SUN Jingkuan, CHI Yuan, FU Zhanyong, LI Tian, DONG Kaikai. Spatiotemporal Variation of Plant Diversity Under a Unique Estuarine Wetland Gradient System in the Yellow River Delta, China[J]. Chinese Geographical Science, 2020, 30(2): 217-232. doi: 10.1007/s11769-020-1109-0
Citation: SUN Jingkuan, CHI Yuan, FU Zhanyong, LI Tian, DONG Kaikai. Spatiotemporal Variation of Plant Diversity Under a Unique Estuarine Wetland Gradient System in the Yellow River Delta, China[J]. Chinese Geographical Science, 2020, 30(2): 217-232. doi: 10.1007/s11769-020-1109-0

Spatiotemporal Variation of Plant Diversity Under a Unique Estuarine Wetland Gradient System in the Yellow River Delta, China

doi: 10.1007/s11769-020-1109-0
Funds:

Under the auspices of the National Natural Science Foundation of China (No. 41871089), the Basic Scientific Fund for National Public Research Institutes of China (No. 2018Q07), the National Natural Science Foundation of China (No. 41971119), the Natural Science Foundation of Shandong Province (No. ZR2019MD024), Shandong Province University Youth Innovation Team(No. 2019KJD010)and the Open Research Fund Program of Shandong Provincial Key Laboratory of Eco-Environmental Science for Yellow River Delta (No. 2019KFJJ01)

  • Received Date: 2019-01-02
  • Multiple natural and human factors in estuarine wetlands result in complicated land surface characteristics with distinct spatial and temporal heterogeneities, thereby contributing to the difficulty in identifying spatiotemporal variations and influencing factors of plant diversity. A unique estuarine wetland gradient system (UEWGS) consisting of soil, vegetation, heat, distance, landscape, and anthropogenic gradients was established based on the ecological features of estuarine wetland through remote sensing and field investigation methods. It resolved the complicated land surface characteristics, covered all aspects of factors influencing plant diversity, and possessed distinct spatiotemporal heterogeneities. The Yellow River Delta, the largest estuarine wetland in the northern China, was selected as the study area to demonstrate UEWGS in four seasons in 2017. A total of 123 species were recorded with considerable seasonal difference. Phragmites australis, Suaeda salsa, and Tamarix chinensis were the dominant species, and crop species also played important roles. In single effect, all aspects of gradients exerted significant influences, yet only vegetation gradient possessed significant influences in all seasons. In comprehensive effect, soil, vegetation, heat, and distance gradients showed significant gross influences. Moisture content in soil gradient and net primary productivity in vegetation gradient possessed significant net influences in all seasons and can be considered as the main driving factor and indicator, respectively, of plant diversity. The results validated the significance of UEWGS in revealing the plant diversity spatiotemporal characteristics and influencing factors, and UEWGS possessed universal applicability in the spatiotemporal analysis of plant diversity in estuarine areas.

