Biomedical subjects

R Pilette

Publications and source records attributed to R Pilette.

4 recordsLinked to original sources

PubMed1992

Construction of simple pathways and simple cycles in ecosystems.

We present software tools for overcoming the problem of combinatorics in the enumeration of simple pathways and simple cycles in a first flow-through analysis of carbon transfer in large ecosystems. Rather than search through the very large number of potential routes in a reasonably sized ecosystem for the relatively small number of actual routes, our main algorithm performs an efficient rule-based construction of the actual routes. The enumeration of the unique pathways becomes tractable in terms of CPU time, which increases linearly with ecosystem size and connectedness. Networks of up to 80 entities can be evaluated using our software.

Algorithms↗

PubMed1991

Stability patterns and trophic structure in a Delaware Bay plankton community.

Using qualitative loop analysis we have extended our examination of a Delaware Bay plankton community to include an investigation of the roles played by the various entities (population, guild or nutrient) in the community. In an entity removal exercise, we used stability relationships as a probe into community structure. Six types of stability change are possible as a result of entity removal from the system: stable to stable (s-->s); stable to unstable (s-->u); stable to disconnected (s-->d); unstable to stable (u-->s); unstable to unstable (u-->u); unstable to disconnected (u-->d). Using these changes as an investigative tool, we found that in order to account for the stability-instability patterns, it was necessary to construct a refined trophic structure model. The observed connections between the entities in the larger model could be grouped into two different types of stability substructures: a simple pattern and a more complex branching pattern. These patterns map easily onto the refined trophic structure model. Using stability analysis it is also possible to model community structure in ways other than the traditional trophic approach. Patterns of system necessity and relative contribution to stability are observed. These patterns match the refined trophic structure model derived previously. The roles that the various entities play in the overall community were followed over an annual cycle. Entities were seen to change their roles as a function of time and status within a subgroup. These results show that stability determinations have the potential to be used as a valuable tool in community analysis.

Animals↗

PubMed1990

Stability-complexity relationships within models of natural systems.

Drawing on the qualitative loop analysis models prepared by Lane for a Delaware Bay plankton community, we evaluated 12 systems that ranged from 14 to 18 entities (population, guild or nutrient). Our approach was to study models of extended trophic biotic communities and examine the stability-complexity issue not only as it exists between systems (the traditional approach) but also with respect to the entities and relationships within a given system. We found no statistically significant inverse relationship for stability and complexity between systems. Within a system, a significant inverse relationship at the entity level was observed embedded in an increasing stability positively related to increasing subsystem size. Also, within a system and from system to system, several entities were seen to vary their roles with respect to stability. These results extend the stability-complexity issue to models of relatively large biotic communities and raise issues concerning the roles, with respect to stability, played by entities within communities.

Animals↗

PubMed1987

The potential for community level evaluations based on loop analysis.

In this paper we present results obtained with a computer simulation in which a community, described by Levins in his presentation of loop analysis (Levins, R., 1975, Evolution in communities near equilibrium, in: Ecology and Evolution of Communities, M.L. Cody and J.M. Diamond (eds) (Harvard University Press, Cambridge, Mass.) pp. 16-50), is analysed. We show how our simulation accurately reproduces Levins' calculations and further, (i) how our simulation can be used to answer questions raised by Levins but never answered, (ii) how the simulation can be used to dissect a community in order to analyse the roles played by the various entities, and (iii) how predictions relating to the evolution of this community, proposed by Levins, can be analysed with some interesting and unexpected results. In particular, it becomes clear that discussion of the type of selection that may take place needs to be done in the framework of the community in which it occurs.

Biological Evolution↗