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Journal of Arid Land  2020, Vol. 12 Issue (5): 775-790    DOI: 10.1007/s40333-020-0059-9
Research article     
Impacts of snow on seed germination are independent of seed traits and plant ecological characteristics in a temperate desert of Central Asia
Anlifeire ANNIWAER1,2, SU Yangui1, ZHOU Xiaobing1, ZHANG Yuanming1,*()
1State Kay Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2University of Chinese Academy of Sciences, Beijing 100049, China
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Abstract  

Seed germination profoundly impacts plant community composition within the plant life cycle. Snow is an important source of water for seed germination in the temperate deserts of Central Asia. Understanding how seed germination responds to variations in snow cover in relation to seed traits and plant ecological characteristics can help predict plant community sustainability and stability in Central Asia under a scenario climate change. This study investigated the seed germination of 35 plant species common to the Gurbantunggut Desert in Central Asia under the three snow treatments: (1) snow addition; (2) ambient snow; and (3) snow removal. Two-way analysis of variance (ANOVA) tests were performed to assess interactions among the impacts of snow treatments, seed traits and plant ecological characteristics on seed germination. Phylogenetic generalized least-squares (PGLS) model was used to test the relationships between seed traits and seed germination. The results demonstrated that snow variations had no significant impacts on seed germination overall. Seed germination under the snow addition treatment was similar with that under the ambient snow treatment, irrespective of seed traits and plant ecological characteristics. Snow removal only had negative impacts on seed germination for certain groups of seed traits and plant ecological characteristics. Seed mass positively affected seed germination, showing a linear increase of arcsin square root-transformed seed germination with log-transformed seed mass. Seed shape also profoundly impacted seed germination, with a higher germination percentage for elongated and flat seeds. Seed germination differed under different plant life forms, with semi-shrub species showing a significantly higher germination percentage. Most importantly, although snow treatments, seed traits and plant ecological characteristics had no interactive effects on seed germination overall, some negative impacts from the snow removal treatment were detected when seeds were categorized on the basis of seed mass and shape. This result suggests that variations of snow cover may change plant community composition in this temperate desert due to their impacts on seed germination.



Key wordssnow cover      seed germination      seed traits      plant life form      Gurbantunggut Desert     
Received: 22 August 2019      Published: 10 September 2020
Corresponding Authors: Yuanming ZHANG     E-mail: zhangym@ms.xjb.ac.cn
About author: *Corresponding author: ZHANG Yuanming (E-mail: zhangym@ms.xjb.ac.cn)

The first and second authors contributed equally to this work.

Cite this article:

Anlifeire ANNIWAER, SU Yangui, ZHOU Xiaobing, ZHANG Yuanming. Impacts of snow on seed germination are independent of seed traits and plant ecological characteristics in a temperate desert of Central Asia. Journal of Arid Land, 2020, 12(5): 775-790.

URL:

http://jal.xjegi.com/10.1007/s40333-020-0059-9     OR     http://jal.xjegi.com/Y2020/V12/I5/775

