@article{sollmann_mohamed_niedballa_bender_ambu_lagan_mannan_ong_langner_gardner_et al._2017, title={Quantifying mammal biodiversity co-benefits in certified tropical forests}, volume={23}, ISSN={["1472-4642"]}, DOI={10.1111/ddi.12530}, abstractNote={AbstractAimFinancial incentives to manage forests sustainably, such as certification or carbon storage payments, are assumed to have co‐benefits for biodiversity conservation. This claim remains little studied for rain forest mammals, which are particularly threatened, but challenging to survey.LocationSabah, Malaysia, Borneo.MethodsWe used photographic data from three commercial forest reserves to show how community occupancy modelling can be used to quantify mammalian diversity conservation co‐benefits of forest certification. These reserves had different management histories, and one was certified by the Forest Stewardship Council.ResultsMany threatened species occupied larger areas in the certified reserve. Species richness, estimated per 200 × 200‐m grid cell throughout all reserves, was higher in the certified site, particularly for threatened species. The certified reserve held the highest aboveground biomass. Within reserves, aboveground biomass was not strongly correlated with patterns of mammal richness (Spearman's rho from 0.03 to 0.32); discrepancies were strongest along reserve borders.Main conclusionsOur approach provides a flexible and standardized tool to assess biodiversity and identify winners of sustainable forestry. Inferring patterns of species richness from camera‐trapping carries potential for the objective designation of high conservation value forest. Correlating species richness with aboveground biomass further allows evaluating the biodiversity co‐benefits of carbon protection. These advantages make the present approach an ideal tool to overcome the difficulties to rigorously quantify biodiversity co‐benefits of forest certification and carbon storage payments.}, number={3}, journal={DIVERSITY AND DISTRIBUTIONS}, author={Sollmann, Rahel and Mohamed, Azlan and Niedballa, Jurgen and Bender, Johannes and Ambu, Laurentius and Lagan, Peter and Mannan, Sam and Ong, Robert C. and Langner, Andreas and Gardner, Beth and et al.}, year={2017}, month={Mar}, pages={317–328} }
 @article{gardner_garner_cobb_moorman_2016, title={Factors Affecting Occupancy and Abundance of American Alligators at the Northern Extent of Their Range}, volume={50}, ISSN={["1937-2418"]}, DOI={10.1670/15-147}, abstractNote={Abstract Populations of American Alligators (Alligator mississippiensis) generally are considered more abundant at present than historically; however, little information exists to assess the population of alligators in North Carolina at the northern extent of the species' range. Investigation of the factors influencing the distribution and abundance of alligators in North Carolina could shed light on the species' response to rapid environmental change in the region. We conducted a two-phase study: 1) to assess the distribution of alligators in North Carolina using a site-occupancy design; and 2) to assess the patterns in abundance using a repeated sampling design for population estimation. Results showed that both occupancy and abundance decreased in more northern sites, in sites with higher salinity, and in sites that were generally more westward. Sites sampled later in June were more likely to be occupied than those sampled earlier in the month. Abundance also increased with greater shoreline vegetation complexity and varied between lakes, rivers, and estuaries. Compared with studies from 30 years prior, the population seems fairly stable in terms of abundance and distribution. Given the northern limits of the species and the negative association with salinity, continued monitoring is warranted to understand changes in distribution and abundance with respect to predicted rates of sea-level rise, salinization, and urbanization locally around coastal cities like Wilmington.}, number={4}, journal={JOURNAL OF HERPETOLOGY}, author={Gardner, Beth and Garner, Lindsey A. and Cobb, David T. and Moorman, Christopher E.}, year={2016}, month={Dec}, pages={541–547} }
 @article{goyert_gardner_sollmann_veit_gilbert_connelly_williams_2016, title={Predicting the offshore distribution and abundance of marine birds with a hierarchical community distance sampling model}, volume={26}, ISSN={["1939-5582"]}, DOI={10.1890/15-1955.1}, abstractNote={AbstractProposed offshore wind energy development on the Atlantic Outer Continental Shelf has brought attention to the need for baseline studies of the distribution and abundance of marine birds. We compiled line transect data from 15 shipboard surveys (June 2012–April 2014), along with associated remotely sensed habitat data, in the lower Mid‐Atlantic Bight off the coast of Delaware, Maryland, and Virginia, USA. We implemented a recently developed hierarchical community distance sampling model to estimate the seasonal abundance of 40 observed marine bird species. Treating each season separately, we included six oceanographic parameters to estimate seabird abundance: three static (distance to shore, slope, sediment grain size) and three dynamic covariates (sea surface temperature [SST], salinity, primary productivity). We expected that avian bottom‐feeders would respond primarily to static covariates that characterize seafloor variability, and that surface‐feeders would respond more to dynamic covariates that quantify surface productivity. We compared the variation in species‐specific and community‐level responses to these habitat features, including for rare species, and we predicted species abundance across the study area. While several protected species used the study area in summer during their breeding season, estimated abundance and observed diversity were highest for nonbreeding species in winter. Distance to shore was the most common significant predictor of abundance, and thus useful in estimating the potential exposure of marine birds to offshore development. In many cases, our expectations based on feeding ecology were confirmed, such as in the first winter season, when bottom‐feeders associated significantly with the three static covariates (distance to shore, slope, and sediment grain size), and surface‐feeders associated significantly with two dynamic covariates (SST, primary productivity). However, other cases revealed significant relationships between static covariates and surface‐feeders (e.g., distance to shore) and between dynamic covariates and bottom‐feeders (e.g., primary productivity during that same winter). More generally, we found wide interannual, seasonal, and interspecies variation in habitat relationships with abundance. These results show the importance of quantifying detection and determining the ecological drivers of a community's distribution and abundance, within and among species, for evaluating the potential exposure of marine birds to offshore development.}, number={6}, journal={ECOLOGICAL APPLICATIONS}, author={Goyert, Holly F. and Gardner, Beth and Sollmann, Rahel and Veit, Richard R. and Gilbert, Andrew T. and Connelly, Emily E. and Williams, Kathryn A.}, year={2016}, month={Sep}, pages={1797–1815} }
 @article{sollmann_gardner_williams_gilbert_veit_2016, title={A hierarchical distance sampling model to estimate abundance and covariate associations of species and communities}, volume={7}, ISSN={["2041-2096"]}, DOI={10.1111/2041-210x.12518}, abstractNote={Summary


Distance sampling is a common survey method in wildlife studies, because it allows accounting for imperfect detection. The framework has been extended to hierarchical distance sampling (HDS), which accommodates the modelling of abundance as a function of covariates, but rare and elusive species may not yield enough observations to fit such a model.

We integrate HDS into a community modelling framework that accommodates multi‐species spatially replicated distance sampling data. The model allows species‐specific parameters, but these come from a common underlying distribution. This form of information sharing enables estimation of parameters for species with sparse data sets that would otherwise be discarded from analysis. We evaluate the performance of the model under varying community sizes with different species‐specific abundances through a simulation study. We further fit the model to a seabird data set obtained from shipboard distance sampling surveys off the East Coast of the USA.

