All-Male Groups in Asian Elephants: A Novel, Adaptive Social Strategy in Increasingly Anthropogenic Landscapes of Southern India

Male Asian elephants are known to adopt a high-risk high-gain foraging strategy by venturing into agricultural areas and feeding on nutritious crops in order to improve their reproductive fitness. We hypothesised that the high risks to survival posed by increasingly urbanising and often unpredictable production landscapes may necessitate the emergence of behavioural strategies that allow male elephants to persist in such landscapes. Using 1445 photographic records of 248 uniquely identified male Asian elephants over a 23-month period, we show that male Asian elephants display striking emergent behaviour, particularly the formation of stable, long-term all-male groups, typically in non-forested or human-modified and highly fragmented areas. They remained solitary or associated in mixed-sex groups, however, within forested habitats. These novel, large all-male associations, may constitute a unique life history strategy for male elephants in the high-risk but resource-rich production landscapes of southern India. This may be especially true for the adolescent males, which seemed to effectively improve their body condition by increasingly exploiting anthropogenic resources when in all-male groups. This observation further supports our hypothesis that such emergent behaviours are likely to constitute an adaptive strategy for male Asian elephants that may be forced to increasingly confront anthropogenically intrusive environments

Examining leopard attacks: spatio-temporal clustering of human injuries and deaths in Western Himalayas, India

Shared spaces in Africa and Asia accommodate both humans and big cats. This engenders rare but distinctive cases of human fatalities by lions, tigers, and leopards. Among big cats, leopards have the widest range and occur even among high densities of humans. This increased potential for encounters with humans results in attacks, exemplified most by India where 50% of the states report human injuries and deaths due to leopards. Himachal Pradesh (HP) state reported 30 lethal and 287 non-lethal leopard attacks on humans per year between 2004 – 2015 (N=317). Identifying patterns in big cat attacks on people facilitates targeted interventions for decreasing such fatalities. This study aims to detect if leopards are cluster-causing agents of human injuries and deaths. We identify the patterns of leopard attacks on humans in Himachal Pradesh by examining the following questions: (a) do leopard-attributed attacks on humans cluster in space and time? and among the leopard-attributed attacks (b) do unprovoked attacks on humans cluster spatio-temporally? and (c) what environmental factors are associated with the clustered leopard attacks on humans? We employed a space-time permutation scan statistic commonly used in epidemiology to test for spatio-temporal clustering of leopard attacks. Attacks were spread across 75% (~42,000 km sq.) of HP in 11 out of 12 districts. We found that 23% of attacks clustered into 12 significant spatio-temporal clusters. Nearly 14% of the leopard-attributed attacks (N=317) were unprovoked and attacks displaying “predatory” signs did not form significant clusters. Binomial regression models were run to test association of eight environmental factors with clustered attacks. We found that leopard-attributed attacks farther away from the protected area boundary and closer to the district boundary had higher probability of clustering. The framework developed in this study to identify the outbreak of unprovoked leopard attacks confirms the absence of dedicated “man-eaters” in the study region. This approach can be applied to adaptively manage human-wildlife conflict and it also demonstrates the utility of scan statistic in ecological research

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

A DCT-Gaussian Classification Scheme for Human-Robot Interface

Abstract-The ultimate success of a human-robot-interface system depends on how accurately user control signals are classified. This paper is aimed at developing and testing a strategy to accurately classify human-robot control signals. The primary focus is on overcoming the dimensionality problem frequently encountered in the design of Gaussian multivariate signal classifiers. The dimensionality problem is overcome by selecting, using two different ranking criteria, a small set of linear combinations of the input signal space generated by the discrete cosine transform (DCT). The application of the resulting DCT-Gaussian signal classification strategy is demonstrated by classifying tongue-movement earpressure (TMEP) bioacoustic signals that have been proposed for control of an assistive robotic arm. Classification results show that the DCT-Gaussian classifiers outperform classifiers described in a previous study. Most noteworthy is the fact that the Gaussian multivariate control signal classifiers developed in this paper can be designed without having to collect a prohibitively large number of training signals in order to satisfy the dimensionality conditions. Consequently, the classification strategies will be especially beneficial for designing personalized assistive interfaces for individuals from whom only a limited number of training signals can reliably be collected due to severe disabilities

attack_interviews

Details of human attacks by leopards and activity of the person before attacks. NOTE: Geographic coordinates of attack location were removed to protect individual's identity, and because Panthera pardus is a vulnerable species. To obtain these values, please contact Aritra Kshettry <[email protected]

Leopard_attacks_victims

Details of all leopard attacks within study area. Month, Year and location of village where attack occurred. NOTE: Geographic coordinates of attack location were removed to protect individual's identity, and because Panthera pardus is a vulnerable species. To obtain these values, please contact Aritra Kshettry <[email protected]

Fire and grazing modify grass community response to environmental determinants in savannas: Implications for sustainable use

Tropical dry forests and savannas are important repositories of plant diversity and ecosystem services in the tropics. These ecosystems are also used extensively for grazing by livestock, and represent a critical element of the rural economy of many tropical countries. Fire is considered as a part of co-evolution in these ecosystems across the globe. However, in recent decades, there has been a shift in historical fire regime. Fire has become more frequent in these landscapes, and could be further enhanced under climate change. This poses threats to existing biodiversity, ecosystem processes, and rural economy. We asked how variability in fire frequency has influenced diversity and heterogeneity in grass species composition, and richness and abundance of grass species preferred by large herbivores (referred to as grazing acceptability) in a South Indian tropical savanna forest. We assumed that an increase in fire frequency acts as the active constraint and limits an ecosystem from attaining the maximum heterogeneity, and the maximum grazing acceptability (maximum richness and abundance of grass species preferred by herbivores) in its native settings. We used MODIS active fire and burned area products to estimate fire frequency across the landscape. A nested sampling approach was used to collect information on vegetation and soil at different fire frequencies. Quantile regression analyses indicated that diversity and heterogeneity in grass species composition as well as grazing acceptability decreased with increasing fire frequencies. We found that livestock grazing intervened with the observed vegetation patterns; grass species diversity and heterogeneity, and grazing acceptability increased with grazing intensity at lower quantiles. Other measured covariates, rainfall, and soil-fertility, alone were not able to explain the observed vegetation patterns in the landscape. The results show a need to control annual fires but allow and manage intermittent fires in this landscape. A complete suppression of fire is not desirable as fire releases nutrients from burning of deeper-rooted vegetation and thus acts as a periodic nutrient pump. It also played an important role in maintaining the grass cover by reducing shrub cover. Hence, it is important to consider the complex interactions between fires–grazers–soil vegetation to develop effective management practices. We conclude that fire frequency should be managed at low to intermediate levels (one fire in every 5–9 years, resembling the native settings), and grazing regulated, in order to sustain wild and domestic herbivores, biodiversity, and other key ecosystem processes and services over the long-term