Listening and watching : do camera traps or acoustic sensors more efficiently detect wild chimpanzees in an open habitat?

This work was supported by the Primate Society of Great Britain through the Cyril Rosen Conservation Grant. Long term funding for ongoing research at Issa is supported by the UCSD/Salk Center for Academic Research and Training in Anthropogeny (CARTA).1.  With one million animal species at risk of extinction, there is an urgent need to regularly monitor threatened species. However, in practice this is challenging, especially with wide‐ranging, elusive and cryptic species or those that occur at low density. 2.  Here we compare two non‐invasive methods, passive acoustic monitoring (n=12) and camera trapping (n=53), to detect chimpanzees (Pan troglodytes) in a savanna‐woodland mosaic habitat at the Issa Valley, Tanzania. With occupancy modelling we evaluate the efficacy of each method, using the estimated number of sampling days needed to establish chimpanzee absence with 95% probability, as our measure of efficacy. 3.  Passive acoustic monitoring was more efficient than camera trapping in detecting wild chimpanzees. Detectability varied over seasons, likely due to social and ecological factors that influence party size and vocalisation rate. The acoustic method can infer chimpanzee absence with less than ten days of recordings in the field during the late dry season, the period of highest detectability, which was five times faster than the visual method. 4.  Synthesis and applications: Despite some technical limitations, we demonstrate that passive acoustic monitoring is a powerful tool for species monitoring. Its applicability in evaluating presence/absence, especially but not exclusively for loud call species, such as cetaceans, elephants, gibbons or chimpanzees provides a more efficient way of monitoring populations and inform conservation plans to mediate species‐loss.PostprintPeer reviewe

Nest grouping patterns of bonobos (Pan paniscus) in relation to fruit availability in a forest-savannah mosaic

A topic of major interest in socio-ecology is the comparison of chimpanzees and bonobos’ grouping patterns. Numerous studies have highlighted the impact of social and environmental factors on the different evolution in group cohesion seen in these sister species. We are still lacking, however, key information about bonobo social traits across their habitat range, in order to make accurate inter-species comparisons. In this study we investigated bonobo social cohesiveness at nesting sites depending on fruit availability in the forest-savannah mosaic of western Democratic Republic of Congo (DRC), a bonobo habitat which has received little attention from researchers and is characterized by high food resource variation within years. We collected data on two bonobo communities. Nest counts at nesting sites were used as a proxy for night grouping patterns and were analysed with regard to fruit availability. We also modelled bonobo population density at the site in order to investigate yearly variation. We found that one community density varied across the three years of surveys, suggesting that this bonobo community has significant variability in use of its home range. This finding highlights the importance of forest connectivity, a likely prerequisite for the ability of bonobos to adapt their ranging patterns to fruit availability changes. We found no influence of overall fruit availability on bonobo cohesiveness. Only fruit availability at the nesting sites showed a positive influence, indicating that bonobos favour food ‘hot spots’ as sleeping sites. Our findings have confirmed the results obtained from previous studies carried out in the dense tropical forests of DRC. Nevertheless, in order to clarify the impact of environmental variability on bonobo social cohesiveness, we will need to make direct observations of the apes in the forest-savannah mosaic as well as make comparisons across the entirety of the bonobos’ range using systematic methodology

Deer Behavior Affects Density Estimates With Camera Traps, but Is Outwighted by Spatial Variability

Density is a key trait of populations and an essential parameter in ecological research, wildlife conservation and management. Several models have been developed to estimate population density based on camera trapping data, including the random encounter model (REM) and camera trap distance sampling (CTDS). Both models need to account for variation in animal behavior that depends, for example, on the species and sex of the animals along with temporally varying environmental factors. We examined whether the density estimates of REM and CTDS can be improved for Europe’s most numerous deer species, by adjusting the behavior-related model parameters per species and accounting for differences in movement speeds between sexes, seasons, and years. Our results showed that bias through inadequate consideration of animal behavior was exceeded by the uncertainty of the density estimates, which was mainly influenced by variation in the number of independent observations between camera trap locations. The neglection of seasonal and annual differences in movement speed estimates for REM overestimated densities of red deer in autumn and spring by ca. 14%. This GPS telemetry-derived parameter was found to be most problematic for roe deer females in summer and spring when movement behavior was characterized by small-scale displacements relative to the intervals of the GPS fixes. In CTDS, density estimates of red deer improved foremost through the consideration of behavioral reactions to the camera traps (avoiding bias of max. 19%), while species-specific delays between photos had a larger effect for roe deer. In general, the applicability of both REM and CTDS would profit profoundly from improvements in their precision along with the reduction in bias achieved by exploiting the available information on animal behavior in the camera trap data.Deer Behavior Affects Density Estimates With Camera Traps, but Is Outwighted by Spatial VariabilitypublishedVersio

