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Aspects of ecology-based environmentalism may run counter to how nature works; it is important to get the science right. The Janus Enigma Hypothesis is formulated as a flow–storage network approach to holistic ecological understanding. It proceeds from primary energy–matter consumption toward maximization of throughflow. When transferred material is energy, the goal function is maximum power (energy flow). The Janus Hypothesis has the following line of development: 1. The 2nd Law of Thermodynamics requires that the environments of aggrading (anti-entropic) processes become themselves degraded. To restrict such degradation is to limit life's processes. 2. A maximum power conjecture holds that aggrading systems self-organize to maximize power generating work. Maximal resource use, work production, and environmental degradation necessarily follow. This applies also to material flow in generalized energy–matter (throughflow) processing. 3. In maximizing power (throughflow), biota perform work to maximize their fitness (Type I, biological), but at the expense of degraded environments. Zero-sumness of conservative, consumptive transfers produces a proximate life–environment relationship that is win–lose. 4. But covert mechanisms also operate such that maximizing throughflow also maximizes a system-wide, nonzero-sum, network property— dominant indirect effects . 5. These maximize another property of network organization, network synergism . This transforms proximate, tangible, zero-sum, agonistic, (+, −) transactions into ultimate, intangible, nonzero-sum, mainly positive (+, +) and synergistic relations . The proximate transactions lead by network processes to ultimate nonzero-sum benefits > costs, which is network synergism. 6. By the indirect line from maximum power (throughflow) to network synergism, biotic work maximizes both biological and ecological fitness (Type II), and the life–environment relationship becomes win–win. This cannot be seen from pure empiricism because it plays out diffusely as limit processes in networks that are virtual. Three lines of evidence are presented in support of the Janus Hypothesis: (1) “Building a biosphere” by progressively adding nodes and links in simple compartment models shows throughflow and network synergism to be positively correlated. (2) Decomposing the utility measure of network synergism in these models into its constituents shows them to be largely made up of throughflows; maximum network synergism likely follows from the maximization of throughflow. (3) Comparing total system throughflow with network synergism in 31 food webs described for Ukrainian pasturelands shows the two measures to be positively correlated in this large empirical database. The Janus Hypothesis has a built-in paradox. Because the positive benefits derived from the nonzero-sum maximum throughflow → network synergism → Fitness-II line exceed the negative costs generated by the zero-sum maximum throughflow → Fitness-I line, applied programs designed to reduce environmental degradation will reduce not only Fitness-I, but also Fitness-II by foregoing the implicit benefits of network synergism that inherently exceed the explicit costs of maximizing throughflow. This is the Janus Enigma. It means that well-meaning but misguided environmental programs may actually, in fact must, induce a lose–lose relationship between life and environment. If the Janus Hypothesis proves scientifically valid, environmentalism must resolve and manage the apparent conflict, and ecology as its parent science must expand its dimensions and become a complex systems science competent in understanding and methodology to meet the challenges of complex, intractable, non-obvious holism in nature's living networks. [ABSTRACT FROM AUTHOR]

This is the first of two numbered papers for this Special Issue dealing with the ecological basis of environmentalism. The second follows, in a subsequent issue if not here. Patten (2013) gives a short preview of both papers. Problems of environmentalism—environmental protection, conservation, and preservation—are now widely appreciated as important to human enterprise and destiny. Called to attention by advances in descriptive empirical ecology, the new problems are too complex for this same ecology to solve without further expansion of basic knowledge. To understand how nature works two kinds of science are needed, one empirical, describing what is immediate and tangible, the other theoretical, developing first-principles understanding of what is indirect and intangible. Development of a complex systems theory based ecology is hindered by over-commitment of attention and resources to applied environmentalism. This may in its inadequacy run counter to how nature works, which could be detrimental to both humanity and nature. It is important to get the science right. As background for a revisionary hypothesis presented in Part II, five elements of basic ecology and five of applied environmentalism are here reviewed. The basic topics are ecological energetics, linear vs. nonlinear dynamics, steady vs. non-steady states, epistemic mediation, and indirect effects. The environmental topics are overpopulation, biodiversity, invasive species, sustainability, and global change. [ABSTRACT FROM AUTHOR]

