N-mixture Models Research Articles

The Endangered Ganges River dolphin Platanista gangetica gangetica in Nepal: abundance, habitat and conservation threats

ESR Endangered Species Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials ESR 29:59-68 (2015) - DOI: https://doi.org/10.3354/esr00702 The Endangered Ganges River dolphin Platanista gangetica gangetica in Nepal: abundance, habitat and conservation threats Shambhu Paudel1,2,*, Prabhat Pal2, Michael V. Cove3, Shant Raj Jnawali4, Grant Abel5, John L. Koprowski6, Rishi Ranabhat7 1Kathmandu Forestry College, PO Box 8973, Kathmandu, Nepal 2The Himalaya, Kathmandu, Nepal 3Department of Applied Ecology, North Carolina State University, Raleigh, North Carolina 27695, USA 4Hariyo Ban Program, World Wildlife Fund (WWF-Nepal), Kathmandu, Nepal 5Ocean Park Corporation, Hong Kong 6Wildlife and Fisheries Science, School of Natural Resources and the Environment, University of Arizona, Tucson, Arizona 85721, USA 7Department of National Parks and Wildlife Conservation, Kathmandu, Nepal *Corresponding author: oasis.excurrent@gmail.com ABSTRACT: Conservation of the last remaining Ganges River dolphins Platanista gangetica gangetica in Nepal will require robust population estimates and better information on suitable habitat characteristics. To gain a better understanding of these parameters, we conducted boat-based surveys in the 3 major river systems (Karnali, Sapta Koshi, and Narayani) of Nepal. We recorded covariates at high spatial resolution and utilized these data to inform occurrence and abundance models. We allowed for detection bias by applying occupancy and N-mixture models that account for imperfect and heterogeneous detection. Occupancy results indicate that dolphin site use varies among the different river systems, across 2 seasons, and increases with river depth. River effects received nearly 100% of the model support and had the strongest influence on dolphin occurrence and abundance. The seasonal influence on dolphin occurrence in the systems (Σωi = 0.997) revealed that occupancy probabilities were heightened during the pre-monsoon season. Deep pool habitat was also identified as a predictor of dolphin habitat use, which accounted for 41.02% of all dolphin sightings occurring in this habitat. Although estimates vary depending on season, we estimate that there are between 37 and 42 (95% CI: 28 to 52) Ganges River dolphins distributed in the rivers of Nepal. Results suggest that seasonality and each specific river affect dolphins and their habitat in Nepal; we strongly recommend site and season-specific conservation actions. Further research on the integration of additional and alternative abundance techniques, behavioral studies, and pursuit of a conservation genetics approach are all important steps in the management of this endangered species. KEY WORDS: Ganges River dolphin · Endangered species · Abundance · Habitat · Distribution · Nepal Full text in pdf format PreviousNextCite this article as: Paudel S, Pal P, Cove MV, Jnawali SR, Abel G, Koprowski JL, Ranabhat R (2015) The Endangered Ganges River dolphin Platanista gangetica gangetica in Nepal: abundance, habitat and conservation threats. Endang Species Res 29:59-68. https://doi.org/10.3354/esr00702 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in ESR Vol. 29, No. 1. Online publication date: November 25, 2015 Print ISSN: 1863-5407; Online ISSN: 1613-4796 Copyright © 2015 Inter-Research.

Accuracy or precision: Implications of sample design and methodology on abundance estimation

Sampling by spatially replicated counts (point-count) is an increasingly popular method of estimating population size of organisms. Challenges exist when sampling by point-count method, and it is often impractical to sample entire area of interest and impossible to detect every individual present. Ecologists encounter logistical limitations that force them to sample either few large-sample units or many small sample-units, introducing biases to sample counts. We generated a computer environment and simulated sampling scenarios to test the role of number of samples, sample unit area, number of organisms, and distribution of organisms in the estimation of population sizes using N-mixture models. Many sample units of small area provided estimates that were consistently closer to true abundance than sample scenarios with few sample units of large area. However, sample scenarios with few sample units of large area provided more precise abundance estimates than abundance estimates derived from sample scenarios with many sample units of small area. It is important to consider accuracy and precision of abundance estimates during the sample design process with study goals and objectives fully recognized, although and with consequence, consideration of accuracy and precision of abundance estimates is often an afterthought that occurs during the data analysis process.

