Environ analysis, based on network theory, is a methodology to quantify how objects interact with and depend on other objects in a system. The primary result from the method provides input and output 'environs'. In addition, application of network environ analysis on empirical data sets and ecosystem models has revealed several important and unexpected results that have been identified and summarized in the literature as network environ properties. Data requirements for the analysis include the intercompartmental flows, compartmental storages, and boundary input and output flows. This article reviews the theoretical underpinning of the analysis and briefly introduces some the main properties such as indirect effects ratio, network homogenization, and network mutualism.

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.

In this chapter, we provide an overview of the rise of ecological modeling as a problem-solving tool for environmental management including a review of some of the more important and widely used models. While there has been a great increase in the computing power available to simulate ecological systems, a few fundamental concepts, which were already identified in the early days of ecological modeling, are still unresolved. These include boundary formulation, objective function identification, data requirements, subsystem integration, clarity on the acceptability of assumptions, and effective communication of results to decision makers. In order for ecological modeling to realize its full potential, further progress is needed in these areas. By looking back over the history and successes of this important approach, we hope to set the stage for the next period of development to address these issues.

Urban activities currently consume 75% of global final energy demand, which is expected to increase given absolute and relative population growth in cities. Assessments of both producer (upstream) and consumer (downstream) ecological and socioeconomic impacts of urban inter-industry exchanges are needed to reduce energy consumption and resource use behind the industrial footprints of cities. Environmental extensions in the input-output analysis are designed from the user side perspective, focusing only on commercial energy supply and use. This study introduced emergy-evaluated supply-extended and use-extended carbon footprint models for Vienna and compared their empirical and conceptual implications. Emergy-evaluated footprints of Vienna's urban consumption were estimated by combining industrial and systems ecology approaches as per the research question, based on previous investigations of GHG emissions and energy supply- and use-extensions. Results showed that the ranking of footprints of final product categories is sensitive to the evaluation method, with products of extractive and manufacturing industries differing by more than 10% depending on whether emergy or carbon evaluation is chosen. The emergy-based comparison further reveals that for products of extractive industries, the difference between use and supply extension results can be more than 20% as opposed to carbon-based comparison with the difference between supply and use extension results for services not even amounting to 5%. Future studies could address the over-estimation of direct energy supply to the economy, under-estimation of product and service, inconsistency in standard use-extension design, and challenges in assembling emergy-evaluated supply and use extensions. Fundings are relevant for unified responsibility assessment of upstream and downstream sectors without prioritising structural features.

The goal of testing the theoretical fruitfulness and empirical utility of the links between ecology and thermodynamics has been elusive. This could explain the breakdown of ecology into multiple branches, some of them intended to develop models in agreement with the principles of physics. The maximum entropy algorithm (MaxEnt) is one of the most frequently mentioned topics in this field. Within the MaxEnt framework, a quantitative relationship between various ecological parameters has recently been proposed as a seeming ecological equation of state (EESH; Harte et al. 2022. An equation of state unifies diversity, productivity, abundance and biomass. Commun. Biol. 5: 874). We analyze the EESH from the interdisciplinary perspective of Organic Biophysics of Ecosystems (OBEC). Consistent with this analysis, the EESH neglects the analytical similarity between key ecological variables and statistical mechanical variables, it does not include any intensive variable useful to determine the distance of ecological systems from equilibrium, it does not involve any constant useful to define the statistical range within which the system can be considered out of danger despite widespread effects of anthropogenic impact, and its general structure bears no resemblance to previous equations of state because it is based on a subjective approach devoid of physical content that is only useful as a tool for statistical inference. So, our conclusions are: (i) the EESH does not withstand comparison with prior knowledge and empirical evidence from both ecology and physics, and (ii) it cannot be considered an ecological equation of state.

The historical development of the urban realm has brought marvelous benefits to humankind, which has profited from the infrastructure, services, and social networks provided by cities. Nonetheless, considering current and future risks, understanding how cities can absorb impacts and reorganize their structure while keeping their identities is fundamental and timely. In other words, understanding how to promote resilience is crucial. This study developed a comparative urban resilience index (CURI) formed by 29 indicators and applied it to case studies in Europe, China, and the Americas (Malmö, Vienna, Beijing, Shanghai, Baltimore, and São Paulo). An innovative identity dimension was built to embrace the cultural traits of studied cities. Results point to a systemic property of CURI when comparing cities in both timeframes (2000 and 2020). In addition, two groups were formed: Malmö, Beijing, and Baltimore increased their resilience due to higher performance in at least two dimensions; Shanghai, Vienna, and São Paulo decreased their resilience due to lower performance in at least three dimensions. Ranking the data in terms of the benchmark promoted a quick understanding of which city is the “best in class” for each dimension, creating a clear way forward for other cities to follow.

