PREDICTING TROPICAL RAINFOREST DEFORESTATION USING MACHINE LEARNING, REMOTE SENSING & GIS: CASE STUDY OF THE CROSS RIVER NATIONAL PARK, NIGERIA

Population growth, urban sprawl, agricultural expansion, and illegal logging has led to losses in forested land in most parts of the world, especially in a highly populated country like Nigeria. The Cross River National Park (CRNP) in southeastern Nigeria with an area just above 4000km2 is designated a biodiverse hotspot and one of the oldest rainforests in Africa. As with all other tropical forests spread across the globe the CRNP is not immune to these factors that threaten its existence. The focus of this study is to analyze the change of forest cover at the Oban division of the Cross River National Park using multi-temporal remotely sensed data to predict and model the future probability of deforestation within the area of interest. This study made use of the Landsat West Africa Land Use/Land Cover Time Series dataset for the years 1975, 2000 and 2013 and Landsat 8 operational land imager (OLI) imagery for the year 2020 in a post classification change detection model to determine the extent of change in forest cover classes. Random forest decision tree machine learning algorithm was used to predict the future risk of forest cover loss using the datasets produced from the post classification change detection. The model related deforestation probabilities with several physical and anthropogenic factors such as elevation, slope angle, solar radiation, aspect, topographic roughness, soil type, distance from roads, distance from towns, distance from rivers, distance from plantations and population density. The results from the change detection analysis showed that from 1975 to 2020 the forest cover declined by 1909km2 a rate of 42km2 per year. The random forest regression analysis predicted areas of the forest with modest to high deforestation probabilities and indicated that socio-economic factors are major drivers of deforestation in the region rather than physical factors

Desertification

IPCC SPECIAL REPORT ON CLIMATE CHANGE AND LAND (SRCCL) Chapter 3: Climate Change and Land: An IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystem

Integrative Assessment and Modelling of the Non Timber Forest Products Potential in Nuba Mountains of Sudan by Field Methods, Remote Sensing and GIS

