A comparison of abundance and distribution model outputs using camera traps and sign surveys for feral pigs
Derek R. Risch
A E , Jeremy Ringma A B , Shaya Honarvar C D and Melissa R. Price A
+ Author Affiliations
- Author Affiliations
A University of Hawai‘i at Mānoa, 1910 East-west Road, Honolulu, HI 96822, USA.
B Present address: Royal Melbourne Institute of Technology University, GPO Box 2476V, Melbourne, Vic. 3001, Australia.
C Department of Land and Natural Resources, Division of Forestry and Wildlife, 1151 Punchbowl Street, Honolulu, HI 96822, USA.
D Present address: University of Hawai‘i at Mānoa, School of Life Sciences, 3190 Maile Way, Honolulu, HI 96822, USA.
E Corresponding author. Email: drisch@hawaii.edu
Pacific Conservation Biology 27(2) 186-194 https://doi.org/10.1071/PC20032
Submitted: 8 April 2020 Accepted: 20 September 2020 Published: 14 October 2020
Journal Compilation © CSIRO 2021 Open Access CC BY-NC
Abstract
Species distribution models play a central role in informing wildlife management. For models to be useful, they must be based on data that best represent the presence or abundance of the species. Data used as inputs in the development of these models can be obtained through numerous methods, each subject to different biases and limitations but, to date, few studies have examined whether these biases result in different predictive spatial models, potentially influencing conservation decisions. In this study, we compare distribution model predictions of feral pig (Sus scrofa) relative abundance using the two most common monitoring methods: detections from camera traps and visual surveys of pig sign. These data were collected during the same period using standardised methods at survey sites generated using a random stratified sampling design. We found that although site-level observed sign data were only loosely correlated with observed camera detections (R2 = 0.32–0.45), predicted sign and camera counts from zero-inflated models were well correlated (R2 = 0.78–0.88). In this study we show one example in which fitting two different forms of abundance data using environmental covariates explains most of the variance between datasets. We conclude that, as long as outputs are produced through appropriate modelling techniques, these two common methods of obtaining abundance data may be used interchangeably to produce comparable distribution maps for decision-making purposes. However, for monitoring purposes, sign and camera trap data may not be used interchangeably at the site level.
Keywords: abundance index, feral pig, invasive species, monitoring, Pacific region, species distribution, Sus scrofa, ungulates, wild pig, wildlife management.
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