Improving network approaches to the study of complex social-ecological interdependencies

Understanding Trophic Interactions in a Warming World by Bridging Foraging Ecology and Biomechanics with Network Science

Climate change will disrupt biological processes at every scale. Ecosystem functions and services vital to ecological resilience are set to shift, with consequences for how we manage land, natural resources, and food systems. Increasing temperatures cause morphological shifts, with concomitant implications for biomechanical performance metrics crucial to trophic interactions. Biomechanical performance, such as maximum bite force or running speed, determines the breadth of resources accessible to consumers, the outcome of interspecific interactions, and thus the structure of ecological networks. Climate change-induced impacts to ecosystem services and resilience are therefore on the horizon, mediated by disruptions of biomechanical performance and, consequently, trophic interactions across whole ecosystems. Here, we argue that there is an urgent need to investigate the complex interactions between climate change, biomechanical traits, and foraging ecology to help predict changes to ecological networks and ecosystem functioning. We discuss how these seemingly disparate disciplines can be connected through network science. Using an ant-plant network as an example, we illustrate how different data types could be integrated to investigate the interaction between warming, bite force, and trophic interactions, and discuss what such an integration will achieve. It is our hope that this integrative framework will help to identify a viable means to elucidate previously intractable impacts of climate change, with effective predictive potential to guide management and mitigation.

Temporal shifts in the phytoplankton network in a large eutrophic shallow freshwater lake subjected to major environmental changes due to human interventions

Phytoplankton communities are crucial components of aquatic ecosystems, and since they are highly interactive, they always form complex networks. Yet, our understanding of how interactive phytoplankton networks vary through time under changing environmental conditions is limited. Using a 29-year (339 months) long-term dataset on Lake Taihu, China, we constructed a temporal network comprising monthly sub-networks using "extended Local Similarity Analysis" and assessed how eutrophication, climate change, and restoration efforts influenced the temporal dynamics of network complexity and stability. The network architecture of phytoplankton showed strong dynamic changes with varying environments. Our results revealed cascading effects of eutrophication and climate change on phytoplankton network stability via changes in network complexity. The network stability of phytoplankton increased with average degree, modularity, and nestedness and decreased with connectance. Eutrophication (increasing nitrogen) stabilized the phytoplankton network, mainly by increasing its average degree, while climate change, i.e., warming and decreasing wind speed enhanced its stability by increasing the cohesion of phytoplankton communities directly and by decreasing the connectance of network indirectly. A remarkable shift and a major decrease in the temporal dynamics of phytoplankton network complexity (average degree, nestedness) and stability (robustness, persistence) were detected after 2007 when numerous eutrophication mitigation efforts (not all successful) were implemented, leading to simplified phytoplankton networks and reduced stability. Our findings provide new insights into the organization of phytoplankton networks under eutrophication (or re-oligotrophication) and climate change in subtropical shallow lakes.

Evolution of system connectivity to support food production in the Indus Basin in Pakistan

Sustainability challenges related to food production arise from multiple nature-society interactions occurring over long time periods. Traditional methods of quantitative analysis do not represent long-term changes in the networks of system components, including institutions and knowledge that affect system behavior. Here, we develop an approach to study system structure and evolution by combining a qualitative framework that represents sustainability-relevant human, technological, and environmental components, and their interactions, mediated by knowledge and institutions, with network modeling that enables quantitative metrics. We use this approach to examine the water and food system in the Punjab province of the Indus River Basin in Pakistan, exploring how food production has been sustained, despite high population growth, periodic floods, and frequent political and economic disruptions. Using network models of five periods spanning 75 y (1947 to 2022), we examine how quantitative metrics of network structure relate to observed sustainability-relevant outcomes and how potential interventions in the system affect these quantitative metrics. We find that the persistent centrality of some and evolving centrality of other key nodes, coupled with the increasing number and length of pathways connecting them, are associated with sustaining food production in the system over time. Our assessment of potential interventions shows that regulating groundwater pumping and phasing out fossil fuels alters network pathways, and helps identify potential vulnerabilities for future food production.

Identifying and optimizing ecological spatial patterns based on the bird distribution in the Yellow River Basin, China

In the Yellow River Basin (YRB), there exists a rich biodiversity of species that has been shaped by its unique geography, climate, and human activities. However, the high speed of economic development has resulted in the fragmentation and loss of habitats that are crucial for the survival of these species. To address this problem, constructing ecological networks has emerged as a promising approach for biodiversity preservation. In the study, we centered on the YRB and employed bird communities as an indicator species to identify ecological sources by combining bioclimatic variables and land use data with the Maximum Entropy (MaxEnt) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models. We generated a resistance surface using various data such as Digital Elevation Model (DEM), the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), nighttime light, road density, railway density, and waterway density. So, we then simulated ecological corridors applying the Minimum Cumulative Resistance (MCR) model and constructed a bird diversity protection network. The results we found suggested that bird hotspots were predominantly clustered upstream and downstream in the YRB. We identified 475 sources covering a total area of 65,088 km2, 681 corridors with a total length of 11,495.05 km. This network served as a critical ecological facility to sustain and protect biodiversity. The bird ecological corridors in the YRB showed that a dense east-west pattern in the central area, with a short length in the west and east and a long length in the central area. Although the central region lacked ecological sources, the east and west were still connected as a tight whole. Two scenarios showed adding ecological stepping stones had a better optimization effect than enhancing ecological connectivity.

