Bhatt, D. D. | Search bioRxiv

bioRxiv2021

Distribution modeling of Lantana camara and identification of hotspot for future management of the species in the lower Shivalik region of Uttarakhand, India

Invasive alien species are one of the most significant threats to biodiversity of the earth ecosystem. Spatial modeling has played a vital role in predicting and mapping the suitable areas of the species habitat for management implementation. Lantana camara is one of the ten worst invasive weed enlisted by IUCN., and has its distribution in more than 154000 sq. km area in India. We predicted the distribution of Lantana camara using Ecological Niche Modeling (ENM) in MaxEnt software for Rajaji- Corbett landscape in the lower Shivalik region of the state of Uttarakhand, India. The predicted area for the invasion was classified into four categories high, good, medium, and low potential areas. The distribution hotspots were identified using Getis Ord G* method in ArcGIS 10.5 by calculating plot-wise species occurrence. Major hotspot areas under threat of high infestation are Dholkhand, Gohri, Ramgarh, Motichur, and Chilla from Rajaji Tiger Reserve, Palain, Mandal and Maidavan from Kalagarh Tiger Reserve and Bijrani, Dheela, Dhikala, Jhirna and Kalagarh from Corbett Tiger Reserve. This study provides a current status of the invasive species in the landscape with identified areas that need immediate actions to control the spread of the species. The study results can help the policymakers and stakeholders build an efficient and strategically weed management plan.

ecology↗

bioRxiv2019

Risk factors associated with Avian Influenza subtype H9 outbreaks on poultry farms in Kathmandu valley, Nepal

Poultry sector contributes to four percent in national GDP of Nepal. However, this sector is under threat with periodic outbreaks of Avian Influenza (AI) subtypes H5 and H9 since 2009. This has been both a both public health threat and an economic issue. Since last three years, outbreaks of AI subtype H9 has caused huge economic losses in major poultry producing areas of Nepal. However, the risk factors associated with these outbreaks have not been assessed. A retrospective case-control study was conducted from April 2018 to May 2019 in Kathmandu Valley to understand the risk factors associated with AI subtype H9 outbreaks. Out of 100 farms selected, 50 were \"case\" farms, confirmed positive to H9 at Central Veterinary Laboratory, Kathmandu, and other 50 farms were \"control\" farms, matched for farm size and locality within a radius of three km from the case farm. Each farm was visited to collect information using semi-structured questionnaire. Nineteen potential risk factors were included in the questionnaire under the broad categories: birds and farm characteristics, management aspects and biosecurity status of the farms. Univariable and multivariable logistic regression analysis were conducted to calculate corresponding odds ratios. Identified risk factors associated with AI subtype H9 outbreaks in Kathmandu valley were: \"Birds of age 31-40 days\" (OR= 11.31, 95% CI: 1.31-98.02, p=0.028), \"Older farms operating for >5 years\" (OR= 10.9, 95% CI: 1.76-66.93, p=0.01), \"Commercial layers farms\" (OR=36.0, 95% CI: 0.97-1332.40, p=0.052), \"Used stream water to water birds (OR= 5.7, 95% CI: 1.10-30.13, p=0.039)\", \"Farms without practice of fumigation after each batch of poultry (OR= 4, 95% CI: 1.44-13.13, p=0.009)., \"Farm with previous history of AI (OR= 13.8, 95% CI: 1.34-143.63, p = 0.028), \"Did not applied farm boots (OR= 2.58, 95% CI: 0.98-6.80, p= 0.055), \"Visitors allowed to enter the farms (OR= 2.5, 95% CI: 1.011-6.17, p = 0.047) and \"No foot bath at entry of farms (OR= 3.3, 95% CI: 1.29-8.38, p = 0.013). This study depicts that outbreaks of AI subtype H9 in Kathmandu valley was related to poor management practices and biosecurity in the poultry farms. We suggest improving management practices and increase biosecurity in the farms to reduce incidences of AI subtype H9 outbreaks in Kathmandu valley.

scientific communication and education↗