Nondetection of a species at a site does not imply that the species is absent unless the probability of detection is 1. We propose a model and likelihood-based method for estimating site occupancy rates when detection probabilities are 0.3). We estimated site occupancy rates for two anuran species at 32 wetland sites in Maryland, USA, from data collected during 2000 as part of an amphibian monitoring program, Frogwatch USA. Site occupancy rates were estimated as 0.49 for American toads (Bufo americanus), a 44% increase over the proportion of sites at which they were actually observed, and as 0.85 for spring peepers (Pseudacris crucifer), slightly above the observed proportion of 0.83.

/pdf/estimating-site-occupancy-rates-when-detection-probabilities-3listkvns9.pdf

Estimating site occupancy rates when detection probabilities are less than one

1980 Preface * 1999 Preface * 1999 Acknowledgements * Introduction * 1 Circular Logic * 2 Phase Singularities (Screwy Results of Circular Logic) * 3 The Rules of the Ring * 4 Ring Populations * 5 Getting Off the Ring * 6 Attracting Cycles and Isochrons * 7 Measuring the Trajectories of a Circadian Clock * 8 Populations of Attractor Cycle Oscillators * 9 Excitable Kinetics and Excitable Media * 10 The Varieties of Phaseless Experience: In Which the Geometrical Orderliness of Rhythmic Organization Breaks Down in Diverse Ways * 11 The Firefly Machine 12 Energy Metabolism in Cells * 13 The Malonic Acid Reagent ('Sodium Geometrate') * 14 Electrical Rhythmicity and Excitability in Cell Membranes * 15 The Aggregation of Slime Mold Amoebae * 16 Numerical Organizing Centers * 17 Electrical Singular Filaments in the Heart Wall * 18 Pattern Formation in the Fungi * 19 Circadian Rhythms in General * 20 The Circadian Clocks of Insect Eclosion * 21 The Flower of Kalanchoe * 22 The Cell Mitotic Cycle * 23 The Female Cycle * References * Index of Names * Index of Subjects

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/596B270197FE27DE5FABB598B6210622/S0025557200150892a.pdf/div-class-title-span-class-italic-the-geometry-of-biological-time-span-by-a-t-winfree-pp-544-dm68-corrected-second-printing-1990-isbn-3-540-52528-9-springer-div.pdf

The geometry of biological time , by A. T. Winfree. Pp 544. DM68. Corrected Second Printing 1990. ISBN 3-540-52528-9 (Springer)

Despite being recognized as a promoter of diversity and a condition for local coexistence decades ago, the importance of intraspecific variance has been neglected over time in community ecology. Recently, there has been a new emphasis on intraspecific variability. Indeed, recent developments in trait-based community ecology have underlined the need to integrate variation at both the intraspecific as well as interspecific level. We introduce new T-statistics ('T' for trait), based on the comparison of intraspecific and interspecific variances of functional traits across organizational levels, to operationally incorporate intraspecific variability into community ecology theory. We show that a focus on the distribution of traits at local and regional scales combined with original analytical tools can provide unique insights into the primary forces structuring communities.

/pdf/the-return-of-the-variance-intraspecific-variability-in-5yhbt5e8oz.pdf

The return of the variance: intraspecific variability in community ecology

We describe an approach for estimating occupancy rate or the proportion of area occupied when heterogeneity in detection probability exists as a result of variation in abundance of the organism under study. The key feature of such problems, which we exploit, is that variation in abundance induces variation in detection probability. Thus, heterogeneity in abundance can be modeled as heterogeneity in detection probability. Moreover, this linkage between heterogeneity in abundance and heterogeneity in detection probability allows one to exploit a heterogeneous detection probability model to estimate the underlying distribution of abundances. Therefore, our method allows estimation of abundance from repeated observations of the presence or absence of animals without having to uniquely mark individuals in the population.

Estimating abundance from repeated presence–absence data or point counts

The global emergence and spread of the pathogenic, virulent, and highly transmissible fungus Batrachochytrium dendrobatidis, resulting in the disease chytridiomycosis, has caused the decline or extinction of up to about 200 species of frogs. Key postulates for this theory have been completely or partially fulfilled. In the absence of supportive evidence for alternative theories despite decades of research, it is important for the scientific community and conservation agencies to recognize and manage the threat of chytridiomycosis to remaining species of frogs, especially those that are naive to the pathogen. The impact of chytridiomycosis on frogs is the most spectacular loss of vertebrate biodiversity due to disease in recorded history.

/pdf/spread-of-chytridiomycosis-has-caused-the-rapid-global-3258w0sbzd.pdf

Spread of Chytridiomycosis Has Caused the Rapid Global Decline and Extinction of Frogs

Summary. Agresti (1994, Biometrics50, 494–500) and Norris and Pollock (1996a, Biometrics52, 639–649) suggested using methods of finite mixtures to partition the animals in a closed capture-recapture experiment into two or more groups with relatively homogeneous capture probabilities. This enabled them to fit the models Mh, Mbh (Norris and Pollock), and Mth (Agresti) of Otis et al. (1978, Wildlife Monographs62, 1–135). In this article, finite mixture partitions of animals and/or samples are used to give a unified linear-logistic framework for fitting all eight models of Otis et al. by maximum likelihood. Likelihood ratio tests are available for model comparisons. For many data sets, a simple dichotomy of animals is enough to substantially correct for heterogeneity-induced bias in the estimation of population size, although there is the option of fitting more than two groups if the data warrant it.