Collaborative Modeling of the Tick-Borne Disease Social-Ecological System: A Conceptual Framework

Hard-bodied ticks have become a major concern in temperate regions because they transmit a variety of pathogens of medical significance. Ticks and pathogens interact with hosts in a complex social-ecological system (SES) that influences human exposure to tick-borne diseases (TBD). We argue that addressing the urgent public health threat posed by TBD requires an understanding of the integrated processes in the forest ecosystem that influence tick density and infection prevalence, transmission among ticks, animal hosts, and ultimately disease prevalence in humans. We argue that collaborative modeling of the human-tick SES is required to understand the system dynamics as well as move science toward policy action. Recent studies in human health have shown the importance of stakeholder participation in understanding the factors that contribute to human exposure to zoonotic diseases. We discuss how collaborative modeling can be applied to understand the impacts of forest management practices on ticks and TBD. We discuss the potential of collaborative modeling for encouraging participation of diverse stakeholders in discussing the implications of managing forest ticks in the absence of large-scale control policy.

Progress in modeling dynamic systems for sustainable development

This Perspective evaluates recent progress in modeling nature-society systems to inform sustainable development. We argue that recent work has begun to address longstanding and often-cited challenges in bringing modeling to bear on problems of sustainable development. For each of four stages of modeling practice-defining purpose, selecting components, analyzing interactions, and assessing interventions-we highlight examples of dynamical modeling methods and advances in their application that have improved understanding and begun to inform action. Because many of these methods and associated advances have focused on particular sectors and places, their potential to inform key open questions in the field of sustainability science is often underappreciated. We discuss how application of such methods helps researchers interested in harnessing insights into specific sectors and locations to address human well-being, focus on sustainability-relevant timescales, and attend to power differentials among actors. In parallel, application of these modeling methods is helping to advance theory of nature-society systems by enhancing the uptake and utility of frameworks, clarifying key concepts through more rigorous definitions, and informing development of archetypes that can assist hypothesis development and testing. We conclude by suggesting ways to further leverage emerging modeling methods in the context of sustainability science.

Including animals in sociology

How do we include animals in sociology? Although sociology's initial avoidance of the nonhuman world may have been necessary to the field's development, recent scholarship - within mainstream sociology, environmental sociology and animal-centred research - is helping expand the field's horizons. With a focus on variety, this article reviews four key paths that researchers are taking to include animals in their research: (1) studying interspecies relations, (2) theorizing animals as an oppressed group, (3) investigating the social and ecological impacts of animal agriculture and (4) analysing social-ecological networks. This review shows how applying - and innovating - existing social theories and research methods allows researchers to include animals in their analyses and will be relevant to a variety of scholars, including mainstream and environmental sociologists, animal-focused researchers and social network analysts, to name a few.

The monetary facilities payment for ecosystem services as an approach to restore the Degraded Urmia Lake in Iran

This study analyzed the potential use of Payment for Ecosystem Services (PES) as a strategy for improving water supply management. This study focused on the Siminehroud Sub-basin due to its high importance to the Basin of Urmia Lake (UL). Siminehroud is the second provider of water (by volume) to Urmia Lake. To evaluate the technical and economic feasibility of a PES scheme, the current land use map was extracted using satellite imagery. In addition, the two algorithms of Support Vector Machines (SVMs) and Maximum Likelihood (ML) are used for Landsat images classification, rather than analyzing the relationship between land use and ecosystem services. Then, the most relevant ecosystem services provided in the region were evaluated using the Benefit Transfer Method. In the last step, by designing and implementing a survey, on the one hand, the local farmers' Willingness to Accept (WTA) cash payments for reducing the area they cultivate, and on the other hand, the farmers' Willingness to Pay (WTP) for managing the water consumption were determined. The results illustrated that the WTA program is more acceptable among the beneficiaries. It is also notable that this program needs very high governmental funding. Furthermore, the results of the program indicate that the land area out of the cultivation cycle will gradually increase while the price of agricultural water will also increase.

The community perception of human-water connections is indirectly influenced by the landscape context: A case study in the lower reaches of the Yellow river

Humans and water are closely connected in large river basins and form social-ecological systems (SESs). However, cross-scale effect in SESs make it difficult to identify the key forces driving human-water connections at the community scale when ignoring the landscape context. Focusing on the incongruous human-water relationships in the lower reaches of the Yellow River, we built local resident perception-based networks linking the agricultural subsystem, environmental subsystem, and cultural subsystem by distributing farmer household questionnaires and extracted 13 indicators from 7 kinds of network metrics to indicate human-water connections. We applied analysis of variance (ANOVA), random forest (RF) and multilevel linear model (MLM) methods to identify the driving forces of perception-based human-water connections among 20 factors at both the community and landscape scales. The results showed that the perception-based network indicators were mainly directly influenced by community-level driving factors, especially the accessibility of information, such as the frequency of going out, the frequency of accessing the Yellow River channel, and the information source for the national policy on the Yellow River. The influences of community-level driving factors on network indicators were affected by landscape-level driving factors, e.g., the nighttime light, population density, gross domestic product and proportion of artificial land, thus indicating indirect influences from the landscape context. These analyses and findings can enrich the methods by which social, ecological and hydrological elements are structurally linked in sociohydrologic research and highlight the cross-scale effect of the landscape context on human-water systems at the community level.

