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Plant traits and biogeochemical cycles, including optimality, acclimation and adaptation in land ecosystem models (co-organized)
Convener: Jens Kattge  | Co-Conveners: Markus Reichstein , Michael Bahn , Sönke Zaehle , Han Wang , Oskar Franklin 
 / Mon, 09 Apr, 10:30–12:00
 / Attendance Mon, 09 Apr, 17:30–19:00

Plant traits extend the range of earth observations to the level of individual organisms, providing a link to ecosystem function and modeling in the context of rapid global changes. However, overcoming the differences in temporal and spatial scales between plant trait data and biogeochemical cycles remains a challenge. This session will address the role of plant species, biodiversity and adaptation / acclimation in the biogeochemical cycles of water, carbon, nitrogen and phosphorus. We welcome conceptual, observational, experimental and modeling approaches, and studies from the local to the global scale, including e.g. remote sensing observations.

The optimality principle proposes that organisms adjust to environmental variations so as to maximize measures that impinge on fitness, and are thereby subject to natural selection. A generalization is that ecosystem function is maintained by acclimation within individuals, adaptation within species, changing abundances within ecosystems, and migration within regions.
In an emerging paradigm, optimality concepts are used to generate testable predictions at multiple scales. This approach may eventually resolve the stubborn, largely untraceable differences among current ecosystem models’ projections of the impacts of environmental change. Optimality concepts have been applied to aspects of plant and ecosystem function including stomatal behaviour, plant water use and photosynthetic capacity, nitrogen uptake, and phenology. To seed communication and collaboration among pioneers of this field, including observational scientists and experimental ecologists, we invite contributions on all topics related to optimality principles in plant and ecosystem function including theoretical analyses, experimental tests, and models.