Complex Ecological Systems Research Articles

An Analysis of the Operation Mechanism of Chemical Industry Park Ecosystem Based on Theory of Ecological Organization

Based on the theory of ecological organization, this paper analyzes the operation mechanism of chemical industry park (CIP) ecosystem by means of dynamic simulation. The research shows that the CIP ecosystem is a complex ecological system whose operation mechanism includes two levels, namely individual enterprises and ecosystem. At the level of individual enterprise, there are competition, symbiosis, invasion and other interactions between enterprises in the CIP ecosystem. Through the pre-determined judgment of the competition effect coefficient and the symbiosis effect coefficient, we calculate how the enterprises influence each other, and then generate their respective operation paths, and finally realize the long-term balance of the system. At the level of ecosystem, the CIP ecosystem makes self-organizing and self-adaptive adjustments and changes due to the changes of the external environment in policy, manpower, technology, capital, market, etc., thus reaching the equilibrium state of coordinated operation and stable symbiosis with the external environment.

Developing shared qualitative models for complex systems.

Understanding complex systems is essential to ensure their conservation and effective management. Models commonly support understanding of complex ecological systems and, by extension, their conservation. Modeling, however, is largely a social process constrained by individuals’ mental models (i.e., a small‐scale internal model of how a part of the world works based on knowledge, experience, values, beliefs, and assumptions) and system complexity. To account for both system complexity and the diversity of knowledge of complex systems, we devised a novel way to develop a shared qualitative complex system model. We disaggregated a system (carbonate coral reefs) into smaller subsystem modules that each represented a functioning unit, about which an individual is likely to have more comprehensive knowledge. This modular approach allowed us to elicit an individual mental model of a defined subsystem for which the individuals had a higher level of confidence in their knowledge of the relationships between variables. The challenge then was to bring these subsystem models together to form a complete, shared model of the entire system, which we attempted through 4 phases: develop the system framework and subsystem modules; develop the individual mental model elicitation methods; elicit the mental models; and identify and isolate differences for exploration and identify similarities to cocreate a shared qualitative model. The shared qualitative model provides opportunities to develop a quantitative model to understand and predict complex system change.

Automated Discovery of Relationships, Models, and Principles in Ecology

Ecological systems are the quintessential complex systems, involving numerous high-order interactions and non-linear relationships. The most used statistical modeling techniques can hardly accommodate the complexity of ecological patterns and processes. Finding hidden relationships in complex data is now possible using massive computational power, particularly by means of artificial intelligence and machine learning methods. Here we explored the potential of symbolic regression (SR), commonly used in other areas, in the field of ecology. Symbolic regression searches for both the formal structure of equations and the fitting parameters simultaneously, hence providing the required flexibility to characterize complex ecological systems. Although the method here presented is automated, it is part of a collaborative human–machine effort and we demonstrate ways to do it. First, we test the robustness of SR to extreme levels of noise when searching for the species-area relationship. Second, we demonstrate how SR can model species richness and spatial distributions. Third, we illustrate how SR can be used to find general models in ecology, namely new formulas for species richness estimators and the general dynamic model of oceanic island biogeography. We propose that evolving free-form equations purely from data, often without prior human inference or hypotheses, may represent a very powerful tool for ecologists and biogeographers to become aware of hidden relationships and suggest general theoretical models and principles.

Open challenges in environmental data analysis and ecological complex systems (a) (a)Contribution to the Focus Issue Progress on Statistical Physics and Complexity edited by Roberta Citro, Giorgio Kaniadakis, Claudio Guarcello, Antonio Maria Scarfone and Davide Valenti.

This letter focuses on open challenges in the fields of environmental data analysis and ecological complex systems. It highlights relations between research problems in stochastic population dynamics, machine learning and big data research, and statistical physics. Recent and current developments in statistical modeling of spatiotemporal data and in population dynamics are briefly reviewed. The presentation emphasizes stochastic fluctuations, including their statistical representation, data-based estimation, prediction, and impact on the physics of the underlying systems. Guided by the common thread of stochasticity, a deeper and improved understanding of environmental processes and ecosystems can be achieved by forging stronger interdisciplinary connections between statistical physics, spatiotemporal data modeling, and ecology.

