Earth Observation in Support of the City Biodiversity Index

Today, we are living in an urban world. For the first time in history, there are now more people living in cities than in rural areas. In Europe their share has reached almost three quarters. Urban areas supposedly will absorb almost all the population growth expected over the next decades. This will pose a range of challenges for cities and their surroundings, not only on resource availability and the quality of urban environments, but also on biodiversity in cities. Capturing the status and trends of biodiversity and ecosystem services in urban landscapes represents an important part of understanding whether a metropolitan area is developing along a sustainable trajectory or not. Actions to conserve biodiversity should start with stock-taking and identifying baselines, followed by regular monitoring of conservation initiatives. The City Biodiversity Index (CBI), also known as the Singapore Index on Cities‘ Biodiversity (or Singapore Index) because of Singapore‘s leadership in its development, has been adopted during COP-9 of the CBD in 2008. It is conceived as a self-assessment tool to evaluate the state of biodiversity in cities and to provide insights for improving conservation efforts. This includes an initial baseline measurement, the identification of policy priorities based on their measurements and then a monitoring at periodic intervals. Today, the CBI includes 23 indicators from three categories such as the proportion of natural areas in the city or the budget allocated to conservation projects. The CBI is designed to be applied by many cities in the world to monitor their progress in conservation efforts and their success in halting the rate of biodiversity loss. The project provides support to 4 of the 23 indicators. The results illustrated below are based on satellite earth observation data combined with local in-situ information. The output of the data analysis (i.e. percentage or an area value) can be directly used to determine the relevant CBI score

Reimagining invasions; the social and cultural impacts of Prosopis on pastoralists in Southern Afar

Abstract Whilst the environmental impacts of biological invasions are clearly conceptualised and there is growing evidence on the economic benefits and costs, the social and cultural dimensions remain poorly understood. This paper presents the perceptions of pastoralist communities in southern Afar, Ethiopian lowlands, on one invasive species, Prosopis juliflora. The socio-cultural impacts are assessed, and the manner in which they interact with other drivers of vulnerability, including political marginalisation, sedentarisation and conflict, is explored. The research studied 10 communities and undertook semi-structured interviews and focus group discussions with pastoralists and agro-pastoralists. These results were supported by interviews with community leaders and key informants. The benefits and costs were analysed using the asset-based framework of the Sustainable Livelihoods Framework and the subject-focused approach of Wellbeing in Development. The results demonstrate that the costs of invasive species are felt across all of the livelihood capital bases (financial, natural, physical, human and social) highlighted within the framework and that the impacts cross multiple assets, such as reducing access through blocking roads. The concept of Wellbeing in Development provides a lens to examine neglected impacts, like conflict, community standing, political marginalisation and cultural impoverishment, and a freedom of definition and vocabulary to allow the participants to define their own epistemologies. The research highlights that impacts spread across assets, transcend objective and subjective classification, but also that impacts interact with other drivers of vulnerability. Pastoralists report deepened and broadened conflict, complicated relationships with the state and increased sedentarisation within invaded areas. The paper demonstrates that biological invasions have complex social and cultural implications beyond the environmental and economic costs which are commonly presented. Through synthesising methodologies and tools which capture local knowledge and perceptions, these implications and relationships are conceptualised

Unpacking ecosystem service bundles: towards predictive mapping of synergies and trade-offs between ecosystem services

Multiple ecosystem services (ES) can respond similarly to social and ecological factors to form bundles. Identifying key social-ecological variables and understanding how they co-vary to produce these consistent sets of ES may ultimately allow the prediction and modelling of ES bundles, and thus, help us understand critical synergies and trade-offs across landscapes. Such an understanding is essential for informing better management of multi-functional landscapes and minimising costly trade-offs. However, the relative importance of different social and biophysical drivers of ES bundles in different types of social-ecological systems remains unclear. As such, a bottom-up understanding of the determinants of ES bundles is a critical research gap in ES and sustainability science. Here, we evaluate the current methods used in ES bundle science and synthesize these into four steps that capture the plurality of methods used to examine predictors of ES bundles. We then apply these four steps to a cross-study comparison (North and South French Alps) of relationships between social-ecological variables and ES bundles, as it is widely advocated that cross-study comparisons are necessary for achieving a general understanding of predictors of ES associations. We use the results of this case study to assess the strengths and limitations of current approaches for understanding distributions of ES bundles. We conclude that inconsistency of spatial scale remains the primary barrier for understanding and predicting ES bundles. We suggest a hypothesis-driven approach is required to predict relationships between ES, and we outline the research required for such an understanding to emerge

Unveiling Undercover Cropland Inside Forests Using Landscape Variables: A Supplement to Remote Sensing Image Classification

The worldwide demand for food has been increasing due to the rapidly growing global population, and agricultural lands have increased in extent to produce more food crops. The pattern of cropland varies among different regions depending on the traditional knowledge of farmers and availability of uncultivated land. Satellite images can be used to map cropland in open areas but have limitations for detecting undergrowth inside forests. Classification results are often biased and need to be supplemented with field observations. Undercover cropland inside forests in the Bale Mountains of Ethiopia was assessed using field observed percentage cover of land use/land cover classes, and topographic and location parameters. The most influential factors were identified using Boosted Regression Trees and used to map undercover cropland area. Elevation, slope, easterly aspect, distance to settlements, and distance to national park were found to be the most influential factors determining undercover cropland area. When there is very high demand for growing food crops, constrained under restricted rights for clearing forest, cultivation could take place within forests as an undercover. Further research on the impact of undercover cropland on ecosystem services and challenges in sustainable management is thus essential