Sutherland, Chris

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Ecology and Evolutionary Biology
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Now showing 1 - 7 of 7
  • Publication
    Visual Head Counts: A Promising Method for Efficient Monitoring of Diamondback Terrapins
    (2019-01-01) Levasseur, Patricia; Sterrett, Sean; Sutherland, Chris
    Determining the population status of the diamondback terrapin (Malaclemys terrapin spp.) is challenging due to their ecology and limitations associated with traditional sampling methods. Visual counting of emergent heads offers a promising, efficient, and non-invasive method for generating abundance estimates of terrapin populations across broader spatial scales than has been achieved using capture–recapture, and can be used to quantify determinants of spatial variation in abundance. We conducted repeated visual head count surveys along the shoreline of Wellfleet Bay in Wellfleet, Massachusetts, and analyzed the count data using a hierarchical modeling framework designed specifically for repeated count data: the N-mixture model. This approach allows for simultaneous modeling of imperfect detection to generate estimates of true terrapin abundance. Detection probability was lowest when temperatures were coldest and when wind speed was highest. Local abundance was on average higher in sheltered sites compared to exposed sites and declined over the course of the sampling season. We demonstrate the utility of pairing visual head counts and N-mixture models as an efficient method for estimating terrapin abundance and show how the approach can be used to identifying environmental factors that influence detectability and distribution.
  • Publication
    A demographic, spatially explicit patch occupancy model of metapopulation dynamics and persistence
    (2014-11-01) Sutherland, Chris; Elston, D.; Lambin, X.
    Patch occupancy models are extremely important and popular tools forunderstanding the dynamics, and predicting the persistence, of spatially structuredpopulations. Typically this endeavor is facilitated either by models from classic metapopulationtheory focused on spatially explicit, dispersal-driven colonization–extinction dynamicsand generally assuming perfect detection, or by more recent hierarchical site occupancymodels that account for imperfect detection but rarely include spatial effects, such as dispersal,explicitly. Neither approach explicitly considers local demographics in a way that can be usedfor future projections. However, despite being arguably of equal importance, dispersal andconnectivity, local demography, and imperfect detection are rarely modeled explicitly andsimultaneously. Understanding the spatiotemporal occurrence patterns of spatially structuredpopulations and making biologically realistic long-term predictions of persistence wouldbenefit from the simultaneous treatment of space, demography, and detectability. Weintegrated these key ideas in a tractable and intuitive way to develop a demographic andspatially realistic patch occupancy model that incorporates components of dispersal, localdemographic stage-structure, and detectability. By explicitly relating stage-specific abundancesto measurable patch properties, biologically realistic projections of long-term metapopulationdynamics could be made. We applied our model to data from a naturally fragmentedpopulation of water voles Arvicola amphibius to describe observed patch occupancy dynamicsand to investigate long-term persistence under scenarios of elevated stage-specific localextinction. Accounting for biases induced by imperfect detection, we were able to estimate:stable, and higher than observed metapopulation occupancy; high rates of patch turnover andstage-specific colonization and extinction rates ( juvenile and adult, respectively); and juveniledispersal distances (average 2.10 km). We found that metapopulation persistence in thepresence of elevated extinction risk differed depending on which life stage was exposed, andwas more sensitive to elevated juvenile rather than adult extinction risk. Predictions ofpersistence when dynamics are stage-specific suggest that metapopulations may be moreresilient to changes in the environment than predicted when relationships are based on patchsize approximations rather than population sizes. Our approach allows explicit considerationof local dynamics and dispersal in spatially structured and stage-structured populations,provides a more detailed mechanistic understanding of metapopulation functioning, and canbe used to investigate future extinction risk under biologically meaningful scenarios.
