ECO Soft

Copenhagen, Denmark
Copenhagen, Denmark
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Nielsen S.N.,ECO Soft | Ulanowicz R.E.,University of Maryland College Park | Ulanowicz R.E.,University of Florida
Ecological Modelling | Year: 2011

The physicist Walter M. Elsasser is mostly known for his work on the Earth's magnetism. Less attention has been paid to his efforts toward identifying what are the real differences between physical and biological systems. One essential distinction he recognized was that physical systems are largely homogenous while biological systems always revealed what he called ordered heterogeneity. Calculation of the possible configurations of such heterogeneous systems almost always leads to combinatorial explosions and to what Elsasser referred to as immense numbers. Such calculations have the consequence that any such systems are necessarily unique - mathematically speaking they represent one-sets.Another consequence is that immense numbers automatically introduce enormous uncertainty and indeterminacy into the system. Such systems are said to be ontically open. Applying this perspective to the genome and employing the notion of informational entropy reveals a common drive behind all development. This means that both conventional Darwinian evolution as well as the genomic mistakes that are believed to lie behind processes like aging and diseases can be interpreted against the background of one and the same process.At the same time the approach demonstrates how Darwinian evolution encompasses other notions such as Kauffman's " adjacent possible" (Kauffman, 1995, 2000) and Eldrege's and Gould's " evolution via punctuated equilibria" (e.g., Eldredge and Gould, 1972; Gould and Eldredge, 1977). © 2011 Elsevier B.V.

Jorgensen S.E.,Copenhagen University | Nielsen S.N.,ECO Soft
Ecological Indicators | Year: 2013

After a short overview of the hierarchical organization, that characterizes ecological systems, a quantification of the openness of the various hierarchical levels is introduced. By the use of statistical calculations, it is furthermore shown that the random variations due to environmental disturbances in one level of the hierarchy are averaged and therefore result in less variations or disturbances in the next level. Random disturbances are with other words damped when we go up through the hierarchical levels, which obviously is a clear advantage by the hierarchical organization. Thus it is shown that diversity at all levels has the consequences of ensuring a more stable system and less sensitive to environmental disturbances. This is a result that is in contradiction to earlier findings of May (1973, 1981). Approximate calculations of this damping effect can be carried out. The level out effects of the hierarchical organization and the recovery time makes it possible for ecosystems to cope with the relationship between the frequency and the magnitude of the disturbances. These important properties that are crucial for the reactions of the various hierarchical levels to the impacts on ecosystems, are applied in a discussion of the choice of ecological indicators and the applicability of these indicators are demonstrated. The presented hierarchical properties entail that biodiversity on all hierarchical levels is a very important ecological indicator, which is the core topic for the discussion, that summarizes the results and conclusions.© 2012 Elsevier Ltd.

Jorgensen S.E.,Copenhagen University | Nielsen S.N.,ECO Soft
Ecological Indicators | Year: 2012

Integrated ecological-environmental management represents a new approach to traditional environmental management as it is to be understood as environmental management that also include ecological principles. It may be described by a procedure which follows 7 steps: (1) define the problem, (2) determine the ecosystem(s) involved, (3) identify causes and quantify all the sources to the problem, (4) set up a diagnosis to understand the relation between the problem and the sources, (5) determine the tools we need to implement to solve the problem, (6) take the proper measures or actions and (7) follow the recovery process. Steps 4-6 require the use of recently developed ecological disciplines and concepts. First, it involves ecological modelling, ecological indicators and ecosystem services, fields which are used to gain insight, increase understanding and set up a diagnosis for the problems of ecosystems. Second, it is necessary to identify measures and find solutions. This involves the use of environmental technology, one of the earliest initiatives, followed by ecological engineering (also designated ecotechnology), environmental legislation and cleaner technology, including industrial ecology, as tools to solve the problems. Without these seven relatively new ecological disciplines, it would not be possible to make an up-to-date integrated and holistic ecological-environmental management. These new disciplines serve to build an indispensable and strong bridge from ecology to environmental management. © 2011 Elsevier Ltd. All rights reserved.

Wang Q.,East China Normal University | Jorgensen S.E.,Copenhagen University | Lu J.,East China Normal University | Nielsen S.N.,ECO Soft | Zhang J.,East China Normal University
Ecological Modelling | Year: 2013

Spartina alterniflora (Smooth Cordgrass) and Phragmites australis (Common Reed) are dominant types of vegetation in Jiuduansha Shoals in the Yangtze Estuary of China. Each species has advantages in terms of growth and competition in different tidal zones. The vegetation types are dynamic due to the variation in the extension and position of different elevation zones due to the deposition of the sediments carried by river runoff. A model was constructed to simulate the vegetation changes over time due to the changes in sediment loads and zonation. A structurally dynamic model was built using Stella software which based on: (i) S. alterniflora and P. australis biological interaction at different elevation; (ii) the morphometric changes of the island which are increasing based on sediment disposition and the sediment trapping effect of plants. The model simulations predict that the areas of P. australis will continue to increase; it will be reach to 1100. ha in 2028. S. alterniflora areas will decrease after the areas slightly increasing to maximum 712. ha in 2015. © 2012 Elsevier B.V.

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