Methodological Challenges in Sustainability Science: A Call for Method Plurality, Procedural Rigor and Longitudinal Research

Sustainability science encompasses a unique field that is defined through its purpose, the problem it addresses, and its solution-oriented agenda. However, this orientation creates significant methodological challenges. In this discussion paper, we conceptualize sustainability problems as wicked problems to tease out the key challenges that sustainability science is facing if scientists intend to deliver on its solution-oriented agenda. Building on the available literature, we discuss three aspects that demand increased attention for advancing sustainability science: 1) methods with higher diversity and complementarity are needed to increase the chance of deriving solutions to the unique aspects of wicked problems; for instance, mixed methods approaches are potentially better suited to allow for an approximation of solutions, since they cover wider arrays of knowledge; 2) methodologies capable of dealing with wicked problems demand strict procedural and ethical guidelines, in order to ensure their integration potential; for example, learning from solution implementation in different contexts requires increased comparability between research approaches while carefully addressing issues of legitimacy and credibility; and 3) approaches are needed that allow for longitudinal research, since wicked problems are continuous and solutions can only be diagnosed in retrospect; for example, complex dynamics of wicked problems play out across temporal patterns that are not necessarily aligned with the common timeframe of participatory sustainability research. Taken together, we call for plurality in methodologies, emphasizing procedural rigor and the necessity of continuous research to effectively addressing wicked problems as well as methodological challenges in sustainability science

Delivering community benefits through REDD +: Lessons from Joint Forest Management in Zambia

In implementing reducing emissions from deforestation and degradation (REDD), significant attention is being paid to ensuring that communities stand to benefit. Safeguards to protect local people's rights and interests have been formulated in response concerns over the potential negative impact on communities of forest preservation. To fulfil safeguards, many sub-Saharan African countries are looking to community-based natural resource management (CBNRM). Current critiques of CBNRM projects outline the importance of project design and policy context in shaping whether or not communities actually stand to benefit. This paper explores these aspects in a case study of Joint Forest Management (JFM) in Zambia, and examines the role of Zambia's REDD preparedness programme in shaping them. The case study was evaluated using stakeholder and policy document analyses, informed by interviews, and tied into the broader forest governance network. The findings highlight the way in which the politics and policies of forest governance in Zambia shape the on-the-ground JFM project and influence community benefits. In the case studied, even with careful local-level project design, JFM would be hindered in its delivery of REDD safeguards. Therefore, for REDD to deliver community safeguards, it must be considered as a broader process of political and governance change

Level Set Segmentation with Shape and Appearance Models Using Affine Moment Descriptors

We propose a level set based variational approach that incorporates shape priors into edge-based and region-based models. The evolution of the active contour depends on local and global information. It has been implemented using an efficient narrow band technique. For each boundary pixel we calculate its dynamic according to its gray level, the neighborhood and geometric properties established by training shapes. We also propose a criterion for shape aligning based on affine transformation using an image normalization procedure. Finally, we illustrate the benefits of the our approach on the liver segmentation from CT images

Probabilistic Atlas Based Segmentation Using Affine Moment Descriptors and Graph-Cuts

We show a procedure for constructing a probabilistic atlas based on affine moment descriptors. It uses a normalization procedure over the labeled atlas. The proposed linear registration is defined by closed-form expressions involving only geometric moments. This procedure applies both to atlas construction as atlas-based segmentation. We model the likelihood term for each voxel and each label using parametric or nonparametric distributions and the prior term is determined by applying the vote-rule. The probabilistic atlas is built with the variability of our linear registration. We have two segmentation strategy: a) it applies the proposed affine registration to bring the target image into the coordinate frame of the atlas or b) the probabilistic atlas is non-rigidly aligning with the target image, where the probabilistic atlas is previously aligned to the target image with our affine registration. Finally, we adopt a graph cut - Bayesian framework for implementing the atlas-based segmentation

Soil Functions & Ecosystem Services

In order to fulfil RECARE’s aim to quantify in a harmonized, spatially explicit way impacts of degradation and conservation on soil functions and ecosystem services, it is important to understand the concept and review the current scientific debate. This will lay the foundation for the development and selection of appropriate methods to measure, evaluate, communicate and negotiate the services we obtain from soils with stakeholders in order to improve land management. Despite various research activities in the last decades across the world, many challenges remain to integrate the concept of ecosystem services (ES) in decision-making, and a coherent approach to assess and value ES is still lacking (de Groot et al., 2010). There are many different, often context-specific, ES frameworks with their own definitions and understanding of terms. This chapter therefore aims to identify the state of the art and knowledge gaps in order to develop an operational framework of the ES concept for the RECARE project. It will provide an overview on existing soil functions and ES frameworks and on approaches to monitor and value ES, with a special focus on soil aspects. Furthermore, it will address the question how the ES concept is operationalized in research projects and land management in Europe so far. Based on this review, the chapter concludes with a suggestion of an adapted ES framework for RECARE and on how to operationalize it for practical application in preventing and remediating degradation of soils in Europe