Multilevel network interventions: Goals, actions, and outcomes

COVID-19 has resulted in dramatic and widespread social network interventions across the globe, with public health measures such as distancing and isolation key epidemiological responses to minimize transmission. Because these measures affect social interactions between people, the networked structure of daily lives is changed. Such largescale changes to social structures, present simultaneously across many different societies and touching many different people, give renewed significance to the conceptualization of social network interventions. As social network researchers, we need a framework for understanding and describing network interventions consistent with the COVID-19 experience, one that builds on past work but able to cast interventions across a broad societal framework. In this theoretical paper, we extend the conceptualization of social network interventions in these directions. We follow Valente (2012) with a tripartite categorization of interventions but add a multilevel dimension to capture hierarchical aspects that are a key feature of any society and implicit in any network. This multilevel dimension distinguishes goals, actions, and outcomes at different levels, from individuals to the whole of the society. We illustrate this extended taxonomy with a range of COVID-19 public health measures of different types and at multiple levels, and then show how past network intervention research in other domains can also be framed in this way. We discuss what counts as an effective network, an effective intervention, plausible causality, and careful selection and evaluation, as central to a full theory of network interventions.

Engagement in water governance action situations in the Lake Champlain Basin

Water quality governance encompasses multiple "wicked" interacting problems that manifest within social-ecological systems. Concerned governments, institutions, and actors concerned with addressing these issues must wrestle with complex systems that span time, space, and scale. This complexity of connected systems requires the participation of multiple actors across political boundaries, problem areas, and hydrologic domains. In Lake Champlain (US), frequent cyanobacteria blooms negatively affect property values, recreational activities, and public infrastructure, in addition to their impacts on the aquatic ecosystem. Through a survey of actors working on water quality in the Lake Champlain Basin, we analyze how actor participation in structured issue forums creates a network of connected action situations across multiple spatial scales and problem domains. We apply exponential random graph models to quantify the effects of scale, issues, and homophily on actor participation in these forums. Our findings show that actors tend to favor participating in similarly scoped forums at their spatial scale, that actors are less likely to participate in structured forums focused on agriculture, and that actors participate independently of others with whom they have pre-existing collaborative relationships. Further, we find that in the case of the Lake Champlain Basin, actor participation in issues related to water quality is misaligned with modeled sources of nutrient pollution. This study demonstrates that the design and maintenance of water quality action situations play an important role in attracting the participation of actors working collaboratively to address wicked social-ecological problems. Further, linking current and potential configurations of governance networks to social-ecological outcomes can aid in the effective and efficient achievement of management objectives.

Reducing socio-ecological conflict using social influence modelling

Polarisation of opinions across communities can lead to social conflict, reputational damage and the disruption of operations and markets. Social influence models have been widely used to better understand processes driving conflict from a theoretical perspective. Using aquaculture as a case study, we demonstrate how such models can be extended to accurately hindcast the transition from population consensus to high conflict, including observed catastrophic tipping points. We then use the model to quantitatively evaluate strategies aimed at reducing aquaculture conflict. We found that persuasive advocacy was ineffective and often counterproductive, whereas meaningful engagement, collaborative learning and improving scientific literacy targeted broadly across the population was effective in moderating opinions and reducing conflict. When such messaging was targeted too narrowly or too infrequently, it tended to be negated by ongoing exchange of misinformation within the population. Both the modelling approach and lessons on effective communication strategies are relevant to a broad range of environmental conflicts.

Trees as brokers in social networks: Cascades of rights and benefits from a Cultural Keystone Species

Indigenous trees play key roles in West African landscapes, such as the néré tree (Parkia biglobosa (Jacq.) R.Br. ex G.Don). We applied social-ecological network analysis to understand the social-ecological interactions around néré. We documented the benefits néré provides and the multiple social interactions it creates amongst a large range of actors. The flows of rights over the trees and benefits from them formed two hierarchical networks, or cascades, with different actors at the top. The two forms of power revealed by the two cascades of rights and benefits suggest possible powers and counter-powers across gender, ethnicity, and age. We documented how the tree catalyses social interactions across diverse groups to sustain vital social connections, and co-constitute places, culture, and relationships. We argue that a paradigm shift is urgently needed to leverage the remarkable untapped potential of indigenous trees and Cultural Keystone Species in current global restoration and climate change agendas.

