Quantifying Environmental Drivers of Future Tropical Forest Extent

Abstract

Future changes in atmospheric greenhouse gas concentrations, and their associated influences on climate, will affect the future sustainability of tropical forests. While dynamic global vegetation models (DGVMs) represent the processes by which climate and vegetation interact, there is limited quantitative understanding of how specific environmental drivers each affect the simulated patterns of vegetation behavior and the resultant tropical forest fraction. Here, an attempt is made to improve on the qualitative understanding of how changes in dry season length, temperature, and CO2 combine to drive forest changes. Investigation of these topics is undertaken by integrating the Hadley Centre Climate Model version 3, run at lower spatial resolution with a coupled climate?carbon cycle (HadCM3LC), to steady state. This represents the situation where vegetation has adjusted fully to the prevailing climate and vice versa, permitting direct analysis of how climate and vegetation interact. These links are quantified by fitting the simulated tropical broadleaf tree fraction with a simple function of CO2 concentration, surface temperature, and dry season length. The resulting empirical function (denoted dry season resilience or DSR) is able to predict a sustainable tropical broadleaf fraction in this model across a very wide range of climates. The DSR function can also be used to compare the importance of different environmental drivers and to explore other emissions scenarios. While this DSR function is specific to the vegetation?land surface scheme in HadCM3LC, the method employed in this work is applicable to steady-state simulations from other vegetation?land surface schemes. The DSR metric is applied first as a framework to evaluate the DGVM by comparison of the simulated and observed forest fractions. For tropical broadleaf resilience in this model, a warming of 1°C is approximately equivalent to a 2-week increase in dry season. In HadCM3LC climate model projections under the International Panel on Climate Change?s (IPCC?s) Special Report on Emissions Scenarios (SRES) A1B scenario, twenty-first-century increases in forest resilience due to CO2 fertilization approximately balance the tropical mean decrease from warming (the relative importance of rainfall and temperature changes depends on the uncertain spatial pattern of rainfall change). DSR is a tool that could be applied to different vegetation models to help us understand and narrow uncertainty in tropical forest projections.