Complementarity of ecological goal functions

How greedy is too greedy? A network toy model for evaluating the sustainability of biased evolutionary dynamics

Modern humanity has changed the biosphere at a global scale, threatening its own sustainability. It is claimed that through technology humans maximize the extraction of energy from the natural system towards their own benefit, with rates of appropriation that surpass the time-scales for systemic adaptation. This time-decoupled coevolutionary dynamic is at the core of human societal unsustainability. Here, we developed in silico experiments of an open energy-based flowing network toy model of natural systems and study the effects that greedy evolutionary strategies, resembling human societal demands, have upon the performance and scarcity tolerance of the system. We aim to determine the flexibility that those biased evolutionary dynamics have for matching or surpassing natural evolution outcomes. We studied four different indexes of system's growth and development (total system throughflow (TST), average mutual information, ascendency and entropy difference) and compare their scarcity tolerance and performance outcomes with respect to four different greedy scenarios. The results showed that greedy strategies rarely surpassed the tolerance and performance achieved by natural systemic evolution. The nature of the greedy scenarios developed were closely related to increases in TST and therefore, we emphasized this comparison. Here, the maximum percentage of greedy networks capable of surpassing natural dynamics was around one-third (approx. [Formula: see text]). However, results suggest the existence of a space parameter where local increases of energy flow can outperform the outcomes of natural systemic evolution, but no evident network property seems to characterize those greedy networks. A mild inverse relationship was found between the number of links that greedy nodes have towards the output and their capacity to outpass the control evolution. As many of the human societal effect upon biospheric processes have dissipative byproducts, knowing that such dynamics might diminish the systems tolerance and performance suggest care in their (ab)use. This article is part of the theme issue 'Evolution and sustainability: gathering the strands for an Anthropocene synthesis'.

On the History of Ecosystem Dynamical Modeling: The Rise and Promises of Qualitative Models

Ecosystem modeling is a complex and multidisciplinary modeling problem which emerged in the 1950s. It takes advantage of the computational turn in sciences to better understand anthropogenic impacts and improve ecosystem management. For that purpose, ecosystem simulation models based on difference or differential equations were built. These models were relevant for studying dynamical phenomena and still are. However, they face important limitations in data-poor situations. As a response, several formal and non-formal qualitative dynamical modeling approaches were independently developed to overcome some limitations of the existing methods. Qualitative approaches allow studying qualitative dynamics as relevant abstractions of those provided by quantitative models (e.g., response to press perturbations). Each modeling framework can be viewed as a different assemblage of properties (e.g., determinism, stochasticity or synchronous update of variable values) designed to satisfy some scientific objectives. Based on four stated objectives commonly found in complex environmental sciences ((1) grasping qualitative dynamics, (2) making as few assumptions as possible about parameter values, (3) being explanatory and (4) being predictive), our objectives were guided by the wish to model complex and multidisciplinary issues commonly found in ecosystem modeling. We then discussed the relevance of existing modeling approaches and proposed the ecological discrete-event networks (EDEN) modeling framework for this purpose. The EDEN models propose a qualitative, discrete-event, partially synchronous and possibilistic view of ecosystem dynamics. We discussed each of these properties through ecological examples and existing analysis techniques for such models and showed how relevant they are for environmental science studies.

Maximum power in evolution, ecology and economics

Ludwig Boltzmann suggested that natural selection was fundamentally a struggle among organisms for available energy. Alfred Lotka argued that organisms that capture and use more energy than their competition will have a selective advantage in the evolutionary process, i.e. the Darwinian notion of evolution was based on a fundamental, generalized energy principle. He extended this general principle from the energetics of a single organism or species to the energetics of entire energy pathways through ecosystems. Howard Odum and Richard Pinkerton, building on Lotka, extended this concept to 'The maximum power principle' and applied it to many biological and physical systems including human economies. We examine this history and how these ideas relate to concepts from other disciplines including philosophy. But there has been considerable confusion in understanding and applying these concepts which we attempt to resolve while providing various examples from routine life and discussing some unresolved issues. This article is part of the theme issue 'Thermodynamics 2.0: Bridging the natural and social sciences (Part 2)'.

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.

