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

Addressing environmental and atmospheric challenges for capturing high-precision thermal infrared data in the field of astro-ecology

Using thermal infrared detectors mounted on drones, and applying techniques from astrophysics, we hope to support the field of conservation ecology by creating an automated pipeline for the detection and identification of certain endangered species and poachers from thermal infrared data. We test part of our system by attempting to detect simulated poachers in the field. Whilst we find that we can detect humans hiding in the field in some types of terrain, we also find several environmental factors that prevent accurate detection, such as ambient heat from the ground, absorption of infrared emission by the atmosphere, obscuring vegetation and spurious sources from the terrain. We discuss the effect of these issues, and potential solutions which will be required for our future vision for a fully automated drone-based global conservation monitoring system.Comment: Published in Proceedings of SPIE Astronomical Telescopes and Instrumentation 2018. 8 pages, 3 figure

A chimpanzee’s time to feast: seasonality of Macrotermes flight hole activity and alate dispersal flights detected by termite-fishing experiments and camera traps in the Issa Valley, Tanzania

Introduction: Investigation into chimpanzee termite-fishing behavior has provided invaluable insights into the evolution of animal tool use and culture. However, research to date often overlooks how the ecology of termites may shape the nature of this predator–prey interaction. Though anecdotal links between meteorological factors, termite dispersal flights and the ability of chimpanzees to termite-fish have been made, these relationships were never empirically tested. In this study, we examined if and how the reproductive ecology of mound building termites (Macrotermes subhyalinus) affects the availability of this resource to termite-fishing chimpanzees in the Issa Valley, Tanzania. // Methods: We utilized in-person termite-fishing experiments, remote camera trap footage, as well as meteorological data to model both the availability of termite prey across seasons for chimpanzees as well as the timing of dispersal flights of the termite reproductive caste (alates). Additionally, we describe the predator diversity that characterizes alate swarming events during their seasonal dispersal flights. // Results: We identify strong relationships between meteorological factors, Macrotermes alate dispersal flights and vulnerability of the colony to predation. As rainfall accumulates, Macrotermes become more abundant in their flight holes and are thus more vulnerable to researcher termite-fishing experiments. This increased accessibility to Macrotermes continues until alate dispersal flights which we also find are linked to cumulative rainfall as well as negatively correlated to wind speed. // Discussion: This type of baseline data on Macrotermes ecology is fundamental when forming hypotheses and designing studies into topics such as chimpanzee culture, tool-use, and foraging cognition

A case of intercommunity lethal aggression by chimpanzees in an open and dry landscape, Issa Valley, western Tanzania

Intercommunity (lethal) aggression is a familiar component of the behavioural repertoire of many forest-dwelling chimpanzee (Pan troglodytes) communities. However, until now, the absence of intercommunity attacks - including killings - in communities that live in open, mosaic environments has supported hypotheses of reduced resource competition in drier habitats, and informed referential models of early hominin social dynamics in a similar habitat. In June 2020, we observed the first instance of intercommunity lethal aggression, a male-committed infanticide, by the Issa chimpanzee community, which live in a savannah-mosaic habitat in the Issa Valley, western Tanzania. The carcass was recovered by researchers after it was abandoned by the attackers. Here, we give a detailed account of the events leading up to and including the infanticide, and contextualise our observations with what has been described for other chimpanzee communities. Notably, in contrast to the majority of reported intercommunity infanticides, the infant male victim was castrated (and not cannibalised), making this the youngest reported castration. This observation of intercommunity aggression disproves its hypothesised absence in savannah-dwelling chimpanzees, which by extension, has implications for early hominin evolution. We suggest that the near absence of observations of intercommunity aggression in savannah chimpanzee communities is most likely due to the lack of long-term study communities, and in some cases geographic isolation. We hypothesise that food-rich areas within a habitat with otherwise widely distributed food sources may select for intense intercommunity aggression despite the low population density characteristic of savannah communities. Anecdotes such as this add to the comparative database available on intercommunity killings in chimpanzee society, improving our ability to draw inferences about their evolutionary significance

