Comparative network analysis toward characterization of systemic organization for human–environmental sustainability

A preliminary study in comparative ecological network analysis was conducted to identify key assumptions and methodological challenges, test initial hypotheses and explore systemic and network structural characteristics for environmentally sustainable ecosystems. A nitrogen network for the U.S. beef supply chain – a small sub-network of the industrial food system analyzed as a pilot study – was constructed and compared to four non-human carbon and nitrogen trophic networks for the Chesapeake Bay and the Florida Everglades. These non-human food webs served as sustainable reference systems. Contrary to the main original hypothesis, the “window of vitality” and the number of network roles did not clearly differentiate between a human sub-network and the more complete non-human networks. The effective trophic level of humans (a partial estimate of trophic level based on the single food source of beef) was much higher (8.1) than any non-human species (maximum of 4.88). Network connectance, entropy, total dependency coefficients, trophic efficiencies and the ascendency to capacity ratio also indicated differences that serve as hypotheses for future tests on more comprehensive human food webs. The study elucidated important issues related to (1) the steady state assumption, which is more problematic for industrial human systems, (2) the absence or dearth of data on contributions of dead humans and human wastes to feed other species in an integrated food web, (3) the ambiguity of defining some industrial compartments as living versus non-living, and (4) challenges with constructing compartments and trophic transfers in industrial versus non-human food webs. The two main novel results are (1) the progress made toward adapting ecological network analysis (ENA) methodology for analysis of human food networks in industrial cultures and (2) characterizing the critical aspects of comparative ENA for understanding potential causes of the problems, and providing avenues for solutions, for environmental sustainability. Based on this work, construction and comparative network analysis of a more comprehensive industrial human food network seems warranted and likely to provide valuable insights for modifying structures of industrial food networks to be more like natural networks and more sustainable.     

Adaptations in a hierarchical food web of southeastern Lake Michigan

Two issues in ecological network theory are: (1) how to construct an ecological network model and (2) how do entire networks (as opposed to individual species) adapt to changing conditions? We present a novel method for constructing an ecological network model for the food web of southeastern Lake Michigan (USA) and we identify changes in key system properties that are large relative to their uncertainty as this ecological network adapts from one time point to a second time point in response to multiple perturbations. To construct our food web for southeastern Lake Michigan, we followed the list of seven recommendations outlined in Cohen et al. [Cohen, J.E., et al., 1993. Improving food webs. Ecology 74, 252–258] for improving food webs. We explored two inter-related extensions of hierarchical system theory with our food web; the first one was that subsystems react to perturbations independently in the short-term and the second one was that a system's properties change at a slower rate than its subsystems’ properties. We used Shannon's equations to provide quantitative versions of the basic food web properties: number of prey, number of predators, number of feeding links, and connectance (or density). We then compared these properties between the two time-periods by developing distributions of each property for each time period that took uncertainty about the property into account. We compared these distributions, and concluded that non-overlapping distributions indicated changes in these properties that were large relative to their uncertainty. Two subsystems were identified within our food web system structure (p < 0.001). One subsystem had more non-overlapping distributions in food web properties between Time 1 and Time 2 than the other subsystem. The overall system had all overlapping distributions in food web properties between Time 1 and Time 2. These results supported both extensions of hierarchical systems theory. Interestingly, the subsystem with more non-overlapping distributions in food web properties was the subsystem that contained primarily benthic taxa, contrary to expectations that the identified major perturbations (lower phosphorous inputs and invasive species) would more greatly affect the subsystem containing primarily pelagic taxa. Future food-web research should employ rigorous statistical analysis and incorporate uncertainty in food web properties for a better understanding of how ecological networks adapt.     

Informing ecological engineering through ecological network analysis,ecological modelling,and concepts of systems and engineering ecology

A shift in the basic philosophy of nature developed by Francis Bacon, Renè Descartes, and Isaac Newton, has been suggested but for the most part rejected within mainstream science. It suggests the need for viewing nature as a deeply organic and connected system of relationships that is not necessarily or readily submissive to reductive thinking and analysis. Ecosystem design within the construct of a field called ecological engineering poses fundamental questions with respect to the philosophy of nature upon which our current scientific paradigm is predominantly based. In an effort to foster development of rigorous, quantitative methods for developing insight into complex ecosystem phenomena we propose systems and engineering ecology—an integrated science comprised of principles from environ theory, ascendency theory, exergy theory, emergy theory, ecological network analysis and ecological modelling, synthesized through the formal agency of systems science. We contend that ecological engineering will be limited in its robustness apart from development of rigorous systems-based sciences that are quantitative and incorporate the complex, emergent properties of ecosystem. We justify our proposed framework on the philosophical paradox of transferring aspects of traditional engineering design into ecological engineering and on the four causes of Aristotle.     