Comparing communities comprised of 5, 15 or 30 species, bias of all community‐level parameters and some species‐level parameters decreased with increasing community size, while precision increased. Most species‐level parameters were less biased for more abundant species. For larger communities, the community model increased precision in abundance estimates of rarely observed species when compared to single‐species models. For the seabird application, we found a strong negative association of community and species abundance with distance to shore. Water temperature and prey density had weak effects on seabird abundance. Patterns in overall abundance were consistent with known seabird ecology.

The community distance sampling model can be expanded to account for imperfect availability, imperfect species identification or other missing individual covariates. The model allowed us to make inference about ecology of species communities, including rarely observed species, which is particularly important in conservation and management. The approach holds great potential to improve inference on species communities that can be surveyed with distance sampling.

}, number={5}, journal={METHODS IN ECOLOGY AND EVOLUTION}, author={Sollmann, Rahel and Gardner, Beth and Williams, Kathryn A. and Gilbert, Andrew T. and Veit, Richard R.}, year={2016}, month={May}, pages={529–537} }
 @article{mollet_kery_gardner_pasinelli_royle_2015, title={Estimating Population Size for Capercaillie (Tetrao urogallus L.) with Spatial Capture-Recapture Models Based on Genotypes from One Field Sample}, volume={10}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0129020}, abstractNote={We conducted a survey of an endangered and cryptic forest grouse, the capercaillie Tetrao urogallus, based on droppings collected on two sampling occasions in eight forest fragments in central Switzerland in early spring 2009. We used genetic analyses to sex and individually identify birds. We estimated sex-dependent detection probabilities and population size using a modern spatial capture-recapture (SCR) model for the data from pooled surveys. A total of 127 capercaillie genotypes were identified (77 males, 46 females, and 4 of unknown sex). The SCR model yielded atotal population size estimate (posterior mean) of 137.3 capercaillies (posterior sd 4.2, 95% CRI 130–147). The observed sex ratio was skewed towards males (0.63). The posterior mean of the sex ratio under the SCR model was 0.58 (posterior sd 0.02, 95% CRI 0.54–0.61), suggesting a male-biased sex ratio in our study area. A subsampling simulation study indicated that a reduced sampling effort representing 75% of the actual detections would still yield practically acceptable estimates of total size and sex ratio in our population. Hence, field work and financial effort could be reduced without compromising accuracy when the SCR model is used to estimate key population parameters of cryptic species.}, number={6}, journal={PLOS ONE}, author={Mollet, Pierre and Kery, Marc and Gardner, Beth and Pasinelli, Gilberto and Royle, J. Andrew}, year={2015}, month={Jun} }
 @article{sollmann_white_gardner_manley_2015, title={Investigating the effects of forest structure on the small mammal community in frequent-fire coniferous forests using capture-recapture models for stratified populations}, volume={80}, ISSN={["1618-1476"]}, DOI={10.1016/j.mambio.2015.03.002}, abstractNote={Small mammals comprise an important component of forest vertebrate communities. Our understanding of how small mammals use forested habitat has relied heavily on studies in forest systems not naturally prone to frequent disturbances. Small mammal populations that evolved in frequent-fire forests, however, may be less restricted to specific habitat conditions due to the instability of these resources in time and space. We investigate how canopy cover and the volume of coarse woody debris (CWD), covariates that are considered important for small mammals, impact abundance and body mass of eight small mammal species. Based on live-trapping data collected across 23 sites over three years in a frequent fire forest in the Sierra Nevada we apply capture-recapture models for stratified populations, a statistically rigorous, rarely used framework that allows joint modeling of detection, abundance and its response to covariates. Canopy cover had a strong negative association with the abundance of yellow-pine chipmunks and California ground squirrels, and a strong positive association with deer mice. CWD had a strong negative association with the abundance of golden-mantled ground squirrels, yellow-pine and long-eared chipmunks, and a strong positive association with deer mice. Whereas canopy cover influenced abundance and body mass similarly, CWD had a positive association with body mass and a negative association with abundance in some species. These patterns could arise if suitable habitat is monopolized by socially dominant individuals. Despite these habitat associations, the small mammal community in our study was dynamic and diverse, with spatial and temporal variation in dominant species suggesting that species were flexible in their use of habitat. This study suggests that it is important to understand the disturbance regimes when investigating habitat requirements, coexistence and evolutionary ecology of small mammal species.}, number={4}, journal={MAMMALIAN BIOLOGY}, author={Sollmann, Rahel and White, Angela M. and Gardner, Beth and Manley, Patricia N.}, year={2015}, month={Aug}, pages={247–254} }
 @article{flanders_gardner_winiarski_paton_allison_allan f. o'connell_2015, title={Key seabird areas in southern New England identified using a community occupancy model}, volume={533}, ISSN={["1616-1599"]}, DOI={10.3354/meps11316}, abstractNote={Seabirds are of conservation concern, and as new potential risks to seabirds are arising, the need to provide unbiased estimates of species’ distributions is growing. We applied community occupancy models to detection/non-detection data collected from repeated aerial striptransect surveys conducted in 2 large study plots off southern New England, USA; one off the coast of Rhode Island and the other in Nantucket Sound. A total of 17 seabird species were observed at least once in each study plot. We found that detection varied by survey date and effort for most species and the average detection probability across species was less than 0.4. We estimated the influence of water depth, sea surface temperature, and sea surface chl a concentration on species-specific occupancy. Diving species showed large differences between the 2 study plots in their predicted winter distributions, which were largely explained by water depth acting as a stronger predictor of occupancy in Rhode Island than in Nantucket Sound. Conversely, similarities between the 2 study plots in predicted winter distributions of surface-feeding species were explained by sea surface temperature or chlorophyll a concentration acting as predictors of these species’ occupancy in both study plots. We predicted the number of species at each site using the observed data in order to detect ‘hot-spots’ of seabird diversity and use in the 2 study plots. These results provide new information on detection of species, areas of use, and relationships with environmental variables that will be valuable for biologists and planners interested in seabird conservation in the region.}, journal={MARINE ECOLOGY PROGRESS SERIES}, author={Flanders, Nicholas P. and Gardner, Beth and Winiarski, Kristopher J. and Paton, Peter W. C. and Allison, Taber and Allan F. O'Connell}, year={2015}, month={Aug}, pages={277–290} }