Fig. 1 Phylogenetic position of the selected 35 species (a), seed mass (b), GP-1 (c1, c2 and c3) and GP-2 (d1, d2 and d3) under the snow addition (c1 and d1), ambient snow (c2 and d2) and snow removal (c3 and d3) treatments. Different color lines indicate different dispersal modes (red for anemochory, light blue for autochory, dark blue for barochory, green for ombrohydrochory, and pink for zoochory). GP-1 and GP-2 represent two forms of germination percentage (GP). GP-1 was calculated as field germinated seeds divided by the total number of experimental seeds and GP-2 was calculated as field germinated seeds divided by the sum of field germinated seeds and laboratory germinated seeds. We built the phylogenetic tree according to the study of Zanne et al. (2014).
Fig. 2 Comparison of volumetric soil water content (SWC; a) and soil temperature (b) in the surface 2 cm soil layer under the snow addition, ambient snow and snow removal treatments from October to April
Source of variation df GP-1 GP-2
F P F P
Snow 2 1.346 0.265 1.892 0.156
Snow×seed mass 10 0.157 0.998 0.392 0.947
Snow×seed shape 6 0.848 0.536 0.353 0.907
Snow×seed color 8 0.047 1.000 0.261 0.977
Snow×plant life form 6 0.291 0.967 0.111 0.999
Snow×plant ecotype 2 0.078 0.925 0.083 0.921
Table 1 Results of two-way analysis of variance (ANOVA) of snow in relation to seed traits (seed mass, shape and color) and plant ecological characteristics (plant life form and ecotype) on seed germination
Fig. 3 Linear relationships between log-transformed seed mass and arcsine square root-transformed GP-1 (a) and between log-transformed seed mass and arcsine square root-transformed GP-2 (b) under the snow addition, ambient snow and snow removal treatments. Slope differences among ambient snow, snow addition and snow removal treatments were analyzed by the two-way analysis of variance (ANCOVA) analysis.
Fig. 4 Seed germination percentage (GP) influenced by seed shape variance under the snow addition, ambient snow and snow removal treatments for GP-1 (a) and GP-2 (b). Different lowercase letters indicate significant differences among the three snow treatments within a level of seed shape variance at P<0.05 level; different uppercase letters indicate significant differences among different levels of seed shape variance within the same snow treatment at P<0.05 level.
Fig. 5 Seed GP influenced by seed color under the snow addition, ambient snow and snow removal treatments for GP-1 (a) and GP-2 (b). The number of replicates (n) is different among different colors of seeds, i.e., n=3 for white seeds, n=15 for yellow seeds, n=15 for green seeds, n=69 for brown seeds, and n=6 for black seeds. Different lowercase letters indicate significant differences among the three snow treatments within the same seed color at P<0.05 level; different uppercase letters indicate significant differences among different seed colors within the same snow treatment at P<0.05 level. Yellow color includes pale yellow or yellow; green color includes yellowish green or brownish green; brown color includes light yellowish brown, light reddish brown, brown, dark brown, yellowish brown or reddish brown.
Fig. 6 Seed GP influenced by plant life form under the snow addition, ambient snow and snow removal treatments for GP-1 (a) and GP-2 (b). Different lowercase letters indicate significant differences among the three snow treatments within the same plant life form at P<0.05 level; different uppercase letters indicate significant differences among different plant life forms within the same snow treatment at P<0.05.
Fig. 7 Seed GP influenced by plant ecotype under the snow addition, ambient snow and snow removal treatments for GP-1 (a) and GP-2 (b). Different lowercase letters indicate significant differences among the three snow treatments within the same plant ecotype at P<0.05 level; different uppercase letters indicate significant differences between the two plant ecotypes within the same snow treatment at P<0.05 level.
Fig. 8 Relationships of log-transformed seed mass with GP-1 (a-c) and GP-2 (d-f) described by the phylogenetic generalized least-squares (PGLS) models and generalized least-squares (GLS) models under the snow addition (a, d), ambient snow (b, e) and snow removal (c, f) treatments
Fig. 9 Relationships of seed shape variance with GP-1 (a-c) GP-2 (d-f) described by the PGLS models and GLS models under the snow addition (a, d), ambient snow (b, e) and snow removal (c, f) treatments
Response Y X Slope SD t P r λ
GP-1 Snow addition Seed mass (log10) 3.365 2.088 1.611 0.117 0.313 0.722
Ambient snow Seed mass (log10) 1.896 1.828 1.037 0.308 0.169 0.728
Snow removal Seed mass (log10) 1.544 1.313 1.175 0.248 0.201 0.940
GP-2 Snow addition Seed mass (log10) 2.960 66.212 0.044 0.964 -0.075 0.000
Ambient snow Seed mass (log10) 1.896 1.828 1.037 0.308 0.054 0.728
Snow removal Seed mass (log10) -4.683 3.800 -1.232 0.227 -0.253 0.000
GP-1 Snow addition Seed shape variance 15.863 34.576 0.458 0.649 0.063 0.612
Ambient snow Seed shape variance 17.239 29.495 0.584 0.563 0.071 0.709
Snow removal Seed shape variance 24.552 21.199 1.158 0.255 0.198 1.000
GP-2 Snow addition Seed shape variance 2.960 66.212 0.044 0.964 -0.048 0.000
Ambient snow Seed shape variance -4.870 60.795 -0.080 0.936 -0.030 0.000
Snow removal Seed shape variance -4.569 58.389 -0.078 0.938 0.152 0.000
Table 2 Results of the phylogenetic generalized least-squares (PGLS) models examining the impacts of seed traits (seed mass and seed shape variance) on GP (GP-1 and GP-2) under the snow addition, ambient snow and snow removal treatments
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