Estimates of forest elephant abundance: projecting the relationship between precision and effort

1. A key element of African elephant conservation is monitoring how differe nt forms of human activity influence elephant distribution and abundance. I nformation on human-elephant interaction is critical for guiding conservati on action at all levels, from very local management interventions, through national protected area planning, to international policy initiatives such as the ban on ivory trade. However, methods for monitoring elephant numbers often produce rather poor estimate precision. Therefore, a major challenge for elephant monitoring programmes at all levels is to allocate survey eff ort efficiently: the greatest possible statistical power to detect the effe cts of particular forms of human activity must be obtained from limited sur vey effort. 2. This study examined an approach to survey design based on the assumption that the precision of an abundance estimate is directly proportional to sa mpling effort. Field data from three sites in Central Africa were used to e valuate the potential of this approach for projecting how much effort will be necessary to survey and monitor forest elephants. 3. Variance in elephant dung pile encounter rate was proportional to sampli ng effort, but variance was also influenced by mean encounter rate. The rel ationship between variance and mean encounter rate followed a power law mor e closely than the linear model suggested by many previous authors. The lin ear model tended to substantially underestimate the effort level required f or areas with high encounter rates. A bootstrapping exercise suggested that modelling the precision-effort relationship across strata should produce m ore accurate projections than estimating a distinct precision-effort relati onship for each stratum. 4. Our results suggest that the survey design framework examined could subs tantially improve the statistical power of forest elephant monitoring progr ammes, although the use of a power law (rather than linear) model seems pre ferable. A similar approach should be appropriate for designing savanna ele phant monitoring programmes and for addressing other issues, including rate s of hunting and human elephant conflict. Furthermore, the parameter estima tes reported in this study should be useful in designing elephant survey an d monitoring programmes at other forested sites in Central Africa.