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Social-ecological functional types in the Argentine Chaco at census tract resolution (corresponding to the year 2002). Eight subclasses of SEFT are shown in the map: 1a, 1b, 1c, 2a, 2b, 3a, 3b and 3c. The polar diagrams at the right of the figure illustrate the contribution of the 17 variables for each subclass of SEFT. All the variables are scaled from 0 to 1. Variables: 1. Pop (population density); 2. Pov (poverty); 3. Lab (permanent labor); 4. School (number of schools); 5. Nf (native forest area); 6. PPm (mean annual primary productivity); 7. PPs (annual seasonality of primary productivity); 8. Irrig (irrigated area); 9. Tract (number of tractors per area); 10. Cattle (stocking rate); 11. Defor (natural cover transformation); 12. Crops (annual crops area); 13. Forage (forage crops area); 14. Calf (% cow pregnancy); 15. Roads (roads density); 16. Farmer (legal type of farmer); 17. Tenure (land tenure regime).
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Sustainability science recognizes the importance of the integrated assessment of the ecological and social systems in land-use planning. However, most studies so far have been conceptual rather than empirical. We developed a framework to characterize the social-ecological systems heterogeneity according to its functioning through the identification...
Contexts in source publication
Context 1
... mapped the social-ecological functional types in the Argentine Chaco at the census tract resolution ( Figure 5). Not all the census tracts are represented on the map because some tracts were discarded from the analysis (lack or inconsistency of data). ...
Context 2
... example, the area of the triple border of the Santiago del Estero, Chaco and Santa Fe provinces shares the same biophysical characteristics. However, provincial boundaries define different SEFT due to differences in the human aspects or the interaction between the biophysical and ecological components ( Figure 5). Whereas in eastern Santiago del Estero SEFTs associated with an expanding agribusiness were dominant, in western Chaco dominant SEFT were associated with more traditional middle-scale agriculture. ...
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... al., 2021;Kuemmerle et al., 2017). This large-scale deforestation and industrial agriculture is performed by foreign companies that take advantage of the land-tenure insecurity of IPLC (Cáceres, 2015; le Polain de Waroux et al., 2018;Vallejos et al., 2020). A recent study titled "Indigenous Lands with secure land-tenure can reduce forest-loss in deforestation hotspots" found that most of the residual forest in good ecological conditions is inhabited by local criollos and Indigenous people, and if they can remain in the area under secure land titles, they will continue managing the environment in a sustainable way (Camino et al., 2023). ...
Protected areas are essential for biodiversity conservation. However, the creation of protected areas often excludes Indigenous Peoples and Local Communities (IPLC), who are seen as a threat to biodiversity, and therefore their access to natural resources becomes restricted. This approach is known as fortress conservation and it is a colonialist approach towards conservation because IPLCs are excluded from decision making and often from their own lands and banned from using natural resources in the areas to be conserved, while only governments and professionals have agency to decide the future of these lands. Approaches to decolonize conservation that attempt to integrate IPLCs´ worldviews, local ecological knowledge (LEK) and practices may be highly efficient in biodiversity conservation as well as local development. In the Argentine Dry Chaco region, Quimilero Project frames its conservation efforts in this inclusive framework, aiming to conserve cultural and biological diversity and seeing both as interconnected. This project involves multiple approaches, based on the principles of horizontality, IPLCs´ empowerment and the co-creation of knowledge and conservation initiatives based both on scientific and on LEK. In this paper we explain our work approach in the Argentine Chaco from a decolonizing perspective. We describe two of our programs, community-based wildlife and hunting monitoring and environmental education, to demonstrate what a decolonial approach to conservation can look like in practice.
... We chose the same number of subcomponents per component to work with square matrices (6 × 6), simplifying matrix multiplications for this example. To define landscape types, we integrated a regional classification based on social-ecological functional types (Vallejos et al., 2020a) and one based on bundles of ecosystem services supply (Barral et al., 2020) (Fig. S1). Then, we reviewed the sparse and fragmented literature on the 288 links contained in this tool application (36 links per matrix in 8 matrices). ...
... Their results highlight the need to integrate each archetype's characteristics and conservation challenges. Vallejos et al. (2020) identified eight subclasses of social-ecological functional types (SEFTs) in El Chaco region in Argentina. The SEFT framework that they built is based on the ecosystem and agent functional types approaches to characterize administrative units hierarchically; by this methodological framework, they found that the degree of anthropization and the mean annual productivity were the variables that captured the most spatial variability of SEFTs. ...