Nano-Titanium Dioxide Exposure Impacts Nitrogen Metabolism Pathways in Cyanobacteria

The wide and increasing use of nano-titanium dioxide (nTiO2) has led to its release in the environment that will likely impact aquatic eco-relevant biota. In this study, we investigated the impact of sublethal concentrations of nTiO2 on the nitrogen (N) metabolism of the primary producer, nitrogen-fixing cyanobacteria Anabaena PCC 7120, using transcriptional-level information of biomarker genes involved in global N regulation, N fixation-, N assimilation-, and N storage-specific pathways. The results showed that both the circadian patterns of cyanobacterial metabolism and nTiO2 intrinsic properties distinctively governed the toxicity responses during light and dark exposure to nTiO2. During illuminated conditions, the majority of genes linked to cellular nitrogen status exhibited a clear upregulation in the dose range of 6–60 mg/L·h, whereas overall gene downregulation was mainly observed at the end of dark cycle, characterized by low cell metabolism and energy (ATP) levels. The nTiO2 dose-dependent production of intracellular metabolites (amino acids) involved in both the GS-GOGAT pathway of N assimilation and the intracellular N storage pathway suggests that pathways involving amino acid biosynthesis or degradation might be activated or repressed. This, possibly, contributes to the increase of newly synthesized proteins needed for detoxification in response to the cellular stresses induced by nTiO2 treatment. These findings suggest that under environmental perturbations generated by nTiO2, cyanobacteria are likely to modify their intracellular carbon and nitrogen balance, thus impact, at a larger scale, ecological trophic interactions and food web dynamics within complex ecological systems.

Mussel Shutdown: Does the Fear of Trematodes Regulate the Functioning of Filter Feeders in Coastal Ecosystems?

Parasite infections have negative impacts on their hosts. Accordingly, many organisms try to detect and avoid infective parasite stages, leading to changes in host behaviour or physiology. Such non-consumptive effects on host traits can have cascading impacts on whole ecosystems but remain largely overlooked. Here, we discuss the potential impacts of the presence of free-living trematode stages on blue mussels Mytilus edulis, an important ecosystem engineer in coastal habitats, and highlight the ecological implications of these interactions. Specifically, we discuss how parasite avoidance behaviour can regulate the filtration activity of these bivalves in coastal ecosystems and show how even moderate changes in mussel behaviour can lead to far-reaching shifts in energy flow. Such processes might be further amplified under future climate change developments, since both parasite abundance and biotic productivity are highly temperature dependent. Overall, we hypothesize that, in addition to their more evident consumptive impacts, trematodes act as cryptic ecosystem engineers by shaping bivalve filtration processes via non-consumptive effects. Due to our still very limited understanding of these parasite-mediated processes, we outline key questions for future research directions. We hope this perspective will help encourage new efforts to empirically investigate these fascinating processes that can be crucial regulatory forces in complex ecological systems.

Altering Neighborhood Relatedness and Species Composition Affects Interior Douglas-Fir Size and Morphological Traits With Context-Dependent Responses

Trees often exist in a complex ecological system with many biological interactions. Here we examine kin interactions of Pseudotsuga menziesii var. glauca (interior Douglas-fir) both in the context of pure kin stands, in accordance with established plant kin selection and recognition studies, but also in combination with inter and intraspecific neighbors in order to observe how interactions may differ in a more complex system. Seedlings grown with kin neighbors (i.e. in stands that contained only kin) were significantly larger (biomass, height and root length) than those grown with any type of unrelated neighbor. However, of those with an unrelated neighbor, performance was better if that neighbor was interspecific (lodgepole pine rather than a stranger, or non-kin, Douglas-fir neighbor). Interestingly when Douglas-fir was grown in mixed stands, the four growth and four morphological traits of the seedlings examined paralleled neither pure stranger nor pure kin stands. This suggests that a mixed stand environment yielded cues that were uniquely different than either type of pure stand and that these seedlings are able to integrate that information and respond in a different way; for example, with increased early mycorrhizal fungal colonization. The morphological traits fine: coarse root allocation and slenderness (height relative to diameter) closely paralleled the seeding-size results, with the greatest values in pure kin stands. Whereas, fine root: needle allocation showed a kin response of less fine root allocation relative to needle mass compared to strangers, but kin seedlings had more fine root allocation when grown with a pine compared to a stranger Douglas-fir neighbor. We have demonstrated that the kin response in Douglas-fir is influenced by the complexity of the environment in which it grows, and this has significant effects on growth, morphology and mycorrhizal fungal colonization that may affect the success and resiliency of regeneration.

A guide to ecosystem models and their environmental applications.

