Effective wildlife management requires monitoring
changes in the spatial distribution of species, their
population size and population trends (Sinclair et
al. 2006). However, obtaining this data, particularly
for rare and elusive species such as forest elephants
(Loxodonta cyclotis), is not a trivial task. Surveys
designed to collect the relevant data are often
challenged by environmental factors (weather,
land cover) and animal behaviours that can cause
imperfect detection of all individuals, leading to
estimates that are biased and/or imprecise (Williams
et al. 2002). Moreover, methods currently used
for assessing wildlife density in rainforests are
time-consuming and expensive, or not suitable
to cover large areas, at least on a regular basis
(Hoeven et al. 2004; Zhou and Griffiths 2007).
Significant research effort continues to be directed
at developing reliable, cost-effective monitoring
methods for rare and elusive species (Thompson
2004; Conroy et al. 2008; Royle et al. 2013).
However, field data with which to assess the forest
elephant’s status and population trends across its
geographical range remain limited, and recent field
surveys using standard ecological field techniques
have typically failed to detect wild individuals
(Camino et al. 2020).