Modelling detection probabilities to evaluate management and control tools for an invasive species

Abstract

Summary1. For most ecologists, detection probability (p) is a nuisance variable that must be modelled to estimate the state variable of interest (i.e. survival, abundance, or occupancy). However, in the realm of invasive species control, the rate of detection and removal is the rate-limiting step for management of this pervasive environmental problem. 2. For strategic planning of an eradication (removal of every individual), one must identify the least likely individual to be removed, and determine the probability of removing it. 3. To evaluate visual searching as a control tool for populations of the invasive brown treesnake Boiga irregularis, we designed a mark-recapture study to evaluate detection probability as a function of time, gender, size, body condition, recent detection history, residency status, searcher team and environmental covariates. 4. We evaluated these factors using 654 captures resulting from visual detections of 117 snakes residing in a 5-ha semi-forested enclosure on Guam, fenced to prevent immigration and emigration of snakes but not their prey. Visual detection probability was low overall ( p = 0AE07 per occasion) but reached 0AE18 under optimal circumstances. 5. Our results supported sex-specific differences in detectability that were a quadratic function of size, with both small and large females having lower detection probabilities than males of those sizes. There was strong evidence for individual periodic changes in detectability of a few days duration, roughly doubling detection probability (comparing peak to non-elevated detections). Snakes in poor body condition had estimated mean detection probabilities greater than snakes with high body condition. Search teams with high average detection rates exhibited detection probabilities about twice that of search teams with low average detection rates. Surveys conducted with bright moonlight and strong wind gusts exhibited moderately decreased probabilities of detecting snakes. 6. Synthesis and applications. By emphasizing and modelling detection probabilities, we now know: (i) that eradication of this species by searching is possible, (ii) how much searching effort would be required, (iii) under what environmental conditions searching would be most efficient, and (iv) several factors that are likely to modulate this quantification when searching is applied to new areas. The same approach can be use for evaluation of any control technology or population monitoring programme.

Cold-induced mortality of invasive Burmese pythons in south Florida

“…Knowledge of detectability of an invasive species is important for planning control and eradication programs (Christy et al 2010). Pythons are less detectable in natural areas than in artificial habitats, but are more detectable in both areas after a cold spell.…”

“…Pythons may also have been more visible to human researchers during this study because the snakes appeared to increase the amount of time spent basking after the cold event. Because maximizing removal rates is an important component of invasive species control (Christy et al 2010), timing rapid responses (Stanford and Rodda 2007) in suitable habitats during and after unusual climatic events might increase removal rates of pythons.…”

Detection probabilities of two introduced frogs in Hawaii: implications for assessing non-native species distributions

“…Even if a site is well surveyed, a cryptic species may go overlooked or undetected by an investigator, and result in an underestimation of sites or habitat occupied (MacKenzie et al 2006). In the case of nonnative species, detectability is important because it influences our understanding of the degree of invasiveness and our ability to manage the species (Christy et al 2010). A cryptic invader presents several specific problems: (1) because early detection is difficult, it is more likely to become widespread and unmanageable; (2) it is likely to be more widespread than appreciated; and (3) it is more difficult to control because individuals are easily missed (Bomford and O'Brien 1995;Pitt and Witmer 2006).…”

Estimating population size in the presence of temporary migration using a joint analysis of telemetry and capture–recapture data

“…The probability of an individual being captured in a single sample from a population plays a pivotal role in how ecological data are collected and interpreted, including estimates of population abundance (Besbeas et al, Morgan & Lebreton 2003;Schnabel 1938), individual survival rates (Cormack 1964), species extinctions (K ery 2004), site occupancy (Royle et al 2007), species invasions (Britton, Pegg & Gozlan 2011;Christy et al 2010) and range expansion (Altwegg, Wheeler & Erni 2008). Capture-mark-recapture (CMR) methods provide one of the most reliable means of estimating capture probabilities.…”