Juvenile diversity of tree species in Theobroma cacao L. agroforestry and primary forest – Central Sulawesi, Indonesia

This thesis studies the tree species’ juvenile diversity in cacao (Theobroma cacao L.) based agroforestry and in primary forest in a natural conservation forest environment of Lore Lindu National Park, Sulawesi, Indonesia. Species’ adult composition in Lore Lindu National Park is relatively well studied, less is known about tree species’ diversity in seedling communities particularly in frequently disturbed cacao agroforestry field environment. Cacao production forms a potentially serious thread for maintaining the conservation areas pristine and forested in Sulawesi. The impacts of cacao production on natural environment are directly linked to the diversity and abundance of shade tree usage. The study aims at comparing differences between cacao agroforestry and natural forest in the surrounding area in their species composition in seedling and sapling size categories. The study was carried out in two parts. Biodiversity inventory of seedlings and saplings was combined with social survey with farmer interviews. Aim of the survey was to gain knowledge of the cacao fields, and farmers’ observations and choices regarding tree species associated with cacao. Data was collected in summer 2008. The assessment of the impact of environmental factors of solar radiation, weeding frequency, cacao tree planting density, distance to forest and distance to main park road, and type of habitat on seedling and sapling compositions was done with Non-metric Multidimensional Scaling (NMS). Outlier analysis was used to assess distorting variables for NMS, and Multi-Response Permutation Procedures (MRPP) analysis to differentiate the impact of categorical variables. Sampling success was estimated with rarefaction curves and jackknife estimate of species richness. In the inventory 135 species of trees and shrubs were found. Only some agroforestry related species were dominating. The most species rich were sapling communities in forest habitat. NMS was showing generally low linear correlation between variation of species composition and environmental variables. Solar radiation was having most significance as explaining variable. The most clearly separated in ordination were cacao and forest habitats. The results of seedling and sapling inventory were only partly coinciding with farmers’ knowledge of the tree species occurring on their fields. More research with frequent assessment of seedling cohorts is needed due to natural variability of cohorts and high mortality rate of seedlings.

Forest governance and climate change adaptation : Case studies of four African countries

Africa is threatened by climate change. The adaptive capacity of local communities continues to be weakened by ineffective and inefficient livelihood strategies and inappropriate development interventions. One of the greatest challenges for climate change adaptation in Africa is related to the governance of natural resources used by vulnerable poor groups as assets for adaptation. Practical and good governance activities for adaptation in Africa is urgently and much needed to support adaptation actions, interventions and planning. The adaptation role of forests has not been as prominent in the international discourse and actions as their mitigation role. This study therefore focused on the forest as one of the natural resources used for adaptation. The general objective of this research was to assess the extent to which cases of current forest governance practices in four African countries Burkina Faso, The Democratic Republic of Congo (DRC), Ghana and Sudan are supportive to the adaptation of vulnerable societies and ecosystems to impacts of climate change. Qualitative and quantitative analyses from surveys, expert consultations and group discussions were used in analysing the case studies. The entire research was guided by three conceptual sets of thinking forest governance, climate change vulnerability and ecosystem services. Data for the research were collected from selected ongoing forestry activities and programmes. The study mainly dealt with forest management policies and practices that can improve the adaptation of forest ecosystems (Study I) and the adaptive capacity through the management of forest resources by vulnerable farmers (Studies II, III, IV and V). It was found that adaptation is not part of current forest policies, but, instead, policies contain elements of risk management practices, which are also relevant to the adaptation of forest ecosystems. These practices include, among others, the management of forest fires, forest genetic resources, non-timber resources and silvicultural practices. Better livelihood opportunities emerged as the priority for the farmers. These vulnerable farmers had different forms of forest management. They have a wide range of experience and practical knowledge relevant to ensure and achieve livelihood improvement alongside sustainable management and good governance of natural resources. The contributions of traded non-timber forest products to climate change adaptation appear limited for local communities, based on their distribution among the stakeholders in the market chain. Plantation (agro)forestry, if well implemented and managed by communities, has a high potential in reducing socio-ecological vulnerability by increasing the food production and restocking degraded forest lands. Integration of legal arrangements with continuous monitoring, evaluation and improvement may drive this activity to support short, medium and long term expectations related to adaptation processes. The study concludes that effective forest governance initiatives led by vulnerable poor groups represent one practical way to improve the adaptive capacities of socio-ecological systems against the impacts of climate change in Africa.

Markov random fields and spatial smoothing in improving of forest inventory estimates

Markov random fields (MRF) are popular in image processing applications to describe spatial dependencies between image units. Here, we take a look at the theory and the models of MRFs with an application to improve forest inventory estimates. Typically, autocorrelation between study units is a nuisance in statistical inference, but we take an advantage of the dependencies to smooth noisy measurements by borrowing information from the neighbouring units. We build a stochastic spatial model, which we estimate with a Markov chain Monte Carlo simulation method. The smooth values are validated against another data set increasing our confidence that the estimates are more accurate than the originals.