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资助项目
GST, p < 0.01). At the regional level, Chinese and Japanese L. hodgsonii had a similar estimate of genetic diversity (China: Hd = 0.847, HT = 0.869; Japan: Hd = 0.766, HT = 0.867). Populations from China and Japan possess unique sets of haplotypes, and no haplotypes were shared between the regions. Furthermore, both the phyloegenetic and network analyses recovered the haplotypes of China and Japan as two distinct clades. Thus, we suggested the disjunct distribution of L. hodgsonii in China and Japan may present the climatic vicariant relicts of the ancient widely distributed populations. After divergence, this species within each region experienced independent evolutionary process. In China, L. hodgsonii was distributed around the Sichuan Basin. This distribution range can be divided into five regions. They were Jiajin Mountain region, E’mei Mountain region, Yunnan-Guizhou Plateau region, Wushan-Wuling Mountain region and Qinling Mountain region. Twelve haplotypes were indentified within these regions. Each region had its own specific haplotypes, which had different ancestry in the network. We deduced that Chinese L. hodgsonii might survive the LGM in multiple isolated refugia around the Sichuan Basin. In Japan, L. hodgsonii was disjunctively distributed in northern Honshu and Hokkaido. Seven haplotypes were identified within this region. However, the genetic diversity in Honshu (Hd = 0.821) was much higher than that in Hokkaido (Hd = 0.513). And all haplotypes in Hokkaido were derived from Honshu. This haplotype distribution suggested that the northern Honshu could have served as refuge in Japan. Nested clade analysis (NCA) indicated multiple forces including the vicariance and long-distance dispersal affected the disjunctive distribution among populations of L. hodgsonii in Japan.2. The phylogeography of L. tongolensis，Ligularia tongolensis was distributed along the Jinshajiang watershed, Yalongjiang watershed and Wumeng Mountain. In order to deduce the demographic history of this species, we sequenced two chloroplast DNA (cpDNA) intergenic spacers (trnQ-5’rps16, trnL-rpl32) in 140 individuals from 14 populations of three groups (Jinshajiang vs. Yalongjiang vs. Wumeng) within this species range. High levels of haplotype diversity (Hd = 0.814) and total genetic diversity (HT = 0.862) were detected at the species level, based on a total oftwelve haplotypes identified. However, the intrapopulation diversity (HS = 0.349) was low, which led to the high levels of genetic divergence (GST = 0.595, NST = 0.614, FST = 0.597). In consideration of the speciation of L. tongolensis resulting from the uplifts of the Qinghai-Tibetan Plateau (QTP), we thought the present genetic structure of L. tongolensis was shaped by the fragmentation of ancestral populations during the courses of QTP uplifts. This was further supported by the absence of IBD tests (r = –0.291, p = 0.964), which suggest that the differentiation had not occurred in accordance with the isolation by distance model. The genetic differentiation in L. tongolensis appears to be associated with historical events. Meanwhile, H2 and H5, the dominant haplotypes that located on internal nodes and deviated from extinct ancestral haplotype in the network, were detected to be shared between Jinshajiang and Yalongjiang groups. We deduced that ancestral populations of this species might have had a continuous distribution range, which was then fragmented and isolated by the following tectonic events. Finally, the ancestral polymorphism, H2 and H5, were randomly allocated in Jinshajiang watershed and Yalongjiang watershed. Meanwhile, H5 was the dominant haplotype in Jinshajiang watershed; H7 