Statistical analysis and feedback exploration of land use change determinants at local scale in the Brazilian Amazon

This work focus on two municipalities established first as rural settlements in Rondonia State in 1982. These two municipalities consist on a unique land use change study due to the differences in settlements planning, but also because they are part of recent frontiers of deforestation. The main land use patterns in the study area are mainly related to small farmers. However, medium and big farms, mineral extraction and timber exploration are also expressive. To understand the land use and land change processes, we have investigated and connected these different patterns to their possible causes and driving forces. This was realized by the use of statistical analysis and spatial-temporal modeling. The simulation was useful as learning tool to explore previous feedbacks of deforestation observed during fieldwork campaigns in the are

Road development in the Brazilian Amazon and its ecological implications

Roads are a distinctive feature in any landscape, with many countries giving 1-2% of their land surface over to roads and roadsides (Forman 1998). However, the ecological effects of roads spread beyond the physical footprint of the network and may impact 15-20% of the land or more (Forman & Alexander 1998). The Brazilian Amazon contains approximately one third of the world’s remaining rainforest, covering an area of 4.1 million km2. The region is highly biodiverse with 10-20 percent of the planet’s known species, it is also one of the three most bioculturally diverse areas in the world (Loh & Harmon 2005), and it provides many valuable ecosystem services. However, the Brazilian Amazon is rapidly undergoing extensive development with widespread land-use conversion. Road development is often perceived as the initial stage of development, opening access to remote areas for colonisation, agriculture development, resource extraction, and linked with these; deforestation (Chomitz & Gray 1996, Laurance et al. 2001, Perz et al. 2007, Laurance et al. 2009, Caldas et al. 2010). As such roads are a key spatial determinant of land use conversion in the Amazon region, dictating the spatial pattern of deforestation and biodiversity loss (Fearnside 2005, Kirby et al. 2006, Perz et al. 2008). Given that roads are a key spatial determinant of land use conversion and that they have extensive impacts on rates and patterns of habitat loss, it is important that we know how much, how fast and where road networks are developing in this globally important ecosystem. In this thesis, I aim to construct models of road network development to help better understand and predict the impacts of economic development in the Brazilian Amazon.Open Acces

Modelling land cover change in tropical rainforests

Tropical deforestation is one of the most important drivers of biodiversity loss and carbon emissions. This thesis seeks to analyse the dynamics of tropical deforestation and develop a probabilistic model that predicts land cover change (LCC) in the tropics. The main findings from the analysis of the Brazilian Amazon deforestation dynamics are that large clearings comprised progressively smaller amounts of total annual deforestation while the number of smaller clearings remained unchanged over time. These changes were coincident with the implementation of conservation policies by the government. The review of LCC models presented here showed that this modelling community would benefit from improving: the openness to share model inputs, code and outputs; model validations; and standardised frameworks to be used for model comparisons. The modelling framework developed aimed to tackle the limitations found before and two scenarios of deforestation in the Brazilian Amazon were simulated. For both scenarios forest next to roads and areas already deforested were found to be more likely to be deforested. States in the south and east of the region showed high predicted probability of losing nearly all forest outside of protected areas by 2050. The release of carbon to the atmosphere is an important consequence of tropical deforestation. Even if deforestation had ended in 2010 there would still be large quantities of carbon to be released. The amount of carbon released immediately is higher than the one committed for future release in the first few years of analysis, but presently these accounted for at least two-thirds of total carbon emissions. Finally, the drivers of LCC were found to vary among transition types, but less so through time. The accuracy of the model predictions was heavily dependent on the year calibrated, suggesting that a widespread reliance on single calibration time period may be providing biased predictions of future LCC

Land use and land cover dynamics in the Brazilian Amazon: understanding human-environmental interactions

Land use and land cover dynamics are a result of the interactions between human activities and the environment. The objective of this thesis is to analyze Amazonian land use and land cover pattern dynamics in order to identify the underlying system dynamics. By combining empirical statistical models and Fuzzy Cognitive Mapping, feedbacks in the human-environment system can be explored to identify more sustainable development pathways. The results show that specific feedback loops can lead to a sustainable human-environment system in the Brazilian Amazon, e.g., in case policies such as Payment for Ecosystems Services (PES) and Reducing Emissions from Deforestation and Forest Degradation (REDD) are enforced. Also, the analysis indicates that land market regulations and the enforcement of the Forestry Code can reduce deforestation. It is concluded that policy effectiveness of sustainable land use practices can be better evaluated by using the combination of statistical and cognitive methods. In summary, the thesis illustrates that added value in analyzing land system changes is achieved if insights obtained at different scales are combined through different methods of analysis.</p