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基于判别分析的野生果树物种物候行为变异性

Variability of Phenological Behaviours of Wild Fruit Tree Species Based on Discriminant Analysis.

作者信息

Cosmulescu Sina, Ștefănescu Dragoș, Stoenescu Ana-Maria

机构信息

Department of Horticulture & Food Science, Horticulture Faculty, University of Craiova, A.I. Cuza Street 13, 200585 Craiova, Romania.

Department of Biology & Environmental Engineering, Horticulture Faculty, University of Craiova, A.I. Cuza Street 13, 200585 Craiova, Romania.

出版信息

Plants (Basel). 2021 Dec 24;11(1):45. doi: 10.3390/plants11010045.

Abstract

Vegetation phenology is considered an important biological indicator in understanding the behaviour of ecosystems and how it responds to environmental cues. The aim of this paper is to provide information on the variability of phenological behaviours based on discriminant analysis using the R software package with the following libraries: ggplot2, heplots, candisc, MASS, car, and klaR. Three phenological phases were analysed with eight wild fruit tree species from a forest ecosystem in the southwestern part of Romania (44°05'19.5" N 23°54'03.5" E). It was found that there is a large and very large variability for the "bud burst" phenophase, medium and low for "full flowering", and reduced for the "all petals fallen" phenophase. For the analyzed data, the discriminant analysis model has high accuracy (accuracy: 0.9583; 95% CI: (0.7888, 0.9989). Partition plots show the results of "full flowering" and "all petals fallen" as a function of the "bud burst" of pockmarks when separated into eight clusters and eight clusters of "full flowering" as a function of "all petals fallen". The differences observed, from a phenological point of view, are not only due to the different cold requirements of these species but also to the temperatures during the spring.

摘要

植被物候学被认为是理解生态系统行为及其对环境线索响应方式的重要生物学指标。本文旨在基于判别分析,使用R软件包及以下库(ggplot2、heplots、candisc、MASS、car和klaR)提供物候行为变异性的信息。对罗马尼亚西南部(北纬44°05'19.5",东经23°54'03.5")一个森林生态系统中的8种野生果树的三个物候阶段进行了分析。结果发现,“芽萌动”物候阶段的变异性很大和非常大,“盛花”阶段为中等和低变异性,“花瓣落尽”阶段的变异性则降低。对于所分析的数据,判别分析模型具有较高的准确性(准确率:0.9583;95%置信区间:(0.7888, 0.9989))。分区图展示了分为8个聚类时“盛花”和“花瓣落尽”作为麻点“芽萌动”函数的结果,以及8个“盛花”聚类作为“花瓣落尽”函数的结果。从物候学角度观察到的差异不仅归因于这些物种不同的低温需求,还归因于春季的温度。

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