From data and theory to environmental models and indices formation

A prerequisite for environmental indices is that they represent environmental pressure, and the state of, and impact on environmental conditions. In other words, they should capture as much as possible of the cause-effect chains they represent and relate pressure and effect to criteria of environmental quality. The approach proposed in the article attempts to link the pressure–state–impact–response framework of indicators to the integrated environmental model, based on the method of response function (MRF). The MRF allows to construct purposeful, credible models from data and prior knowledge or information. The data are usually time series observations of system inputs and outputs, and sometimes of internal states. The output of such models is presented with highly aggregated environmental indices, reflecting the main pressure–state–impact–response cause-effect chains. The proposed approach is illustrated with the example of soil erosion indices.     

A study on the Spatial Distribution of Nitrogen and Phosphorus Balance, and Regional Nitrogen Flow Through Crop Production

The spatial distribution patterns of the nitrogen and phosphorus input/intake amounts in crop production within two small basins are examined, based upon a cropping unit distribution map that is obtained from remote sensing data analysis. Firstly, we examine the availability and suitability of approaches to the spatial distribution analysis of cultivation patterns classified from material flow characteristics of crop production using seasonal remote-sensing data. Secondly, material flow units in crop production are grouped according to the cultivation patterns obtained from the remote-sensing data analysis. Consequently, the spatial patterns of the amounts of both nitrogen and phosphorus inputs/intakes through crop production on farmland are examined and their spatial distribution maps are prepared according to the material flow units. In addition, we developed a nitrogen flow and runoff model and the model is simulated based on the examination of the results of spatial distribution patterns of the material flow units. The annual nitrogen runoff from small catchments, where various crops are cultivated, varies from 2.7 kg ha^–1 year^–1 to 108 kg ha^–1 year^–1 and the annual balanced losses of nitrogen in small catchments varied from –30 kg ha^–1 year^–1 to 101 kg ha^–1 year^–1. Also, the monthly changes in soil nitrogen of each material flow unit is estimated at –55 kg ha^–1 as a maximum decrease and 114 kg ha^–1 as a maximum increase. These results indicate that the spatial distribution patterns of nutrient input and intake through agricultural activities should be considered when analyzing the material flows and nutritient movement in soil–water systems in rural areas for watershed environmental control and regional agricultural management.     

Identifying a Linked Reserve System Using a Regional Landscape Approach: the Florida Ecological Network

Abstract: We completed an analysis of potential ecological connectivity to identify areas with priority conservation significance and landscape linkages as part of a state of Florida program called Greenways. This is the latest step in the state's design and protection of a reserve system based on an aggressive land acquisition program. We used geographic information systems software (Arc-Info) to develop a decision support model that uses land-use data and information on significant ecological areas—including important habitats for target species, priority ecological communities, wetlands, roadless areas, floodplains, and important aquatic systems—to identify larger areas of ecological priority and potential ecological linkages. The result of this process, the Florida Ecological Network, includes approximately half the state's area, with over half of this network already in conservation lands or public-domain water. This network could provide a linked statewide reserve system containing most of each major ecological community and most known occurrences of rare species. Although the ecological network represents significant progress toward a more integrated approach to biodiversity conservation in Florida, further analysis is needed to (1) ensure that the needs of wide-ranging species, such as the Florida panther (   Puma concolor coryi ) and Florida black bear (   Ursus americanus floridanus ), are addressed; (2) identify other biodiversity elements not well represented; and (3) designate a system of cores and buffers that will address management issues. Reserve design is an iterative process, and future plans need to address new information, including the results of the Florida GAP analysis project and ongoing habitat loss.     

