Predicting population survival under future climate change: density dependence, drought and extraction in an insular bighorn sheep.
1. Our understanding of the interplay between density dependence, climatic perturbations, and conservation practices on the dynamics of small populations is still limited. This can result in uninformed strategies that put endangered populations at risk. Moreover, the data available for a large number of populations in such circumstances are sparse and mined with missing data. Under the current climate change scenarios, it is essential to develop appropriate inferential methods that can make use of such data sets. 2. We studied a population of desert bighorn sheep introduced to Tiburon Island, Mexico in 1975 and subjected to irregular extractions for the last 10 years. The unique attributes of this population are absence of predation and disease, thereby permitting us to explore the combined effect of density dependence, environmental variability and extraction in a 'controlled setting.' Using a combination of nonlinear discrete models with long-term field data, we constructed three basic Bayesian state space models with increasing density dependence (DD), and the same three models with the addition of summer drought effects. 3. We subsequently used Monte Carlo simulations to evaluate the combined effect of drought, DD, and increasing extractions on the probability of population survival under two climate change scenarios (based on the Intergovernmental Panel on Climate Change predictions): (i) increase in drought variability; and (ii) increase in mean drought severity. 4. The population grew from 16 individuals introduced in 1975 to close to 700 by 1993. Our results show that the population's growth was dominated by DD, with drought having a secondary but still relevant effect on its dynamics. 5. Our predictions suggest that under climate change scenario (i), extraction dominates the fate of the population, while for scenario (ii), an increase in mean drought affects the population's probability of survival in an equivalent magnitude as extractions. Thus, for the long-term survival of the population, our results stress that a more variable environment is less threatening than one in which the mean conditions become harsher. Current climate change scenarios and their underlying uncertainty make studies such as this one crucial for understanding the dynamics of ungulate populations and their conservation.
Colchero
Fernando
F
Nicholas School of the Environment, Duke University, Box 90328, Durham, NC 27708 USA. colchero@demogr.mpg.de
Medellin
Rodrigo A
RA
Clark
James S
JS
Lee
Raymond
R
Katul
Gabriel G
GG
D000220:Adaptation, Biological; D000818:Animals; D055864:Droughts; D053476:Extinction, Biological; D005843:Geography; D017752:Greenhouse Effect; D008800:Mexico; D009010:Monte Carlo Method; D011157:Population Dynamics; D034581:Sheep, Bighorn / Q000502:physiology*; D013997:Time Factors