck Survey for ten years starting in the early 1990s. We modeled count data for each species within ten-nautical-mile linear survey segments using a zero-inflated negative binomial model that included four local-scale habitat covariates (sea surface temperature, mean bottom depth, maximum bottom slope, and a variable to indicate if the segment was in a bay or not), one broad-scale covariate (the North Atlantic Oscillation), and a temporal correlation component. Our results indicate that species distributions have strong latitudinal gradients and consistency in local habitat use. The North Atlantic Oscillation was the only environmental covariate that had a significant (but variable) effect on the expected count for all five species, suggesting that broad-scale climatic conditions may be directly or indirectly important to the distributions of wintering sea ducks. Our results provide critical information on species-habitat associations, elucidate the complicated relationship between the North Atlantic Oscillation, sea surface temperature, and local sea duck abundances, and should be useful in assessing the impacts of climate change on seabirds.
Oecologia 04/2010; 163(4):893-902. · 3.41 Impact Factor
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ABSTRACT: a b s t r a c t Conservation and management actions often have direct and indirect effects on a wide range of species. As such, it is important to evaluate the impacts that such actions may have on both target and non-target species within a region. Understanding how species richness and composition differ as a result of man-agement treatments can help determine potential ecological consequences. Yet it is difficult to estimate richness because traditional sampling approaches detect species at variable rates and some species are never observed. We present a framework for assessing management actions on biodiversity using a multi-species hierarchical model that estimates individual species occurrences, while accounting for imperfect detection of species. Our model incorporates species-specific responses to management treat-ments and local vegetation characteristics and a hierarchical component that links species at a commu-nity-level. This allows for comprehensive inferences on the whole community or on assemblages of interest. Compared to traditional species models, occurrence estimates are improved for all species, even for those that are rarely observed, resulting in more precise estimates of species richness (including spe-cies that were unobserved during sampling). We demonstrate the utility of this approach for conserva-tion through an analysis comparing bird communities in two geographically similar study areas: one in which white-tailed deer (Odocoileus virginianus) densities have been regulated through hunting and one in which deer densities have gone unregulated. Although our results indicate that species and assem-blage richness were similar in the two study areas, point-level richness was significantly influenced by local vegetation characteristics, a result that would have been underestimated had we not accounted for variability in species detection. Published by Elsevier Ltd.
01/2010;
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ABSTRACT: Population control through harvest has the potential to reduce the abundance of nuisance and invasive species. However, demographic structure and density-dependent processes can confound removal efforts and lead to undesirable consequences, such as overcompensation (an increase in abundance in response to harvest) and instability (population cycling or chaos). Recent empirical studies have demonstrated the potential for increased mortality (such as that caused by harvest) to lead to overcompensation and instability in plant, insect, and fish populations. We developed a general population model with juvenile and adult stages to help determine the conditions under which control harvest efforts can produce unintended outcomes. Analytical and simulation analyses of the model demonstrated that the potential for overcompensation as a result of harvest was significant for species with high fecundity, even when annual stage-specific survivorship values were fairly low. Population instability as a result of harvest occurred less frequently and was only possible with harvest strategies that targeted adults when both fecundity and adult survivorship were high. We considered these results in conjunction with current literature on nuisance and invasive species to propose general guidelines for assessing the risks associated with control harvest based on life history characteristics of target populations. Our results suggest that species with high per capita fecundity (over discrete breeding periods), short juvenile stages, and fairly constant survivorship rates are most likely to respond undesirably to harvest. It is difficult to determine the extent to which overcompensation and instability could occur during real-world removal efforts, and more empirical removal studies should be undertaken to evaluate population-level responses to control harvests. Nevertheless, our results identify key issues that have been seldom acknowledged and are potentially generic across taxa.
