Soil biota and global change at the ecosystem level: describing soil biota in mathematical models
Identifieur interne : 001005 ( Istex/Curation ); précédent : 001004; suivant : 001006Soil biota and global change at the ecosystem level: describing soil biota in mathematical models
Auteurs : Pete. Smith ; Olof. Andrén ; Lijbert Brussaard [Pays-Bas] ; Mark. Dangerfield ; Klemens Ekschmitt ; Patrick Lavelle ; Kevin TateSource :
- Global Change Biology [ 1354-1013 ] ; 1998-10.
Descripteurs français
- Wicri :
English descriptors
- KwdEn :
- Agricultural science, America journal, Andren, Belowground food webs, Biodiversity, Biomass, Biota, Blackwell science, Brussaard, Case daisy, Century model, Chertov komarov, Climate change, Csiro information services, Current models, Datasets, Detrital food, Detrital model, Different scales, Dynamics, Earthworm, Earthworm activities, Earthworm activity, Ecological, Ecological bulletins, Ecological modelling, Ecology, Ecosystem, Ecosystem engineers, Ecosystem level, Ecosystem models, Ecosystem processes, Ecosystem scale, Explicit description, Fertilizer research, Food webs, Functional groups, Further research, Future process rate, Gcte, Gcte focus, Gcte somnet, Global, Global biogeochemical cycles, Global change, Global change biology, Global change research, Global change studies, Grassland, Gupta vvsr, Hierarchical approach, Humus forms, Implicit description, Jenkinson, Longterm datasets, Many models, Mathematical models, Matter dynamics, Matter models, Matter network, Mcgill, Microbial, Microbial biomass, Mineralization, Model structure, Modelling, Modelling approach, Molina, Molina smith, Nitrogen dynamics, Nitrogen mineralization, Nitrogen transformations, Nutrient cycling, Nutrient dynamics, Organic matter, Organic matter models, Organism, Organismorientated, Organismorientated components, Organismorientated models, Other models, Parton, Paustian, Perennial pasture, Personal communication, Philosophical transactions, Potential effects, Powlson, Predictive, Predictive purposes, Predictive tools, Process rate, Real world, Relative advantages, Research tools, Response surface, Royal society, Ruiter, Same problem, Schematic diagram, Schimel, Schimel gulledge, Simulating, Simulating trends, Simulation, Simulation model, Simulation models, Soil biodiversity, Soil biology, Soil biota, Soil carbon, Soil community, Soil community function, Soil community structure, Soil ecosystem models, Soil fauna, Soil organisms, Soil science, Soil science department, Soil science society, Soil structure, Soil system, Somnet, Special issue, Springer, Sustainable farming systems, System feedbacks, Taxonomic groups, Terrestrial ecosystems, Theoretical analysis, Turnover, Turnover rates, Various approaches, Winter wheat, Wormless pasture.
- Teeft :
- Agricultural science, America journal, Andren, Belowground food webs, Biodiversity, Biomass, Biota, Blackwell science, Brussaard, Case daisy, Century model, Chertov komarov, Climate change, Csiro information services, Current models, Datasets, Detrital food, Detrital model, Different scales, Dynamics, Earthworm, Earthworm activities, Earthworm activity, Ecological, Ecological bulletins, Ecological modelling, Ecology, Ecosystem, Ecosystem engineers, Ecosystem level, Ecosystem models, Ecosystem processes, Ecosystem scale, Explicit description, Fertilizer research, Food webs, Functional groups, Further research, Future process rate, Gcte, Gcte focus, Gcte somnet, Global, Global biogeochemical cycles, Global change, Global change biology, Global change research, Global change studies, Grassland, Gupta vvsr, Hierarchical approach, Humus forms, Implicit description, Jenkinson, Longterm datasets, Many models, Mathematical models, Matter dynamics, Matter models, Matter network, Mcgill, Microbial, Microbial biomass, Mineralization, Model structure, Modelling, Modelling approach, Molina, Molina smith, Nitrogen dynamics, Nitrogen mineralization, Nitrogen transformations, Nutrient cycling, Nutrient dynamics, Organic matter, Organic matter models, Organism, Organismorientated, Organismorientated components, Organismorientated models, Other models, Parton, Paustian, Perennial pasture, Personal communication, Philosophical transactions, Potential effects, Powlson, Predictive, Predictive purposes, Predictive tools, Process rate, Real world, Relative advantages, Research tools, Response surface, Royal society, Ruiter, Same problem, Schematic diagram, Schimel, Schimel gulledge, Simulating, Simulating trends, Simulation, Simulation model, Simulation models, Soil biodiversity, Soil biology, Soil biota, Soil carbon, Soil community, Soil community function, Soil community structure, Soil ecosystem models, Soil fauna, Soil organisms, Soil science, Soil science department, Soil science society, Soil structure, Soil system, Somnet, Special issue, Springer, Sustainable farming systems, System feedbacks, Taxonomic groups, Terrestrial ecosystems, Theoretical analysis, Turnover, Turnover rates, Various approaches, Winter wheat, Wormless pasture.
