Department of Physical Geography and Ecosystem Science, Lund University, Lund, SE-223 62, Sweden.
Glob Chang Biol. 2014 Nov;20(11):3492-507. doi: 10.1111/gcb.12593. Epub 2014 May 8.
Budburst models have mainly been developed to capture the processes of individual trees, and vary in their complexity and plant physiological realism. We evaluated how well eleven models capture the variation in budburst of birch and Norway spruce in Germany, Austria, the United Kingdom and Finland. The comparison was based on the models performance in relation to their underlying physiological assumptions with four different calibration schemes. The models were not able to accurately simulate the timing of budburst. In general the models overestimated the temperature effect, thereby the timing of budburst was simulated too early in the United Kingdom and too late in Finland. Among the better performing models were three models based on the growing degree day concept, with or without day length or chilling, and an empirical model based on spring temperatures. These models were also the models least influenced by the calibration data. For birch the best calibration scheme was based on multiple sites in either Germany or Europe, and for Norway spruce the best scheme included multiple sites in Germany or cold years of all sites. Most model and calibration combinations indicated greater bias with higher spring temperatures, mostly simulating earlier than observed budburst.
萌芽模型主要用于捕捉个体树木的生长过程,其复杂性和植物生理现实性存在差异。我们评估了十一个模型在德国、奥地利、英国和芬兰对桦树和挪威云杉萌芽变化的捕捉能力。该比较基于模型在四个不同的校准方案下与基础生理假设的关系表现。模型无法准确模拟萌芽的时间。总的来说,模型高估了温度的影响,因此在英国,萌芽的时间模拟得太早,而在芬兰则太晚。表现较好的模型包括三个基于生长度日概念的模型,其中包括或不包括日照时间或需冷量,以及一个基于春季温度的经验模型。这些模型也是受校准数据影响最小的模型。对于桦树,最好的校准方案是基于德国或欧洲的多个地点,而对于挪威云杉,最好的方案包括德国的多个地点或所有地点的寒冷年份。大多数模型和校准组合在较高的春季温度下显示出更大的偏差,主要是模拟比观察到的更早的萌芽。