Indirect effects are important components of ecological and evolutionary interactions that may maintain biodiversity, enable or inhibit invasive species, and challenge ecosystem assessment and management. A central hypothesis of Network Environ Analysis (NEA), one type of ecological network analysis, is that indirect flows tend to dominate direct flows in ecosystem networks of conservative substance exchanges. However, current NEA methods assume that these ecosystems are stationary (i.e. time invariant exchange rates), which is unlikely to be true for many ecosystems for interesting time and space scales. For the work reported here, we investigated the sensitivity of the dominance of indirect effects hypothesis to the stationary modeling assumption by determining the development rate of indirect effects and flow intensity, as expressed as the number of transfer steps, in thirty-one ecosystem models. We hypothesized that indirect effects develop rapidly in ecological networks, but that they would develop faster in biogeochemically based models than in trophically based models. In contrast, our results show that indirect effects develop rapidly in all thirty-one models examined. In 94% of the models, indirect flows exceeded direct flows by a pathway length of 3. This indicates that ecological systems do not need to maintain a particular configuration for long for indirect effects to dominate. Thus, the dominance of indirect effects hypothesis remains plausible. We also found that biogeochemical models tended to require more of the extended path network than the trophic models to account for 50% and 95% of the total system activity, but that both types of models required more of the power series than is typically considered in engineered systems. These results succinctly illustrate the complexity of ecological systems and help explain why they are challenging to assess and manage. [ABSTRACT FROM AUTHOR]

Abstract: This paper reviews literature on the life cycle of the marine algal genus Phaeocystis, and organizes existing information in the form of a qualitative conceptual model of life-cycle stages, stage transitions, ecosystem inputs and outputs, and internal and external controlling factors. Conceptualization is the first phase of modeling, typically continued in later quantitative phases by mathematical formulation, calibration of parameters, dynamic simulation, and different forms of systems analysis. Qualitative conceptualization can also promote multidisciplinary interactions and structure early stages of scientific inquiry. To exploit the qualitative benefits of conceptual modeling, the goals of this paper are to: (1) review the literature of Phaeocystis life-cycle biology and ecology; (2) from the material of this review, construct, a conceptual life-cycle model covering all Phaeocystis species; and (3) show how this model, a platform for further quantitative development, is also used as a qualitative tool to guide empirical research. The conceptual model includes known and putative life-cycle stages, colony size classes, and genetic, physiological, semiotic, and ecological information expressed or potentially expressed across the genus. It consists of 15 compartments. Seven are single-celled: Solitary Diploid Flagellates (x 1), Solitary Diploid Non-flagellates (x 2), Benthic Solitary Diploid Non-Flagellates (x 3), Solitary Diploid Flagellated Macrozoospores (x 8), Solitary Haploid Flagellated Microzoospores (x 9), Solitary Haploid Microflagellates (x 10), and Solitary Haploid Mesoflagellates (x 11). The remaining eight compartments represent the New stage, and Small, Medium, and Large size classes of Healthy/Growing Colonies (x 4–x 7), and Senescent/Declining Colonies (x 12–x 15). Six flow types interconnect the compartments: (a) physical transport, (b) solitary cell transformations, (c) solitary cell↔colony transitions, (d) colony growth and differentiation, (e) colony senescence, and (f) syngamy of solitary haploid cells. Boundary inputs and outputs include flows associated with transport, nutrient exchange, chemical signals, and grazing and cell lysis. Factors controlling flows include genetics, cellular and organismal biology, info-chemistry, and ecology. [Copyright &y& Elsevier]

An experimental course in mathematical ecology at the University of Tennessee is described. Applied statistics is not emphasized, the objectives being to develop: (1) appreciation for natural affinities between ecology and mathematics. (2) familiarity with techniques of systems analysis, and (3) skill in the use of analog and digital computers. [ABSTRACT FROM AUTHOR]

