Appalachian Lab, University of Maryland Center for Environmental Science, Frostburg, MD, 21532, USA.
W. K. Kellogg Biological Station, Michigan State University, Hickory Corners, MI, 49060, USA.
New Phytol. 2018 Oct;220(1):121-131. doi: 10.1111/nph.15270. Epub 2018 Jun 14.
While much research has focused on the timing of individual plant phenological events, the sequence of phenological events has received considerably less attention. Here we identify drivers and patterns of flower and leaf emergence sequence (FLS) in deciduous tree species of the Great Lakes region of North America. Five hypotheses related to cold tolerance, water dynamics, seed mass, pollination syndrome, and xylem anatomy type were compared for their ability to explain FLS. Phylogenetic and geographic patterns of FLS were also assessed. We identified additional traits associated with FLS using Random Forest models. Of the hypotheses assessed, those related to species' water dynamics and seed mass had the greatest support. The spatial pattern of FLS was found to be strongly related to minimum monthly temperature and the phylogenetic pattern was clustered among species. Based on results from Random Forest models, species' fruiting characteristics were found to be the most important variables in explaining FLS. Our results show that FLS is related to a suite of plant traits and environmental tolerances. We emphasize the need to expand phenological research to include both the timing and sequence of plant's entire phenology, in particular in relation to plant physiology and global change.
虽然许多研究都集中在单个植物物候事件的时间上,但物候事件的顺序却受到了相当少的关注。在这里,我们确定了北美的五大湖地区落叶树种的花和叶出现序列(FLS)的驱动因素和模式。比较了与耐寒性、水分动态、种子质量、授粉综合征和木质部解剖类型有关的五个假说,以确定它们解释 FLS 的能力。还评估了 FLS 的系统发育和地理模式。我们使用随机森林模型确定了与 FLS 相关的其他特征。在所评估的假设中,与物种水分动态和种子质量有关的假设得到了最大的支持。发现 FLS 的空间模式与最低月平均温度密切相关,系统发育模式在物种中聚类。基于随机森林模型的结果,发现物种的结实特征是解释 FLS 的最重要变量。我们的研究结果表明,FLS 与一系列植物特征和环境耐受性有关。我们强调需要扩展物候学研究,将植物整个物候的时间和顺序都包括在内,特别是与植物生理学和全球变化有关。