Fecal standing crop with real time correction using scat detection dogs to estimate population density
Data files
Apr 01, 2024 version files 15.64 KB
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Raw_Data.xlsx
12.46 KB
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README.md
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Abstract
Population density is fundamental information for assessing the conservation status of species and support management and conservation actions for in situ populations, but is unknown for many forest species due to their difficulty in detection. The Fecal Standing Crop (FSC) method using detection dogs is an alternative for cryptic or elusive species. An intrinsic difficulty of FSC is the ability to find fecal samples in the field and to estimate the probability of which feces detection is influenced by degradation due to climatic conditions. Our goal was to propose a concurrent FSC parameter estimation using a scat detection dog under different climatic conditions and apply those parameters in a wild deer population. Ten fecal samples of gray brocket deer (Subulo gouazoubira) were placed weekly in a transect (24 x 1200 m) in both dry and wet seasons (12 weeks each). A scat detection dog was then employed to find experimental fecal samples to determine the FSC parameters that were subsequently used with naturally occurring fecal samples (also dog-detected) to estimate population density. The oldest dog found samples were 21 (Dry) and seven (Wet) days after placement, resulting in dog efficiency of 23% (Dry) and 30% (Wet). Adjusting the model to account for efficiency and scat durability, we estimated similar, seasonal, densities of 4.54 individuals km-2 (SD = 2.21, Dry) and 5.52 indiv. km-2 (SD = 3.71, Wet).
Synthesis and applications: Our results demonstrate that our concurrent methodology corrected the effects of weather and habitat on FSC parameters thereby allowing for accurate population density estimation. Additionally, this method can provide reasonably precise density estimates with a logistically feasible sample size, as demonstrated by simulation. Following our recommendations, this method allows a reliable estimate of population density because it incorporates any influence of study area, dog ability, and climate in fecal sample detection, providing fundamental information for the conservation of many cryptic and elusive species.
README: Fecal Standing Crop with real time correction using scat detection dogs to estimate population density
https://doi.org/10.5061/dryad.5qfttdzdx
This dataset contains a file with two tables. One table was obtained by traversing the experimental transects, and the other was obtained by traversing the density estimation transects. For the first table, we established a 1440 m length transect in the study area with 120 places in 5 distance classes (0, 3, 6, 9 and 12) from the mid-line of the transect on alternating sides of, and perpendicularly to, the mid-line. Then, one day each week for 12 weeks, we randomly selected 10 distances from the beginning and the midline of the transect (two at each distance) at which we placed fresh faecal samples (20 pellets each sample) of gray brocket deer. After the last placement, the transect had a total of 120 samples, with 10 groups from 12 different ages and 24 group in five different perpendicular distances. We conducted this experiment twice: dry season (April to July 2021) and wet season (October to December 2021). At week 12, two hours after placing the last scat samples in the field, we brought the scat detection dog and began the search for scat samples that were in the field for 0 (2 hours) to 11 weeks.
For the second table, the day following the experimental placement and recovery of the feces to estimate the model parameters as described above, we used the same dog to find natural deer faeces in six transects (750 – 1710 m long) during the dry season (July 2021) and wet season (December 2021). As a result, in the dry season, the dog found 12 samples, and in the wet season, the dog found six fecal samples. In the six sampling transects, the scat detection dog found 55 (dry season) and 28 (wet season) fecal samples. Using the parameters estimated by season, the gray brocket deer densities were similar in both seasons at 4.51 individuals km-2 in the dry season and 5.37 individuals km-2 in the wet season.
Description of the data and file structure
We have structured the data in a straightforward manner to facilitate comprehension for our readers. The table labeled "Table density" contains, in the first column, the names of the transects for each of the seasons, with the transect labeled "ET" referring to the test transect. The second column contains the transect sizes, followed by the quantity of fecal samples found per transect in the third column, and finally, the season to which the transect belongs in the last column. Similarly, the table labeled "Table experimental" follows the same logic, with the first two columns pertaining to the age of the samples, followed by the quantity of available and found samples, the perpendicular distance of the sample relative to the transect, and the season to which the data belong. In this table, the rows filled with "null" represent ages for which the dog did not find any samples.
Code/Software
We are currently in the process of preparing an organized script for deposition on GitHub. Should readers require access to the code, they are welcome to contact the corresponding author directly.