VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies
7. Dynamic Ecosystems
Saavedra, Serguei, et al. A Simple Model of Bipartite Cooperation for Ecological and Organizational Networks. Nature. 457/463, 2009. Since science now proceeds on the plane of a worldwide personal humankind, rather than by one man, real discoveries being made often pass unnoticed. A case in point might be a flurry of papers (Sugihara, Griffen, Wills, Palmer, May, Heng, Misteli) on a repetitive occurrence of the same dynamic patterns and processes across widely disparate natural and social realms. In this case, with Northwestern University’s Brian Uzzi as mentor, similar “metrics” are found in plant-animal pollination networks and manufacturer-contractor business.
Our study identifies striking similarities in the general structural characteristics of networks that are formed as a result of cooperative mechanisms operating in radically different contexts, linking partners in ecological and socio-economic systems, respectively. This empirical finding motivates the proposed simple model for bipartite cooperation, which captures the most important generic features of mutualistic interaction patterns starting from a minimal set of input parameters. At the level of partner–partner interactions, equivalent behaviour in different systems appears to be driven by similar types of interaction constraints. These correspond to complementarity in traits or characteristics, a hierarchical organization limiting the range of potential partners, and the environmental context. (465-466)
Santos, F. and J. Pacheco. Scale-Free Networks Provide a Unifying Framework for the Emergence of Cooperation. Physical Review Letters. 95/098104, 2005. A paper cited in Tom Siegfried’s A Beautiful Math which theoretically affirms an innate favorable bias to cooperate rather than compete.
We study the evolution of cooperation in the framework of evolutionary game theory, adopting the prisoner’s dilemma and snowdrift game as metaphors of cooperation between unrelated individuals. In sharp contrast with previous results we find that, whenever individuals interact following networks of contacts generated via growth and preferential attachment, leading to strong correlations between individuals, cooperation becomes the dominating trait throughout the entire range of parameters of both games, as such providing a unifying framework for the emergence of cooperation. (098104-1)
Schneider, David. The Rise of the Concept of Scale in Ecology. BioScience. 51/7, 2001. Ecosystems are best characterized by a dynamic hierarchy due to a power-law self-organized criticality.
Schramski, John, et al. Metabolic Theory Predicts Whole-Ecosystem Properties. Proceedings of the National Academy of Sciences. 112/2617, 2015. An update on this large project hosted by James Brown of the University of New Mexico, a co-author. Into the mid 2010s, decades of field and laboratory study are paying off with a general, robust synthesis such as this.
Understanding the effects of individual organisms on material cycles and energy fluxes within ecosystems is central to predicting the impacts of human-caused changes on climate, land use, and biodiversity. Here we present a theory that integrates metabolic (organism-based bottom-up) and systems (ecosystem-based top-down) approaches to characterize how the metabolism of individuals affects the flows and stores of materials and energy in ecosystems. The theory provides a robust basis for estimating the flux and storage of energy, carbon, and other materials in terrestrial, marine, and freshwater ecosystems and for quantifying the roles of different kinds of organisms and environments at scales from local ecosystems to the biosphere. Abstract excerpts)
Sendzimir, Jan, et al. Implications of Body Mass Patterns. Bissonette, John and Ilse Storch, eds. Landscape Ecology and Resource Management. Washington, DC: Island Press, 2003. In an article typical of this collection of papers, the use of complex adaptive systems theory can elucidate a self-similar pattern of ecological processes, landscape structure and species body size.
The fine-scale structure of herbaceous vegetation, the medium-scale mosaic of forest patches, and the grand geological sweep of the landscape have an appealing cohesiveness and fit, like nested Russian dolls. (129)
Seuront, Laurent. Fractals and Multifractals in Ecology and Aquatic Science. Boca Rotan: CRC Press, 2009. With theoretical and evidential depth, a Flinders University, Adelaide, biologist and oceanographer articulates the self-organizing mathematics of a newly intelligible, untangled nature where the same patterns recur everywhere on land and sea. A gloss of main topics can attest: About Geometries, Self-Similar and Self-Affine Fractals, Frequency Distributions, Fractal-Related Clarifications (re self-organized criticality), Estimating Dimensions, and Multifractals. The volume is thus intended as a handbook to aid ecologists in these novel appreciations.
Shachak, Moshe and Bertrand Boeken. Patterns of Biotic Community Organization and Reorganization. Ecological Complexity. 7/4, 2010. Ben Gurion University ecologists report that complex adaptive systems theory, from Simon Levin, can well model variable shrub vegetation patterns in the face of ever-changing environments.