Emergy-based indicators for evaluating ecosystem health: A case study of three benthic ecosystem networks influenced by coastal upwelling in northern Chile (SE Pacific coast)

It has been hypothesized that ecosystem health describes the state in which all processes operating within an ecosystem are functioning at a level of optimum efficiency to maximize system empower. In this study, systems analysis of networks and information flows is used within this definition of ecosystem health to assess the condition of the benthic ecosystems in three coastal bays in northern Chile. These highly productive ecosystems are characterized by the inflow of cold, nutrient-rich waters of low oxygen concentration derived from coastal upwelling of deep waters and the interruption of upwelling flow during El Niño events when warmer waters with higher oxygen and lower nutrient concentrations enter these coastal systems. Also, these ecosystems support important artisanal benthic fisheries and are affected by industrial activities in the coastal zone. Energy Systems Theory (EST) and Emergy Analysis (EA) were applied to quantify the health of these benthic ecosystems and evaluate differences in their structure, organization and functional capacities, which are related to their emergy signatures. The marked dominance of these benthic ecosystems by nitrate from upwelling resulted in unbalanced emergy signatures, suggesting less development and system diversity compared to other coastal ecosystems with more balanced emergy signatures. Macro-descriptors and network properties, such as emergy-based ascendency and the quality-adjusted Shannon diversity index were highest for Mejillones Bay, followed by Antofagasta and then Tongoy Bay. The Average Mutual Information (AMI) index adjusted for energy quality and the emergy-based A/C (ascendency to capacity) ratio, were higher for Tongoy Bay, suggesting functional differences in health among the three ecosystems. Thus, the emergy-based macro descriptors and other indicators used in our analysis indicate that the benthic networks examined have different structural and functional characteristics that lead to different characterizations of their states of health. As a result of this complexity, management policies should be implemented within a systemic context for analysis that considers all the factors determining the relative health of each ecosystem.

Microbial bioenergetics of coral-algal interactions

Human impacts are causing ecosystem phase shifts from coral- to algal-dominated reef systems on a global scale. As these ecosystems undergo transition, there is an increased incidence of coral-macroalgal interactions. Mounting evidence indicates that the outcome of these interaction events is, in part, governed by microbially mediated dynamics. The allocation of available energy through different trophic levels, including the microbial food web, determines the outcome of these interactions and ultimately shapes the benthic community structure. However, little is known about the underlying thermodynamic mechanisms involved in these trophic energy transfers. This study utilizes a novel combination of methods including calorimetry, flow cytometry, and optical oxygen measurements, to provide a bioenergetic analysis of coral-macroalgal interactions in a controlled aquarium setting. We demonstrate that the energetic demands of microbial communities at the coral-algal interaction interface are higher than in the communities associated with either of the macroorganisms alone. This was evident through higher microbial power output (energy use per unit time) and lower oxygen concentrations at interaction zones compared to areas distal from the interface. Increases in microbial power output and lower oxygen concentrations were significantly correlated with the ratio of heterotrophic to autotrophic microbes but not the total microbial abundance. These results suggest that coral-algal interfaces harbor higher proportions of heterotrophic microbes that are optimizing maximal power output, as opposed to yield. This yield to power shift offers a possible thermodynamic mechanism underlying the transition from coral- to algal-dominated reef ecosystems currently being observed worldwide. As changes in the power output of an ecosystem are a significant indicator of the current state of the system, this analysis provides a novel and insightful means to quantify microbial impacts on reef health.

The Thermodynamics of Marine Biogeochemical Cycles: Lotka Revisited

Nearly 100 years ago, Alfred Lotka published two short but insightful papers describing how ecosystems may organize. Principally, Lotka argued that ecosystems will grow in size and that their cycles will spin faster via predation and nutrient recycling so as to capture all available energy, and that evolution and natural selection are the mechanisms by which this occurs and progresses. Lotka's ideas have often been associated with the maximum power principle, but they are more consistent with recent developments in nonequilibrium thermodynamics, which assert that complex systems will organize toward maximum entropy production (MEP). In this review, we explore Lotka's hypothesis within the context of the MEP principle, as well as how this principle can be used to improve marine biogeochemistry models. We need to develop the equivalent of a climate model, as opposed to a weather model, to understand marine biogeochemistry on longer timescales, and adoption of the MEP principle can help create such models.