... Integrating local perspectives into global scale frameworks can facilitate the development of metrics more appropriate for in situ communities and support the innovative approaches to research-based policy and action necessary to confront complex environmental challenges (Sterling et al. 2017). Previous social-ecological exercises to foster monitoring at local scales have identified a set of relevant variables at the local scales , Frey 2017, Sterling et al. 2017, Pacheco-Romero et al. 2020. However, there is a latent need for a dialogue between global and local scales in the monitoring and policy interphases. ...
... SES frameworks, specifically, aimed to guide research by identifying the concepts, variables, and processes that are relevant to explain the dynamics of SES, predicting changes, or delineating management strategies toward sustainability (Biggs et al. 2021). In doing so, SES frameworks provide reference lists of variables that can represent the most relevant SES components and the interactions between them (e.g., McGinnis and Ostrom, 2014;Frey, 2017;Pacheco-Romero et al., 2020). Despite these developments, analytical tools that allow the assessment and monitoring of SES dynamics are still lacking. ...
One of the key challenges of our era is to halt biodiversity loss and foster the sustainable use of nature. The Sustainable Development Goals (SDGs) recognize the importance of the inextricable link between social and ecological systems and human quality of life (QoL) and biodiversity. Therefore, understanding the feedback and interactions between biodiversity, nature‘s contributions to people (NCP), and QoL plays a central role in advancing toward sustainability. In this context, the social-ecological systems (SES) approach has advanced on the subject, particularly in recent decades; however, much remains to be done to comprehensively understand these relationships and interactions, especially at local decision-making scales. In this thesis, through the lenses of the SES approach, I investigate connections between biodiversity, NCP, and QoL in a tropical dry forest (TDF) on the Western coast of Mexico. This place is one of the best-known Neotropical TDF and has been the focus of SES research in the past 20 years, making it an excellent case study for exploring these connections.
First, to approach the need for dialogue among different global and local scales and between global and local frameworks, the thesis identifies five key components of the SES dynamics-(1) ecological supply, (2) co-production of NCP, (3) management, (4) demand, and (5) benefits- and three local decision-making scales of analysis- individual plot, smallholder, and land tenure or governance units. A literature review was performed on the social-ecological indicators for the last 11 years in the Chamela-Cuixmala region to operationalize this framework. The representability of the framework shows that research has emphasized the components of NCP co-production (42% of indicators) and SES management (21%). By analyzing SES dynamics through this new framework, we can support the monitoring of NCP and potentially detect regime shifts or radical changes before they happen. The framework is simultaneously context-specific and operationable across global contexts, providing an opportunity to inform discussions on global sustainability from local contexts.
Second, this thesis uses social-ecological information to identify social-ecological systems units (SESU) spatially explicitly. A methodology was provided to spatially identify the components of social-ecological systems that environmental conditions and management practices have shaped at three previously stated relevant decision-making scales: plots owned by individuals, plot owners, and governance units. To do so, we identified and characterized: (1) ecological clusters (EC), (2) social-management clusters (SC), and (3) SESU in a TDF in western Mexico. Our findings suggested that decision-makers (ejidatarios, i.e., type of ownership (related to agrarian reform), that in most cases the land allocated is small-smallholders-) are bounded by the topographical characteristics and the public policies that determine communal (or private) governance and the number of resources available to them. The methodology can be applied to other contexts and nested decision-making scales. The spatial identification of these interdependencies is critical for landscape planning since it can contribute to reconciling productive activities and biodiversity conservation.
Finally, the thesis examines the self-perceived QoL across the different SESU, finding 48 QoL items, which were grouped into six categories: 1) social capital, 2) economic capital, 3) agency, 4) nature, 5) peasant non-work activities, and 6) government and services; and two additional dimensions referred to obstacles and enablers of QoL. We found that the more land cover transformation, the more enablers, and obstacles of QoL are identified; emphasis was put on economic capital to achieve QoL. As management is intensified and governance fosters individualism across SES, the higher the Current Welfare Index, and the lower the self-perceived material and non-material satisfaction. We discuss the need for governance structures promoting smallholders' worldviews that move beyond utilitarianism and foster commons. The social-ecological systems approach employed throughout this dissertation contributed towards crosscutting insights; the testing of new frameworks and methodologies represent important steps towards unraveling the connections between biodiversity, NCP, and QoL and contributes to achieving sustainable scenarios such as the ones proposed by the SDGs.
