Assessment of Dynamic Land System in Nilgiri Biosphere Reserve Using MODIS Derived Temporal Data Sets during 2001 to 2018

Srinivasan, Karthik K.; S, Anand; Bilyaminu, H.; Haritha, S.

doi:10.9734/ijecc/2021/v11i630430

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…The Nilgiri Biosphere Reserve (NBR) is one of the top twenty-ve global hotspots of biodiversity in the world based on the level of endemic fauna and ora (Baskaran et al, 2012) and within India is the "largest protected ecologically sensitive areas" (Srinivasan et al, 2021) the NBR is composed of protected forests and human-dominated landscapes, including that of tea, coffee and eucalyptus plantations, orchards and vegetable farms. We chose ten coffee-growing farms (Coffea arabica) during the coffee owering season of February to May (2014), which were part of the agricultural land belonging to the Irula and Kurumba Indigenous communities of the NBR (Fig.…”

Section: Study Sitesmentioning

confidence: 99%

Factors influencing pollinator abundance in Indigenous coffee farms of the Nilgiris, Western Ghats, India

Sharma

Viswanathan

Leo

et al. 2023

Preprint

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Wild pollinators are shown to be declining in many parts of the world where data and evidence exist; trends could be similar in other regions, but data and evidence are lacking. Land-use change is recognized as the top driver of biodiversity loss, including pollinator loss. In this study, we focused on coffee plantations in Indigenous land holdings in the Nilgiri Biosphere Reserve in the Western Ghats of India, where changing agricultural practices and reducing tree shade diversity and/or changing tree cover type may threaten pollinator communities. We assessed pollinator abundance, through scan sampling of flowers, in ten coffee farms — five of which had (Grevillea robusta) silver oak as shade trees and five of which had native tree species. We then evaluated the combined effect of (a) tree cover type, (b) distance from the forest edge, and (c) area under coffee cultivation on the abundance of four dominant coffee pollinators (Apis dorsata, A. cerana, A. florea, and Tetragonula iridipennis) and the abundance of Xylocopa sp., which is also known as a coffee pollinator. We found that the abundances of all five species were associated positively with the area under coffee cultivation. The abundance of A. cerana and T. iridipennis were also associated with the distance from the forest edge; the closer a farm to the forest, the more individuals of A. cerana and T. iridipennis were found visiting coffee flowers on the farm. Lastly, we found no statistically significant relationship between the abundances of the five species examined and tree cover type (either mixed native forest trees or silver oak (G. robusta)). The absence of a pattern may have been driven partly by our relatively small sample size since the abundances of A. cerana, A. florea, and T. iridipennis were on average higher in farms with native tree species. Our results suggest that maintaining forests near coffee systems increases insect pollinator abundance (i.e., delivery of pollination services) in the case of A. cerana and T. iridipennis and maintaining forest cover with native tree species composition plays a role in supporting pollinator habitats as well as providing foraging resources. Implications for insect conservation In working with Indigenous land holdings in India, our results show that forests and land use (area under cultivation) play a key role in maintaining bee pollinators in coffee agroecosystems and further investigation is needed to clarify the role of tree cover type and insect populations.

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Section: Study Sitesmentioning

confidence: 99%

Factors influencing pollinator abundance in Indigenous coffee farms of the Nilgiris, Western Ghats, India

Sharma

Viswanathan

Leo

et al. 2023

Preprint

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Climate Change and Human Activities: Their Roles in Shaping Land Productivity in Northern Nigeria

Yabo,

Pereira,

Siqueira

et al. 2024

Land Degrad Dev

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The Northern Nigeria Region (NNR) has historically suffered from land productivity changes due to anthropogenic and climatic factors. The development of methodologies that can evaluate these changes at the pixel level and spatialize the effects of driving factors is a key requisite to provide targeted solutions for land degradation, in a country with population growth and desert advancement. In this study, we applied MODIS series data to assess land productivity changes in the NNR (2001–2021) using NDVI trend analysis. We also used correlation and RESTREND analyses to discriminate between climate and human factors and map their effects. The results indicated that approximately 30.7% of the NNR showed land degradation, whereas 27.1% showed an increase in land productivity. There was a clear spatial pattern, with increasing productivity closer to the northern Nigeria boundary with Niger, and decreasing productivity concentrated in the central and southern parts of the NNR. Anthropogenic factors had a greater impact on land degradation and improvement, compared with rainfall. The climate forcing contributed most to land productivity in the northeastern part of the NNR. Land degradation is mainly associated with overgrazing and unsustainable agricultural practices, which lead to decreasing productivity of grasslands and crops. On the other hand, human influence on improvements involves land abandonment and recovery programs. These results can be used to planning initiatives to better integrate food production with environmental protection in the NNR, contributing to policies to Nigeria achieving land degradation neutrality as soon as possible.

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Assessment of Dynamic Land System in Nilgiri Biosphere Reserve Using MODIS Derived Temporal Data Sets during 2001 to 2018

Cited by 2 publications

References 22 publications

Factors influencing pollinator abundance in Indigenous coffee farms of the Nilgiris, Western Ghats, India

Factors influencing pollinator abundance in Indigenous coffee farms of the Nilgiris, Western Ghats, India

Climate Change and Human Activities: Their Roles in Shaping Land Productivity in Northern Nigeria

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