Eco-exergy and emergy based self-organization of three forest plantations in lower subtropical China

The bio-thermodynamic structures of a mixed native species plantation, a conifer plantation and an Acacia mangium plantation in Southern China were quantified over a period of 15 years based on eco-exergy methods. The efficiencies of structural development and maintenance were quantified through an integrated application of eco-exergy and emergy methods. The results showed that the storage of eco-exergy increased over 3 times in all three plantations, as predicted by the maximum eco-exergy principle. This trend was primarily seen due to the accumulation of biomass, instead of an increase in the specific eco-exergy (eco-exergy per unit biomass), although species richness did increase. The eco-exergy to emergy and eco-exergy to empower ratios of the three plantations generally increased during the study period, but the rate of increase slowed down after 20 years. The dominant trees are the largest contributors to the eco-exergy stored in the plantations, and thus, the introduction of suitable indigenous tree species should be considered after the existing trees pass through their period of most rapid growth or around 20 years after planting. The combined application of C-values and suggested weighting factors in the eco-exergy calculation can imply opposite results, but may also supply useful information for forest management.

Spatial effects in real networks: measures, null models, and applications

Spatially embedded networks are shaped by a combination of purely topological (space-independent) and space-dependent formation rules. While it is quite easy to artificially generate networks where the relative importance of these two factors can be varied arbitrarily, it is much more difficult to disentangle these two architectural effects in real networks. Here we propose a solution to this problem, by introducing global and local measures of spatial effects that, through a comparison with adequate null models, effectively filter out the spurious contribution of nonspatial constraints. Our filtering allows us to consistently compare different embedded networks or different historical snapshots of the same network. As a challenging application we analyze the World Trade Web, whose topology is known to depend on geographic distances but is also strongly determined by nonspatial constraints (degree sequence or gross domestic product). Remarkably, we are able to detect weak but significant spatial effects both locally and globally in the network, showing that our method succeeds in retrieving spatial information even when nonspatial factors dominate. We finally relate our results to the economic literature on gravity models and trade globalization.

EXTREMAL PRINCIPLES WITH SPECIAL EMPHASIS ON EXERGY AND ASCENDENCY — THE MODERN APPROACH IN THEORETICAL ECOLOGY

Extremal principles or ecological orientors or goal functions are the most modern approach in theoretical ecology. There are many such principles proposed by different theoretical ecologists. In this paper, the most important extremal principles are discussed based on their theoretical backgrounds. Two widely accepted goal functions, i.e. exergy and ascendency are optimized and treated in a quantitative manner in an aquatic ecosystem model of planktonic and fish systems for their appropriateness. In the model varied body sizes of phytoplankton and zooplankton are considered. Parameter values varied according to the allometric principle with the body sizes. For self-organization of the model system two goal functions predict different results, however both are realistic.

Continuous cultivation and thermodynamic aspects of niche definition in the nitrogen cycle

The study of model organisms in pure culture has provided detailed information about the physiology and biochemistry of nitrification and related processes. Metagenomic sequencing of environmental samples is providing information to what extent this understanding also applies to natural microbial communities. Here, we outline a conceptual and experimental strategy that links these two approaches. It consists of the mathematical modeling of nitrification and related processes. The model predictions are subsequently validated experimentally by the study of natural microbial communities in continuous cultures under precisely defined environmental conditions. Combined with calorimetry and metagenomic monitoring this form of "experimental metagenomics" enables the answering of current questions in the ecology of the nitrogen cycle.

Relative urban ecosystem health assessment: a method integrating comprehensive evaluation and detailed analysis

Regarding the basic roles of urban ecosystem health assessment (i.e., discovering the comprehensive health status, and diagnosing the limiting factors of urban ecosystems), the general framework integrating comprehensive evaluation and detailed analysis is established, from both bottom-up and top-down directions. Emergy-based health indicators are established to reflect the urban ecosystem health status from a biophysical viewpoint. Considering the intrinsic uncertainty and relativity of urban ecosystem health, set pair analysis is combined with the emergy-based indicators to fill the general framework and evaluate the relative health level of urban ecosystems. These techniques are favorable for understanding the overall urban ecosystem health status and confirming the limiting factors of concerned urban ecosystems from biophysical perspective. Moreover, clustering analysis is applied by combining the health status with spatial geographical conditions. Choosing 26 typical Chinese cities in 2005, relative comprehensive urban ecosystem health levels were evaluated. The higher health levels of Xiamen, Qingdao, Shenzhen, and Zhuhai are in particular contrast to those of Wuhan, Beijing, Yinchuan, and Harbin, which are relatively poor. In addition, the conditions of each factor and related indicators are investigated through set pair analysis, from which the critical limiting factors of Beijing are confirmed. According to clustering analysis results, the urban ecosystems studied are divided into four groups. It is concluded that the proposed framework of urban ecosystem health assessment, which integrates comprehensive evaluation and detailed analysis and is fulfilled by emergy synthesis and set pair analysis, can serve as a useful tool to conduct diagnosis of urban ecosystem health.

