Prediction of suitable climatic areas for <i>Fortunella</i> species in China

ZHANG Yi; XUE Shuai; HUANG Hongmei; LI Dazhi; TANG Shuai; KONG Weizheng; YI Zili

doi:10.12357/cjea.20210416

Volume 29 Issue 11

Nov. 2021

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Article Navigation > Chinese Journal of Eco-Agriculture > 2021 > 29(11): 1838-1845

ZHANG Y, XUE S, HUANG H M, LI D Z, TANG S, KONG W Z, YI Z L. Prediction of suitable climatic areas for Fortunella species in China[J]. Chinese Journal of Eco-Agriculture, 2021, 29(11): 1838−1845 doi: 10.12357/cjea.20210416

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ZHANG Y, XUE S, HUANG H M, LI D Z, TANG S, KONG W Z, YI Z L. Prediction of suitable climatic areas for Fortunella species in China[J]. Chinese Journal of Eco-Agriculture, 2021, 29(11): 1838−1845 doi: 10.12357/cjea.20210416

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Prediction of suitable climatic areas for Fortunella species in China

doi: 10.12357/cjea.20210416

1.
College of Bioscience and Biotechnology, Hunan Agricultural University, Changsha 410128, China
2.
Horticulture and Landscape College, Hunan Agricultural University, Changsha 410128, China
3.
National Center for Citrus Improvement, Changsha 410128, China

Funds: This study was supported by the First Major Research Projects and the Cultivation Project of Innovation Teams of Hunan Agricultural University (17PYXM02)

More Information

Corresponding author: E-mail: yizili@hunau.net
Received Date: 2021-06-30
Accepted Date: 2021-09-26

Available Online: 2021-10-16

Publish Date: 2021-11-10

Abstract

Abstract

Fortunella is one group of the citrus fruit trees in southern China, a kind of edible hesperidium with rich flavonoids, carotenoids, limonoids, coumarins, and the fruit of these evergreen trees also have ornamental value. In recent years, areas of growth of commercial species of Fortunella have been decreasing due to a low net interest of planting single species. Meanwhile, natural resources have also withered due to the Huanglong disease caused by gram-negative bacteria. National collection of germplasm resources of Fortunella has been completed in parts of China, including Hunan, Fujian, Guangxi, etc.; however, this work did not take the effects of climatic factors on their distribution into consideration, which could provide a scientific basis for protection and collection of natural resources of Fortunella species. In this study, we predicted suitable climatic areas for six species (F. hindsii Swingle, F. margarita Swingle, F. japonica Swingle, F. polyandra Tanaka, F. crassifolia Swingle, and F. obovata Tanaka) of Fortunella using the MaxEnt (the maximum entropy, MaxEnt 3.3.3) model and the ArcGIS (the geographic information, ArcGIS 10.3) system to analyze actual geographical distribution data and 18 climate factors affecting their distribution. The dominant climate factors were screened through Jackknife test. Results showed that the suitable climatic region for the six species analyzed were distributed mainly in the southern areas of Dabie—Daba Mountain. The suitable region for the six species covered 354 000 km² (F. hindsii Swingle), 276 100 km² (F. margarita Swingle), 495 800 km² (F. japonica Swingle), 613 600 km² (F. polyandra Tanaka), 474 400 km² (F. crassifolia Swingle), and 663 403 km² (F. obovata Tanaka). The optimum climate region for F. polyandra Tanaka mainly extended to Chongqing, Guangxi, Guangdong, Hainan, and south of Yunnan, while that for the other five species was predominantly distributed in Hunan, Jiangxi, Guangxi, Fujian, Zhejiang, and Guangdong; some favorable region for F. obovata Tanaka even extended to Chongqing. The main climatic factors affecting the growth of Fortunella include minimum temperature, precipitation, and isothermality. The major climatic factors affecting F. hindsii Swingle distribution included isothermality and precipitation in April and June, while for F. margarita Swingle such climatic factors comprised precipitation in April and June, minimum temperature in February and July, and isothermality and precipitation in the driest month. Similarly, geographical distribution of F. japonica Swingle was influenced by precipitation in April and June, minimum temperature in July, isothermality and precipitation in the driest month, and precipitation in the warmest quarter. Likewise, the major climatic factors affecting natural distribution of F. polyandra Tanaka comprised precipitation in July and in December, minimum temperature in February and June, isothermality, and mean precipitation in the warmest quarter. Similar analytical results demonstrated that the dominant climatic factors affecting the distribution of both F. crassifolia Swingle and F. obovata Tanaka were in terms of precipitation in June, and isothermality and mean precipitation of the warmest quarter. The area under the curve (AUC) value of the MaxEnt model for all six species exceeded 0.9 and their actual distribution areas were also integrated, which indicated that the predicted distribution range of this study was highly accurate. Consequently, these results are expected to provide scientific guidance for regional investigation and protection of wild species of Fortunella and promotion of its varieties.
- Fortunella,
- MaxEnt Model,
- Climatic suitable areas,
- Dominant climatic factors

