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V. Life's Corporeal Evolution Develops, Encodes and Organizes Itself: An Earthtwinian Genesis Synthesis

6. Dynamic Fractal Network Ecosystems

Jovani, Roger and Jose Tella. Fractal Bird Nest Distribution Produces Scale-Free Colony Sizes. Proceedings of the Royal Society B. 274/2465, 2007. A research report from the Biological Station of Donana, Spain finds, if one might reflect, a universality of self-similar scale-invariance (nested nests) whereof storks cluster in trees in the same fashion as galaxies and genomes. (Compare also with May Lim, et al, for ethnic cultures.) Once again a novel, self-generating nature employs and displays the same recursive pattern and process everywhere.

Thus, although storks were locally highly clumped even with tens of nests in a single tree, the population was not structured in colonies (a simple clustered distribution) as previously thought. Rather they were distributed in a continuous hierarchical set of clusters within clusters across scales, clusters lacking the commonly assumed characteristic mean size. These quantitative solutions to previously perceived scaling problems will potentially improve our understanding of the ecology and evolution of bird coloniality and animal spacing patterns and group living in general. (2465)

More generally, these results intimately link colony size variation and spatial distribution, by realizing that colony size variation was the outcome of the spatial distribution of nests, but not the reverse. This supports empirically the idea that colony size variation is intrinsically related to settlement decisions of individuals, also reinforcing the recent suggestion that self-organization processes could be behind these (and other) clustering patterns. (2469)

Kaitala, Hiroya, et al, eds. Mutualism and Community Organization. New York: Oxford University Press. 1993. An initial attempt toward a revised ecology which can emphasize holism, synergy, symbiosis, and connectionism.

Kefi, Sonia, et al. How Structured Is the Entangled Bank? The Surprisingly Simple Organization of Multiplex Ecological Networks Leads to Increased Persistence and Resilience. PLoS Biology. Online August, 2016. A good example of how the 2010s discernment of a network nature from cosmic webs to social media can serve to explain every realm. Here French, Chilean, and American scientists attest that the latest theories reveal heretofore unnoticed, common interconnections between all manner of fauna and flora. As a result, 157 years after The Origin of Species a mathematical ecological milieu can be described that would surely please Charles Darwin. And as Network Physics, and this whole site seeks to report, if of a mind to do so, a worldwise discovery of a procreative genesis uniVerse can be seen in our midst which we seem meant to read, realize, save and intentionally continue.

Species are linked to each other by a myriad of positive and negative interactions. This complex spectrum of interactions constitutes a network of links that mediates ecological communities’ response to perturbations, such as exploitation and climate change. In the last decades, there have been great advances in the study of intricate ecological networks. We have, nonetheless, lacked both the data and the tools to more rigorously understand the patterning of multiple interaction types between species (i.e., “multiplex networks”), as well as their consequences for community dynamics. Using network statistical modeling applied to a comprehensive ecological network, which includes trophic and diverse non-trophic links, we provide a first glimpse at what the full “entangled bank” of species looks like. The community exhibits clear multidimensional structure, which is taxonomically coherent and broadly predictable from species traits. Moreover, dynamic simulations suggest that this non-random patterning of how diverse non-trophic interactions map onto the food web could allow for higher species persistence and higher total biomass than expected by chance and tends to promote a higher robustness to extinctions. (Abstract)

Keil, Petr, et al. Macroecological and Macroevolutionary Patterns Emerge in the Universe of GNU/Linux Operating Systems. Ecography. 41/11, 2018. This rich paper by European theoretical ecologists is reviewed more in Common Principles.

Keitt, Timothy, et al. Scaling in the Growth of Geographically Subdivided Populations. Philosophical Transactions of the Royal Society of London B. 357/627, 2002. Statistical patterns of variation in growth rates of over 400 species of birds exhibit common, power-law patterns, which are suggestive of general laws at work.

It is interesting to note that our results are in striking qualitative agreement with similar studies from a broad range of social systems, ranging from growth of companies in the US economy to the GDP of countries. (627)

Keller, Evelyn Fox. Ecosystems, Organisms, and Machines. . . For a special section on “new thinking in biology,” the MIT philosopher of science discusses the historical perception from Immanuel Kant to mid 20th century cybernetics to current nonlinear dynamical theory of an animate, developing nature that organizes itself. Reviewed more in Part V.

Kerkhoff, Andrew and Brian Enquist. The Implications of Scaling Approaches for Understanding Resilience and Reorganization in Ecosystems. BioScience. 57/6, 2007. Natural flora and fauna, in variegated biotas, are arrayed in nested hierarchies so as to maintain their viability. A disturbance of this functional constitution can then be used as a measure of their health and a guide to its restoration if perturbed.

Our thesis is that ecological scaling relationships may serve as baselines or attractors describing the steady-state structure and functioning of ecological systems; and, as a result, departures from scaling may serve as indicators of the disproportionate influence of particular structuring processes and their role in organizing, or reorganizing, the ecosystem. (491)

Klimasara, Pawel and Marta Tyran-Kaminska. A Model of Seasonal Savanna Dynamics. arXiv:2211:05859. We cite this entry by University of Information Technology, Katowicz and University of Silesia, Poland researchers as a current example of how a mathematical presence that underlies flora foliage has been well quantified. In regard, it would serve if this double genetic-like domain became fully realized (see Suzanne Simard) so to aid untangling and sustaining nature’s bank account.

We introduce a mathematical model of savanna vegetation dynamics. The usual approach of nonequilibrium ecology is extended by including the impact of wet and dry seasons. We present and rigorously analyze a model describing a mixed woodland-grassland ecosystem with stochastic environmental noise in the form of vegetation biomass losses manifesting fires. Both, the probability of ignition and the strength of these losses depend on the current season (as well as vegetation growth rates etc.). Formally it requires an introduction and analysis of a system that is a piecewise deterministic Markov process with parameters switching between given constant periods of time. We study the long time behavior of time averages for such processes. (Abstract)

Kohn, Marek. The Needs of the Many. Nature. 456/296, 2008. As part of a kickoff “Darwin200” issue, a broad survey of the past reception and current pros and cons of how to understand the presence of group selection.

Lassig, M., et al. Shape of Ecological Networks. Physical Review Letters. 86/19, 2001. Ecosystems are found to have a characteristic topology analogous to biological systems and quantum phenomena.

Lek, Sovan and J.-F. Guegan, eds. Artificial Neural Networks: Applications to Ecology and Evolution. Berlin: Springer, 2000. The generic network principles developed from how the brain forms and learns are found to apply and help explain many areas from gene regulation and biodiversity to epidemiology and social discourse.

Leveque, Christian. Ecology: From Ecosystem to Biosphere. Enfield, NH: Science Publishers, 2003. A translation of an extensive 2001 work in French on applying systems principles to diverse environments.

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