Estimating the Effects of Habitat and Biological Interactions in an Avian Community.

We used repeated sightings of individual birds encountered in community-level surveys to investigate the relative roles of habitat and biological interactions in determining the distribution and abundance of each species. To analyze these data, we developed a multispecies N-mixture model that allowed estimation of both positive and negative correlations between abundances of different species while also estimating the effects of habitat and the effects of errors in detection of each species. Using a combination of single- and multispecies N-mixture modeling, we examined for each species whether our measures of habitat were sufficient to account for the variation in encounter histories of individual birds or whether other habitat variables or interactions with other species needed to be considered. In the community that we studied, habitat appeared to be more influential than biological interactions in determining the distribution and abundance of most avian species. Our results lend support to the hypothesis that abundances of forest specialists are negatively affected by forest fragmentation. Our results also suggest that many species were associated with particular types of vegetation as measured by structural attributes of the forests. The abundances of 6 of the 73 species observed in our study were strongly correlated. These species included large birds (American Crow (Corvus brachyrhynchos) and Red-winged Blackbird (Agelaius phoeniceus)) that forage on the ground in open habitats and small birds (Red-eyed Vireo (Vireo olivaceus), House Wren (Troglodytes aedon), Hooded Warbler (Setophaga citrina), and Prairie Warbler (Setophaga discolor)) that are associated with dense shrub cover. Species abundances were positively correlated within each size group and negatively correlated between groups. Except for the American Crow, which preys on eggs and nestlings of small song birds, none of the other 5 species is known to display direct interactions, so we suspect that the correlations may have been associated with species-specific responses to habitat components not adequately measured by our covariates.

The usefulness of top predators as biodiversity surrogates indicated by the relationship between the reproductive outputs of raptors and other bird species

Given the global reduction in biodiversity, conservation actions must occur even with only a partial understanding of the distribution and abundance of species in various locales. The concept of surrogate species, those whose protection affords the protection of other species, is considered a conservation short-cut. Although surrogate species have been used as practical conservation tools, whether they serve as indicators of the reproductive output of other species is still unknown. We hypothesized that the reproductive output of the eastern marsh harrier (Circus spilonotus) can serve as a surrogate for both the adult abundance and reproductive output of sympatric birds. In a fragmented wetland landscape (approximately 211.60km2), we measured the reproductive output of harriers for 3years and conducted replicated counts of the adults and juveniles of other wetland bird species in wetland patches that varied in harrier reproductive output. We used playbacks of mobbing calls in replicated counts and accounted for imperfect detection using an N-mixture model. We modeled adult and juvenile abundances for 10 and 7 species, respectively, and showed that the reproduction-based habitat quality of the marsh harrier (cumulative numbers of both years occupying the habitat and chicks produced) was positively associated with adult abundances in four species and with juvenile abundances in five species. We suggest that areas with high reproductive output of several sympatric bird species could be selected based on the reproduction-based habitat quality of the marsh harrier. Furthermore, the approach combining the playback of mobbing calls and N-mixture models enabled us to estimate juvenile abundances for many bird species on a landscape scale over a short period of time.

A guild-based approach to assessing the influence of beech forest structure on bird communities

The advantages of using birds as indicators of biodiversity and/or habitat quality in forest habitats rely principally (1) on their relative ease of detection and (2) on their strong association with many forest features. Here we investigate how forest structure can shape a bird community at the stand level (ca. 30hectares), using an expeditious sampling protocol and a simple but reasoned guild approach. We focused on three beech (Fagus sylvatica) forests in Italy with different structures resulting from different management histories: Cansiglio, Chiarano-Sparvera and Marchesale. We hypothesise that the abundance of the selected guilds varies in relation to forest structure as a result of forest management; to test this hypothesis we modelled guild abundance along a latitudinal transect in a similar habitat (i.e. beech forest) in order to offset the geographical and environmental sources of variability. Birds were surveyed through replicated aural/visual point counts. Thus we identified four guilds: generalist cavity nesters (TIT), generalist canopy nesters (WAR), insectivorous cavity nesters (INS) and granivorous canopy nesters (FIN). Forest structure and deadwood were estimated for each of the 27 sampling points. Guild abundance was estimated using the N-mixture models approach, which allows the mean abundance at each sampling location and the detectability to be estimated. Both the mean abundance and detectability were constrained to forest structure and time variables. Guild-estimated abundance was tested for differences among sites using ANOVA. Mean guild abundance proved different only for two guilds. INS was more abundant in Cansiglio than in Chiarano and Marchesale while between Chiarano and Marchesale there was no significant difference. Also WAR abundance was greater in Chiarano, followed by Marchesale and Cansiglio. Shelterwood management may result in a higher abundance of specialist guilds (i.e. insectivorous cavity nesters), compared to other management options. Our results highlight this pattern in the Cansiglio forest, where the age and the applied treatments resulted in a lower tree density and in a larger mean diameter. Such features are often correlated with a larger amount of dead wood which, in turn, promotes the presence of cavity nesters, otherwise rare-to-absent in the bird community. Forest structure is largely influenced by forest management that can be guided to benefit specific bird assemblages by applying specific treatments focused at increasing structural diversity and at multi-functionality.