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References(28)

References

[1]	SWINGLE W T, TEECE P C. The botany and citrus and its wild relatives[J]. Citrus Industry, 1967, 1: 190−430
[2]	叶荫民. 中国金柑种质资源[J]. 作物品种资源, 1983, (4): 2−5 YE Y M. Germplasm resources of Fortunella in China[J]. China Seed Industry, 1983, (4): 2−5
[3]	LOU S N, LAI Y C, HUANG J D, et al. Drying effect on flavonoid composition and antioxidant activity of immature kumquat[J]. Food Chemistry, 2015, 171: 356−363 doi: 10.1016/j.foodchem.2014.08.119
[4]	ZHANG J C, TAO N G, XU Q, et al. Functional characterization of Citrus PSY gene in Hongkong kumquat (Fortunella hindsii Swingle)[J]. Plant Cell Reports, 2009, 28(11): 1737−1746 doi: 10.1007/s00299-009-0774-3
[5]	林大盛, 吴方崇. 我国金柑分布和种类[J]. 中国柑桔, 1987, 16(1): 3−5 LIN D S, WU F C. Distribution and species of Fortunlla in China[J]. South China Fruits, 1987, 16(1): 3−5
[6]	REINKING O A. Diseases of economic plants in southern China[J]. Philippine Agriculturist, 1919, 8: 109−135
[7]	KUMAR S, JENA S N, NAIR N K. ISSR polymorphism in Indian wild orange (Citrus indica Tanaka, Rutaceae) and related wild species in Northeast India[J]. Scientia Horticulturae, 2010, 123(3): 350−359 doi: 10.1016/j.scienta.2009.10.008
[8]	崔德珍. 湖南省金柑种质资源的初步研究[J]. 湖南农学院学报, 1987, 13(4): 29−35 CUI D Z. A preliminary study on kumquat (Fortunella) germplasm resources in Hunan[J]. Journal of Hunan Agricultural University, 1987, 13(4): 29−35
[9]	黄新忠, 雷龑, 陈小明, 等. 福建山橘、金豆野生资源调查与分析[J]. 植物遗传资源学报, 2010, 11(4): 509−513 HUANG X Z, LEI Y, CHEN X M, et al. Investigation and analysis of wild Fortunella hindsii and Fortunella venosa resources in Fujian[J]. Journal of Plant Genetic Resources, 2010, 11(4): 509−513
[10]	王运生, 谢丙炎, 万方浩, 等. ROC曲线分析在评价入侵物种分布模型中的应用[J]. 生物多样性, 2007, 15(4): 365−372 doi: 10.3321/j.issn:1005-0094.2007.04.005 WANG Y S, XIE B Y, WAN F H, et al. Application of ROC curve analysis in evaluating the performance of alien species’ potential distribution models[J]. Biodiversity Science, 2007, 15(4): 365−372 doi: 10.3321/j.issn:1005-0094.2007.04.005
[11]	ELITH J, GRAHAM C H, ANDERSON R P, et al. Novel methods improve prediction of species’ distributions from occurrence data[J]. Ecography, 2006, 29(2): 129−151 doi: 10.1111/j.2006.0906-7590.04596.x
[12]	PEARSON R G, RAXWORTHY C J, NAKAMURA M, et al. Original article: predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar[J]. Journal of Biogeography, 2006, 34(1): 102−117 doi: 10.1111/j.1365-2699.2006.01594.x
[13]	CAO B, BAI C K, ZHANG L L, et al. Modeling habitat distribution of Cornus officinalis with Maxent modeling and fuzzy logics in China[J]. Journal of Plant Ecology, 2016, 9(6): 742−751 doi: 10.1093/jpe/rtw009
[14]	王茹琳, 李庆, 何仕松, 等. 中华猕猴桃在中国潜在分布及其对气候变化响应的研究[J]. 中国生态农业学报, 2018, 26(1): 27−37 WANG R L, LI Q, HE S S, et al. Potential distribution of Actinidia chinensis in China and its predicted response to climate change[J]. Chinese Journal of Eco-Agriculture, 2018, 26(1): 27−37
