Decreasing resilience of China's coupled nitrogen-phosphorus cycling network requires urgent action.

The coupled nature of the nitrogen (N) and phosphorus (P) cycling networks is of critical importance for sustainable food systems. Here we use material flow and ecological network analysis methods to map the N-P-coupled cycling network in China and evaluate its resilience. Results show a drop in resilience between 1980 and 2020, with further decreases expected by 2060 across different socio-economic pathways. Under a clean energy scenario with additional N and P demand, the resilience of the N-P-coupled cycling network would suffer considerably, especially in the N layer. China's socio-economic system may also see greater N emissions to the environment, thus disturbing the N cycle and amplifying the conflict between energy and food systems given the scarcity of P. Our findings on scenario-specific synergies and trade-offs can aid the management of N- and P-cycling networks in China by reducing chemical fertilizer use and food waste, for example.

Participatory approach for assessing institutional resilience: a case study of crises in Austria.

This paper outlines the procedure of employing novel software tools within a series of participatory workshops designed for measuring and monitoring the resilience of Austria's socioeconomic system based on network analysis and systems research. This study employs the principles of the four-stage adaptive cycle to quantify the perspectives of major stakeholders regarding resilience readiness in Austrian society and to explore the implications. At the FASresearch company in Vienna, 278 representatives from 15 key sectors of Austrian society were asked to estimate the resilience of their respective sectors and identify the key resilience factors for each sector. Results pinpoint the most critical stakeholders and resilience factors, highlight the importance of quality relationships among stakeholders, and indicate that while stakeholders accurately perceive the stages of growth (r), equilibrium (K), and regeneration (α), they tend to underestimate the significance of the final (Ω) stage of the adaptive cycle, characterized by disturbance and collapse of outdated systems. Improved recognition and preparation for each stage may result in the increased resilience of each sector to potential crises in the future. Notably, perspectives regarding resilience in the face of a crisis were gathered prior to the occurrence of the COVID-19 pandemic. Thus, in addition to fulfilling an analytic-diagnostic function, resilience monitoring techniques are also intended as an adaptive tool for novel resilience management. Supplementary Information: The online version contains supplementary material available at 10.1007/s10668-022-02430-3.

Two classes of functional connectivity in dynamical processes in networks.

The relationship between network structure and dynamics is one of the most extensively investigated problems in the theory of complex systems of recent years. Understanding this relationship is of relevance to a range of disciplines-from neuroscience to geomorphology. A major strategy of investigating this relationship is the quantitative comparison of a representation of network architecture (structural connectivity, SC) with a (network) representation of the dynamics (functional connectivity, FC). Here, we show that one can distinguish two classes of functional connectivity-one based on simultaneous activity (co-activity) of nodes, the other based on sequential activity of nodes. We delineate these two classes in different categories of dynamical processes-excitations, regular and chaotic oscillators-and provide examples for SC/FC correlations of both classes in each of these models. We expand the theoretical view of the SC/FC relationships, with conceptual instances of the SC and the two classes of FC for various application scenarios in geomorphology, ecology, systems biology, neuroscience and socio-ecological systems. Seeing the organisation of dynamical processes in a network either as governed by co-activity or by sequential activity allows us to bring some order in the myriad of observations relating structure and function of complex networks.

Global Urban Carbon Networks: Linking Inventory to Modeling.

Cities utilize and manipulate an immense amount of global carbon flows through their economic and technical activities. Here, we establish the carbon networks of eight global cities by tracking the carbon exchanges between various natural and economic components. The metabolic properties of these carbon networks are compared by combining flow-based and interpretative network metrics. We further assess the relations of these carbon metabolic properties of cities with their socioeconomic attributes that are deemed important in urban development and planning. We find that, although there is a large difference in city-level carbon balance and flow pattern, a similarity in intercomponent relationships and metabolic characteristicsdoes exist. Cities with lower per capita carbon emissions tend to have healthier metabolic systems with more cooperative resource allocation among various industries, which indicates that there may be synergy between urban decarbonization and carbon-containing resource system optimization. A combination of indicators from flow balance and network models is a promising scheme for linking sector-based carbon inventories to system-based simulations of carbon management efforts. With this done, we may be able to reduce the knowledge gap with respect to how various carbon flows in cities can be concertedly managed considering both the restraint from their climate mitigation goals as well as the impact on urban social and economic development.

Redundancy, Diversity, and Modularity in Network Resilience: Applications for International Trade and Implications for Public Policy.