Invasive species impacts on ecosystem structure and function: A comparison of the Bay of Quinte, Canada, and Oneida Lake, USA, before and after zebra mussel invasion

As invasion rates of exotic species increase, an ecosystem level understanding of their impacts is imperative for predicting future spread and consequences. We have previously shown that network analyses are powerful tools for understanding the effects of exotic species perturbation on ecosystems. We now use the network analysis approach to compare how the same perturbation affects another ecosystem of similar trophic status. We compared food web characteristics of the Bay of Quinte, Lake Ontario (Canada), to previous research on Oneida Lake, New York (USA) before and after zebra mussel (Dreissena polymorpha) invasion. We used ecological network analysis (ENA) to rigorously quantify ecosystem function through an analysis of direct and indirect food web transfers. We used a social network analysis method, cohesion analysis (CA), to assess ecosystem structure by organizing food web members into subgroups of strongly interacting predators and prey. Together, ENA and CA allowed us to understand how food web structure and function respond simultaneously to perturbation. In general, zebra mussel effects on the Bay of Quinte, when compared to Oneida Lake, were similar in direction, but greater in magnitude. Both systems underwent functional changes involving focused flow through a small number of taxa and increased use of benthic sources of production; additionally, both systems structurally changed with subgroup membership changing considerably (33% in Oneida Lake) or being disrupted entirely (in the Bay of Quinte). However, the response of total ecosystem activity (as measured by carbon flow) differed between both systems, with increasing activity in the Bay of Quinte, and decreasing activity in Oneida Lake. Thus, these analyses revealed parallel effects of zebra mussel invasion in ecosystems of similar trophic status, yet they also suggested that important differences may exist. As exotic species continue to disrupt the structure and function of our native ecosystems, food web network analyses will be useful for understanding their far-reaching effects.     

What is hidden behind the concept of ecosystem efficiency in energy transformation?

The number of energy transformation levels in trophic webs is usually below five, but can be extended up to ten when parasites and hyper-parasites are included. Research on the structure and function of food webs is relevant to the complexity–stability–productivity debate. The aim of this theoretical analysis is to link energetic and connectional aspects of ecosystems with information theory. Updating an energetic model reported by Ricklefs [Ecologia, Zanichelli Editore S.p.A., Bologna, Italy, 1993, p. 896], our approach is integrated with a static analysis of food webs. The length of food webs is theoretically associated with the average ecological efficiency which can be empirically correlated with the effective connectance between species. Furthermore, the advantage of greater complexity when applied to a signalling network is qualitatively addressed.The overall efficiency of energy transformation into biomass throughout a trophic web, in an ecosystem with a given number of species, is the resultant of the various ecological efficiencies, η, at the transitions between the trophic levels. However, we propose that an increment in effective connectance and interspecies connectivity based on a superimposed signalling web may increase the η values, despite the fact that signalling per se has an energetic cost. According to this hypothesis, ecosystem stability would not be necessarily reduced by increasing the number of trophic levels, N, whenever stability in terms of persistence is improved by a cost-efficient regulatory network.     

Diversity–stability relationships revisited: scaling rules for biological communities near equilibrium

The debate on diversity–stability relationships has a long history of theoretical interest and plays a central role in development of modern ecology. But such debate has recently re-opened under critical scrutiny both in theoretical and empirical studies. In this paper we use allometric (or energetic) scaling and statistical physics approaches to this problem. On the basis of local Damuth symmetry, a Markov model of transfer of energy between different species, and the fluctuation–dissipation theorem, scaling rules of species number and population variability of biological communities near equilibrium are derived. These scaling rules indicate that the diversity–stability relationship may be an energetic and thermodynamic consequence of ecological systems near equilibrium, not a simple statistical consequence as derived by other recent theoretical work.     

Using a Bayesian network to clarify areas requiring research in a host–pathogen system

Bayesian network analyses can be used to interactively change the strength of effect of variables in a model to explore complex relationships in new ways. In doing so, they allow one to identify influential nodes that are not well studied empirically so that future research can be prioritized. We identified relationships in host and pathogen biology to examine disease‐driven declines of amphibians associated with amphibian chytrid fungus (Batrachochytrium dendrobatidis). We constructed a Bayesian network consisting of behavioral, genetic, physiological, and environmental variables that influence disease and used them to predict host population trends. We varied the impacts of specific variables in the model to reveal factors with the most influence on host population trend. The behavior of the nodes (the way in which the variables probabilistically responded to changes in states of the parents, which are the nodes or variables that directly influenced them in the graphical model) was consistent with published results. The frog population had a 49% probability of decline when all states were set at their original values, and this probability increased when body temperatures were cold, the immune system was not suppressing infection, and the ambient environment was conducive to growth of B. dendrobatidis. These findings suggest the construction of our model reflected the complex relationships characteristic of host–pathogen interactions. Changes to climatic variables alone did not strongly influence the probability of population decline, which suggests that climate interacts with other factors such as the capacity of the frog immune system to suppress disease. Changes to the adaptive immune system and disease reservoirs had a large effect on the population trend, but there was little empirical information available for model construction. Our model inputs can be used as a base to examine other systems, and our results show that such analyses are useful tools for reviewing existing literature, identifying links poorly supported by evidence, and understanding complexities in emerging infectious‐disease systems.     