[15]	CHEJARA V K, KRITICOS D J, KRISTIANSEN P, et al. The current and future potential geographical distribution of Hyparrhenia hirta[J]. Weed Research, 2010, 50(2): 174−184 doi: 10.1111/j.1365-3180.2010.00765.x
[16]	MA B B, SUN J. Predicting the distribution of Stipa purpurea across the Tibetan Plateau via the MaxEnt model[J]. BMC Ecology, 2018, 18(1): 10 doi: 10.1186/s12898-018-0165-0
[17]	李颖, 姜小龙, 邓敏, 等. 乌冈栎的潜在分布模拟及分析[J]. 生态学杂志, 2017, 36(10): 2971−2978 LI Y, JIANG X L, DENG M, et al. Potential distribution modeling and analysis of Quercus phillyraeoides[J]. Chinese Journal of Ecology, 2017, 36(10): 2971−2978
[18]	YANG X Q, KUSHWAHA S P S, SARAN S, et al. Maxent modeling for predicting the potential distribution of medicinal plant, Justicia adhatoda L. in lesser Himalayan foothills[J]. Ecological Engineering, 2013, 51: 83−87 doi: 10.1016/j.ecoleng.2012.12.004
[19]	吴建国, 周巧富. 中国嵩草属植物地理分布模式和适应的气候特征[J]. 植物生态学报, 2012, 36(3): 199−221 doi: 10.3724/SP.J.1258.2012.00199 WU J G, ZHOU Q F. Geographical distribution pattern and climate characteristics of adaptation for Kobresia in China[J]. Chinese Journal of Plant Ecology, 2012, 36(3): 199−221 doi: 10.3724/SP.J.1258.2012.00199
[20]	PEARCE J, FERRIER S. Evaluating the predictive performance of habitat models developed using logistic regression[J]. Ecological Modelling, 2000, 133(3): 225−245 doi: 10.1016/S0304-3800(00)00322-7
[21]	ELITH J, PHILLIPS S J, HASTIE T, et al. A statistical explanation of MaxEnt for ecologists[J]. Diversity and Distributions, 2011, 17(1): 43−57 doi: 10.1111/j.1472-4642.2010.00725.x
[22]	朱耿平, 乔慧捷. Maxent模型复杂度对物种潜在分布区预测的影响[J]. 生物多样性, 2016, 24(10): 1189−1196 doi: 10.17520/biods.2016265 ZHU G P, QIAO H J. Effect of the Maxent model’ complexity on the prediction of species potential distributions[J]. Biodiversity Science, 2016, 24(10): 1189−1196 doi: 10.17520/biods.2016265
[23]	MORENO R, ZAMORA R, MOLINA J R, et al. Predictive modeling of microhabitats for endemic birds in south Chilean temperate forests using maximum entropy (Maxent)[J]. Ecological Informatics, 2011, 6(6): 364−370 doi: 10.1016/j.ecoinf.2011.07.003
[24]	MUSCARELLA R, GALANTE P J, SOLEY-GUARDIA M, et al. ENMeval: an R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models[J]. Methods in Ecology and Evolution, 2014, 5(11): 1198−1205 doi: 10.1111/2041-210X.12261
[25]	WALTHER G R, POST E, CONVEY P, et al. Ecological responses to recent climate change[J]. Nature, 2002, 416(6879): 389−395 doi: 10.1038/416389a
[26]	苗平生. 长叶金柑[J]. 果树科学, 1990, 7(4): 238−239 MIAO P S. Fortunella polyandra Tanaka[J]. Journal of Fruit Science, 1990, 7(4): 238−239
[27]	PHILLIPS S J, ANDERSON R P, SCHAPIRE R E. Maximum entropy modeling of species geographic distributions[J]. Ecological Modelling, 2006, 190(3/4): 231−259
[28]	祁春节. 中国柑橘产业的经济分析与政策研究[D]. 武汉: 华中农业大学, 2001 QI C J. The citrus industry in China: An economic analysis and policy studies[D]. Wuhan: Huazhong Agricultural University, 2001