Understanding External Influences on Target Detection and Classification Using Camera Trap Images and Machine Learning

Using machine learning (ML) to automate camera trap (CT) image processing is advantageous for time-sensitive applications. However, little is currently known about the factors influencing such processing. Here, we evaluate the influence of occlusion, distance, vegetation type, size class, height, subject orientation towards the CT, species, time-of-day, colour, and analyst performance on wildlife/human detection and classification in CT images from western Tanzania. Additionally, we compared the detection and classification performance of analyst and ML approaches. We obtained wildlife data through pre-existing CT images and human data using voluntary participants for CT experiments. We evaluated the analyst and ML approaches at the detection and classification level. Factors such as distance and occlusion, coupled with increased vegetation density, present the most significant effect on DP and CC. Overall, the results indicate a significantly higher detection probability (DP), 81.1%, and correct classification (CC) of 76.6% for the analyst approach when compared to ML which detected 41.1% and classified 47.5% of wildlife within CT images. However, both methods presented similar probabilities for daylight CT images, 69.4% (ML) and 71.8% (analysts), and dusk CT images, 17.6% (ML) and 16.2% (analysts), when detecting humans. Given that users carefully follow provided recommendations, we expect DP and CC to increase. In turn, the ML approach to CT image processing would be an excellent provision to support time-sensitive threat monitoring for biodiversity conservation

Wild chimpanzee behavior suggests that a savanna-mosaic habitat did not support the emergence of hominin terrestrial bipedalism

Bipedalism, a defining feature of the human lineage, is thought to have evolved as forests retreated in the late Miocene-Pliocene. Chimpanzees living in analogous habitats to early hominins offer a unique opportunity to investigate the ecological drivers of bipedalism that cannot be addressed via the fossil record alone. We investigated positional behavior and terrestriality in a savanna-mosaic community of chimpanzees (Pan troglodytes schweinfurthii) in the Issa Valley, Tanzania as the first test in a living ape of the hypothesis that wooded, savanna habitats were a catalyst for terrestrial bipedalism. Contrary to widely accepted hypotheses of increased terrestriality selecting for habitual bipedalism, results indicate that trees remained an essential component of the hominin adaptive niche, with bipedalism evolving in an arboreal context, likely driven by foraging strategy

Anthropogenic disturbance and chimpanzee (Pan troglodytes) habitat use in the Masito-Ugalla Ecosystem, Tanzania

This research article published by the American Society of Mammalogists, 2020The habitat quality of chimpanzee (Pan troglodytes), including the availability of plant food and nesting species, is important to ensure the long-term survival of this endangered species. Botanical composition of vegetation is spatially variable and depends on soil characteristics, weather, topography, and numerous other biotic and abiotic factors. There are few data regarding the availability of chimpanzee plant food and nesting species in the Masito-Ugalla Ecosystem (MUE), a vast area that lies outside national park boundaries in Tanzania, and how the availability of these resources varies with human disturbance. We hypothesized that chimpanzee plant food species richness, diversity, and abundance decline with increasing human disturbance. Further, we predicted that chimpanzee abundance and habitat use is influenced negatively by human disturbance. Published literature from Issa Valley, Gombe, and Mahale Mountains National Parks, in Tanzania, was used to document plant species consumed by chimpanzees, and quantify their richness, diversity, and abundance, along 32 transects totaling 63.8 km in length across four sites of varying human disturbance in MUE. We documented 102 chimpanzee plant food species and found a significant difference in their species richness (H = 55.09, P 0.964). The least disturbed site exhibited the highest encounter rate of chimpanzee nests/km, with rates declining toward the highly disturbed sites. Our results show that severe anthropogenic disturbance in MUE is associated with the loss of chimpanzee plant food species and negatively influences chimpanzee habitat use, a relationship that threatens the future of all chimpanzee populations outside national parks

