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Climate change, phenology, and phenological control of vegetation feedbacks to the climate system

物候学 生物群落 气候变化 环境科学 植被(病理学) 气候学 生态学 生态系统 生物 医学 地质学 病理
作者
Andrew D. Richardson,Trevor F. Keenan,Mirco Migliavacca,Youngryel Ryu,Oliver Sonnentag,Michael Toomey
出处
期刊:Agricultural and Forest Meteorology [Elsevier BV]
卷期号:169: 156-173 被引量:2068
标识
DOI:10.1016/j.agrformet.2012.09.012
摘要

Vegetation phenology is highly sensitive to climate change. Phenology also controls many feedbacks of vegetation to the climate system by influencing the seasonality of albedo, surface roughness length, canopy conductance, and fluxes of water, energy, CO2 and biogenic volatile organic compounds. In this review, we first discuss the environmental drivers of phenology, and the impacts of climate change on phenology, in different biomes. We then examine the vegetation-climate feedbacks that are mediated by phenology, and assess the potential impact on these feedbacks of shifts in phenology driven by climate change. We finish with an overview of phenological modeling and we suggest ways in which models might be improved using existing data sets. Several key weaknesses in our current understanding emerge from this analysis. First, we need a better understanding of the drivers of phenology, particularly in under-studied biomes (e.g. tropical forests). We do not have a mechanistic understanding of the role of photoperiod, even in well-studied biomes. In all biomes, the factors controlling senescence and dormancy are not well-documented. Second, for the most part (i.e. with the exception of phenology impacts on CO2 exchange) we have only a qualitative understanding of the feedbacks between vegetation and climate that are mediated by phenology. We need to quantify the magnitude of these feedbacks, and ensure that they are accurately reproduced by models. Third, we need to work towards a new understanding of phenological processes that enables progress beyond the modeling paradigms currently in use. Accurate representation of phenological processes in models that couple the land surface to the climate system is particularly important, especially when such models are being used to predict future climate.
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