Trends in entropy production during ecosystem development in the Amazon Basin

Understanding successional trends in energy and matter exchange across the ecosystem-atmosphere boundary layer is an essential focus in ecological research; however, a general theory describing the observed pattern remains elusive. This paper examines whether the principle of maximum entropy production could provide the solution. A general framework is developed for calculating entropy production using data from terrestrial eddy covariance and micrometeorological studies. We apply this framework to data from eight tropical forest and pasture flux sites in the Amazon Basin and show that forest sites had consistently higher entropy production rates than pasture sites (0.461 versus 0.422 W m(-2) K(-1), respectively). It is suggested that during development, changes in canopy structure minimize surface albedo, and development of deeper root systems optimizes access to soil water and thus potential transpiration, resulting in lower surface temperatures and increased entropy production. We discuss our results in the context of a theoretical model of entropy production versus ecosystem developmental stage. We conclude that, although further work is required, entropy production could potentially provide a much-needed theoretical basis for understanding the effects of deforestation and land-use change on the land-surface energy balance.

Ecosystem functioning and maximum entropy production: a quantitative test of hypotheses

The idea that entropy production puts a constraint on ecosystem functioning is quite popular in ecological thermodynamics. Yet, until now, such claims have received little quantitative verification. Here, we examine three 'entropy production' hypotheses that have been forwarded in the past. The first states that increased entropy production serves as a fingerprint of living systems. The other two hypotheses invoke stronger constraints. The state selection hypothesis states that when a system can attain multiple steady states, the stable state will show the highest entropy production rate. The gradient response principle requires that when the thermodynamic gradient increases, the system's new stable state should always be accompanied by a higher entropy production rate. We test these three hypotheses by applying them to a set of conventional food web models. Each time, we calculate the entropy production rate associated with the stable state of the ecosystem. This analysis shows that the first hypothesis holds for all the food webs tested: the living state shows always an increased entropy production over the abiotic state. In contrast, the state selection and gradient response hypotheses break down when the food web incorporates more than one trophic level, indicating that they are not generally valid.

Ecosystem biogeochemistry considered as a distributed metabolic network ordered by maximum entropy production

We examine the application of the maximum entropy production principle for describing ecosystem biogeochemistry. Since ecosystems can be functionally stable despite changes in species composition, we use a distributed metabolic network for describing biogeochemistry, which synthesizes generic biological structures that catalyse reaction pathways, but is otherwise organism independent. Allocation of biological structure and regulation of biogeochemical reactions is determined via solution of an optimal control problem in which entropy production is maximized. However, because synthesis of biological structures cannot occur if entropy production is maximized instantaneously, we propose that information stored within the metagenome allows biological systems to maximize entropy production when averaged over time. This differs from abiotic systems that maximize entropy production at a point in space-time, which we refer to as the steepest descent pathway. It is the spatio-temporal averaging that allows biological systems to outperform abiotic processes in entropy production, at least in many situations. A simulation of a methanotrophic system is used to demonstrate the approach. We conclude with a brief discussion on the implications of viewing ecosystems as self-organizing molecular machines that function to maximize entropy production at the ecosystem level of organization.

Linking biodiversity and ecosystems: towards a unifying ecological theory

Community ecology and ecosystem ecology provide two perspectives on complex ecological systems that have largely complementary strengths and weaknesses. Merging the two perspectives is necessary both to ensure continued scientific progress and to provide society with the scientific means to face growing environmental challenges. Recent research on biodiversity and ecosystem functioning has contributed to this goal in several ways. By addressing a new question of high relevance for both science and society, by challenging existing paradigms, by tightly linking theory and experiments, by building scientific consensus beyond differences in opinion, by integrating fragmented disciplines and research fields, by connecting itself to other disciplines and management issues, it has helped transform ecology not only in content, but also in form. Creating a genuine evolutionary ecosystem ecology that links the evolution of species traits at the individual level, the dynamics of species interactions, and the overall functioning of ecosystems would give new impetus to this much-needed process of unification across ecological disciplines. Recent community evolution models are a promising step in that direction.