Science, statistics and surveys: a herpetological perspective.

Science, statistics and surveys: a herpetological perspective.

Rachel S. McCrea and Byron J. T. Morgan, Analysis of Capture–Recapture Data

Analysis of Capture–Recapture Data by McCrea and Morgan is an excellent, easy to read monograph about capture–recapture models. In this book, the authors provide a concise overview of traditional closed population capture–recapture models (Models M0, Mb, Mh, etc.), individual covariate models, and open population models such as the Cormack–Jolly– Seber, Jolly–Seber models, multi-state models, andmore recent developments such as occupancy models, state-space models, and integrated population models. The authors write “In this book we aim to cover the many modern developments in the area of capture–recapture and related models, and to set them in historical context of relevant research over the past 100 years.” The book does a good job of achieving this objective. And it is a very easy to read because it is well organized and the writing is clear and concise. I would recommend this book as a reference for the quantitative ecologist or statistician interested in knowing what’s out there. And I’m glad to have it on my bookshelf. The main topical chapters focus on specific classes of capture–recapture models and contain a mix of classical concepts and methods as well as more recent innovations. For example, the chapter on closed population models contains material on N-mixture models and also spatial capture–recapture models1. There is a strong emphasis on mark-recovery models which are important when band recoveries are available. I think chapters 11 and 12 are the strongest. Chapter 11, on state-space models (covering Gaussian time-series models and Kalman filtering), is not specifically a capture–recapture topic but sometimes used as a component of integrated population models and the concepts are of general interest in population modeling. This chapter also covers state-space formulations of CJS and

Repeated count surveys help standardize multi-agency estimates of American Oystercatcher (Haematopus palliatus) abundance

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 pro...

The northern coastal forests of Kenya are nationally and globally important for the conservation of Aders’ duiker Cephalophus adersi and other antelope species

Aders’ duiker Cephalophus adersi is a critically endangered small antelope endemic to the coastal forests of east Africa. Threatened by habitat loss and hunting, the species was until recently known to persist only on Zanzibar, Tanzania, and in the Arabuko-Sokoke National Reserve, Kenya. However, more recent observations, have confirmed the occurrence of Aders’ duiker in Kenyan coastal forests north of the Tana River. This paper reports systematic camera trapping results for three sites in the Boni–Dodori coastal forest system north of the Tana and the only other known mainland site for Aders’ duiker, the Arabuko-Sokoke forest. From a total survey effort of 5,723 camera trap days, we demonstrated that the known area of occurrence for Aders’ duiker has more than doubled with occupancy values at or close to 100 % for all three northern sites. An index of relative abundance for Aders’ duiker was also one to two orders of magnitude greater at these sites compared to Arabuko-Sokoke. Application of a replicate count N-mixture model to camera trap data from Boni National Reserve resulted in an estimate of 7.3 Aders’ duikers/km2 (95 % CI 4.5–10.1/km2). The results also indicate higher densities of suni Nesotragus moschatus and Harvey’s duiker Cephalophus harveyi in the northern forests relative to Arabuko-Sokoke. Blue duiker Philantomba monticola was recorded at low density in Arabuko-Sokoke forest but not detected at the northern sites. These findings significantly improve the conservation prospects for Aders’ duiker and highlight the global importance of the northern coastal forests of Kenya.

Computational aspects of N-mixture models.

