Complex Socio-environmental Systems Research Articles

Combining vector and raster data in regionalization: A unified framework for delineating spatial unit boundaries for socio-environmental systems analyses

Regionalization has emerged as a crucial research area for the past 50 years, including aggregating smaller areas into larger, contiguous, and/or homogeneous regions. Spatial optimization techniques are advantageous for solving regionalization problems, yet their nondeterministic polynomial-time (NP) hard nature leads to computational complexity and time consumption, especially with extensive datasets. Although regionalization studies play a pivotal role in defining boundaries for multi-scalar analysis and modeling complex socio-environmental systems (SES), current approaches lack integrated consideration of raster and vector data. We introduce a unified, structured framework integrating Geographic Information Systems (GIS), image segmentation, and regionalization to identify and characterize socio-environmental units accounting for various data models and types. We use a public geodatabase of the Rio Grande/Bravo basin, an SES covering diverse cultures, ecosystems, and economies, to demonstrate the functionality of our newly developed method, which effectively identifies spatial units for subsequent SES analysis and modeling. The delineation process accounts for various factors, including administrative boundaries, estimated total quantities, compactness, spatial contiguity, and similarity in socio-environmental characteristics. To make this work reproducible, replicable, and expandable, we developed the approach entirely based on open-source Python packages. Our method is easily transferable to other research using various data formats and spatial scales to delineate spatial unit boundaries effectively and efficiently.

Cultural, creative, and complex: A computational foundation of culture-driven urban governance

Culture and creative production have an important but somewhat elusive role in urban development. None of the many conceptual paradigms that have been proposed so far to explain it has turned out entirely satisfactory. We argue that the main reason behind this failure is the implicit linear thinking that informs all these approaches: namely, the idea that a few, major drivers explain urban development through a direct, clearly readable systemic impact. Cities are complex socio-environmental systems whose functioning depends on the concurrent interaction of many different factors which cannot be reduced to the action of a few, simple causal forces. Failing to understand such complexity easily leads to dysfunctional urban governance approaches. In this paper, we analyze a database of 144 European cities as described by 58 variables belonging to different domains, as designed by a preliminary stage of the Cultural and Creative City Monitor (CCCM). Our analysis builds on innovative machine learning techniques (PST) and on the Minimum Spanning Tree (MST) representation to map the structural interdependencies between the cultural and non-cultural sectors in cities with a strong cultural policy orientation. This toolbox carries considerable potential for precision cultural policies and data-driven urban governance strategies of the future.

Handling multiple levels in agent-based models of complex socio-environmental systems: A comprehensive review

Agent-based modeling (ABM) has been successfully used, since its emergence in the 1990s, to model and simulate the dynamics at work in complex socio-environmental systems, in many domains and applications where interactions between people and their environments give rise to emergent phenomena that are difficult to study otherwise (urban planning, land-use change, adaptation to environmental changes, biodiversity protection in socio-ecosystems, environmental pollution control, etc.). The inclusion of multiple levels of analysis, abstraction, and representation in these models, however, is much more recent and is still the subject of many proposals and discussions within a relatively informal field, Multilevel Agent-Based Modeling (ML-ABM), which is most often presented as an approach that extends the classical ABM paradigm to include multilevel concepts. Over the past decade, ML-ABM has been increasingly adopted and explored by researchers as an effective paradigm for framing and defining the mechanisms underlying multilevel dynamics. However, due to the youth of the field, no single definition, methodology, or tool unifies studies in this rapidly expanding area. This review will begin with an introduction to socio-environmental systems (SES) and the challenges that modeling approaches face in representing them properly, especially regarding the complexity of human behaviors and organizations. ABM presents opportunities for modeling SESs with respect to these challenges, including the simulation of individual and social behavior and their ability to provide a descriptive and generative representation of the simulated system. However, ABM is limited in its ability to represent levels and scales, as these concepts are absent from the classical ABM metamodel. A complete review of the ML-ABM literature will be carried out, structured around a continuum that emerged during the review: that of the distribution of behaviors (and thus, from a software engineering perspective, of control) across the levels, from approaches that allow only one level to be active at a time, to approaches that rely on simultaneous activity and feedback loops between several levels. Different design choices will, thus, be presented to meet the different needs of multi-level representation, focusing on the interest on modelers and the strengths and limitations of each. In particular, we will highlight a limitation shared by all the reviewed approaches, namely their inability to represent several parallel hierarchies of levels and their interactions, a capability that appears more and more crucial to finely represent social behaviors in SES. A new perspective on the interest that the AGR approach could represent to allow this representation of hierarchies allows us to conclude on the research perspectives are still open.

