Simultaneous estimation of seasonal population density, habitat preference and catchability of wild boars based on camera data and harvest records

Abstract

Analyses of life history and population dynamics are essential for effective population control of wild mammals. We developed a model for the simultaneous estimation of seasonal changes in three parameters—population density, habitat preference and trap catchability of target animals—based on camera-trapping data and harvest records. The random encounter and staying time model, with no need for individual recognition, is the core component of the model—by combining this model with the catch-effort model, we estimated density at broad spatial scales and catchability by traps. Here, the wild boar population in central Japan was evaluated as a target population. We found that the estimated population density increased after the birth period and then decreased until the next birth period, mainly due to harvesting. Habitat preference changed seasonally, but forests having abandoned fields nearby were generally preferred throughout the season. These patterns can be explained by patterns of food availability and resting or nesting sites. Catchability by traps also changed seasonally, with relatively high values in the winter, which probably reflected changes in the attractiveness of the trap bait due to activity changes in response to food scarcity. Based on these results, we proposed an effective trapping strategy for wild boars, and discussed the applicability of our model to more general conservation and management issues.

Predicting bushmeat biomass from species composition captured by camera traps: Implications for locally based wildlife monitoring

“…Moreover, REST can incorporate habitat covariates and random effects into the linear predictors of staying time and density. Previous studies (Nakashima et al, 2020; Yokoyama et al, 2020) applied this approach to successfully estimate spatial density variations in forest ungulates, including duikers.…”

“…Previous studies (Nakashima et al, 2020;Yokoyama et al, 2020) applied this approach to successfully estimate spatial density variations in forest ungulates, including duikers.…”

Estimating animal density with camera traps: a practitioner’s guide of the REST model

“…Furthermore, because the REST model has been developed as a likelihood-based model, it can be incorporated into a model that can integrate data from different sources. Indeed, Yokoyama et al (2020) gathered animal capture data from administration and constructed a state-space model to integrate data from multiple sources to estimate boar density, habitat use, and catchability. Such integrated models would extend the REST model's further applications and contribute to actual wildlife management.…”

“…Surveyors need to carefully plan the survey to meet them. Surveyors can refer to previous studies applying the REST model (Garland et al 2020;Yokoyama et al 2020), but research papers usually describe the survey method details only briefly. This makes it difficult for them to prepare plans with confidence.…”

Estimation of the Lethality Rate, Recovery Rate, and Case Fatality Ratio of Classical Swine Fever in Japanese Wild Boar: An Analysis of the Epidemics From September 2018 to March 2019

“…The present study aimed to estimate the two key parameters for estimating the dynamics of CSF in wild boar: the lethality rate and the recovery rate. To estimate them, detailed data on the population dynamics of wild boar are required; however, reliable estimation of the population size for wild boar is often challenging and lacks a standard methodological framework ( 34 , 35 ). In this paper, we propose a method for estimating the lethality and recovery rates of CSF when detailed data on the population dynamics of wild boar are not available.…”