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Pattern change of the coastal wetland system and its dynamic impact on the habitat of red-crowned cranes in Yancheng， Jiangsu Province

  • role： First author第一作者
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：lijx@aircas.ac.cn
  • Introduction：李景霞，1995年生，女，硕士研究生，研究方向为资源与环境遥感。E-mail： lijx@aircas.ac.cn
LI Jingxia12,  
  • role： Corresponding author通信作者
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

  • Email：fubh@aircas.ac.cn
  • Introduction：付碧宏，1966年生，男，研究员，研究方向为资源与环境遥感。E-mail： fubh@aircas.ac.cn
FU Bihong1*

Resümee

The Yancheng coastal wetland in Jiangsu province, as a UNESCO (United Nations Educational, Scientific and Cultural Organization) natural heritage site with an area of 2687 km², is one of the most important habitats for the overwintering of red-crowned cranes in Asia. In recent decades, due to the combined effects of intensive human activities in sectors, such as industry, agriculture, aquaculture, and urbanization, the pattern of coastal wetland system and the suitable habitat for red-crowned cranes have changed dramatically. Therefore, the spatio-temporal variation pattern of coastal wetland system must be identified, and its key impact factors must be explored to protect the coastal wetland and conserve its biodiversity. Currently, research on land cover changes in the Yancheng coastal wetland is insufficient for species habitat monitoring. Thus, further study on the suitable habitat for red-crowned cranes in a long-term and large regional scale is warranted.In this study, multi-temporal and multi-source remote sensing data, such as Landsat TM/OLI data during 1989 to 2019 and Sentinel-2 data in 2019, were used to analyze the features of spatio-temporal variation in the Yancheng coastal wetland. First, the classification system and image interpretation symbols of the study area were established to draw the maps of classification and transfer distribution in six periods from 1989 to 2019. Then, the structural and functional connectivity of the suitable habitat for red-crowned cranes were evaluated on the basis of the species diffusion ability. Finally, the key ecological nodes for the overwintering of red-crowned cranes were evaluated.Results show that the eco-environment of natural wetland has degraded rapidly, with an area loss of 49.46%. Contrastingly, the artificial wetland increased by 69.24%, which was mainly realized by occupying the natural wetland and reclaiming the tidal flat. The center of reclamation tended to migrate from north to south and from coastal land to sea. The area of seepweed saltmarsh and alkaline land as suitable habitat decreased by 489.10 km², with a proportion decreased from 19.88% in 1989 to 4.36% in 2019. As for structural connectivity, our results reveal that the connectance index of suitable habitat patches decreased from 1.83 to 1.30, showing a downward trend. The distance between the patches increased and the fragmentation intensified. Concurrently, the estimations of functional connectivity index demonstrate that the integral and probability indexes of connectivity in 2019 are less than 0.01. The functional connectivity decreased, and the connection network was generally broken with only a small part of the connection network with high betweenness centrality index. They exist in the core area of UNESCO natural heritage site and the Tiaozini region. They are also the key ecological nodes for the habitat of red-crowned cranes.In summary, the connectivity of the suitable habitat for red-crowned cranes has decreased sharply because of land cover changes in the UNESCO natural heritage site—Yancheng coastal wetland in the past 30 years. However, the habitat for red-crowned cranes has been greatly improved since the core area has reverted aquaculture pond and cultivated land to natural wetland in 2014. In addition to enhancing the scientific conservation of the existing suitable habitat, such as the core area of UNESCO natural heritage site and Tiaozini region, the key ecological nodes in the natural wetland should be restored to improve the connectivity among the habitat patches.

Schlüsselwort

remote sensing application;coastal wetland;habitat for red-crowned cranes;UNESCO natural heritage site;multi-temporal remote sensing;landscape connectivity

