Estimating the Density of Secretive, at-Rsk Snake Species on Department of Defense Installations Using an Innovative Approach: IDEASS

Dr. Brett DeGregorio | ERDC-CERL



The Department of Defense (DoD) spends considerable resources managing and conserving a number of threatened,endangered, or at-risk snake species. Management for these species is often hampered by a lack of basic knowledge regarding their population size and trajectory thus managers tasked with recovering these populations currently do not have an appropriate tool to provide them with the primary, yet basic, starting point to conservation: current abundance. Consequently, regulators are often forced to use availability of suitable habitat as a proxy for population size and trend, an approach that may be heavily biased and unreliable. Two critical pieces of data needed for effective management of snake populations are density and individual detection probability, but the low detectability of most snake species makes it difficult to determine even if they are present at a particular site, let alone quantifying metrics related to their population (e.g., density, size distribution). Traditional methods such as capture-mark-recapture (CMR) are the most frequently employed methods of quantifying snake population sizes but this technique cannot overcome the low detectability of most snake species and even when feasible, requires considerable investments of time and resources. Here, the researchers propose to demonstrate and validate a novel, simulation-based method; Innovative Density Estimation Approach for Secretive Snakes (IDEASS) for estimating detection probabilities and densities of secretive terrestrial snakes using systematic road surveys, behavioral observations of snake movement, and spatial movement (radiotelemetry) data.

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Technology Description

IDEASS is a modeling approach that combines road crossing behavior (crossing speed), effort-corrected road survey data, and simulation-based analysis of spatial movement patterns derived from radiotelemetry to estimate densities of secretive animals, without relying on CMR. Radiotelemetry data are collected and used to quantify movement frequency, distance, and orientation in relation to home range, landscape, and habitat features such as roads. These movement data are then used to parameterize individual-based movement models which incorporate movement metrics in a biased correlated random-walk framework to estimate the frequency with which individual cross roads. Next, information on vehicle speed and snake crossing speed (derived from measurements of natural snake crossing events) are used to determine the probability of detecting a snake, given that it crosses the road transect during a survey. Detection probabilities and simulation model results are then used to determine the relationship between observation rate during surveys and density in the surrounding landscape. Finally, sensitivity analyses can be completed to determine precision of density estimates (i.e., confidence intervals) and assess factors most likely to affect abundance estimation. By combining all of these pieces in an IDEASS model, one can calculate individual detection probability and population density for even very secretive, rarely encountered species that are not tractable to CMR approaches.

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Managers tasked with assessing or recovering populations of secretive snakes often lack appropriate tools to provide them with the foundational starting point to conservation: abundance. Because road collecting is the primary method of capture for many rare and secretive snake species, the applicability of IDEASS makes it a robust and adaptable approach for snake conservation and management on numerous DoD installations. Importantly, the IDEASS approach can make use of existing data sets to further reduce cost and facilitate adoption. Applying the IDEASS model will allow managers to quantify densities of rare, often protected species, on installations for the first time and routinely monitor the population trajectories in relation to management. These data will be integral in evaluating Endangered Species Recovery Plans and in consultation with federal regulators.

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Points of Contact

Principal Investigator

Dr. Brett DeGregorio


Phone: 217-373-7253

Program Manager

Resource Conservation and Resiliency