37,124 research outputs found
Theoretical ecology as etiological from the start
The world’s leading environmental advisory institutions look to ecological theory and research as an objective guide for policy and resource management decision-making. In addition to various theoretical merits of doing so, it is therefore crucially important to clear up confusions about ecology’s conceptual foundations and to make plain the basic workings of inferential methods used in the science. Through discussion of key moments in the genesis of the theoretical branch of ecology, this essay elucidates a general heuristic role of teleological metaphor in ecological research and defuses certain enduring confusions and misguided criticisms of current work in ecology
Digital Ecosystems: Ecosystem-Oriented Architectures
We view Digital Ecosystems to be the digital counterparts of biological
ecosystems. Here, we are concerned with the creation of these Digital
Ecosystems, exploiting the self-organising properties of biological ecosystems
to evolve high-level software applications. Therefore, we created the Digital
Ecosystem, a novel optimisation technique inspired by biological ecosystems,
where the optimisation works at two levels: a first optimisation, migration of
agents which are distributed in a decentralised peer-to-peer network, operating
continuously in time; this process feeds a second optimisation based on
evolutionary computing that operates locally on single peers and is aimed at
finding solutions to satisfy locally relevant constraints. The Digital
Ecosystem was then measured experimentally through simulations, with measures
originating from theoretical ecology, evaluating its likeness to biological
ecosystems. This included its responsiveness to requests for applications from
the user base, as a measure of the ecological succession (ecosystem maturity).
Overall, we have advanced the understanding of Digital Ecosystems, creating
Ecosystem-Oriented Architectures where the word ecosystem is more than just a
metaphor.Comment: 39 pages, 26 figures, journa
Biology of Applied Digital Ecosystems
A primary motivation for our research in Digital Ecosystems is the desire to
exploit the self-organising properties of biological ecosystems. Ecosystems are
thought to be robust, scalable architectures that can automatically solve
complex, dynamic problems. However, the biological processes that contribute to
these properties have not been made explicit in Digital Ecosystems research.
Here, we discuss how biological properties contribute to the self-organising
features of biological ecosystems, including population dynamics, evolution, a
complex dynamic environment, and spatial distributions for generating local
interactions. The potential for exploiting these properties in artificial
systems is then considered. We suggest that several key features of biological
ecosystems have not been fully explored in existing digital ecosystems, and
discuss how mimicking these features may assist in developing robust, scalable
self-organising architectures. An example architecture, the Digital Ecosystem,
is considered in detail. The Digital Ecosystem is then measured experimentally
through simulations, with measures originating from theoretical ecology, to
confirm its likeness to a biological ecosystem. Including the responsiveness to
requests for applications from the user base, as a measure of the 'ecological
succession' (development).Comment: 9 pages, 4 figure, conferenc
Ecosystem-Oriented Distributed Evolutionary Computing
We create a novel optimisation technique inspired by natural ecosystems,
where the optimisation works at two levels: a first optimisation, migration of
genes which are distributed in a peer-to-peer network, operating continuously
in time; this process feeds a second optimisation based on evolutionary
computing that operates locally on single peers and is aimed at finding
solutions to satisfy locally relevant constraints. We consider from the domain
of computer science distributed evolutionary computing, with the relevant
theory from the domain of theoretical biology, including the fields of
evolutionary and ecological theory, the topological structure of ecosystems,
and evolutionary processes within distributed environments. We then define
ecosystem- oriented distributed evolutionary computing, imbibed with the
properties of self-organisation, scalability and sustainability from natural
ecosystems, including a novel form of distributed evolu- tionary computing.
Finally, we conclude with a discussion of the apparent compromises resulting
from the hybrid model created, such as the network topology.Comment: 8 pages, 5 figures. arXiv admin note: text overlap with
arXiv:1112.0204, arXiv:0712.4159, arXiv:0712.4153, arXiv:0712.4102,
arXiv:0910.067
Information Technology Platforms: Definition and Research Directions
The concept of an information technology (IT) related platform is broad and
covers phenomena ranging from the operating system Linux to the Internet. Such
platforms are of increasing importance to innovation and value creation across
many facets of industry and daily life. There is, however, a lack of common
understanding in both research and industry about what is mean by the term
platform when related to IT. This lack of consensus is detrimental to research
and knowledge development. Thus, the aims of this study are to: (i) provide a
sound definition of the IT-platform concept by identifying its distinguishing
dimensions; and (ii) identify important current research directions for the
IT-platform concept. To achieve these aims a systematic literature review was
undertaken with 133 relevant articles taken from major information systems
journals, conferences, and business publications. The study contributes by
providing a sound base for future research into IT-platforms.Comment: Research-in-progress ISBN# 978-0-646-95337-3 Presented at the
Australasian Conference on Information Systems 2015 (arXiv:1605.01032
Throughflow centrality is a global indicator of the functional importance of species in ecosystems
To better understand and manage complex systems like ecosystems it is
critical to know the relative contribution of system components to system
functioning. Ecologists and social scientists have described many ways that
individuals can be important; This paper makes two key contributions to this
research area. First, it shows that throughflow, the total energy-matter
entering or exiting a system component, is a global indicator of the relative
contribution of the component to the whole system activity. It is global
because it includes the direct and indirect exchanges among community members.
Further, throughflow is a special case of Hubbell status as defined in social
science. This recognition effectively joins the concepts, enabling ecologists
to use and build on the broader centrality research in network science. Second,
I characterize the distribution of throughflow in 45 empirically-based trophic
ecosystem models. Consistent with expectations, this analysis shows that a
small fraction of the system components are responsible for the majority of the
system activity. In 73% of the ecosystem models, 20% or less of the nodes
generate 80% or more of the total system throughflow. Four or fewer dominant
nodes are required to account for 50% of the total system activity. 121 of the
130 dominant nodes in the 45 ecosystem models could be classified as primary
producers, dead organic matter, or bacteria. Thus, throughflow centrality
indicates the rank power of the ecosystems components and shows the power
concentration in the primary production and decomposition cycle. Although these
results are specific to ecosystems, these techniques build on flow analysis
based on economic input-output analysis. Therefore these results should be
useful for ecosystem ecology, industrial ecology, the study of urban
metabolism, as well as other domains using input-output analysis.Comment: 7 figures, 2 table
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