State space and movement specification in open population spatial capture–recapture models. Issue 20 (27th September 2018)

• Record Type: Journal Article
• Authors: Gardner, Beth; Sollmann, Rahel; Kumar, N. Samba; Jathanna, Devcharan; Karanth, K. Ullas
• Is Part Of: Ecology and evolution. Volume 8:Issue 20(2018)
• Page Start: 10336
• Page End: 10344
• Publication Date: 2018-09-27
• Subjects: camera‐trapping -- dispersal -- Markovian movement -- population dynamics -- tigers -- transience; Ecology -- Periodicals; Evolution -- Periodicals; 577.05
• DOI: 10.1002/ece3.4509
• Languages: English
• ISSNs: 2045-7758

Abstract

Abstract: With continued global changes, such as climate change, biodiversity loss, and habitat fragmentation, the need for assessment of long‐term population dynamics and population monitoring of threatened species is growing. One powerful way to estimate population size and dynamics is through capture–recapture methods. Spatial capture (SCR) models for open populations make efficient use of capture–recapture data, while being robust to design changes. Relatively few studies have implemented open SCR models, and to date, very few have explored potential issues in defining these models. We develop a series of simulation studies to examine the effects of the state‐space definition and between‐primary‐period movement models on demographic parameter estimation. We demonstrate the implications on a 10‐year camera‐trap study of tigers in India. The results of our simulation study show that movement biases survival estimates in open SCR models when little is known about between‐primary‐period movements of animals. The size of the state‐space delineation can also bias the estimates of survival in certain cases.We found that both the state‐space definition and the between‐primary‐period movement specification affected survival estimates in the analysis of the tiger dataset (posterior mean estimates of survival ranged from 0.71 to 0.89). In general, we suggest that open SCR models can provide an efficient and flexible framework for long‐term monitoring of populations; however, in many cases, realistic modeling of between‐primary‐period movements is crucial for unbiased estimates of survival and density. Abstract : Open spatial capture recapture models provide a powerful method for estimating population size and dynamics. We explore the performance of these models through a simulation study and analysis of a 10‐year dataset on tigers. Results indicate that open spatial capture–recapture models are robust generally, but that users should pay careful attention when specifying the between‐primary‐period movement model.