Using Drones to Determine Chimpanzee Absences at the Edge of Their Distribution in Western Tanzania

Effective species conservation management relies on detailed species distribution data. For many species, such as chimpanzees (Pan troglodytes), distribution data are collected during ground surveys. For chimpanzees, such ground surveys usually focus on detection of the nests they build instead of detection of the chimpanzees themselves due to their low density. However, due to the large areas they still occur in, such surveys are very costly to conduct and repeat frequently to monitor populations over time. Species distribution models are more accurate if they include presence as well as absence data. Earlier studies used drones to determine chimpanzee presence using nests. In this study, therefore, we explored the use of drones to determine the absence of chimpanzee nests in areas we flew over on the edge of the chimpanzee distribution in western Tanzania. We conducted 13 flights with a fixed-wing drone and collected 3560 images for which manual inspection took 180 h. Flights were divided into a total of 746 25 m2 plots for which we determined the absence probability of nests. In three flights, we detected nests, in eight, absence was assumed based on a 95% probability criterion, and in two flights, nest absence could not be assumed. Our study indicates that drones can be used to cover relatively large areas to determine the absence of chimpanzees. To fully benefit from the usage of drones to determine the presence and absence of chimpanzees, it is crucial that methods are developed to automate nest detection in images

Spatio-temporal changes in chimpanzee density and abundance in the Greater Mahale Ecosystem, Tanzania

Authors would like to acknowledge the Arcus Foundation, Jane Goodall Institute, United States Agency for International Development (USAID), National Aeronautics and Space Administration (NASA), The Nature Conservancy, and Frankfurt Zoological Society for supporting, facilitating, and funding this work.Species conservation and management require reliable information about animal distribution and population size. Better management actions within a species' range can be achieved by identifying the location and timing of population changes. In the Greater Mahale Ecosystem (GME), western Tanzania, deforestation due to the expansion of human settlements and agriculture, annual burning, and logging are known threats to wildlife. For one of the most charismatic species, the Endangered eastern chimpanzee (Pan troglodytes schweinfurthii), about 75% of the individuals are distributed outside national park boundaries, requiring monitoring and protection efforts over a vast landscape of various protection statuses. These efforts are especially challenging when we lack data on trends in density and population size. To predict spatio-temporal chimpanzee density and abundance across the GME, we employed density surface modelling, fitting a generalised additive model to a ten-year time series data set of nest counts based on line transect surveys. Chimpanzee population declined at an annual rate of 2.41%, including declines of 1.72% in riparian forests (hereafter forests), 2.05% in miombo-woodlands (hereafter woodlands) and 3.45% in non-forests. These population declines were accompanied by ecosystem-wide declines in vegetation types of 1.36% and 0.32% per year for forests and woodlands, respectively; we estimated an annual increase of 1.35% for non-forests. Our model predicted the highest chimpanzee density in forests (0.86 chimpanzees/km2, 95% CI 0.60-1.23; as of 2020), followed by woodlands (0.19, 95% CI 0.12-0.30) and non-forests (0.18, 95% CI 0.10-1.33). Although forests represent only 6% of the landscape, they support nearly a quarter of the chimpanzee population (769 chimpanzees, 95% CI 536-1,103). Woodlands dominate the landscape (71%) and thus support more than a half of the chimpanzee population (2,294; 95% CI 1,420-3,707). The remaining quarter of the landscape is represented by non-forests and supports another quarter of the chimpanzee population (750; 95% CI 408-1,381). Given the pressures on the remaining suitable habitat in Tanzania and the need of chimpanzees to access both forest and woodland vegetation to survive, we urge future management actions to increase resources and expand the efforts to protect critical forest and woodland habitat and promote strategies and policies that more effectively prevent irreversible losses. We suggest that regular monitoring programmes implement a systematic random design to effectively inform and allocate conservation actions and facilitate inter-annual comparisons for trend-monitoring, measuring conservation success and guiding adaptive management.Publisher PDFPeer reviewe