Livestock activity shifts large herbivore temporal distributions to their crepuscular edges
Data files
Dec 22, 2023 version files 4.02 MB
Abstract
Wildlife species are transitioning to greater crepuscular and nocturnal activity in response to high human densities. This plasticity in temporal niches may partially mitigate the impacts of human activity but may also result in underestimating human effects on species foraging, predator-prey relationships, and community level interactions. We deployed remote cameras to characterize shifts in herbivore diel activity in protected habitat vs pastoralist landscapes. We then compared species traits including body mass, dietary preferences, and behavioral characteristics as potential predictors of species sensitivity to livestock. Our data capture a significant temporal shift away from core cattle activity for nearly every herbivore species in our study, leading to more crepuscular activity patterns. As livestock were primarily diurnal and predators primarily nocturnal in pastoralist habitat, species that decreased their overlap with livestock were more likely to increase their overlap with potential predators. Other than species’ typical daytime activity levels, we found no evidence that any particular trait significantly predicted temporal shifts in response to livestock. Instead, species generally trended toward greater activity levels at dawn, suggesting that cattle have a homogenizing effect on community-wide activity patterns. Our findings highlight how cohabitation with livestock can profoundly alter the temporal niches of wild herbivores. Shifts in diel activity patterns may reduce herbivore foraging time or efficiency and potentially have cascading shifts on predator-prey dynamics. Given that species traits could not predict responses to livestock, our analysis suggests that conservation strategies should consider each species separately when designing interventions for wildlife management.
README: Livestock activity shifts large herbivore temporal distributions to their crepuscular edges
https://doi.org/10.5061/dryad.79cnp5j28
Attached are csv files describing species occurrence in mara conservancy camera trap sites. The data has been pre-filtered for temporal independence by species occurring within the same 30-minute intervals.
Description of the data and file structure
Mara_Filtered.csv – List of mara conservancy image data filtered at 30-minute intervals for the same species for temporal independence. Data columns described as follows:
· Capture_id: A unique identifier for each capture event and resultant image set.
· Park: The name of the mara conservancy sampled: ENO (Enonkishu), OLC (Ol Choro), and LEM (Lemek).
· Season: The numbered batch of images, ~1 year of data (ie: S1, S2, S3…).
· Site: The unique alpha-numeric site code each camera trap site in the grid.
· Roll: Unique identifier for each memory card swap (ie: R1, R2, R3…).
· Date: The date stamp from the image is reported in yyyy-mm-dd.
· Time: The time stamp from the image is reported in hh:mm:ss. Time zone is UTC + 3:00. Daylight savings time is not observed Kenya.
· Species: Species of animal in the capture event. Multiple species in a single capture event are represented in separate rows.
Mara_Metadata.csv – Camera site metadata, including habitat characteristics and distance to nearest points of interest. NA values indicate habitat metadata not recorded for that camera site. Data columns described as follows:
· Park: The name of the mara conservancy sampled: ENO (Enonkishu), OLC (Ol Choro), and LEM (Lemek).
· Site_ID: The unique alpha-numeric site code each camera trap site in the grid.
· Status: Whether this is the current location of the camera site (current), an old location that has since been changed (moved), or the camera site has been permanently removed (pulled).
· Date: Date that camera site was initially established.
· DD_Lat, DD_Long: X and Y coordinates of the site (datum Arc1960, zone 36S)
· Habitat: Classification of habitat at camera site (Grassland, Open Shrub, Dense Shrub, Forest).
· Shade: Categorical ranking of shade over camera trap; 0-4 (4 highest).
· Vis_Mean: Average Visibility at camera trap; rangefinders were placed 1.0 m above the ground and three readings were taken: one reading directly pointing out in front of the camera trap and two slightly angled to either side.
· Mean_TreeDist: Averaged distance in meters to ten nearest trees; if no trees are present, we used “1500 meters”.
· Road: Distance in meters of camera trap to nearest paved road.
· Trail: Distance in meters of camera trap to nearest trail.
· Settlement: Distance in meters of camera trap to nearest settlement.
· Water: Distance in meters of camera trap to nearest body of water (dam, stream, river).
Sharing/Access information
Files above include Mara conservancy data only. For Serengeti camera image data see:
Swanson, Alexandra B. et al. (2016). Data from: Snapshot Serengeti, high-frequency annotated camera trap images of 40 mammalian species in an African savanna [Dataset]. Dryad. https://doi.org/10.5061/dryad.5pt92
Methods
Camera-Trap Data Collection
This study was a comparative assessment of species activity patterns in the presence (Mara conservancies) and absence (Serengeti National Park) of cattle. Species activity patterns were inferred from camera image data. Serengeti camera data was previously published on dataDryad (doi: 10.1038/sdata.2015.26). For Mara conservancy data, we deployed unpaired, unbaited remote cameras along systematic grids in accrodance with Snapshot Serengeti methodology. In the conservancies, a total of 63 Cuddeback cameras (Models 1347 and 1279; Cuddeback Inc., Green Bay, WI, USA) were spaced at ~1.15 km intervals. Enonkishu housed 21 cameras from Nov. 2018 to 2022, and the grid was expanded into Ol Choro and Lemek conservancies in Aug. 2021. For optimal species detection and camera efficiency, cameras captured 3 images per trigger during the day and 1 image per trigger at night. Each trigger was considered an individual “capture event”, remaining dormant for 1-minute in between captures. To insure temporal independence. capture events were filtered to remove repeats of the same species at the same camera within 30-minute intervals.