Pressure imposed at any one place or point in time results in a complexity of spatial and temporal interactions within topographical ecosystems. It can be propagated through the system and may have implications for future ecosystem functions over a wide array of various spatial and temporal scales. Under conditions of wars and other socio-economic conflicts, these processes are most forceful in developing countries amidst declining economic growth, lack of awareness, deterioration of ecosystem services, loss of existing traditional knowledge bases and weak governance structures. Forests are an essential part of ecosystem services, not only as a resource but as a contributor to biological systems as well. They represent one of the most important sectors in the context of Environmental Change (EC), both from the point of mitigation as well as adaptation. While forests are projected to be adversely impacted under EC, they are also providing opportunities to mitigate these changes. Yet this is one of the least understood sectors, especially at the regional level - many of its fundamental metrics such as mitigation potential, vulnerability and the likely impacts of EC are still not well understood until now. Thus, there is a need for research and field investigations into the synergy of mitigation and adaptation so that the cost of addressing EC impacts can be reduced and the co-benefits can be increased. The aim of this study is to focus particularly on forest-based ecosystem services and to use forests as a strategy for inducing environmental change within the Nuba Mountains in Sudan, specifically for systems in poor condition under EC, and furthermore to explore forests as an entry point for investigating the relationship between urban and rural development and ecosystem services. In addition, the aim is also to raise understanding of the relations between patterns of local-level economic and demographic changes, the nature and value of local ecosystem services, and the role of such services in increasingly interlinked urban and rural livelihood systems. The methodology applied in the current research is three-pronged: a formal literature review, a socio–economic survey (based on semi-structured interviews of household heads via Rapid Rural Appraisal (RRA), with a focus on group discussions, informal meetings, free listening and key informant techniques), and multitemporal optical satellite data analysis (i.e. Landsat and RapidEye). Landsat imagery was utilized to gather the spatial characteristics of the region and to study the Land Use/Land Cover (LU/LC) changes during the period from 1984 to 2014. Meanwhile, RapidEye imagery was used to generate the tree species distribution map. Qualitative and quantitative techniques were applied to analyze socio-economic data. Moreover, Food Consumption Score (FCS) was used to gauge both diversity and frequency of food consumption in surveyed areas. Geographic object-based image analysis (i.e. K-Nearest Neighbour classifier and knowledge-based classifiers) based on a developed model of integrated features (such as vegetation indices, DEM, thematic layers and meteorological information) was applied. Post Classification Analysis (PCA) as well as Post Change Detection (PCD) techniques were used. Hotspot analysis was conducted to detect the areas affected by deforestation. Furthermore, Ordinary Least Squares regression (OLS), Autocorrelation (Moran's) analysis, and Geographically Weighted Regression analyses (GWR) were applied to address the interaction of the different socioeconomic/ecological factors on Non Timber Forest Products (NTFPs) collection and to simulate the dependency scenarios of NTFPs along with their impact on poverty alleviation. Additionally, simulation was performed to estimate the future forest density and predict the dependency on forest services. An increasing impact of intensive interactions between the rural and urban areas has long been acknowledged. However, recent changes in the global political economy and environmental systems, as well as local dynamics of the study area driven by war, drought and deforestation, have led to an increasing rapidity and depth in rural transformation, as well as to a significant impact on urban areas. Like most environmental problems, the effects of these drivers are complex and are stressed diversely across different geographic regions by the socio-political processes that underlie recent economic and cultural globalization. These interactions and processes have increasingly brought rapid changes in land cover, social, institutional and livelihood transformation across broad areas of South Kordofan. Moreover, the study unveils new dynamics such as high rates of migration and mobility by the indigenous population and the increasing domination of market-centric livelihoods in many villages that were once dominated by rural agricultural and natural resourcesbased socio-economic systems. Furthermore, the research highlights the significant roles of NTFPs and trees in contributing to Nuba Mountains’ economic development, food security and environmental health, indicating which requirements need to be addressed in order to improve these potentials. The study proves that drawing on a wide range of these products for livelihood strengthens rural people’s ability to deal with and adapt to both EC and extreme events. Moreover, the results underline the importance of participatory approaches of rural women and their impact on NTFPs management with recommendations of more emphasis on potential roles and the ability of women to participate in public fora. Furthermore, the study shows that the use of high-resolution satellite imagery, integrated with model-based terrestrial information, provides a precise knowledge about the magnitude and distribution of LU/LC patterns. These methods can make an important contribution towards a better understanding of EC dynamics over time. The study reveals that more information exchange is needed to inform actors and decision makers regarding specific experiences, capacity gaps and knowledge to address EC. Subsequently, new policies and strategies are required to much more specifically focus on how to deal with consequences of longer-term EC rather than with the impacts of sudden natural disasters

Improved land management in the Lake Victoria Basin: Final report on the TransVic project

This report addresses the challenges of land management in the Lake Victoria basin of East Africa. In 1999 the World Agroforestry Centre launched a major effort to identify, diagnose and reverse degradation in the Lake Victoria basin, focusing primarily on the Kenyan part of the basin. Dubbed “TransVic,” this project was supported by a number of donor agencies and collaborators, with particularly strong support from the Swedish International Development Cooperation Agency (Sida). Field activities in the Kenyan part of the basin were undertaken with Kenya’s National Agriculture and Livestock Extension Programme. This report summarizes the major achievements of TransVic from 1999 to the end of 2004. The project greatly improved understanding of land degradation processes, costs and hotspots, the linkages between poverty, degradation and water resource management, and the possibilities for and constraints to solving those problems through various technical and institutional approaches. The research and development agenda for the region is now able to concentrate on the investments in land and water resources that can curtail degradation and help restore these degraded resources

The telecoupled sustainability impacts of global agricultural value chains:Assessing the cross-scale sustainability impacts of the cocoa sector

