1. 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. (This is the dataset presented here).

2. 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.

3. We found that both the state space definition and between-primary-period movement specification affected survival estimates in the analysis of the tiger dataset (posterior mean estimates of survival ranged from 0.71-0.89).

4. 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.

These data were collected by Wildlife Conservation Society under the supervision of Dr. Ullas Karanth and are the joint intellectual property of entities, please use proper citations.

Tiger camera-trap data used in this study come from a study implemented in the central part of Nagarahole Reserve, in the state of Karnataka, southwestern India. The camera-trap study was initiated in 1991 and we analyze data from 1991 to 2000, which had previously been analyzed using non-spatial capture–recapture models (Karanth et al. 2006). The number of camera trap stations used in each year varies from 6 to 80 and the sampled area expanded from 41.4km2 to 231.8km2. In addition, the sampling duration was reduced from 162 days in 1991 to 30-40 days in the later years of the study. There are 10 primary periods over 9 years, thus the data are not evenly spaced. Tigers were uniquely identified from the photographs. Details concerning the field methods are given in Karanth and Nichols (1998) and Table 1 of Karanth et al. (2006) shows the primary periods, number of days sampled, the estimated sampled area, the effort in trap-nights, and the number of detected individuals. In the original analysis of the data set, records of 74 individuals collected over 5725 trap nights were included. Because data collected in later years allowed for the identification of additional individuals, the data set for the present analysis contained 75 individuals.

Please see the ReadMeTigers.txt file for more details.

EECam_act.csv: This file contains the number of occasions that camera stations were active within a given primary period.

EERecords.csv: This file contains all of the recorded individuals, the trap (camera station), occassion, and year for each time the animal was recorded on camera.

EEtraplocs.csv: This file contains all of the trap (camera station) locations. The x and y are centered to remove exact locations within the park, but are still given in meters.