The N-mixture model is widely used to estimate the abundance of a population in the presence of unknown detection probability from only a set of counts subject to spatial and temporal replication (Royle, 2004, Biometrics 60, 105–115). We explain and exploit the equivalence of N-mixture and multivariate Poisson and negative-binomial models, which provides powerful new approaches for fitting these models. We show that particularly when detection probability and the number of sampling occasions are small, infinite estimates of abundance can arise. We propose a sample covariance as a diagnostic for this event, and demonstrate its good performance in the Poisson case. Infinite estimates may be missed in practice, due to numerical optimization procedures terminating at arbitrarily large values. It is shown that the use of a bound, K, for an infinite summation in the N-mixture likelihood can result in underestimation of abundance, so that default values of K in computer packages should be avoided. Instead we propose a simple automatic way to choose K. The methods are illustrated by analysis of data on Hermann's tortoise Testudo hermanni.

Using dynamic N-mixture models to test cavity limitation on northern flying squirrel demographic parameters using experimental nest box supplementation.

Dynamic N-mixture models have been recently developed to estimate demographic parameters of unmarked individuals while accounting for imperfect detection. We propose an application of the Dail and Madsen (2011: Biometrics, 67, 577–587) dynamic N-mixture model in a manipulative experiment using a before-after control-impact design (BACI). Specifically, we tested the hypothesis of cavity limitation of a cavity specialist species, the northern flying squirrel, using nest box supplementation on half of 56 trapping sites. Our main purpose was to evaluate the impact of an increase in cavity availability on flying squirrel population dynamics in deciduous stands in northwestern Québec with the dynamic N-mixture model. We compared abundance estimates from this recent approach with those from classic capture–mark–recapture models and generalized linear models. We compared apparent survival estimates with those from Cormack–Jolly–Seber (CJS) models. Average recruitment rate was 6 individuals per site after 4 years. Nevertheless, we found no effect of cavity supplementation on apparent survival and recruitment rates of flying squirrels. Contrary to our expectations, initial abundance was not affected by conifer basal area (food availability) and was negatively affected by snag basal area (cavity availability). Northern flying squirrel population dynamics are not influenced by cavity availability at our deciduous sites. Consequently, we suggest that this species should not be considered an indicator of old forest attributes in our study area, especially in view of apparent wide population fluctuations across years. Abundance estimates from N-mixture models were similar to those from capture–mark–recapture models, although the latter had greater precision. Generalized linear mixed models produced lower abundance estimates, but revealed the same relationship between abundance and snag basal area. Apparent survival estimates from N-mixture models were higher and less precise than those from CJS models. However, N-mixture models can be particularly useful to evaluate management effects on animal populations, especially for species that are difficult to detect in situations where individuals cannot be uniquely identified. They also allow investigating the effects of covariates at the site level, when low recapture rates would require restricting classic CMR analyses to a subset of sites with the most captures.

Coping with heterogeneity to detect species on a large scale: N-mixture modeling applied to red-legged partridge abundance

The reliability of long-term population estimates is crucial for conservation and management purposes. Most game species population monitoring programs assume that count indices are proportionally related to abundance. However, this assumption is untenable when detection varies spatially and temporally. We assessed whether N-mixture models, which allow detection modeling using spatially and temporally repeated count data, were relevant for monitoring the population of red-legged partridge (Alectoris rufa). Unbiased estimates are needed for calculating hunting quotas for this game species. We used the simple aural playback point-count method and adatasetof 121 point-transects(n ¼16,288 counts) collected from 1992 to 2010. Covariates such as date, hour, wind, rain, and vegetation density influenced detection probability. Estimated abundance ranged from 0 to 15 males per point and exhibited variable coefficients of variation depending on sites (range: 0.14-1.31, mean: 0.44). We found a positive and linear relationship between the abundance estimated by the N-mixture model and the densities provided by 2 other counting methods, square sampling and kilometric abundance index, but not with blank beat. We established a maximum detection radius for the playback surveys, which enabled conversion of abundance at the points into density. The N-mixture modeling approach is more cost-effective for game species monitoring than capture-recapture methods or square sampling, and more reliable than indices of relative abundances. 2014 The Wildlife Society.

