Environmental Policy, Science & Technology: Illuminating the Interconnectivity of Global Ecology Through Maximum Entropy

Rapid climate change has become perceived as the major threat to planetary stability of our time, forcing fundamental changes to the multiple spheres of the climate system--the cryosphere, lithosphere, biosphere, hydrosphere--that make the Earth a livable planet. Though it may not sequester the most carbon at any given period of time, among these spheres the biosphere is responsible for the greatest flux in the carbon cycle. Climate change is also predicted to become a salient driver of biodiversity loss, exposing its influence on the biosphere as well. Under the climate change paradigm forests--a salient aspect of the biosphere--may be considered as both biodiversity and biosequestration (i.e. the sequestration of carbon via life) hotspots. Given the forest-climate interconnectivity potentially adverse feedbacks create a moral prerogative of stewardship illuminated by a strong environmental ethic. Thus, advanced statistical computer modeling--the Maximum Entropy model--was employed to test the effects of climate change on terrestrial ecology: namely forests. These Maximum Entropy, or MaxEnt, simulations specifically tested to see if potential future climate scenarios would lead to expansions or contractions in woodland areas of the three major forest biomes (i.e. boreal, temperate, and tropical) for comparative purposes. Modeling iterations with high levels of atmospheric CO2 concentrations--8.5 watts of radiative forcing for the 2050's and 2070's--forecasted the largest degree of woodland expansion to take place within the boreal region, whereas the Amazon region presented the least growth for such simulations. While simulations for the temperate zone divulged moderate growth on average under climate change we have already seen a great increase in disturbance regimes in the US--fires, droughts, pine beetle outbreaks--increasing tree mortality rates. Consequentially, valid first approximations were still able to be derived from subsequent modeling results for general regional policy recommendations, while such omissions in the parameterization of the model opened up the discussion to further recommendations for science and technology as well.