... S1 and S2 online). This approach has been widely used in previous studies to cluster different regions or countries based on their multidimensional characteristics [23,24]. The Euclidean distance between two countries, i1 and i2, was calculated as ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi P ...
... We chose the same number of subcomponents per component to work with square matrices (6 × 6), simplifying matrix multiplications for this example. To define landscape types, we integrated a regional classification based on social-ecological functional types (Vallejos et al., 2020a) and one based on bundles of ecosystem services supply (Barral et al., 2020) (Fig. S1). Then, we reviewed the sparse and fragmented literature on the 288 links contained in this tool application (36 links per matrix in 8 matrices). ...
... Despite recent efforts, there is no consensus on how to analytically delineate and define SES boundaries, or zones with consistent social and ecological characteristics, organized by a common set of system variables, and defined by diverse sets of socio-ecological dynamics (Jones et al., 2019;Quintas-Soriano et al., 2022). Current SEZ mapping efforts (e.g., Cruz-Cardenas et al., 2017;Dressel et al., 2018;Hamann et al., 2015;Hanspach et al., 2016;Kok et al., 2016;Martín-L opez et al., 2017;Vallejos et al., 2019;Zhang et al., 2011) have used a similar three-step analytical approach (Appendix S1: Figure S1). Briefly, these are as follows: (1) collection of spatially referenced social and bio-geo-physical data, followed generally by application of dimension-reduction methods (e.g., principal components analysis [PCA]); (2) cluster analyses to separately identify social and ecological system types; and (3) synthesis of social and ecological classification types into conjoined SEZs, based on spatial overlap. ...
Policy interest in socio‐ecological systems has driven attempts to define and map socio‐ecological zones (SEZs), that is, spatial regions, distinguishable by their conjoined social and bio‐geo‐physical characteristics. The state of Idaho, USA, has a strong need for SEZ designations because of potential conflicts between rapidly increasing and impactful human populations, and proximal natural ecosystems. Our Idaho SEZs address analytical shortcomings in previously published SEZs by: (1) considering potential biases of clustering methods, (2) cross‐validating SEZ classifications, (3) measuring the relative importance of bio‐geo‐physical and social system predictors, and (4) considering spatial autocorrelation. We obtained authoritative bio‐geo‐physical and social system datasets for Idaho, aggregated into 5‐km grids = 25 km2, and decomposed these using principal components analyses (PCAs). PCA scores were classified using two clustering techniques commonly used in SEZ mapping: hierarchical clustering with Ward's linkage, and k‐means analysis. Classification evaluators indicated that eight‐ and five‐cluster solutions were optimal for the bio‐geo‐physical and social datasets for Ward's linkage, resulting in 31 SEZ composite types, and six‐ and five‐cluster solutions were optimal for k‐means analysis, resulting in 24 SEZ composite types. Ward's and k‐means solutions were similar for bio‐geo‐physical and social classifications with similar numbers of clusters. Further, both classifiers identified the same dominant SEZ composites. For rarer SEZs, however, classification methods strongly affected SEZ classifications, potentially altering land management perspectives. Our SEZs identify several critical regions of social–ecological overlap. These include suburban interface types and a high desert transition zone. Based on multinomial generalized linear models, bio‐geo‐physical information explained more variation in SEZs than social system data, after controlling for spatial autocorrelation, under both Ward's and k‐means approaches. Agreement (cross‐validation) levels were high for multinomial models with bio‐geo‐physical and social predictors for both Ward's and k‐means SEZs. A consideration of historical drivers, including indigenous social systems, and current trajectories of land and resource management in Idaho, indicates a strong need for rigorous SEZ designations to guide development and conservation in the region. Our analytical framework can be broadly applied in SES research and applied in other regions, when categorical responses—including cluster designations—have a spatial component.
... These data could provide deep insights into how deforestation frontiers advance and help to identify typical, recurrent patterns of deforestation frontiers. Recently, detecting and assessing such archetypical human-environment interactions has become a major focus in sustainability science 18,19 , including for identifying static land systems 20 or driver/outcome constellations 8,21,22 . In this study we have pioneered the use of archetype analyses to identify the major, recurring patterns in global deforestation frontiers. ...
