Geology topics

B.T. McClintock

Publications and source records attributed to B.T. McClintock.

5 recordsLinked to original sources

USGS2022

Integrated animal movement and spatial capture–recapture models: Simulation, implementation, and inference

Over the last decade, spatial capture–recapture (SCR) models have become widespread for estimating demographic parameters in ecological studies. However, the underlying assumptions about animal movement and space use are often not realistic. This is a missed opportunity because interesting ecological questions related to animal space use, habitat selection, and behavior cannot be addressed with most SCR models, despite the fact that the data collected in SCR studies — individual animals observed at specific locations and times — can provide a rich source of information about these processes and how they relate to demographic rates. We developed SCR models that integrated more complex movement processes that are typically inferred from telemetry data, including a simple random walk, correlated random walk (i.e., short-term directional persistence), and habitat-driven Langevin diffusion. We demonstrated how to formulate, simulate from, and fit these models with standard SCR data using data-augmented Bayesian analysis methods. We evaluated their performance through a simulation study, in which we varied the detection, movement, and resource selection parameters. We also examined different numbers of sampling occasions and assessed performance gains when including auxiliary location data collected from telemetered individuals. Across all scenarios, the integrated SCR movement models performed well in terms of abundance, detection, and movement parameter estimation. We found little difference in bias for the simple random walk model when reducing the number of sampling occasions from T = 25 to T = 15. We found some bias in movement parameter estimates under several of the correlated random walk scenarios, but incorporating auxiliary location data improved parameter estimates and significantly improved mixing during model fitting. The Langevin movement model was able to recover resource selection parameters from standard SCR data, which is particularly appealing because it explicitly links the individual-level movement process with habitat selection and population density. We focused on closed population models, but the movement models developed here can be extended to open SCR models. The movement process models could also be easily extended to accommodate additional “building blocks” of random walks, such as central tendency (e.g., territoriality) or multiple movement behavior states, thereby providing a flexible and coherent framework for linking animal movement behavior to population dynamics, density, and distribution.

Ecology↗

USGS2021

Evaluation of camera trap-based abundance estimators for unmarked populations

Estimates of species abundance are critical to understand population processes and to assess and select management actions. However, capturing and marking individuals for abundance estimation, while providing robust information, can be economically and logistically prohibitive, particularly for species with cryptic behavior. Camera traps can be used to collect data at temporal and spatial scales necessary for estimating abundance, but the use of camera traps comes with limitations when target species are not uniquely identifiable (i.e., “unmarked”). Abundance estimation is particularly useful in the management of invasive species, with herpetofauna being recognized as some of the most pervasive and detrimental invasive vertebrate species. However, the use of camera traps for these taxa presents additional challenges with relevancy across multiple taxa. It is often necessary to use lures to attract animals in order to obtain sufficient observations, yet lure attraction can influence species’ landscape use and potentially induce bias in abundance estimators. We investigated these challenges and assessed the feasibility of obtaining reliable abundance estimates using camera-trapping data on a population of invasive brown treesnakes ( Boiga irregularis ) in Guam. Data were collected using camera traps in an enclosed area where snakes were subject to high-intensity capture–recapture effort, resulting in presumed abundance of 116 snakes (density = 23/ha). We then applied spatial count, random encounter and staying time, space to event, and instantaneous sampling estimators to photo-capture data to estimate abundance and compared estimates to our presumed abundance. We found that all estimators for unmarked populations performed poorly, with inaccurate or imprecise abundance estimates that limit their usefulness for management in this system. We further investigated the sensitivity of these estimators to the use of lures (i.e., violating the assumption that animal behavior is unchanged by sampling) and camera density in a simulation study. Increasing the effective distances of a lure (i.e., lure attraction) and camera density both resulted in biased abundance estimates. Each estimator rarely recovered truth or suffered from convergence issues. Our results indicate that, when limited to unmarked estimators and the use of lures, camera traps alone are unlikely to produce abundance estimates with utility for brown treesnake management.

Ecological Applications↗

USGS2010

Experimental investigation of observation error in anuran call surveys

Occupancy models that account for imperfect detection are often used to monitor anuran and songbird species occurrence. However, presenceabsence data arising from auditory detections may be more prone to observation error (e.g., false-positive detections) than are sampling approaches utilizing physical captures or sightings of individuals. We conducted realistic, replicated field experiments using a remote broadcasting system to simulate simple anuran call surveys and to investigate potential factors affecting observation error in these studies. Distance, time, ambient noise, and observer abilities were the most important factors explaining false-negative detections. Distance and observer ability were the best overall predictors of false-positive errors, but ambient noise and competing species also affected error rates for some species. False-positive errors made up 5 of all positive detections, with individual observers exhibiting false-positive rates between 0.5 and 14. Previous research suggests false-positive errors of these magnitudes would induce substantial positive biases in standard estimators of species occurrence, and we recommend practices to mitigate for false positives when developing occupancy monitoring protocols that rely on auditory detections. These recommendations include additional observer training, limiting the number of target species, and establishing distance and ambient noise thresholds during surveys. ?? 2010 The Wildlife Society.

Journal of Wildlife Management↗

USGS2009

A less field-intensive robust design for estimating demographic parameters with Mark-resight data

The robust design has become popular among animal ecologists as a means for estimating population abundance and related demographic parameters with mark-recapture data. However, two drawbacks of traditional mark-recapture are financial cost and repeated disturbance to animals. Mark-resight methodology may in many circumstances be a less expensive and less invasive alternative to mark-recapture, but the models developed to date for these data have overwhelmingly concentrated only on the estimation of abundance. Here we introduce a mark-resight model analogous to that used in mark-recapture for the simultaneous estimation of abundance, apparent survival, and transition probabilities between observable and unobservable states. The model may be implemented using standard statistical computing software, but it has also been incorporated into the freeware package Program MARK. We illustrate the use of our model with mainland New Zealand Robin (Petroica australis) data collected to ascertain whether this methodology may be a reliable alternative for monitoring endangered populations of a closely related species inhabiting the Chatham Islands. We found this method to be a viable alternative to traditional mark-recapture when cost or disturbance to species is of particular concern in long-term population monitoring programs. ?? 2009 by the Ecological Society of America.

Ecology↗

USGS2009

A generalized mixed effects model of abundance for mark-resight data when sampling is without replacement

In recent years, the mark-resight method for estimating abundance when the number of marked individuals is known has become increasingly popular. By using field-readable bands that may be resighted from a distance, these techniques can be applied to many species, and are particularly useful for relatively small, closed populations. However, due to the different assumptions and general rigidity of the available estimators, researchers must often commit to a particular model without rigorous quantitative justification for model selection based on the data. Here we introduce a nonlinear logit-normal mixed effects model addressing this need for a more generalized framework. Similar to models available for mark-recapture studies, the estimator allows a wide variety of sampling conditions to be parameterized efficiently under a robust sampling design. Resighting rates may be modeled simply or with more complexity by including fixed temporal and random individual heterogeneity effects. Using information theory, the model(s) best supported by the data may be selected from the candidate models proposed. Under this generalized framework, we hope the uncertainty associated with mark-resight model selection will be reduced substantially. We compare our model to other mark-resight abundance estimators when applied to mainland New Zealand robin (Petroica australis) data recently collected in Eglinton Valley, Fiordland National Park and summarize its performance in simulation experiments.

Book chapter↗