A Generalized Estimating Equations Approach to Model Heterogeneity and Time Dependence in Capture-Recapture Studies

Individual heterogeneity in capture probabilities and time dependence are fundamentally important for estimating the closed animal population parameters in capture-recapture studies. A generalized estimating equations (GEE) approach accounts for linear correlation among capture-recapture occasions, and individual heterogeneity in capture probabilities in a closed population capture-recapture individual heterogeneity and time variation model. The estimated capture probabilities are used to estimate animal population parameters. Two real data sets are used for illustrative purposes. A simulation study is carried out to assess the performance of the GEE estimator. A Quasi-Likelihood Information Criterion (QIC) is applied for the selection of the best fitting model. This approach performs well when the estimated population parameters depend on the individual heterogeneity and the nature of linear correlation among capture-recapture occasions

How ideas from ecological capture-recapture models may inform multiple systems estimation analyses

Abundance estimation, for both human and animal populations, informs policy decisions and population management. Capture-recapture and multiple sources data share a common structure; the population can be partially enumerated and individuals are identifiable. Consequently, the analytical methods were developed simultaneously. However, whilst ecological models have been developed to describe highly complex, biologically realistic scenarios, for example modeling population changes through time and combining different forms of data, multiple systems estimation has changed comparatively less so. In this paper we provide a brief description of the historical development of ecological and epidemiological capture-recapture and discuss the associated underlying differences that have led to model divergence. We identify three key areas where ecological modeling methods may inform and improve multiple systems estimation.Publisher PDFPeer reviewe

iDNA from terrestrial haematophagous leeches as a wildlife surveying and monitoring tool - prospects, pitfalls and avenues to be developed

Invertebrate-derived DNA (iDNA) from terrestrial haematophagous leeches has recently been proposed as a powerful non-invasive tool with which to detect vertebrate species and thus to survey their populations. However, to date little attention has been given to whether and how this, or indeed any other iDNA-derived data, can be combined with state-of-the-art analytical tools to estimate wildlife abundances, population dynamics and distributions. In this review, we discuss the challenges that face the application of existing analytical methods such as site-occupancy and spatial capture-recapture (SCR) models to terrestrial leech iDNA, in particular, possible violations of key assumptions arising from factors intrinsic to invertebrate parasite biology. Specifically, we review the advantages and disadvantages of terrestrial leeches as a source of iDNA and summarize the utility of leeches for presence, occupancy, and spatial capture-recapture models. The main source of uncertainty that attends species detections derived from leech gut contents is attributable to uncertainty about the spatio-temporal sampling frame, since leeches retain host-blood for months and can move after feeding. Subsequently, we briefly address how the analytical challenges associated with leeches may apply to other sources of iDNA. Our review highlights that despite the considerable potential of leech (and indeed any) iDNA as a new survey tool, further pilot studies are needed to assess how analytical methods can overcome or not the potential biases and assumption violations of the new field of iDNA. Specifically we argue that studies to compare iDNA sampling with standard survey methods such as camera trapping, and those to improve our knowledge on leech (and other invertebrate parasite) physiology, taxonomy, and ecology will be of immense future value