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

Sex-Segregated Range Use by Black-and-White Ruffed Lemurs (Varecia variegata) in Ranomafana National Park, Madagascar

Ranging behavior is one important strategy by which nonhuman primates obtain access to resources critical to their biological maintenance and reproductive success. As most primates live in permanent social groups, their members must balance the benefits of group living with the costs of intragroup competition for resources. However, some taxa live in more spatiotemporally flexible social groups, whose members modify patterns of association and range use as a method to mitigate these costs. Here, we describe the range use of one such taxon, the black-and-white ruffed lemur (Varecia variegata), at an undisturbed primary rain forest site in Ranomafana National Park, Madagascar, and characterize sex differences in annual home range area, overlap, and daily distances traveled. Moreover, we characterize seasonal variability in range use and ask whether ranging behaviors can be explained by either climatic or reproductive seasonality. We found that females used significantly larger home ranges than males, though sexes shared equal and moderate levels of home range overlap. Overall, range use did not vary across seasons, although within sexes, male range use varied significantly with climate. Moreover, daily path length was best predicted by day length, female reproductive state, and sex, but was unrelated to climate variables. While the patterns of range use and spatial association presented here share some similarities with “bisexually bonded” community models described for chimpanzees, we argue that ruffed lemurs best conform to a “nuclear neighborhood” community model wherein nuclear (core) groups share the highest levels of home range overlap, and where these groups cluster spatially into adjacent “neighborhoods” within the larger, communally defended territory

2009 Annual Meeting of the American Society of Primatologists

No abstract.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/64333/1/20230_ftp.pd

Exposing the human nude phenotype [4]

Peer reviewedSubmitted Versio

Leveraging open hardware to alleviate the burden of COVID-19 on global health systems.

With the current rapid spread of COVID-19, global health systems are increasingly overburdened by the sheer number of people that need diagnosis, isolation and treatment. Shortcomings are evident across the board, from staffing, facilities for rapid and reliable testing to availability of hospital beds and key medical-grade equipment. The scale and breadth of the problem calls for an equally substantive response not only from frontline workers such as medical staff and scientists, but from skilled members of the public who have the time, facilities and knowledge to meaningfully contribute to a consolidated global response. Here, we summarise community-driven approaches based on Free and Open Source scientific and medical Hardware (FOSH) as well as personal protective equipment (PPE) currently being developed and deployed to support the global response for COVID-19 prevention, patient treatment and diagnostics

Learning at the Interstices; Locating Practical Philosophies for Understanding Physical/virtual Inter-spaces

Virtual worlds are relatively recent developments, and so it is tempting to believe that they need to be understood through newly developed theories and philosophies. However, humans have long thought about the nature of reality and what it means to be “real.” This paper examines the three persistent philosophical concepts of Metaxis, Liminality and Space that have evolved across more than 2000 years of meditation, contemplation and reflection. Our particular focus here is on the nature of the interface between the virtual and the physical: at the interstices, and how the nature of transactions and transitions across those interfaces may impact upon learning. This may, at first, appear to be an esoteric pursuit, but we ground our arguments in primary and secondary data from research studies in higher education

LemurFaceID: a face recognition system to facilitate individual identification of lemurs

Background: Long-term research of known individuals is critical for understanding the demographic and evolutionary processes that influence natural populations. Current methods for individual identification of many animals include capture and tagging techniques and/or researcher knowledge of natural variation in individual phenotypes. These methods can be costly, time-consuming, and may be impractical for larger-scale, populationlevel studies. Accordingly, for many animal lineages, long-term research projects are often limited to only a few taxa. Lemurs, a mammalian lineage endemic to Madagascar, are no exception. Long-term data needed to address evolutionary questions are lacking for many species. This is, at least in part, due to difficulties collecting consistent data on known individuals over long periods of time. Here, we present a new method for individual identification of lemurs (LemurFaceID). LemurFaceID is a computer-assisted facial recognition system that can be used to identify individual lemurs based on photographs. Results: LemurFaceID was developed using patch-wise Multiscale Local Binary Pattern features and modified facial image normalization techniques to reduce the effects of facial hair and variation in ambient lighting on identification. We trained and tested our system using images from wild red-bellied lemurs (Eulemur rubriventer) collected in Ranomafana National Park, Madagascar. Across 100 trials, with different partitions of training and test sets, we demonstrate that the LemurFaceID can achieve 98.7% ± 1.81% accuracy (using 2-query image fusion) in correctly identifying individual lemurs. Conclusions: Our results suggest that human facial recognition techniques can be modified for identification of individual lemurs based on variation in facial patterns. LemurFaceID was able to identify individual lemurs based on photographs of wild individuals with a relatively high degree of accuracy. This technology would remove many limitations of traditional methods for individual identification. Once optimized, our system can facilitate long-term research of known individuals by providing a rapid, cost-effective, and accurate method for individual identification

Evaluating a Second Life PBL Demonstrator Project: What Can We Learn?

This article reports the findings of a demonstrator project to evaluate how effectively Immersive Virtual Worlds (IVWs) could support Problem-based Learning. The project designed, created and evaluated eight scenarios within Second Life (SL) for undergraduate courses in health care management and paramedic training. Evaluation was primarily qualitative, using illuminative evaluation which provided multiple perspectives through interviews, focus groups and questionnaires with designers, facilitators, learning technologists and students. Results showed that SL provided a rich, engaging environment which enhanced authenticity of the scenarios, though there were issues of access and usability. The article concludes by drawing together the lessons learned which will inform educators who seek to design and develop learning scenarios in this medium