Modeling of Valeriana wallichii Habitat Suitability and Niche Dynamics in the Himalayan Region under Anticipated Climate Change

Abstract

An increase in atmospheric greenhouse gases necessitates the use of species distribution models (SDMs) in modeling suitable habitats and projecting the impact of climate change on the future range shifts of the species. The present study is based on the BIOMOD ensemble approach to map the currently suitable habitats and predict the impact of climate change on the niche shift of Valeriana wallichii. We also studied its niche dynamics using the ecospat package in R software. Values of the area under curve (AUC) and true skill statistics (TSS) were highly significant (>0.9), which shows that the model has run better. From 19 different bioclimatic variables, only 8 were retained after correlation, among which bio_17 (precipitation of driest quarter), bio_1 (annual mean temperature), and bio_12 (annual mean precipitation) received the highest gain. Under future climate change, the suitable habitats will be significantly contracted by −94% (under representative concentration pathway RCP 8.5 for 2070) and −80.22% (under RCP 8.5 for 2050). There is a slight increase in habitat suitability by +16.69% (RCP 4.5 for 2050) and +8.9% (RCP 8.5 for 2050) under future climate change scenarios. The equivalency and similarity tests of niche dynamics show that the habitat suitability for current and future climatic scenarios is comparable but not identical. Principal Component Analysis (PCA) analysis shows that climatic conditions will be severely affected between current and future scenarios. From this study, we conclude that the habitats of Valeriana wallichii are highly vulnerable to climate shifts. This study can be used to alleviate the threat to this plant by documenting the unexplored populations, restoring the degraded habitats through rewilding, and launching species recovery plans in the natural habitats.

Climate Change Drives the Transmission and Spread of Vector-Borne Diseases: An Ecological Perspective

“…The ten publications in this Special Issue illuminate the impacts of climate change on ecosystems and human health from different perspectives in diverse disciplines, including phytology, biology, epidemiology, pathology, and molecular biology. In phytology and biology, the geographical ranges of plants and animals have been shown to be affected by climate change [ 6 , 7 , 8 ]. In epidemiology and pathology, the future geographic expansion of vector species that carry vector-borne diseases (VBDs) has been evaluated [ 9 , 10 , 11 , 12 ], and proved the invasive and evolutionary adaptation of vectors to different ecological and environmental conditions [ 13 ].…”

Identifying Cultivation Hotspots of Aquilegia fragrans Benth.-an Endangered Medicinally Important Plant via Ensemble Modelling under Climate Change Scenarios

“…Those models having TSS scores of ≥ 0.8 were retained for the creation of nal ensemble models. Consequently, ve ensemble projections were created, one reciprocates with current climatic suitability and the remaining ones for anticipation of future prediction on habitat suitability for the time periods of 2050 and 2070 periods), representing 2 typical concentration trajectories RCP4.5 and 8.5 (Kumari et al, 2022, Rather et al, 2022.…”

“…Predictions were generated during this process by using a predetermined algorithm after changing just a solitary target variable whilst holding other variables constant.Taking these output types into consideration one will come to know about absolute metrics such as "loss", "absent" and "stable". So far "loss" is concerned it denotes pixel in number forfeited by species under study owing to the fact of climate alterations; "absent" represents pixel resolution in number presently not engrossed through species under study besides having no prediction for suitability under a peculiar environmental scenario; and "stable," represents a pixel in number engrossed via species under research and additionally predicted to be appropriate beneath a particular climatic scenario(Guisan et al, 2017;Rather et al 2022;Kumari et al, 2022).We also get three additional relative metrics like: "percentage loss" indicating a loss in the percentage of sites inhabited presently and measured via (loss/ (loss + stable); "percentage gain" which is gured out through (gain/(loss + stable); simply can be put as a percentage of new sites taking into account the present distribution size of species and "range change" expresses comprehensive projection output equivalent to percentage gain-percentage loss(Guisan et al, 2017;Rather et al 2022).…”

Ensemble modeling to predict the impact of future climate change on the global distribution of Olea europaea subsp. cuspidata

“…Interestingly, detailed information on four absolute metrics related to "species loss" (i.e., loss of suitable habitat by the studied species under future climate change), "species absence" (i.e., amount of area not occupied by the studied species under current and future climatic scenarios), "stable" (i.e., the amount of area occupied by the studied species both under current and future climatic scenarios) and "gain" (i.e., a gain of suitable habitat by the studied species under future climate change) can be obtained (Guisan et al, 2017). Lastly, from the above four absolute metrics, three additional relative metrics can be calculated, including "percentage loss" (i.e., percentage of currently suitable areas predicted to be lost and is calculated as [loss/(loss + stable)]; "percentage gain" (i.e., percentage of new habitats predicted to be suitable when compared with the species' current distribution size and is calculated as [gain/(loss + stable)]; and "range change, " i.e., the overall output of predictions and is calculated as (percentage gain-percentage loss) (Kumari et al, 2022;Wani et al, 2022b).…”