An environ is a within-system partition of the environment associated with each ecosystem component. The methodologies for calculating throughflow-based and storage-based environs have heretofore been considered quantitatively and qualitatively different. Below, we show, from the fundamental environ equations, that these two approaches are mathematically equivalent by proving the throughflow-storage-equivalence relationship, T E = S E. This implies that ecosystem flows of energy or matter to storage and throughflow are one and the same, differing only in storage delays (flow impedances) along the way in the storage case. [Copyright &y& Elsevier]

Network environ analysis is motivated by a desire to investigate ecosystems from a holistic perspective. It provides a quantitative measure of the integral (direct plus indirect) relationship between compartments and their within-system environments. In this analysis, each compartment within a system has an incoming interactive network that brings matter to it from the system''s boundary inputs, and an outgoing network that takes matter from it to boundary outputs. These are, respectively, input and output environs. Methods described herein are used to compare environs from a time series of ecological networks for which the flow structure remains constant while flow quantities change. Observed differences in environs are analyzed with respect to: (a) differences between the steady-state seasonal ecosystem networks, and (b) which compartment receives the ‘analytical input’ in output-environ analysis. The Neuse River estuary is an ideal subject for this because a time series of 16 seasonal steady-state networks of nitrogen (N) storage and flow were constructed for the period spring 1985 through winter 1989 by Christian and colleagues. We explore two levels of analysis. The first is macro-level analysis of whole environs; total environ throughflow, an index of whole-environ activity, is computed and compared. The second is micro-level analysis which involves the individual intercompartmental flow and boundary output elements of output environs for two selected focal compartments, phytoplankton (x 1-PN-Phyto) and nitrate/nitrite (x 5-NO x ). Our findings indicate that most of the observed variation in environs is being driven by differences in the seasonal networks analyzed. The macro-scale patterns observed for the environs show the same seasonal patterns evident in the whole steady-state network time series. These results support and extend the constancy of temporal indirect effects results reported by Borrett et al. [Borrett, S.R., Whipple, S.J., Patten, B.C., 2006. Indirect effects and distributed control in ecosystems: temporal variation of indirect effects in a seven-compartment model of nitrogen flow in the Neuse River estuary, USA—time series analysis. Ecol. Model. 194, 178–188]. When comparing different environs within the same season, the macro-scale patterns show that the environs are quantitatively very similar; however, when micro-scale patterns are observed, it is found that the environs are indeed unique. Macro-scale similarities are thought to be driven by high cycling indices and high network homogenization. A conclusion from the comparative analysis of the Neuse estuary networks is that these environs display a weak autonomy. We hypothesize that the individuality of the environs is suppressed by two characteristics of the Neuse estuary networks: they are strongly connected graphs, and they contain many linked autocatalytic cycles. Two aspects of our results provide a means to link ecological measures important to the Neuse River estuary and environ analysis. Environ throughflow () is driven by boundary inputs, which is equivalent to the ecological measure of N loading, with dominance of total by DON (x 4-DON), nitrate–nitrite (x 5-NO x ), and ammonium (x 6-NH4), which receive the largest boundary inputs. Previous network analysis demonstrated that, on average, one-half of the nitrogen needs of phytoplankton are met by nitrogen that once resided in the sediments. Phytoplankton (x 1-PN-Phyto) and sediment (x 3-Sed), and ammonium (x 6-NH4) had distinctly different pattern than the steady-state TST pattern... [Copyright &y& Elsevier]

This essay evaluates visualization practices in data science and the digital humanities by drawing on the resources of the environmental humanities. I show how certain conceptions of ecology and natural systems have provided constitutive metaphors in the design and theorization of data visualization practices. This genealogy of the visual culture of data science began with the professionalization of graph theory in the nineteenth century. Ecological analogies were also a prominent feature in twentieth-century computer and network design, and they have continued to inform many of the layout algorithms that generate present-day data visualizations. This history of ideas and practices shows how ecological metaphors have naturalized information systems in ways that obscure the material and social realities of those systems. [ABSTRACT FROM AUTHOR]

An essay analyzing the ecological value claims made by environmental advisory institutions is presented. It explains the meaning given by environmental institutions and agencies to the concepts of ecological entities, functionality and properties and examines the management strategy directives issued by such agencies that are relevant to the three concepts. It also analyzes how the lack of criteria for categorizing ecological entities and functionality hinder the understanding of their value.