Resource variability, aggregation and direct density dependence in an open context: the local regulation of an African elephant population

Abstract

Summary1. An emerging perspective in the study of density dependence is the importance of the spatial and temporal heterogeneity of resources. Although this is well understood in temperate ungulates, few studies have been conducted in tropical environments where both food and water are limiting resources. 2. We studied the regulation of one of the world's largest elephant populations in Hwange National Park, Zimbabwe. The study period started in 1986 when the population was released from culling. Using census data we investigated changes in elephant abundance with respect to rainfall and density across the entire park and across waterholes. 3. The population more than doubled since culling stopped. The population increased continuously during the first 6 years, and then fluctuated widely at about 30 000 individuals. Immigration processes must have been involved in the increase of the population size. 4. Population growth rates were negatively related to previous population density by a convex relationship, and negatively related to the ratio of previous population density on annual rainfall by a linear relationship. However, only this latter model (i.e. assuming a fluctuating carrying capacity related to annual rainfall) produced realistic dynamics. Overall, population decreased during dry years when the elephant density was high. 5. During dry years there were fewer waterholes retaining water during the dry season and consequently elephant numbers at waterholes increased, while their aggregation level across waterholes decreased. On the long-run elephant numbers increased only at the less crowded waterholes. 6. We suggest that the interaction between population size and the available foraging range determined by the number of active waterholes during the dry season controls the park population. 7. Our results emphasize the need to understand how key-resource areas cause resource-based aggregation, which ultimately influences the strength of density dependence. More specifically, this study suggests that climate variability strongly affects local elephant population dynamics through changes in surface-water availability. Finally, as dispersal is likely to be an important driver of the dynamics of this population, our results support views that a metapopulation framework should be endorsed for elephant management in open contexts.

Temporal Variation in the Carrying Capacity of a Perennial Grass Population

“…Variation in K may provide insights into mechanisms underlying population regulation, especially if variation in K accounts for a substantial portion of the variation in N, as it did here (j K was at least three times the variation in N from all other sources). Previous models that have implicitly incorporated variation in K have done so by making resource levels a function of one or more climatic variables, often rainfall, usually with good success (e.g., Illius and O'Connor 2000;Davis et al 2002;Owen-Smith 2002;Georgiadis et al 2003;Lima et al 2006Lima et al , 2008Hone and Clutton-Brock 2007;Chamaillé-Jammes et al 2008;Yang et al 2008). Bouteloua rigidiseta readily adds tillers in response to rain and dies back in response to drought (N. L. Fowler, personal observation).…”

“…Rainfall, mediated through total plant biomass, is also an obvious limiting factor for large herbivores in arid climates. The majority of models that have implicitly incorporated variation in equilibrium population size have done so by incorporating the effects of rainfall into population models of large herbivores (e.g., Illius and O'Connor 2000;Davis et al 2002;Owen-Smith 2002;Georgiadis et al 2003;Chamaillé-Jammes et al 2008). In most cases, the inclusion of rainfall-dependent variation in resource levels has improved the prediction of herbivore population sizes.…”

Decoupling of component and ensemble density feedbacks in birds and mammals

“…Furthermore, the Gompertz-logistic model has performed robustly in describing the general dynamics of populations of birds and mammals over a wide range of body sizes (e.g., Saitoh et al 1997, 2008, Wang et al 2002, White et al 2007, Seavy et al 2009, Pasinelli et al 2011, is present in multi-model inference scenarios where competing models are contrasted (Saitoh et al 1997, Zeng et al 1998, Fryxell et al 2005, Chamaille´-Jammes et al 2008, McMahon et al 2009), is the top-ranked model in meta-analyses of hundreds of species in which various alternatives have also been evaluated (e.g., Brook and Bradshaw 2006), and has been a model used in theoretical development about density feedback (e.g., Dennis et al 2006). We avoided fitting the fully parameterized h-logistic model, due to recent caveats of application to analyses of time series (Clark et al 2010), or other highly parameterized analogues (e.g., hyperbolic growth).…”

How should the psychological well‐being of zoo elephants be objectively investigated?

“…Studies of wild African elephants' ranging behavior certainly reveal clustering around important resources like water [Chamaille´-Jammes et al, 2008], and the avoidance of potential threats or wastes of energy. Thus, they show avoidance of roads [e.g.…”