  • [1] Aragüés R, Medina E T, Zribi W et al., 2014. Soil salinization as a threat to the sustainability of deficit irrigation under present and expected climate change scenarios. Irrigation Science, 33(1):67-79. doi: 10.1007/s00271-014-0449-x
    [2] Arias M E, Wittmann F, Parolin P et al., 2018. Interactions between flooding and upland disturbance drives species diversity in large river floodplains. Hydrobiologia, 814(1):5-17. doi: 10.1007/s10750-016-2664-3
    [3] Austrheim G, 2002. Plant diversity patterns in semi-natural grasslands along an elevational gradient in Southern Norway. Plant Ecology, 161(2):193-205. doi: 10.1023/a:1020315718720
    [4] Barbier E B, Koch E W, Silliman B R et al., 2008. Coastal ecosystem-based management with nonlinear ecological functions and values. Science, 319(5861):321-323. doi: 10.1126/science.1150349
    [5] Bárcena J F, Gómez A G, García A et al., 2017. Quantifying and mapping the vulnerability of estuaries to point-source pollution using a multi-metric assessment:the Estuarine Vulnerability Index (EVI). Ecological Indicators, 76:159-169. doi: 10.1016/j.ecolind.2017.01.015
    [6] Bertoldi G, Notarnicola C, Leitinger G et al., 2010. Topographical and ecohydrological controls on land surface temperature in an alpine catchment. Ecohydrology, 3(2):189-204. doi: 10.1002/eco.129
    [7] Cassel F, Goorahoo D, Sharmasarkar S, 2015. Salinization and yield potential of a salt-laden Californian soil:an in situ geophysical analysis. Water, Air, & Soil Pollution, 226(12):422. doi: 10.1007/s11270-015-2682-1
    [8] Chen Jilong, Li Guosheng, Liao Huajun et al., 2017. Simulation of maximum light coversion efficiency for a Phragmites salt marsh in the Liaohe River estuarine wetland. Acta Ecologica Sinica, 37(7):2263-2273. (in Chinese)
    [9] Chen Lin, Ren Chunying, Zhang Bai et al., 2018. Spatiotemporal dynamics of coastal wetlands and reclamation in the Yangtze Estuary during past 50 years (1960s-2015). Chinese Geographical Science, 28(3):386-399. doi: 10.1007/s11769-017-0925-3
    [10] Chi Yuan, Shi Honghua, Wang Xiaoli et al., 2015. Spatial-temporal characteristics and impact factors of land surface temperature of five southern Islands of Miaodao Archipelago, Shandong, China. Chinese Journal of Ecology, 34(8):2309-2319. (in Chinese)
    [11] Chi Y, Shi H H, Wang X L et al., 2016. Impact factors identification of spatial heterogeneity of herbaceous plant diversity on five southern islands of Miaodao Archipelago in North China. Chinese Journal of Oceanology and Limnology, 34(5):937-951. doi: 10.1007/s00343-016-5111-4
    [12] Chi Y, Shi H H, Zheng W et al., 2018a. Spatiotemporal characteristics and ecological effects of the human interference index of the Yellow River Delta in the last 30 years. Ecological Indicators, 89:880-892. doi: 10.1016/j.ecolind.2017.12.025
    [13] Chi Y, Zheng W, Shi H H et al., 2018b. Spatial heterogeneity of estuarine wetland ecosystem health influenced by complex natural and anthropogenic factors. Science of the Total Environment, 634:1445-1462. doi: 10.1016/j.scitotenv.2018.04.085
    [14] Chi Yuan, Shi Honghua, Sun Jingkuan et al., 2018c. Spatio-temporal characteristics and main influencing factors of vegetation net primary productivity in the Yellow River Delta in recent 30 years. Acta Ecologica Sinica, 38(8):2683-2697. (in Chinese)
    [15] Chi Y, Shi H H, Zheng W et al., 2018d. Simulating spatial distribution of coastal soil carbon content using a comprehensive land surface factor system based on remote sensing. Science of the Total Environment, 628-629:384-399. doi: 10.1016/j.scitotenv.2018.02.052
    [16] Chust G, Albaina A, Aranburu A et al., 2013. Connectivity, neutral theories and the assessment of species vulnerability to global change in temperate estuaries. Estuarine, Coastal and Shelf Science, 131:52-63. doi: 10.1016/j.ecss.2013.08.005
    [17] Connell J H, 1979. Intermediate-disturbance hypothesis. Science, 204(4399):1345. doi: 10.1126/science.204.4399.1345
    [18] Cook E A, 2002. Landscape structure indices for assessing urban ecological networks. Landscape and Urban Planning, 58(2-4):269-280. doi: 10.1016/s0169-2046(01)00226-2
    [19] Cui B L, Li X Y, 2011. Coastline change of the Yellow River estuary and its response to the sediment and runoff (1976-2005). Geomorphology, 127(1-2):32-40. doi: 10.1016/j.geomorph.2010.12.001
