Research Article |
Corresponding author: Finagnon Galvius Degbelo ( dgalvius@gmail.com ) Academic editor: Enrico Di Minin
© 2022 Finagnon Galvius Degbelo, Chabi Adéyèmi Marc Sylvestre Djagoun, Sêwanoudé Scholastique Mireille Toyi, Elie A. Padonou, Méryas Kouton, Nathan Gichohi, Philip Muruthi, Brice Sinsin.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Degbelo FG, Djagoun CAMS, Toyi SSM, Padonou EA, Kouton M, Gichohi N, Muruthi P, Sinsin B (2022) What shapes the mammal species poaching in protected areas: biophysical or anthropogenic factors? A case study in Pendjari Biosphere Reserve. Nature Conservation 48: 149-160. https://doi.org/10.3897/natureconservation.48.68243
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Understanding what shapes the mammal species poaching in protected areas is critical to developing targeted management strategies for reducing poaching. We collected the data for poaching incidents on the GPS coordinates from 2011 to 2017 to map poaching incidents in the Pendjari Biosphere Reserve. Poaching incidents were then related to environmental and anthropogenic variables using regression analyses. The study shows that poaching is more concentrated along the main river in the Pendjari National Park. Only nearest distance to the main river significantly predicted the location of high poaching incidents. These results could be used as the starting point by the park managers when planning the anti-poaching activities.
Benin, GIS layers, Pendjari Biosphere Reserve, poaching incidents, wildlife
The major driver of large mammal species population decreasing in Africa is poaching (
Some decades ago, an investigation on a continent-wide scale about elephant anti-poaching efficacy recommended a range of USD 50–200 per km2 annually to protect them in their natural ranges in Africa (
Efforts to assess the drivers of large mammal species poaching in PAs have highlighted several factors. It shown that areas with extensive forest cover, with more challenging patrolling and enforcement than in open savannah, show, for example, a top level of poaching in elephant (
This study aims to describe the most wildlife species poached between 2011 and 2017, together with the spatial distribution of large mammal species poaching incidents in the Pendjari’s landscape and to identify the biophysical and human factors that determine the distribution of poaching incidents. We use an explicit spatial modelling approach to quantify the relative contribution of multiple potential factors described in literature as a priori to explain the poaching incidents. We hypothesised that poacher sites would be associated with: (1) water availability, (2) accessibility (roads and topography) and (3) proximity of human settlements and land uses.
The Pendjari Biosphere Reserve successively classified as a National Forest, a partial Wildlife Reserve of the Pendjari loop and a National Park, acquired the labels of Biosphere Reserve in 1986, RAMSAR site in 2007 and now considered as a UNESCO World Heritage Site. The PBR is in the Atakora Province, north-western Benin. It is situated at 10°30' to 11°30'N; 0°50' to 2°00'E (Fig.
Annual mean precipitation is 1000 mm, with 60% falling between July and September (
Mammal species poaching data from 2011 to 2017 was obtained from the PBR anti-poaching database, which has been developed over the years during routine daily patrols by rangers. The anti-poaching patrols are randomly distributed and the poaching incidents observed during these surveillance patrols are geo-referenced. Data on poached mammal species were then entered into an EXCEL spreadsheet. Each record had the following fields: X and Y coordinates (using Universal Transverse Mercator), date of registration and name of the place where the poaching incident occurred. A total of 279 poaching points were recorded by the guards for the period. Of these locations, 228 points fell inside the PBR. A total 303 mammal individuals were poached in the PBR from 2011 to 2017.
The locations of ranger patrol bases and park gates were obtained by visiting the sites and recording their locations using a Global Positioning System (GPS). The geographic coordinates of the Park boundaries, roads, rivers and waterholes were obtained from an ecological biomonitoring service (Fig.
GIS layers generated showing locations of poaching incidents in Pendjari Biosphere Reserve.
Poaching incidents locations, as well as locations of ranger patrol bases and park gates, have been projected on to the Pendjari Biosphere Reserve map. Then, with the ARCGIS 9.2 software, the biophysical variables, such as the closest distance to waterholes (NDis_Wh); the distance closest to the main river (NDis_Rv) and anthropogenic variables, such as the closest distance to the park gate (NDis_Pg); closest distance to the patrol base (NDis_PaB); distance closest to the park road (NDis_Pr) and the distance closest to the park boundary (NDis_Pb) were measured for each of the identified poaching sites.
The measured values of each of the variables, cited above, were used to model the distribution of poached species within the RBP.
We performed all analyses in the statistical programme R v. 3.5.2 (
To assess multi-collinearity into the variables, variance inflation factors (VIF) were examined. This parameter estimates how much the variance of a coefficient is increased due to a linear relationship with other predictors (
We also estimated spatial distribution patterns of poaching sites in the PBR and around waterholes from 2011 to 2017. We used functions from the spatstat package to calculate K statistics to model Monte Carlo envelopes (999 simulations) to test the complete spatial randomness (CSR) hypothesis (
Figure
Only the variable “nearest distance to the main river” (p-value = 0.041) contributed significantly in explaining the poaching incidents (Table
Results of the generalised linear model between poaching incidents locations and predictors.
Parameters | Signs | Coef. | Odds ratio | Robust SE | Pr(> |z|) |
---|---|---|---|---|---|
(Intercept) | - | 1.53945 | 0.19178 | 2.212365 | 0.68366 |
NDis_Wh | - | 0.97483 | 0.92650 | 0.025397 | 0.29987 |
NDis_Rv | - | 0.89485 | 0.79059 | 0.06097 | 0.0410* |
NDis_Pr | - | 0.98852 | 0.89355 | 0.026652 | 0.63059 |
NDis_PaB | + | 1.01985 | 0.95631 | 0.037449 | 0.55261 |
Figure
Our study helped to assess the biophysical or anthropogenic factors predicting the mammal species poaching areas in the western African PAs using poaching data over seven years (2011–2017). In total, we found 14 ungulate species to be mostly poached in the PBR with more poaching occurring in the Park. The study further highlighted the nearest distance to the river as the main driver of the poaching incidents in the PBR. Ripley’s K-function analysis, performed on the mammal species poaching site in the PBR, showed significant random patterns up to 26 km and clusters beyond that. However clustered patterns of the mammal species poaching sites are found extensively in the PBR when considering the waterholes.
The results about the most species poached confirm the work of many authors, notably,
The poaching incidents mapping within Pendjari Biosphere Reserve shows that the high poaching areas are near to the main river and far from the park road, waterholes and patrol base. The high incidence of poaching along the river leads them to conduct repeated main patrols in the area. These results support previous research, such as
Knowledge of the spatial distribution of poaching activities is very important for managers. It will allow them to bring together all the resources suited to the areas of concentration (
Our work has the particularity of having used spatial analysis methods to understand poacher’s behaviour according to the biophysical or anthropogenic factors in the PAs. This study finding is important for ranger deployment and demonstrates the value of a full spatio-temporal analysis. This study could, therefore, form the basis for the formulation of future hypotheses which test the effect of poaching on the wildlife conservation in PAs. Future studies exploring similar hypotheses should include seasonality to understand the temporal patterns of poaching. This will allow better generalisations regarding the incidence of poaching according to the different seasons. Additionally, our findings represent a baseline for any further evaluation of the new management system put in place in PBR by the African Park Network since 2017.
The authors thank the African Wildlife Foundation for funding this study, all the staff members of the Pendjari National Park management office and the Laboratory of Applied Ecology (LEA) for providing help and assistance during the fieldwork.
The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: this study received financial support from the African Wildlife Foundation.