Comparing interview methods with camera trap data to inform occupancy models of hunted mammals in forest habitats

Abstract

Few studies explicitly assess the robustness and practicality of occupancy analysis informed by local inhabitants, compared to estimates from conventional monitoring methods within different contexts. This study evaluates the efficacy and robustness of occupancy models based on camera trap data, and two locally informed methods: seasonal interviews and hunter diaries, for monitoring 13 hunted mammal species in south‐eastern Cameroon. We triangulate estimates of detectability and occupancy to assess the precision and comparability of their estimates for different species, and their cost. Camera trap estimates are comparable with estimates from locally informed methods in 7 of 11 available cases, but produced the lowest detection probabilities for all species in both villages. While camera traps provide robust estimates for abundant species with a high detection probability, locally informed methods can provide estimates of occupancy comparable to camera trap estimates, but at significantly less cost. They are particularly useful where camera trap detection rates (p) are too low to produce robust occupancy model estimates, notably for rare or cryptic species. The methods, survey effort and animals that can be monitored robustly vary between villages. As such, consideration should be given before monitoring commences to ensure that the most effective and informative approach is used.

Perceptions and uses of pangolins (Pholidota) among remote rural communities in the Republic of the Congo: A baseline study from the Odzala‐Kokoua National Park

“…not make conclusions based solely on local knowledge of pangolins, because the use of long-term standard ecological monitoring is needed, possibly in combination with the other methods (Brittain, Rowcliffe, et al, 2022;Willcox et al, 2019). However, just as in the other studies in West and Central Africa (Fopa et al, 2020;Mouafo et al, 2021;, the white-bellied pangolin was reported to be the most observed species.…”

“…Local knowledge of communities can provide a wide range of information about species living in the study area and reflects the need for a collaborative and comprehensive approach to conservation (Archer et al, 2020; Brittain, Rowcliffe, et al, 2022; Fopa et al, 2020; Huntington, 2000; Mouafo et al, 2021). However, species misidentification happens commonly and can largely impact the reliability of data and generate biases (Newing, 2011; Willcox et al, 2019).…”

“…However, species misidentification happens commonly and can largely impact the reliability of data and generate biases (Newing, 2011; Willcox et al, 2019). Due to this, we do not make conclusions based solely on local knowledge of pangolins, because the use of long‐term standard ecological monitoring is needed, possibly in combination with the other methods (Brittain, Rowcliffe, et al, 2022; Ingram, Willcox, & Challender, 2019; Willcox et al, 2019). However, just as in the other studies in West and Central Africa (Fopa et al, 2020; Mouafo et al, 2021; Segniagbeto et al, 2020), the white‐bellied pangolin was reported to be the most observed species.…”

Power to the people: Analysis of occupancy models informed by local knowledge

“…By carrying out occupancy analysis, including both observer-based and environmental variables, we were able to account for variation in both occupancy and detection. This work adds to the growing body of research that combines interviewbased data with occupancy analysis and finds that the results are robust, informative and cost-effective (Brittain et al, 2018;Brittain et al, 2022;Camino et al, 2020;Martínez-Martí et al, 2016). However, some biases cannot be accounted for with occupancy analysis, and must instead be addressed during the survey design and data collection phases.…”

Putting conservation efforts in Central Africa on the right track for interventions that last

“…2. Use the traditional ecological knowledge of local communities to undertake regular monitoring of the status of wild populations and assess whether management plans are indeed providing the predicted sustainability (e.g., Brittain et al, 2022). 3.…”