Sustainability is increasingly concerned with the complex interactions between nature and society, and we need to seek solutions towards the challenges that threaten humanity's collective wellbeing. Towards this end, it is critical to advance the application of research examining the dynamic interactions of the components of complex social-ecological systems and their emerging properties. A key research area is on advancing tools and strategies relevant to the evaluation and strengthening of resilience. Redundancy, diversity, and modularity are important characteristics of resilience with a high potential for application in various critical social-ecological systems. This paper provides a critical overview of the theoretical underpinnings of modularity and redundancy and their application in measuring resilience of trade networks with implications for public policy and institutional design.

Network resilience of phosphorus cycling in China has shifted by natural flows, fertilizer use and dietary transitions between 1600 and 2012.

The resilience of the phosphorus (P) cycling network is critical to ecosystem functioning and human activities. Although P cycling pathways have been previously mapped, a knowledge gap remains in evaluating the P network's ability to withstand shocks or disturbances. Applying principles of mass balance and ecological network analysis, we examine the network resilience of P cycling in China from 1600 to 2012. The results show that changes in network resilience have shifted from being driven by natural P flows for food production to being driven by industrial P flows for chemical fertilizer production. Urbanization has intensified the one-way journey of P, further deteriorating network resilience. Over 2000-2012, the network resilience of P cycling has decreased by 11% owing to dietary changes towards more animal-based foods. A trade-off between network resilience improvement and increasing food trade is also observed. These findings can support policy decisions for enhanced P cycling network resilience in China.

A Systems Approach To Assess Trade Dependencies in U.S. Food-Energy-Water Nexus.

We present a network model of the United States (U.S.) interstate food transfers to analyze the trade dependency with respect to participating regions and embodied irrigation impacts from a food-energy-water (FEW) nexus perspective. To this end, we utilize systems analysis methods including the pointwise mutual information (PMI) measure to provide an indication of interdependencies by estimating probability of trade between states. PMI compares observed trade with a benchmark of what is statistically expected given the structure and flow in the network. This helps assess whether dependencies arising from empirically observed trade occur due to chance or preferential attachment. The implications of PMI values are demonstrated by using Texas as an example, the largest importer in the U.S. grain transfer network. We find that strong dependencies exist not only just with states (Kansas, Oklahoma, Nebraska) providing high volume of transfer to Texas but also with states that have comparatively lower trade (New Mexico). This is due to New Mexico's reliance on Texas as an important revenue source compared to its other connections. For Texas, import interdependencies arise from geographical proximity to trade. As these states primarily rely on the commonly shared High Plains aquifer for irrigation, overreliance poses a risk for water shortage for food supply in Texas. PMI values also indicate the capacity to trade more (the states are less reliant on each other than expected), and therefore provide an indication of where the trade could be shifted to avoid groundwater scarcity. However, some of the identified states rely on GHG emission intensive fossil fuels such as diesel and gasoline for irrigation, highlighting a potential tradeoff between crop water footprint and switching to lower emissions pumping fuels.

Causal relationship in the interaction between land cover change and underlying surface climate in the grassland ecosystems in China.

Land-climate interactions are driven by causal relations that are difficult to ascertain given the complexity and high dimensionality of the systems. Many methods of statistical and mechanistic models exist to identify and quantify the causality in such highly-interacting systems. Recent advances in remote sensing development allowed people to investigate the land-climate interaction with spatially and temporally continuous data. In this study, we present a new approach to measure how climatic factors interact with each other under land cover change. The quantification method is based on the correlation analysis of the different order derivatives, with the canonical mathematical definitions developed from the theories of system dynamics and practices of the macroscopic observations. We examined the causal relationship between the interacting variables on both spatial and temporal dimensions based on macroscopic observations of land cover change and surface climatic factors through a comparative study in the different grassland ecosystems of China. The results suggested that the interaction of land-climate could be used to explain the temporal lag effect in the comparison of the three grassland ecosystems. Significant spatial correlations between the vegetation and the climatic factors confirmed feedback mechanisms described in the theories of eco-climatology, while the uncertain temporal synchronicity reflects the causality among the key indicators. This has been rarely addressed before. Our research show that spatial correlations and the temporal synchronicity among key indicators of the land surface and climatic factors can be explained by a novel method of causality quantification using derivative analysis.

A dynamic management framework for socio-ecological system stewardship: A case study for the United States Bureau of Ocean Energy Management.

