Browsing by Author "Augustine, Ben C."

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    Consequences of severe habitat fragmentation on density, genetics, and spatial capture-recapture analysis of a small bear population
    Murphy, Sean M.; Augustine, Ben C.; Ulrey, Wade A.; Guthrie, Joseph M.; Scheick, Brian K.; McCown, J. Walter; Cox, John J. (PLOS, 2017-07-24)
    Loss and fragmentation of natural habitats caused by human land uses have subdivided several formerly contiguous large carnivore populations into multiple small and often isolated subpopulations, which can reduce genetic variation and lead to precipitous population declines. Substantial habitat loss and fragmentation from urban development and agriculture expansion relegated the Highlands-Glades subpopulation (HGS) of Florida, USA, black bears (Ursus americanus floridanus) to prolonged isolation; increasing human land development is projected to cause ≥ 50% loss of remaining natural habitats occupied by the HGS in coming decades. We conducted a noninvasive genetic spatial capture-recapture study to quantitatively describe the degree of contemporary habitat fragmentation and investigate the consequences of habitat fragmentation on population density and genetics of the HGS. Remaining natural habitats sustaining the HGS were significantly more fragmented and patchier than those supporting Florida’s largest black bear subpopulation. Genetic diversity was low (AR = 3.57; HE = 0.49) and effective population size was small (NE = 25 bears), both of which remained unchanged over a period spanning one bear generation despite evidence of some immigration. Subpopulation density (0.054 bear/km2) was among the lowest reported for black bears, was significantly female-biased, and corresponded to a subpopulation size of 98 bears in available habitat. Conserving remaining natural habitats in the area occupied by the small, genetically depauperate HGS, possibly through conservation easements and government land acquisition, is likely the most important immediate step to ensuring continued persistence of bears in this area. Our study also provides evidence that preferentially placing detectors (e.g., hair traps or cameras) primarily in quality habitat across fragmented landscapes poses a challenge to estimating density-habitat covariate relationships using spatial capture-recapture models. Because habitat fragmentation and loss are likely to increase in severity globally, further investigation of the influence of habitat fragmentation and detector placement on estimation of this relationship is warranted.
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    The effects of habitat, climate, and Barred Owls on long-term demography of Northern Spotted Owls
    Dugger, Katie M.; Forsman, Eric D.; Franklin, Alan B.; Davis, Raymond J.; White, Gary C.; Schwarz, Carl J.; Burnham, Kenneth P.; Nichols, James D.; Hines, James E.; Yackulic, Charles B.; Doherty, Paul F., Jr.; Bailey, Larissa L.; Clark, Darren A.; Ackers, Steven H.; Andrews, Lawrence S.; Augustine, Ben C.; Biswell, Brian L.; Blakesley, Jennifer; Carlson, Peter C.; Clement, Matthew J.; Diller, Lowell V.; Glenn, Elizabeth M.; Green, Adam; Gremel, Scott A.; Herter, Dale R.; Higley, J. Mark; Hobson, Jeremy; Horn, Rob B.; Huyvaert, Kathryn P.; McCafferty, Christopher; McDonald, Trent; McDonnell, Kevin; Olson, Gail S.; Reid, Janice A.; Rockweit, Jeremy; Ruiz, Viviana; Saenz, Jessica; Sovern, Stan G. (2016-02)
    Estimates of species' vital rates and an understanding of the factors affecting those parameters over time and space can provide crucial information for management and conservation. We used mark-recapture, reproductive output, and territory occupancy data collected during 1985-2013 to evaluate population processes of Northern Spotted Owls (Strix occidentalis caurina) in 11 study areas in Washington, Oregon, and northern California, USA. We estimated apparent survival, fecundity, recruitment, rate of population change, and local extinction and colonization rates, and investigated relationships between these parameters and the amount of suitable habitat, local and regional variation in meteorological conditions, and competition with Barred Owls (Strix varia). Data were analyzed for each area separately and in a meta-analysis of all areas combined, following a strict protocol for data collection, preparation, and analysis. We used mixed effects linear models for analyses of fecundity, Cormack-Jolly-Seber open population models for analyses of apparent annual survival (phi), and a reparameterization of the Jolly-Seber capture-recapture model (i.e. reverse Jolly-Seber; RJS) to estimate annual rates of population change (lambda(RJS)) and recruitment. We also modeled territory occupancy dynamics of Northern Spotted Owls and Barred Owls in each study area using 2-species occupancy models. Estimated mean annual rates of population change (lambda) suggested that Spotted Owl populations declined from 1.2% to 8.4% per year depending on the study area. The weighted mean estimate of lambda for all study areas was 0.962 (+/- 0.019 SE; 95% CI: 0.925-0.999), indicating an estimated range-wide decline of 3.8% per year from 1985 to 2013. Variation in recruitment rates across the range of the Spotted Owl was best explained by an interaction between total winter precipitation and mean minimum winter temperature. Thus, recruitment rates were highest when both total precipitation (29 cm) and minimum winter temperature (-9.5 degrees C) were lowest. Barred Owl presence was associated with increased local extinction rates of Spotted Owl pairs for all 11 study areas. Habitat covariates were related to extinction rates for Spotted Owl pairs in 8 of 11 study areas, and a greater amount of suitable owl habitat was generally associated with decreased extinction rates. We observed negative effects of Barred Owl presence on colonization rates of Spotted Owl pairs in 5 of 11 study areas. The total amount of suitable Spotted Owl habitat was positively associated with colonization rates in 5 areas, and more habitat disturbance was associated with lower colonization rates in 2 areas. We observed strong declines in derived estimates of occupancy in all study areas. Mean fecundity