was the domiant haplotype in Yalongjiang watershed and Wumeng Mountain. This haplotype distribution pattern indicated that each group might have served as a refuge for L. tongolensis during the Quaternary Glaciation. Postglacial demographic expansion was supported by unimodal mismatch distribution and star-like phylogenies, with expansion ages of 274 ka B. P. for this 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relationship between leaf physiognomy and climate is widely used to reconstruct paleoclimates of Cenozoic floras. Previous works demonstrate that LMA show regional constraints. Until now, no equation has been set up directly from Chinese forests. This relationship is exhaustively studied based on 50 samples from mesic to humid forests across China. Models including Leaf Margin Analysis (LMA), Single Linear regression for Precipitation, and Climate Leaf Analysis Multivariate Program (CLAMP), are set up and used to quantitatively reconstruct paleoclimates of Chinese Neogene floras. Meanwhile, a paleoflora, i.e., Yangjie flora, which belongs to the Upper Pliocene Sanying formation in West Yunnan Province, is studied. The species assemblage, paleoclimate and paleoecology of Yangjie flora are discussed. Conclusions in this dissertation are as following: 1. Chinese leaf physiognomy-climate models based on regression analyses，LMA is a widely used method that applies present-day linear correlation between the proportion of woody dicotyledonous species with untoothed leaves (P) and mean annual temperature (MAT) to estimate paleotemperatures from fossil leaf floras. The Chinese data indicate that P shows a strong linear correlation with MAT, but the actual relationship is slightly different from those recognized from other regions. Among all currently used LMA equations, the one resulting from North and Central American and Japanese data, rather than the widely used East Asian LMA equation, yields the closest values to the actual MATs of the Chinese samples (mean absolute error = 1.9°C). A new equation derived from the Chinese forests is therefore developed, where MAT = 1.038 + 27.6 × P. This study not only demonstrates the similarity of the relationship between P and MAT in the Northern Hemisphere, but also improves the reliability of LMA for paleoclimate reconstructions of Chinese paleofloras. Besides, regression analyses are used to explore the relationship between leaf physiognomy and precipitation. In contrast to former studies, entire leaf margin shows the highest correlation with the Growing Season Precipitation (GSP). A new equation is proposed: GSP = 228.0 + 1707.0 × P. 2. The new calibrated CLAMP dataset – PHYSGCHINA，CLAMP, which is based on canonical correspondence analysis, is improved by the inclusion of 50 Chinese samples. The result indicates that, new calibrated data from 50 Chinese sample sites are situated away from the former 144 samples in the physiognomic space, which may be caused by the unique characters of leaf physiognomy under monsoon condition. Therefore, a new calibrated CLAMP dataset, i.e., PHYSGCHINA, is set up based on 50 new Chinese samples, and 144 former samples from PHYSG3BRC. This new dataset could improve the accuracy of paleoclimate reconstructions for floras under the monsoon climate condition. When it is applied to Chinese Neogene floras, PHYSGCHINA could improve the accuracy of paleoclimate parameters, especially parameters related to precipitation. 