An effective and efficient stewardship of natural resources requires consistency across all decision-informing approaches and components involved, i.e., managerial, governmental, political, and legal. To achieve this consistency, these elements must be aligned under an overarching management goal that is consistent with current and well-accepted knowledge. In this article, we investigate the adoption by the US Bureau of Ocean Energy Management of an environmental resilience-centered system that manages for resilience of marine ecological resources and its associated social elements. Although the framework is generally tailored for this Bureau, it could also be adapted to other federal or non-federal organizations. This paper presents a dynamic framework that regards change as an inherent element of the socio-ecological system in which management structures, e.g., federal agencies, are embedded. The overall functioning of the management framework being considered seeks to mimic and anticipate environmental change in line with well-accepted elements of resilience-thinking. We also investigate the goal of using management for resilience as a platform to enhance socio-ecological sustainability by setting specific performance metrics embedded in pre-defined and desired social and/or ecological scenarios. Dynamic management frameworks that couple social and ecological systems as described in this paper can facilitate the efficient and effective utilization of resources, reduce uncertainty for decision and policy makers, and lead to more defensible decisions on resources.

Effects of abiotic factors on ecosystem health of Taihu Lake, China based on eco-exergy theory.

A lake ecosystem is continuously exposed to environmental stressors with non-linear interrelationships between abiotic factors and aquatic organisms. Ecosystem health depicts the capacity of system to respond to external perturbations and still maintain structure and function. In this study, we explored the effects of abiotic factors on ecosystem health of Taihu Lake in 2013, China from a system-level perspective. Spatiotemporal heterogeneities of eco-exergy and specific eco-exergy served as thermodynamic indicators to represent ecosystem health in the lake. The results showed the plankton community appeared more energetic in May, and relatively healthy in Gonghu Bay with both higher eco-exergy and specific eco-exergy; a eutrophic state was likely discovered in Zhushan Bay with higher eco-exergy but lower specific eco-exergy. Gradient Boosting Machine (GBM) approach was used to explain the non-linear relationships between two indicators and abiotic factors. This analysis revealed water temperature, inorganic nutrients, and total suspended solids greatly contributed to the two indicators that increased. However, pH rise driven by inorganic carbon played an important role in undermining ecosystem health, particularly when pH was higher than 8.2. This implies that climate change with rising CO2 concentrations has the potential to aggravate eutrophication in Taihu Lake where high nutrient loads are maintained.

Network structure impacts global commodity trade growth and resilience.

Global commodity trade networks are critical to our collective sustainable development. Their increasing interconnectedness pose two practical questions: (i) Do the current network configurations support their further growth? (ii) How resilient are these networks to economic shocks? We analyze the data of global commodity trade flows from 1996 to 2012 to evaluate the relationship between structural properties of the global commodity trade networks and (a) their dynamic growth, as well as (b) the resilience of their growth with respect to the 2009 global economic shock. Specifically, we explore the role of network efficiency and redundancy using the information theory-based network flow analysis. We find that, while network efficiency is positively correlated with growth, highly efficient systems appear to be less resilient, losing more and gaining less growth following an economic shock. While all examined networks are rather redundant, we find that network redundancy does not hinder their growth. Moreover, systems exhibiting higher levels of redundancy lose less and gain more growth following an economic shock. We suggest that a strategy to support making global trade networks more efficient via, e.g., preferential trade agreements and higher specialization, can promote their further growth; while a strategy to increase the global trade networks' redundancy via e.g., more abundant free-trade agreements, can improve their resilience to global economic shocks.

Coupling ecological and social network models to assess "transmission" and "contagion" of an aquatic invasive species.

Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensis alters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems.

A Network Flow Analysis of the Nitrogen Metabolism in Beijing, China.

Rapid urbanization results in high nitrogen flows and subsequent environmental consequences. In this study, we identified the main metabolic components (nitrogen inputs, flows, and outputs) and used ecological network analysis to track the direct and integral (direct + indirect) metabolic flows of nitrogen in Beijing, China, from 1996 to 2012 and to quantify the structure of Beijing's nitrogen metabolic processes. We found that Beijing's input of new reactive nitrogen (Q, which represents nitrogen obtained from the atmosphere or nitrogen-containing materials used in production and consumption to support human activities) increased from 431 Gg in 1996 to 507 Gg in 2012. Flows to the industry, atmosphere, and household, and components of the system were clearly largest, with total integrated inputs plus outputs from these nodes accounting for 31, 29, and 15%, respectively, of the total integral flows for all paths. The flows through the sewage treatment and transportation components showed marked growth, with total integrated inputs plus outputs increasing to 3.7 and 5.2 times their 1996 values, respectively. Our results can help policymakers to locate the key nodes and pathways in an urban nitrogen metabolic system so they can monitor and manage these components of the system.