 @article{henry_haddad_wilson_hughes_gardner_2015, title={Point-count methods to monitor butterfly populations when traditional methods fail: a case study with Miami blue butterfly}, volume={19}, ISSN={["1572-9753"]}, DOI={10.1007/s10841-015-9773-6}, number={3}, journal={JOURNAL OF INSECT CONSERVATION}, author={Henry, Erica H. and Haddad, Nick M. and Wilson, John and Hughes, Phillip and Gardner, Beth}, year={2015}, month={Jun}, pages={519–529} }
 @article{hostetter_gardner_schweitzer_boettcher_wilke_addison_swilling_pollock_simons_2015, title={Repeated count surveys help standardize multi-agency estimates of American Oystercatcher (Haematopus palliatus) abundance}, volume={117}, ISSN={0010-5422 1938-5129}, url={http://dx.doi.org/10.1650/CONDOR-14-185.1}, DOI={10.1650/condor-14-185.1}, abstractNote={ABSTRACT The extensive breeding range of many shorebird species can make integration of survey data problematic at regional spatial scales. We evaluated the effectiveness of standardized repeated count surveys coordinated across 8 agencies to estimate the abundance of American Oystercatcher (Haematopus palliatus) breeding pairs in the southeastern United States. Breeding season surveys were conducted across coastal North Carolina (90 plots) and the Eastern Shore of Virginia (3 plots). Plots were visited on 1–5 occasions during April–June 2013. N-mixture models were used to estimate abundance and detection probability in relation to survey date, tide stage, plot size, and plot location (coastal bay vs. barrier island). The estimated abundance of oystercatchers in the surveyed area was 1,048 individuals (95% credible interval: 851–1,408) and 470 pairs (384–637), substantially higher than estimates that did not account for detection probability (maximum counts of 674 individuals and 316 pairs). Detection probability was influenced by a quadratic function of survey date, and increased from mid-April (~0.60) to mid-May (~0.80), then remained relatively constant through June. Detection probability was also higher during high tide than during low, rising, or falling tides. Abundance estimates from N-mixture models were validated at 13 plots by exhaustive productivity studies (2–5 surveys wk−1). Intensive productivity studies identified 78 breeding pairs across 13 productivity plots while the N-mixture model abundance estimate was 74 pairs (62–119) using only 1–5 replicated surveys season−1. Our results indicate that standardized replicated count surveys coordinated across multiple agencies and conducted during a relatively short time window (closure assumption) provide tremendous potential to meet both agency-level (e.g., state) and regional-level (e.g., flyway) objectives in large-scale shorebird monitoring programs.}, number={3}, journal={The Condor}, publisher={Oxford University Press (OUP)}, author={Hostetter, Nathan J. and Gardner, Beth and Schweitzer, Sara H. and Boettcher, Ruth and Wilke, Alexandra L. and Addison, Lindsay and Swilling, William R. and Pollock, Kenneth H. and Simons, Theodore R.}, year={2015}, month={Aug}, pages={354–363} }
 @article{bozarth_gardner_rockwood_maldonado_2015, title={Using Fecal DNA and Spatial Capture-Recapture to Characterize a Recent Coyote Colonization}, volume={22}, ISSN={["1938-5307"]}, DOI={10.1656/045.022.0124}, abstractNote={Abstract 
 The arrival of a novel predator in an ecosystem necessitates many wildlife-management decisions that should be based on sound demographic data. Canis latrans (Coyote) has experienced a dramatic range expansion across North America since the early 19th century, completing its colonization of the continental US in the mid-Atlantic region over the past 20 years. Their arrival in the suburbs of Washington, DC, has generated much public attention, and demonstrated a need for demographic information about this species. To address the challenges of surveying an elusive animal, we used fecal DNA to describe the population genetics and demographics of a newly colonized Coyote population at Marine Corps Base Quantico (MCBQ) in northern Virginia. We collected 331 scats over a period of 2 years at MCBQ, resulting in identification of 23 unique individual Coyotes and 41 total Coyote captures that were analyzed using spatial capture—recapture models. We found evidence of colonization by multiple genetic lineages and a low population density of 0.047 individuals/km2. Importantly, this study incorporates a new class of models on individual animals identified by genotype data derived from fecal DNA and demonstrates the utility of these models in surveying elusive animals.}, number={1}, journal={NORTHEASTERN NATURALIST}, author={Bozarth, Christine A. and Gardner, Beth and Rockwood, Larry L. and Maldonado, Jesus E.}, year={2015}, month={Mar}, pages={144–162} }
 @article{reich_gardner_2014, title={A spatial capture-recapture model for territorial species}, volume={25}, DOI={10.1002/env.2317}, abstractNote={Advances in field techniques have lead to an increase in spatially referenced capture–recapture data to estimate a species' population size as well as other demographic parameters and patterns of space usage. Statistical models for these data have assumed that the number of individuals in the population and their spatial locations follow a homogeneous Poisson point process model, which implies that the individuals are uniformly and independently distributed over the spatial domain of interest. In many applications, there is reason to question independence, for example, when species display territorial behavior. In this paper, we propose a new statistical model, which allows for dependence between locations to account for avoidance or territorial behavior. We show via a simulation study that accounting for this can improve population size estimates. The method is illustrated using a case study of small mammal trapping data to estimate avoidance and population density of adult female field voles (Microtus agrestis) in Northern England. Copyright © 2014 John Wiley & Sons, Ltd.}, number={8}, journal={Environmetrics}, author={Reich, Brian and Gardner, B.}, year={2014}, pages={630–637} }
 @article{sollmann_gardner_chandler_royle_sillett_2015, title={An open-population hierarchical distance sampling model}, volume={96}, ISSN={["1939-9170"]}, DOI={10.1890/14-1625.1}, abstractNote={Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for Island Scrub‐Jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis‐specified model with a log‐linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying numbers of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.}, number={2}, journal={ECOLOGY}, author={Sollmann, Rahel and Gardner, Beth and Chandler, Richard B. and Royle, J. Andrew and Sillett, T. Scott}, year={2015}, month={Feb}, pages={325–331} }