Abstract Nitrogen (N) and phosphorus (P) are essential nutrients for living systems and play a central role in human food systems. While N and P pathways have been investigated individually in the literature, the N-P coupled cycling network has not received sufficient attention. The coupled nature of N and P cycling networks and the importance of their resilience for the future of food and energy systems is of critical importance for sustainable development. In this avenue, we use the material flow and ecological network analysis methods to construct the N-P coupled cycling network in China and evaluate its resilience. The results show that the resilience of China’s N-P coupled cycling network decreased during the 1980–2017 period and, given China’s goal of further carbon neutrality, resilience is expected to continue decreasing throughout the study period (until 2060). Furthermore, under our clean energy scenario, the N-P coupled cycling network will have a very substantial decrease in its resilience, especially in the N layer (by 20%). China’s socio-economic system also suffers the risk of great 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 reveal trade-offs and synergies under future anthropogenic nexus scenarios and can equip policymakers to make more informed deliberations on the management of N and P cycling networks in China, e.g., reducing fertilizer use and food waste.

Urban land is the primary scene for economic manufacturing and services providing, through which the economic activities and trade flows amplify and cascade, interacting the natural and human systems. However, our understanding of the economic sectoral urban land metabolism remains inadequate. Here, we establish a spatially explicit sectoral urban land use inventory and a virtual land flow network for 13 cities in the Jing-Jin-Ji region in China to understand urban land use metabolism. Results show spatial heterogeneity in urban land use among industries and across spatial scales. Four cities exhibit reverse import and export roles in regional and national virtual land flow networks. It also reveals inequalities in benefit-cost and supply chain networks across cities, and a wide range of control and exploitation relationships in the region. We suggest that Beijing and Tianjin, as main beneficiaries in the regional economic network, are responsible for promoting regional sustainable development collaboration.

Current human population is mostly located in urban areas making cities the center of attention in terms of achieving sustainability goals. Evidence shows that ecosystems have evolved over time toward a balanced configuration between resource efficiency and functional redundancy. For this reason, they are exemplary models to follow in terms of sustainability. Here, we apply similar ecological network-based methods to study the virtual water metabolic network (VWMN) of the Metropolitan District of Quito. The VWMN was obtained using novel bottom-up, survey-based methods to generate the urban metabolic network. We compare the VWMN results with those previously obtained from ecological food webs, to learn if there are insights about the sustainability of urban metabolic processes. We conclude that VWMN does not exhibit characteristics observed in sustainable ecological networks because this socioeconomic network exhibits higher levels of path redundancy. Urban metabolism studies are gaining in popularity as a research tool aimed at informing resource management and this is one of the first covering a city in the Global South and using a bottom-up survey method.

The social and ecological impacts of urbanization require integrated management of cities and their resource metabolism for long-term sustainability and economic prosperity. Traditionally, network models are used to study internal metabolic processes in cities, complementing the traditional "black box" urban models to account for the input of material and energy resources and the output of final products and wastes. This study introduces a multi-criteria assessment framework by integrating a unique hybrid-unit input-output model with the emergy accounting method to estimate the environmental support provided to urban socio-economic systems, applied here to the case of Vienna, Austria. By focusing on the internal organisation and functioning of urban socio-economic systems, the proposed framework strengthens the understanding of ecological and socio-economic flows exchanged among industries and the environment. The results suggest that resources can be saved by applying supply-side and demand-side interventions and improving share of renewables. The multi-criteria assessment framework developed in this study allows to investigate the urban metabolism of cities and regional contexts through the identification of sustainable pathways rooted in material circularity and resource efficiency, supporting the design of policies in line with the "integrated wealth assessment" and "circular economy" principles.

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.

