Data from: Ecological correlates of the spatial co-occurrence of sympatric mammalian carnivores worldwide

Davis, Courtney L., Pennsylvania State University

Rich, Lindsey N., Pennsylvania State University

Farris, Zach J., Virginia Tech, Appalachian State University

Kelly, Marcella J., Virginia Tech

Di Bitetti, Mario S., National University of Misiones

Di Blanco, Yamil, National University of Misiones

Albanesi, Sebastian, Panthera Corporation

Farhadinia, Mohammad S., University of Oxford

Gholikhani, Navid, Virginia Tech

Hamel, Sandra, The Arctic University of Norway

Harmsen, Bart J., University of Belize, Panthera Corporation

Wultsch, Claudia, Virginia Tech, Panthera Corporation

Kane, Mamadou D., Senegalese National Parks Directorate; Dakar Senegal

Martins, Quinton, Cape Leopard Trust

Murphy, Asia J., Pennsylvania State University

Steenweg, Robin, Species at Risk, Resource Management; Alberta Environment and Parks; Grande Prairie AB Canada

Sunarto, S., World Wide Fund for Nature

Taktehrani, Atieh, Iranian Cheetah Society; PO Box 14155-8549 Tehran Iran

Thapa, Kanchan, Virginia Tech

Tucker, Jody M., US Forest Service

Whittington, Jesse, Parks Canada

Widodo, Febri A., The Arctic University of Norway

Yoccoz, Nigel G., The Arctic University of Norway

Miller, David A.W., Pennsylvania State University

Publication date: June 15, 2019

Publisher: Dryad

https://doi.org/10.5061/dryad.7f9j57n

Citation

Davis, Courtney L. et al. (2019), Data from: Ecological correlates of the spatial co-occurrence of sympatric mammalian carnivores worldwide, Dryad, Dataset, https://doi.org/10.5061/dryad.7f9j57n

Abstract

The composition of local mammalian carnivore communities has far-reaching effects on terrestrial ecosystems worldwide. To better understand how carnivore communities are structured, we analyzed camera trap data for 108,087 trap days across 12 countries spanning 5 continents. We estimate local probabilities of co-occurrence among 768 species pairs from the order Carnivora and evaluate how shared ecological traits correlated with probabilities of co-occurrence. Within individual study areas, species pairs co-occurred more frequently than expected at random. Co-occurrence probabilities were greatest for species pairs that shared ecological traits including similar body size, temporal activity pattern, and diet. However, co-occurrence decreased as compared to other species pairs when the pair included a large-bodied carnivore. Our results suggest that a combination of shared traits and top-down regulation by large carnivores shape local carnivore communities globally.

Usage Notes

Camera Trap Detections of Carnivore Species for Co-occurrence Model

Raw camera trap detections of paired mammalian carnivore species in each of the 13 study areas. Detections of the paired species (Spp1Det and Spp2Det) reflect the number of 24-hr. time periods that species 1 (SppCode1) and species 2 (SppCode2) were detected. Species codes (SppCode1 and SppCode2) were derived from the first two letters of the genus and species name (e.g., EIBA = Eira barbara). Num.nights reflects the number of 24-hr. periods during which the camera trap was active at a particular site. This file can be used to estimate the species interaction factor (SIF) within the species co-occurrence model.

SIF_InputData.csv

Species Trait Data for Regression Analysis

Species trait data for each of the 768 paired carnivores in all 13 study areas. Species codes (Spp1 and Spp2) were derived from the first two letters of the genus and species name (e.g., EIBA = Eira barbara). Appendix S2 contains the full list of species examined in this study. We summarized the categorical variables of diet, temporal activity pattern, social structure, body size and taxonomic similarity in two ways. For the first coarse comparison method (e.g., DietCovSimple), we compared species with differing trait values (e.g., when species A | B are strict carnivore | omnivore) to those where pairs shared the trait value (e.g., strict carnivore | strict carnivore). In other words, species pairs were either labeled the ‘same’ or ‘different’ for all categorical variables of interest. For the fine-scale trait comparison (e.g., DietCov), species pairs were categorically valued for all combinations of a trait (e.g., strict carnivore | strict carnivore = 1, strict carnivore | omnivore = 2, strict carnivore | insectivore = 3, etc.). We also characterized the mean weight ratio (heavier:lighter species, MeanBodySize) between two species, including it as a log-transformed continuous variable (logMeanBodySize). We also include the observed number of carnivore species in each study area (NumSpecies) and the study area’s climate as determined by the Köppen-Geiger climate classification system (Climate). Finally, this file also includes the estimated Species Interaction Factor (SIF), the standard deviation of SIF (sd), and the log-transformed SIF values (logSIF).

SIF_TraitData.csv

Location

Canada

Argentina

Iran

Norway

Senegal

Botswana

South Africa

Belize

Madagascar

U.S.A.

Nepal

Indonesia