 @article{martin_edwards_bled_fonnesbeck_dupuis_gardner_koslovsky_aven_ward-geiger_carmichael_et al._2014, title={Estimating Upper Bounds for Occupancy and Number of Manatees in Areas Potentially Affected by Oil from the Deepwater Horizon Oil Spill}, volume={9}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0091683}, abstractNote={The explosion of the Deepwater Horizon drilling platform created the largest marine oil spill in U.S. history. As part of the Natural Resource Damage Assessment process, we applied an innovative modeling approach to obtain upper estimates for occupancy and for number of manatees in areas potentially affected by the oil spill. Our data consisted of aerial survey counts in waters of the Florida Panhandle, Alabama and Mississippi. Our method, which uses a Bayesian approach, allows for the propagation of uncertainty associated with estimates from empirical data and from the published literature. We illustrate that it is possible to derive estimates of occupancy rate and upper estimates of the number of manatees present at the time of sampling, even when no manatees were observed in our sampled plots during surveys. We estimated that fewer than 2.4% of potentially affected manatee habitat in our Florida study area may have been occupied by manatees. The upper estimate for the number of manatees present in potentially impacted areas (within our study area) was estimated with our model to be 74 (95%CI 46 to 107). This upper estimate for the number of manatees was conditioned on the upper 95%CI value of the occupancy rate. In other words, based on our estimates, it is highly probable that there were 107 or fewer manatees in our study area during the time of our surveys. Because our analyses apply to habitats considered likely manatee habitats, our inference is restricted to these sites and to the time frame of our surveys. Given that manatees may be hard to see during aerial surveys, it was important to account for imperfect detection. The approach that we described can be useful for determining the best allocation of resources for monitoring and conservation.}, number={3}, journal={PLOS ONE}, author={Martin, Julien and Edwards, Holly H. and Bled, Florent and Fonnesbeck, Christopher J. and Dupuis, Jerome A. and Gardner, Beth and Koslovsky, Stacie M. and Aven, Allen M. and Ward-Geiger, Leslie I. and Carmichael, Ruth H. and et al.}, year={2014}, month={Mar} }
 @article{wilton_puckett_beringer_gardner_eggert_belant_2014, title={Trap Array Configuration Influences Estimates and Precision of Black Bear Density and Abundance}, volume={9}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0111257}, abstractNote={Spatial capture-recapture (SCR) models have advanced our ability to estimate population density for wide ranging animals by explicitly incorporating individual movement. Though these models are more robust to various spatial sampling designs, few studies have empirically tested different large-scale trap configurations using SCR models. We investigated how extent of trap coverage and trap spacing affects precision and accuracy of SCR parameters, implementing models using the R package secr. We tested two trapping scenarios, one spatially extensive and one intensive, using black bear (Ursus americanus) DNA data from hair snare arrays in south-central Missouri, USA. We also examined the influence that adding a second, lower barbed-wire strand to snares had on quantity and spatial distribution of detections. We simulated trapping data to test bias in density estimates of each configuration under a range of density and detection parameter values. Field data showed that using multiple arrays with intensive snare coverage produced more detections of more individuals than extensive coverage. Consequently, density and detection parameters were more precise for the intensive design. Density was estimated as 1.7 bears per 100 km2 and was 5.5 times greater than that under extensive sampling. Abundance was 279 (95% CI = 193–406) bears in the 16,812 km2 study area. Excluding detections from the lower strand resulted in the loss of 35 detections, 14 unique bears, and the largest recorded movement between snares. All simulations showed low bias for density under both configurations. Results demonstrated that in low density populations with non-uniform distribution of population density, optimizing the tradeoff among snare spacing, coverage, and sample size is of critical importance to estimating parameters with high precision and accuracy. With limited resources, allocating available traps to multiple arrays with intensive trap spacing increased the amount of information needed to inform parameters with high precision.}, number={10}, journal={PLOS ONE}, author={Wilton, Clay M. and Puckett, Emily E. and Beringer, Jeff and Gardner, Beth and Eggert, Lori S. and Belant, Jerrold L.}, year={2014}, month={Oct} }
 @article{carrillo-rubio_kery_morreale_sullivan_gardner_cooch_lassoie_2014, title={Use of Multispecies Occupancy Models to Evaluate the Response of Bird Communities to Forest Degradation Associated with Logging}, volume={28}, ISSN={["1523-1739"]}, DOI={10.1111/cobi.12261}, abstractNote={AbstractForest degradation is arguably the greatest threat to biodiversity, ecosystem services, and rural livelihoods. Therefore, increasing understanding of how organisms respond to degradation is essential for management and conservation planning. We were motivated by the need for rapid and practical analytical tools to assess the influence of management and degradation on biodiversity and system state in areas subject to rapid environmental change. We compared bird community composition and size in managed (ejido, i.e., communally owned lands) and unmanaged (national park) forests in the Sierra Tarahumara region, Mexico, using multispecies occupancy models and data from a 2‐year breeding bird survey. Unmanaged sites had on average higher species occupancy and richness than managed sites. Most species were present in low numbers as indicated by lower values of detection and occupancy associated with logging‐induced degradation. Less than 10% of species had occupancy probabilities >0.5, and degradation had no positive effects on occupancy. The estimated metacommunity size of 125 exceeded previous estimates for the region, and sites with mature trees and uneven‐aged forest stand characteristics contained the highest species richness. Higher estimation uncertainty and decreases in richness and occupancy for all species, including habitat generalists, were associated with degraded young, even‐aged stands. Our findings show that multispecies occupancy methods provide tractable measures of biodiversity and system state and valuable decision support for landholders and managers. These techniques can be used to rapidly address gaps in biodiversity information, threats to biodiversity, and vulnerabilities of species of interest on a landscape level, even in degraded or fast‐changing environments. Moreover, such tools may be particularly relevant in the assessment of species richness and distribution in a wide array of habitats.Uso de Modelos de Ocupación para Múltiples Especies para Evaluar la Respuesta de las Comunidades de Aves a la Degradación de Bosques Asociada con la Tala}, number={4}, journal={CONSERVATION BIOLOGY}, author={Carrillo-Rubio, Eduardo and Kery, Marc and Morreale, Stephen J. and Sullivan, Patrick J. and Gardner, Beth and Cooch, Evan G. and Lassoie, James P.}, year={2014}, month={Aug}, pages={1034–1044} }
 @article{raabe_gardner_hightower_2014, title={A spatial capture-recapture model to estimate fish survival and location from linear continuous monitoring arrays}, volume={71}, ISSN={["1205-7533"]}, DOI={10.1139/cjfas-2013-0198}, abstractNote={ We developed a spatial capture–recapture model to evaluate survival and activity centres (i.e., mean locations) of tagged individuals detected along a linear array. Our spatially explicit version of the Cormack–Jolly–Seber model, analyzed using a Bayesian framework, correlates movement between periods and can incorporate environmental or other covariates. We demonstrate the model using 2010 data for anadromous American shad (Alosa sapidissima) tagged with passive integrated transponders (PIT) at a weir near the mouth of a North Carolina river and passively monitored with an upstream array of PIT antennas. The river channel constrained migrations, resulting in linear, one-dimensional encounter histories that included both weir captures and antenna detections. Individual activity centres in a given time period were a function of the individual’s previous estimated location and the river conditions (i.e., gage height). Model results indicate high within-river spawning mortality (mean weekly survival = 0.80) and more extensive movements during elevated river conditions. This model is applicable for any linear array (e.g., rivers, shorelines, and corridors), opening new opportunities to study demographic parameters, movement or migration, and habitat use. }, number={1}, journal={CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES}, author={Raabe, Joshua K. and Gardner, Beth and Hightower, Joseph E.}, year={2014}, month={Jan}, pages={120–130} }
