Drivers of deforestation in the basin of the Usumacinta River: Inference on process from pattern analysis using generalised additive models.

Quantifying patterns of deforestation and linking these patterns to potentially influencing variables is a key component of modelling and projecting land use change. Statistical methods based on null hypothesis testing are only partially successful for interpreting deforestation in the context of the processes that have led to their formation. Simplifications of cause-consequence relationships that are difficult to support empirically may influence environment and development policies because they suggest simple solutions to complex problems. Deforestation is a complex process driven by multiple proximate and underlying factors and a range of scales. In this study we use a multivariate statistical analysis to provide contextual explanation for deforestation in the Usumacinta River Basin based on partial pattern matching. Our approach avoided testing trivial null hypotheses of lack of association and investigated the strength and form of the response to drivers. As not all factors involved in deforestation are easily mapped as GIS layers, analytical challenges arise due to lack of a one to one correspondence between mappable attributes and drivers. We avoided testing simple statistical hypotheses such as the detectability of a significant linear relationship between deforestation and proximity to roads or water. We developed a series of informative generalised additive models based on combinations of layers that corresponded to hypotheses regarding processes. The importance of the variables representing accessibility was emphasised by the analysis. We provide evidence that land tenure is a critical factor in shaping the decision to deforest and that direct beam insolation has an effect associated with fire frequency and intensity. The effect of winter insolation was found to have many applied implications for land management. The methodology was useful for interpreting the relative importance of sets of variables representing drivers of deforestation. It was an informative approach, thus allowing the construction of a comprehensive understanding of its causes.

Are Mayan community forest reserves effective in fulfilling people's needs and preserving tree species?

Mayan community forest reserves (MCFR) play an important role in agricultural landscapes in Mexico, as they provide forest products and a broad variety of benefits that contribute to improving local people's livelihoods. Nevertheless, academia has generally considered conservation and use of forest resources to be incompatible. We describe the spatial configuration of MCFR, evaluate floristic and structural characteristics of woody vegetation present in selected reserves, and identify social norms that govern use and conservation of MCFR. These reserves largely consist of mature vegetation (80% of total cover); their plant structure is similar to that of the surrounding tropical sub-deciduous forest; and they house a large number of endemic species. The MCFR studied contain a total of 146 tree species and cover 11% of the study area, which includes at least 140 villages in the north-central part of the Yucatan Peninsula. These reserves are collectively managed and conserved by Mayan peasants in the interest of the common good. The communities in our study area combine conservation and use of forest resources, and we recommend that in public policy, government agencies and NGOs incorporate MCFR as a model of biological conservation and sustainable natural resource use, taking into account traditional knowledge and local norms that allow these reserves to function in a sustainable manner.