Spatial variation in the ecological relationships among the components of Beijing's carbon metabolic system.

In this paper, we construct a spatially explicit model of carbon metabolism for the flows of carbon among the components of an urban area. We used the model to identify spatial heterogeneity in the ecological relationships within a carbon metabolic network. We combined land-use and cover type maps for Beijing from 1990 to 2010 with empirical coefficients and socioeconomic data to quantify the flows. We used utility analysis to determine the ecological relationships between the components of the system and analyzed their changes during urban development. We used ArcGIS to analyze their spatial variation. We found that the positive utilities in Beijing decreased over time and that negative relationships mostly outweighed positive relationships after 2000. The main ecological relationships were distributed throughout the entire urban area before 2000; subsequently, exploitation, control, and mutualism relationships became concentrated in the southeast, leaving competition relationships to dominate the northwest. Mutualism relationships were most common for natural components, but were not stable because they were easily disturbed by urban expansion. Transportation and industrial land and urban land were the most important contributors to exploitation and control relationships and may be important indicators of spatial adjustment. Increasing competition relationships unbalanced the carbon metabolism, and limitations on the area of land available for development and on the water resources led to increasingly serious competition. The results provide an objective basis for planning adjustments to Beijing's land-use patterns to improve its carbon metabolism and reduce carbon emission.

Urban ecosystem modeling and global change: potential for rational urban management and emissions mitigation.

Urbanization is a strong and extensive driver that causes environmental pollution and climate change from local to global scale. Modeling cities as ecosystems has been initiated by a wide range of scientists as a key to addressing challenging problems concomitant with urbanization. In this paper, 'urban ecosystem modeling (UEM)' is defined in an inter-disciplinary context to acquire a broad perception of urban ecological properties and their interactions with global change. Furthermore, state-of-the-art models of urban ecosystems are reviewed, categorized as top-down models (including materials/energy-oriented models and structure-oriented models), bottom-up models (including land use-oriented models and infrastructure-oriented models), or hybrid models thereof. Based on the review of UEM studies, a future framework for explicit UEM is proposed based the integration of UEM approaches of different scales, guiding more rational urban management and efficient emissions mitigation.

Ecological network analysis of an urban metabolic system based on input-output tables: model development and case study for Beijing.

If cities are considered as "superorganisms", then disorders of their metabolic processes cause something analogous to an "urban disease". It is therefore helpful to identify the causes of such disorders by analyzing the inner mechanisms that control urban metabolic processes. Combining input-output analysis with ecological network analysis lets researchers study the functional relationships and hierarchy of the urban metabolic processes, thereby providing direct support for the analysis of urban disease. In this paper, using Beijing as an example, we develop a model of an urban metabolic system that accounts for the intensity of the embodied ecological elements using monetary input-output tables from 1997, 2000, 2002, 2005, and 2007, and use this data to compile the corresponding physical input-output tables. This approach described the various flows of ecological elements through urban metabolic processes and let us build an ecological network model with 32 components. Then, using two methods from ecological network analysis (flow analysis and utility analysis), we quantitatively analyzed the physical input-output relationships among urban components, determined the ecological hierarchy of the components of the metabolic system, and determined the distribution of advantage-dominated and disadvantage-dominated relationships, thereby providing scientific support to guide restructuring of the urban metabolic system in an effort to prevent or cure urban "diseases".

Ecological network analysis of an urban water metabolic system: model development, and a case study for Beijing.

