Effects of chilling on heat requirement of spring phenology vary between years

Abstract Spring warming substantially advances leaf unfolding and flowering time for perennials. Winter warming, however, decreases chilling accumulation (CA), which increases the heat requirement (HR) and acts to delay spring phenology. Whether or not this negative CA-HR relationship is correctly interpreted in ecosystem models remains unknown. Using leaf unfolding and flowering data for 30 perennials in Europe, here we show that more than half (7 of 12) of current chilling models are invalid since they show a positive CA-HR relationship. The possible reason is that they overlook the effect of freezing temperature on dormancy release. Overestimation of the advance in spring phenology by the end of this century by these invalid chilling models could be as large as 7.6 and 20.0 days under RCPs 4.5 and 8.5, respectively. Our results highlight the need for a better representation of chilling for the correct understanding of spring phenological responses to future climate change.

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

Nature Communications ◽

10.1038/s41467-019-13365-1 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 10

Author(s):

Marc Peaucelle ◽

Ivan A. Janssens ◽

Benjamin D. Stocker ◽

Adrià Descals Ferrando ◽

Yongshuo H. Fu ◽

...

Keyword(s):

Light Availability ◽

Temperature Response ◽

Climatic Conditions ◽

Deciduous Tree ◽

Spring Temperature ◽

Spatial Variance ◽

Spring Phenology ◽

Leaf Unfolding ◽

Temperate Deciduous ◽

Heat Requirement

AbstractLeaf 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, GDDreq) 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 GDDreq. Radiation intensity is positively correlated with GDDreq and aridity is negatively correlated with GDDreq 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.

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Examining Relationships between Heat Requirement of Remotely Sensed Green-Up Date and Meteorological Indicators in the Hulun Buir Grassland

Remote Sensing ◽

10.3390/rs13051044 ◽

2021 ◽

Vol 13 (5) ◽

pp. 1044

Author(s):

Jian Guo ◽

Xiuchun Yang ◽

Fan Chen ◽

Jianming Niu ◽

Sha Luo ◽

...

Keyword(s):

Future Research ◽

Spring Phenology ◽

Important Indicator ◽

Mechanism Model ◽

Partial Correlations ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

Heat Requirement ◽

Grassland Types

The accumulation of heat and moderate precipitation are the primary factors that are used by grasslands to trigger a green-up date. The accumulated growing degree-days (AGDD) requirement over the preseason is an important indicator of the response of grassland spring phenology to climate change. This study adopted the Normalized Difference Phenology Index (NDPI), which derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), to extract annual green-up dates in the Hulun Buir grassland in China between 2001–2015. Our analysis indicated that the range (standard deviation) and trend for the green-up date were DOY (day of year) 104 to DOY 144 (10.6 days) and −2.0 days per decade. Nine point two percent of the study area had significant (p < 0.05) changes in AGDD requirements. The partial correlations between the AGDD requirements and chilling days (67.04%, pixels proportion) were negative and significant (p < 0.05). The partial correlations between the AGDD requirement and precipitation (28.87%) were positive and significant (p < 0.05). Finally, the partial correlation between the AGDD requirement and insolation (97.65%) were positive and significant (p < 0.05). The results of this study could reveal the response of vegetation to climate warming and contribute to improving the phenological mechanism model of different grassland types in future research.

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