Abstract
The spring flowering of tree peony (Paeonia suffruticosa) not only attract tens of million tourists every year, but it can also serve as a bio-indicator of climate change. Examining climate-associated spatiotemporal changes in peony flowering can contribute to the development of smarter flower-viewing tourism by providing more efficient decision-making information. We developed a panel data model for the tree peony to quantify the relationship between full-flowering date (FFD) and air temperature in the middle and lower reaches of China’s Yellow River. Then, on the basis of the model and temperature data, FFD series at 24 sites during 1955–2011 were reconstructed and the spatiotemporal variation in FFD over the region was analysed. Our results showed that the panel data model could well simulate the phenophase at the regional scale with due consideration paid to efficiency and difficulty, and the advance of peony FFD responded to the increase in February–April temperature at a rate of 3.02 days/1 °C. In addition, the simulation revealed that regional FFDs followed the latitudinal gradient and had advanced by 6–9 days over the past 57 years, at the rate of 0.8 to 1.8 days/decade. Among sub-areas, the eastern forelands of Taihang Mountains and Luliang Mountains showed more FFD advances than the other areas.
Highlights
Phenological events, which are independent of instrumental records, could serve as bioindicators of climate change [1,2]
Panel data models haven’t been widely applied in the phenological field, so we tried this new approach to peony full-flowering date (FFD)
Panel data models applied to econometric estimates can reduce the collinearity among expla4n.2a.tTohreyCvoanrsiiasbtelnecsy[o2f3R,2e4g]io. nTahl uPsh,entholeogpiacanleTlrdenadtas model should be expected to have more application in phenoTlohgeicaadlvsatnucdeidesF.FD trend of Zhongyuan Peony was largely consistent with spring phenological changes in other places
Summary
Phenological events, which are independent of instrumental records, could serve as bioindicators of climate change [1,2]. Similar conclusions were made in Chinese literature [6,7,8]. These studies provided insight into how future climate changes may manifest in biological systems. Among these studies, ornamental plants and economic plants in China have received a few attention (e.g., [9,10,11]). Most of related studies were still on local scales. By comparison, scaling phenology from the local to the regional level has been an international trend in oversea studies [12,13]. Further phenological investigations on the two kinds of plants in China are still necessary [14]
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