duikers-abundance

Data and R code for "Elenga et al. PLoS 2020: Distance sampling of duikers in the rainforest: dealing with transect avoidance"

Paper summary

Over-harvesting is increasingly recognised as a critical issue for people and communities that rely on bushmeat for proteins or for income. The implementation of wildlife abundance monitoring tools could help to achieve a sustainable exploitation of animal populations. We investigate the use of distance sampling methodologies to document baseline animal population densities of forest-dwelling species as a first step towards evidence-based management of bushmeat stocks. The animals may commonly avoid the transects from which they are surveyed, leading to a negative bias in the estimates of population densities. This negative bias would then lead to over-pessimistic population viability analyses. We used a combination of simulations and transect survey data of blue duikers (Philantomba monticola) collected in the Lomako wildlife reserve in the Democratic Republic of the Congo to illustrate these points. We recommend recording both the forward and perpendicular distances routinely when detecting an animal, implementing multiple-observer protocols, and repeating the surveys multiple times per season. We warn that sometimes the propensity of animals to avoid the transects is too strong to apply distance sampling. We also outline the general principles of a local stakeholder-based program combining distance sampling with less intensive types of ecological indicators.

Provided files and description

• monticola_FINAL_20122013.csv is the distance sampling data of blue duikers at Lomako. X an Y are the recorded coordinates of each observation (WGS84 projection system); transect_id is the name of the transect; obs_period describe if the observation was made by day or night; obs_type describes if the observation was a dung pile or a direct observation of a blue duiker; nb stands for the number of observed individuals; distance is the perpendical distance of the detected dung or duiker from the transect; obs_time is the recorded timestamp for each observation; transect_start_time is the time at which observers started to walk the transect; transect_end_time is the time at which observers ended to walk the transect; X_prog and Y_proj are location coordinates in the XX projection system;

• Customized R Code to run the analyses, based on Borcher & Cox (2017)