Abstract
All current mathematical models of the soil system are underpinned by a wealth of research into soil biology and new research continues to improve the description of the real world by mathematical models. In this review we examine the various approaches for describing soil biology in mathematical models and discuss the use of each type of model in global change research. The approaches represented among models participating in the Global Change and Terrestrial Ecosystems (GCTE) Soil Organic Matter Network (SOMNET) are described. We examine the relative advantages and constraints of each modelling approach and, using these, suggest appropriate uses of each. We show that for predictive purposes at ecosystem scale and higher, process‐orientated models (which have only an implicit description of soil organisms) are most commonly used. As a research tool at the ecosystem level, both process‐orientated and organism‐orientated models (in which functional or taxonomic groups of soil organisms are explicitly described) are commonly used. Because of uncertainties introduced in internal model parameter estimation and system feedbacks, the predictive use of organism‐orientated models at the ecosystem scale and larger is currently less feasible than is the use of process‐orientated models. In some specific circumstances, however, an explicit description of some functional groups of soil organisms within models may be required to adequately describe the effects of global change. No existing models can adequately predict the feedback between global change, a change in soil community function, and the response of the changed system to future global change. To find out if these feedbacks exist and to what extent they affect future global change, more research is urgently required into the response of soil community function to global change and its potential ecosystem‐level effects.
Url:
DOI: 10.1046/j.1365-2486.1998.00193.x
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Pete. Smith<affiliation><mods:affiliation>Soil Science Department, IACR‐Rothamsted, Harpenden, Herts AL5 2JQ, UK,</mods:affiliation>
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<affiliation><mods:affiliation>Key Centre for Biodiversity & Bioresources, School of Biological Sciences, Macquarie University, Syndey, NSW 2109, Australia,</mods:affiliation>
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<affiliation><mods:affiliation>Department of Animal Ecology, University of Giessen, Stephanstrasse 24, 35390 Giessen, Germany,</mods:affiliation>
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<affiliation><mods:affiliation>ORSTOM, Ecologie des Sol Tropicaux, 32 avenue Varagnat, F‐93143, Bondy cedex, France,</mods:affiliation>
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<affiliation><mods:affiliation>Landcare Research, Massey University, Private Bag 11052, Palmerston North, New Zealand</mods:affiliation>
<wicri:noCountry code="subField">New Zealand</wicri:noCountry>
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<term>Nitrogen mineralization</term>
<term>Nitrogen transformations</term>
<term>Nutrient cycling</term>
<term>Nutrient dynamics</term>
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<term>Soil biota</term>
<term>Soil carbon</term>
<term>Soil community</term>
<term>Soil community function</term>
<term>Soil community structure</term>
<term>Soil ecosystem models</term>
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<term>Soil science</term>
<term>Soil science department</term>
<term>Soil science society</term>
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<term>Soil system</term>
<term>Somnet</term>
<term>Special issue</term>
<term>Springer</term>
<term>Sustainable farming systems</term>
<term>System feedbacks</term>
<term>Taxonomic groups</term>
<term>Terrestrial ecosystems</term>
<term>Theoretical analysis</term>
<term>Turnover</term>
<term>Turnover rates</term>
<term>Various approaches</term>
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<term>Wormless pasture</term>
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<front><div type="abstract" xml:lang="en">All current mathematical models of the soil system are underpinned by a wealth of research into soil biology and new research continues to improve the description of the real world by mathematical models. In this review we examine the various approaches for describing soil biology in mathematical models and discuss the use of each type of model in global change research. The approaches represented among models participating in the Global Change and Terrestrial Ecosystems (GCTE) Soil Organic Matter Network (SOMNET) are described. We examine the relative advantages and constraints of each modelling approach and, using these, suggest appropriate uses of each. We show that for predictive purposes at ecosystem scale and higher, process‐orientated models (which have only an implicit description of soil organisms) are most commonly used. As a research tool at the ecosystem level, both process‐orientated and organism‐orientated models (in which functional or taxonomic groups of soil organisms are explicitly described) are commonly used. Because of uncertainties introduced in internal model parameter estimation and system feedbacks, the predictive use of organism‐orientated models at the ecosystem scale and larger is currently less feasible than is the use of process‐orientated models. In some specific circumstances, however, an explicit description of some functional groups of soil organisms within models may be required to adequately describe the effects of global change. No existing models can adequately predict the feedback between global change, a change in soil community function, and the response of the changed system to future global change. To find out if these feedbacks exist and to what extent they affect future global change, more research is urgently required into the response of soil community function to global change and its potential ecosystem‐level effects.</div>
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