Applied ecology has traditionally approached management problems through a simplified, single-species lens. Repeated failures of single-species management have led us to a new paradigm - managing at the ecosystem level. Ecosystem management involves a complex array of interacting organisms, processes and scientific disciplines. Accounting for interactions, feedback loops and dependencies between ecosystem components is therefore fundamental to understanding and managing ecosystems. We provide an overview of the main types of ecosystem models and their uses, and discuss challenges related to modelling complex ecological systems. Existing modelling approaches typically attempt to do one or more of the following: describe and disentangle ecosystem components and interactions; make predictions about future ecosystem states; and inform decision making by comparing alternative strategies and identifying important uncertainties. Modelling ecosystems is challenging, particularly when balancing the desire to represent many components of an ecosystem with the limitations of available data and the modelling objective. Explicitly considering different forms of uncertainty is therefore a primary concern. We provide some recommended strategies (such as ensemble ecosystem models and multi-model approaches) to aid the explicit consideration of uncertainty while also meeting the challenges of modelling ecosystems.

Natural Resources Globalization and Its Effect on the Indigenous People; Evidence from the Theoretical and Empirical literature: Review

The globalized view of natural resource is strictly connected with quantitative measures and strongly depends on expert assessments and assumptions with poorly understanding local knowledge and local facts, finally leads to unreliable conclusion. Hence, this review intends to investigate the globalization of natural resources and its effect on the lives of indigenous people. The study found that the conventional global approach tends to focus on quantitative measures by contrast the local and traditional approach tend to focus on qualitative information. Thus, local tailored forest conservation and management programs create a social environment that allows unique local environmental values to emerge increasing motivational force of environmental values in the conventional science. This reflects that giving recognition to and work with and through local real situations where problems are identified and solutions are determined makes environmental conservation more cost effective and sustainable. Local people believed that resources not only provide material benefits but also other cultural and social values. Indigenous peoples with a historical continuity of resource-use practices often possess a broad knowledge base of the behavior of complex ecological systems in their own localities. This knowledge has accumulated through a long series of observations transmitted from generation to generation. Where indigenous peoples have depended, for long periods of time, on local forests for the provision of a variety of resources, they have developed a stake in conserving, and in some cases, enhancing biodiversity.

The aquaculture sustainability continuum – Defining an environmental performance framework

Abstract Estimating the magnitude and sustainability of aquaculture’s environmental impacts is challenging. A lack of quantifiable performance data on sustainability is limiting the industry’s ability to demonstrate the potential benefits of aquaculture as it plays an essential role in the future supply of seafood. Environmental Indicator Sets (EISs) have emerged as tools to express the sustainability of complex ecological systems. The intent of this work was to harness the collective expert input reflected in the EISs of global certification and ratings schemes to provide new tools to further define and advance the quantification of sustainable aquaculture. Every environmental indicator from four prominent schemes was analyzed and categorized by their level of application (site- and resource-level) and by their mode of action (status, control and risk). Impact-specific parameters were defined (Impact, Resource, Target, Limit Reference Point (LRP), and Recovery Timeframe) and used to develop a 0–100 performance scale for key environmental impacts. The resulting two-dimensional categorical-performance frameworks represent a formalized way to reflect on the different approaches of the certification and ratings schemes. Performance comparisons between schemes were avoided but the analysis indicates there is an opportunity for the different approaches to be considered complimentary. The novel parameters proposed here, particularly the LRP, highlight the incongruence between the common definitions of sustainable wild caught and farmed seafood. As such, the present work serves as an orientation point for further discussion on the quantification and ongoing development of sustainable aquaculture, anchored on the existing content of established aquaculture certification and ratings schemes.

The impact of system specifics on systems thinking

AbstractPresent and future social and ecological challenges are complex both to understand and to attempt to solve. To comprehend the complex systems underlying these issues, students need systems thinking skills. However, in science education, a uniform delineation of systems thinking across contexts has yet to be established. While there seems to be consensus on a number of key skills from a theoretical perspective, it remains uncertain whether it is possible to distinguish levels of systems thinking, and if so, how they would be determined. In this study, we investigated the impact of the specifics of a system on the skills and levels of systems thinking. We administered a 36‐item multiple‐choice test to 196 Grade 5 and 6 students. For our analysis, we followed a quantitative approach, applying a systems thinking model that incorporates the latest insights on the levels and skills of systems thinking in geography to the context of ecology. By following an Item Response Theory approach, we confirmed a set of systems thinking skills that are necessary to understand complex systems in ecology: identifying system organization, analyzing system behavior, and system modeling. We examined whether individual skill levels can be distinguished to determine whether a system's general principle or system‐specific features cause difficulty for students. Our results indicate that system specifics, such as type of relation within ecosystems (e.g., predator–prey), appear to determine the formation of levels. Students struggled most with the difference between basic, direct cause‐and‐effect relationships and indirect effects. Once they understood the relevance of indirect relationships in moderately complex systems, a further increase in complexity caused little additional difficulty. Accordingly, we suggest that systems thinking should be examined from a variety of perspectives. To promote interdisciplinary learning, a systems thinking model that defines key commonalities across fields while leaving space for system specifics is needed.

