Effect of free-ranging cattle on mammalian diversity 881
TABLE 1(Cont.) Species (by family)
Erithizontidae Bicolored-spined porcupine Coendou bicolor Prehensile-tailed porcupine Coendou prehensilis
Hydrochaeridae Capybara Hydrochoerus hydrochaeris
Dasyproctidae Yungas agouti Dasyprocta sp.
Myocastoridae Coypu Myocastor coypus
Suidae Pig Sus scrofa
Bovidae Cattle Bos taurus
Equidae Horse Equus caballus Donkey Equus asinus
Ovidae Sheep Ovis aries
Capridae Goat Capra sp.
1Ministerio de Ambiente y Desarrollo Sostenible & Sociedad Argentina para el Estudio de los Mamíferos (2019). 2IUCN (2021).
DD, Deficient Data; LC, Least Concern; NT, Near Threatened; EN, Endangered; CR Critically Endangered. index (RAI) as: RAIi = ntot/daystot ×100 (1)
where ntot is the number of independent events of the ith species and daystot is the total number of effective trap- nights, using the package camtrapR (Bengsen et al., 2011; Mandujano & Pérez-Solano, 2019)in R 2.15.2 (R Core Team, 2019). We calculated two measures of diversity, using the package vegan (Oksanen et al., 2019)in R: species richness (S) and the Shannon–Weaver index (H). The latter was calculated as:
H =−S i=1 RAIi ×ln(RAIi)(2)
The value of the relative abundance index increases with in- creasing richness and evenness in the abundance of species in the community. We developed generalized linear models (GLM) to
examine the effect of cattle and land protection status on S and H. As biodiversity follows global patterns, with an in- crease in species richness toward the tropics and a decline in species richness with increasing elevation (Pianka, 1966; Lomolino, 2001; Hillebrand, 2004), we included altitude and latitude as factors in the models. For each of the four species groups we examined the potential influence of ex- planatory variables on presence/absence of species and on relative abundance index; for small mammals: cattle abun- dance and primary production; for large herbivores: cattle
abundance, primary production and the human influence index; for species of conservation concern: cattle abun- dance, primary production, human influence index, land protection status and distance to water lines; for the felid community: cattle relative abundance index and the human impact index. For presence/absence models, we used the negative binomial error and Gaussian distributions for abundance, using the package MASS (Venables&Ripley, 2007)in R. We checked for homogeneity by plotting resi- duals vs fitted values, for normality using quantile-quantile plots, and for independence by plotting residuals vs each ex- planatory variable. Because we had several combinations of variables and therefore multiple models, we used single- term deletions to obtain the most parsimonious model, using Akaike’s information criterion (AIC; Burnham & Anderson, 2002).
A niche-based model for cattle
Species distribution models examine the potential influence of environmental variables on species presence. MaxEnt finds the distribution of maximum entropy (i.e. the largest spread in a geographical dataset of species presences), sub- ject to the constraint that the projected value of each variable is close to its empirical average (Phillips et al., 2020). This information can then be extrapolated to non-sampled areas (Phillips et al., 2006).
Oryx, 2022, 56(6), 877–887 © The Author(s), 2022. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S0030605321001538
Species group
National status1
VU VU
LC
Small mammal LC LC
Red List status2
LC LC
LC LC LC
Native/ exotic
Recorded
Native No Native No
Native No Native Yes Native No Exotic Exotic Exotic
Yes Yes Yes
Exotic Exotic Exotic
Yes Yes Yes
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