Updated: Jul 26
~ By Satvik Parashar
Species occurrence and their distributions are not random phenomenon but governed by a number of factors. Identifying these factors would help in predicting possible species ranges. A recent study (Yadav et al., 2021) discusses how such factors and climate change affects few of the floral species in the Central Indian Landscape that are important for Non-Timber Forest Products (NTFPs). The six tree species considered were – Mahua (M. longifolia), Achar (B. lanzan), Aonla (E. officinalis), Behera (T. bellirica), Harad (T. chebula) and Bhutya/ Kullu (S. urens).
The study site lies in the Central Indian state of Madhya Pradesh, where the species occurrence records were collected through field surveys from the districts of Hoshangabad and Mandla, between 2013 and 2017.
Figure 1 in the Paper: Study area map: Hoshangabad and Mandla districts
Predictive vegetation modelling was used to predict suitable habitats for these species under future climate scenarios for the years – 2050 and 2080. The objective of the study was to help management planning for the long-term resilience of these species.
After analyzing the available prediction models, the MaxEnt model was selected to determine the bioclimatic variables that govern the distribution of selected NTFPs in the region. Initially, 19 bioclimatic variables were selected under the broad categories of temperature and rainfall. To minimize overfitting of the model, highly correlated variables (with r>= 0.8) were removed for the final assessment (see table below).
Table 2 in the paper: Details of environmental variables used for modelling species response towards climate variations (variables shown in bold were selected for model run)
The contribution of a bioclimatic variable in determining species presence and distribution is specific to the species under investigation. However, considering the combined influence on all the species, rainfall of wettest quarter (Bio_16) was the most significant contributory variable. Its absence negatively impacts the growth and distribution of the species considerably. For all the species the growth stabilizes at 1600mm of rainfall. A small amount of rainfall (5-45 mm) in the driest quarter (Bio_17) has a positive influence on all the species, while its complete absence negatively affects every species. The mean diurnal range of temperature (Bio_2) has a positive effect on all the species except E. officinalis (Aonla). Mean temperature of 14 to 28 °C in the driest quarter (Bio_9) significantly helps in the growth of T. bellirica (Behera), T. chebula (Harad) and M. longifolia (Mahua).
Table 3 in the paper: Percentage contribution of selected environmental variables
The southeastern part of Madhya Pradesh, which has rich forest cover and is home to many biodiverse protected areas was found to be the most habitable place for the selected species, while the western part being unfavorable to most of these species currently.
Figure 5 in the paper: Potential current distribution of Madhuca longifolia, Buchanania lanzan, Emblica officinalis, Terminalia bellirica, Terminalia chebula and Sterculia urens in Madhya Pradesh
To predict the potential distribution of these species, the study used the representative concentration pathways (RCPs) approach by the IPCC, which represents four possible climate scenarios (RCP – 2.6, 4.5,6 and 8.5). All of these scenarios are possible depending on the greenhouse gas emissions in the years to come. The study indicated that M. longifolia (Mahua) is most resilient to climate change, with the possibility of increasing temperature and rainfall even having a positive influence on its distribution. All RCP scenarios have negative effect on B. lanzan (Achar) and T. chebula (Harad), with large areas proving to be of low suitability for these species in the future. These species may face survival risk if greenhouse gas emissions continue to rise at current pace. The model states that, the highly suitable areas for other three remaining species too would decrease in future. Under few RCP scenarios, M. longifolia (Mahua), S. urens (Butya/Kullu) and T. bellirica (Behera) showed expansion towards the central part of Madhya Pradesh. This shift from the currently most habitable eastern part may be due to the westward shift of rainfall pattern over northern India. This change in the rainfall pattern has also been reported in other studies such as Mall et al. (2007) and Yadav et al. (2019).
The study found that, for the state of Madhya Pradesh, the rainfall variation has been a more significant contributor than the temperature in determining species distribution. This is because, unlike higher latitudinal and temperate regions where temperature contributes significantly to species growth, the average temperature in the tropics usually never go below 17-18 degree Celsius. Other similar studies also pointed the rainfall as a strong determinant of suitability in central India (Chitale and Behera (2012) and Bahuguna (2018)); while rainfall, as well as temperature significantly determining the species distribution in the north-western Himalayas (Bahndari et al. (2020)), making these findings consistent with the other similar studies.
Credits: Amrita Neelakantan | NCCI Coordinator
Many forest dwellers in the region are dependent on the selected tree species for their livelihood and nutritional security. Changes in climatic factors that affect these species also affect the lives of people living in these forest fringes. Such forecasting, as in this study, can help in future management planning that involves conservation of these species and secure people’s livelihoods dependent on NTFP collection. Original Paper: Yadav, S., Bhattacharya, P., A reendran, G., Sahana, M., Raj, K. and Sajjad, H., 2021. Predicting impact of climate change on geographical distribution of major NTFP species in the Central India Region. Modeling Earth Systems and Environment, pp.1-20.
All Agriculture Community Participation Corridors Deforestation Human Health Human Wildlife Interactions Land Use Planning Livelihoods LULC Management Mining NCCI Pollution Project Update Science Summary Spatial Analyses Water Wildlife