Recent developments in the field of complex systems provide new frontiers for the study of ecological organization. One of the hallmarks of complexity is that global phenomena emerge out of local interactions that affect global properties and behavior of systems. Non-linear interactions provide important sources for large-scale order that emerges from self-organization. In ecological systems three global phenomena of self-organization result from local interactions among species. On the community level, local interactions determine species assemblage organization, i.e. the distribution of species and their abundance in time and space. On the ecosystem level, the global phenomenon is food web organization, which is the source of functional properties such as energy flow and nutrient cycling. On the landscape level, order appears in the form of biotically induced mosaics of patches such as vegetation patterns in arid and semi-arid lands. (433-434)
Shade, Ashley, et al. Macroecology to Unite All Life, Large and Small. Trends in Ecology & Evolution. Online September, 2018. As many other fields lately seek an integral synthesis to fulfill and cap decades of diverse studies, eleven scientists from the USA, Denmark, Germany and the Czech Republic here propose a comprehensive systems ecology. A salient principle of metabolic rates across microbial to “macrobial” phases is taken as a good guide. A glossary includes terms as Abundance-occupancy, Metagenomics, Mesocosm, Morphospecies, Taxonomic Units, and so on. See also An Integrated View of Complex Landscapes: A Big Data-Model Integration Approach to Transdisciplinary Science by Debra Peters, et al in BioScience (68/9, 2018) and herein for another effort.
Macroecology is the study of the mechanisms underlying general patterns of ecology across scales. Research in microbial ecology and macroecology have long been detached. Here, we argue that it is time to bridge the gap, as they share a common currency of species and individuals, and a common goal of understanding the causes and consequences of changes in biodiversity. Microbial ecology and macroecology will mutually benefit from a unified research agenda and shared datasets that span the entirety of the biodiversity of life and the geographic expanse of the Earth. (Abstract)
Solari, Aldo, et al. On Skipjack Tuna Dynamics: Similarity at Several Scales. Seuront, Laurent and Peter Strutton, eds. Handbook of Scaling Methods in Aquatic Ecology. Boca Rotan, FL: CRC Press, 2004. Of special interest is the finding that these tuna populations have invariant structures because their nautical environment itself is an iteration of temperature patterns, surface waves, wind effects, and so on, which carry on into the depths of a “fractal ocean.”
Sole, Ricard. Scaling Laws in the Drier. Nature. 449/151, 2007. A synopsis of two technical reports in the same issue as breakthrough examples of how complex system theories can reveal the presence of dynamic, scale-free, self-organization due to localized interactions, in this case for the spatial distribution of vegetation. Based on the Kalahari and Iberian ecosystems studied, this work is said to be of especial import because changes in such patterns can be employed to portend a shift to an arid desert condition, so measures might be taken to avert it.
Sole, Ricard and Jordi Bascompte. Self-Organization in Complex Ecosystems. Princeton: Princeton University Press, 2006. Sole lists the Universitat Pompeu Fabra in Barcelona and Santa Fe Institute, while Bascompte cites the Spanish Research Council and University of California, Santa Barbara. In this collaboration, the field of a dynamic ecological science is brought to a new phase of experimental and theoretical synthesis. Living nature is perceived not in an equilibrium balance but as distinguished by far-from-equilibrium nested networks from microbial realms to species macroevolution. Importantly, the authors go on to attribute such “complex adaptive systems” everywhere to an universal, independent source.
This book presents theoretical evidence of the potential of nonlinear ecological interactions to generate nonrandom, self-organized patterns at all levels. (1) Life itself is a good example: (irreducible) nucleic acids, proteins, or lipids are not “alive” by themselves. It is the cooperation among different sets that actually creates a self-sustained, evolvable pattern called life. Over the last decades of the twentieth century the shortcomings of the reductionist approach had become increasingly apparent, and at some point a new type of integrative biology began to emerge. (11) Such universality reminds us of a different perspective of evolutionary change emphasizing the role of fundamental constraints. These theories suggest that basic, universal laws of organization shape the large-scale architecture of biological systems. (14)
Stauffer, Dietrich, et al. Evolutionary Ecology in Silico: Evolving Food Webs, Migrating Population and Speciation. Physica A. 352/202, 2005. An update and review of Stauffer and colleagues on-going project to understand dynamic ecosystems in terms of complex systems science.
Biology is a storehouse of exotic and fascinating phenomena at all levels of organization – from sub-cellular level to cells, tissues, organs, organisms, colonies,…, up to level of ecosystems. In this paper we review some of the exciting new developments in modeling dynamical phenomena at the level of ecosystems using some concepts and techniques that have been found extremely useful in studying self-organized complex adaptive systems. (203)