A global Bayesian sensitivity analysis of the 1d SimSphere soil–vegetation–atmospheric transfer (SVAT) model using Gaussian model emulation

Sensitivity analysis consists of an integral and important validatory check of a computer simulation model before the code is used in performing any kind of analysis operation. The present paper demonstrates the use of a relatively new method and tool for conducting global sensitivity analysis (GSA) for environmental models, providing simultaneously the first GSA study of the widely used 1d soil–vegetation–atmospheric transfer (SVAT) model named SimSphere. A software platform called the Gaussian emulation machine for sensitivity analysis (GEM SA), which has been developed for performing a GSA via Bayesian theory, is applied to SimSphere model in order to identify the most responsive model inputs to the simulation of key model outputs, detect their interactions and derive absolute sensitivity measures concerning the model structure. This study is also very timely in that, use of this particular SVAT model is currently being considered to be used in a scheme being developed for the operational retrieval of the soil surface moisture content by National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellite platforms that are due to be launched in the next 12 years starting from 2016.The employed GSA method was found capable of identifying the most responsive SimSphere inputs and also of capturing their key interactions for each of the simulated target quantities on which the GSA was conducted. The most sensitive model inputs were the topography parameters (slope, aspect) as well as the fractional vegetation cover and soil surface moisture availability. The implications of these findings for the future use of SimSphere are discussed.     

Preferential allocation of food by magpies Pica pica to great spotted cuckoo Clamator glandarius chicks

Adult magpies Pica pica provide parasitic great spotted cuckoo Clamator glandarius nestlings with a diet very similar to that fed to their own chicks. In both naturally and experimentally parasitized nests, great spotted cuckoo chicks were fed at a higher rate than magpie chicks in the same nest. This preferential allocation of food by magpie parents to great spotted cuckoo chicks is consistent with the supernormal stimulus hypothesis, because this result implies that cuckoo chicks provide stronger stimuli for parental care than host chicks. Great spotted cuckoo chicks receive most of the food brought to the nest by the foster parents, because they exploit a series of stimuli which jointly (or sometimes individually) operate as a supernormal stimulus. This hypothesis predicts that if any stimulus is masked, the efficiency of the cuckoo in eliciting parental care will decrease. Here, we analyze experimentally the effects of two of these stimuli, preferential feeding of large nestlings and of nestlings with conspicuous palatal papillae. Firstly, when we experimentally introduced one medium-sized (7–9 days) cuckoo chick into an unparasitized magpie nest where the largest magpie chick was 12–15 days old, the cuckoo did not receive significantly more food than the average or the largest magpie chick. Secondly, when unparasitized nests were experimentally parasitized with a cuckoo chick that had its gape painted to mimic that of magpie chicks, the parasitic cuckoo received less food than the average magpie chick.     

稻田流失养分循环利用系统构建研究初探

针对长江三角洲经济发达地区集约化农田化肥投入超量、稻区水体N、P、K富集度超高,农田生态环境遭到严重破坏等现状,该文系统研究了农田流失养分从农田到水体,再由水体回到农田的循环利用过程,并构建农田养分流失循环利用系统工程,为我国农田流失养分循环利用和农业生态环境健康提供科技支撑。研究结果表明：本区域农田面积为18.6 hm2,水稻季农田化肥N、P、K投入量分别为305.7、44.9、150.8 kg·hm-2;整个水稻季本区域农田地表径流量为4 518.0 kg·hm-2,其中N、P、K流失量分别为16.6、0.5、9.6 kg·hm-2,占水稻季N、P、K肥投入量的5.45%、1.07%和6.37%;农田周围净化池塘中水生植物的N、P、K拦截量分别为67.8、8.1、99.7 kg,分别占本研究区域N、P、K流入量的21.84%、90.31%和55.73%。将水生植物还田,晒干水葫芦（Halerpestes cymbalaria）按4 500 kg·hm-2农田施用,可分别减少农田化肥N、P、K的投入量106.2、9.5、105.8 kg·hm-2。该研究成果对于减轻农业生产面源污染,推进农业生产可持续发展具有积极意义。     