  • Publication
    Spatial Capture–Recapture: A Promising Method for Analyzing Data Collected Using Artificial Cover Objects
    (2016-01-01) Sutherland, Chris; Mun'Oz, David; Miller, David; Grant, Evan
    Spatial capture–recapture (SCR) is a relatively recent development in ecological statistics that provides a spatial context for estimating abundance and space use patterns, and improves inference about absolute population density. SCR has been applied to individual encounter data collected noninvasively using methods such as camera traps, hair snares, and scat surveys. Despite the widespread use of capture based surveys to monitor amphibians and reptiles, there are few applications of SCR in the herpetological literature. We demonstrate the utility of the application of SCR for studies of reptiles and amphibians by analyzing capture–recapture data from Red-Backed Salamanders, Plethodon cinereus, collected using artificial cover boards. Using SCR to analyze spatial encounter histories of marked individuals, we found evidence that density differed little among four sites within the same forest (on average, 1.59 salamanders/m2) and that salamander detection probability peaked in early October (Julian day 278) reflecting expected surface activity patterns of the species. The spatial scale of detectability, a measure of space use, indicates that the home range size for this population of Red-Backed Salamanders in autumn was 16.89 m2. Surveying reptiles and amphibians using artificial cover boards regularly generates spatial encounter history data of known individuals, which can readily be analyzed using SCR methods, providing estimates of absolute density and inference about the spatial scale of habitat use.
  • Publication
    Modelling non-Euclideanmovement and landscape connectivity in highly structured ecological networks
    (2014-12-30) Sutherland, Chris; Fuller, Angela; Royle, J.
    1. Movement is influenced by landscape structure, configuration and geometry, but measuring distance as perceived by animals poses technical and logistical challenges. Instead, movement is typically measured using Euclidean distance, irrespective of location or landscape structure, or is based on arbitrary cost surfaces. Arecently proposed extension of spatial capture-recapture (SCR)models resolves this issue using spatial encounterhistories of individuals to calculate least-cost paths (ecological distance: Ecology, 94, 2013, 287) thereby relaxingthe Euclidean assumption. We evaluate the consequences of not accounting for movement heterogeneity whenestimating abundance in highly structured landscapes, and demonstrate the value of this approach for estimatingbiologically realistic space-use patterns and landscape connectivity.2. We simulated SCR data in a riparian habitat network, using the ecological distance model under a range of scenarios where space-use in and around the landscape was increasingly associated with water (i.e. increasingly less Euclidean). To assess the influence of miscalculating distance on estimates of population size, we compared the results from the ecological and Euclidean distance based models. We then demonstrate that the ecologicaldistance model can be used to estimate home range geometry when space use is not symmetrical. Finally, we providea method for calculating landscape connectivity based on modelled species-landscape interactions generated from capture-recapture data.3. Using ecological distance always produced unbiased estimates of abundance. Explicitly modelling the strength of the species-landscape interaction provided a direct measure of landscape connectivity and better characterized true home range geometry. Abundance under the Euclidean distance model was increasingly (negatively) biasedas space use was more strongly associated with water and, because home ranges are assumed to be symmetrical, produced poor characterisations of home range geometry and no information about landscape connectivity.4. The ecological distance SCR model uses spatially indexed capture-recapture data to estimate how activity patterns are influenced by landscape structure. As well as reducing bias in estimates of abundance, this approach provides biologically realistic representations of home range geometry, and direct information about species landscape interactions. The incorporation of both structural (landscape) and functional (movement) components of connectivity provides a direct measure of species-specific landscape connectivity.
  • Publication
    Spatial capture–recapture models allowing Markovian transience or dispersal
    (2016-01-01) Royle, J.; Fuller, Angela; Sutherland, Chris
    Spatial capture–recapture (SCR) models are a relatively recent development in quantitative ecology, and they are becoming widely used to model density in studies of animal populations using camera traps, DNA sampling and other methods which produce spatially explicit individual encounter information. One of the core assumptions of SCR models is that individuals possess home ranges that are spatially stationary during the sampling period. For many species, this assumption is unlikely to be met and, even for species that are typically territorial, individuals may disperse or exhibit transience at some life stages. In this paper we first conduct a simulation study to evaluate the robustness of estimators of density under ordinary SCR models when dispersal or transience is present in the population. Then, using both simulated and real data, we demonstrate that such models can easily be described in the BUGS language providing a practical framework for their analysis, which allows us to evaluate movement dynamics of species using capture–recapture data. We find that while estimators of density are extremely robust, even to pathological levels of movement (e.g., complete transience), the estimator of the spatial scale parameter of the encounter probability model is confounded with the dispersal/transience scale parameter. Thus, use of ordinary SCR models to make inferences about density is feasible, but interpretation of SCR model parameters in relation to movement should be avoided. Instead, when movement dynamics are of interest, such dynamics should be parameterized explicitly in the model.