 @article{dunn_boustany_roberts_brazer_sanderson_gardner_halpin_2014, title={Empirical move-on rules to inform fishing strategies: a New England case study}, volume={15}, ISSN={["1467-2979"]}, DOI={10.1111/faf.12019}, abstractNote={AbstractIncreasingly, fisheries are being managed under catch quotas that are often further allocated to specific permit holders or sectors. At the same time, serious consideration is being given to the effects of discards on the health of target and non‐target species. Some quota systems have incorporated discard reduction as an objective by counting discards (including unmarketable fish) against the overall quota. The potential effect of the introduction of a quota system that includes accountability for discards on the fishing strategies employed by fishermen is enormous. This is particularly true for multispecies fisheries where healthy and depleted stocks co‐exist; resulting in a trip's catch being applied to very large and very small stock quotas simultaneously. Under such a scenario, fishermen have a strong incentive to minimize (i) catch of low‐quota or ‘choke’ stocks, (ii) regulatory discards due to minimum size limits and (iii) catch partially consumed by predators. ‘Move‐on’ rules (i.e. event‐triggered, targeted, temporary closure of part of a fishery when a catch or bycatch threshold is reached) have been employed in a variety of fisheries. However, their efficacy has been limited by a lack of empirical analyses underpinning the rules. Here, we examine the utility of spatiotemporal autocorrelation analyses to inform ‘move‐on’ rules to assist a sector of the New England Multispecies Fishery to reduce discards and maximize profits. We find the use of empirical move‐on rules could reduce catch of juvenile and choke stocks between 27 and 33%, and depredation events between 41 and 54%.}, number={3}, journal={FISH AND FISHERIES}, author={Dunn, Daniel C. and Boustany, Andre M. and Roberts, Jason J. and Brazer, Eric and Sanderson, Melissa and Gardner, Beth and Halpin, Patrick N.}, year={2014}, month={Sep}, pages={359–375} }
 @article{mcgowan_gardner_2013, title={Evaluating Methodological Assumptions of Catch-Curve Survival Estimation for Unmarked Precocial Shorebird Chicks}, volume={36}, ISSN={["1938-5390"]}, DOI={10.1675/063.036.0112}, abstractNote={Abstract. 
 Estimating productivity for precocial species can be difficult because young birds leave their nest within hours or days of hatching and detectability thereafter can be very low. Recently, a method for using a modified catch-curve to estimate precocial chick daily survival for age based count data was presented using Piping Plover (Charadrius melodus) data from the Missouri River. However, many of the assumptions of the catch-curve approach were not fully evaluated for precocial chicks. We developed a simulation model to mimic Piping Plovers, a fairly representative shorebird, and age-based count-data collection. Using the simulated data, we calculated daily survival estimates and compared them with the known daily survival rates from the simulation model. We conducted these comparisons under different sampling scenarios where the ecological and statistical assumptions had been violated. Overall, the daily survival estimates calculated from the simulated data corresponded well with true survival rates of the simulation. Violating the accurate aging and the independence assumptions did not result in biased daily survival estimates, whereas unequal detection for younger or older birds and violating the birth death equilibrium did result in estimator bias. Assuring that all ages are equally detectable and timing data collection to approximately meet the birth death equilibrium are key to the successful use of this method for precocial shorebirds.}, number={1}, journal={WATERBIRDS}, author={McGowan, Conor P. and Gardner, Beth}, year={2013}, month={Mar}, pages={82–87} }
 @article{mattsson_zipkin_gardner_blank_sauer_royle_2013, title={Explaining Local-Scale Species Distributions: Relative Contributions of Spatial Autocorrelation and Landscape Heterogeneity for an Avian Assemblage}, volume={8}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0055097}, abstractNote={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.}, number={2}, journal={PLOS ONE}, author={Mattsson, Brady J. and Zipkin, Elise F. and Gardner, Beth and Blank, Peter J. and Sauer, John R. and Royle, J. Andrew}, year={2013}, month={Feb} }
 @article{bowling_moorman_deperno_gardner_2014, title={Influence of Landscape Composition on Northern Bobwhite Population Response to Field Border Establishment}, volume={78}, ISSN={["1937-2817"]}, DOI={10.1002/jwmg.639}, abstractNote={ABSTRACTSince the 1960s, habitat loss resulting from cleaner farming, increased urbanization, and maturation of early successional cover has caused range‐wide decline of northern bobwhite (Colinus virginianus). Although field borders increase bobwhite habitat and increase local populations, understanding how the surrounding landscape influences bobwhite response to this management practice is critical to efficient implementation. We determined the relative influence of landscape composition and field border implementation on bobwhite densities and occupancy dynamics around crop fields in North Carolina and South Carolina, USA. We used 10‐minute distance point counts to estimate density, occupancy, colonization, and extinction rates of male bobwhite around 154 agriculture fields, half of which had a fallow field border. We estimated percent of cropland, forest, pasture, early successional, and urban cover within 1‐km radius buffers (314 ha) surrounding all point count locations. We examined the influence of 6 predictor variables (landscape composition metrics and field border presence) on bobwhite density and occupancy dynamics. Bobwhite density increased with the presence of field borders. Conversely, bobwhite density decreased as the percentage of urban, pasture, and forest lands increased. The presence of a field border did not influence occupancy, colonization, or extinction rates. However, as the percentage of cropland increased within the landscape, bobwhite occupancy increased and as the percentage of pasture increased, bobwhite colonization decreased. As the percentage of forest and urban increased and cropland decreased, bobwhite extinction rate increased. Our results indicated that local establishment of field borders does not increase bobwhite occupancy rates, but field borders can increase densities in suitable landscapes where bobwhite are present. Habitat restoration for bobwhite will most effectively increase population densities if focused in landscapes dominated by suitable cover types, where bobwhite occurrence is high. © 2013 The Wildlife Society.}, number={1}, journal={JOURNAL OF WILDLIFE MANAGEMENT}, author={Bowling, Shannon A. and Moorman, Christopher E. and Deperno, Christopher S. and Gardner, Beth}, year={2014}, month={Jan}, pages={93–100} }
 @article{ergon_gardner_2014, title={Separating mortality and emigration: modelling space use, dispersal and survival with robust-design spatial capture-recapture data}, volume={5}, ISSN={["2041-2096"]}, DOI={10.1111/2041-210x.12133}, abstractNote={Summary