Socio-Environmental Vulnerability Assessment for Sustainable Management

Research on complex socio-environmental systems (also known as socio-ecological systems) has a long tradition in scientific considerations [...]

The Number and Spatial Distribution of Forest-Proximate People Globally

Summary Forest landscapes are complex socio-environmental systems. The degree to which forests support human livelihoods, and humans affect forest ecology, depends in part on the spatial relationship between people and forests. Here, we estimate the number of people who live in and around forests globally. We combined forest cover and human population density data to map the spatial relationship between people and forests on a global scale in 2000 and 2012. Globally, 1.6 billion rural people lived within 5 km of a forest in 2012. Of these, 64.5% lived in tropical countries and 71.3% lived in low-income, lower-middle-income, or upper-middle-income countries. We propose the term “forest-proximate people” to refer to people who live in and around forests. Forest proximity is related to, but not synonymous with, forest dependency. Our findings have implications for researchers and decision-makers interested in forest conservation, forest livelihoods, and sustainable socio-economic development in communities in and around forests.

Assessing model equifinality for robust policy analysis in complex socio-environmental systems

Equifinality—a situation in which multiple plausible explanations exist for a single outcome—presents a challenge for socio-environmental systems modeling. When equifinality is ignored in model calibration, subsequent policy analyses may mis-estimate the range of potential policy effects. In this paper, we present and demonstrate an approach—called DMC-RPA—for generating a set of diverse model calibrations (DMC) to enable more robust policy analysis (RPA). The optimization-based approach maximizes diversity in the model parameters and/or structural configurations to efficiently represent any equifinality in the model set. We demonstrate the approach for an agent-based model that is used to compare resilience-enhancing strategies in a smallholder farming system. Results over the set of diverse model calibrations demonstrate consistent policy effects, enabling stronger conclusions than a single model analysis. Going forward, this approach can be applied in the development of socio-environmental systems models to facilitate more robust policy analysis and inference.

Spatially-explicit simulation of two-way coupling of complex socio-environmental systems: Socio-hydrological risk and decision making in Mexico City

We present here MEGADAPT (MEGAcity-ADAPTation), a hybrid, dynamic, spatially-explicit, integrated modeling approach to simulate the vulnerability of urban coupled socio-environmental systems – in our case, the vulnerability of Mexico City to socio-hydrological risk. Although vulnerability is widely understood to be influenced by human decision-making, these decisions are rarely captured as endogenous to dynamic vulnerability models. The objective of this paper is to use MEGADAPT to demonstrate a methodological approach that allows vulnerability to be simulated as a reflexive process: the result of the interplay between mental models held by influential actors and the response of the biophysical and social world to the realization of decisions based on these mental models. MEGADAPT represents Mexico City as a self-organizing system. Hence, its computational framework involves the implementation of a suite of system models, geographic information system-multicriteria decision analysis, and geosimulation. A novel contribution of this approach is the use of the Analytic Network Process to synthesize the dynamic feedback between mental models and conditions of geographic automata. In this way, MEGADAPT depicts the shift in the behavior of socio-environmental systems from one-way coupling/single-loop learning to two-way coupling/double-loop learning, with the decision-making process as an endogenous system driver.

A qualidade de vida em unidades rurais planejadas pela permacultura avaliada com base no MESMIS

Este artigo apresenta um estudo de caso realizado pelo Projeto Terra Permanente, que teve como objetivo avaliar se houve melhoria na qualidade de vida de agricultores/as da grande Florianópolis a partir da adoção dos princípios da permacultura como forma de manejo em suas unidades familiares de produção (UFP). Para avaliar a qualidade de vida antes, durante e após o curso de planejamento em permacultura (PDC, do inglês Permaculture Design Course), foram acompanhadas quatro UFP ao longo de dois anos. Foi utilizada como referência metodológica o "Marco para a Avaliação de Sistemas de Manejo Incorporando Indicadores de Sustentabilidade” – MESMIS - com adaptações necessárias às éticas e princípios da permacultura gerando uma metodologia personalizada aqui proposta como “MESMIS permacultural”. Os resultados obtidos indicam que além de melhorias na qualidade de vida dos integrantes das UFP, a metodologia “MESMIS permacultural” apresenta potencial para ser aplicada em outras pesquisas cujo enfoque precise abordar os princípios da permacultura.

