Cartosat-1 Image Segmentation Technique for Shade Tree Crown Density in Tea Gardens of East India in Relation to Terrain Geometry

Dutta, Dibyendu; Lukose, Libeesh; Bajpai, Anju; Bhunia, U.; Singh, Raj Kumar; Samanta, Sourav

doi:10.5376/jtsr.2018.08.0001

Cited by 2 publications

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“…We also that found elevation and tree species abundance/richness to be significant contributors, which were common for soil arthropod abundance, richness across both seasons and across all study sites. However, in the Eastern Himalayan tea landscape, as the elevation increases, the average abundance and diversity of shade trees decreases (Dutta et al, 2018) as a result of management decisions. Furthermore, Rainforest Alliance certification, was a significant positive predictor for soil arthropod abundance but not for soil arthropod richness and diversity, whereas organic practise was a significant positive predictor of soil arthropod richness.…”

Section: Discussionmentioning

confidence: 99%

Section: Season On-farm Practise and Soil Arthropods Community Compos...mentioning

confidence: 99%

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Native tree species richness enhances matrix functionality for soil arthropods in tropical plantation landscapes: A case study from the Himalayas

Chowdhury

Samrat

Pandian³

et al. 2022

Insect Conserv Diversity

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1. Despite their distinctive role in regulating agroecosystems, soil fauna is largely excluded from conservation action. With increasing evidence supporting matrix functionality as critical for multiple species in agroecosystems, it is important that efforts meant to enhance biodiversity in managed systems be inclusive and effective for all species and not just charismatic fauna. 2. Third party certifications are a popular mechanism for claiming pro-conservation practises in tropical agricultural lands. Therefore, we asked whether voluntary practises codified by third party certifications of tropical tea plantations support soil biodiversity, and what factors explain soil arthropod abundance and richness in such certified and uncertified landscapes.3. We used pitfall trap data and soil samples across two seasons in large tea plantations, and small tea-growing agroforestry farms in the Darjeeling Himalayas in India.Plantations certified and those not certified were selected for the study.4. Soil arthropod morphospecies abundance, richness and diversity were significantly higher in summer as opposed to winter. Contrary to our expectations, there was no significant difference in soil arthropod abundance, richness and diversity between uncertified small agroforestry farms and certified large monoculture plantations.Our analysis establishes tree species richness and season as the most important predictors of soil arthropod abundance, richness and effective number of species.5. We recommend that increased abundance and diversity of native trees in the tea matrix should be a crucial criterion for agroecosystem management. This would improve matrix functionality for species that are sensitive to management and reflect practises that enhance biodiversity.

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Section: Discussionmentioning

confidence: 99%

Section: Season On-farm Practise and Soil Arthropods Community Compos...mentioning

confidence: 99%

Native tree species richness enhances matrix functionality for soil arthropods in tropical plantation landscapes: A case study from the Himalayas

Chowdhury

Samrat

Pandian³

et al. 2022

Insect Conserv Diversity

View full text Add to dashboard Cite

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Estimation of Shade Tree Density in Tea Garden using Remote Sensing Images and Deep Convolutional Neural Network

Paul

Bhattacharyya

Chakraborty

2021

Journal of Spatial Science

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Cartosat-1 Image Segmentation Technique for Shade Tree Crown Density in Tea Gardens of East India in Relation to Terrain Geometry

Cited by 2 publications

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Native tree species richness enhances matrix functionality for soil arthropods in tropical plantation landscapes: A case study from the Himalayas

Native tree species richness enhances matrix functionality for soil arthropods in tropical plantation landscapes: A case study from the Himalayas

Estimation of Shade Tree Density in Tea Garden using Remote Sensing Images and Deep Convolutional Neural Network

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