  • Publication
    Accounting for false positive detection error induced by transient individuals
    (2013-11-01) Sutherland, Chris; Elston, D; Lambin, X.
    Context. In metapopulations, colonisation is the result of dispersal from neighbouring occupied patches, typically juveniles dispersing from natal to breeding sites. When occupancy dynamics are dispersal driven, occupancy should refer to the presence of established, breeding populations. The detection of transient individuals at sites that are, by definition, unoccupied (i.e. false positive detections), may result in misleading conclusions about metapopulation dynamics. Until recently, the issue of false positives has been considered negligible and current efforts to account for such error have beenrestricted to the context of species misidentification. However, the detection of transient individuals visiting multiple siteswhile dispersing is a distinct source of false positives that can bias estimates of occupancy because visited sites do not contribute to metapopulation dynamics in the same way as do sites occupied by established, reproducing populations. Although transient-induced false positive error presents a challenge to occupancy studies aiming to account for all sources of detection error and estimate occupancy without bias, accounting for it has received little attention.Aims. Using a novel application of an existing occupancy model, we sought to account for false positives that result fromtransient individuals being observed at truly unoccupied sites (i.e. where no establishment has occurred).Methods. We applied a Bayesian multi-season occupancy model correcting for false negative and false positive errors, to3 years of detection or non-detection data from a metapopulation of water voles, Arvicola amphibious, in which both types ofpatch-state misclassification are suspected.Key results.We provide evidence that transient individuals can cause false positive detection errors.Wethen demonstratethe flexibility of the occupancy model to account for both false negative and false positive detection errors beyond the typicalapplication to species misidentification. Accounting for both types of observation error reduces the bias in estimates ofoccupancy and avoids misleading conclusions about the status of (meta) populations by allowing for the distinction to bemade between resident and transient occupancy.Conclusion. In many species, transience may result in patch-state misclassification which needs to be accounted for so asto draw correct inference about metapopulation status. Making the distinction between occupancy by established populationsand visitation by transients will influence how we interpret patch occupancy dynamics, with important implications for themanagement of wildlife.Implications. The ability to estimate occupancy free of bias induced by false positive detections can help ensure thatdownward trends in occupancy are detected despite such declines being accompanied by increasing frequency of transientsassociated with, for example, reductions in mate availability or failure to establish. Our approach can be applied to anyoccupancy study in which false positive detections are suspected because of the behaviour of the focal species.
  • Publication
    Likelihood analysis of spatial capture-recapture models for stratified or class structured populations
    (2015-02-12) Royle, J.; Sutherland, Chris; Fuller, Angela; Sun, Catherine
    We develop a likelihood analysis framework for fitting spatial capture-recapture (SCR) models to data collected on class structured or stratified populations. Our interest is motivated by thenecessity of accommodating the problem of missing observations of individual class membership. This is particularly problematic in SCR data arising from DNA analysis of scat, hair or other material, whichfrequently yields individual identity but fails to identify the sex. Moreover, this can represent a large fraction of the data and, given the typically small sample sizes of many capture-recapture studies based on DNA information, utilization of the data with missing sex information is necessary. We develop the class structured likelihood for the case of missing covariate values, and then we address the scaling of the likelihood so that models with and without class structured parameters can be formally compared regardless of missing values.We apply our class structured model to black bear data collected in New York in which sex could be determined for only 62 of 169 uniquely identified individuals. The models containingsex-specificity of both the intercept of the SCR encounter probability model and the distance coefficient, and including a behavioral response are strongly favored by log-likelihood. Estimated population sex ratio is strongly influenced by sex structure in model parameters illustrating the importance of rigorous modeling of sex differences in capture-recapture models.