Tropical dry woodlands are rapidly being lost to agricultural expansion, but how deforestation dynamics play out in these woodlands remains poorly understood. We have developed an approach to detect and map high-level patterns of deforestation frontiers, that is, the expansion of woodland loss across continents in unprecedented spatio-temporal detail. Deforestation in tropical dry woodlands is pervasive, with over 71 Mha lost since 2000 and one-third of wooded areas located in deforestation frontiers. Over 24.3 Mha of deforestation frontiers fall into what we term ‘rampant frontiers’. These are characterized by drastic woodland loss and conditions favourable for capital-intensive agriculture, as seen in the South American Chaco and Southeast Asia. We have found many active and emerging frontiers (~59% of all frontiers), mostly in the understudied dry woodlands of Africa and Asia, where greater frontier monitoring is needed. Our approach enables consistent, repeatable frontier monitoring, and our global frontier typology fosters comparative research and context-specific policymaking. Agricultural expansion is responsible for tree loss in tropical dry woodlands, but the dynamics of such loss are not well understood. This study presents a global, high-resolution assessment of deforestation dynamics in dry woodlands and provides a tool for consistent monitoring.
... We considered the results at two nested spatial levels of detail (1 st level corresponds to social-ecological regions or SER and 2 nd level to social-ecological land systems or SELS) because findings at different levels can complement each other and improve analysis robustness (Sietz et al. 2017, Vallejos et al. 2020. The authors analyzed the clustering outputs (spatial layout, cluster's statistics, and method's performance metrics) at successive dendrogram cuts in relation to their territorial knowledge to agree on the optimal number of clusters. ...
... Consideramos los resultados del agrupamiento en dos niveles de detalle espacial anidados (1er nivel corresponde a las Regiones Socio-Ecológicas -SER-y el 2do nivel a los Sistemas Territoriales Socio-Ecológicos -SELS-) ya que los diferentes niveles aportan información complementaria y mejoran la robustez del análisis (Sietz et al. 2017, Vallejos et al. 2020. Los autores analizamos los productos del agrupamiento (distribución espacial, estadísticas de los grupos, y métricas de desempeño del método) en cortes sucesivos del dendrograma (árbol) en relación a su conocimiento territorial para acordar en el número óptimo de grupos. ...
Humans place strong pressure on land and have modified around 75% of Earth’s terrestrial surface. In this context, ecoregions and biomes, merely defined on the basis of their biophysical features, are incomplete characterizations of the territory. Land system science requires classification schemes that incorporate both social and biophysical dimensions. In this study, we generated spatially explicit social-ecological land system (SELS) typologies for South America with a hybrid methodology that combined data-driven spatial analysis with a knowledge-based evaluation by an interdisciplinary group of regional specialists. Our approach embraced a holistic consideration of the social-ecological land systems, gathering a dataset of 26 variables spanning across 7 dimensions: physical, biological, land cover, economic, demographic, political, and cultural. We identified 13 SELS nested in 5 larger social-ecological regions (SER). Each SELS was discussed and described by specific groups of specialists. Although 4 environmental and 1 socioeconomic variable explained most of the distribution of the coarse SER classification, a diversity of 15 other variables were shown to be essential for defining several SELS, highlighting specific features that differentiate them. The SELS spatial classification presented is a systematic and operative characterization of South American social-ecological land systems. We propose its use can contribute as a reference framework for a wide range of applications such as analyzing observations within larger contexts, designing system-specific solutions for sustainable development, and structuring hypothesis testing and comparisons across space. Similar efforts could be done elsewhere in the world.
... Em cada escala, a complexidade do sistema aumenta conforme aspropriedades emergentes entram em cena (instituições, normas, fenômenos biofísicos). Esta é uma maneira muito simples de conceituar a agricultura e fenômenos relacionados em múltiplas escalas, como nas abordagens dos sistemas agrários (COCHET, 2012), sistemas sócio-ecológicos(VALLEJOS et al., 2020;WITTMAN et al., 2017) e agroecologia(FRANCIS et al., 2003;MÉNDEZ;BACON;COHEN, 2013).Intrínseca a esta visão é a compreensão da agricultura como um fenômeno sócioecológico. Análogo ao conceito de ecótono na Ecologia 23 , pensamos na agricultura como um socioecótono, algo que emerge da tensão entre o ser humano e a natureza exterior, entre o sistema social e o sistema natural, o meio ambiente e a sociedade. ...