Capture–recapture (CR) techniques are commonly used to gain information about population dynamics, demography and life‐history traits of populations. However, traditional CR models cannot separate mortality from emigration. Recently developed spatial–capture–recapture (SCR) models explicitly incorporate spatial information into traditional CR models, thus allowing for individuals' movements to be modelled explicitly.

In this paper, we extend SCR models using robust‐design data to allow for both processes in which individuals can disappear from the population, mortality and dispersal, to be estimated separately. We formulate a general robust‐design spatial capture–recapture (RD‐SCR) model, explore the properties of the model in a simulation study and compare the results to a Cormack–Jolly–Seber model and a non‐spatial robust‐design model with temporary emigration. In the case study, we fit several versions of the general model to data on field voles (Microtus agrestis) and compare the results with those from the non‐spatial models fitted to the same data. We also evaluate assumptions of the fitted models with a series of simulation‐based posterior predictive goodness‐of‐fit checks that are applicable to the SCR models in general and the RD‐SCR model in particular.

The simulation results show that the model preforms well under a wide range of dispersal distances. Our model outperforms the traditional CR models in terms of both accuracy and precision for survival. The case study showed that adult females have an c. 3·5 times higher mortality rate than adult males. Males have larger home ranges and disperse longer distances than females, but both males and females mostly move their activity centres within their previous home range between trapping sessions at 3‐week intervals.

Our RD‐SCR model has several advantages compared to other approaches to estimate ‘true’ survival instead of only ‘apparent’ survival. Additionally, the model extracts information about space use and dispersal distributions that are relevant for behavioural studies as well as studies of life‐history variation, population dynamics and management. The model can be widely applied due to the flexible framework, and other variations of the model could easily be implemented.

}, number={12}, journal={METHODS IN ECOLOGY AND EVOLUTION}, author={Ergon, Torbjorn and Gardner, Beth}, year={2014}, month={Dec}, pages={1327–1336} }
 @article{sollmann_gardner_chandler_shindle_onorato_royle_allan f. o'connell_2013, title={Using multiple data sources provides density estimates for endangered Florida panther}, volume={50}, ISSN={["1365-2664"]}, DOI={10.1111/1365-2664.12098}, abstractNote={Summary


To assess recovery of endangered species, reliable information on the size and density of the target population is required. In practice, however, this information has proved hard to acquire, especially for large carnivores that exist at low densities, are cryptic and range widely. Many large carnivore species such as the endangered Florida panther Puma concolor coryi lack clear visual features for individual identification; thus, using standard approaches for estimating population size, such as camera‐trapping and capture–recapture modelling, has so far not been possible.


We developed a spatial capture–recapture model that requires only a portion of the individuals in the population to be identifiable, using data from two 9‐month camera‐trapping surveys conducted within the core range of panthers in southwestern Florida. Identity of three radio‐collared individuals was known, and we incorporated their telemetry location data into the model to improve parameter estimates.


The resulting density estimates of 1·51 (±0·81) and 1·46 (±0·76) Florida panthers per 100 km2 for each year are the first estimates for this endangered subspecies and are consistent with estimates for other puma subspecies.


A simulation study showed that estimates of density may exhibit some positive bias but coverage of the true values by 95% credible intervals was nominal.


Synthesis and applications. This approach provides a framework for monitoring the Florida panther – and other species without conspicuous markings – while fully accounting for imperfect detection and varying sampling effort, issues of fundamental importance in the monitoring of wildlife populations.


}, number={4}, journal={JOURNAL OF APPLIED ECOLOGY}, author={Sollmann, Rahel and Gardner, Beth and Chandler, Richard B. and Shindle, David B. and Onorato, David P. and Royle, Jeffrey Andrew and Allan F. O'Connell}, year={2013}, month={Aug}, pages={961–968} }
 @article{sollmann_gardner_parsons_stocking_mcclintock_simons_pollock_allan f. o'connell_2013, title={A spatial mark-resight model augmented with telemetry data}, volume={94}, ISSN={["1939-9170"]}, DOI={10.1890/12-1256.1}, abstractNote={Abundance and population density are fundamental pieces of information for population ecology and species conservation, but they are difficult to estimate for rare and elusive species. Mark–resight models are popular for estimating population abundance because they are less invasive and expensive than traditional mark–recapture. However, density estimation using mark–resight is difficult because the area sampled must be explicitly defined, historically using ad hoc approaches. We developed a spatial mark–resight model for estimating population density that combines spatial resighting data and telemetry data. Incorporating telemetry data allows us to inform model parameters related to movement and individual location. Our model also allows <100% individual identification of marked individuals. We implemented the model in a Bayesian framework, using a custom‐made Metropolis‐within‐Gibbs Markov chain Monte Carlo algorithm. As an example, we applied this model to a mark–resight study of raccoons (Procyon lotor) on South Core Banks, a barrier island in Cape Lookout National Seashore, North Carolina, USA. We estimated a population of 186.71 ± 14.81 individuals, which translated to a density of 8.29 ± 0.66 individuals/km2 (mean ± SD). The model presented here will have widespread utility in future applications, especially for species that are not naturally marked.}, number={3}, journal={ECOLOGY}, author={Sollmann, Rahel and Gardner, Beth and Parsons, Arielle W. and Stocking, Jessica J. and McClintock, Brett T. and Simons, Theodore R. and Pollock, Kenneth H. and Allan F. O'Connell}, year={2013}, month={Mar}, pages={553–559} }
 @article{noss_gardner_maffei_cuellar_montano_romero-munoz_sollman_o'connell_2012, title={Comparison of density estimation methods for mammal populations with camera traps in the Kaa-Iya del Gran Chaco landscape}, volume={15}, ISSN={["1469-1795"]}, DOI={10.1111/j.1469-1795.2012.00545.x}, abstractNote={AbstractSampling animal populations with camera traps has become increasingly popular over the past two decades, particularly for species that are cryptic, elusive, exist at low densities or range over large areas. The results have been widely used to estimate population size and density. We analyzed data from 13 camera trap surveys conducted at five sites across the Kaa‐Iya landscape, Bolivian Chaco, for jaguar, puma, ocelot and lowland tapir. We compared two spatially explicit capture–recapture (SCR) software packages: secr, a likelihood‐based approach, and SPACECAP, a Bayesian approach, both of which are implemented within the R environment and can be used to estimate animal density from photographic records of individual animals that simultaneously employ spatial information about the capture location relative to the sample location. As a non‐spatial analysis, we used the program CAPTURE 2 to estimate abundance from the capture–recapture records of individuals identified through camera trap photos combined with an ad hoc estimation of the effective survey area to estimate density. SCR methods estimated jaguar population densities from 0.31 to 1.82 individuals per 100 km2 across the Kaa‐Iya sites; puma from 0.36 to 7.99; ocelot from 1.67 to 51.7; and tapir from 7.38 to 42.9. Density estimates using either secr or SPACECAP were generally lower than the estimates generated using the non‐spatial method for all surveys and species; and density estimates using SPACECAP were generally lower than that using secr. We recommend using either secr or SPACECAP because the spatially explicit methods are not biased by an informal estimation of an effective survey area. Although SPACECAP and secr are less sensitive than non‐spatial methods to the size of the grid used for sampling, we recommend grid sizes several times larger than the average home range (known or estimated) of the target species.}, number={5}, journal={ANIMAL CONSERVATION}, author={Noss, A. J. and Gardner, B. and Maffei, L. and Cuellar, E. and Montano, R. and Romero-Munoz, A. and Sollman, R. and O'Connell, A. F.}, year={2012}, month={Oct}, pages={527–535} }
 @article{martin_edwards_burgess_percival_fagan_gardner_ortega-ortiz_ifju_evers_rambo_2012, title={Estimating Distribution of Hidden Objects with Drones: From Tennis Balls to Manatees}, volume={7}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0038882}, abstractNote={Unmanned aerial vehicles (UAV), or drones, have been used widely in military applications, but more recently civilian applications have emerged (e.g., wildlife population monitoring, traffic monitoring, law enforcement, oil and gas pipeline threat detection). UAV can have several advantages over manned aircraft for wildlife surveys, including reduced ecological footprint, increased safety, and the ability to collect high-resolution geo-referenced imagery that can document the presence of species without the use of a human observer. We illustrate how geo-referenced data collected with UAV technology in combination with recently developed statistical models can improve our ability to estimate the distribution of organisms. To demonstrate the efficacy of this methodology, we conducted an experiment in which tennis balls were used as surrogates of organisms to be surveyed. We used a UAV to collect images of an experimental field with a known number of tennis balls, each of which had a certain probability of being hidden. We then applied spatially explicit occupancy models to estimate the number of balls and created precise distribution maps. We conducted three consecutive surveys over the experimental field and estimated the total number of balls to be 328 (95%CI: 312, 348). The true number was 329 balls, but simple counts based on the UAV pictures would have led to a total maximum count of 284. The distribution of the balls in the field followed a simulated environmental gradient. We also were able to accurately estimate the relationship between the gradient and the distribution of balls. Our experiment demonstrates how this technology can be used to create precise distribution maps in which discrete regions of the study area are assigned a probability of presence of an object. Finally, we discuss the applicability and relevance of this experimental study to the case study of Florida manatee distribution at power plants.}, number={6}, journal={PLOS ONE}, author={Martin, Julien and Edwards, Holly H. and Burgess, Matthew A. and Percival, H. Franklin and Fagan, Daniel E. and Gardner, Beth E. and Ortega-Ortiz, Joel G. and Ifju, Peter G. and Evers, Brandon S. and Rambo, Thomas J.}, year={2012}, month={Jun} }
 @article{sollmann_gardner_belant_2012, title={How Does Spatial Study Design Influence Density Estimates from Spatial Capture-Recapture Models?}, volume={7}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0034575}, abstractNote={When estimating population density from data collected on non-invasive detector arrays, recently developed spatial capture-recapture (SCR) models present an advance over non-spatial models by accounting for individual movement. While these models should be more robust to changes in trapping designs, they have not been well tested. Here we investigate how the spatial arrangement and size of the trapping array influence parameter estimates for SCR models. We analysed black bear data collected with 123 hair snares with an SCR model accounting for differences in detection and movement between sexes and across the trapping occasions. To see how the size of the trap array and trap dispersion influence parameter estimates, we repeated analysis for data from subsets of traps: 50% chosen at random, 50% in the centre of the array and 20% in the South of the array. Additionally, we simulated and analysed data under a suite of trap designs and home range sizes. In the black bear study, we found that results were similar across trap arrays, except when only 20% of the array was used. Black bear density was approximately 10 individuals per 100 km2. Our simulation study showed that SCR models performed well as long as the extent of the trap array was similar to or larger than the extent of individual movement during the study period, and movement was at least half the distance between traps. SCR models performed well across a range of spatial trap setups and animal movements. Contrary to non-spatial capture-recapture models, they do not require the trapping grid to cover an area several times the average home range of the studied species. This renders SCR models more appropriate for the study of wide-ranging mammals and more flexible to design studies targeting multiple species.}, number={4}, journal={PLOS ONE}, author={Sollmann, Rahel and Gardner, Beth and Belant, Jerrold L.}, year={2012}, month={Apr} }
 @article{chen_kery_plattner_ma_gardner_2013, title={Imperfect detection is the rule rather than the exception in plant distribution studies}, volume={101}, ISSN={["1365-2745"]}, DOI={10.1111/1365-2745.12021}, abstractNote={Summary