Model selection with overdispersed distance sampling data

We thank the Robert Bosch Foundation, the Max Planck Society and the University of St Andrews for funding.1. Distance sampling (DS) is a widely used framework for estimating animal abundance. DS models assume that observations of distances to animals are independent. Non‐independent observations introduce overdispersion, causing model selection criteria such as AIC or AICc to favour overly complex models, with adverse effects on accuracy and precision. 2. We describe, and evaluate via simulation and with real data, estimators of an overdispersion factor (ĉ), and associated adjusted model selection criteria (QAIC) for use with overdispersed DS data. In other contexts, a single value of ĉ is calculated from the “global” model, that is the most highly parameterised model in the candidate set, and used to calculate QAIC for all models in the set; the resulting QAIC values, and associated ΔQAIC values and QAIC weights, are comparable across the entire set. Candidate models of the DS detection function include models with different general forms (e.g. half‐normal, hazard rate, uniform), so it may not be possible to identify a single global model. We therefore propose a two‐step model selection procedure by which QAIC is used to select among models with the same general form, and then a goodness‐of‐fit statistic is used to select among models with different forms. A drawback of thi approach is that QAIC values are not comparable across all models in the candidate set. 3. Relative to AIC, QAIC and the two‐step model selection procedure avoided overfitting and improved the accuracy and precision of densities estimated from simulated data. When applied to six real datasets, adjusted criteria and procedures selected either the same model as AIC or a model that yielded a more accurate density estimate in five cases, and a model that yielded a less accurate estimate in one case. 4. Many DS surveys yield overdispersed data, including cue counting surveys of songbirds and cetaceans, surveys of social species including primates, and camera‐trapping surveys. Methods that adjust for overdispersion during the model selection stage of DS analyses therefore address a conspicuous gap in the DS analytical framework as applied to species of conservation concern.PostprintPeer reviewe

Macaques can contribute to greener practices in oil palm plantations when used as biological pest control

Conversion of tropical forests into oil palm plantations reduces the habitats of many species, including primates, and frequently leads to human–wildlife conflicts. Contrary to the widespread belief that macaques foraging in the forest–oil palm matrix are detrimental crop pests, we show that the impact of macaques on oil palm yield is minor. More importantly, our data suggest that wild macaques have the potential to act as biological pest control by feeding on plantation rats, the major pest for oil palm crops, with each macaque group estimated to reduce rat populations by about 3,000 individuals per year (mitigating annual losses of 112 USD per hectare). If used for rodent control in place of the conventional method of poison, macaques could provide an important ecosystem service and enhance palm oil sustainability

Sustainable protected areas: Synergies between biodiversity conservation and socioeconomic development

1. Reconciling conservation and socioeconomic development goals is key to sus- tainability but remains a source of fierce debate. Protected areas (PAs) are be- lieved to play an essential role in achieving these seemingly conflicting goals. Yet, there is limited evidence as to whether PAs are actually achieving the two goals simultaneously. 2. Here, we investigate when and to what extent synergies or trade- offs between biodiversity conservation and local socioeconomic development occur. To ex- plore these relationships, we collected data across a wide range of socioeco- nomic settings through face-to-face survey with PA managers from 114 African and European PAs using structured questionnaire. 3. We found synergies between biodiversity conservation and socioeconomic development for 62% of the PAs, albeit with significant differences between African (55%) and European PAs (75%). Moreover, the sustainability of PAs in conserving biodiversity was strongly correlated with the empowerment of the PA management and the involvement of local communities in PA planning and decision-making processes. 4. Our results demonstrate that for PAs to promote synergies between biodiver- sity conservation and local socioeconomic development, and to enhance their long-term sustainability, they should invest in the empowerment of their respec- tive management and involvement of local communities in their planning and management activitie

Sustainable protected areas: Synergies between biodiversity conservation and socioeconomic development

1. Reconciling conservation and socioeconomic development goals is key to sustainability but remains a source of fierce debate. Protected areas (PAs) are believed to play an essential role in achieving these seemingly conflicting goals. Yet, there is limited evidence as to whether PAs are actually achieving the two goals simultaneously. 2. Here, we investigate when and to what extent synergies or trade‐offs between biodiversity conservation and local socioeconomic development occur. To explore these relationships, we collected data across a wide range of socioeconomic settings through face‐to‐face survey with PA managers from 114 African and European PAs using structured questionnaire. 3. We found synergies between biodiversity conservation and socioeconomic development for 62% of the PAs, albeit with significant differences between African (55%) and European PAs (75%). Moreover, the sustainability of PAs in conserving biodiversity was strongly correlated with the empowerment of the PA management and the involvement of local communities in PA planning and decision‐making processes. 4. Our results demonstrate that for PAs to promote synergies between biodiversity conservation and local socioeconomic development, and to enhance their long‐term sustainability, they should invest in the empowerment of their respective management and involvement of local communities in their planning and management activities

Predicting Range Shifts of African Apes and Effectiveness of Protected Areas under Global Change Scenarios

First paragraph: Given a burgeoning human population and rapidly-growing global demand for natural resources, reconciling biodiversity conservation and human-related activities is a fundamental challenge. Tropical forests support at least two-thirds of the world's biodiversity, providing important ecosystem services at both global and local scales. However, a decline of 3% in global forest cover was reported between 2010 and 2015, with the highest rates of land-use change and degradation found in the tropics, where deforestation rates exceeded five million hectares per year. Africa had an annual rate of net forest loss at 3.9 million hectares between 2010 and 2020, and has up to 400 million hectares of forest that could potentially be used for agricultural expansion. Therefore, continued widespread expansion of agriculture is likely. Moreover, the African continent is the most vulnerable to the effects of climate change, and future droughts, floods and other extreme weather events will lead to the expansion of agriculture into more humid tropical areas. These areas are where great apes live and are generally high in biodiversity