This README.txt file was generated on 2022-02-14 by Cheryl Cheah GENERAL INFORMATION 1. Title of Dataset: Data from: Recent estimate of Asian elephants in Borneo reveals a smaller population. 2. Author Information A. Corresponding Investigator Name: Cheryl Cheah Institution: WWF-Malaysia Address: WWF-Malaysia, 6th Floor, CPS Tower, Centre Point Complex, 1 Jalan Centre Point 88800, Kota Kinabalu, Sabah, Malaysia. Email: ccheah@wwf.org.my B. Co-investigator Name: K. Yoganand Institution: WWF-Greater Mekong Address: WWF-Greater Mekong, House no. 39, Unit 05, Saylom Village, Chanthabouly, District, Vientiane Capital, Lao PDR. Email: k.yoganand@gmail.com 3. Date of data collection: 2014-2015 4. Geographic location of data collection: Central Sabah, Malaysia 5. Information about funding sources that supported the collection of the data: WWF-Netherlands, WWF-UK, WWF-Germany, WWF-Japan, WWF’s Asian Rhino and Elephant Action Strategy (AREAS), WWF-International, and Forever Sabah. 6. Recommended citation for this dataset: Cheah, C. and Yoganand, K. 2022. Data from: Recent estimate of Asian elephants in Borneo reveals a smaller population, Dryad, Dataset DATA & FILE OVERVIEW 1. Description of dataset These data were generated to obtain an up-to-date estimate of the Asian elephant population size in the Central Sabah elephant range. In order to obtain estimates of elephant density and population size, three parameters are required; a) Estimates of dung pile density, b) Dung decay rates (persistence time), and c) Defecation rates. Data on defecation rates were obtained from Tyson et al. (2001), and Hedges et al. (2005). 2. File List: File 1 Name: Cheah&Yoganand_2022_a_Dung_transect_density.csv File 1 Description: Estimates of elephant dung pile density. File 2 Name: Cheah&Yoganand_2022_b_Dung_decay.csv File 2 Description: Dung decay rate or persistence time of dung piles. File 3 Name: Cheah&Yoganand_2022_c_analysis_script.R File 3 Description: The R command script provides the codes to run the analysis and to obtain the posterior distributions. METHODOLOGICAL INFORMATION 1. Description of methods used for collection/generation of data: A distance-sampling framework was used. Transect lines were laid out following a stratified random design for counting elephant dung piles. The CITES MIKE Program’s “S” system by Hedges and Lawson (2006) was used for dung pile classification. References: Hedges, S. and Lawson, D. 2006. Dung survey standards for the MIKE programme. – CITES MIKE Programme, Nairobi, Kenya. 2. Methods for processing the data: a) Defecation rates: We used a mean defecation rate of 18.15 defecations per 24 hours (CV = 13.94%). This rate was estimated from observations on wild-caught and tamed elephants that foraged naturally in the forest in Way Kambas National Park, Sumatra, Indonesia (Tyson et al. 2001, Hedges et al. 2005). Since freshly estimating the defecation rate in wild elephants in dense tropical forests is difficult (Dawson 1993, Hedges 2012), we used the estimate from Sumatra, as the environmental conditions in Sumatra and Borneo are similar. References: Hedges, S. et al. 2005. Distribution, status, and conservation needs of Asian elephants (Elephas maximus) in Lampung Province, Sumatra, Indonesia. – Biol. Conserv. 124: 35-48. Tyson, M. J. et al. 2001. Elephant Defecation Rate Study, Way Kambas National Park 2000/2001: Final Report to WWF, WCS, and PHKA, 20 December 2001. – Wildlife Conservation Society, Bogor, Indonesia. b) Dung decay rate (persistence time) We used the ‘retrospective’ method of estimating dung decay rate (Laing et al. 2003, Hedges and Lawson 2006, Hedges 2012), which involves monitoring dung decay preceding the transect surveys for dung density estimation. We searched for fresh dung piles and marked them monthly from November 2014 until August 2015. The earliest marked dung piles were thus allowed about eight months to decay before ending the estimation around the midpoint of the transect survey period. Using a handheld global positioning system (GPS), we marked the dung piles with tags and recorded their locations. The marked dung piles were visited a few times during the monitoring period to replace any lost tags (Hedges et al. 2012). Finally, in September 2015, the midpoint of the transect survey period, we checked all the marked dung piles and recorded their decay stages. We included dung piles corresponding to the classes ‘S1’ and ‘S2’ of the CITES MIKE Program’s “S” system for dung pile classification (Hedges and Lawson 2006) in the decay rate estimation and considered those in the ‘S3’ and ‘S4’ stages as decayed. References: Hedges, S. and Lawson, D. 2006. Dung survey standards for the MIKE programme. – CITES MIKE Programme, Nairobi, Kenya. Hedges, S. 2012. Estimating Elephant Population Density and Abundance from Dung Pile Density: Theoretical Concepts. –¬ In: Hedges, S. (ed.), Monitoring Elephant Populations and Assessing Threats. A manual for researchers, managers and conservationists. Universities Press (India) Private Limited, pp. 61-111. Laing, S. E. et al. 2003. Dung and nest surveys: estimating decay rates. – J. Appl. Ecol. 40: 1102-1111. c) Transect surveys for dung density (Estimates of dung pile density) The transect surveys were conducted from June to December 2015. We used stratified random sampling for selecting the transect locations. A map of elephant habitat suitability – high, medium, and low suitability, of the study