Birds of Gunung Leuser National Park, Northern Sumatra – Part 2

Gunung Leuser National Park (GLNP) in northern Sumatra has over 85% of Sumatra5 resident breeding bird species and important populations of globally threatened mammals such as Sumatran orangutan Pongo abelii and Sumatran rhinoceros Dicerorhinus sumatrensis. Information is here presented on a number of important bird records from GLNP from March 1995 to December 2000. These records include: 23 new species for the park, seven globally threatened species, and several species for which there are few previous records for Sumatra. An appendix lists the 413 species recorded in GLNP comprising records from previous publications (van Marle &: Voous 1988; Holmes 1996; Wind 1996a) and the new records included here

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

Ape Population Abundance Estimates

This annex presents ape abundance estimates at the site level. The term “site” refers to a protected area and its buffer zone, a logging concession or group of concessions, or any discrete area where a survey has taken place in the past two decades, although this annex also lists a few sites that were last surveyed in the 1970s and 1980s.Output Type: Online-only anne

Acoustic models of orangutan hand-assisted alarm calls

B.d.B. was funded by the European research council starting grant ABACUS project and the Innoviris ‘Brains back to Brussels’ programme. S.A.W. was funded by the Netherlands Organisation for Scientific Research NWO. A.R.L. was funded by the Menken Funds (University of Amsterdam).Orangutans produce alarm calls called kiss-squeaks, which they sometimes modify by putting a hand in front of their mouth. Through theoretical models and observational evidence, we show that using the hand when making a kiss-squeak alters the acoustics of the production in such a way that more formants per kilohertz are produced. Our theoretical models suggest that cylindrical wave propagation is created with the use of the hand and face as they act as a cylindrical extension of the lips. The use of cylindrical wave propagation in animal calls appears to be extremely rare, but is an effective way to lengthen the acoustic system; it causes the number of resonances per kilohertz to increase. This increase is associated with larger animals, and thus using the hand in kiss-squeak production may be effective in exaggerating the size of the producer. Using the hand appears to be a culturally learned behavior, and therefore orangutans may be able to associate the acoustic effect of using the hand with potentially more effective deterrence of predators.Publisher PDFPeer reviewe

Terrestrial Megafauna Response to Drone Noise Levels in Ex Situ Areas

Drone use has significantly grown in recent years, and there is a knowledge gap on how the noise produced by these systems may affect animals. We investigated how 18 species of megafauna reacted to drone sound pressure levels at different frequencies. The sound pressure level on the low frequency generated by the drone did not change the studied species’ behavior, except for the Asian elephant. All other studied species showed higher noise sensitivity at medium and high frequencies. The Asian elephant was the most sensitive species to drone noise, mainly at low frequencies. Felines supported the highest sound pressure level before showing behavioral reactions. Our results suggest that drone sound pressure levels in different frequencies cause behavioral changes that differ among species, which is relevant to assessing drone disturbances in ex situ environments. The findings presented here can help to reduce drone impact for target species and serve as an experimental study for future drone use guidelines.M.M.P. contract is funded by the European Union “NextGenerationEU” Programa María Zambrano, Ministerio de Universidades, Spain. Fundación Barcelona Zoo, 310557 Project (Ayuntamiento de Barcelona)

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

Mapping orangutan habitat and agricultural areas using Landsat OLI imagery augmented with unmanned aircraft system aerial photography

Conservation of the Sumatran orangutans’ (Pongo abelii) habitat is threatened by change in land use/land cover (LULCC), due to the logging of its native primary forest habitat, and the primary forest conversion to oil palm, rubber tree, and coffee plantations. Frequent LULCC monitoring is vital to rapid conservation interventions. Due to the costs of high-resolution satellite imagery, researchers are forced to rely on cost-free sources (e.g. Landsat), those, however, provide images at a moderate-to-low resolution (e.g. 15–250 m), permitting identification only general LULC classes, and limit the detection of small-scale deforestation or degradation. Here, we combine Landsat imagery with very high-resolution imagery obtained from an unmanned aircraft system (UAS). ​The UAS imagery was used as ‘drone truthing’ data to train image classification algorithms. Our results show that UAS data can successfully be used to help discriminate similar land-cover/use classes (oil palm plantation vs. reforestation vs. logged forest) with consistently high identification of over 75% on the generated thematic map, where the oil palm detection rate was as high as 89%. Because UAS is employed increasingly in conservation projects, this approach can be used in a large variety of them to improve land-cover classification or aid-specific mapping needs

Speech-like rhythm in a voiced and voiceless orangutan call

A.R.L. thanks the Menken Funds of the University of Amsterdam.The evolutionary origins of speech remain obscure. Recently, it was proposed that speech derived from monkey facial signals which exhibit a speech-like rhythm of ∼5 open-close lip cycles per second. In monkeys, these signals may also be vocalized, offering a plausible evolutionary stepping stone towards speech. Three essential predictions remain, however, to be tested to assess this hypothesis' validity; (i) Great apes, our closest relatives, should likewise produce 5Hz-rhythm signals, (ii) speech-like rhythm should involve calls articulatorily similar to consonants and vowels given that speech rhythm is the direct product of stringing together these two basic elements, and (iii) speech-like rhythm should be experience-based. Via cinematic analyses we demonstrate that an ex-entertainment orangutan produces two calls at a speech-like rhythm, coined "clicks" and "faux-speech." Like voiceless consonants, clicks required no vocal fold action, but did involve independent manoeuvring over lips and tongue. In parallel to vowels, faux-speech showed harmonic and formant modulations, implying vocal fold and supralaryngeal action. This rhythm was several times faster than orangutan chewing rates, as observed in monkeys and humans. Critically, this rhythm was seven-fold faster, and contextually distinct, than any other known rhythmic calls described to date in the largest database of the orangutan repertoire ever assembled. The first two predictions advanced by this study are validated and, based on parsimony and exclusion of potential alternative explanations, initial support is given to the third prediction. Irrespectively of the putative origins of these calls and underlying mechanisms, our findings demonstrate irrevocably that great apes are not respiratorily, articulatorilly, or neurologically constrained for the production of consonant- and vowel-like calls at speech rhythm. Orangutan clicks and faux-speech confirm the importance of rhythmic speech antecedents within the primate lineage, and highlight potential articulatory homologies between great ape calls and human consonants and vowels.Publisher PDFPeer reviewe

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