Socio-technical networks of infrastructure management: Network concepts and motifs for studying digitalization, decentralization, and integrated management

Networked infrastructure systems - including energy, transportation, water, and wastewater systems - provide essential services to society. Globally, these services are undergoing major transformative processes such as digitalization, decentralization, or integrated management. Such processes not only depend on technical changes in infrastructure systems but also include important social and socio-technical dimensions. In this article, we propose a socio-technical network perspective to study the ensemble of social actors and technical elements involved in an infrastructure system, and their complex relations. We conceptualize structurally explicit socio-technical networks of networked infrastructure systems based on methodological considerations from network analysis and draw on concepts from socio-technical system theories and social-ecological network studies. Based on these considerations, we suggest analytical methods to study basic network concepts such as density, reciprocity, and centrality in a socio-technical network. We illustrate socio-technical motifs, i.e., meaningful sub-structures in socio-technical networks of infrastructure management. Drawing on these, we describe how infrastructure systems can be analyzed in terms of digitalization, decentralization, and integrated management from a socio-technical network perspective. Using the example of urban wastewater systems, we illustrate an empirical application of our approach. The results of an empirical case study in Switzerland demonstrate the potential of socio-technical networks to promote a deeper understanding of complex socio-technical relations in networked infrastructure systems. We contend that such a deeper understanding could improve management practices of infrastructure systems and is becoming even more important for enabling future data-driven, decentralized, and more integrated infrastructure management.

Untangling social-ecological interactions: A methods portfolio approach to tackling contemporary sustainability challenges in fisheries

Meeting the objectives of sustainable fisheries management requires attention to the complex interactions between humans, institutions and ecosystems that give rise to fishery outcomes. Traditional approaches to studying fisheries often do not fully capture, nor focus on these complex interactions between people and ecosystems. Despite advances in the scope and scale of interactions encompassed by more holistic methods, for example ecosystem-based fisheries management approaches, no single method can adequately capture the complexity of human-nature interactions. Approaches that combine quantitative and qualitative analytical approaches are necessary to generate a deeper understanding of these interactions and illuminate pathways to address fisheries sustainability challenges. However, combining methods is inherently challenging and requires understanding multiple methods from different, often disciplinarily distinct origins, demanding reflexivity of the researchers involved. Social-ecological systems' research has a history of utilising combinations of methods across the social and ecological realms to account for spatial and temporal dynamics, uncertainty and feedbacks that are key components of fisheries. We describe several categories of analytical methods (statistical modelling, network analysis, dynamic modelling, qualitative analysis and controlled behavioural experiments) and highlight their applications in fisheries research, strengths and limitations, data needs and overall objectives. We then discuss important considerations of a methods portfolio development process, including reflexivity, epistemological and ontological concerns and illustrate these considerations via three case studies. We show that, by expanding their methods portfolios, researchers will be better equipped to study the complex interactions shaping fisheries and contribute to solutions for sustainable fisheries management.

How deep to dig: effects of web-scraping search depth on hyperlink network analysis of environmental stewardship organizations

Social network analysis (SNA) tools and concepts are essential for addressing many environmental management and sustainability issues. One method to gather SNA data is to scrape them from environmental organizations' websites. Web-based research can provide important opportunities to understand environmental governance and policy networks while potentially reducing costs and time when compared to traditional survey and interview methods. A key parameter is 'search depth,' i.e., how many connected pages within a website to search for information. Existing research uses a variety of depths and no best practices exist, undermining research quality and case study comparability. We therefore analyze how search depth affects SNA data collection among environmental organizations, if results vary when organizations have different objectives, and how search depth affects social network structure. We find that scraping to a depth of three captures the majority of relevant network data regardless of an organization's focus. Stakeholder identification (i.e., who is in the network) may require less scraping, but this might under-represent network structure (i.e., who is connected). We also discuss how scraping web-pages of local programs of larger organizations may lead to uncertain results and how our work can combine with mixed methods approaches.

Big data, computational social science, and other recent innovations in social network analysis

While sociologists have studied social networks for about one hundred years, recent developments in data, technology, and methods of analysis provide opportunities for social network analysis (SNA) to play a prominent role in the new research world of big data and computational social science (CSS). In our review, we focus on four broad topics: (1) Collecting Social Network Data from the Web, (2) Non-traditional and Bipartite/Multi-mode Networks, including Discourse and Semantic Networks, and Social-Ecological Networks, (3) Recent Developments in Statistical Inference for Networks, and (4) Ethics in Computational Network Research.

Conceptualizing ecosystem services using social-ecological networks

Social-ecological networks (SENs) represent the complex relationships between ecological and social systems and are a useful tool for analyzing and managing ecosystem services. However, mainstreaming the application of SENs in ecosystem service research has been hindered by a lack of clarity about how to match research questions to ecosystem service conceptualizations in SEN (i.e., as nodes, links, attributes, or emergent properties). Building from different disciplines, we propose a typology to represent ecosystem service in SENs and identify opportunities and challenges of using SENs in ecosystem service research. Our typology provides guidance for this growing field to improve research design and increase the breadth of questions that can be addressed with SEN to understand human-nature interdependencies in a changing world.

