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Cited by 349

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

Ecological optimality in water‐limited natural soil‐vegetation systems: 1. Theory and hypothesis

Eagleson, Peter S.·1982·Water Resources Research

Abstract

The solution space of an approximate statistical‐dynamic model of the average annual water balance is explored with respect to the hydrologic parameters of both soil and vegetation. Within the accuracy of this model it is shown that water‐limited natural vegetation systems are in stable equilibrium with their climatic and pedologic environments when the canopy density and species act to minimize average water demand stress. Theory shows a climatic limit to this equilibrium above which it is hypothesized that ecological pressure is toward maximization of biomass productivity. It is further hypothesized that natural soil‐vegetation systems will develop gradually and synergistically, through vegetation‐induced changes in soil structure, toward a set of hydraulic soil properties for which the minimum stress canopy density of a given species is maximum in a given climate. Using these hypotheses, only the soil effective porosity need be known to determine the optimum soil and vegetation parameters in a given climate.

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Metadata

Authors
Eagleson, P. S.
Venue
Water Resources Research
Published
1982-04
Volume
18
Issue
2
Pages
325-340
ISSN
  • 0043-1397 (ISSN-L)
  • 1944-7973
OpenAlex
W1998251298
Cited by
349
References
17
FWCI
5.70
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Ecological optimality in water‐limited natural soil‐vegetation systems: 1. Theory and hypothesis. https://app.cochat.ai/papers/10.1029/wr018i002p00325
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Eagleson, P. S. (1982). Ecological optimality in water‐limited natural soil‐vegetation systems: 1. Theory and hypothesis. Water Resources Research. https://doi.org/10.1029/wr018i002p00325

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.