3. Paleoclimate reconstructions of Chinese Cenozoic floras，Paleoclimates of Chinese Cenozoic floras are reconstructed using leaf physiognomy- climate models being set up in this study. The Chinese paleoclimate history in Eocene is similar to the trend from worldwide record. That is, hot climate presented in early Eocene and early Middle Eocene, and then, climate cooled down from late Middle Eocene to Late Eocene in China. Moreover, paleoclimates of two Late Miocene floras from Yunnan province, i.e., Xiaolongtan flora and Bangmai flora, are reconstructed using different models. The results indicate that, temperature of Yunnan is slightly higher than that in nowadays, but the precipitation is much higher than that at present day, which may be caused by the uplift of Hengduan Mountain. 4. Late Pliocene Yangjie flora in West Yunnan Province, China，A Late Pliocene Yangjie flora form Yongping County, western Yunnan province, which belongs to Sanying formation, is studied in this dissertation. Yangjie flora is dominated by Quercus sect. Heterobalanus (Oerst.) Menits. (evergreen sclerophyllous oaks), and this forest type is quite common in SW China at present. The discovery of Yangjie flora provides evidence that, vegetations of Yunnan in Miocene were dominated by evergreen forests, and the dominant families were Fabaceae, Fagaceae and Lauraceae. In Pliocene, this vegetation type changed gradually to evergreen sclerophyllous oak forests. This vegetation change may have been caused by the uplift of Hengduan Mountain in Neogene. A polypodiaceous fern, Drynaria callispora sp. nov., is described from the upper Pliocene Sanying Formation in western Yunnan Province, southwestern China. The species with well-preserved pinnae and in situ spores is the first convincing Drynaria fossil record. Detailed morphological investigation reveals that D. callispora is characterized by 1) pinnatifid fronds with entire-margined pinnae having straight or zigzag secondary veins; 2) finer venation showing void quadrangular areoles, but occasionally with one unbranched veinlet; 3) one row of circular sori on each side of the strong primary vein; and 4) in situ spores with verrucate exospores elliptical in polar view and bean-shaped in equatorial view. A morphological comparison shows that D. callispora is significantly different from all the fossil species previously identified as drynarioids. A phylogenetic analysis of D. callispora supports that the fossil is closely related to D. sinica Diels and D. mollis Bedd., two extant species distributing in the Himalayas. The discovery of the new fern indicates that the genus Drynaria became diversified in its modern distribution region no later than the late Pliocene and had retained the similar ecology to that of many modern drynarioid ferns ever since. 5. Paleoclimate reconstruction of Yangjie flora，LMA, Single Linear Regression for Precipitation and PHYSGCHINA are applied to reconstruct paleoclimate of Yangjie flora. MAT calculated by LMA and CLAMP is 22.0 ± 2.4°C and 20.0 ± 1.4°C, respectively, and GSP calculated by Single Linear Regression for Precipitation and PHYSGCHINA is 1521.9 ± 131.3 mm and 2084.7 ± 223.1 mm, respectively All methods agree that, both temperature and precipitation were higher in Late Pliocene than in nowadays. Meanwhile, precipitation parameters calculated by CLAMP gets high values. 6. Preliminary study of insect herbivory in Yangjie flora，Insect herbivory on leaves of Quercus preguyavaefolia Tao and Q. presenescens Zhou, two dominant species in Yangjie flora, is reported by the preliminary research. Each of these two species has a high diversity of insect damage. Among all damage types, margin feeding and surface feeding are most common, and skeletonization, piercing and sucking, and galling are less found. Most of these damage types belonge to the high host specialization (HS = 1). However, the proportion of leaves without insect damage in Q. presenescens is much higher than that in Q. preguyavaefolia. According to the log-log linear