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Impact of individual demographic and social factors on human–wildlife interactions: a comparative study of three macaque species

ABSTRACT: Despite increasing conflict at human–wildlife interfaces, there exists little research on how the attributes and behavior of individual wild animals may influence human–wildlife interactions. Adopting a comparative approach, we examined the impact of animals’ life-history and social attributes on interactions between humans and (peri)urban macaques in Asia. For 10 groups of rhesus, long-tailed, and bonnet macaques, we collected social behavior, spatial data, and human–interaction data for 11–20 months on pre-identified individuals. Mixed-model analysis revealed that, across all species, males and spatially peripheral individuals interacted with humans the most, and that high-ranking individuals initiated more interactions with humans than low-rankers. Among bonnet macaques, but not rhesus or long-tailed macaques, individuals who were more well-connected in their grooming network interacted more frequently with humans than less well-connected individuals. From an evolutionary perspective, our results suggest that individuals incurring lower costs related to their life-history (males) and resource-access (high rank; strong social connections within a socially tolerant macaque species), but also higher costs on account of compromising the advantages of being in the core of their group (spatial periphery), are the most likely to take risks by interacting with humans in anthropogenic environments. From a conservation perspective, evaluating individual behavior will better inform efforts to minimize conflict-related costs and zoonotic-risk.

SUBMITTER: Balasubramaniam K

PROVIDER: S-EPMC7738552 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Project description:Macaques (genus Macaca) are the most widely distributed non-human primates, and their evolutionary history, gene expression profiles, and genetic differences have been extensively studied. However, the DNA methylomes of macaque species are not available in public databases, which hampers understanding of epigenetic differences among macaque species. Epigenetic modifications can potentially affect development, physiology, behavior, and evolution. Here, we investigated the methylation patterns of the Tibetan macaque (M. thibetana; TM), Chinese rhesus macaque (M. mulatta lasiota; CR), and crab-eating macaque (M. fascicularis; CE) through whole-genome bisulfite sequencing from peripheral blood. We compared genome-wide methylation site information for the three species. We identified 12,128 (CR vs. CE), 59,165 (CR vs. TM), and 39,751 (CE vs. TM) differentially methylated regions (DMRs) in the three macaques. Furthermore, we obtained the differentially expressed genes (DEGs) among the three macaque species. The differences between CR and CE were smaller at both the methylome and transcriptome levels than compared with TM (CR vs. TM and CE vs. TM). We also found a change in the density of single nucleotide mutations in DMRs relative to their flanking regions, indicating a potential mechanism through which genomic alterations may modulate methylation landscapes, thereby influencing the transcriptome. Functional enrichment analyses showed the DMR-related genes were enriched in developmental processes and neurological functions, such as the growth hormone-related pathway, insulin secretion pathway, thyroid hormone synthesis pathway, morphine addiction, and GABAergic synapses. These differences may be associated with variations in physiology and habitat among the macaques. Our study provides one of the first genome-wide comparisons of genetic, gene expression, and epigenetic variations across different macaques. Our results should facilitate further research on comparative genomic and genetic differences in macaque species.

Project description:ImportanceGestational diabetes is common in pregnancy and is associated with adverse pregnancy and fetal outcomes. Currently, population-based data on the prevalence of gestational diabetes are limited in India.ObjectiveTo provide a comprehensive national assessment of gestational diabetes in India and its socioeconomic, demographic, and geographic associations, using elevated random blood glucose data as a proxy for a gestational diabetes diagnosis.Design, setting, and participantsThis cross-sectional study analyzed the fourth National Family Health Survey, conducted in India between January 2015 and December 2016. This nationally representative sample comprised 699 686 women 15 to 49 years of age, of whom 32 428 (4.6%) were pregnant. Data were analyzed between July and December 2019 and between July and August 2020.ExposuresAge, body mass index, hypertension, wealth, and social caste were factors potentially associated with gestational diabetes.Main outcomes and measuresGestational diabetes, defined as elevated random blood glucose according to predetermined thresholds (≥200 mg/dL for nonfasting, ≥92 mg/dL for fasting).ResultsOf the 31 746 pregnant women with complete data in the study, the mean (SD) age was 24.3 (4.7) years, and the mean (SD) gestational age was 5.1 (2.3) months. The weighted age-adjusted prevalence of gestational diabetes was 1.3% (95% CI, 1.1%-1.5%). The prevalence of gestational diabetes increased with age, from 1.0% (95% CI, 0.5%-1.5%) at age 15 to 19 years to 2.4% (95% CI, 1.0%-3.8%) at age 35 years or older. The age-adjusted prevalence of gestational diabetes was higher among women with a body mass index of 27.5 or greater (1.8%; 95% CI, 1.0%-2.5%) compared with women with a body mass index of less than 18.5 (0.8%; 95% CI, 0.5%-1.1%), among women in the highest wealth quartile (1.7%; 95% CI, 1.1%-2.5%) compared with those in the lowest (0.9%; 95% CI, 0.7%-1.2%), and women in the south (eg, Kerala: 4.5%; 95% CI, 2.4%-6.7%; Telangana: 5.4%; 95% CI, 0.0%-11.0%) compared with the northeast (eg, Assam: 0.23%; 95% CI, 0.0%-0.48%; Mizoram: 0.16%; 95% CI, 0.0%-0.49%).Conclusions and relevanceIn this study, considerable variation was found in the prevalence of gestational diabetes by state, socioeconomic status, and demographic factors. This finding has implications for the method of gestational diabetes screening in low-resource settings in India, especially in areas or among demographic groups with lower prevalence.

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Impact of individual demographic and social factors on human–wildlife interactions: a comparative study of three macaque species

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