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Fossil leaf traits as archives for the past — and lessons for the future?

Author:
Roth-Nebelsick, Anita, Konrad, Wilfried
Source:
Flora 2019 v.254 pp. 59-70
ISSN:
0367-2530
Subject:
carbon dioxide, carbon dioxide enrichment, climate change, ecophysiology, embryophytes, environmental factors, evolution, fossils, gas exchange, heat transfer, leaf morphology, leaves, models, paleoclimatology, prediction, stomatal conductance, temperature, vegetation, water supply
Abstract:
Correlations of leaf traits with environmental conditions are widely used for reconstruction of palaeoclimate and to analyse the evolution of land plants. Evaluation of climate-dependent leaf traits of fossil floras can potentially contribute to our understanding of long-term responses of vegetation to changing climate. In this contribution, basic aspects and methods of palaeoclimate reconstruction by fossil leaf morphology, such as leaf margin analysis and CLAMP, are presented and discussed with respect to recent results on functional leaf traits. Also addressed is the use of stomatal data (density and size) for obtaining palaeoatmospheric CO2 as well as the (possible) interference of CO2 with other abiotic environmental parameters, leading to “non-analogue climates” which cannot be found today. There is much evidence that CO2, as an essential factor for gas exchange and therefore palaeoecophysiology, acted as an important driver in land plant evolution. For instance, elevated CO2 levels of the past and present are assumed to affect leaf shape evolution, because stomatal conductance is negatively correlated with atmospheric CO2 thereby affecting leaf heat dissipation. This topic is addressed in detail as an exemplary case of the interference of multiple environmental parameters. Results of a gas exchange model with coupled heat transfer indicate that the effect of elevated CO2 on leaf temperature may be minor, at least when water supply is not limited. This example demonstrates that ecophysiological analyses of trait–climate relationships can contribute to identifying adaptive features of leaf architecture and to evaluate predictions into the future as well as into the past.
Agid:
6134393