regression model, both Quercus preguyavaefolia and Q. presenescens have very high leaf mass per area (with 184.8 ± 6.7 g/m2 and 155.3 ± 10.7 g/m2, respectively). The high diversity of insect herbivory demonstrates a warm climate in the Late Pliocene of West Yunnan 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Plateau is one of the most sensitive areas to global climate change. The response of alpine ecosystem to climate change becomes a hot topic of scientific research. Plant phenology is best indicator of climate change. It will be meaningful to look at the response of alpine ecosystem to climate change from the plant phenology point of view. However, phenology research is still very weak on the Tibetan Plateau, and the ground observations are also very limited. Therefore, study on the growing season change and relation with temperature and precipitation will be scientifically and practically meaningful.In this study, we studied the interannual change of NDVI, temperature and precipitation and their correlation. Then the growing season on the Tibetan Plateau was simulated using both the slope method and NDVI ratio method. By comparing the results with ground observation, the NDVI ratio method with certain threshold was selected. Growing season from 1982-2006 was simulated with the selected method and then the spatial and temporal distribution of growing season was analyzed. Finally, we used multi-regression to derive the relation between growing season, temperature and precipitation. Some main conclusions were drawn from this study. NDVI ratio method performs better in simulating the growing season than slope method. The final thresholds selected for simulating the start and end dates of growing season are 0.2 and 0.6, respectively. Both the mean NDVI in May and June and beginning dates of growing season of meadow and steppe shows non-linear trend from 1982 to 2006. However, the beginning dates of growing season of meadow and steppe before 2000 display significant advance trend(0.48 d yr-1 and 0.62d yr-1,respectively), but delay after 2000；the end dats of meadow shows no significant trend during 1982 and 2000,but trend of the end dats of steppe is significant(0.52 d yr-1)；the lengths of growing season of meadow and steppe become longer before 2000(0.49d yr-1 and 0.55 d yr-1,respectively), then become shorter afterwards. Relation between temperature and precipitation with beginning dates of growing season is more significant than with end dates. The significantly rising temperature in winter delay the beginning dates of growing season because of the reduction of chilling requirement. Increase of spring temperature and precipitation promotes early beginning dates of growing season. The end dates of growing season are early due to the increase of temperature in July and August, but are late when temperature in September and precipitation from May to September increases.Finally, we figure out the shortcoming of the study and recommend possible way to solve the problem and more detailed future work is required.","jscount":"1","jsurl":"/simple-search?field1=all&field=eperson.unique.id&advanced=false&fq=location.comm.id%3A1&query1=Land%2BPlant&&fq=dc.project.title_filter%3ATibetan%5C+Plateau%5C+is%5C+one%5C+of%5C+the%5C+most%5C+sensitive%5C+areas%5C+to%5C+global%5C+climate%5C+change.%5C+The%5C+response%5C+of%5C+alpine%5C+ecosystem%5C+to%5C+climate%5C+change%5C+becomes%5C+a%5C+hot%5C+topic%5C+of%5C+scientific%5C+research.%5C+Plant%5C+phenology%5C+is%5C+best%5C+indicator%5C+of%5C+climate%5C+change.%5C+It%5C+will%5C+be%5C+meaningful%5C+to%5C+look%5C+at%5C+the%5C+response%5C+of%5C+alpine%5C+ecosystem%5C+to%5C+climate%5C+change%5C+from%5C+the%5C+plant%5C+phenology%5C+point%5C+of%5C+view.