Contouring of an indistinct sex ratio and COVID-19 threat to the sustainability of Myrica esculenta in the Northwestern Himalayas

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Research Articles | Published:

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DOI: 10.1007/s42535-024-00984-3
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Keywords: n Myrica esculentan , Sex ratio, Generalized linear model, Variance estimation, Abiotic factors, Northwestern Himalayan landscape


Abstract


COVID-19 has dramatically affected every landscape on Earth, and the Indian Himalayan Region (IHR) forest biodiversity is also affected by the local inhabitants and immigrants during the pandemic scenario, as they are still dependent upon the procurement of raw materials for their socio-economic upliftment. The research aimed to determine the indeterminate sex ratios in M. esculenta by implying a stratified random sampling procedure with proportional allocation. Forest surveys were conducted during 2018–2020 and quadrats (each with an area of 400 m2) were laid in various forest strata across the northwestern Himalayas (Uttarakhand, India). The anthropogenic stress encountered by this species was also observed and analysed to reveal the threats obstructing its perpetuity. To analyse and assess the impact of human intervention on the female trees of M. esculenta, a General Linear Model (GLM) was applied. Results revealed a ratio of 1.45 (Male:Female) was obtained, indicating the prevalence of a male-dominant population of M. esculenta across the northwestern Himalayas. The ANOVA (p = 0.008) suggested magnified anthropogenic stress upon females (average damage on female trees per 400 m2 ((widehat{Y})) = 0.64 ± 0.751) in 2020, where the estimator revealed an overall damage of 50.02% in the surveyed areas. The study provides a scenario defining the detrimental impact of lockdown on species-specific diversity levels in the Himalayas. It also suggests that managing and unearthing the sex ratio of already depleting resources is the key step for in situ and ex situ conservation programmes in M. esculenta.

n                     Myrica esculentan                  , Sex ratio, Generalized linear model, Variance estimation, Abiotic factors, Northwestern Himalayan landscape


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Author Information


Division of Genetics & Tree Improvement, ICFRE-Forest Research Institute, Dehradun, India