of females was highest for adults (0.309 +/- 0.027 SE), intermediate for 2-yr-olds (0.179 +/- 0.040 SE), and lowest for 1-yr-olds (0.065 +/- 0.022 SE). The presence of Barred Owls and habitat covariates explained little of the temporal variation in fecundity in most study areas. Climate covariates occurred in competitive fecundity models in 8 of 11 study areas, but support for these relationships was generally weak. The fecundity meta-analysis resulted in 6 competitive models, all of which included the additive effects of geographic region and annual time variation. The 2 top-ranked models also weakly supported the additive negative effects of the amount of suitable core area habitat, Barred Owl presence, and the amount of edge habitat on fecundity. We found strong support for a negative effect of Barred Owl presence on apparent survival of Spotted Owls in 10 of 11 study areas, but found few strong effects of habitat on survival at the study area scale. Climate covariates occurred in top or competitive survival models for 10 of 11 study areas, and in most cases the relationships were as predicted; however, there was little consistency among areas regarding the relative importance of specific climate covariates. In contrast, meta-analysis results suggested that Spotted Owl survival was higher across all study areas when the Pacific Decadal Oscillation (PDO) was in a warming phase and the Southern Oscillation Index (SOI) was negative, with a strongly negative SOI indicative of El Nino events. The best model that included the Barred Owl covariate (BO) was ranked 4th and also included the PDO covariate, but the BO effect was strongly negative. Our results indicated that Northern Spotted Owl populations were declining throughout the range of the subspecies and that annual rates of decline were accelerating in many areas. We observed strong evidence that Barred Owls negatively affected Spotted Owl populations, primarily by decreasing apparent survival and increasing local territory extinction rates. However, the amount of suitable owl habitat, local weather, and regional climatic patterns also were related to survival, occupancy (via colonization rate), recruitment, and, to a lesser extent, fecundity, although there was inconsistency in regard to which covariates were important for particular demographic parameters or across study areas. In the study areas where habitat was an important source of variation for Spotted Owl demographics, vital rates were generally positively associated with a greater amount of suitable owl habitat. However, Barred Owl densities may now be high enough across the range of the Northern Spotted Owl that, despite the continued management and conservation of suitable owl habitat on federal lands, the long-term prognosis for the persistence of Northern Spotted Owls may be in question without additional management intervention. Based on our study, the removal of Barred Owls from the Green Diamond Resources (GDR) study area had rapid, positive effects on Northern Spotted Owl survival and the rate of population change, supporting the hypothesis that, along with habitat conservation and management, Barred Owl removal may be able to slow or reverse Northern Spotted Owl population declines on at least a localized scale.
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    Integrating multiple genetic detection methods to estimate population density of social and territorial carnivores
    Murphy, Sean M.; Augustine, Ben C.; Adams, Jennifer R.; Waits, Lisette P.; Cox, John J. (Ecological Society of America, 2018-10)
    Spatial capture-recapture models can produce unbiased estimates of population density, but sparse detection data often plague studies of social and territorial carnivores. Integrating multiple types of detection data can improve estimation of the spatial scale parameter (sigma), activity center locations, and density. Noninvasive genetic sampling is effective for detecting carnivores, but social structure and territoriality could cause differential detectability among population cohorts for different detection methods. Using three observation models, we evaluated the integration of genetic detection data from noninvasive hair and scat sampling of the social and territorial coyote (Canis latrans). Although precision of estimated density was improved, particularly if sharing sigma between detection methods was appropriate, posterior probabilities of sigma and posterior predictive checks supported different sigma for hair and scat observation models. The resulting spatial capture-recapture model described a scenario in which scat-detected individuals lived on and around scat transects, whereas hair-detected individuals had larger sigma and mostly lived off of the detector array, leaving hair but not scat samples. A more supported interpretation is that individual heterogeneity in baseline detection rates (lambda(0)) was inconsistent between detection methods, such that each method disproportionately detected different population cohorts. These findings can be attributed to the sociality and territoriality of canids: Residents may be more likely to strategically mark territories via defecation (scat deposition), and transients may be more likely to exhibit rubbing (hair deposition) to increase mate attraction. Although this suggests that reliance on only one detection method may underestimate population density, integrating multiple sources of genetic detection data may be problematic for social and territorial carnivores. These data are typically sparse, modeling individual heterogeneity in lambda(0) and/or sigma with sparse data is difficult, and positive bias can be introduced in density estimates if individual heterogeneity in detection parameters that is inconsistent between detection methods is not appropriately modeled. Previous suggestions for assessing parameter consistency of sigma between detection methods using Bayesian model selection algorithms could be confounded by individual heterogeneity in lambda(0) in noninvasive detection data. We demonstrate the usefulness of augmenting those approaches with calibrated posterior predictive checks and plots of the posterior density of activity centers for key individuals.