Unified Maximum Likelihood Estimates for Closed Capture–Recapture Models Using Mixtures

Dans les etudes de capture-recapture dans des population ouvertes, il est generalement suppose que des animaux similaires (c'est-a-dire de meme sexe et de meme groupe d'âge) ont des taux de survie et des probabilites de capture similaires. Ces hypotheses sont generalement percues pour etre des simplifications excessives, et elles peuvent conduire a une selection de modele incorrecte et des estimations de parametres biaisees. Autoriser une variabilite individuelle pour les probabilites de capture d'animaux apparemment similaires est maintenant devenu possible grâce aux avancees des modeles pour population fermee et un puissance de calcul accrue. Cet article presente un cadre souple de modeles bases sur la vraisemblance qui permet l'heterogeneite des taux de survie et de capture. L'heterogeneite est modelisee en utilisant des melanges finis qui ont assez de souplesse dans la forme des distributions pour s'adapter a une grande variete de schemas differents de variation individuelle. Les modeles conditionnent sur la premiere capture de l'animal, et comprennent comme cas particulier le modele de Cormack-Jolly-Seber. La selection de modele est faite usuellement par le critere d'information d'Akmike, ou par des tests du rapport de vraisemblance, ce qui permet de tester differentes influences sur les taux de survie. Le biais dans les estimations des parametres est reduit par l'inclusion de l'heterogeneite individuelle. La selection de modele et la reduction du biais sont importants dans les etudes de population et pour prendre des decisions de gestion adaptees.

Open capture-recapture models with heterogeneity: I. Cormack-Jolly-Seber model.

Summary
Unconstrained ordination is commonly used in ecology to visualize multivariate data, in particular, to visualize the main trends between different sites in terms of their species composition or relative abundance.
Methods of unconstrained ordination currently used, such as non-metric multidimensional scaling, are algorithm-based techniques developed and implemented without directly accommodating the statistical properties of the data at hand. Failure to account for these key data properties can lead to misleading results.
A model-based approach to unconstrained ordination can address this issue, and in this study, two types of models for ordination are proposed based on finite mixture models and latent variable models. Each method is capable of handling different data types and different forms of species response to latent gradients. Further strengths of the models are demonstrated via example and simulation.
Advantages of model-based approaches to ordination include the following: residual analysis tools for checking assumptions to ensure the fitted model is appropriate for the data; model selection tools to choose the most appropriate model for ordination; methods for formal statistical inference to draw conclusions from the ordination; and improved efficiency, that is model-based ordination better recovers true relationships between sites, when used appropriately.

https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.12236

Model‐based approaches to unconstrained ordination

http://www.tmd.ac.jp/artsci/biol/textbiodiv/ConsevNZFrogPop.pdf

The recent decline of a New Zealand endemic: how and why did populations of Archey's frog Leiopelma archeyi crash over 1996–2001?

Summary 1. Competition theory predicts that community structure may be shaped by resource partitioning between co-occurring species. As such, quantifying the degree of resource partitioning (i.e., niche overlap) is a key component of studies examining community structure and species coexistence. 2. For many organisms, multiple resource axes quantify niche space. Each axis may be described by a different type of data (e.g. categorical, continuous, count or binary data, as well as electivity scores), with different data types requiring different statistical treatments. Therefore, incorporating multiple axes into a single measure of niche space is problematic. 3. Here, we propose general methods for combining multiple niche axes, each characterized by different data types, within a unified analysis of niche overlap. Using appropriate transformations and probability models, we show that each data type can give rise to directly comparable measures of niche overlap, with the overlap statistic between two species defined as the overlapping area between the distributions for each species. 4. Measurements derived from different types of data can be combined into a single unified analysis of niche overlap by averaging over multiple axes. 5. We then describe null model permutation tests that assess statistical differences in niche overlap, which can address questions commonly posed by population ecologists (e.g. do two species occupy different niche space?) and community ecologists (e.g. are multiple species evenly distributed across niche space?). 6. To illustrate the use of these newly devised indices, we use an example from reef fishes that combines ratio, categorical and electivity data, and an example from alpine plants that combines continuous and ratio data. 7. The methods described in this article are relevant to a wide variety of ecological projects, including the investigation of invasive species, relative abundance distributions, global change, species coexistence and evolutionary diversification.

/pdf/a-unified-analysis-of-niche-overlap-incorporating-data-of-44ike9hlid.pdf

Shirley Pledger

Papers

Unified Maximum Likelihood Estimates for Closed Capture–Recapture Models Using Mixtures

Open capture-recapture models with heterogeneity: I. Cormack-Jolly-Seber model.

Model‐based approaches to unconstrained ordination

The recent decline of a New Zealand endemic: how and why did populations of Archey's frog Leiopelma archeyi crash over 1996–2001?

A unified analysis of niche overlap incorporating data of different types