Nondetection of a species at site does not imply that the is absent unless probability detection 1. We propose model and likelihood-based method for estimating occupancy rates when probabilities are <1. The provides flexible framework enabling covariate information to be included allowing missing observations. Via computer simulation, we found good estimates rates, generally unbiased moderate (>0.3). estimated two anuran 32 wetland sites in Maryland, USA, from data collected during 2000 as...

Spatial replication is a common theme in count surveys of animals. Such often generate sparse data from which it difficult to estimate population size while formally accounting for detection probability. In this article, I describe class models (N-mixture models) allow estimation such data. The key idea view site-specific sizes, N, as independent random variables distributed according some mixing distribution (e.g., Poisson). Prior parameters are estimated the marginal likelihood data,...

Summary The fraction of sampling units in a landscape where target species is present (occupancy) an extensively used concept ecology. Yet many applications the will not always be detected unit even when present, resulting biased estimates occupancy. Given that are surveyed repeatedly within relatively short timeframe, number similar methods have now been developed to provide unbiased occupancy estimates. However, practical guidance on efficient design studies has lacking. In this paper we...

We describe an approach for estimating occupancy rate or the proportion of area occupied when heterogeneity in detection probability exists as a result variation abundance organism under study. The key feature such problems, which we exploit, is that induces probability. Thus, can be modeled Moreover, this linkage between and allows one to exploit heterogeneous model estimate underlying distribution abundances. Therefore, our method estimation from repeated observations presence absence...

Summary Recently, interest in species distribution modelling has increased following the development of new methods for analysis presence‐only data and deployment these user‐friendly powerful computer programs. However, reliable inference from tools requires that several assumptions be met, including observed presences are consequence random or representative sampling detectability during does not vary with covariates determine occurrence probability. Based on our interactions researchers...

We develop a model that uses repeated observations of biological community to estimate the number and composition species in community. Estimators community-level attributes are constructed from model-based estimators occurrence individual incorporate imperfect detection individuals. Data North American Breeding Bird Survey analyzed illustrate variety ecologically important quantities easily estimated using our occurrence. In particular, we compute site-specific estimates richness honor...

A statistical model is developed for estimating species richness and accumulation by formulating these community-level attributes as functions of model-based estimators occurrence while accounting imperfect detection individual species. The requires a sampling protocol wherein repeated observations are made at collection sample locations selected to be representative the community. This temporal replication provides data needed resolve ambiguity between absence nondetection when unobserved...

Summary 1. Understanding the factors affecting species occurrence is a pre‐eminent focus of applied ecological research. However, direct information about lacking for many species. Instead, researchers sometimes have to rely on so‐called presence‐only data (i.e. when no absences available), which often results from opportunistic, unstructured sampling. maxent widely used software program designed model and map distribution using data. 2. We provide critical review as modelling discuss how it...

Species occurrence and its dynamic components, extinction colonization probabilities, are focal quantities in biogeography metapopulation biology, for species conservation assessments. It has been increasingly appreciated that these parameters must be estimated separately from detection probability to avoid the biases induced by non-detection error. Hence, there is now considerable theoretical practical interest occupancy models contain explicit representations of dynamics such as...

Nondetection of a species at site does not imply that the is absent unless probability detection 1. We propose model and likelihood-based method for estimating occupancy rates when probabilities are <1. The provides flexible framework enabling covariate information to be included allowing missing observations. Via computer simulation, we found good estimates rates, generally unbiased moderate (>0.3). estimated two anuran 32 wetland sites in Maryland, USA, from data collected during 2000 as...

Estimating density is a fundamental objective of many animal population studies. Application methods for estimating size from ostensibly closed populations widespread, but ineffective absolute because most are subject to short-term movements or so-called temporary emigration. This phenomenon invalidates the resulting estimates effective sample area unknown. A number involving adjustment based on heuristic considerations in widespread use. In this paper, hierarchical model spatially indexed...

Site occupancy models have been developed that allow for imperfect species detection or "false negative" observations. Such become widely adopted in surveys of many taxa. The most fundamental assumption underlying these is positive" errors are not possible. That is, one cannot detect a where it does occur. However, such possible sampling situations number reasons, and even low false positive error rates can induce extreme bias estimates site when they accounted for. In this paper, we develop...

Relationships between species abundance and occupancy are of considerable interest in metapopulation biology macroecology. Such relationships may be described concisely using probability models that characterize variation a species. However, estimation the parameters these most ecological problems is impaired by imperfect detection. When organisms detected imperfectly, observed counts biased estimates true abundance, this induces bias stated or occurrence probability. In paper we consider...

Abundance estimation in ecology is usually accomplished by capture–recapture, removal, or distance sampling methods. These may be hard to implement at large spatial scales. In contrast, binomial mixture models enable abundance without individual identification, based simply on temporally and spatially replicated counts. Here, we evaluate using data from the national breeding bird monitoring program Switzerland, where some 250 1‐km 2 quadrats are surveyed territory mapping method three times...

Detecting individuals of amphibian and reptile species can be a daunting task. Detection hindered by various factors such as cryptic behavior, color patterns, or observer experience. These complicate the estimation state variables interest (e.g., abundance, occupancy, richness) well vital rates that induce changes in these survival probabilities for abundance; extinction occupancy). Although ad hoc methods counts uncorrected detection, return rates) typically perform poorly face no they...

Summary 1. Species richness is often used as a tool for prioritizing conservation action. One method predicting and other summaries of community structure to develop species‐specific models occurrence probability based on habitat or landscape characteristics. However, this approach can be challenging rare elusive species which survey data are sparse. 2. Recent developments have allowed improved inference about probability, integrated within hierarchical modelling framework. This framework...

We develop a class of models for inference about abundance or density using spatial capture–recapture data from studies based on camera trapping and related methods. The model is hierarchical composed two components: point process describing the distribution individuals in space (or their home range centers) observation traps. suppose that trap‐ individual‐specific capture probabilities are function distance between individual centers trap locations. show can be regarded as generalized...

Recently developed spatial capture-recapture (SCR) models represent a major advance over traditional (CR) because they yield explicit estimates of animal density instead population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR account for heterogeneity in capture probability arising from the juxtaposition activity centers and sample locations. Although utility methods is gaining recognition, requirement that all individuals can be uniquely identified excludes...

Occupancy modeling focuses on inference about the distribution of organisms over space, using temporal or spatial replication to allow detection process. Inference based strictly requires that replicates be selected randomly and with replacement, but importance these design requirements is not well understood. This paper an increasingly popular sampling are expected exhibit Markovian dependence. We develop two new occupancy models for data collected under this sort design, one underlying...

Abstract Species distribution models (SDMs) are widely applied to understand the processes governing spatial and temporal variation in species abundance but often do not account for measurement errors such as false negatives positives. We describe unmarked , a package freely available open‐source R software that provides complete workflow modelling while explicitly accounting errors. Here we focus on recent advances functionality support multi‐species, multi‐state, multi‐season data, well...

Distance-sampling methods are commonly used in studies of animal populations to estimate population density. A common objective such is evaluate the relationship between abundance or density and covariates that describe habitat other environmental influences. However, little attention has been focused on modeling covariate effects conventional distance-sampling models. In this paper we propose a model accommodates abundance. The based specification likelihood at level sample unit terms local...