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Eco‐evolutionary optimality as a means to improve vegetation and land‐surface models

SummaryGlobal vegetation and land‐surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. However, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco‐evolutionary optimality (EEO) principles can provide novel, parameter‐sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf‐level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change.
- Aix-Marseille University France
- University of Reading United Kingdom
- Imperial College London United Kingdom
- The University of Texas System United States
- University of California, Berkeley United States
Climate Change, STOMATAL CONDUCTANCE, Plant Biology & Botany, acclimation, TRAIT VARIATION, land-surface model, CARBON-DIOXIDE, water and carbon trade-offs, stomatal behaviour, PLANT FUNCTIONAL TYPES, 07 Agricultural and Veterinary Sciences, XXXXXX - Unknown, TROPICAL MOIST FORESTS, Ecosystem, Plant Physiological Phenomena, 580, Science & Technology, CLIMATE-CHANGE, QUANTUM YIELD, Agricultural and Veterinary Sciences, plant functional ecology, leaf economics spectrum, Plant Sciences, eco-evolutionary optimality, 06 Biological Sciences, Biological Sciences, Plants, Plant Leaves, global vegetation model, [SDE]Environmental Sciences, ISOPRENE EMISSIONS, ELEVATED CO2, Life Sciences & Biomedicine, WATER-USE EFFICIENCY
Climate Change, STOMATAL CONDUCTANCE, Plant Biology & Botany, acclimation, TRAIT VARIATION, land-surface model, CARBON-DIOXIDE, water and carbon trade-offs, stomatal behaviour, PLANT FUNCTIONAL TYPES, 07 Agricultural and Veterinary Sciences, XXXXXX - Unknown, TROPICAL MOIST FORESTS, Ecosystem, Plant Physiological Phenomena, 580, Science & Technology, CLIMATE-CHANGE, QUANTUM YIELD, Agricultural and Veterinary Sciences, plant functional ecology, leaf economics spectrum, Plant Sciences, eco-evolutionary optimality, 06 Biological Sciences, Biological Sciences, Plants, Plant Leaves, global vegetation model, [SDE]Environmental Sciences, ISOPRENE EMISSIONS, ELEVATED CO2, Life Sciences & Biomedicine, WATER-USE EFFICIENCY
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).90 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1% visibility views 59 download downloads 41 - 59views41downloads
Data source Views Downloads Spiral - Imperial College Digital Repository 40 20 Central Archive at the University of Reading 19 21


