New insights on plant phenological response to temperature revealed from long‐term widespread observations in China. (19th December 2017)

• Record Type: Journal Article
• Authors: Zhang, Haicheng; Liu, Shuguang; Regnier, Pierre; Yuan, Wenping
• Is Part Of: Global change biology. Volume 24:Number 5(2018)
• Page Start: 2066
• Page End: 2078
• Publication Date: 2017-12-19
• Subjects: growing degree day -- leaf onset date -- phenology model -- plant phenology -- terrestrial biosphere model -- winter chilling; Climatic changes -- Environmental aspects -- Periodicals; Troposphere -- Environmental aspects -- Periodicals; Biodiversity conservation -- Periodicals; Eutrophication -- Periodicals; 551.5
• DOI: 10.1111/gcb.14002
• Languages: English
• ISSNs: 1354-1013

Abstract

Abstract: Constraints of temperature on spring plant phenology are closely related to plant growth, vegetation dynamics, and ecosystem carbon cycle. However, the effects of temperature on leaf onset, especially for winter chilling, are still not well understood. Using long‐term, widespread in situ phenology observations collected over China for multiple plant species, this study analyzes the quantitative response of leaf onset to temperature, and compares empirical findings with existing theories and modeling approaches, as implemented in 18 phenology algorithms. Results show that the growing degree days (GDD) required for leaf onset vary distinctly among plant species and geographical locations as well as at organizational levels (species and community), pointing to diverse adaptation strategies. Chilling durations (CHD) needed for releasing bud dormancy decline monotonously from cold to warm areas with very limited interspecies variations. Results also reveal that winter chilling is a crucial component of phenology models, and its effect is better captured with an index that accounts for the inhomogeneous effectiveness of low temperature to chilling rate than with the conventional CHD index. The impact of spring warming on leaf onset is nonlinear, better represented by a logistical function of temperature than by the linear function currently implemented in biosphere models. The optimized base temperatures for thermal accumulation and the optimal chilling temperatures are species‐dependent and average at 6.9 and 0.2°C, respectively. Overall, plants' chilling requirement is not a constant, and more chilling generally results in less requirement of thermal accumulation for leaf onset. Our results clearly demonstrate multiple deficiencies of the parameters (e.g., base temperature) and algorithms (e.g., method for calculating GDD) in conventional phenology models to represent leaf onset. Therefore, this study not only advances our mechanistic and quantitative understanding of temperature controls on leaf onset but also provides critical information for improving existing phenology models. Abstract : The performance of the 18 phenology models (Table 2) with optimized parameters were evaluated and compared based on the Root mean square error (RMSE) and Akaike Information Criterion (AIC) in predicted LOD. Statistics on the 24 plant species reveal that broadly consistent results are obtained across the 18 phenology models for both criterions. All models with a calibrated base temperature (Tb) lead to a lower AIC than those with a fixed Tb of 0 °C (compare F2, S2, P2, A2 and Ar2 to F1, S1, P1, A1 and Ar1, respectively), while models with a chilling rate constrained according to Rc2 (Table 1) further reduces the AIC (S3, P3, A3 and Ar3). In addition, parallel and revised alternating models relying on Rf2 to constrain the forcing rate have lower AICs than Rf1 ‐based models (compare P4 and Ar4 to P3 and Ar3, respectively). The opposite is true for sequential and alternating models, which are characterized by higher AICs when the Rf2 formulation is used (compare S4 and A4 to S3 and A3, respectively). Furthermore, the lowest RMSE and lowest AIC is obtained for model Ar4.