unmarked: An R Package for Fitting Hierarchical Models of Wildlife Occurrence and Abundance

Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientific questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mechanisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unified modeling interface. The R package unmarked provides such a unified modeling framework, including tools for data exploration, model fitting, model criticism, post-hoc analysis, and model comparison

Spatially explicit models for inference about density in unmarked or partially marked populations

Recently developed spatial capture-recapture (SCR) models represent a major advance over traditional capture-recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5-10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19-1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating that neither spatial independence nor individual recognition is needed to estimate population density - rather, spatial dependence can be informative about individual distribution and density.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS610 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

The forest resources of rural householders in Dent County, Missouri

This bulletin reports on School of Forestry research project 124, Timber Economics--P. [3].Digitized 2007 AES.Includes bibliographical references (page 21)

Uncertainty and the Entanglement of Habitat Loss and Fragmentation Effects in the Management of Northern Bobwhite

There is a need to understand the effects of habitat loss and fragmentation on northern bobwhite (Colinus virginianus) and other grassland bird species and relate this to conservation action and delivery, especially in areas of intensive anthropogenic development. Through our research, we investigated the factors contributing to habitat loss and fragmentation in order to prioritize management within the Gulf Coast Prairie Landscape Conservation Cooperative (GCP LCC) region of Texas, USA. For this geographic region, we completed these objectives: analyzed grassland bird habitat loss and fragmentation resulting from oil and gas development, which has become especially rapid in this region beginning in 2008, projected future habitat loss under possible future economic scenarios, modeled the outcomes of potential management alternatives, and identified drivers of habitat loss and fragmentation to direct management action toward minimizing threats to high-risk habitats. Using a modeling approach, we identified suitable bobwhite habitat and prioritized high-risk areas, particularly focusing on the best candidate areas for successful restoration. Briefly, point count data were related to patch- and landscape-level habitat characteristics using a modeling technique that formally estimated the scale of the landscape effect on bobwhite abundance. Thereafter, we identified possible management alternatives with the guidance of the GCP LCC and other stakeholders and modeled the consequences of these alternatives. Using results from this modeling, we produced an extinction risk map for northern bobwhite in this region. Our research adds to the understanding of the relationship between northern bobwhite populations and the expansion of energy extraction and also uses modeling informed by data to support a decision-making framework that incorporates uncertainty about this system to prioritize the conservation of high-risk and high-value areas of bobwhite habitat

Effects of Broad-Scale Conservation on Northern Bobwhite Populations in Agricultural Landscapes

Private land initiatives such as the Conservation Reserve Enhancement Program (CREP) are avenues for broad-scale northern Bobwhite (Colinus virginianus) conservation. The CREP in Kentucky established 40,468 ha of native prairie grasses and riparian corridors in the Green River Basin. Northern bobwhite responses to similar conservation measures at local scales (i.e., the site of implementation) have been positive; however, the geographic extent of the influence of private land initiatives on populations is less understood. Our objectives were to investigate landscape-scale effects of CREP on northern bobwhite populations. Using a stratified random sampling design, 254 roadside point counts were performed over 5 years throughout the Green River Basin along a gradient of landscape-scale CREP density. Local-scale (500 m radius) CREP density was held constant at monitoring points. We analyzed data using an openpopulation distance sampling model that included estimators of appropriate landscape scale and strength of density dependence. Population response to the CREP was positive and outweighed conservation footprint. Our results suggest that broad-scale conservation can influence wildlife populations outside of targeted areas. Concurrently, because the majority of land in the Eastern U.S. is privately owned, private land conservation initiatives present an effective strategy for promoting wildlife population recovery across large areas. Our future directions with this research include improving model estimators, determining mechanisms behind landscape-scale effects of CREP, and determining the influence of the spatial arrangement of landscape features on local populations

Habitat associations of Golden-winged Warblers and Blue-winged Warblers during the non-breeding season

The Golden-winged Warbler (Vermivora chyrsoptera) and Blue-winged Warbler (Vermivora cyanoptera) are both Neotropical migratory species of elevated conservation concern that overlap in distribution on their Central American wintering grounds, yet the extent to which they overlap in terms of habitat use is unknown, potentially hindering conservation efforts. We surveyed these two species along habitat and elevational gradients within a coffee-growing landscape during 2016 and 2017 in Yoro, Honduras. We used playback with a mobbing track known to enhance detections of female warblers, since examining sexual habitat segregation was another objective of our study. Habitat occupied by these two species differed, with male Golden-winged Warblers occurring in landscapes dominated by humid forest/coffee (forest with some dense shade coffee, which were indistinguishable with remote sensing at our sites) at higher elevations than male Blue-winged Warblers, which were positively associated with the amount of agriculture in the landscape. Six of seven female Golden-winged Warblers were encountered in shade coffee, however, this association was not significant, likely due to small sample size and low detectability. The association between male Golden-winged Warblers and humid forest/coffee and elevation, and contrasts in habitat use between male and female Golden-winged Warblers, are consistent with prior research in the region. Furthermore, the landscape associations of these non-breeding Vermivora species mirror their breeding landscape associations, with Golden-winged Warblers occupying more forested landscapes and Blue-winged Warblers occupying more agricultural landscapes. The use of shade coffee by female Golden-winged Warblers and Blue-winged Warblers suggests agroforestry could be a promising tool for conserving wintering populations of these species, although this result should be viewed with caution given that use of shade coffee is reported to elevate predation risk in other migratory species, and may not provide habitat for forest-dependent resident birds