Here we introduce a new feature from the Center for the Study of Science, “On the Bright Side.” OBS will highlight the beneficial impacts of human activities on the state of our world, including improvements to human health and welfare, as well as the natural environment. Our emphasis will typically focus on the oft-neglected positive externalities of carbon dioxide emissions and associated climate change. Far too often, the media, environmental organizations, governmental panels and policymakers concentrate their efforts on the putative negative impacts of potential CO2-induced global warming. We hope to counter that pessimism with a heavy dose of positive reporting on the considerable good humans are doing for themselves and for the planet.
According to Piao et al. (2015), the reliable detection and attribution of changes in vegetation growth are essential prerequisites for “the development of successful strategies for the sustainable management of ecosystems.” And indeed they are, especially in today’s world in which so many scientists and policy makers are concerned with what to do (or not do) about the potential impacts of CO2-induced climate change. However, detecting vegetative change, let alone determining its cause, can be an extraordinarily difficult task to accomplish. Nevertheless, that is exactly what Piao et al. set out to do in their recent study.
More specifically, the team of sixteen Chinese, Australian and American researchers set out to investigate trends in vegetational change across China over the past three decades (1982-2009), quantifying the contributions from different factors including (1) climate change, (2) rising atmospheric CO2 concentrations, (3) nitrogen deposition and (4) afforestation. To do so, they used three different satellite-derived Leaf Area Index (LAI) datasets (GLOBMAP, GLASS, and GIMMIS) to detect spatial and temporal changes in vegetation during the growing season (GS, defined as April to October), and five process-based ecosystem models (CABLE, CLM4, ORCHIDEE, LPJ and VEGAS) to determine the attribution.