Applying social factors in spatial analysis for planted forest ecosystems

Abstract

Forestation originated in the planting of forest plantations with timber-sourcing as a goal. The practice has since changed to include a much wider number of forest types and aims. In recent years, forestation efforts are increasingly focused on forest ecosystem generation. These forest ecosystems can have a wide variety of goals, including Climate Adaptation and Ecosystem-based Disaster Risk Reduction. Forest ecosystems can help in Disaster Risk Reduction in two ways; they can decrease exposure to disasters (for example through increasing soil stability and decreasing landslides) as well as increase community resilience (for example through diversifying the income of local communities). These forest ecosystems require a different project approach than forest plantations as they need to be sustained on a much longer time-scale and their success often depends on interaction with the surrounding communities. One part of the planning- and decision-making process of forestation projects is spatial analysis. Large scale spatial analysis used in the initial phases of forestation projects to identify suitable areas for forestation. Most current analyses focus on bio-physical factors for single tree species. However, forest ecosystems projects include a wider variety of species and social factors are crucial in their success. Therefore, this research aims to understand the possibility of using socio-economic factors as spatial indicators in the planning of forest ecosystem projects. In order to understand the possibility of using different indicators for forest ecosystem suitability analysis, a number of bio-physical and socio-economic indicators are compared to forestation success for existing forestation projects in Ethiopia. Forestation projects are assessed from 5 different organizations with a total of 12 projects and 67 forestation sites. A literature review is conducted to understand factors influencing forestation success. From all identified factors influencing forestation success, 11 indicators are chosen based on data availability and limiting overlap in effects. Despite its lack of representation of social and economic success, vegetation growth, using Normalized Difference Vegetation Index or NDVI is identified as the most reliable way to determine forestation success because of the availability of consistent data for all projects. The suitability indicators selected are: soil texture, drainage, pH of soil, minimum monthly rain, solar radiation, elevation, distance to closest road, population, GDP, land cover and district. The forestation sites show a minimal average increase in NDVI. However, it is also found that areas without forestation projects with similar environmental and social factors show an increase in NDVI as well. When the success indicators of the reference sites are compared to the increase in NDVI, we see that the suitability indicators do not show a significant relationship with the NDVI increase over active project years. The study shows the importance of standardized monitoring of forestation projects in order to gather not only bio-physical improvement but also social success, especially for projects with a social purpose. The use of satellite imagery to make forestation success assessments do not only give an incomplete understanding of the forestation project, the data availability in temporal and spatial scale and resolution limit the assessment. Additionally, the study shows the difficulty in comparing varying project types with different aims, timespans and sizes. More research is needed that includes a larger number of forestation projects that have similar goals, methods, timespan and sizes, as well as a standardized reporting of social and environmental success. This could be achieved by combining data from several similar countries and by working closely together with forestation organizations that have standardized monitoring of their projects on both social and environmental success.