    [20] Ding Wenhui, Jiang Junyan, Li Xiuzhen et al., 2015. Spatial distribution of species and influencing factors across salt marsh in southern Chongming Dongtan. Chinese Journal of Plant Ecology, 39(7):704-716. (in Chinese)
    [21] Du Q, Zhang C, Zhong Q C et al., 2011. Single-species versus mixed-species community:which one is better for shore stabilization. A case study of Chongming Island, China. Ecological Engineering, 37(3):444-452. doi: 10.1016/j.ecoleng.2010.11.010
    [22] Fan X, Pedroli B, Liu G et al., 2012. Soil salinity development in the Yellow River Delta in relation to groundwater dynamics. Land Degradation & Development, 23(2):175-189. doi: 10.1002/ldr.1071
    [23] Fang Jingyun, Wang Xiangping, Shen Zehao et al., 2009. Methods and protocols for plant community inventory. Biodiversity Science, 17(6):533-548. (in Chinese)
    [24] Filippi P, Cattle S R, Bishop T F A et al., 2018. Digital soil monitoring of top-and sub-soil pH with bivariate linear mixed models. Geoderma, 322:149-162. doi:10.1016/j.geoderma. 2018.02.033
    [25] Gao Y C, Wang J N, Guo S H et al., 2015. Effects of salinization and crude oil contamination on soil bacterial community structure in the Yellow River Delta region, China. Applied Soil Ecology, 86:165-173. doi: 10.1016/j.apsoil.2014.10.011
    [26] Hadria R, Benabdelouahab T, Mahyou H et al., 2018. Relationships between the three components of air temperature and remotely sensed land surface temperature of agricultural areas in morocco. International Journal of Remote Sensing, 39(2):356-373. doi: 10.1080/01431161.2017.1385108
    [27] He Y L, Li X Z, Craft C et al., 2011. Relationships between vegetation zonation and environmental factors in newly formed tidal marshes of the Yangtze River estuary. Wetlands Ecology and Management, 19(4):341-349. doi: 10.1007/s11273-011-9220-8
    [28] Hooper D U, Chapin III F S, Ewel J J et al., 2005. Effects of biodiversity on ecosystem functioning:a consensus of current knowledge. Ecological Monographs, 75(1):3-35. doi: 10.1890/04-0922
    [29] Huang B R, Ouyang Z Y, Zheng H et al., 2008. Construction of an eco-island:a case study of Chongming Island, China. Ocean & Coastal Management, 51(8-9):575-588. doi: 10.1016/j.ocecoaman.2008.06.007
    [30] Jiang Y, Kang M Y, Zhu Y et al., 2007. Plant biodiversity patterns on Helan Mountain, China. Acta Oecologica, 32(2):125-133. doi: 10.1016/j.actao.2006.12.003
    [31] Kong D X, Miao C Y, Borthwick A G L et al., 2015. Evolution of the Yellow River Delta and its relationship with runoff and sediment load from 1983 to 2011. Journal of Hydrology, 520:157-167. doi: 10.1016/j.jhydrol.2014.09.038
    [32] Li X, Zhou Y X, Zhang L P et al., 2014. Shoreline change of Chongming Dongtan and response to river sediment load:a remote sensing assessment. Journal of Hydrology, 511(4):432-442. doi: 10.1016/j.jhydrol.2014.02.013
    [33] Li X M, Zhou Y Y, Asrar G R et al., 2018. Creating a seamless 1 km resolution daily land surface temperature dataset for urban and surrounding areas in the conterminous United States. Remote Sensing of Environment, 206:84-97. doi: 10.1016/j.rse.2017.12.010
    [34] Ma Keping, 2013. Studies on biodiversity and ecosystem function via manipulation experiments. Biodiversity Science, 21(3):247-248. (in Chinese)
    [35] Mansur A V, Brondízio E S, Roy S et al., 2016. An assessment of urban vulnerability in the Amazon Delta and Estuary:a multi-criterion index of flood exposure, socio-economic conditions and infrastructure. Sustainability Science, 11(4):625-643. doi: 10.1007/s11625-016-0355-7
    [36] McKinney M L, 2008. Effects of urbanization on species richness:a review of plants and animals. Urban Ecosystems, 11(2):161-176. doi: 10.1007/s11252-007-0045-4
    [37] Michelsen O, McDevitt J E, Coelho C R V, 2014. A comparison of three methods to assess land use impacts on biodiversity in a case study of forestry plantations in New Zealand. The International Journal of Life Cycle Assessment, 19(6):1214-1225. doi: 10.1007/s11367-014-0742-1
    [38] Moffatt S F, McLachlan S M, Kenkel N C, 2004. Impacts of land use on riparian forest along an urban-rural gradient in southern Manitoba. Plant Ecology, 174(1):119-135. doi: 10.1023/B:VEGE.0000046055.27285.fd
