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Scientia Silvae Sinicae ›› 2020, Vol. 56 ›› Issue (4): 1-11.doi: 10.11707/j.1001-7488.20200401

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Dominant Climatic Factors Influencing the Geographical Distribution Pattern of Picea in China

Xiaowei Zhang1,2,Jingru Wang2,Minghao Wang2,Yi Yang2,Changming Zhao2   

  1. 1. Forestry College of Gansu Agricultural University Lanzhou 730070
    2. State Key Laboratory of Grassland Agro-Ecosystems School of Life Sciences of Lanzhou University Lanzhou 730000
  • Received:2018-05-07 Online:2020-04-25 Published:2020-05-26

Abstract:

Objective: In order to clarify the dominant climatic factors for the Picea (spruce) distributed along mountains of geographical steps in China,the relationship between climatic factors and geographical distribution of 12 species of Picea genus was analyzed. Methods: A total of 389 points of georeferenced data of 12 Picea species were collected from long-term field researches and Chinese Virtual Herbarium(CVH). Corresponding climatic variables were obtained from global climate data by the geographical information system software(ArcGIS). The climatic factors which restricted the distribution of Picea were determined through variance analysis and comparison of the coefficient of variation (CV). The contribution of climatic factors to the geographical divergence among Picea species were illuminated by linear regression,Monte Carlo permutation test and Redundancy analysis(RDA). Results: Annual mean temperature,monthly mean temperature difference between day and night,maximal temperature of warmest month,minimal temperature of coldest month,temperature annual range,annual precipitation,precipitation of warmest quarter,precipitation of coldest quarter and aridity index among the geographical distributions of the 12 tree species were significantly different. The percentage of variance of monthly mean temperature difference between day and night and precipitation of the coldest quarter were larger within each species' distribution,but other climatic factors showed larger percentage variance among each species' distribution. In terms of coefficient of variation (CV),the values of monthly mean temperature difference between day and night and maximal temperature of the warmest month were less than 20%,showing the lower values than the other climatic factors in distributions at both genus and species level. Latitude and longitude were significantly correlated with all corresponding climatic factors in geographical distributions of Picea species (P < 0.05),apart from mean diurnal temperature range along latitude and longitude,and the relationship between precipitation of coldest quarter and longitude. Among the correlation coefficients between latitude or longitude and each climatic factor,the highest value was exhibited in the annual range of temperature,followed by minimal temperature of coldest month. Further,Monte Carlo permutation test further showed that the annual range of temperature and minimal temperature of coldest month contributed to the geographical distribution by 84% and 66.8% respectively. RDA analysis revealed that the first principal component was mainly reflecting the thermal conditions due to annual range of temperature,maximal temperature of warmest month and min temperature of coldest month had higher loading values. Whereas annual precipitation,aridity index,and precipitation of warmest quarterhad higher loading values on the second principal component,which indicated environmental water conditions. These two principal components could cumulatively explaine 89.2% and 100% variance of species and of species-environment relation,respectively. Conclusion: Our research indicated that the monthly mean temperature difference between day and night and maximal temperature of the warmest month were the major climatic factors limiting the distribution of Picea,and temperature annual range and min temperature of coldest month were the key driving factors that influences each Picea species' geographic distribution in China. This study further confirmed that thermal conditions were likely the key factors that influence the distribution pattern of Picea species,followed by precipitation conditions.

Key words: Picea, climatic factor, latitude and longitude, geographical distribution pattern, limiting factor, driving factor

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