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• W4386324987 abstract "Abstract Although the impact of climate change is slow, the transformation in climate regime can lead to an ecosystem structure change from one stable to another stable state through intermediate bistable or metastable conditions. Therefore, the state transition or resilience in nature can never be sharp or be quantified with a single tipping point across the scales; rather, it should be understood through a tipping point range (tipping zone) across hysteresis loop(s). This study uses a satellite data-derived actual forest cover state map of India and high-resolution long-term average precipitation data to predict various tipping point range hysteresis for different forest cover states such as forest, scrubland, grassland and vegetation-less. The forest and vegetation-less states could have one-way, while scrubland and grassland have two-way transition probabilities with a probable shift in precipitation regime. In the dry conditions, the precipitation tipping zone predicted between 154 mm and 452 mm for the forest to scrubland transitions, while the reverse transition (from scrubland to forest) could occur in wet conditions between 1080 mm and 1400 mm. Similarly, the transition between scrubland and grassland, between grassland and vegetation-less state, may occur in contrasting dry and wet conditions, creating a hysteresis loop. The study indicates that the reversal of state change requires differential energy spent during the onward transition. The study proposes a novel characteristic curve demonstrating the varied precipitation tipping points/ zones, precipitation overlaps and distribution of the various life forms, and co-existence zones. The characteristic curve offers valuable inputs to explain life form transition and demarcate regions where forest enrichment and degradation may occur due to climate regime shifts. Such a spatially explicit database could provide vital inputs for planning forest cover restoration and management activities and mitigate the climate change impact." @default.
• W4386324987 created "2023-09-01" @default.
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• W4386324987 date "2023-08-31" @default.
• W4386324987 modified "2023-09-27" @default.
• W4386324987 title "Predicting Tipping Points of Forest Cover Resilience as a Response to Precipitation – a Step Towards Understanding Climate Resilience" @default.
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• W4386324987 doi "https://doi.org/10.21203/rs.3.rs-3300791/v1" @default.
• W4386324987 hasPublicationYear "2023" @default.
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