MULTIDISCIPLINARY AND INNOVATIVE METHODOLOGIES FOR SUSTAINABLE MANAGEMENT IN AGRICULTURAL SYSTEMS

Sustainability issues have driven academic researchers towards the definition of methodological tools to assess the impacts derived from products and services and to make them more ecologically friendly, economically profitable and socially suitable, and whose results have to be clear and understandable to a broad public. In the evaluation of complex socio-environmental systems, like agricultural ones, uncertainty often arises and the quality of decision processes can be a high concern. This paper presents the conceptual and methodological framework of an Italian research project entitled MIMeSMAS , i.e. Multidisciplinary and Innovative Methodologies for Sustainable Management in Agricultural Systems. Through a multidisciplinary, multi-methodological, systemic and participatory approach, the project attempts to define an integrated approach for the assessment of environmental, economic and social sustainability of innovative agricultural practices in Mediterranean areas. The project activities are carried out by four Italian research institutions in order to bring together agronomic, hydraulic and mechanical expertise and to conduct a combined implementation of Life Cycle methodologies (LCA, LCC and s-LCA) and multi-criteria analysis tools. The approach is applied to assess and rank alternative cropping systems scenarios; results are expected to help optimising the management of soil, water and energy macro-systems of perennial crops (olive), horticultural crops (artichoke) and dedicated energy crops (giant reed). In this paper the theoretical concept of the project, the preliminary results of project s activities linked to the identification of experimental trials scenarios and to the definition of specific indicators are presented.

A participatory approach for system conceptualization and analysis applied to coastal management in Egypt

This paper presents a participatory approach to conceptualizing system's models and to identifying critical issues in complex socio-environmental systems, combining information collected from individual experts and stakeholders. A method was developed to: (i) capture individuals mental models in the form of causal loop diagrams, using interaction matrices; (ii) build a conceptual model of the system combining the contribution of all stakeholders; (iii) identify critical issues for the system and (iv) prepare a combined causal loop diagram for further discussion and system dynamics simulations. This method was used to engage a group of stakeholders involved in the preparation of a plan for integrated coastal zone management in Egypt. The experience helped highlight the critical issues of the system in terms of importance given by the actors involved in the exercise and their impact on the coastal system. This approach also demonstrated the utility of conceptualizing complex socio-environmental systems for identifying critical issues in data-poor environments.

Evaluating the sustainability of complex socio-environmental systems. the MESMIS framework

Sustainable development has become a leading target of scientific research and policy agenda. In the context of natural resource management, understanding and evaluating the performance of complex socio-environmental systems has become a challenge, and the design of more sustainable alternatives is a driving need. In addition, there is a need to translate the general principles of sustainability into operational definitions and practices. This paper examines key methodological issues in the selection, transformation and aggregation of economic, environmental and social indicators for sustainability analysis. Specific reference is given to the MESMIS approach, a systemic, participatory, interdisciplinary and flexible framework for sustainability evaluation. The MESMIS framework has been developed by a multi-institutional team in Mexico and validated through its application to more than 20 case studies in Mexico and Latin America. The MESMIS operative structure is a six step cycle. The first three steps are devoted to the characterisation of the systems, the identification of critical points and the selection of specific indicators for the environmental, social and economic dimensions of sustainability. In the last three steps, the information obtained by means of the indicators is integrated through mixed (qualitative and quantitative) techniques and multicriteria analysis, so as to obtain a value judgement about the resource management systems and to provide suggestions and insights aimed at improving their socio-environmental profile. MESMIS attempts to generate a cyclic process which, by effectively integrating the evaluation into the decision making process, improves the likelihood of success in the design of alternatives and the implementation of development projects.