Development of a Neuro-Fuzzy System for Selection of Tree Species for Afforestation Purpose

Majumder, Mrinmoy; Chackraborty, Tilottama; Datta, Sumana; Chakraborty, Tilottama; Barman, Rabindra Nath

doi:10.1007/978-94-007-5152-1_20

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…SDMs are quite useful tool to plan afforestation projects by projecting suitable areas for species under different climate change pathways (Hidalgo et al 2008). Afforestation projects even in degraded landscapes of the world have been reported as successful, however, climatic factors such as climate extremes, seasonality factors and species selection play a vital role in success of any afforestation project (Cuong et al 2019;Li et al 2016;Majumder et al 2013). High temperatures, drought stress, disease and low soil nutrient levels are factors responsible for extensive dieback and mortality of many tree species (Allen et al 2010;Colangelo et al 2018;Gazol and Camarero 2022).…”

Section: Introductionmentioning

confidence: 99%

Tree species migration to north and expansion in their habitat under future climate: an analysis of eight tree species Khyber Pakhtunkhwa, Pakistan

Durrani,

Raza,

Shakil

et al. 2024

J Ecol Environ

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Background: Khyber Pakhtunkhwa government initiated the Billion Tree Tsunami Afforestation Project including regeneration and afforestation approaches. An effort was made to assess the distribution characteristics of afforested species under present and future climatic scenarios using ecological niche modelling. For sustainable forest management, landscape ecology can play a significant role. A significant change in the potential distribution of tree species is expected globally with changing climate. Ecological niche modeling provides the valuable information about the current and future distribution of species that can play crucial role in deciding the potential sites for afforestation which can be used by government institutes for afforestation programs. In this context, the potential distribution of 8 tree species, Cedrus deodara, Dalbergia sissoo, Juglans regia, Pinus wallichiana, Eucalyptus camaldulensis, Senegalia modesta, Populus ciliata, and Vachellia nilotica was modeled.Results: Maxent species distribution model was used to predict current and future distribution of tree species using bioclimatic variables along with soil type and elevation. Future climate scenarios, shared socio-economic pathways (SSP)2-4.5 and SSP5-8.5 were considered for the years 2041-2060 and 2081-2100. The model predicted high risk of decreasing potential distribution under SSP2-4.5 and SSP5-8.5 climate change scenarios for years 2041-2060 and 2081-2100, respectively. Recent afforestation conservation sites of these 8 tree species do not fall within their predicted potential habitat for SSP2-4.5 and SSP5-8.5 climate scenarios. Conclusions: Each tree species responded independently in terms of its potential habitat to future climatic conditions. Cedrus deodara and P. ciliata are predicted to migrate to higher altitude towards north in present and future climate scenarios. Habitat of D. sissoo, P. wallichiana, J. regia, and V. nilotica is practiced to be declined in future climate scenarios. Eucalyptus camaldulensis is expected to be expanded its suitability area in future with eastward shift. Senegalia modesta habitat increased in the middle of the century but decreased afterwards in later half of the century. The changing and shifting forests create challenges for sustainable landscapes. Therefore, the study is an attempt to provide management tools for monitoring the climate change-driven shifting of forest landscapes.

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