Estimation of the Size of a Closed Population when Capture Probabilities vary Among Animals

Burnham, K. P.; Overton, W. Scott

doi:10.2307/2335915

Cited by 286 publications

(387 citation statements)

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“…Species richness was estimated through species accumulation curves based on two non-parametric estimators: the Jack2 estimator (Burnham & Overton, 1978, 1979 and ACE (Abundance based Coverage Estimator) (Chazdon et al, 1998). ACE is a modified version of the Chao2 estimator developed by Chao & Lee (1992) that takes into account the overestimation in species richness of the Chao2, especially when a small number of samples is used.…”

Section: Methodsmentioning

confidence: 99%

Epifaunal Inventory of Two Shipwrecks from the Belgian Continental Shelf

et al. 2006

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Shipwrecks are almost the only subtidal substrata available for epifaunal colonization along the Belgian coastal waters and have never been scientifically prospected up to now. Two shipwrecks have been investigated during the summers of 2001 and 2002. De-visu observations and examination of 14 scraped surfaces of 0.0625 m 2 allowed the identification of a total of 121 macrofauna species. Species richness cumulative curves provide an estimated number of 150-280 species. Both shipwrecks are dominated by Cnidarians. The tube-dwelling amphipod Jassa herdmani was also particularly abundant. Striking differences were observed between shipwrecks. Different faunal assemblages were observed on vertical and horizontal surfaces. Species richness could not been correlated with diversity indices. Samples with high species diversity were observed when the Hydrozoan Tubularia indivisa was dominant. On the contrary, when the Anthozoan Metridium senile was dominant, samples showed a very low species richness. Finally, the Poriferan Dysidea fragilis has to be considered as a new species for the Belgian fauna.

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Section: Methodsmentioning

confidence: 99%

Epifaunal Inventory of Two Shipwrecks from the Belgian Continental Shelf

et al. 2006

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“…For the comparison of ant species richness, EstimateS 5.0 (Colwell 1997) was used to compute cumulative species curves of the pooled samples and the extrapolated incidence was based on firstorder jack-knife calculations (Burnham and Overton 1978). All calculations were randomized 100 times.…”

Section: Diversity Measuresmentioning

confidence: 99%

Influence of forest type and tree species on canopy ants (Hymenoptera: Formicidae) in Budongo Forest, Uganda

Schulz

Wagner

2002

Oecologia

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The arboreal ant fauna was investigated in Budongo Forest, a seasonal rain forest in Uganda, using the insecticidal fogging technique. Ants were collected from 61 trees, between 7 and 33 m in height, belonging to four tree species. Trees were growing in adjacent plots of forests characterized by different use and structure: an old primary forest, a primary swamp forest along a small river, and a secondary forest where selective logging was carried out for 30 years. A total number of 37,065 ants, belonging to 161 species in 30 genera were collected. Considering the high number of species found only once, the completeness of the canopy ant fauna was relatively high and of relatively similar magnitude as samples from the Neotropics or the Oriental region. Up to 37 ant species on a single tree, with an average of 18.2 species per tree, were found. Forty-four ant species (28.1%) were found only once, less than ten individuals were found for each of 88 species (54.7%), but 64.0% of all individuals belonged to one of five species. Considering the high numerical dominance of a few ant species like a Pheidole sp., Tetramorium aculeatum (Mayr) and a Crematogaster sp., there is some evidence for an ant mosaic in the lower canopy of the Budongo Forest. Individual numbers of ants were strongly correlated with nests in the fogged tree, though the ants were not homogeneously distributed in the tree crowns. Diversity measures that strongly depend on individual numbers such as the Morisita-Horn index or rarefaction methods were calculated, but results were not concordant with those of incidence-based estimates such as jack-knife calculations. Differences in ant species richness and faunal composition between tree species were low, but more significant between forest types. The ant fauna in the secondary forest was less diverse with 12.6% fewer species compared to the primary forest sites. The average number of ant species per tree was significantly lower in the secondary forest (<20% of the species; F=8.03, df=59, P<0.01) than in the undisturbed forest types. Cataulacus, Leptothorax, Tetraponera, and Polyrhachis, which are typical canopy-dwelling ant genera, had a significantly higher diversity and frequency in the two primary forest types (F=4.17, df=53, P<0.05). Secondary forest trees are often younger, lacking dead branches and epiphytes which are important requisites for ant colonization on trees.

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“…An important class of models includes those with latent (unobservable) sources of individual heterogeneity. So-called ''Model M h '' is a standard closed-population model (e.g., Burnham and Overton 1978;Dorazio and Royle 2003;Link 2003;Pledger 2005), and similar ideas have been applied to open populations (Pledger et al 2003;Gimenez et al 2007;Royle 2009;Gimenez and Choquet 2010). Another useful class of models includes the individual covariate models, in which covariates are measured on each individual in the sample.…”

Section: Introductionmentioning

confidence: 99%

Parameter-expanded data augmentation for Bayesian analysis of capture–recapture models

Royle¹,

2010

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Data augmentation (DA) is a flexible tool for analyzing closed and open population models of capturerecapture data, especially models which include sources of hetereogeneity among individuals. The essential concept underlying DA, as we use the term, is based on adding ''observations'' to create a dataset composed of a known number of individuals. This new (augmented) dataset, which includes the unknown number of individuals N in the population, is then analyzed using a new model that includes a reformulation of the parameter N in the conventional model of the observed (unaugmented) data. In the context of capture-recapture models, we add a set of ''all zero'' encounter histories which are not, in practice, observable. The model of the augmented dataset is a zeroinflated version of either a binomial or a multinomial base model. Thus, our use of DA provides a general approach for analyzing both closed and open population models of all types. In doing so, this approach provides a unified framework for the analysis of a huge range of models that are treated as unrelated ''black boxes'' and named procedures in the classical literature. As a practical matter, analysis of the augmented dataset by MCMC is greatly simplified compared to other methods that require specialized algorithms. For example, complex capture-recapture models of an augmented dataset can be fitted with popular MCMC software packages (WinBUGS or JAGS) by providing a concise statement of the model's assumptions that usually involves only a few lines of pseudocode. In this paper, we review the basic technical concepts of data augmentation, and we provide examples of analyses of closed-population models (M 0 , M h , distance sampling, and spatial capture-recapture models) and open-population models (Jolly-Seber) with individual effects.

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Estimation of the Size of a Closed Population when Capture Probabilities vary Among Animals

Cited by 286 publications

References 0 publications

Epifaunal Inventory of Two Shipwrecks from the Belgian Continental Shelf

Epifaunal Inventory of Two Shipwrecks from the Belgian Continental Shelf

Influence of forest type and tree species on canopy ants (Hymenoptera: Formicidae) in Budongo Forest, Uganda

Parameter-expanded data augmentation for Bayesian analysis of capture–recapture models

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