Study on the Relationship between Topological Characteristics of Vegetation Ecospatial Network and Carbon Sequestration Capacity in the Yellow River Basin, China

Achieving carbon neutrality is a necessary effort to rid humanity of a catastrophic climate and is a goal for China in the future. Ecological space plays an important role in the realization of carbon neutrality, but the relationship between the structure of vegetation ecological space and vegetation carbon sequestration capacity has been the focus of research. In this study, we extracted the base data from MODIS products and other remote sensing products, and then combined them with the MCR model to construct a vegetation ecospatial network in the Yellow River Basin in 2018. Afterward, we calculated the topological indicators of ecological nodes in the network and analyzed the relationship between the carbon sequestration capacity (net biome productivity) of ecological nodes and these topological indicators in combination with the Biome-BGC model. The results showed that there was a negative linear correlation between the betweenness centrality of forest nodes and their carbon sequestration capacity in the Yellow River Basin (p < 0.05, R2 = 0.59). On the other hand, there was a positive linear correlation between the clustering coefficient of grassland nodes and their carbon sequestration capacity (p < 0.01, R2 = 0.49). In addition, we briefly evaluated the vegetation ecospatial network in the Yellow River BASIN and suggested its optimization direction under the background of carbon neutrality in the future. Increasing the carbon sequestration capacity of vegetation through the construction of national ecological projects is one of the ways to achieve carbon neutrality, and this study provides a reference for the planning of future national ecological projects in the Yellow River Basin. Furthermore, this is also a case study of the application of remote sensing in vegetation carbon budgeting.

Complex Network-Based Research on the Resilience of Rural Settlements in Sanshui Watershed

In the context of farmland afforestation and urbanization, it is necessary for the small watershed rural settlements in the hilly–gully Loess Plateau to coordinate spatiotemporal changes and take the path of resilience development. In the case of the Sanshui Watershed, this paper investigates the rural settlement systems based on complex networks, and develops a research framework of “spatial simulation–resilience evaluation–spatial planning”. The results include the evolution trends of settlement space from present to future, as well as its spatial resilience in static and dynamic states. In this study, a total of six central villages and six types of rural development are finalized, and the study area possesses a prolonged spatiotemporal resilience when 29 villages remain, thus forming an ideal spatial pattern of “rural corridor zones + characteristic towns”. The findings of this study can represent guidance for resilience development in small watershed villages and provide a basis for guiding the regional urban–rural integration, village layout, as well as resource allocation and construction.

Environmental impacts of coronavirus disease 2019 (COVID-19)

The coronavirus disease (COVID-19), a variant of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) originated in Wuhan city of China and has now transmitted over the world. Till the April 24, 2020, nearly 144,367,284 confirmed positive cases with 3,066,270 deaths worldwide. The recent studies have reported that SARS-CoV-2 is transmitted through respiratory droplets. Several vaccines are available now. However, the vaccination process has not completed yet. Worldwide lockdown was initiated to restrict gathering, transport and industrial activities. Lockdown due to COVID-19 showed reduction in environmental pollution. The quality of air and water improved in metro cities and in rivers during COVID-19. This review not only provides the updated information related to impact of COVID-19 on air, water and noise pollution, generation of biomedical waste and global environmental sustainable development but also it covers the basic mechanism of COVID-19 transmission.

Universal scaling of robustness of ecosystem services to species loss

Ensuring reliable supply of services from nature is key to the sustainable development and well-being of human societies. Varied and frequently complex relationships between biodiversity and ecosystem services have, however, frustrated our capacity to quantify and predict the vulnerability of those services to species extinctions. Here, we use a qualitative Boolean modelling framework to identify universal drivers of the robustness of ecosystem service supply to species loss. These drivers comprise simple features of the networks that link species to the functions they perform that, in turn, underpin a service. Together, they define what we call network fragility. Using data from >250 real ecological networks representing services such as pollination and seed-dispersal, we demonstrate that network fragility predicts remarkably well the robustness of empirical ecosystem services. We then show how to quantify contributions of individual species to ecosystem service robustness, enabling quantification of how vulnerability scales from species to services. Our findings provide general insights into the way species, functional traits, and the links between them together determine the vulnerability of ecosystem service supply to biodiversity loss.

Effects of COVID-19 on the Sustainable Development Goals (SDGs)

Global crises caused by the pandemic of COVID-19, since early 2020, can compromise the world commitment to the 2030 Agenda for Sustainable Development. This study discusses critical aspects of the global pandemic for the achievement of the Sustainable Development Goals (SDGs). More precisely, we analyze how the new circumstances created by the pandemic have affected the interdependencies between SDGs. Following a synopsis of the current literature, we focus on effects regarding SDG3 (Health & Well-Being), SDG4 (Quality Education), SDG8 (Decent Work & Economic Growth), SDG12 (Consumption & Production) and SDG13 (Climate Action). Following a qualitative research approach, we based our analysis on moderated focus group discussions (FGD). Our observations reveal a unique pattern of interconnectedness between SDGs that can be related to COVID-19 consequences. Qualitative interpretations of focus group discussions also depict, that additional spillover effects can be obstacles for achieving SDG 5 (Gender Equality), SDG 9 (Infrastructure & Innovation) and SDG 10 (Reducing Inequalities), SDG 17 (partnerships for the goals), SDG 11 (sustainable cities). Therefore, we consider the interdependent implications and recent trends in international development related to sustainability as a useful framework in the post-pandemic recovery period.