Agriculture is a major contributor to the global environmental crisis. Natural ecosystems are being replaced by agricultural land, which leads to the extinction of species and the release of tons of carbon emissions. Global agricultural value chains (GVCs) have grown due to the intensification of international trade. While GVCs have undeniably created economic opportunities for the agriculture sector, they have also led to the escalation of local environmental issues. Several initiatives have been implemented to reduce the negative impacts of agriculture, including government regulations, sustainability certification labels, and voluntary sustainability commitments. However, the effectiveness of these initiatives has been questioned due to several reasons, including the mismatches between the scale of the problem and the solution, the lack of monitoring and verification of sustainability actions, and their weak enforcement. Sustainability initiatives are informed by studies assessing the impacts of agriculture that often only focus on local impacts, while disregarding larger-scale – telecoupled– dynamics that can trigger impacts across geographic and temporal scales. This thesis aims to help bridge these knowledge gaps by examining the impacts of agricultural GVCs across scales, studying the role of GVC’s configuration in modulating these impacts and investigating the role of GVC actors in mitigating sustainability risks across scales. The global cocoa value chain is used as a case study. Chapter 2 examines various impact assessment methods and their ability to capture the effects caused by telecoupled dynamics across different scales. The study concludes that no single method is sufficient to capture all telecoupled cross-scale dynamics and that the integration of different methods is necessary to bridge gaps between methods and complement their scope. Chapter 3 implements the recommendations outlined in Chapter 2 by analyzing the impacts caused by cocoa agroforestry and cocoa full-sun production in Ghana. Impacts on carbon, biodiversity stocks, and environmental pollution were analyzed within and beyond the farm-level. This chapter reveals that findings drawn from farm-level assessments can contradict those from landscape-level assessments. Decision-makers focused should be wary of extrapolating farm-level assessment results to larger scales. Chapter 4 expands the scope to the global scale by examining the role of the cocoa GVC configuration on the capacity of the sector to address sustainability challenges across scales. The chapter identifies different types of cocoa traders, their market dominance, and sustainability commitments. The chapter highlights that to address the telecoupled impacts of the cocoa GVC, coordinated action between traders is required, along with government interventions to balance power asymmetries. Chapter 5 measured the degree to which cocoa traders, as identified in Chapter 4, are exposed to deforestation and climate change. This chapter highlights that sustainability challenges in agricultural value chains cannot be resolved in isolation as farming systems are constantly interacting with other farming systems and land competing sectors. To avoid displacing negative impacts across scales, it is necessary to have a coordinated and collaborative effort from stakeholders and sectors involved in making decisions related to land use. This thesis shows that addressing the telecoupled impacts caused by agricultural value chains needs a good understanding of the cause-effect dynamics at play. This requires the quantification of impacts caused by agriculture across scales and the characterization of the GVC network of actors modulating these impacts. Interdisciplinary methods need to be leveraged and integrated to generate actionable insights. The findings of this thesis can assist decision-makers and private actors in devising customized sustainability strategies, prioritizing action, and addressing the most vulnerable hotspots while being mindful of global teleconnections and avoiding spillovers

Epidemiology of the zoonotic malaria Plasmodium knowlesi in changing landscapes

Within the past two decades, incidence of human cases of the zoonotic malaria Plasmodium knowlesi has increased markedly. P. knowlesi is now the most common cause of human malaria in Malaysia and threatens to undermine malaria control programmes across Southeast Asia. The emergence of zoonotic malaria corresponds to a period of rapid deforestation within this region. These environmental changes impact the distribution and behaviour of the simian hosts, mosquito vector species and human populations, creating new opportunities for P. knowlesi transmission. Here, we review how landscape changes can drive zoonotic disease emergence, examine the extent and causes of these changes across Southeast and identify how these mechanisms may be impacting P. knowlesi dynamics. We review the current spatial epidemiology of reported P. knowlesi infections in people and assess how these demographic and environmental changes may lead to changes in transmission patterns. Finally, we identify opportunities to improve P. knowlesi surveillance and develop targeted ecological interventions within these landscapes

Protected Area Management

Until recently, values and benefits from protected areas have often been underestimated as well as taken for granted. Protected Area Management - Recent Advances demonstrates that there are deep necessities in how the wider scientific, environmental, socioeconomic, and cultural values that these natural ecosystems provide should increasingly be recognized. The book highlights various approaches for managing and conserving protected areas to respond to some pressing global challenges such as climate change, demand for food and energy, overexploitation, and habitat change. It addresses these issues in five main sections that cover biodiversity and genetic resources; protected marine areas; community, ecotourism, and protected areas; and protected area conservation and monitoring