A simple method for estimating the effective detection distance of camera traps

Estimates of animal abundance are essential for understanding animal ecology. Camera traps can be used to estimate the abundance of terrestrial mammals, including elusive species, provided that the sensitivity of the sensor, estimated as the effective detection distance (EDD), is quantified. Here, we show how the EDD can be inferred directly from camera trap images by placing markers at known distances along the midline of the camera field of view, and then fitting distance-sampling functions to the frequency of animal passage between markers. EDD estimates derived from simulated passages using binned detection distances approximated those obtained from continuous detection distance measurements if at least five intervals were used over the maximum detection distance. A field test of the method in two forest types with contrasting vegetation density, with five markers at 2.5 m intervals, produced credible EDD estimates for 13 forest-dwelling mammals. EDD estimates were positively correlated with species body mass, and were shorter for the denser vegetation, as expected. Our findings suggest that this simple method can produce reliable estimates of EDD. These estimates can be used to correct photographic capture rates for difference in sampling effort resulting from differences in sensor sensitivity between species and habitats. Simplifying the estimation of EDD will result in less biased indices of relative abundance, and will also facilitate the use of camera trap data for estimating animal density

Analysing age structure, residency and relatedness uncovers social network structure in aggregations of young birds

Animal sociality arises from the cumulative effects of both individual social decisions and environmental factors. While juveniles' social interactions with parents prior to independence shape later life sociality, in most bird and mammal species at least one sex undergoes an early life dispersal before first-year reproduction. The social associations from this period could also have implications for later life yet are rarely characterized. Here, we derived predictions from available examples of juvenile groups in the literature (mobile ‘flocks’, spatially stable ‘gangs’ or adult-associated ‘crèches’) and then used three cohorts of juvenile hihi, Notiomystis cincta, a threatened New Zealand passerine, to demonstrate how multistate modelling and social network analysis approaches can be used to characterize group type based on residency, movement, relatedness and social associations. At sites where hihi congregated, we found that juveniles were resighted at a higher frequency than adults and associated predominantly with unrelated juveniles rather than siblings or parents. Movement between group sites occurred, but associations developed predominantly within the sites. We suggest therefore that juvenile hihi social structure is most similar to a ‘gang’, a group structure in which juveniles congregate without adults at predictable sites. Such gangs have previously only been described formally in ravens, Corvus corax. By combining spatial and social network analyses, our study demonstrates how social group structures can be described and therefore facilitate broader comparisons and discussion about the form and function of juvenile groups across taxa

The impacts of human activity on mammals in a community forest near the Dja Biosphere Reserve in Cameroon

Human activity in African tropical rainforests continues to threaten wild mammals. Many rural communities are dependent on hunting, yet there is a widespread lack of baseline data on ecology and the sustainability of hunting. We investigated the impacts of human activity on mammal species composition and distributions within a community forest surrounding a village in the buffer zone of the Dja Biosphere Reserve in south-east Cameroon. We conducted a camera-trap survey in August–November 2017 and detected 24 mammal species, including Critically Endangered western lowland gorilla Gorilla gorilla gorilla, Endangered central African chimpanzee Pan troglodytes troglodytes and Endangered tree pangolin Phataginus tricuspis. We used occupancy analysis to explore relationships between indicators of human activity (distance to a road and the Reserve), habitat quality (distance to the river and tree cover) and the distributions of species. We found that the local distribution of threatened mammals was not apparently limited by human activity, and proximity to the road did not negatively influence occupancy for any species. However, most of the Reserve's large species were not detected, including the African forest elephant Loxodonta cyclotis and the largest ungulates, and the occupancy of two species commonly hunted for wild meat was positively correlated with distance from the village, indicating hunting may be unsustainable. Our results show that the community forest provides habitat for threatened species outside the Reserve and in close proximity to people. However, effective conservation management will require continued monitoring and research to determine whether current rates of hunting are sustainable

Revealing kleptoparasitic and predatory tendencies in an African mammal community using camera traps: a comparison of spatiotemporal approaches

Camera trap data are increasingly being used to characterise relationships between the spatiotemporal activity patterns of sympatric mammal species, often with a view to inferring inter-specific interactions. In this context, we attempted to characterise the kleptoparasitic and predatory tendencies of spotted hyaenas Crocuta crocuta and lions Panthera leo from photographic data collected across 54 camera trap stations and two dry seasons in Tanzania's Ruaha National Park. We applied four different methods of quantifying spatiotemporal associations, including one strictly temporal approach (activity pattern overlap), one strictly spatial approach (co-occupancy modelling), and two spatiotemporal approaches (co-detection modelling and temporal spacing at shared camera trap sites). We expected a kleptoparasitic relationship between spotted hyaenas and lions to result in a positive spatiotemporal association, and further hypothesised that the association between lions and their favourite prey in Ruaha, the giraffe Giraffa camelopardalis and the zebra Equus quagga, would be stronger than those observed with non-preferred prey species (the impala Aepyceros melampus and the dikdik Madoqua kirkii). Only approaches incorporating both the temporal and spatial components of camera trap data resulted in significant associative patterns. The latter were particularly sensitive to the temporal resolution chosen to define species detections (i.e. occasion length), and only revealed a significant positive association between lion on spotted hyaena detections, as well as a tendency for both species to follow each other at camera trap sites, during the dry season of 2013, but not that of 2014. In both seasons, observed spatiotemporal associations between lions and each of the four herbivore species considered provided no convincing or consistent indications of any predatory preferences. Our study suggests that, when making inferences on inter-specific interactions from camera trap data, due regards should be given to the potential behavioural and methodological processes underlying observed spatiotemporal patterns

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

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

Remote sensing and the UN Ocean Decade: high expectations, big opportunities

This year officially marks the beginning of the United Nations Decade of Ocean Science for Sustainable Development (2021–2030)—the Ocean Decade. A primary objective of this coordination framework is to support scientific research and technological developments that can contribute to the conservation and sustainable management of the world’s oceans. One of the seven Decade Outcomes is to secure healthy and resilient oceans where marine biodiversity is mapped and protected; however, fulfilling this goal will require data, knowledge, and technology. The use of remote sensing is now established in marine research and management and is crucial in developing our understanding of ocean patterns and processes at multiple spatial and temporal scales (e.g., Jawak et al., 2015). As such, remote sensing technology is expected to play a critical role in achieving the vision set by the Ocean Decade