Enabling Biomimetic Place-Based Design at Scale.

Amidst the inter-related challenges of climate change, resource scarcity, and population growth, the built environment must be designed in a way that recognises its role in shaping and being shaped by complex social and ecological systems. This includes avoiding the degradation of living systems in the design and construction of buildings and infrastructure, as well as enhancing the built environment’s resilience to disturbance by those systems. This paper explores the potential for biomimetic place-based design (BPD) to inform resilient and regenerative built environment outcomes by learning from local ecosystems. One recognised hurdle is the upfront resourcing required to establish the biomimetic knowledge base for each project. However, conducting BPD projects at-scale (i.e., city or region) can improve the method’s value-proposition by better leveraging upfront research efforts, design concepts, and strategies. This research identifies existing barriers to the widespread adoption of BPD and presents an action framework for capability-building across industry, government, and academia to enable application at-scale. Drawing on findings from workshops in the USA and Australia, it creates a resource for colleagues looking to apply BPD in a city or region and offers next steps for research and development.

Decoding the language of microbiomes using word-embedding techniques, and applications in inflammatory bowel disease.

Microbiomes are complex ecological systems that play crucial roles in understanding natural phenomena from human disease to climate change. Especially in human gut microbiome studies, where collecting clinical samples can be arduous, the number of taxa considered in any one study often exceeds the number of samples ten to one hundred-fold. This discrepancy decreases the power of studies to identify meaningful differences between samples, increases the likelihood of false positive results, and subsequently limits reproducibility. Despite the vast collections of microbiome data already available, biome-specific patterns of microbial structure are not currently leveraged to inform studies. Here, we derive microbiome-level properties by applying an embedding algorithm to quantify taxon co-occurrence patterns in over 18,000 samples from the American Gut Project (AGP) microbiome crowdsourcing effort. We then compare the predictive power of models trained using properties, normalized taxonomic count data, and another commonly used dimensionality reduction method, Principal Component Analysis in categorizing samples from individuals with inflammatory bowel disease (IBD) and healthy controls. We show that predictive models trained using property data are the most accurate, robust, and generalizable, and that property-based models can be trained on one dataset and deployed on another with positive results. Furthermore, we find that properties correlate significantly with known metabolic pathways. Using these properties, we are able to extract known and new bacterial metabolic pathways associated with inflammatory bowel disease across two completely independent studies. By providing a set of pre-trained embeddings, we allow any V4 16S amplicon study to apply the publicly informed properties to increase the statistical power, reproducibility, and generalizability of analysis.

Enzootic maintenance of sylvatic plague in Canada's threatened black‐tailed prairie dog ecosystem

AbstractData paucity can seem to hinder science‐based approaches to the conservation of imperiled species. Yet, even individually limited datasets can improve understanding and management of complex ecological systems when carefully integrated. We demonstrate this approach to gain first insights on the transmission ecology of Yersinia pestis in Grasslands National Park (GNP), Canada, where both the bacterium and its rodent host, the nationally threatened black‐tailed prairie dog (BTPD, Cynomys ludovicianus), reach the northern limit of their distribution in North America. Primarily flea‐borne, Y. pestis causes sylvatic plague, a disease of exceptional relevance to both human health and wildlife conservation. We integrated data collected independently by multiple organizations in 2010–2017 across 17 BTPD colonies, where the species co‐occur with Richardson's ground squirrels (RGS, Urocitellus richardsonii). Available data included estimates of BTPD density and occupancy from visual counts and colony mapping; information on flea distribution, abundance, and prevalence of infection with Y. pestis from burrow swabbing, animal combing, and PCR assays; and the response of these variables to deltamethrin application on BTPD colony sections. Our analyses suggest that sylvatic plague in GNP is maintained at an enzootic level (i.e., chronic presence affecting a low proportion of individuals) with no evidence of widespread mortality, at least partially due to reduced flea activity after spring (percentage of prevalence in burrows: April–May = 11.69–33.89%; June–September: 1.75–3.19%), low prevalence of Y. pestis in flea samples (95% CI = 0.42–2.27%), and relatively low BTPD densities. Nonetheless, reducing flea prevalence through insecticide application had a positive effect on BTPD abundance, suggesting that enzootic plague is causing chronic mortality. Because flea prevalence on hosts was higher following drier years and higher on RGS than on BTPD (26.69% vs. 3.27%), insecticide application may be particularly important during dry periods and may need to take RGS and their movements into consideration. Differences between flea communities sampled by burrow swabbing and host combing suggest that plague surveillance should integrate both methods. Effects of projected climate change on vector life cycles, flea community composition, and host–parasite interactions warrant continued monitoring and an adaptive approach to species recovery actions and plague mitigation measures.