%5C+However%2C%5C+phenology%5C+research%5C+is%5C+still%5C+very%5C+weak%5C+on%5C+the%5C+Tibetan%5C+Plateau%2C%5C+and%5C+the%5C+ground%5C+observations%5C+are%5C+also%5C+very%5C+limited.%5C+Therefore%2C%5C+study%5C+on%5C+the%5C+growing%5C+season%5C+change%5C+and%5C+relation%5C+with%5C+temperature%5C+and%5C+precipitation%5C+will%5C+be%5C+scientifically%5C+and%5C+practically%5C+meaningful.In%5C+this%5C+study%2C%5C+we%5C+studied%5C+the%5C+interannual%5C+change%5C+of%5C+NDVI%2C%5C+temperature%5C+and%5C+precipitation%5C+and%5C+their%5C+correlation.%5C+Then%5C+the%5C+growing%5C+season%5C+on%5C+the%5C+Tibetan%5C+Plateau%5C+was%5C+simulated%5C+using%5C+both%5C+the%5C+slope%5C+method%5C+and%5C+NDVI%5C+ratio%5C+method.%5C+By%5C+comparing%5C+the%5C+results%5C+with%5C+ground%5C+observation%2C%5C+the%5C+NDVI%5C+ratio%5C+method%5C+with%5C+certain%5C+threshold%5C+was%5C+selected.%5C+Growing%5C+season%5C+from%5C+1982%5C-2006%5C+was%5C+simulated%5C+with%5C+the%5C+selected%5C+method%5C+and%5C+then%5C+the%5C+spatial%5C+and%5C+temporal%5C+distribution%5C+of%5C+growing%5C+season%5C+was%5C+analyzed.%5C+Finally%2C%5C+we%5C+used%5C+multi%5C-regression%5C+to%5C+derive%5C+the%5C+relation%5C+between%5C+growing%5C+season%2C%5C+temperature%5C+and%5C+precipitation.%5C+Some%5C+main%5C+conclusions%5C+were%5C+drawn%5C+from%5C+this%5C+study.%5C+NDVI%5C+ratio%5C+method%5C+performs%5C+better%5C+in%5C+simulating%5C+the%5C+growing%5C+season%5C+than%5C+slope%5C+method.%5C+The%5C+final%5C+thresholds%5C+selected%5C+for%5C+simulating%5C+the%5C+start%5C+and%5C+end%5C+dates%5C+of%5C+growing%5C+season%5C+are%5C+0.2%5C+and%5C+0.6%2C%5C+respectively.%5C+Both%5C+the%5C+mean%5C+NDVI%5C+in%5C+May%5C+and%5C+June%5C+and%5C+beginning%5C+dates%5C+of%5C+growing%5C+season%5C+of%5C+meadow%5C+and%5C+steppe%5C+shows%5C+non%5C-linear%5C+trend%5C+from%5C+1982%5C+to%5C+2006.%5C+However%2C%5C+the%5C+beginning%5C+dates%5C+of%5C+growing%5C+season%5C+of%5C+meadow%5C+and%5C+steppe%5C+before%5C+2000%5C+display%5C+significant%5C+advance%5C+trend%5C%280.48%5C+d%5C+yr%5C-1%5C+and%5C+0.62d%5C+yr%5C-1%2Crespectively%5C%29%2C%5C+but%5C+delay%5C+after%5C+2000%EF%BC%9Bthe%5C+end%5C+dats%5C+of%5C+meadow%5C+shows%5C+no%5C+significant%5C+trend%5C+during%5C+1982%5C+and%5C+2000%2Cbut%5C+trend%5C+of%5C+the%5C+end%5C+dats%5C+of%5C+steppe%5C+is%5C+significant%5C%280.52%5C+d%5C+yr%5C-1%5C%29%EF%BC%9Bthe%5C+lengths%5C+of%5C+growing%5C+season%5C+of%5C+meadow%5C+and%5C+steppe%5C+become%5C+longer%5C+before%5C+2000%5C%280.49d%5C+yr%5C-1%5C+and%5C+0.55%5C+d%5C+yr%5C-1%2Crespectively%5C%29%2C%5C+then%5C+become%5C+shorter%5C+afterwards.%5C+Relation%5C+between%5C+temperature%5C+and%5C+precipitation%5C+with%5C+beginning%5C+dates%5C+of%5C+growing%5C+season%5C+is%5C+more%5C+significant%5C+than%5C+with%5C+end%5C+dates.%5C+The%5C+significantly%5C+rising%5C+temperature%5C+in%5C+winter%5C+delay%5C+the%5C+beginning%5C+dates%5C+of%5C+growing%5C+season%5C+because%5C+of%5C+the%5C+reduction%5C+of%5C+chilling%5C+requirement.%5C+Increase%5C+of%5C+spring%5C+temperature%5C+and%5C+precipitation%5C+promotes%5C+early%5C+beginning%5C+dates%5C+of%5C+growing%5C+season.%5C+The%5C+end%5C+dates%5C+of%5C+growing%5C+season%5C+are%5C+early%5C+due%5C+to%5C+the%5C+increase%5C+of%5C+temperature%5C+in%5C+July%5C+and%5C+August%2C%5C+but%5C+are%5C+late%5C+when%5C+temperature%5C+in%5C+September%5C+and%5C+precipitation%5C+from%5C+May%5C+to%5C+September%5C+increases.Finally%2C%5C+we%5C+figure%5C+out%5C+the%5C+shortcoming%5C+of%5C+the%5C+study%5C+and%5C+recommend%5C+possible%5C+way%5C+to%5C+solve%5C+the%5C+problem%5C+and%5C+more%5C+detailed%5C+future%5C+work%5C+is%5C+required."},{"jsname":"lastIndexed","jscount":"2024-08-20"}],"资助项目","dc.project.title_filter")'>
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