Using ecological network analysis, we analyzed the network structure and ecological relationships in an urban water metabolic system. We developed an ecological network model for the system, and used Beijing as an example of analysis based on the model. We used network throughflow analysis to determine the flows among components, and measured both indirect and direct flows. Using a network utility matrix, we determined the relationships and degrees of mutualism among six compartments--1) local environment, 2) rainwater collection, 3) industry, 4) agriculture, 5) domestic sector, and 6) wastewater recycling--which represent producer, consumer, and reducer trophic levels. The capacity of producers to provide water for Beijing decreased from 2003 to 2007, and consumer demand for water decreased due to decreasing industrial and agricultural demand; the recycling capacity of reducers also improved, decreasing the discharge pressure on the environment. The ecological relationships associated with the local environment or the wastewater recycling sector changed little from 2003 to 2007. From 2003 to 2005, the main changes in the ecological relationships among components of Beijing's water metabolic system mostly occurred between the local environment, the industrial and agricultural sectors, and the domestic sector, but by 2006 and 2007, the major change was between the local environment, the agricultural sector, and the industrial sector. The other ecological relationships did not change during the study period. Although Beijing's mutualism indices remained generally stable, the ecological relationships among compartments changed greatly. Our analysis revealed ways to further optimize this system and the relationships among compartments, thereby optimizing future urban water resources development.

Urban ecosystem health assessment: a review.

Due to the important role of cities for regional, national, and international economic development and the concurrent degradation of the urban environmental quality under rapid urbanization, a systematic diagnosis of urban ecosystem health for sustainable ecological management is urgently needed. This paper reviews the related research on urban ecosystem health assessment, beginning from the inception of urban ecosystem health concerns propelled by the development needs of urban ecosystems and the advances in ecosystem health research. Concepts, standards, indicators, models, and case studies are introduced and discussed. Urban ecosystem health considers the integration of ecological, economic, social and human health factors, and as such it is a value-driven concept which is strongly influenced by human perceptions. There is not an absolute urban ecosystem standard because of the uncertainty caused by the changing human needs, targets, and expectation of urban ecosystem over time; thus, suitable approaches are still needed to establish health standards of urban ecosystems. Several conceptual models and suitable indicator frameworks have been proposed to organize the multiple factors to represent comprehensively the health characteristics of an urban ecosystem, while certain mathematical methods have been applied to deal with the indicator information to get a clear assessment of the urban ecosystem health status. Instead of perceiving the urban ecosystem assessment as an instantaneous measurement of the health state, it is suggested to conceptualize the urban ecosystem health as a process, which impels us to focus more studies on the dynamic trends of health status and projecting possible development scenarios.

Functional integration of ecological networks through pathway proliferation.

Large-scale structural patterns commonly occur in network models of complex systems including a skewed node degree distribution and small-world topology. These patterns suggest common organizational constraints and similar functional consequences. Here, we investigate a structural pattern termed pathway proliferation. Previous research enumerating pathways that link species determined that as pathway length increases, the number of pathways tends to increase without bound. We hypothesize that this pathway proliferation influences the flow of energy, matter, and information in ecosystems. In this paper, we clarify the pathway proliferation concept, introduce a measure of the node-node proliferation rate, describe factors influencing the rate, and characterize it in 17 large empirical food-webs. During this investigation, we uncovered a modular organization within these systems. Over half of the food-webs were composed of one or more subgroups that were strongly connected internally, but weakly connected to the rest of the system. Further, these modules had distinct proliferation rates. We conclude that pathway proliferation in ecological networks reveals subgroups of species that will be functionally integrated through cyclic indirect effects.

Ecosystem growth and development.

One of the most important features of biosystems is how they are able to maintain local order (low entropy) within their system boundaries. At the ecosystem scale, this organization can be observed in the thermodynamic parameters that describe it, such that these parameters can be used to track ecosystem growth and development during succession. Thermodynamically, ecosystem growth is the increase of energy throughflow and stored biomass, and ecosystem development is the internal reorganization of these energy mass stores, which affect transfers, transformations, and time lags within the system. Several proposed hypotheses describe thermodynamically the orientation or natural tendency that ecosystems follow during succession, and here, we consider five: minimize specific entropy production, maximize dissipation, maximize exergy storage (includes biomass and information), maximize energy throughflow, and maximize retention time. These thermodynamic orientors were previously all shown to occur to some degree during succession, and here we present a refinement by observing them during different stages of succession. We view ecosystem succession as a series of four growth and development stages: boundary, structural, network, and informational. We demonstrate how each of these ecological thermodynamic orientors behaves during the different growth and development stages, and show that while all apply during some stages only maximizing energy throughflow and maximizing exergy storage are applicable during all four stages. Therefore, we conclude that the movement away from thermodynamic equilibrium, and the subsequent increase in organization during ecosystem growth and development, is a result of system components and configurations that maximize the flux of useful energy and the amount of stored exergy. Empirical data and theoretical models support these conclusions.