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. Recent advances in occupancy estimation that adjust for imperfect detection have provided substantial improvements over traditional approaches and are receiving considerable use applied ecology. To estimate detectability, modelling requires multiple surveys at a site the assumption of ‘closure’ between surveys, i.e. no changes surveys. Violations this could bias parameter estimates; however, little work has assessed model sensitivity to violations or how commonly such occur...

Abstract Aim During the past decade ecologists have attempted to estimate parameters of species distribution models by combining locations presence observed in opportunistic surveys with spatially referenced covariates occurrence. Several statistical been proposed for analysis presence‐only data, but these largely ignored effects imperfect detection and survey bias. In this paper I describe a model‐based approach data that accounts errors individuals biased selection locations. Innovation...

Environmental DNA (eDNA) methods are used to detect that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be estimate occurrence and detection probabilities thereby account for imperfect detection. However, terminology has been applied inconsistently many have calculated while not considering effects of Low invasive giant constrictors using visual surveys traps hampered estimation estimates needed population management...

Multinomial models with unknown index (“sample size”) arise in many practical settings. In practice, Bayesian analysis of such has proved difficult because the dimension parameter space is not fixed, being some cases a function index. We describe data augmentation approach to this class that provides for generic and efficient implementation. Under approach, are augmented all-zero detection histories. The resulting dataset modeled as zero-inflated version complete-data model where an...

Summary 1. Trends of animal populations are great interest in ecology but cannot be directly observed owing to imperfect detection. Binomial mixture models use replicated counts estimate abundance, corrected for detection, demographically closed populations. Here, we extend these open and illustrate them using sand lizard Lacerta agilis from the national Dutch reptile monitoring scheme. 2. Our model requires multiple sites each several periods, within which population closure is assumed....

We develop a parameterization of the beta-binomial mixture that provides sensible inferences about size closed population when probabilities capture or detection vary among individuals. Three classes models (beta-binomial, logistic-normal, and latent-class) are fitted to recaptures snowshoe hares for estimating abundance counts bird species richness. In both sets data, rates appear more individuals (animals species) than sampling occasions locations. The estimates richness sensitive...

In this article, we describe ednaoccupancy, an r package for fitting Bayesian, multiscale occupancy models. These models are appropriate surveys that include three nested levels of sampling: primary sample units within a study area, secondary collected from each unit and replicates unit. This design is commonly used in environmental DNA (eDNA). ednaoccupancy allows users to specify fit with or without covariates, estimate posterior summaries occurrence detection probabilities, compare...

A set of universal guidelines is needed to determine the limit detection (LOD) in PCR-based analyses low-concentration DNA. In particular, environmental DNA (eDNA) studies require sensitive and reliable methods detect rare cryptic species through shed genetic material samples. Current strategies for assessing limits eDNA are either too stringent or subjective, possibly resulting biased estimates species' presence. Here, a conservative LOD analysis grounded analytical chemistry proposed...

Summary Two main sources of data for species distribution models (SDMs) are site‐occupancy (SO) from planned surveys, and presence‐background (PB) opportunistic surveys other sources. SO give high quality about presences absences the in a particular area. However, due to their cost, they often cover smaller area relative PB data, usually not representative geographic range species. In contrast, is plentiful, covers larger area, but less reliable lack information on absences, characterised by...

A critical variable in both ecological and conservation field studies is determining how many individuals of a species are present within defined sampling area. Labor intensive techniques such as capture-mark-recapture removal may provide estimates abundance, but there logistical constraints to their widespread application. Many on terrestrial aquatic salamanders use counts an index assuming that detection remains constant while sampling. If this constancy violated, determination...

Species richness is the most common biodiversity metric, although typically some species remain unobserved. Therefore, estimates of and related quantities should account for imperfect detectability. Community dynamics can often be represented as superposition species‐specific phenologies (e.g., in taxa with well‐defined flight [insects], activity [rodents], or vegetation periods [plants]). We develop a model such predictably open communities wherein expressed sum over observed unobserved...

Models currently used to estimate patterns of species co-occurrence while accounting for errors in detection can be difficult fit when the effects covariates on occurrence probabilities are included. The source estimation problems is particular parameterization specify probability. We develop a new estimating interacting that allows specified quite naturally without problems. In our model, one assumed depend another, but second not presence first species. This pattern co-occurrence, wherein...

A variety of processes are thought to be involved in the formation and dynamics species assemblages. For example, various metacommunity theories based on differences relative contributions dispersal among local communities interactions within communities. Interestingly, continue advanced without much empirical validation. Part problem is that statistical models used analyze typical survey data either fail specify ecological with sufficient, complexity or they account for errors detection...

Summary Several models have been developed to predict the geographic distribution of a species by combining measurements covariates occurrence at locations where is known be present with same other status (presence or absence) unknown. In absence detection errors, spatial point‐process and binary‐regression for case‐augmented surveys provide consistent estimators species’ without prior knowledge prevalence. addition, these regression can modified produce abundance that are asymptotically...

Abstract During the 20th century ecologists largely relied on frequentist system of inference for analysis their data. However, in past few decades have become increasingly interested use Bayesian methods data analysis. In this article I provide guidance to who would like decide whether can be used improve conclusions and predictions. begin by providing a concise summary analysis, including comparison differences between approaches when using hierarchical models. Next list problems where may...

Bayesian inference and decision theory may be used in the solution of relatively complex problems natural resource management, owing to recent advances statistical computing. In particular, Markov chain Monte Carlo algorithms provide a computational framework for fitting models adequate complexity evaluating expected consequences alternative management actions. We illustrate these features using an example based on waterfowl habitat. Corresponding Editor: D. B. Lindenmayer.

Summary The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival fecundity plant animal populations have developed quantitative approaches study the dynamics population size. Of particular interest invasive species. Such nonindigenous animals plants can levy significant impacts on native communities. Effective models for relative abundance been developed; however, a better understanding actual size (as opposed...

Summary A statistical modeling framework is described for estimating the abundances of spatially distinct subpopulations animals surveyed using removal sampling. To illustrate this framework, hierarchical models are developed Poisson and negative‐binomial distributions to model variation in abundance among beta distribution capture probabilities. These fitted counts observed a survey federally endangered fish species. The resulting estimates have similar or better precision than those...

Summary Spatially clustered populations create unique challenges for conservation monitoring programmes. Advances in methodology typically are focused on either the design or modelling stage of study but do not involve integration both. We integrate adaptive cluster sampling and spatial occupancy by developing two models to handle dependence induced sampling. compare these scenarios using simple random traditional via simulation data collected a rare plant species, Tamarix ramosissima ,...