Dynamic forest vegetation models for predicting impacts of climate change on forests: An Indian perspective

Understanding climate change vulnerability of Indian forests has received wider attention in recent years and a number of assessments with different approaches have emerged over time. These assessments have mostly used climate-sensitive vegetation models to explain the climate change impacts. In these studies, trees constituting a particular forest are often clubbed together into small number of groups having similar functional traits referred as Plant Functional Types (PFTs). Most of the Forest Vegetation Models (FVMs) are still in their developmental stage and there have been attempts at various levels to develop more versatile and precise models. Several developing countries, including India, still lag behind in developing dynamic vegetation models (DVMs), which could be appropriate for the local applications to predict the impact on forests at regional level. This is restrained mainly because of the lack of long-term observations with respect to various interacting biotic, abiotic and climatic (or environmental) variables in a forest ecosystem, like water and nitrogen use efficiency, response to elevated concentration of CO2, nutrient cycling, net primary productivity, etc. The observations on influence of the environmental variables on forest ecosystems are available in discrete form. Existing FVMs integrate observations more appropriately for their place of origin for which they have been developed. Different types of forests in different climatic zones are supposed to respond differently to climatic changes. Hence, it is imperative that models are developed for the specific biogeographic regions in order to predict the influences more accurately. It may not be wise to use existing FVMs in their pristine form for all of the region without considering the regional influences. Various challenges associated with the usage of the generic models of external origin with special reference to Integrated Biosphere Simulator (IBIS) model - being widely used and accepted in Indian policy documents- is presented in this paper. We also discuss on the need for developing a regional FVM for climate change impact studies, so that the impact prediction is more precise and reliable.

Influence of Soil Properties in Different Management Systems: Estimating Soybean Water Changes in the Agro-IBIS Model

The water balance in agricultural cropping systems is dependent on the physical and hydraulic characteristics of the soil and the type of farming, both of which are sensitive to the soil management. Most models that describe the interaction between the surface and the atmosphere do not efficiently represent the physical differences across different soil management areas. In this study, the authors analyzed the dynamics of the water exchange in the agricultural version of the Integrated Biosphere Simulator (IBIS) model (Agro-IBIS) in the presence of different physical soil properties because of the different long-term soil management systems. The experimental soil properties were obtained from two management systems, no tillage (NT) and conventional tillage (CT) in a long-term experiment in southern Brazil in the soybean growing season of 2009/10. To simulate NT management, this study modified the top soil layer in the model to represent the residual layer. Moreover, a mathematical adjustment to the computation of leaf area index (LAI) is suggested to obtain a better representation of the grain fill to the physiological maturity period. The water exchange dynamics simulated using Agro-IBIS were compared against experimental data collected from both tillage systems. The results show that the model well represented the water dynamics in the soil and the evapotranspiration (ET) in both management systems, in particular during the wet periods. Better results were found for the conventional tillage management system for the water balance. However, with the incorporation of a residual layer and soil properties in NT, the model improved the estimation of evapotranspiration by 6%. The ability of the Agro-IBIS model to estimate ET indicates its potential application in future climate scenarios.