Adapting astronomical source detection software to help detect animals in thermal images obtained by unmanned aerial systems

In this paper we describe an unmanned aerial system equipped with a thermal-infrared camera and software pipeline that we have developed to monitor animal populations for conservation purposes. Taking a multi-disciplinary approach to tackle this problem, we use freely available astronomical source detection software and the associated expertise of astronomers, to efficiently and reliably detect humans and animals in aerial thermal-infrared footage. Combining this astronomical detection software with existing machine learning algorithms into a single, automated, end-to-end pipeline, we test the software using aerial video footage taken in a controlled, field-like environment. We demonstrate that the pipeline works reliably and describe how it can be used to estimate the completeness of different observational datasets to objects of a given type as a function of height, observing conditions etc. - a crucial step in converting video footage to scientifically useful information such as the spatial distribution and density of different animal species. Finally, having demonstrated the potential utility of the system, we describe the steps we are taking to adapt the system for work in the field, in particular systematic monitoring of endangered species at National Parks around the world

Orangutans venture out of the rainforest and into the Anthropocene

Conservation benefits from understanding how adaptability and threat interact to determine a taxon’s vulnerability. Recognizing how interactions with humans have shaped taxa such as the critically endangered orangutan (Pongo spp.) offers insights into this relationship. Orangutans are viewed as icons of wild nature, and most efforts to prevent their extinction have focused on protecting minimally disturbed habitat, with limited success. We synthesize fossil, archeological, genetic, and behavioral evidence to demonstrate that at least 70,000 years of human influence have shaped orangutan distribution, abundance, and ecology and will likely continue to do so in the future. Our findings indicate that orangutans are vulnerable to hunting but appear flexible in response to some other human activities. This highlights the need for a multifaceted, landscape-level approach to orangutan conservation that leverages sound policy and cooperation among government, private sector, and community stakeholders to prevent hunting, mitigate human-orangutan conflict, and preserve and reconnect remaining natural forests. Broad cooperation can be encouraged through incentives and strategies that focus on the common interests and concerns of different stakeholders. Orangutans provide an illustrative example of how acknowledging the long and pervasive influence of humans can improve strategies to preserve biodiversity in the Anthropocene

High-resolution global map of smallholder and industrial closed-canopy oil palm plantations

Oil seed crops, especially oil palm, are among the most rapidly expanding agricultural land uses, and their expansion is known to cause significant environmental damage. Accordingly, these crops often feature in public and policy debates which are hampered or biased by a lack of accurate information on environmental impacts. In particular, the lack of accurate global crop maps remains a concern. Recent advances in deep-learning and remotely sensed data access make it possible to address this gap. We present a map of closed-canopy oil palm (Elaeis guineensis) plantations by typology (industrial versus smallholder plantations) at the global scale and with unprecedented detail (10 m resolution) for the year 2019. The DeepLabv3+ model, a convolutional neural network (CNN) for semantic segmentation, was trained to classify Sentinel-1 and Sentinel-2 images onto an oil palm land cover map. The characteristic backscatter response of closed-canopy oil palm stands in Sentinel-1 and the ability of CNN to learn spatial patterns, such as the harvest road networks, allowed the distinction between industrial and smallholder plantations globally (overall accuracy =98.52±0.20 %), outperforming the accuracy of existing regional oil palm datasets that used conventional machine-learning algorithms. The user's accuracy, reflecting commission error, in industrial and smallholders was 88.22 ± 2.73 % and 76.56 ± 4.53 %, and the producer's accuracy, reflecting omission error, was 75.78 ± 3.55 % and 86.92 ± 5.12 %, respectively. The global oil palm layer reveals that closed-canopy oil palm plantations are found in 49 countries, covering a mapped area of 19.60 Mha; the area estimate was 21.00 ± 0.42 Mha (72.7 % industrial and 27.3 % smallholder plantations). Southeast Asia ranks as the main producing region with an oil palm area estimate of 18.69 ± 0.33 Mha or 89 % of global closed-canopy plantations. Our analysis confirms significant regional variation in the ratio of industrial versus smallholder growers, but it also confirms that, from a typical land development perspective, large areas of legally defined smallholder oil palm resemble industrial-scale plantings. Since our study identified only closed-canopy oil palm stands, our area estimate was lower than the harvested area reported by the Food and Agriculture Organization (FAO), particularly in West Africa, due to the omission of young and sparse oil palm stands, oil palm in nonhomogeneous settings, and semi-wild oil palm plantations. An accurate global map of planted oil palm can help to shape the ongoing debate about the environmental impacts of oil seed crop expansion, especially if other crops can be mapped to the same level of accuracy. As our model can be regularly rerun as new images become available, it can be used to monitor the expansion of the crop in monocultural settings. The global oil palm layer for the second half of 2019 at a spatial resolution of 10 m can be found at https://doi.org/10.5281/zenodo.4473715 (Descals et al., 2021)

Grouping behavior of Sumatran orangutans (Pongo abelii) and Tapanuli orangutans (Pongo tapanuliensis) living in forest with low fruit abundance