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    Leveraging Partial Identity Information in Spatial Capture-Recapture Studies with Applications to Remote Camera and Genetic Capture-Recapture Surveys
    Augustine, Ben C. (Virginia Tech, 2018-04-03)
    Noninvasive methods for monitoring wildlife species have revolutionized the way population parameters, such as population density and survival and recruitment rates, are estimated while accounting for imperfect detection using capture-recapture models. Reliable estimates of these parameters are vital information required for making sound conservation decisions; however to date, noninvasive sampling methods have been of limited use for a vast number of species which are difficult to identify to the individual level–a general requirement of capture-recapture models. Capture-recapture models that utilize partial identity information have only recently been introduced and have not been extended to most types of noninvasive sampling scenarios in a manner that uses the spatial location where noninvasive samples were collected to further inform complete identity (i.e. spatial partial identity models). Herein, I extend the recently introduced spatial partial identity models to the noninvasive methods of remote cameras for species that are difficult to identify from photographs and DNA from hair or scat samples. The ability of these novel models to improve parameter estimation and extend study design options are investigated and the methods are made accessible to applied ecologists via statistical software. This research has the potential to greatly improve wildlife conservation decisions by improving our knowledge of parameters related to population structure and dynamics that inform those decisions. Unfortunately, many species of conservation concern (e.g., Florida panthers, Andean bears) are managed without having the necessary information on population status or trends, largely a result of the cost and difficulty of studying species in decline and because of the difficulty of applying statistical models to sparse data, which can produce imprecise and biased estimates of population parameters. By leveraging partial identity information in noninvasive samples, the models I developed will improve these parameter estimates and allow noninvasive methods to be used for more species, leading to more informed conservation decisions, and a more efficient allocation of conservation resources across species and populations.
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    Long‐term monitoring of ocelot densities in Belize
    Satter, Christopher B.; Augustine, Ben C.; Harmsen, Bart J.; Foster, Rebecca J.; Sanchez, Emma E.; Wultsch, Claudia; Davis, Miranda L.; Kelly, Marcella J. (The Wildlife Society, 2019-01)
    Ocelots (Leopardus pardalis) are listed as least concern on the International Union for Conservation of Nature (IUCN) Red list of Threatened Species, yet we lack knowledge on basic demographic parameters across much of the ocelot's geographic range, including population density. We used camera‐trapping methodology and spatially explicit capture‐recapture (SECR) models with sex‐specific detection function parameters to estimate ocelot densities across 7 field sites over 1 to 12 years (from data collected during 2002–2015) in Belize, Central America. Ocelot densities in the broadleaf rainforest sites ranged between 7.2 and 22.7 ocelots/100 km2, whereas density in the pine (Pinus spp.) forest site was 0.9 ocelots/100 km2. Applying an inverse‐variance weighted average over all years for each broadleaf site increased precision and resulted in average density ranging from 8.5 to 13.0 ocelots/100 km2. Males often had larger movement parameter estimates and higher detection probabilities at their activity centers than females. In most years, the sex ratio was not significantly different from 50:50, but the pooled sex ratio estimated using an inverse weighted average over all years indicated a female bias in 1 site, and a male bias in another. We did not detect any population trends as density estimates remained relatively constant over time; however, the power to detect such trends was generally low. Our SECR density estimates were lower but more precise than previous estimates and indicated population stability for ocelots in Belize.
