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Record Nr. |
UNINA9911132507003321 |
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Autore |
Hunt Allen G |
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Titolo |
Networks on Networks (Second Edition) : Role of Connectivity in Physics of Geobiology and Geochemistry |
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Pubbl/distr/stampa |
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Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : , : IOP Publishing, , [2024] |
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ISBN |
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9780750356985 |
0750356987 |
9780750356923 |
0750356928 |
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Edizione |
[2nd ed.] |
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Descrizione fisica |
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1 online resource (347 pages) |
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Collana |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Geobiology |
Geochemistry |
Geophysics |
SCIENCE / Physics / Geophysics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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"Version: 20241201"--Title page verso. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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1. Introduction -- 1.1. Background -- 1.2. Fundamental scaling relationships : advection versus diffusion -- 1.3. Summary |
2. Networks in ecological systems -- 2.1. Background : ecological networks -- 2.2. Soil networks -- 2.3. Root networks -- 2.4. Vegetation networks -- 2.5. River networks |
3. Percolation theory, effective-medium approximation, and upscaling -- 3.1. Background -- 3.2. Percolation theory and scaling properties -- 3.3. Structure of percolation clusters -- 3.4. Scaling of the macroscopic conductivity -- 3.5. Water partitioning in the pore space -- 3.6. Accessibility -- 3.7. Finite-size scaling -- 3.8. Critical-path analysis -- 3.9. Effective-medium approximation |
4. Predicting morphological, flow, and transport properties of porous media -- 4.1. Background -- 4.2. Models of porous media -- 4.3. Saturated hydraulic conductivity -- 4.4. Saturation-dependent properties |
5. Solute transport and reaction rate in heterogeneous porous media -- |
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5.1. Background -- 5.2. Percolation theory for solute transport in heterogeneous porous media -- 5.3. Dispersivity -- 5.4. Distribution of solute arrival times -- 5.5. Scaling of the reaction rate |
6. Water transport and storage -- 6.1. Background -- 6.2. Water transport : Richards equation, Philip infiltration, and invasion percolation -- 6.3. Water storage and its implications for plants |
7. Water transport in plants -- 7.1. Background -- 7.2. Pore scale -- 7.3. Tissue scale -- 7.4. Ecological implications of the safety-efficiency trade-off -- 7.5. Plant scale |
8. Allometric scaling and metabolism -- 8.1. Background -- 8.2. A general model for scaling of metabolic rates -- 8.3. Plant allometry emerging from fractal branching networks -- 8.4. Conduit furcation -- 8.5. Scaling of above-ground and below-ground characteristic sizes -- 8.6. Scaling of size and age -- 8.7. Ecosystem scale |
9. Edaphic constraints : role of soil in vegetation growth -- 9.1. Background -- 9.2. Fundamental predictions based on percolation scaling -- 9.3. Soil data -- 9.4. Vascular plant data -- 9.5. Generalizations and implications |
10. Geomorphological applications of percolation theory : river networks, and weathering and soil depths -- 10.1. Background -- 10.2. River networks -- 10.3. Steady-state versus unsteady-state soil production and the implications for long time scales -- 10.4. The 'mystery' of one meter-deep soils -- 10.5. Soil depth and landslides |
11. Ecohydrological applications : watershed hydrology and water balance -- 11.1. Background -- 11.2. The water balance -- 11.3. Arid lands -- 11.4. Forests and grasslands -- 11.5. Comparison with data -- 11.6. Net primary productivity -- 11.7. Elasticity of streamflow |
12. Hazards to plants and vegetation : disease propagation, deforestration, and forest fires -- 12.1. Background -- 12.2. Improving production of plants with plague susceptibility -- 12.3. Spread of fungi in soil -- 12.4. Pattern of tropical deforestation -- 12.5. Forest fires |
13. Edaphic constraints : revisiting the gaia hypothesis -- 13.1. Background -- 13.2. A percolation model -- 13.3. The data -- 13.4. Quantitative test of Gaia hypothesis using networks. |
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Sommario/riassunto |
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Treating soil as a physical network allows a better understanding of the biological networks based in the soil as well as enhanced accuracy of the prediction of the water cycle, the carbon cycle, soil physical properties, and plant species richness. This improvement in prediction addresses one of the biggest obstacles to predicting human impacts on climate change. |
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