Ecological Applications 09/2009; 19(6):1585-95. · 5.10 Impact Factor
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ABSTRACT: Summary 1. Species richness is often used as a tool for prioritizing conservation action. One method for predicting richness and other summaries of community structure is to develop species-specific models of occurrence probability based on habitat or landscape characteristics. However, this approach can be challenging for rare or elusive species for which survey data are often sparse. 2. Recent developments have allowed for improved inference about community structure based on species-specific models of occurrence probability, integrated within a hierarchical modelling framework. This framework offers advantages to inference about species richness over typical approaches by accounting for both species-level effects and the aggregated effects of landscape composition on a community as a whole, thus leading to increased precision in estimates of species richness by improving occupancy estimates for all species, including those that were observed infrequently. 3. We developed a hierarchical model to assess the community response of breeding birds in the Hudson River Valley, New York, to habitat fragmentation and analysed the model using a Bayesian approach. 4. The model was designed to estimate species-specific occurrence and the effects of fragment area and edge (as measured through the perimeter and the perimeter/area ratio, P/A), while accounting for imperfect detection of species. 5. We used the fitted model to make predictions of species richness within forest fragments of variable morphology. The model revealed that species richness of the observed bird community was maximized in small forest fragments with a high P/A. However, the number of forest interior species, a subset of the community with high conservation value, was maximized in large fragments with low P/A. 6. Synthesis and applications. Our results demonstrate the importance of understanding the responses of both individual, and groups of species, to environmental heterogeneity while illustrating the utility of hierarchical models for inference about species richness for conservation. This framework can be used to investigate the impacts of land-use change and fragmentation on species or assemblage richness, and to further understand trade-offs in species-specific occupancy probabilities associated with landscape variability.
Journal of Applied Ecology 06/2009; 46(4):815 - 822. · 5.05 Impact Factor
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ABSTRACT: An intensive seven-year removal of adult, juvenile, and young-of-the-year smallmouth bass (Micropterus dolomieu) from a north temperate lake (Little Moose Lake, New York, USA) resulted in an increase in overall population abundance, primarily due to increased abundance of immature individuals. We developed a density-dependent, stage-structured model to examine conditions under which population control through harvest could result in the increase of a targeted species. Parameter values were derived from a 54-year data set collected from another north temperate lake (Lake Opeongo, Ontario, Canada) smallmouth bass population. Sensitivity analyses identified the demographic conditions that could lead to increased abundance in response to harvest. An increase in population abundance with harvest was most likely to occur when either (i) per capita recruitment at low levels of spawner abundance was large, juvenile survivorship was high, and maturation of age-4 and older juveniles was moderately high or (ii) per capita recruitment at low levels of spawner abundance was slightly lower, yet the maturation rate of age-3 juveniles and adult survivorship were high. Our modeling results together with empirical evidence further demonstrate the importance of overcompensation as a substantial factor to consider in efforts to regulate population abundance through harvest.Des captures intensives pendant sept ans des adultes, des juvéniles et des jeunes de l'année d'achigans à petite bouche (Micropterus dolomieu) dans un lac de la région tempérée nord (lac Little Moose, New York, É.-U.) ont eu pour effet un accroissement dans l'abondance globale de la population, principalement à cause d'une augmentation de l'abondance des individus immatures. Nous avons élaboré un modèle dépendant de la densité et structuré en fonction des stades afin d'évaluer les conditions sous lesquelles un contrôle de la population par la récolte peut entraîner une augmentation de l'espèce ciblée. Les valeurs des paramètres ont été tirées d'une banque de données couvrant 54 années et provenant d'une population d'achigans à petite bouche d'un autre lac de la région tempérée nord (lac Opeongo, Ontario, Canada). Des analyses de sensibilité ont permis d'identifier les conditions démographiques qui pourraient mener à une abondance accrue en réaction à la récolte. Une augmentation de l'abondance de la population en réaction à la récolte va plus vraisemblablement se produire quand ou bien (i) le recrutement par individu aux faibles densités de reproducteurs est important, la survie des juvéniles est élevée et la maturation des juvéniles d'âge 4 ou plus est modérément élevée ou alors (ii) le recrutement par individu aux faibles densités de reproducteurs est un peu plus faible, mais malgré tout le taux de maturation des juvéniles d'âge 3 et la survie des adultes sont élevés. Les résultats de notre modélisation combinés à des données empiriques démontrent de plus l'importance de la surcompensation comme facteur important à considérer lorsqu'on tente de contrôler l'abondance d'une population par des récoltes.
Canadian Journal of Fisheries and Aquatic Sciences 09/2008; 65(10):2279-2292. · 2.21 Impact Factor