    [39] Molino J F, Sabatier D, 2001. Tree diversity in tropical rain forests:a validation of the intermediate disturbance hypothesis. Science, 294(5547):1702-1704. doi: 10.1126/science.1060284
    [40] Oindo B O, Skidmore A K, 2002. Interannual variability of NDVI and species richness in Kenya. International Journal of Remote Sensing, 23(2):285-298. doi:10.1080/014311600100 14819
    [41] Prandle D, Lane A, 2015. Sensitivity of estuaries to sea level rise:vulnerability indices. Estuarine, Coastal and Shelf Science, 160:60-68. doi: 10.1016/j.ecss.2015.04.001
    [42] Qin Z H, Dall'Olmo G, Karnieli A et al., 2001. Derivation of split window algorithm and its sensitivity analysis for retrieving land surface temperature from NOAA-advanced very high resolution radiometer data. Journal of Geophysical Research:Atmospheres, 106(D19):22655-22670. doi: 10.1029/2000JD900452
    [43] Ramalho C E, Laliberté E, Poot P et al., 2014. Complex effects of fragmentation on remnant woodland plant communities of a rapidly urbanizing biodiversity hotspot. Ecology, 95(9):2466-2478. doi: 10.1890/13-1239.1
    [44] Strohbach M W, Haase D, 2012. Above-ground carbon storage by urban trees in Leipzig, Germany:analysis of patterns in a European city. Landscape and Urban Planning, 104(1):95-104. doi: 10.1016/j.landurbplan.2011.10.001
    [45] Sun Wen, 2013. The Main Community Types and Distribution of Chongming Island and Ecology and Landscape Coordination Assessment of its Plant Communities. Shanghai:East China Normal University. (in Chinese)
    [46] Tian B, Zhang L Q, Wang X R et al., 2010. Forecasting the effects of sea-level rise at Chongming Dongtan Nature Reserve in the Yangtze Delta, Shanghai, China. Ecological Engineering, 36(10):1383-1388. doi: 10.1016/j.ecoleng.2010.06.016
    [47] Tilman D, Reich P B, Knops J M H, 2006. Biodiversity and ecosystem stability in a decade-long grassland experiment. Nature, 441(7093):629-632. doi: 10.1038/nature04742
    [48] Urqueta H, Jódar J, Herrera C et al., 2018. Land surface temperature as an indicator of the unsaturated zone thickness:a remote sensing approach in the Atacama Desert. Science of the Total Environment, 612:1234-1248. doi: 10.1016/j.scitotenv.2017.08.305
    [49] Wang R, Gamon J A, Montgomery R A et al., 2016. Seasonal variation in the NDVI-species richness relationship in a prairie grassland experiment (Cedar Creek). Remote Sensing, 8(2):128. doi: 10.3390/rs8020128
    [50] Wang Y G, Deng C Y, Liu Y et al., 2018. Identifying change in spatial accumulation of soil salinity in an inland river watershed, China. Science of the Total Environment, 621:177-185. doi 10.1016/j.scitotenv.2017.11.222
    [51] Wang Yihan, Zhou Demin, Sun Yonghua, 2011. Assessment of the ecological health of wetlands in Honghe supported by RS and GIS techniques. Acta Ecologica Sinica, 31(13):3590-3600. (in Chinese)
    [52] Watt C A, Scrosati R A, 2013. Bioengineer effects on understory species richness, diversity, and composition change along an environmental stress gradient:experimental and mensurative evidence. Estuarine, Coastal and Shelf Science, 123:10-18. doi: 10.1016/j.ecss.2013.02.006
    [53] Xing G P, Wang H J, Yang Z S et al., 2016. Spatial and temporal variation in erosion and accumulation of the subaqueous Yellow River Delta (1976-2004). Journal of Coastal Research, 74:32-47. doi: 10.2112/SI74-004.1
    [54] Xue L, Li X Z, Yan Z Z et al., 2017. Native and non-native halophytes resiliency against sea-level rise and saltwater intrusion. Hydrobiologia, 806(1):47-65. doi: 10.1007/s10750-017-3333-x
    [55] Yue T X, Liu J Y, Jørgensen S E et al., 2003. Landscape change detection of the newly created wetland in Yellow River Delta. Ecological Modelling, 164(1):21-31. doi: 10.1016/s0304-3800(02)00391-5
    [56] Zhang Jintun, 2004. Quantitative Ecology. Beijing:Science Press. (in Chinese)
    [57] Zhang Quanguo, Zhang Dayong, 2003. Biodiversity and ecosystem functioning:recent advances and trends. Biodiversity Science, 11(5):351-363. (in Chinese)
    [58] Zheng Jiangkun, Wei Tianxing, Zheng Lukun et al., 2009. Effects of landforms on α biodiversity in slope scale. Ecology and Environmental Sciences, 18(6):2254-2259. (in Chinese)
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Spatiotemporal Variation of Plant Diversity Under a Unique Estuarine Wetland Gradient System in the Yellow River Delta, China