Household and Community Social Capital Links to Smallholder Food Security

Agricultural adaptation to climate change is critical for ensuring future food security. Social capital is important for climate change adaptation, but institutions and social networks at multiple scales (e.g., household, community, and institution) have been overlooked in studying agricultural climate change adaptation. We combine data from 13 sites in 11 low-income countries in East Africa, West Africa, and South Asia to explore how multiple scales of social capital relate to household food security outcomes among smallholder farmers. Using social network theory, we define three community organizational social network types (fragmented defined by lack of coordination, brokered defined as having a strong central actor, or shared defined by high coordination) and examine household social capital through group memberships. We find community and household social capital are positively related, with higher household group membership more likely in brokered and shared networks. Household group membership is associated with more than a 10% reduction in average months of food insecurity, an effect moderated by community social network type. In communities with fragmented and shared organizational networks, additional household group memberships is associated with consistent decreases in food insecurity, in some cases up to two months; whereas in brokered networks, reductions in food insecurity are only associated with membership in credit groups. These effects are confirmed by hierarchical random effects models, which control for demographic factors. This suggests that multiple scales of social capital—both within and outside the household—are correlated with household food security. This social capital may both be bridging (across groups) and bonding (within groups) with different implications for how social capital structure affects food security. Efforts to improve food security could recognize the potential for both household and community level social networks and collaboration, which further research can capture by analyzing multiple scales of social capital data.

Social-ecological analysis of timely rice planting in Eastern India

Timely crop planting is a foundation for climate-resilient rice-wheat systems of the Eastern Gangetic Plains-a global food insecurity and poverty hotspot. We hypothesize that the capacity of individual farmers to plant on time varies considerably, shaped by multifaceted enabling factors and constraints that are poorly understood. To address this knowledge gap, two complementary datasets were used to characterize drivers and decision processes that govern the timing of rice planting in this region. The first dataset was a large agricultural management survey (rice-wheat: n = 15,245; of which rice: n = 7597) from a broad geographic region that was analyzed by machine learning methods. The second dataset was a discussion-based survey (n = 112) from a more limited geography that we analyzed with graph theory tools to elicit nuanced information on planting decisions. By combining insights from these methods, we show for the first time that differences in rice planting times are primarily shaped by ecosystem and climate factors while social factors play a prominent secondary role. Monsoon onset, surface and groundwater availability, and land type determine village-scale mean planting times whereas, for resource-constrained farmers who tend to plant later ceteris paribus, planting is further influenced by access to farm machinery, seed, fertilizer, and labor. Also, a critical threshold for economically efficient pumping appears at a groundwater depth of around 4.5 m; below this depth, farmers do not irrigate and delay planting. Without collective action to spread risk through synchronous timely planting, ecosystem factors such as threats posed by pests and wild animals may further deter early planting by individual farmers. Accordingly, we propose a three-pronged strategy that combines targeted strengthening of agricultural input chains, agroadvisory development, and coordinated rice planting and wildlife conservation to support climate-resilient agricultural development in the Eastern Gangetic Plains.

Monitoring social–ecological networks for biodiversity and ecosystem services in human-dominated landscapes

The demand the human population is placing on the environment has triggered accelerated rates of biodiversity change and created trade-offs among the ecosystem services we depend upon. Decisions designed to reverse these trends require the best possible information obtained by monitoring ecological and social dimensions of change. Here, we conceptualize a network framework to monitor change in social–ecological systems. We contextualize our framework within Ostrom’s social–ecological system framework and use it to discuss the challenges of monitoring biodiversity and ecosystem services across spatial and temporal scales. We propose that spatially explicit multilayer and multiscale monitoring can help estimate the range of variability seen in social–ecological systems with varying levels of human modification across the landscape. We illustrate our framework using a conceptual case study on the ecosystem service of maple syrup production. We argue for the use of analytical tools capable of integrating qualitative and quantitative knowledge of social–ecological systems to provide a causal understanding of change across a network. Altogether, our conceptual framework provides a foundation for establishing monitoring systems. Operationalizing our framework will allow for the detection of ecosystem service change and assessment of its drivers across several scales, informing the long-term sustainability of biodiversity and ecosystem services.

Marine conservation: towards a multi-layered network approach

Valuing, managing and conserving marine biodiversity and a full range of ecosystem services is at the forefront of research and policy agendas. However, biodiversity is being lost at up to a thousand times the average background rate. Traditional disciplinary and siloed conservation approaches are not able to tackle this massive loss of biodiversity because they generally ignore or overlook the interactive and dynamic nature of ecosystems processes, limiting their predictability. To conserve marine biodiversity, we must assess the interactions and impacts among biodiversity and ecosystem services (BD-ES). The scaling up in complexity from single species to entire communities is necessary, albeit challenging, for a deeper understanding of how ecosystem services relate to biodiversity and the roles species have in ecosystem service provision. These interactions are challenging to map, let alone fully assess, but network and system-based approaches provide a powerful way to progress beyond those limitations. Here, we introduce a conceptual multi-layered network approach to understanding how ecosystem services supported by biodiversity drive the total service provision, how different stressors impact BD-ES and where conservation efforts should be placed to optimize the delivery of ecosystem services and protection of biodiversity. This article is part of the theme issue 'Integrative research perspectives on marine conservation'.