area was used to indicate intensities of use (Alfred et al. 2010). Areas of low suitability (steep terrain and far from rivers) were hardly used by elephants and therefore excluded. Our survey effort was focused on the high and medium suitability strata. The high suitability stratum extended over 3655 km2 and the medium suitability stratum over 1844 km2. We chose 75 points randomly across the two strata to serve as line transect starting points. Each transect was 1 km long; however, some were shorter due to difficult field conditions. Thus, we walked 75 transects with a survey effort of 71.55 km, with 57 transects in the high suitability stratum and 18 transects in the medium suitability stratum. On detecting a dung pile along the transects, we measured the perpendicular distance of the centre of the dung pile from the transect line, and recorded the decay stage using the MIKE Program’s “S” system for dung pile classification (Hedges and Lawson 2006). We used only the dung piles in stages S1 and S2 for density estimation as only these two classes were defined as ‘undecayed’ in our decay rate estimation. We grouped the perpendicular distances of dung piles into distance bands (‘bins’) to account for rounding errors made by some of the observers that resulted in ‘data heaping’ (a type of measurement error that occurs when data is recorded with various levels of precision where a subset of the data consists of true values). We used a truncation distance of 5.5 m, as only one dung pile was recorded beyond this distance. This exclusion accounted for less than 2% of total dung piles observed, but it increased the reliability of the estimate (Buckland et al. 2001). After truncation, 63 dung piles in decay stages S1 and S2 were used to estimate density. References: Alfred, R. et al. 2010. Density and population estimation of the Bornean elephants (Elephas maximus borneensis) in Sabah. – Online J. of Biol. Sci. 10: 92-102.. d) Bayesian estimation of dung persistence time and elephant density We used Bayesian analysis to estimate elephant dung pile density and dung dung decay rate (persistence time). Posterior distribution of dung persistence time was estimated based on the logistic regression model of Laing et al. (2003). Posterior distribution of elephant density was estimated by combining dung density from distance sampling (Buckland et al. 2001), dung persistence time, and the defecation rate. We used the package JAGS v.4.3.0 (Plummer 2017) in R environment v.3.2.5 (R Development Core Team 2016) to run the Bayesian models. The R script and JAGS code for the model are available from Kéry and Royle (2016). We used non-informative priors and uniform distributions for all parameters. Even though Alfred et al. (2010) provided population size and density estimates for the study area, we chose not to use them as priors because of the ambiguity and errors we identified in their results, as we discuss in the later sections. We ran the estimation models using the Markov Chain Monte-Carlo (MCMC) procedure in JAGS. For the dung decay analysis, we ran three MCMC chains with 26 000 iterations per chain, discarding the initial 1000 iterations as ‘burn in’. For the density analysis, we ran three MCMC chains with 500 000 iterations per chain, discarding the initial 1000 iterations as ‘burn in’ and thinning by a factor of 20. We assessed the convergence of chains for both analyses using R-hat, with values below 1.1 indicating convergence. We estimated densities for each stratum separately and calculated the overall density for the study area as a weighted-mean of densities of each stratum weighted by their proportional extent. The R file script to run the analysis can be found in File 3. References: Buckland, S.T. et al. 2001. Introduction to Distance Sampling. Estimating Abundance of Biological Populations. – Oxford Univ. Press. Kéry, M. and Royle, J. A. 2016. Applied Hierarchical Modeling in Ecology. Analysis of distribution, abundance, and species richness in R and BUGS. Volume 1. Prelude and Static Models. – Academic Press. Plummer, M. 2017. JAGS Version 4.3.0 manual. – . 3. Software-specific information needed to interpret the data: We used the package JAGS v.4.3.0 (Plummer 2017) in R environment v.3.2.5 (R Development Core Team 2016) to run the Bayesian models. These library packages will need to be downloaded: library(jagsUI) library(wiqid) References: Plummer, M. 2017. JAGS Version 4.3.0 manual. – . R Core Team. 2016. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. – . DATA-SPECIFIC INFORMATION FOR: Cheah&Yoganand_2022_a_Dung_transect_density.csv 1. Number of variables: 6 2. Number of cases/rows: 116 3. Variable List: Stratum : Habitat suitabililty stratum class (High and Medium) Stratum_Area : Size of the stratum area (square kilometers) Transect : Transect label Length : Length of the transect walked (meters) Distance : Perpendicular distance to the centre of the dung pile (meters) Decay : Decay stage 4. Missing data codes: None 5. Abbreviations used: NA; not applicable DATA-SPECIFIC INFORMATION FOR: Cheah&Yoganand_2022_b_Dung_decay.csv 1. Number of variables: 2 2. Number of cases/rows: 97 3. Variable List: DAYS : Number of days it takes for the dung piles to decay. STATE : Decay stage. Dung piles that have disappeared are classified as '0', while dung piles that are still present are classified as '1'. 4. Missing data codes: None 5. Abbreviations used: NA; not applicable