doi: 10.1007/s11769-020-1109-0
Funds:

Under the auspices of the National Natural Science Foundation of China (No. 41871089), the Basic Scientific Fund for National Public Research Institutes of China (No. 2018Q07), the National Natural Science Foundation of China (No. 41971119), the Natural Science Foundation of Shandong Province (No. ZR2019MD024), Shandong Province University Youth Innovation Team(No. 2019KJD010)and the Open Research Fund Program of Shandong Provincial Key Laboratory of Eco-Environmental Science for Yellow River Delta (No. 2019KFJJ01)

Abstract: 

Multiple natural and human factors in estuarine wetlands result in complicated land surface characteristics with distinct spatial and temporal heterogeneities, thereby contributing to the difficulty in identifying spatiotemporal variations and influencing factors of plant diversity. A unique estuarine wetland gradient system (UEWGS) consisting of soil, vegetation, heat, distance, landscape, and anthropogenic gradients was established based on the ecological features of estuarine wetland through remote sensing and field investigation methods. It resolved the complicated land surface characteristics, covered all aspects of factors influencing plant diversity, and possessed distinct spatiotemporal heterogeneities. The Yellow River Delta, the largest estuarine wetland in the northern China, was selected as the study area to demonstrate UEWGS in four seasons in 2017. A total of 123 species were recorded with considerable seasonal difference. Phragmites australis, Suaeda salsa, and Tamarix chinensis were the dominant species, and crop species also played important roles. In single effect, all aspects of gradients exerted significant influences, yet only vegetation gradient possessed significant influences in all seasons. In comprehensive effect, soil, vegetation, heat, and distance gradients showed significant gross influences. Moisture content in soil gradient and net primary productivity in vegetation gradient possessed significant net influences in all seasons and can be considered as the main driving factor and indicator, respectively, of plant diversity. The results validated the significance of UEWGS in revealing the plant diversity spatiotemporal characteristics and influencing factors, and UEWGS possessed universal applicability in the spatiotemporal analysis of plant diversity in estuarine areas.

SUN Jingkuan, CHI Yuan, FU Zhanyong, LI Tian, DONG Kaikai. Spatiotemporal Variation of Plant Diversity Under a Unique Estuarine Wetland Gradient System in the Yellow River Delta, China[J]. Chinese Geographical Science, 2020, 30(2): 217-232. doi: 10.1007/s11769-020-1109-0
Citation: SUN Jingkuan, CHI Yuan, FU Zhanyong, LI Tian, DONG Kaikai. Spatiotemporal Variation of Plant Diversity Under a Unique Estuarine Wetland Gradient System in the Yellow River Delta, China[J]. Chinese Geographical Science, 2020, 30(2): 217-232. doi: 10.1007/s11769-020-1109-0
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