The issue of the transition of agricultural systems to states of strong multifunctionality has been addressed. The concept of multifunctionality has been used to situate and analyze agriculture in the context of broader social changes towards sustainability, highlighting and valuing functions of agriculture beyond primary production (and the productivist logic), and recognizing it as an activity promoting sustainable development. According to the normative view of multifunctionality (MF), the transition trajectories of rural establishments can be conceptualized as multifunctional trajectories within a spectrum bounded by productivist and non-productivist action and thinking, ranging between weak, moderate, and strong MF. Strong MF is characterized by well-developed social, economic, cultural, moral, and environmental capitals, and can be realized through diversified, agroecological, and localized systems. Given this, the main question of the project is: how can rural establishments transition to states of strong multifunctionality that simultaneously promote adequate livelihoods, food sovereignty, and natural resource conservation? Objective: To explore the inter-relationships between human, socio-economic and agro-environmental factors and the quality of multifunctionality of agroecosystems. Methodology: This work is a mixed-methods research in the form of a case study. An a priori conceptual model was developed based on the following concepts: multifunctionality of agriculture; livelihoods approach; agroecology. Based on this model, the phenomenon of multifunctionality of agriculture, and its expression in the context of the municipality of Iperó/SP will be investigated. From a socio-ecological perspective, socio-economic, human and agro-environmental factors of the landscape/territory will be analyzed, to infer about their inter-relationships and their influences on the level of landscape multifunctionality. Data collection will be through participant observation and interviews with farming families, heads of non-family establishments and other local actors relevant to the study (rural extension technicians, representatives of institutions that support agriculture and rural development, managers and public agency officials). Conclusion: this study contributed to the development of an integrative conceptual model that highlighted the factors that influence the performance of multifunctionality. The expression of multifunctionality in a family agroecosystem is a complex process, influenced by several internal and contextual factors and mechanisms.
... Specifically, the identification and mapping of SES archetypes as typologies of cases (sensu Oberlack et al 2019) allows to translate the SES concept into the territory and make it spatially explicit, by delineating territorial units that share similar social, ecological, and human-nature interaction patterns (e.g. SES archetypes by Rocha et al 2020, socio-ecological functional types by Vallejos et al 2020). SES maps can work as templates for decision-makers to develop more integrative and sustainable models of territorial management that consider the coupling between human and natural systems (Oberlack et Recently, the identification of SES archetypes as typologies of cases has moved towards more integrative perspectives that consider the multidimensional aspects of human-nature interactions. ...
The spatial mapping of social-ecological system (SES) archetypes constitutes a fundamental tool to operationalize the SES concept in empirical research. Approaches to detect, map, and characterize SES archetypes have evolved over the last decade towards more integrative and comparable perspectives guided by SES conceptual frameworks and reference lists of variables. However, hardly any studies have investigated how to empirically identify the most relevant set of indicators to map the diversity of SESs. In this study, we propose a data-driven methodological routine based on multivariate statistical analysis to identify the most relevant indicators for mapping and characterizing SES archetypes in a particular region. Taking Andalusia (Spain) as a case study, we applied this methodological routine to 86 indicators representing multiple variables and dimensions of the SES. Additionally, we assessed how the empirical relevance of these indicators contributes to previous expert and empirical knowledge on key variables for characterizing SESs. We identified 29 key indicators that allowed us to map 15 SES archetypes encompassing natural, mosaic, agricultural, and urban systems, which uncovered contrasting land sharing and land sparing patterns throughout the territory. We found synergies but also disagreements between empirical and expert knowledge on the relevance of variables: agreement on their widespread relevance (32.7% of the variables, e.g., crop and livestock production, net primary productivity, population density); relevance conditioned by the context or the scale (16.3%, e.g., land protection, educational level); lack of agreement (20.4%, e.g., economic level, land tenure); need of further assessments due to the lack of expert or empirical knowledge (30.6%). Overall, our data-driven approach can contribute to more objective selection of relevant indicators for SES mapping, which may help to produce comparable and generalizable empirical knowledge on key variables for characterizing SESs, as well as to derive more representative descriptions and causal factor configurations in SES archetype analysis.
