Modelling the impacts of future climate change on plant communities in the Himalaya: a case study from Eastern Himalaya, India

Abstract

That the Himalaya are warming at much higher rates than the global average is known. Here, we assess the future potential distribution of major plant communities in Sikkim Himalaya due to climate change using field observations and maximum entropy modelling approach. We collected data on presence and elevational distribution ranges of 584 endemic angiosperm species during field surveys at 121 sampling locations using 625 study plots and along an elevational gradient of 300-5,300 m. This field data was supplemented by already published records. Endemic species were classified into different growth forms, viz. trees, climbers, shrubs, and herbs. A total of 37,376 different species distribution models (SDMs) were built using climate projections available from 8 different general circulation models and 4 representative concentration pathways. SDMs were built for current climate (average climate for respectively. Weak and insignificant values of phylogenetic signal among the growth forms indicated that climate-induced impacts were spread across the phylogenies. We report significant increase in the habitable areas of shrubs and their northward expansion, gradually replacing the herbaceous communities. This change can alter the structure and function of the Himalayan highland ecosystems besides depleting bioresource base and endangering the local livelihoods.

Effects of Climate Change on the Potentially Suitable Climatic Geographical Range of Liriodendron chinense

“…This finding was consistent with previous studies that have also found a northward shift in the spatial distribution of suitable species climatic habitat [44]. Species would shift their distributions to higher latitudes in response to warming climates, because temperature outside their thermal tolerance would decrease their capacity to survive [44,[71][72][73].…”

“…To reduce the uncertainty arising from the single general circulation model (GCM), we used data from multiple different GCMs [2, 43,44] including BCC-CSM1-1, CCSM4, GISS-E2-R, IPSL-CM5A-LR, HadGEM2-ES, MIROC-ESM-CHEM, MRI-CGCM3, and NorESM1-M. For each GCM, we downloaded bioclimatic variables for four Representative Concentration Pathways (RCP: 2.6, 4.5, 6.0, and 8.5). We assumed that four topographical variables remain unchanged over the next 70 years.…”

“…Based on 212 occurrence records and nine environmental variables, each MaxEnt run randomly selected 80% of the points to train the model, and the remaining 20% of the points to test and validate the model. The MaxEnt model was set to run with five replicates, subsample replicated run type, and 10,000 random background points [44,52,53]. The MaxEnt model limits its complexity by regularization, which is a penalty for including additional constraints (e.g., variables) in the model [54].…”

Climate change effects on the processing tomato growing season in California using growing degree day model

“…Skills in climate model outputs have improved over time, and more recently, a set of climate change scenarios known as representative concentration pathways (RCPs) has been adopted by climate researchers to provide a range of possible futures for the evolution of atmospheric composition and implications on various sectors (Collins et al 2013;Gharbia et al 2016;Zahid and Iqbal 2015;Deb et al 2018;Manish et al 2016;Clarke et al 2007;Smith and Wigley 2006;Thomson et al 2011;Wise et al 2009). However, it needs to be presented in a format which can provide useful information to growers.…”

Climatic variables determining <i>Rhododendron</i> sister taxa distributions and distributional overlaps in the Himalayas

“…Climate change affects species distributions (Parmesan and Yohe 2003), and species with a restricted distribution may be more vulnerable to the changes in climatic factors that determine the boundaries of their distributions (Thuiller et al 2005, Manish et al 2016. Understanding the extent to which a geographical range shift is needed for species to be able to track their climate niche in response to climate change is currently a crucial scientific task.…”