Topographic controls on the distribution of tree cover from local to global scales

Background/Question/Methods

Between 1850 and 1990, an estimated 2.8 billion hectares of forest have been lost to agriculture and harvest, releasing an estimated 108 Pg of carbon to the atmosphere, leading to population declines in many species, and putting stress on economic systems. Understanding the determinants of the spatial pattern of deforestation is crucial for land management and conservation decisions, but is hampered by poor integration of ecological factors with political and economic determinants. Further, because many deforestation studies are local or regional in scope, global pictures of the extent and pattern of deforestation have been difficult to obtain. Here, we seek to overcome these challenges with a global analysis of tree cover and tree cover change using MODIS remote sensing data. We focus particular attention on the role of topography over a wide range of spatial scales, asking whether topographic slopes provide refuges for tree cover in human-dominated landscapes. We then seek to understand spatial variation in this refuge effect with respect to political, economic and climatic predictors.

Results/Conclusions

There was a strong tendency for tree cover to be highest on slopes, across a wide range of spatial scales. This tendency depended strongly on human influence; in the absence of human pressures there was no relationship between tree cover and slope, while it became strongly positive as human impacts increased. Increases in tree cover between 2000 and 2005 were also more likely to occur on slopes than flats, particularly in the presence of high human impacts. The relationship between slope and tree cover also depended upon climate (particularly cumulative annual water deficit), economic context (particularly an index of ecological efficiency) and human demography (an index of population stress). There is a consistent, global, cross-scale relationship between tree cover and slope in human-dominated landscapes. Predictive models of future changes in tree cover – with important impacts on livelihoods, biodiversity, water yield, the atmosphere and climate – need to take this relationship into account.