Hunting data collected in the Ebo forest, Cameroon from 2008 to 2023

The long-term survival of many mammal populations relies on how
effectively we mitigate the threat from unsustainable hunting. Yet,
hunting activities are often cryptic, especially in unprotected forests.
Here, we investigate whether hunting signs can help understand the
spatiotemporal dynamics of hunting activities in an unprotected African
rainforest and examine how landscape characteristics predict various
indicators of hunting. We recorded hunting signs (e.g., shotgun
cartridges, wire snares, direct sightings) systematically on 23 parallel
recce lines across the Ebo forest, Cameroon from 2008 to 2023. We assigned
hunting data and spatial covariates (e.g., elevation, distance to the
village) to 1×1 km grid cells and applied generalized linear mixed models
to predict the effects of these covariates on hunting. We found that
hunting was commonplace across the entire Ebo forest. The best-fitting
models for each hunting sign differed considerably. Shotgun cartridges and
all hunting signs combined increased significantly from 2016 to 2023 and
varied non-linearly along the village-distance gradient. We found a
progressive inversion of hunting trends along the anthropogenic gradient;
between 2016 and 2018, wire snares declined with the distance to the road
but from 2021, they increased along the road distance gradient. Wire
snares showed a similar pattern along the river distance gradient. Our
results also revealed differences between shotgun hunting and snaring
along the altitudinal gradient; the effect of elevation was positive on
shotgun cartridges and negative on wire snares. Hunting signs and trails
decreased significantly with increasing terrain ruggedness. Using
long-term monitoring data, we show how hunting patterns change dynamically
with respect to human and landscape-related features. We also demonstrate
complex hunting patterns along the gradient of human influence, therefore
questioning the use of proxies such as the distance to human settlements
and even topography to account for hunting pressure. Overall, we show that
hunting sign data can reveal the spatiotemporal patterns of hunting,
crucial in evaluating the effectiveness of conservation interventions and
guiding the prioritisation of limited conservation resources.