Analysis of ecosystem structure and function: extended path and flow analysis of a steady-state oyster reef model

An analysis of the extended path and flow structure of a six compartment steady-state oyster reef model was conducted. The extended path and flow structure were analyzed in the context of a refined canonical path classification system based on the systems theory methods of environ and network unfolding analyses. A computer implementation of an operational path classification system facilitated investigation of a finite portion (path length ≤17 arcs) of the direct and indirect path structure of the oyster reef model. Important results of the path structure analysis include: (1) few simple paths and large numbers of compound paths enumerated; (2) dominance of path numbers by subsequent passage terminal cycle paths; (3) structural evidence in support of feedback control in ecosystems; (4) results provide evidence by analogy to support the hypothesis of network homogenization first described using the systems analysis methods of environ analysis and network unfolding; (5) constancy of the pattern of origin–destination path counts with increasing path length; (6) importance of nonliving compartments in the extended path structure of ecosystems. Simultaneous path and flow analysis of the oyster reef model assessed the flow contributions of the fundamental path categories for this model using a modification of a path-based network unfolding method. First passage paths contribute most of the flow; however, multiple passage cyclic paths also provide a large (22%) flow contribution. Because of cycling in the system, the numerous long paths in the extended path structure of this ecosystem model are significant in its function as represented by the flows. These results provide microscopic evidence for the macroscopic results of environ analysis that implicate cycling as a key ecosystem attribute in the mechanisms of holistic system determination. The principles enunciated here for a model with a low cycling index (11%) carry over to, and would be even more significant for, models with high cycling indexes. These results also serve to form a link between the extended structure of food webs and their functioning as represented by energy-matter flows. The present analysis demonstrates that extended path structure, and the component articulation from which it is generated, have significant consequences for ecosystem function.     

近十年生态工程在中国的进展

我国生态工程近 1 0多年有进一步发展 ,研究和应用对象扩展为社会 -经济 -自然复合生态系统 ,目标明确为可持续发展 ,从追求一维的经济增长或环境与自然保护 ,走向富裕、健康、文明三维一体的复合生态繁荣。在充实“整体、协调、循环、自生”的生态工程原理和生态控制论的基础上 ,总结出生态工程设计的 8项原则。方法论发展为从物理过程的量化走向生态过程的序化 ,从工程结构的优化走向生态格局的进化 ,从机器的人工智能走向人的生态智能。技术路线发展了硬件、软件、心件耦合 ;多学科、多技术的系统组合 ;调控复合生态系统全生态过程 ;寓环境保护于生产和消费中 ,寓废弃物处理于利用中 ;结构和功能纵横耦合成食物链网式、生命周期式、生态系统式等网络结构     

Ecosystem states: Creating a data-derived, ecosystem-scale ecological response model that is explicit in space and time

Increasing difficulties associated with balancing consumptive demands for water and achieving ecological benefits in aquatic ecosystems provide opportunities for new ecosystem-scale ecological response models to assist managers. Using an Australian estuary as a case study, we developed a novel approach to create a data-derived state-and-transition model. The model identifies suites of co-occurring birds, fish, benthic invertebrates and aquatic macrophytes (as ‘states’) and the changing physico-chemical conditions that are associated with each (‘transitions’). The approach first used cluster analysis to identify sets of co-occurring biota. Differences in the physico-chemical data associated with each state were identified using classification trees, with the biotic distinctness of the resultant statistical model tested using analysis of similarities. The predictive capacity of the model was tested using new cases. Two models were created using different time-steps (annual and quarterly) and then combined to capture both longer-term trends and more-recent declines in ecological condition. We identified eight ecosystem states that were differentiated by a mix of water-quantity and water-quality variables. Each ecosystem state represented a distinct biotic assemblage under well-defined physico-chemical conditions. Two ‘basins of attraction’ were identified, with four tidally-influenced states, and another four independent of tidal influence. Within each basin, states described a continuum of relative health, manifest through declining taxonomic diversity and abundances. The main threshold determining relative health was whether freshwater flows had occurred in the region during the previous 339 days. Canonical analyses of principal coordinates tested the predictive capacity of the model and demonstrated that the variance in the environmental data set was well captured (87%) with 52% of the variance in the biological data set also captured. The latter increased to >80% when long- and short-term biological data were analysed separately, indicating that the model described the available data for the Coorong well. This approach thus created a data-derived, multivariate model, where neither states nor transitions were determined a priori. The approach did not over-fit the data, was robust to patchy or missing data, the choice of initial clustering technique and random errors in the biological data set, and was well-received by local natural resource managers. However, the model did not capture causal relationships and requires additional testing, particularly during future episodes of ecological recovery. The approach shows significant promise for simplifying management definitions of ecological condition and, via scenario analyses, can be used to assist in manager decision-making of large, complex aquatic ecosystems in the future.     

