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Spatial variance of spring phenology in temperate deciduous forests is constrained by background climatic conditions.

ABSTRACT: Leaf unfolding in temperate forests is driven by spring temperature, but little is known about the spatial variance of that temperature dependency. Here we use in situ leaf unfolding observations for eight deciduous tree species to show that the two factors that control chilling (number of cold days) and heat requirement (growing degree days at leaf unfolding, GDD_req) only explain 30% of the spatial variance of leaf unfolding. Radiation and aridity differences among sites together explain 10% of the spatial variance of leaf unfolding date, and 40% of the variation in GDD_req. Radiation intensity is positively correlated with GDD_req and aridity is negatively correlated with GDD_req spatial variance. These results suggest that leaf unfolding of temperate deciduous trees is adapted to local mean climate, including water and light availability, through altered sensitivity to spring temperature. Such adaptation of heat requirement to background climate would imply that models using constant temperature response are inherently inaccurate at local scale.

SUBMITTER: Peaucelle M

PROVIDER: S-EPMC6879605 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Spatial variance of spring phenology in temperate deciduous forests is constrained by background climatic conditions.

Peaucelle Marc M Janssens Ivan A IA Stocker Benjamin D BD Descals Ferrando Adrià A Fu Yongshuo H YH Molowny-Horas Roberto R Ciais Philippe P Peñuelas Josep J

Nature communications 20191126 1

Leaf unfolding in temperate forests is driven by spring temperature, but little is known about the spatial variance of that temperature dependency. Here we use in situ leaf unfolding observations for eight deciduous tree species to show that the two factors that control chilling (number of cold days) and heat requirement (growing degree days at leaf unfolding, GDD<sub>req</sub>) only explain 30% of the spatial variance of leaf unfolding. Radiation and aridity differences among sites together exp ...[more]

PMID: 31772185

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Project description:AimForest understorey microclimates are often buffered against extreme heat or cold, with important implications for the organisms living in these environments. We quantified seasonal effects of understorey microclimate predictors describing canopy structure, canopy composition and topography (i.e., local factors) and the forest patch size and distance to the coast (i.e., landscape factors).LocationTemperate forests in Europe.Time period2017-2018.Major taxa studiedWoody plants.MethodsWe combined data from a microclimate sensor network with weather-station records to calculate the difference, or offset, between temperatures measured inside and outside forests. We used regression analysis to study the effects of local and landscape factors on the seasonal offset of minimum, mean and maximum temperatures.ResultsThe maximum temperature during the summer was on average cooler by 2.1 °C inside than outside forests, and the minimum temperatures during the winter and spring were 0.4 and 0.9 °C warmer. The local canopy cover was a strong nonlinear driver of the maximum temperature offset during summer, and we found increased cooling beneath tree species that cast the deepest shade. Seasonal offsets of minimum temperature were mainly regulated by landscape and topographic features, such as the distance to the coast and topographic position.Main conclusionsForest organisms experience less severe temperature extremes than suggested by currently available macroclimate data; therefore, climate-species relationships and the responses of species to anthropogenic global warming cannot be modelled accurately in forests using macroclimate data alone. Changes in canopy cover and composition will strongly modulate the warming of maximum temperatures in forest understories, with important implications for understanding the responses of forest biodiversity and functioning to the combined threats of land-use change and climate change. Our predictive models are generally applicable across lowland temperate deciduous forests, providing ecologically important microclimate data for forest understories.

Dataset Information

Spatial variance of spring phenology in temperate deciduous forests is constrained by background climatic conditions.

Publications

Spatial variance of spring phenology in temperate deciduous forests is constrained by background climatic conditions.

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