Influence of hiking trails on montane birds

Montane forests contribute significantly to regional biodiversity. Long-term monitoring data, often located along hiking trails, suggests that several indicator species of this ecosystem have declined in recent decades. Declining montane bird populations have been attributed to anthropogenic stressors such as climate change and atmospheric deposition. Several studies from montane systems have also documented decreased estimates of abundance and reproductive success as well as altered singing rates near hiking trails. Therefore, recreational hiking may be contributing to montane bird population declines and potentially biased population estimates because of trail avoidance or altered detection probabilities near trails. We studied the effect of hiking trails on the abundance, seasonal movements, and detection probabilities of montane birds in the White Mountains, New Hampshire in 2006 and 2007. We used hierarchical, generalized N-mixture models that account for imperfect detection probabilities to examine the effects of recreational hiking on bird communities. We also examined the potential effects of hiking on the reproductive success of a boreal forest songbird, blackpoll warbler (Setophaga striata). We found little evidence to suggest hiking trails influence abundance, detection probabilities, or within and among seasonal movements of montane forest birds. We also found no evidence to suggest daily nest survival of blackpoll warbler nests vary with distance from trail. Our study suggests that recent increases in hiking traffic are unlikely to have caused declines in montane birds in this region. Furthermore, our results provide evidence that trail-based monitoring programs can provide accurate and efficient estimates of abundance for some montane forest bird species in the White Mountains of New Hampshire. © 2014 The Wildlife Society.

Inferences about population dynamics from count data using multistate models: a comparison to capture–recapture approaches

Wildlife populations consist of individuals that contribute disproportionately to growth and viability. Understanding a population's spatial and temporal dynamics requires estimates of abundance and demographic rates that account for this heterogeneity. Estimating these quantities can be difficult, requiring years of intensive data collection. Often, this is accomplished through the capture and recapture of individual animals, which is generally only feasible at a limited number of locations. In contrast, N-mixture models allow for the estimation of abundance, and spatial variation in abundance, from count data alone. We extend recently developed multistate, open population N-mixture models, which can additionally estimate demographic rates based on an organism's life history characteristics. In our extension, we develop an approach to account for the case where not all individuals can be assigned to a state during sampling. Using only state-specific count data, we show how our model can be used to estimate local population abundance, as well as density-dependent recruitment rates and state-specific survival. We apply our model to a population of black-throated blue warblers (Setophaga caerulescens) that have been surveyed for 25 years on their breeding grounds at the Hubbard Brook Experimental Forest in New Hampshire, USA. The intensive data collection efforts allow us to compare our estimates to estimates derived from capture–recapture data. Our model performed well in estimating population abundance and density-dependent rates of annual recruitment/immigration. Estimates of local carrying capacity and per capita recruitment of yearlings were consistent with those published in other studies. However, our model moderately underestimated annual survival probability of yearling and adult females and severely underestimates survival probabilities for both of these male stages. The most accurate and precise estimates will necessarily require some amount of intensive data collection efforts (such as capture–recapture). Integrated population models that combine data from both intensive and extensive sources are likely to be the most efficient approach for estimating demographic rates at large spatial and temporal scales.

Modeling structured population dynamics using data from unmarked individuals

The study of population dynamics requires unbiased, precise estimates of abundance and vital rates that account for the demographic structure inherent in all wildlife and plant populations. Traditionally, these estimates have only been available through approaches that rely on intensive mark-recapture data. We extended recently developed N-mixture models to demonstrate how demographic parameters and abundance can be estimated for structured populations using only stage-structured count data. Our modeling framework can be used to make reliable inferences on abundance as well as recruitment, immigration, stage-specific survival, and detection rates during sampling. We present a range of simulations to illustrate the data requirements, including the number of years and locations necessary for accurate and precise parameter estimates. We apply our modeling framework to a population of northern dusky salamanders (Desmognathus fuscus) in the mid-Atlantic region (USA) and find that the population is unexpectedly declining. Our approach represents a valuable advance in the estimation of population dynamics using multistate data from unmarked individuals and should additionally be useful in the development of integrated models that combine data from intensive (e.g., mark-recapture) and extensive (e.g., counts) data sources.

Detection heterogeneity and abundance estimation in populations of Golden-cheeked Warblers (Setophaga chrysoparia)

ABSTRACT. Abundance estimators that account for imperfect detection, such as N-mixture models, assume that detection of individuals is independent of abundance. Using spot-mapping and N-mixture models applied to point-count data, we estimated abundance of Goldencheeked Warblers (Setophaga chrysoparia) in two years at six study sites at the Balcones Canyonlands Preserve, Austin, Texas. N-mixture model estimates deviated from spot-mapping estimates at the site level by overestimating at low abundances, and at the survey-station level by underestimating at high abundance, which suggests that model assumptions may have been violated. We tested whether detection of individuals is influenced by abundance by assessing per capita song rate in relation to abundance. Per capita song rate increased with abundance, illustrating how the behavior of a territorial passerine may violate the independent-detectability assumption. We next explored violation of this assumption at the survey-station level by applying N-mixtur...