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    Sex-specific population dynamics of ocelots in Belize using open population spatial capture-recapture
    Satter, Christopher B.; Augustine, Ben C.; Harmsen, Bart J.; Foster, Rebecca J.; Kelly, Marcella J. (Ecological Society of America, 2019-07)
    We used open population, spatial capture-recapture (SCR) models to estimate sex-specific density, survival, per capita recruitment, and population growth rate of ocelots (Leopardus pardalis) at five sites in Belize with up to 12 yr of data per site. Open population SCR models enabled us to separate survival and recruitment from migration using an ecologically realistic, spatially explicit movement model. Yearly survival probability across 4 broadleaf forest sites was estimated at 0.73-0.84 for males and 0.81-0.87 for females, with no clear indication of sex differences. Yearly per capita recruitment was estimated across four broadleaf forest sites at 0.06-0.08 recruits/N for males and 0.09-0.12 recruits/N for females, again with no clear indication of sex differences. At a pine forest site with a population comprised largely of males, survival and recruitment estimates were similar to the broadleaf sites. Population densities in the broadleaf forest sites ranged from 6.5 to 14.7 ocelots/100 km(2), and 0.9-2.5 ocelots/100 km(2) in the pine forest site, with strong evidence of a female-biased sex ratio in the broadleaf sites and a male-biased sex ratio in the pine forest site. We also found strong evidence that female within-year space use at the broadleaf sites was smaller than that of males, and that within-year space use at the pine forest site was larger than that at broadleaf sites. Between-year home-range relocation at broadleaf sites was of a similar spatial scale as within-year space use, consistent with philopatry. We found evidence of a small population decline (posterior probability > 0.9) at two of four broadleaf sites; however, given the level of uncertainty about decline magnitudes, we suggest continued monitoring of these sites to increase site-years and gain further precision on population growth rate estimates. Estimating demographic parameters at large spatial and temporal scales is important for establishing reliable baseline estimates for future comparison and for understanding changes in population dynamics. Long-term data sets like those we collected are of particular importance for long-lived species living at low densities and large spatial scales, where not many individuals are exposed to capture in any one year.
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    Spatial capture-recapture for categorically marked populations with an application to genetic capture-recapture
    Augustine, Ben C.; Royle, J. Andrew; Murphy, Sean M.; Chandler, Richard B.; Cox, John J.; Kelly, Marcella J. (Ecological Society of America, 2019-04)
    Recently introduced unmarked spatial capture-recapture (SCR), spatial mark-resight (SMR), and 2-flank spatial partial identity models (SPIMs) extend the domain of SCR to populations or observation systems that do not always allow for individual identity to be determined with certainty. For example, some species do not have natural marks that can reliably produce individual identities from photographs, and some methods of observation produce partial identity samples as is the case with remote cameras that sometimes produce single-flank photographs. Unmarked SCR, SMR, and SPIM share the feature that they probabilistically resolve the uncertainty in individual identity using the spatial location where samples were collected. Spatial location is informative of individual identity in spatially structured populations because a sample is more likely to have been produced by an individual living near the trap where it was recorded than an individual living further away from the trap. Further, the level of information about individual identity that a spatial location contains is related to two key ecological concepts, population density and home range size, which we quantify using a proposed Identity Diversity Index (IDI). We show that latent and partial identity SCR models produce imprecise and biased density estimates in many high IDI scenarios when data are sparse. We then extend the unmarked SCR model to incorporate categorical, partially identifying covariates, which reduce the level of uncertainty in individual identity, increasing the reliability and precision of density estimates, and allowing reliable density estimation in scenarios with higher IDI values and with more sparse data. We illustrate the performance of this "categorical SPIM" via simulations and by applying it to a black bear data set using microsatellite loci as categorical covariates, where we reproduce the full data set estimates with only slightly less precision using fewer loci than necessary for confident individual identification. We then discuss how the categorical SPIM can be applied to other wildlife sampling scenarios such as remote camera surveys, where natural or researcher-applied partial marks can be observed in photographs. Finally, we discuss how the categorical SPIM can be added to SMR, 2-flank SPIM, or other latent identity SCR models.
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    Spatial Capture-Recapture With Partial Identity: An Application to Camera Traps
    Augustine, Ben C.; Royle, J. Andrew; Kelly, Marcella J.; Satter, Christopher B.; Alonso, Robert S.; Boydston, Erin E.; Crooks, Kevin R. (2018-03)
    Camera trapping surveys frequently capture individuals whose identity is only known from a single flank. The most widely used methods for incorporating these partial identity individuals into density analyses discard some of the partial identity capture histories, reducing precision, and, while not previously recognized, introducing bias. Here, we present the spatial partial identity model (SPIM), which uses the spatial location where partial identity samples are captured to probabilistically resolve their complete identities, allowing all partial identity samples to be used in the analysis. We show that the SPIM outperforms other analytical alternatives. We then apply the SPIM to an ocelot data set collected on a trapping array with double-camera stations and a bobcat data set collected on a trapping array with single-camera stations. The SPIM improves inference in both cases and, in the ocelot example, individual sex is determined from photographs used to further resolve partial identities-one of which is resolved to near certainty. The SPIM opens the door for the investigation of trapping designs that deviate from the standard two camera design, the combination of other data types between which identities cannot be deterministically linked, and can be extended to the problem of partial genotypes.