Abstract
Abstract. The impact of long term climate change that imparts stress on forest could be perceived by studying the regime shift of forest ecosystem. With the change of significant precipitation, forest may go through density change around globe at different spatial and temporal scale. The 100 class high resolution (60 meter spatial resolution) Indian vegetation type map was used in this study recoded into four broad categories depending on phrenology as (i) forest, (ii) scrubland, (iii) grassland and (iv) treeless area. The percentage occupancy of forest, scrub, grass and treeless were observed as 19.9 %, 5.05 %, 1.89 % and 7.79 % respectively. Rest of the 65.37 % land area was occupied by the cropland, built-up, water body and snow covers. The majority forest cover were appended into a 5 km × 5 km grid, along with the mean annual precipitation taken from Bioclim data. The binary presence and absence of different vegetation categories in relates to the annual precipitation was analyzed to calculate their resilience expressed in probability values ranging from 0 to 1. Forest cover observed having resilience probability (Pr) < 0.3 in only 0.3 % (200 km2) of total forest cover in India, which was 4.3 % < 0.5 Pr. Majority of the scrubs and grass (64.92 % Pr < 0.5) from North East India which were the shifting cultivation lands showing low resilience, having their high tendency to be transform to forest. These results have spatial explicitness to highlight the resilient and non-resilient distribution of forest, scrub and grass, and treeless areas in India.
Highlights
The state of global forest cover in the regions undergoing significant climate alterations gradually changing in both the directions of stability and instability
In the current study the binary logistic regression technique was adopted for estimating the forest cover resilience
The India vegetation type map recoded into four vegetation where the non-vegetated areas as cold deserts, settlement, barren land, river bed, water body, wet lands and agricultural lands were reclassified as treeless area (Table 1)
Summary
The state of global forest cover in the regions undergoing significant climate alterations gradually changing in both the directions of stability and instability. The magnitude, frequency and duration of external forces and the internal resistive forces of a system define the state of that particular system If this perturbation exceeds the internal resistive threshold value, the internal resilience declines and the ecosystem becomes vulnerable, and progressively smaller disturbances can cause shifts (Folke, et al, 2004). The probability of change proneness or complementarily the resilience can be modelled using the vegetation type map, driving forcing or drivers through statistical approaches or models as logistic regression, generalized additive model (GAM), Integrated Biosphere Simulator (IBIS) (Hirota et al, 2011; Staver et al, 2011; Behera et al, 2018; Chaturvedi et al, 2010). Cox in 1958 is used to predict a binary response (presence or absence) based on one or more predictor variables in estimating their quantitative and qualitative response
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