Soil Functions & Ecosystem Services

In order to fulfil RECARE’s aim to quantify in a harmonized, spatially explicit way impacts of degradation and conservation on soil functions and ecosystem services, it is important to understand the concept and review the current scientific debate. This will lay the foundation for the development and selection of appropriate methods to measure, evaluate, communicate and negotiate the services we obtain from soils with stakeholders in order to improve land management. Despite various research activities in the last decades across the world, many challenges remain to integrate the concept of ecosystem services (ES) in decision-making, and a coherent approach to assess and value ES is still lacking (de Groot et al., 2010). There are many different, often context-specific, ES frameworks with their own definitions and understanding of terms. This chapter therefore aims to identify the state of the art and knowledge gaps in order to develop an operational framework of the ES concept for the RECARE project. It will provide an overview on existing soil functions and ES frameworks and on approaches to monitor and value ES, with a special focus on soil aspects. Furthermore, it will address the question how the ES concept is operationalized in research projects and land management in Europe so far. Based on this review, the chapter concludes with a suggestion of an adapted ES framework for RECARE and on how to operationalize it for practical application in preventing and remediating degradation of soils in Europe

Statistical Model of Shape Moments with Active Contour Evolution for Shape Detection and Segmentation

This paper describes a novel method for shape representation and robust image segmentation. The proposed method combines two well known methodologies, namely, statistical shape models and active contours implemented in level set framework. The shape detection is achieved by maximizing a posterior function that consists of a prior shape probability model and image likelihood function conditioned on shapes. The statistical shape model is built as a result of a learning process based on nonparametric probability estimation in a PCA reduced feature space formed by the Legendre moments of training silhouette images. A greedy strategy is applied to optimize the proposed cost function by iteratively evolving an implicit active contour in the image space and subsequent constrained optimization of the evolved shape in the reduced shape feature space. Experimental results presented in the paper demonstrate that the proposed method, contrary to many other active contour segmentation methods, is highly resilient to severe random and structural noise that could be present in the data

Approximations of Shape Metrics and Application to Shape Warping and Empirical Shape Statistics

International audienceThis chapter proposes a framework for dealing with two problems related to the analysis of shapes: the definition of the relevant set of shapes and that of defining a metric on it. Following a recent research monograph by Delfour and Zolésio [8], we consider the characteristic functions of the subsets of ℝ2 and their distance functions. The L 2 norm of the difference of characteristic functions and the L∞ and the W 1,2 norms of the difference of distance functions define interesting topologies, in particular that induced by the well-known Hausdorff distance. Because of practical considerations arising from the fact that we deal with image shapes defined on finite grids of pixels, we restrict our attention to subsets of ℝ2 of positive reach in the sense of Federer [12], with smooth boundaries of bounded curvature. For this particular set of shapes we show that the three previous topologies are equivalent. The next problem we consider is that of warping a shape onto another by infinitesimal gradient descent, minimizing the corresponding distance. Because the distance function involves an inf, it is not differentiable with respect to the shape. We propose a family of smooth approximations of the distance function which are continuous with respect to the Hausdorff topology, and hence with respect to the other two topologies. We compute the corresponding Gâteaux derivatives. They define deformation flows that can be used to warp a shape onto another by solving an initial value problem. We show several examples of this warping and prove properties of our approximations that relate to the existence of local minima. We then use this tool to produce computational de.nitions of the empirical mean and covariance of a set of shape examples. They yield an analog of the notion of principal modes of variation. We illustrate them on a variety of examples

An applied methodology for stakeholder identification in transdisciplinary research

In this paper we present a novel methodology for identifying stakeholders for the purpose of engaging with them in transdisciplinary, sustainability research projects. In transdisciplinary research, it is important to identify a range of stakeholders prior to the problem-focussed stages of research. Early engagement with diverse stakeholders creates space for them to influence the research process, including problem definition, from the start. However, current stakeholder analysis approaches ignore this initial identification process, or position it within the subsequent content-focussed stages of research. Our methodology was designed as part of a research project into a range of soil threats in seventeen case study locations throughout Europe. Our methodology was designed to be systematic across all sites. It is based on a snowball sampling approach that can be implemented by researchers with no prior experience of stakeholder research, and without requiring significant financial or time resources. It therefore fosters transdisciplinarity by empowering physical scientists to identify stakeholders and understand their roles. We describe the design process and outcomes, and consider their applicability to other research projects. Our methodology therefore consists of a two-phase process of design and implementation of an identification questionnaire. By explicitly including a design phase into the process, it is possible to tailor our methodology to other research projects