Imperfect detection can seriously bias conventional estimators of species distributions and species richness. Plant traits, survey‐specific conditions and site‐specific characteristics may influence plant detection probability. However, the generality of the problems induced by imperfect detection in plants and the magnitude of this challenge for plant distribution studies are currently unknown.

We address this question based on data from the Swiss Biodiversity Monitoring, in which vascular plants are surveyed twice in the same year along a 2.5‐km transect in 451 1‐km2 quadrats. Overall, 1700 species were recorded. We chose a random sample of 100 species from the 1700 species to determine general detection levels. To examine the relationship of covariates on detection, we chose a stratified random sample of 100 species from 886 species that were detected in at least 18 locations, with 25 each from four life‐forms (LF): grass, forb, shrub and tree. Using a Bayesian multispecies site‐occupancy model, we estimated occurrence and detection probability of these species and their relation to covariates.

Based on the random sample of 100 species, detection probability during the first survey ranged 0.03–0.99 (median 0.74) and during the second survey, 0.03–0.99 (median 0.82). Based on the stratified random sample of 100 species, detection probability during the first survey ranged 0.02–0.99 (median 0.87) and during the second survey, 0.01–1 (median 0.89). Detection probability differed slightly among the four LFs. In 60 species, survey season or elevation had significant effects on detection. We illustrated detection probability maps for Switzerland based on the modelled relationships with environmental covariates.

Synthesis. Our findings suggest that even in a standardized monitoring program, imperfect detection of plants may be common. With the absence of a correction for detection errors, maps in plant distribution studies will be confounded with spatial patterns in detection probability. We presume that these problems will be much more widespread in the data sets that are used for conventional plant species distribution modelling. Imperfect detection should be estimated, even in distribution studies of plants and other sessile organisms, to better control detection errors that may compromise the results of species distribution studies.

