Spatiotemporal Variation in Full-Flowering Dates of Tree Peonies in the Middle and Lower Reaches of China’s Yellow River: A Simulation through the Panel Data Model

Haolong Liu, Junhu Dai and Jun Liu
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Haolong Liu: Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
Junhu Dai: Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
Jun Liu: Tourism School, Sichuan University, 24 South Section 1 Ring Road No. 1, Chengdu 610065, China

Sustainability, 2017, vol. 9, issue 8, 1-12

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.

Keywords: tree peony; full-flowering date; panel data model; spatiotemporal variation; climate change; smarter tourism; decision-making information (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
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