In contrast to the African great apes, orangutans (Pongo spp.) are semisolitary: Individuals are often on their own, but form aggregations more often than expected by chance. These temporary aggregations provide social benefits such as mating opportunities. When fruit availability is high, costs of aggregating should be lower, because competition is less pronounced. Therefore, average party size is expected to be higher when fruit availability is high. This hypothesis would also explain why orangutans in highly fruit‐productive habitats on Sumatra are more gregarious than in the usually less productive habitats of Borneo. Here, we describe the aggregation behavior of orangutans in less productive Sumatran habitats (Sikundur and Batang Toru), and compare results with those of previously surveyed field sites. Orangutans in Sikundur were more likely to form parties when fruit availability was higher, but the size of daily parties was not significantly affected by fruit availability. With regard to between‐site comparisons, average party sizes of females and alone time of parous females in Sikundur and Batang Toru were substantially lower than those for two previously surveyed Sumatran sites, and both fall in the range of values for Bornean sites. Our results indicate that the assessment of orangutans on Sumatra as being more social than those on Borneo needs revision. Instead, between‐site differences in sociality seem to reflect differences in average fruit availability

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

Forest Fruit Production Is Higher on Sumatra Than on Borneo

BACKGROUND: Various studies have shown that the population densities of a number of forest vertebrates, such as orangutans, are higher on Sumatra than Borneo, and that several species exhibit smaller body sizes on Borneo than Sumatra and mainland Southeast Asia. It has been suggested that differences in forest fruit productivity between the islands can explain these patterns. Here we present a large-scale comparison of forest fruit production between the islands to test this hypothesis. METHODOLOGY/PRINCIPAL FINDINGS: Data on fruit production were collated from Sumatran and Bornean sites. At six sites we assessed fruit production in three forest types: riverine, peat swamp and dryland forests. We compared fruit production using time-series models during different periods of overall fruit production and in different tree size classes. We examined overall island differences and differences specifically for fruiting period and tree size class. The results of these analyses indicate that overall the Sumatran forests are more productive than those on Borneo. This difference remains when each of the three forest types (dryland, riverine, and peat) are examined separately. The difference also holds over most tree sizes and fruiting periods. CONCLUSIONS/SIGNIFICANCE: Our results provide strong support for the hypothesis that forest fruit productivity is higher on Sumatra than Borneo. This difference is most likely the result of the overall younger and more volcanic soils on Sumatra than Borneo. These results contribute to our understanding of the determinants of faunal density and the evolution of body size on both islands

Distribution and conservation status of the orang-utan (Pongo spp.) on Borneo and Sumatra: how many remain?

In recognition of the fact that orang-utans (Pongo spp.) are severely threatened, a meeting of orang-utan experts and conservationists, representatives of national and regional governmental and non-governmental organizations, and other stakeholders, was convened in Jakarta, Indonesia, in January 2004. Prior to this meeting we surveyed all large areas for which orang-utan population status was unknown. Compilation of all survey data produced a comprehensive picture of orang-utan distribution on both Borneo and Sumatra. These results indicate that in 2004 there were c. 6,500 P. abelii remaining on Sumatra and at least 54,000 P. pygmaeus on Borneo. Extrapolating to 2008 on the basis of forest loss on both islands suggests the estimate for Borneo could be 10% too high but that for Sumatra is probably still relatively accurate because forest loss in orang-utan habitat has been low during the conflict in Aceh, where most P. abelii occur. When those population sizes are compared to known historical sizes it is clear that the Sumatran orang-utan is in rapid decline, and unless extraordinary efforts are made soon, it could become the first great ape species to go extinct. In contrast, our results indicate there are more and larger populations of Bornean orang-utans than previously known. Although these revised estimates for Borneo are encouraging, forest loss and associated loss of orang-utans are occurring at an alarming rate, and suggest that recent reductions of Bornean orang-utan populations have been far more severe than previously supposed. Nevertheless, although orang-utans on both islands are under threat, we highlight some reasons for cautious optimism for their long-term conservatio

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

Effects of anthropogenic disturbance on group densities of Thomas' langurs (Presbytis thomasi) within a lowland tropical forest, north Sumatra

Ecosystems around the globe are facing irreversible impacts due to climate change, habitat destruction, hunting, and an ever-increasing human population. Estimating densities of species across their geographical range helps us to understand natural variation and anthropogenic effects on species densities and to assess the effectiveness of existing conservation measures. Various methods have been used to produce accurate and precise population density estimates, each with associated limitations. Acoustic surveys for species producing loud calls have become common due to their ease of use, low cost, and reduced timescale. Relative to many other mammal taxa, primate species have been studied extensively, producing a wealth of data on socioecology and behavior, but for most species, density estimates over large geographical ranges are still lacking. We used an acoustic spatial capture–recapture model to estimate group density of unhabituated Thomas' langurs (Presbytis thomasi), a primate endemic to the Indonesian island of Sumatra, over a 60 km2 area of lowland dipterocarp forest. We then assessed if vegetation structure and distance from human habitation affected density estimates. Estimates of group density differed almost threefold between survey locations (from 2.79 to 8.08 groups/km2); there was no clear relationship with forest structure, but there was a significantly positive relationship between group density and distance from human habitation, with an increase of 0.38 groups/km2 for every km of distance. Although large-scale logging within the Sikundur region ceased ~30 years ago, the impacts of logging continue to have detrimental effects on the species within the area