Structural path analysis of ecosystem networks

This paper explains the application of structural path analysis (SPA), an input–output-based technique for measuring flows in ecological and linked ecological–economic networks. Previous methods of input–output flow analysis have concluded with aggregate indexes relying on the summing feature of the Leontief inverse in order to completely account for throughflows along a multitude of inter-compartmental paths. This paper shows that for most linear dissipative networks, a manageable number of paths of limited length exist that cover in the order of 99% or more of total throughflow. These paths can be conveniently extracted, enumerated and ranked using SPA.     

Ecosystems emerging. 5: Constraints

Ecosystem constraints are both ontic and epistemic. They limit activity, and as problems to be solved they drive organization, which is our hypothesis:

The driver of organization is constraint.

Solutions proliferate further constraints in an unending spiral of problem (constraint) generation and solution. As constraints proliferate, behavior narrows, and species diversify to compensate (paradox of constraint). Resource enrichment reduces constraints, releases behavior, and reduction of challenges decreases diversity (paradox of enrichment)—high diversity is expressed in low-resource environments and low diversity in high-resource environments. A three-part model of constraints is formulated for non-living systems, and also for goal-directed, problem-solving biota. Mode 1: dynamical means behavior is co-determined by internal states and external inputs. Mode 2: cybernetic employs negative feedback to keep dynamics within goal-oriented operating limits. Mode 3: model-making entails ability to represent (model) physical reality and respond to both phenomenal (modeled) and physical inputs; this property distinguishes living from nonliving systems. Principal sections of the paper elaborate dynamical constraints (three classes), boundary constraints (expressed in edge effects and trophic dynamics), physical constraints (space, time, temperature), chemical constraints (environment fitness, ecological stoichiometry, chemical evolution, limiting factors), coding constraints (environmental vs. genetic coding), network and pathway constraints (connectivity), and natural selection constraints (fitting to the biosphere). Consideration of how the world would look without constraints suggests how fundamental these are in ecosystem emergence, and how the next property in this series, differentiation, would be unmotivated without them. We conclude that constraints as a category are under-studied in ecology, poorly understood in ecological phenomenology, and (our hypothesis) comprise a ubiquitous organizing force in nature.     

Defining an ecological thermodynamics using discrete simulation approaches

New insights into interdisciplinary engineering endeavors, from classical modeling to nano–macroscale extrapolation and critical evaluation, weigh heavily on the pervasive nature of thermodynamics in the physical world. Just as statistical thermodynamic approaches provide a beneficial complement to a process-based macroscale thermodynamic approaches with physical systems, a Lagrangian approach to energetics in biological systems can, we believe, provide a beneficial complement to popular Eulerian approaches. Statistical thermodynamics is used as a springboard for some analogies that are similarly used to leap into the ecological scale. The Lagrangian simulation, a discrete simulation, is implemented with a spreadsheet approach, a discrete simulation approach, and a new stochastic differential equation solution approach. The Lagrangian approach complements the more widely used continuous (or Eulerian) simulation approaches such as STELLA or Environ theory approaches. The Lagrangian approach decomposes energy into small packets or ecological quanta. An ecological entropy is computed based on nodal contacts in the network, with the notion that nodal contact is analogous to molecular speed. In the cases shown, the results of ecological entropy appear generally consistent with thermodynamic entropy. A newly available simulation package (ECONET) enabled an easy Lagrangian approach to analyzing the Cone Springs and Oyster ecological models. An analogy between nodal contact numbers and molecular speed was developed to enable computation of an ecological entropy. There is a similarity between classical and ecological entropy based on similarity in shape of the Maxwell–Boltzmann distributions to the packet-nodal contact numbers. An ecological temperature can be defined based on this similarity. Selected ratios of ecological entropy versus classical macroscopic entropy appeared to have some degree of robustness. Other aspects of ecological thermodynamics remain to be developed. It is felt that the ecological thermodynamics approach presented offers an improved way to combine biochemical and ecological entropy. A sound combination of entropies at multiple scales will help bring together measurements at disparate scales.