Social-Ecological Connectivity to Understand Ecosystem Service Provision across Networks in Urban Landscapes

Landscape connectivity is a critical component of dynamic processes that link the structure and function of networks at the landscape scale. In the Anthropocene, connectivity across a landscape-scale network is influenced not only by biophysical land use features, but also by characteristics and patterns of the social landscape. This is particularly apparent in urban landscapes, which are highly dynamic in land use and often in social composition. Thus, landscape connectivity, especially in cities, must be thought of in a social-ecological framework. This is relevant when considering ecosystem services—the benefits that people derive from ecological processes and properties. As relevant actors move through a connected landscape-scale network, particular services may “flow” better across space and time. For this special issue on dynamic landscape connectivity, we discuss the concept of social-ecological networks using urban landscapes as a focal system to highlight the importance of social-ecological connectivity to understand dynamic urban landscapes, particularly in regards to the provision of urban ecosystem services.

Land-use intensity alters networks between biodiversity, ecosystem functions, and services

Land-use intensification can increase provisioning ecosystem services, such as food and timber production, but it also drives changes in ecosystem functioning and biodiversity loss, which may ultimately compromise human wellbeing. To understand how changes in land-use intensity affect the relationships between biodiversity, ecosystem functions, and services, we built networks from correlations between the species richness of 16 trophic groups, 10 ecosystem functions, and 15 ecosystem services. We evaluated how the properties of these networks varied across land-use intensity gradients for 150 forests and 150 grasslands. Land-use intensity significantly affected network structure in both habitats. Changes in connectance were larger in forests, while changes in modularity and evenness were more evident in grasslands. Our results show that increasing land-use intensity leads to more homogeneous networks with less integration within modules in both habitats, driven by the belowground compartment in grasslands, while forest responses to land management were more complex. Land-use intensity strongly altered hub identity and module composition in both habitats, showing that the positive correlations of provisioning services with biodiversity and ecosystem functions found at low land-use intensity levels, decline at higher intensity levels. Our approach provides a comprehensive view of the relationships between multiple components of biodiversity, ecosystem functions, and ecosystem services and how they respond to land use. This can be used to identify overall changes in the ecosystem, to derive mechanistic hypotheses, and it can be readily applied to further global change drivers.

Governance networks around grasslands with contrasting management history

Romanian grasslands have high nature value, being among the most important biodiversity hotspots at the European level. The European Union Common Agricultural Policy (CAP) contradicts the Biodiversity Strategy to 2020 objectives by hindering coordinated grassland governance and collaboration among the involved actors. At the European level, few attempts have been made in creating conceptual strategies for implementing conservation measures in a multi-actor and multi-scale governance setting. Our paper focuses on a comparative network analysis of grassland governance of three Romanian regions (Iron Gates Natural Park - SW; Sighisoara - Tarnava Mare - center; and Dobrogea - SE), representatives for grassland management in mountain and lowland landscapes. We investigated the structural characteristics of one-mode directed governance networks in the three protected areas (standard cohesion and reciprocity metrics, exponential random graph models), the position of actors participating in networks (node-level centrality metrics), and the perception of CAP influence on grassland governance by farmers benefiting of CAP agri-environmental payments. In Sighisoara, grassland governance has been centralized but biodiversity-friendly, while in Iron Gates, grasslands were traditionally managed through a decentralized, community-level system, and this type of governance continues to date. In Dobrogea, grassland governance was performed in an intensive, centralized state-run management regime during the communist time and by large landowners after the transition period ended. Our findings illustrate the structure of the three governance networks and dissimilar patterns of collaboration, indicating distinct particularities to be considered when exploring barriers to and options for successful governance in traditionally managed grasslands in the context of CAP measures-driven management.

