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Ecological Modelling 189 (2005) 221232 The consequences of the aggregation of detritus pools
 

Summary: Ecological Modelling 189 (2005) 221232
The consequences of the aggregation of detritus pools
in ecological networks
Stefano Allesinaa,b,, Cristina Bondavallia, Ursula M. Scharlerc,d
a Department of Environmental Sciences, University of Parma, Viale delle Scienze 33/A, 43100 Parma, Italy
b Department of Fisheries and Wildlife, Michigan State University, 13 Natural Resources Building, East Lansing, MI 8824, USA
c Chesapeake Biological Laboratory, University of Maryland, Center for Environmental Studies, Solomons, MD 20688, USA
d Smithsonian Environmental Research Center, 647 Contees Wharf Road, Edgewater, MD 21037, USA
Received 19 August 2004; received in revised form 31 March 2005; accepted 6 April 2005
Available online 3 June 2005
Abstract
Ecological networks are quantitative, graph-based descriptions of ecosystems, consisting of compartments (trophospecies and
nutrient pools) that exchange fluxes of nutrients or energy. Previous research pointed out how the model's design is a crucial
task that can heavily influence analyses results, and how merging compartments for the purpose of comparing two or more
different ecosystems can significantly alter the indices on which the comparison is based. All these works have been focused on
the aggregation of trophospecies, whereas networks may comprise several nutrient compartments that may be lumped as well,
either for lack of information or for comparison constraints.
We show how the aggregation of these non-living compartments can have a greater influence on network analysis results than
trophospecies clustering. This problem should on the one hand encourage modelers to make an effort to test the possible effects
of aggregations, and on the other show how the role of non-living compartments could be very important in determining network

  

Source: Allesina, Stefano - Department of Ecology and Evolution, University of Chicago

 

Collections: Environmental Sciences and Ecology; Biology and Medicine