FIELD GRAND CHALLENGE article Front. Sustain. Resour. Manag., 21 October 2022 Volume 1 - 2022 | https://doi.org/10.3389/fsrma.2022.943359

Since the publication of global studies about ecosystem health and their importance to society, understanding and valuing ecosystem services (ES) has been gaining attention. Measuring undesired drivers that impact these services is crucial for planning sound socio-economic policies. This work explores how the coastal ES from Ubatuba, Brazil might behave following climate and tourists’ management scenarios. A new model, embracing ecological functions and their interactions with the city was built and through benefit transfer methods, the value of ten ecosystem services was calculated. Results show that all ES will be affected by the climate scenarios and by tourism reduction. The conclusion is that the region can provide these 10 ES with an economic value of 622 M dollars (± 3.6 M dollars) from 2010 to 2100. When climate change is considered, the values most likely decline from −1.23% (±2.96%) or −7.5 M dollars (±3.8 M dollars) to −2.34% (±3.88%) or −14 M dollars (± 6.3 M dollars) depending on the scenario. Results also show the possibility of an increase in the aggregate ES values due to the climate scenario effect, but it is less likely to occur. Controlling the population visiting the area is the main policy advice from this research which can lead to positive effects on the ES provision in all scenarios.

The rapid economic growth accompanied by health concerns and other global environmental problems in cities and regions has boosted the popularity of the ‘urban metabolism’ topic among academics and policymakers. Currently, 56.2% of the world's population lives in cities, accounting for 80% of the global GDP. It is projected that the current trend for world economic growth complemented by population growth and migration will continue affecting the resource production and consumption in cities and the impact this has on other urban areas. Here, we developed a new model approach that combines emergy input-output tables with ecological network analysis to investigate urban metabolism generally, and applied it to Vienna, Austria. This novel approach allows researchers to study the hierarchy of sectors and functional relationships along all possible metabolic paths of ecological and socio-economic flows exchanging in an urban economy and between the urban economy and its environment. Then, using system-level analyses (flow and contribution analyses) we determined the status of the system components. Finally, the critical components responsible for the status (distribution structure of each industry) and emergy consumption of the other sectors were identified using pairwise control and utility analyses. The results showed that the “agriculture, forestry and fishing” and “mining and quarrying” sectors had the lowest ability to receive financial inputs from the other sectors, reflecting a shortage of agricultural and mining products to meet consumers' demand. Moreover, “agriculture, forestry and fishing” had the highest energy dependence on the other sectors, indicating the lack of self-sufficiency in energy use and the inability of this sector to deliver energy effectively to consuming sectors. This also implies the importance of this sector in achieving the energy efficiency improvement and economic development goals for consumer cities. This work contributes to the existing literature on ecological network analysis via an introduction of the two-step approach that combines the diagnosis of low activity components in the system taken from traditional ecological network analysis with the novel identification of components behind the low activity of the other components. In addition, direct and indirect control, and indirect utility analysis were introduced for the analysis of the impact of the direct energy and indirect pairwise economic control and relational interactions of sectors in cities. Finally, this work explored the inner workings of the service part of the urban economy to reveal the role each tertiary sector plays in the development of primary and secondary sectors of an urban economy. The model developed in this study will provide support for city managers and policymakers to guide resource consumption towards an efficient and sustainable urban metabolic system worldwide.

Networks of mass flows describe the basic structure of ecosystems as food webs, and of economy as input–output tables. Matter leaving a node in these networks can return to it immediately as part of a reciprocal flow, or completing a longer, multi‐node cycle. Previous research comparing cycling of matter in ecosystems and economy was limited by relying on unweighted or few networks. Overcoming this limitation, we study mass cycling in large datasets of weighted real‐world networks: 169 mostly aquatic food webs and 155 economic networks. We quantify cycling as the portion of all flows that is due to cycles, known as the Finn Cycling Index (FCI). We find no correlation between FCI and the largest eigenvalues of unweighted adjacency matrices used as a cycling proxy in the past. Unweighted networks ignore the actual flow values that in reality can differ by even 10 orders of magnitude. FCI can be decomposed into a sum of contributions of individual nodes. This enables us to quantify how organisms recycling dead organic matter dominate mass cycling in weighted food webs. FCI of food webs has a geometric mean of 5%. We observe lower average mass cycling in the economic networks. The global production network had an FCI of 3.7% in 2011. Cycling in economic networks (input–output tables and trade relationships) and food webs strongly correlates with reciprocity. Encouraging reciprocity could enhance cycling in the economy by acting locally, without the need to perfectly know its global structure.

The relationship of network structure and dynamics is one of most extensively investigated problems in the theory of complex systems of the last 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) with a (network) representation of the dynamics (functional connectivity). Analysing such SC/FC relationships has over the past years contributed substantially to our understanding of the functional role of network properties, such as modularity, hierarchical organization, hubs and cycles. 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, Freshwater Ecology, Systems Biology, Neuroscience and Social-Ecological Systems. Seeing the organization of a 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.