Predicting collapse of complex ecological systems: quantifying the stability-complexity continuum.

Dynamical shifts between the extremes of stability and collapse are hallmarks of ecological systems. These shifts are limited by and change with biodiversity, complexity, and the topology and hierarchy of interactions. Most ecological research has focused on identifying conditions for a system to shift from stability to any degree of instability-species abundances do not return to exact same values after perturbation. Real ecosystems likely have a continuum of shifting between stability and collapse that depends on the specifics of how the interactions are structured, as well as the type and degree of disturbance due to environmental change. Here we map boundaries for the extremes of strict stability and collapse. In between these boundaries, we find an intermediate regime that consists of single-species extinctions, which we call the extinction continuum. We also develop a metric that locates the position of the system within the extinction continuum-thus quantifying proximity to stability or collapse-in terms of ecologically measurable quantities such as growth rates and interaction strengths. Furthermore, we provide analytical and numerical techniques for estimating our new metric. We show that our metric does an excellent job of capturing the system's behaviour in comparison with other existing methods-such as May's stability criteria or critical slowdown. Our metric should thus enable deeper insights about how to classify real systems in terms of their overall dynamics and their limits of stability and collapse.

The development of water quality monitoring system using internet of things

Biological diversity or biodiversity is an important element in the river water management system. The interaction between the various organisms in the river makes it a very complex ecological system. Therefore, water safety issues are a very important issue. Consumer complaints and reports made by the relevant government departments indicate that consumers are dissatisfied with the quality of water supplied. Hence, a concept in which equipment, machines, sensors and devices are connected to the Internet and there is data collection and transfer through the network developed to follow the river water quality index. Integration of the elements of sustainability and IR4.0 through the Internet of Thing by adopting electronic and Internet applications of Thing has a very positive impact to refresh the approach to lesions in Malaysia. The project aims to develop a wireless water quality monitoring system that aids in continuous measurements of water conditions based on pH and turbidity measurements. The developed system was successfully detecting both the pH and turbidity values. Water analysis and monitoring is a very important aspect of water conservation and protection. Water is a vital resource that runs more quickly overtime. To ensure continued supply of safe, clean drinking water, together as community to protect and to this vital resource.

Knowledge Models for Spatial Planning: Ecosystem Services Awareness in the New Plan of Bari (Italy)

The concept of ecosystem services (ES) arises as a formal outcome of historical processes of understanding and interpreting settlements as complex ecological systems. Because of a straightforward, bottom-up demand for environment enhancement, this concept increasingly occurs in discourses, in narratives, in the demands of common people, triggering a new urban environmental awareness. This is now often arising spontaneously in the protocols of participatory plan processes, especially when planning for the future of complex environments such as city areas. The present study tries to elicit reflections around the significance of ES issues awareness in the case study of Bari (Italy), which is experiencing an inclusive and participatory process of construction of shared knowledge for the new master plan. Starting from an initial campaign of civic walks (CWs) along the urban neighborhoods and a subsequent semi-structured interview to the community, the paper carries out comparative analyses using problem-structuring methods (PMs), in order to evaluate and reflect on community behaviors and expectations about ES. Then the paper ends by emphasizing the role of structured knowledge-raising approaches, as critical activities to enhance ecosystem awareness in planning settlements as complex ecological systems.

