Forest Elephant Crisis in the Congo Basin

Debate over repealing the ivory trade ban dominates conferences of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Resolving this controversy requires accurate estimates of elephant population trends and rates of illegal killing. Most African savannah elephant populations are well known; however, the status of forest elephants, perhaps a distinct species, in the vast Congo Basin is unclear. We assessed population status and incidence of poaching from line-transect and reconnaissance surveys conducted on foot in sites throughout the Congo Basin. Results indicate that the abundance and range of forest elephants are threatened from poaching that is most intense close to roads. The probability of elephant presence increased with distance to roads, whereas that of human signs declined. At all distances from roads, the probability of elephant occurrence was always higher inside, compared to outside, protected areas, whereas that of humans was always lower. Inside protected areas, forest elephant density was correlated with the size of remote forest core, but not with size of protected area. Forest elephants must be prioritised in elephant management planning at the continental scale

Results of Fitting a Logistic Regression Model to Elephant and Human Presence/Absence Megatransect Data

<p>Distance to road (in kilometres) and location within or outside the protected areas were used as explanatory variables. (A) shows the elephant data, and (B) shows the human data. The observations and regression lines are colour-coded to correspond to within or outside the protected areas and the dashed line shows the regression line with only the distance to road covariate. The covariates distance to road and location within or outside the protected areas are significant for both elephant and human probability of occurrence.</p

Results of Fitting a Logistic Regression Model to Elephant and Human Presence/Absence Data for Each MIKE Survey Site Separately

<p>Distance to road (in kilometres) was used as the explanatory variable (except for probability of elephant occurrence for Minkébé where modelling is not required due to an effective probability of 1). Elephant data are shown to the left, and human data to the right. The observations and regression lines are colour-coded by site, and the 95% confidence interval is indicated by the dotted lines. The probability of elephant occurrence is significantly related to distance to road for all sites except Minkébé and Salonga. Due to the imprecision in the data and other influences not captured by distance to road, the probability of human presence is only significantly related to distance to road for the Ndoki-Dzanga site for the separate site analyses.</p

Interpolated Elephant Dung Count and Human-Sign Frequency across the Ndoki-Dzanga MIKE Site

<p>Increasing colour intensity signifies increasing dung and human-sign frequency.</p

MIKE Survey Sites and the Megatransect

<p>Note that the since the Dzanga-Sangha and Nouabalé-Ndoki MIKE sites comprise a contiguous forest block, they were combined into a single unit (Ndoki-Dzanga) for analytical purposes.</p

Estimated Conditional Dependence of Elephant Dung-Pile Numbers on Distance to Road (in Kilometres)

<p>Estimates (solid line) and confidence intervals (dashed lines), with a rug plot indicating observation density along the bottom of the plot, are shown. To avoid over-fitting, the degrees of freedom were restricted to two for the distance-to-road covariate.</p

Results of Fitting a Logistic Regression Model to Elephant and Human Presence/Absence Data Pooled across MIKE Survey Sites

<p>Distance to road (in kilometres) and site were used as explanatory variables. (A) shows the elephant data, and (B) shows the human data. The observations and regression lines are colour-coded by site and the dashed line shows the regression line without the inclusion of site as a covariate. The covariates distance to road and site are significant for both elephant and human probability of occurrence. The dissimilarity between sites is more pronounced when modelling the probability of elephant occurrence.</p

Estimated Conditional Dependence of Elephant Dung-Pile Numbers on Distance from Road (in Kilometres) and Distance to the Nearest Protected Area Boundary (in Kilometres)

<p>(A) shows the effect of distance from the road, and (B) shows the effect of distance to the nearest boundary of the protected area. Negative distances indicate locations inside protected areas. Estimates (solid lines) and confidence intervals (dashed lines), with a rug plot indicating observation density along the bottom of the plot, are shown. To avoid over-fitting, the degrees of freedom for this model were restricted to 3 for both covariates.</p

Devastating Decline of Forest Elephants in Central Africa.

African forest elephants– taxonomically and functionally unique–are being poached at accelerating rates, but we lack range-wide information on the repercussions. Analysis of the largest survey dataset ever assembled for forest elephants (80 foot-surveys; covering 13,000 km; 91,600 person-days of fieldwork) revealed that population size declined by ca. 62% between 2002–2011, and the taxon lost 30% of its geographical range. The population is now less than 10% of its potential size, occupying less than 25% of its potential range. High human population density, hunting intensity, absence of law enforcement, poor governance, and proximity to expanding infrastructure are the strongest predictors of decline. To save the remaining African forest elephants, illegal poaching for ivory and encroachment into core elephant habitat must be stopped. In addition, the international demand for ivory, which fuels illegal trade, must be dramatically reduced