Bonobo nest site selection and the importance of predictor scales in primate ecology

Decay rates of arboreal and terrestrial nests of Eastern chimpanzees (Pan troglodytes schweinfurthii) in the Bugoma Central Forest Reserve, Uganda: Implications for population size estimates

Chimpanzees were once thought to sleep primarily in the trees, but recent studies indicate that some populations also construct terrestrial night nests. This behavior has relevance not only to understanding the behavioral diversity of Pan troglodytes, but also to the conservation of the species, given that nest encounter rates are often used to estimate great ape population densities. A proper estimate of decay rates for ground nests is necessary for converting the encounter rate of nests to the density of weaned chimpanzees. Here we present the results of the first systematic comparative study between the decay rates of arboreal and terrestrial chimpanzee nests, from the Bugoma Central Forest Reserve in western Uganda. We followed the decay of 56 ground and 51 tree nests in eight nest groups between April 2020 and October 2021. For 15 of the ground and 19 of the tree nests, we collected detailed information on the condition of the nests every two weeks; we checked the remaining 73 nests only twice. On average, ground nests lasted 238 days versus 276 days for tree nests (p = 0.05). Of the 107 total nests surveyed, 51% of tree and 64% of ground nests had disappeared after six months. Based on our results, we propose a modification of the formula used to convert nest density into chimpanzee density. Our results highlight the importance of taking into account potential differences in decay rates between ground versus tree nests, which will likely influence our understanding of the distribution of ground nesting behavior in chimpanzee across tropical Africa, as well as our estimations of the densities of ground nesting populations.

Siland a R package for estimating the spatial influence of landscape

The spatial distributions of populations are both influenced by local variables and by characteristics of surrounding landscapes. Understanding how landscape features spatially structure the frequency of a trait in a population, the abundance of a species or the species' richness remains difficult specially because the spatial scale effects of the landscape variables are unknown. Various methods have been proposed but their results are not easily comparable. Here, we introduce "siland", a general method for analyzing the effect of landscape features. Based on a sequential procedure of maximum likelihood estimation, it simultaneously estimates the spatial scales and intensities of landscape variable effects. It does not require any information about the scale of effect. It integrates two landscape effects models: one is based on focal sample site (Bsiland, b for buffer) and one is distance weighted using Spatial Influence Function (Fsiland, f for function). We implemented "siland" in the adaptable and user-friendly R eponym package. It performs landscape analysis on georeferenced point observations (described in a Geographic Information System shapefile format) and allows for effects tests, effects maps and models comparison. We illustrated its use on a real dataset by the study of a crop pest (codling moth densities).

A description of nesting behaviors, including factors impacting nest site selection, in black-and-white ruffed lemurs (Varecia variegata)

Nest site selection is at once fundamental to reproduction and a poorly understood component of many organisms' reproductive investment. This study investigates the nesting behaviors of black-and-white ruffed lemurs, Varecia variegata, a litter-bearing primate from the southeastern rainforests of Madagascar. Using a combination of behavioral, geospatial, and demographic data, I test the hypotheses that environmental and social cues influence nest site selection and that these decisions ultimately impact maternal reproductive success. Gestating females built multiple large nests throughout their territories. Of these, females used only a fraction of the originally constructed nests, as well as several parking locations as infants aged. Nest construction was best predicted by environmental cues, including the size of the nesting tree and density of feeding trees within a 75 m radius of the nest, whereas nest use depended largely on the size and average distance to feeding trees within that same area. Microhabitat characteristics were unrelated to whether females built or used nests. Although unrelated to nest site selection, social cues, specifically the average distance to conspecifics' nest and park sites, were related to maternal reproductive success; mothers whose litters were parked in closer proximity to others' nests experienced higher infant survival than those whose nests were more isolated. This is likely because nesting proximity facilitated communal crèche use by neighboring females. Together, these results suggest a complex pattern of nesting behaviors that involves females strategically building nests in areas with high potential resource abundance, using nests in areas according to their realized productivity, and communally rearing infants within a network of nests distributed throughout the larger communal territory.

Sleep and nesting behavior in primates: A review

Sleep is a universal behavior in vertebrate and invertebrate animals, suggesting it originated in the very first life forms. Given the vital function of sleep, sleeping patterns and sleep architecture follow dynamic and adaptive processes reflecting trade-offs to different selective pressures. Here, we review responses in sleep and sleep-related behavior to environmental constraints across primate species, focusing on the role of great ape nest building in hominid evolution. We summarize and synthesize major hypotheses explaining the proximate and ultimate functions of great ape nest building across all species and subspecies; we draw on 46 original studies published between 2000 and 2017. In addition, we integrate the most recent data brought together by researchers from a complementary range of disciplines in the frame of the symposium "Burning the midnight oil" held at the 26th Congress of the International Primatological Society, Chicago, August 2016, as well as some additional contributors, each of which is included as a "stand-alone" article in this "Primate Sleep" symposium set. In doing so, we present crucial factors to be considered in describing scenarios of human sleep evolution: (a) the implications of nest construction for sleep quality and cognition; (b) the tree-to-ground transition in early hominids; (c) the peculiarities of human sleep. We propose bridging disciplines such as neurobiology, endocrinology, medicine, and evolutionary ecology, so that future research may disentangle the major functions of sleep in human and nonhuman primates, namely its role in energy allocation, health, and cognition.

Modeling habitat suitability for chimpanzees (Pan troglodytes verus) in the Greater Nimba Landscape, Guinea, West Africa

Tropical forests and the biodiversity within them are rapidly declining in the face of increasing human populations. Resource management and conservation of endangered species requires an understanding of how species perceive and respond to their environments. Species distribution modeling (SDM) is an appropriate tool for identifying conservation areas of concern and importance. In this study, SDM was used to identify areas of suitable chimpanzee (Pan troglodytes verus) habitat within the Greater Nimba Landscape, Guinea, West Africa. This location was ideal for investigating the effects of landscape structure on habitat suitability due to the topographic variation of the landscape and the Critically Endangered status of the Western chimpanzee. Additionally, this is the only mountainous, long-term chimpanzee study site and little is known about the effects of topography on chimpanzee behavior. Suitable habitat was predicted based on the location of direct and indirect signs of chimpanzee presence and the spatial distribution of 12 biophysical variables within the study area. Model performance was assessed by examining the area under the curve. The overall predictive performance of the model was 0.721. The variables most influencing habitat suitability were the normalized difference vegetation index (37.8%), elevation (27.3%), hierarchical slope position (11.5%), surface brightness (6.6%), and distance to rivers (5.4%). The final model highlighted the isolation and fragmentation of chimpanzee habitat within the Greater Nimba Landscape. Understanding the factors influencing chimpanzee habitat suitability, specifically the biophysical variables considered in this study, will greatly contribute to conservation efforts by providing quantitative habitat information and improving survey efficiency.