STATE CHARACTERISTICS OF THE PROBLEM OF ORAL CAVITY ENVIRONMENTAL SYSTEM

The aim: Analysis of literary sources with the study of modern views on the problem of the immune status of the oral mucosa. Materials and methods: The review and analysis of scientific and medical literature for the years 2013-2019, based on Scopus databases, Web of Science, Med Line, The Cochrane Library, EMBASE, Global Health, CyberLeninka, RIC. Conclusions: Bacterial wall antigens are able to affect the local immune response of the oral mucosa. In particular, suppression of lymphocytes and macrophages proliferation, alteration of adhesion molecules expression and homing of the immune system cells to the inflammation site, inhibition of cytokine secretion by contact of the immune system cells with gram-positive bacteria is revealed. Therefore, studying the changes in the differentiation of the oral mucosa epithelium and periodontal tissues under the influence of environmental factors is of relevance. The conception of the oral cavity as a complex ecological system has not only theoretical but also practical value. Summarizing the data, we can say that at the current stage of science development the interaction of all structures should be considered, focusing on epitheliocytes of the oral mucosa, as a closing chain, which initiates changes that can affect the condition of the oral cavity and the results of pathological processes treatment of the oral cavity mucous membrane and periodontal tissues.

Tripartite interaction between Striga spp., cereals, and plant root-associated microorganisms: a review

Abstract Striga spp. is a major threat to cereal and legume production, putting the food security and economy of smallholder farmers in sub-Saharan Africa at severe risk. This is manifested in the fact that Striga spp. infestation can result in up to 90% loss of both cereal and legume production. A consensus exists that there is yet no single measure to efficiently control Striga spp. This is mainly because of the limited fundamental knowledge of the genetics and ecology of Striga spp. and its interaction with its hosts and host root-associated microorganisms, including plant growth-promoting rhizobacteria (PGPR). Since Striga spp. is a root parasite, it is speculated that PGPR play a key role in controlling the emergence and development of Striga spp. At the same time, PGPR may exhibit beneficial effects on growth promotion of the host to strengthen its tolerance against Striga spp. attacks, while on the other hand, it may also induce, similar to biocontrol agents, direct suicidal effects on Striga spp. Such hypothesized associations between Striga spp., crops (e.g., cereals such as sorghum and maize), and PGPR remain largely unknown, and the central question remains if PGPR play an important role in the Striga -crop pathosystem. This knowledge gap is the central impetus of this review. It will elaborate the complex and fascinating tripartite ecological system of cereals, Striga spp. and root-associated microorgamisms. In a first step, the review will provide a comprehensive summary of the pairwise interactions between Striga spp. and cereals, cereals and PGPR, as well as Striga spp. and PGPR. This summary will then merge into the discussion about the yet limited knowledge of the tripartite interaction between cereals, Striga spp., and PGPR. This specifically includes the exploration of recent discoveries related to population genetics and the life cycle of Striga spp, host (cereal) defense responses to and mechanisms of Striga spp. infestation, as well as the inhibitory and stimulatory role of PGPR on Striga spp. seed germination. In a concluding section, remaining research gaps are identified and necessary research perspectives are provided to direct prospective research toward further understanding the relationship between the three biological components paving the avenue to develop biological and environmentally friendly measures to fight off the everlasting threat of Striga spp.

Концептуальні засади фізичної макроекономіки для сталого розвитку: проблеми та перспективи

A new concept of forming physical macroeconomics for sustainable development has been suggested, which broadens the coordinates system of economics, as it takes into account the physical parameters of terrestrial biosphere in economic development. The object of study in physical macroeconomics is complex ecological and socio-economic systems (ESES), the core of which is made up by terrestrial ecological systems characterized by definite amount of soil productivity. Physical macroeconomics analyzes balance models of biophysical and cost estimates on the way to forming sustainable economy of ESES. The article also suggests a physical and economic paradigm of forming sustainable economy, which, unlike the current ones, takes into account natural sources of the first enrichment period in economy. It gives grounds for methodological changes in the theory of value and creating a breakthrough model of monetary economy to solve sustainability problems. Such up-to-date physical economy is an integral (synthesizing) science which uses a transdisciplinary approach to studying cause-and-effect relations in complex stationary ecological and socio-economic systems of various hierarchy levels. Its new conceptual models are based on a synthesis of physical, biological, geobotanic, geochemical, landscape science, biophysical and economic laws. A physical and economic model for sustainable development has been substantiated, which is based on the function method of the environmental offer of the Earth. This function determines the best possible natural capital volume of the Earth, which can be obtained having its targeted volume and the area of a given terrestrial ecological system. Due to the information given above, the author of the article has managed to substantiate and determine new physical and economic sustainable development indicators of ESES.