Assessing trends and seasonal changes in elephant poaching risk at the small area level using spatio-temporal Bayesian modeling

<p>Knowledge about changes in wildlife poaching risk at fine spatial scale can provide essential background intelligence for law enforcement and crime prevention. We assessed interannual trends and seasonal changes in elephant poaching risk for Kenya’s Greater Tsavo ecosystem for 2002 to 2012 using spatio-temporal Bayesian modeling. Poaching data were obtained from the Kenya Wildlife Service’s database on elephant mortality. The novelty of our paper is (1) combining space and time when defining poaching risk for elephant; (2) the inclusion of environmental risk factors to improve the accuracy of the spatio-temporal Bayesian model; and (3) the separate analysis of dry and wet seasons to understand season-dependent poaching patterns. Although Tsavo’s overall poaching level increased over time, the risk of poaching differed significantly across space. Three of the 34 spatial units had a consistently high poaching risk regardless of whether models included environmental risk factors. Adding risk factors enhanced the model’s predictive power. We found that highest poaching risk areas differed between the wet and dry season. The findings improve our understanding of elephant poaching and highlight high risk areas within Tsavo where action to reduce elephant poaching is required.</p

A New Tooth Wear–Based Dietary Analysis Method for Proboscidea (Mammalia)

<div><p>ABSTRACT</p><p>Dietary analyses of herbivorous mammals are important for paleoecological reconstruction. Several methods applicable to fossil teeth have been developed lately. The mesowear method based on wear-induced occlusal shape and relief of ungulate molars has proven to be a robust method for dietary analysis. In its original form it can only be used for selenodont, plagiolophodont, and ectolophodont ungulate molars, but the principle can be extended to other kinds of tooth morphology. We introduce a new method of dietary analysis for proboscideans similar to the mesowear method, based on angle measurements from worn dentin valleys reflecting the relief of enamel ridges. The enamel ridges should be heavily worn when the abrasiveness of diet increases, resulting in lower occlusal relief and larger angles. For testing this, we compared the mesowear angles with stable carbon isotope values from dental enamel from populations of extant and fossil species from localities from Kenya and India. This enables us to compare diet and tooth wear in proboscideans, because the stable carbon isotope ratios in tropical environments provide a reliable standard for assessing the relative amounts of C4 and C3 plants in diet, and most of the C4 plants are grasses, which should be reflected in the mesowear signal.</p><p>SUPPLEMENTAL DATA—Supplemental materials are available for this article for free at www.tandfonline.com/UJVP</p></div

The proportion of illegally killed elephants (PIKE) in the six land use types.

<p>Land uses are abbreviated as PRC (private ranches and conservancies), SET (settlements and farms under private ownership), NR (national reserves), FR (forest reserves on government-owned land), CCA (community conservation), and CPL (community pastoralism on communally owned land). There was no significant difference (abbreviated as ‘n. s.’ on the figure) in the PIKE level between private ranches and settlements Mann-Whitney U test (<i>P</i> = 0.96).</p

The deviance explained by various covariates of the top model for the probability of illegal killing of elephants in the Laikipia-Samburu ecosystem.

<p>* denotes interactive effects</p><p>Land use and time factor explain 38% of the variation in illegal killing.</p

Land ownership and the corresponding land use types in the Laikipia-Samburu ecosystem.

<p>Land ownership and the corresponding land use types in the Laikipia-Samburu ecosystem.</p

Land ownership (private, communal or government) and types of use (managed to enhance wildlife or not) in the Laikipia-Samburu ecosystem.

<p>There are three main land ownership types; private, communal and government. Ranches, community conservancies and national reserves have active wildlife protection measures in place.</p

The numbers of elephants that died from poaching and other causes from 2002–2012.

<p>The dotted line indicates the level of poaching (i.e., 54% PIKE) beyond which populations cannot compensate via births and decline is imminent.</p

Candidate models in the analyses of the relationship between the probability of illegal killing of elephants (<i>P</i>_illegal), land ownership, land use and elephant densities.

<p>‘WF’ denotes wildlife-friendly land regardless of ownership. The asterisk between covariates shows the only interactive effects of ownership and use that were found to be significant predictors of illegal killing.</p

Selection statistics for the top two models of the analyses of relationships between the probability of illegal killing of elephants, land ownership, land uses and elephant density.

<p>* denotes interactive effects. aAICc: Second-order Akaike Information Criterion; bΔi: delta AIC values; cwi: Akaike weights.</p><p>The coefficient for each variable is presented alongside each variable. ‘WF’ denotes wildlife friendly land regardless of ownership.</p

Trends in the level of proportion of illegally killed elephants (PIKE) across the different types of land use for 2002–2012.

<p>An increase in PIKE from 2010–2012 was recorded in most of the land use types.</p