Socio-ecological network structures from process graphs

We propose a process graph (P-graph) approach to develop ecosystem networks from knowledge of the properties of the component species. Originally developed as a process engineering tool for designing industrial plants, the P-graph framework has key advantages over conventional ecological network analysis techniques based on input-output models. A P-graph is a bipartite graph consisting of two types of nodes, which we propose to represent components of an ecosystem. Compartments within ecosystems (e.g., organism species) are represented by one class of nodes, while the roles or functions that they play relative to other compartments are represented by a second class of nodes. This bipartite graph representation enables a powerful, unambiguous representation of relationships among ecosystem compartments, which can come in tangible (e.g., mass flow in predation) or intangible form (e.g., symbiosis). For example, within a P-graph, the distinct roles of bees as pollinators for some plants and as prey for some animals can be explicitly represented, which would not otherwise be possible using conventional ecological network analysis. After a discussion of the mapping of ecosystems into P-graph, we also discuss how this framework can be used to guide understanding of complex networks that exist in nature. Two component algorithms of P-graph, namely maximal structure generation (MSG) and solution structure generation (SSG), are shown to be particularly useful for ecological network analysis. These algorithms enable candidate ecosystem networks to be deduced based on current scientific knowledge on the individual ecosystem components. This method can be used to determine the (a) effects of loss of specific ecosystem compartments due to extinction, (b) potential efficacy of ecosystem reconstruction efforts, and (c) maximum sustainable exploitation of human ecosystem services by humans. We illustrate the use of P-graph for the analysis of ecosystem compartment loss using a small-scale stylized case study, and further propose a new criticality index that can be easily derived from SSG results.

Key considerations and challenges in the application of social-network research for environmental decision making

Attempts to better understand the social context in which conservation and environmental decisions are made has led to increased interest in human social networks. To improve the use of social-network analysis in conservation, we reviewed recent studies in the literature in which such methods were applied. In our review, we looked for problems in research design and analysis that limit the utility of network analysis. Nineteen of 55 articles published from January 2016 to June 2019 exhibited at least 1 of the following problems: application of analytical methods inadequate or sensitive to incomplete network data; application of statistical approaches that ignore dependency in the network; or lack of connection between the theoretical base, research question, and choice of analytical techniques. By drawing attention to these specific areas of concern and highlighting research frontiers and challenges, including causality, network dynamics, and new approaches, we responded to calls for increasing the rigorous application of social science in conservation.

Cross-scale cooperation enables sustainable use of a common-pool resource

In social-ecological systems (SESs), social and biophysical dynamics interact within and between the levels of organization at multiple spatial and temporal scales. Cross-scale interactions (CSIs) are interdependences between processes at different scales, generating behaviour unpredictable at single scales. Understanding CSIs is important for improving SES governance, but they remain understudied. Theoretical models are needed that capture essential features while being simple enough to yield insights into mechanisms. In a stylized model, we study CSIs in a two-level system of weakly interacting communities harvesting a common-pool resource. Community members adaptively conform to, or defect from, a norm of socially optimal harvesting, enforced through social sanctioning both within and between communities. We find that each subsystem's dynamics depend sensitively on the other despite interactions being much weaker between subsystems than within them. When interaction is purely biophysical, stably high cooperation in one community can cause cooperation in the other to collapse. However, even weak social interaction can prevent the collapse of cooperation and instead cause collapse of defection. We identify conditions under which subsystem-level cooperation produces desirable system-level outcomes. Our findings expand evidence that collaboration is important for sustainably managing shared resources, showing its importance even when resource sharing and social relationships are weak.

Alignment of social and ecological structures increased the ability of river management

Large hydrologic basins involve multiple stakeholders, and coupled dynamic social and ecological processes. Managing such basins has long been a challenge. Balancing the demand for water from nature against that from humans is always difficult, particularly in arid watersheds. Here, we analyze potential institutional causes of ecological degradation and how it can be reversed by introducing new forms of governance. The framework and assumptions are illustrated using China's second-largest endorheic basin, where empirical evidence shows that the introduction of a new governing authority connecting midstream and downstream actors facilitated the establishment of a new governance regime that is better aligned with the biophysical scales of the watershed. A trans-regional water allocation project initiated by the new higher-level authority successfully rescued downstream oases and restored a dried terminal lake. These outcomes suggest that when social and ecological structures are better aligned our ability to manage the interplay between social and ecological processes increases. However, the lack of direct connection between the actors of the middle and lower reaches resulted in the paradox of an increase in water demand. We therefore suggest that measures to stimulate the emergence of horizontal social ties linking different critical groups of actors across the watershed could further the alignment of the institutional and biophysical structures-without these changes sustainable management of river basins and other common pool resources will remain problematic.

Social-ecological network analysis for sustainability sciences: a systematic review and innovative research agenda for the future

Social-ecological network (SEN) concepts and tools are increasingly used in human-environment and sustainability sciences. We take stock of this budding research area to further show the strength of SEN analysis for complex human-environment settings, identify future synergies between SEN and wider human-environment research, and provide guidance about when to use different kinds of SEN approaches and models. We characterize SEN research along a spectrum specifying the degree of explicit network representation of system components and dynamics. We then systematically review one end of this spectrum, what we term "fully articulated SEN" studies, which specifically model unique social and ecological units and relationships. Results show more focus on methodological advancement and applied ends. While there has been some development and testing of theories, this remains an area for future work and would help develop SENs as a unique field of research, not just a method. Authors have studied diverse systems, while mainly focused on the problem of social-ecological fit alongside a scattering of other topics. There is strong potential, however, to engage other issues central to human-environment studies. Analyzing the simultaneous effects of multiple social, environmental, and coupled processes, change over time, and linking network structures to outcomes are also areas for future advancement. This review provides a comprehensive assessment of (fully articulated) SEN research, a necessary step that can help scholars develop comparable cases and fill research gaps.