With rapid urbanization, some cities are integrating within urban agglomerations to obtain more opportunities for cooperation. Sustainable development of these agglomerations requires successful management of the material flows, and this requires an in-depth understanding of urban material consumption and its metabolic characteristics. To describe these characteristics, we used flow analysis, factor decomposition, coupling and decoupling status analysis, and power law analysis to examine the metabolic characteristics of Beijing, Tianjin, Langfang, and Tangshan (central cities in the Beijing-Tianjin-Hebei region). We focused on the domestic material consumption (DMC) to analyze inter-city differences in the material metabolism, the driving factors responsible for these differences, and each city's development characteristics. Beijing and Langfang had similar material metabolic fluxes (DMC), as did Tianjin and Tangshan, mainly from the Construction and Manufacturing sectors. The economic size (per capita GDP) and population of the four cities were important drivers of material consumption, but the contributions and trends varied among the cities. Three of the four cities (except Tianjin) have achieved distinct decoupling between consumption growth and per capita GDP growth, and the trends were dominated by relative decoupling (75% of the years). Beijing's and Langfang's DMC become economies of scales as GDP per capita multiplies whereas Tianjin's and Tangshan's DMC increased simultaneously with increasing per capita GDP. Based on these differences in metabolic characteristics and driving factors, we propose suggestions such as carefully regulating the Manufacturing, Construction, Transportation, and Household sectors, as well as implementing policies and technologies to conserve and recycle materials and energy, thereby providing guidance for coordinated and more sustainable development of the Beijing-Tianjin-Hebei region.

The construction of a network capturing the topological structure linked to the interactions among species and the analysis of its properties constitutes a clarifying way to understand the functioning of an ecosystem at different scales of analysis. Here, we present a novel systematic procedure to profit from the enhanced information derived from considering its multiple levels and apply it to analyse the presence of keystone species.The proposed method presents a way to unveil the information stored in a network by comparing it to some randomised modification of itself. The randomising of the original network is done by swapping a controlled number of links while preserving the degree of the nodes. Then, we compare the modularity value of the original network with the randomised counterparts, which gives us a measure of the amount of relevant information stored in the first one. Once we have verified that the modularity value is meaningful, we use it to perform a community analysis and a characterisation of other topological properties in order to identify keystone species.We applied this method to a pollinator–plant–herbivore trophic network as a case study and we found that (a) the comparison between the modularity of the original and the randomised networks is a suitable tool to detect relevant information; and (b) identifying keystone species yields different results in bipartite networks from the ones obtained in networks of more than two trophic levels. We also analysed the effect of eliminating selected species from the system on the cohesion of the network. The selection of these species was made according to the centralities values, such as degree and betweenness, of the corresponding nodes.Our findings show that our analysis, mainly based on the measure of modularity is a reliable tool to characterise ecological networks. Additionally, we argue that since degree and betweenness are not always correlated, it is more reliable to measure both in an attempt to detect keystone species. The methodology proposed here to identify keystone species can be applied to other ecological networks currently available in the literature.

Baffin Bay, located at the Arctic Ocean’s ‘doorstep’, is a heterogeneous environment where a warm and salty eastern current flows northwards in the opposite direction of a cold and relatively fresh Arctic current flowing along the west coast of the bay. This circulation affects the physical and biogeochemical environment on both sides of the bay. The phytoplanktonic species composition is driven by its environment and, in turn, shapes carbon transfer through the planktonic food web. This study aims at determining the effects of such contrasting environments on ecosystem structure and functioning and the consequences for the carbon cycle. Ecological indices calculated from food web flow values provide ecosystem properties that are not accessible by direct in situ measurement. From new biological data gathered during the Green Edge project, we built a planktonic food web model for each side of Baffin Bay, considering several biological processes involved in the carbon cycle, notably in the gravitational, lipid, and microbial carbon pumps. Missing flow values were estimated by linear inverse modeling. Calculated ecological network analysis indices revealed significant differences in the functioning of each ecosystem. The eastern Baffin Bay food web presents a more specialized food web that constrains carbon through specific and efficient pathways, leading to segregation of the microbial loop from the classical grazing chain. In contrast, the western food web showed redundant and shorter pathways that caused a higher carbon export, especially via lipid and microbial pumps, and thus promoted carbon sequestration. Moreover, indirect effects resulting from bottom-up and top-down control impacted pairwise relations between species differently and led to the dominance of mutualism in the eastern food web. These differences in pairwise relations affect the dynamics and evolution of each food web and thus might lead to contrasting responses to ongoing climate change.