French Guianan mammal and bird population densities with spatial-capture recapture, line transect distance sampling, and 'unmarked' density models

Estimating population densities of large wildlife in forests has traditionally relied on either spatial capture-recapture (SCR) for animals that are individually marked, or line transect distance sampling (LTDS) for species observable by researchers. Recent advances have now introduced more general camera trap models that are applicable to a large range of terrestrial medium to large-sized species. However, validation of these unmarked density (UD) models remains scarce due to the lack of available density estimates that can serve as references. We tested the accuracy and precision of three UD models (the random encounter model, camera trap distance sampling, and the time-to-event model) against independent SCR estimates for ocelots and jaguars, and against LTDS estimates for eight unmarked species varying in abundance and ecology. We found that UD model estimates for ocelots were relatively accurate in matching the estimates from SCR, albeit with less precision. Additionally, UD model ..., In 2022-2023, we conducted three surveys at a single tropical forest site in French Guiana: 1) a camera trap survey for unmarked density (UD) models for all terrestrial mammals and birds; 2) a camera trap spatial capture-recapture (SCR) survey for ocelot and jaguar; and 3) a line transect distance sampling (LTDS) survey for all large-bodied mammals and birds that can be observed by researchers walking on transects. The study site is a continuous block of coastal plain swamp forest contained within the boundaries of the Centre Spatial Guyanais (CSG) in French Guiana (RichardHansen et al., 2006; Petit et al., 2018).
Camera trap survey for unmarked density modellingFor the unmarked density models, we installed CTs at 150 deployment locations by rotating 50 camera traps (model BTC-8A) three times after a sampling period of approximately one month. CTs were installed on a systematic grid with 0.5 km interspacing at predetermined points to avoid selecting locations with biased encounter rates..., , # Validating density estimation methods for unmarked wildlife with camera traps

[https://doi.org/10.5061/dryad.fttdz091v](https://doi.org/10.5061/dryad.fttdz091v)

## Description of the data and file structure

The scripts for the unmarked density models are provided as follows:

* o   **image-processing-unmarked-2024.R**: this script takes as input the annotated image database (which we made in the TimeLapse2 sofware) as a.csv and processes the images. The camera model is calibrated following the CTtracking protocol and various unmarked parameters are estimated such as encounter rate, activity level, and animal movement speed.

o   **unmarked-models-2024:** this script takes the output from the former script and uses the parameters to estimate the effective detection zones and eventually the densities with CTDS, the TTE model, and the REM.

The data that are required as input for the first script are provided; the input for the second script is the output from the first script. For ...