}, number={1}, journal={JOURNAL OF ECOLOGY}, author={Chen, Guoke and Kery, Marc and Plattner, Matthias and Ma, Keping and Gardner, Beth}, year={2013}, month={Jan}, pages={183–191} }
 @article{wegan_curtis_rainbolt_gardner_2012, title={Temporal sampling frame selection in DNA-based capture-mark-recapture investigations}, volume={23}, DOI={10.2192/ursus-d-11-00013.1}, abstractNote={Abstract Capture–mark–recapture (CMR) population parameter estimation utilizing DNA analysis from remotely-collected hair samples to identify individuals and generate encounter histories has become the standard methodology for estimating abundance of American black (Ursus americanus) and grizzly bear (U. arctos) populations. However, few published studies have examined the time frame for efficiently collecting high-quality hair samples. Our objectives were to examine several measures of hair trapping success and sample quality, such as DNA amplification rates and the mean number of black bear hair samples collected per trap visit, from hair-snare samples collected in 2 non-overlapping, multi-interval sampling frames conducted during 2005 and 2006 at Fort Drum Military Installation in northern New York. Through our data analyses and a review of 12 other bear CMR studies using remote hair sampling, we emphasize that temporal sampling frame is a crucial consideration in study design. To avoid biased population estimates and to use financial, personnel, and temporal resources effectively, hair sampling should be conducted during late spring and early summer.}, number={1}, journal={URSUS}, author={Wegan, M. T. and Curtis, P. D. and Rainbolt, R. E. and Gardner, B.}, year={2012}, pages={42–51} }
 @article{martin_royle_mackenzie_edwards_kery_gardner_2011, title={Accounting for non-independent detection when estimating abundance of organisms with a Bayesian approach}, volume={2}, ISSN={["2041-2096"]}, DOI={10.1111/j.2041-210x.2011.00113.x}, abstractNote={Summary1. Binomial mixture models use repeated count data to estimate abundance. They are becoming increasingly popular because they provide a simple and cost‐effective way to account for imperfect detection. However, these models assume that individuals are detected independently of each other. This assumption may often be violated in the field. For instance, manatees (Trichechus manatus latirostris) may surface in turbid water (i.e. become available for detection during aerial surveys) in a correlated manner (i.e. in groups). However, correlated behaviour, affecting the non‐independence of individual detections, may also be relevant in other systems (e.g. correlated patterns of singing in birds and amphibians).2. We extend binomial mixture models to account for correlated behaviour and therefore to account for non‐independent detection of individuals. We simulated correlated behaviour using beta‐binomial random variables. Our approach can be used to simultaneously estimate abundance, detection probability and a correlation parameter.3. Fitting binomial mixture models to data that followed a beta‐binomial distribution resulted in an overestimation of abundance even for moderate levels of correlation. In contrast, the beta‐binomial mixture model performed considerably better in our simulation scenarios. We also present a goodness‐of‐fit procedure to evaluate the fit of beta‐binomial mixture models.4. We illustrate our approach by fitting both binomial and beta‐binomial mixture models to aerial survey data of manatees in Florida. We found that the binomial mixture model did not fit the data, whereas there was no evidence of lack of fit for the beta‐binomial mixture model. This example helps illustrate the importance of using simulations and assessing goodness‐of‐fit when analysing ecological data with N‐mixture models. Indeed, both the simulations and the goodness‐of‐fit procedure highlighted the limitations of the standard binomial mixture model for aerial manatee surveys.5. Overestimation of abundance by binomial mixture models owing to non‐independent detections is problematic for ecological studies, but also for conservation. For example, in the case of endangered species, it could lead to inappropriate management decisions, such as downlisting. These issues will be increasingly relevant as more ecologists apply flexible N‐mixture models to ecological data.}, number={6}, journal={METHODS IN ECOLOGY AND EVOLUTION}, author={Martin, Julien and Royle, J. Andrew and Mackenzie, Darryl I. and Edwards, Holly H. and Kery, Marc and Gardner, Beth}, year={2011}, month={Dec}, pages={595–601} }
 @article{oppel_meirinho_ramirez_gardner_allan f. o'connell_miller_louzao_2012, title={Comparison of five modelling techniques to predict the spatial distribution and abundance of seabirds}, volume={156}, ISSN={["1873-2917"]}, DOI={10.1016/j.biocon.2011.11.013}, abstractNote={Knowledge about the spatial distribution of seabirds at sea is important for conservation. During marine conservation planning, logistical constraints preclude seabird surveys covering the complete area of interest and spatial distribution of seabirds is frequently inferred from predictive statistical models. Increasingly complex models are available to relate the distribution and abundance of pelagic seabirds to environmental variables, but a comparison of their usefulness for delineating protected areas for seabirds is lacking. Here we compare the performance of five modelling techniques (generalised linear models, generalised additive models, Random Forest, boosted regression trees, and maximum entropy) to predict the distribution of Balearic Shearwaters (Puffinus mauretanicus) along the coast of the western Iberian Peninsula. We used ship transect data from 2004 to 2009 and 13 environmental variables to predict occurrence and density, and evaluated predictive performance of all models using spatially segregated test data. Predicted distribution varied among the different models, although predictive performance varied little. An ensemble prediction that combined results from all five techniques was robust and confirmed the existence of marine important bird areas for Balearic Shearwaters in Portugal and Spain. Our predictions suggested additional areas that would be of high priority for conservation and could be proposed as protected areas. Abundance data were extremely difficult to predict, and none of five modelling techniques provided a reliable prediction of spatial patterns. We advocate the use of ensemble modelling that combines the output of several methods to predict the spatial distribution of seabirds, and use these predictions to target separate surveys assessing the abundance of seabirds in areas of regular use.}, journal={BIOLOGICAL CONSERVATION}, author={Oppel, Steffen and Meirinho, Ana and Ramirez, Ivan and Gardner, Beth and Allan F. O'Connell and Miller, Peter I. and Louzao, Maite}, year={2012}, pages={94–104} }
 @article{sollmann_furtado_gardner_hofer_jacomo_torres_silveira_2011, title={Improving density estimates for elusive carnivores: Accounting for sex-specific detection and movements using spatial capture-recapture models for jaguars in central Brazil}, volume={144}, ISSN={["1873-2917"]}, DOI={10.1016/j.biocon.2010.12.011}, abstractNote={Owing to habitat conversion and conflict with humans, many carnivores are of conservation concern. Because of their elusive nature, camera trapping is a standard tool for studying carnivores. In many vertebrates, sex-specific differences in movements – and therefore detection by cameras – are likely. We used camera trapping data and spatially explicit sex-specific capture–recapture models to estimate jaguar density in Emas National Park in the central Brazilian Cerrado grassland, an ecological hotspot of international importance. Our spatially explicit model considered differences in movements and trap encounter rate between genders and the location of camera traps (on/off road). We compared results with estimates from a sex-specific non-spatial capture–recapture model. The spatial model estimated a density of 0.29 jaguars 100 km−2 and showed that males moved larger distances and had higher trap encounter rates than females. Encounter rates with off-road traps were one tenth of those for on-road traps. In the non-spatial model, males had a higher capture probability than females; density was estimated at 0.62 individuals 100 km−2. The non-spatial model likely overestimated density because it did not adequately account for animal movements. The spatial model probably underestimated density because it assumed a uniform distribution of jaguars within and outside the reserve. Overall, the spatial model is preferable because it explicitly considers animal movements and allows incorporating site-specific and individual covariates. With both methods, jaguar density was lower than reported from most other study sites. For rare species such as grassland jaguars, spatially explicit capture–recapture models present an important advance for informed conservation planning.}, number={3}, journal={BIOLOGICAL CONSERVATION}, author={Sollmann, Rahel and Furtado, Mariana Malzoni and Gardner, Beth and Hofer, Heribert and Jacomo, Anah T. A. and Torres, Natalia Mundim and Silveira, Leandro}, year={2011}, month={Mar}, pages={1017–1024} }