Short-term responses of small mammals to timber harvest in the United States Central Hardwood Forest Region

Identifying the effect of timber harvest on plant and animal communities is important for managers seeking to conserve ecosystem function. Timber harvest affects many forest species, including small mammals, a key component of forest food webs. We studied short-term responses of several common small-mammal species to clearcutting and shelterwood harvest in hardwood forests of southern Indiana. We trapped small mammals at 32 forest stands for 2 years before harvest. Each stand then received a timber harvest treatment: either the creation of a 0.4-, 2-, or 4-ha clearcut opening, shelterwood harvest, or no harvest. Following harvest, we trapped small mammals for 3 additional years. We estimated abundance from capture data and compared estimates before and after harvests using an N-mixture model fit in a Bayesian framework. Small mammals in our study differed in their responses to timber harvest. Eastern chipmunks (Tamias striatus) increased in all clearcut opening sizes, whereas white-footed mice (Peromyscus leucopus) and short-tailed shrews (Blarina brevicauda) were less abundant in larger clearcuts. The first stage (midstory removal) of a 3-stage shelterwood harvest had no impact on the small-mammal community. Mast production influenced small-mammal populations independent of silvicultural treatments. In the years immediately following harvest, managers can expect populations of common small-mammal species to increase or remain unchanged in small clearcut openings, but some species decline in larger openings that reduce the edge to interior ratio of habitat created. The phased shelterwood harvest system in which habitat is altered over a longer period may be ideal for maintaining existing small-mammal populations. © 2013 The Wildlife Society.

Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts

The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability.

Painted Bunting Abundance and Habitat Use in Florida

Abstract - A cooperative multi-state monitoring effort was initiated for Passerina ciris (Painted Bunting) in 2008 because of a suspected decline in its eastern population. The Florida component of this range-wide study was conducted during 3 consecutive breeding seasons to obtain a better understanding of abundance and habitat use (vegetation associations) than could be obtained from existing indices, to examine factors affecting detectability, and to determine whether short-term trends could be assessed. Sample units (three hundred two 0.01–27-km2 blocks) were allocated for Florida from which 22 were randomly selected, within which 101 point-count survey stations were established. Point-count surveys (n = 906) were conducted annually from 2008 to 2010, and vegetation characteristics were quantified for each location. Abundances were estimated from the counts by an N-mixture model for open populations. Estimated mean breeding density of male Painted Buntings in Florida decreased from 12.4 males/km2 in 20...

Balancing Precision and Risk: Should Multiple Detection Methods Be Analyzed Separately in N-Mixture Models?

Using multiple detection methods can increase the number, kind, and distribution of individuals sampled, which may increase accuracy and precision and reduce cost of population abundance estimates. However, when variables influencing abundance are of interest, if individuals detected via different methods are influenced by the landscape differently, separate analysis of multiple detection methods may be more appropriate. We evaluated the effects of combining two detection methods on the identification of variables important to local abundance using detections of grizzly bears with hair traps (systematic) and bear rubs (opportunistic). We used hierarchical abundance models (N-mixture models) with separate model components for each detection method. If both methods sample the same population, the use of either data set alone should (1) lead to the selection of the same variables as important and (2) provide similar estimates of relative local abundance. We hypothesized that the inclusion of 2 detection methods versus either method alone should (3) yield more support for variables identified in single method analyses (i.e. fewer variables and models with greater weight), and (4) improve precision of covariate estimates for variables selected in both separate and combined analyses because sample size is larger. As expected, joint analysis of both methods increased precision as well as certainty in variable and model selection. However, the single-method analyses identified different variables and the resulting predicted abundances had different spatial distributions. We recommend comparing single-method and jointly modeled results to identify the presence of individual heterogeneity between detection methods in N-mixture models, along with consideration of detection probabilities, correlations among variables, and tolerance to risk of failing to identify variables important to a subset of the population. The benefits of increased precision should be weighed against those risks. The analysis framework presented here will be useful for other species exhibiting heterogeneity by detection method.