References

  1. 1.
    Carrasco L, Vera P, Belda E J and Monrós J S. 2018. Combining remote sensing and field mapping methods to study the vegetation dynamics within a coastal wetland and determine the habitat effects of a threatened bird species (Emberiza schoeniclus witherbyi). Journal of Coastal Research, 34(1): 42-49
  2. 2.
    Chen L, Ren C Y, Wang C, Yao Y C and Song K S. 2017. Dynamic of coastal wetlands of the Yellow River Delta for 6 Periods. Wetland Science, 15(2): 179-186
  3. 3.
    Duan H L, Xia S X, Jackson M V, Zhao N, Liu Y, Teng J K, Meng Z, Yu X B and Shi J B. 2020. Identifying new sites of significance to waterbirds conservation and their habitat modification in the Yellow and Bohai Seas in China. Global Ecology and Conservation, 22: e01031
  4. 4.
    Gong N, Niu Z G, Qi W and Zhang H Y. 2016. Driving forces of wetland change in China. Journal of Remote Sensing, 20(2): 172-183
  5. 5.
    Han Q Q and Niu Z G. 2019. China intertidal zone dataset based on tidal correction. Journal of Global Change Data and Discovery, 3(1): 42-47
  6. 6.
    Han Q Q, Niu Z G, Wu M Q and Wang J W. 2019. Remote-sensing monitoring and analysis of China intertidal zone changes based on tidal correction. Chinese Science Bulletin, 64(4): 456-473
  7. 7.
    Li Y F and Liu H Y. 2014. Advance in wetland classification and wetland landscape classification researches. Wetland Science, 12(1): 102-108
  8. 8.
    Liao H J, Li G S, Wang S H, Cui L L and Ouyang N L. 2014. Evolution and spatial patterns of tidal wetland in North Jiangsu Province in the past 30 Years. Progress in Geography, 33(9): 1209-1217
  9. 9.
    Lin W P, Cen J W, Xu D, Du S Q and Gao J. 2018. Wetland landscape pattern changes over a period of rapid development (1985-2015) in the Zhoushan Islands of Zhejiang province, China. Estuarine, Coastal and Shelf Science, 213: 148-159.
  10. 10.
    Liu D W, Zhang Y L, Sun Y, Lü S C, Cheng H, Mu S J and Lu C H. 2016. Population dynamics and habitat selection of overwintering red-crowned cranes in coastal wetland of Yancheng, Jiangsu Province. Journal of Ecology and Rural Environment, 32(3): 473-477
  11. 11.
    Liu L, Liu H Y, Li Y F, Wang J and Xie F F. 2018. Dynamic changes in population size and habitat distribution of wintering red-crowned crane in northern Jiangsu Province. Acta Ecologica Sinica, 38(3): 926-933
  12. 12.
    Liu R H, Liang S C, Zhao H Y, Qi G C, Li L X, Jiang Y and Niu Z G. 2017. Progress of Chinese coastal wetland based on remote sensing. Remote Sensing Technology and Application, 32(6): 998-1011
  13. 13.
    Lu S C. 2008. Current distribution of red crown crane and its development trends in Yancheng Coastal Marshes. Ecological Science, 27(3): 154-158
  14. 14.
    Lu S L, Wu B F and Li F P. 2011. Wetland pattern change in Hai Basin. Journal of Remote Sensing, 15(2): 349-371
  15. 15.
    MacKinnon J, Verkuil Y I and Murray N. 2012. IUCN Situation Analysis on East and Southeast Asian Intertidal Habitats, with Particular Reference to the Yellow Sea (Including the Bohai Sea). Occasional Paper of the IUCN Species Survival Commission No. 47. IUCN: 5-8
  16. 16.
    Ou W X and Yuan W J. 2015. Priority of red-crowned crane wintering habitat patches using landscape connectivity in the Yancheng coastal wetland. Resources Science, 37(4): 823-831
  17. 17.
    Pang Q. 2014. Change of Red-Crowned Crane Habitat Connectivity and Recovery Based on Graph Theory in Yancheng Coastal Wetland. Nanjing: Nanjing Agricultural University
  18. 18.
    Pascual-Hortal L and Saura S. 2006. Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation. Landscape Ecology, 21(7): 959-967
  19. 19.
    Qin P, Zuo P and He Z X. 2004. Seashore Systems Ecology. Beijing: Chemical Industry Press: 2-11
  20. 20.
    Ren W Y, Wang C, Liu H Y, Li Y F, Zhou Y, Xu J Y and Chen H. 2019. Diversity of vegetation coverage based on birds’ habitat demand in the coastal wetland of Yancheng, Jiangsu Province. Chinese Journal of Ecology, 38(12): 3870-3877
  21. 21.
    Saura S and Pascual-Hortal L. 2007. A new habitat availability index to integrate connectivity in landscape conservation planning: comparison with existing indices and application to a case study. Landscape and Urban Planning, 83(2/3): 91-103
  22. 22.
    Su L Y and Zou H F. 2012. Status, threats and conservation needs for the continental population of the red-crowned crane. Chinese Birds, 3(3): 147-164
  23. 23.
    Suo A N, Guan D M, Sun Y G, Lin Y and Zhang M H. 2016. Advances in coastal landscape ecology and its role in the construction of marine ecological civilization. Acta Ecologica Sinica, 36(11): 3167-3175
  24. 24.
    UNESCO and World Heritage Committee. 2019. Decisions adopted during the 43rd session of the World Heritage Committee. Baku, Republic of Azerbaijan[EB/OL]. [2020-12-28].
  25. 25.
    Wen Q K, Zhang Z X, Xu J Y, Zuo L J, Wang X, Liu B, Zhao X L and Yi L. 2011. Spatial and temporal change of wetlands in Bohai rim during 2000-2008: An analysis based on satellite images. Journal of Remote Sensing, 15(1): 183-200
  26. 26.
    Wu C G, Zhou Z X, Wang P C, Xiao W F and Teng M J. 2010. The concept and measurement of landscape connectivity and its applications. Acta Ecologica Sinica, 30(7): 1903-1910
  27. 27.
    Wu J G. 2007. Landscape Ecology: Pattern, Process, Scale and Hierarchy. 2nd ed. Beijing: Higher Education Press: 102-121
  28. 28.
    Wu Y Q, Xiao X M, Chen B Q, Wang X X and Li X P. 2018. Phenological remote sensing monitoring of salt marsh vegetation in Yancheng intertidal wetland in recent thirty years. Jiangsu Agricultural Sciences, 46(16): 264-270
  29. 29.
    Xie H W. 2014. The Construction of Ecological Networks Based on Natural Heritage Sites in Jiangsu Province. Nanjing: Nanjing Normal University
  30. 30.
    Yun C X and Jiang X W. 2002. Sustainable Development and Comprehensive Management of Coastal Zones. Beijing: Ocean Press
  31. 31.
    Zhang Y, Li L, Wu G S, Zhou Y, Qin S P and Wang X M. 2016. Analysis of landscape connectivity of the Yunnan snub-nosed monkeys (Rhinopithecus bieti) based on habitat patches. Acta Ecologica Sinica, 36(1): 51-58
  32. 32.
    Zhang Y N, Zhao Y Q, Chen H, Lv S C and Zuo P. 2018. Analysis on population change of red-crowned cranes in its wintering habitat Yancheng during 1983~2017. Sichuan Environment, 37(6): 154-159
  33. 33.
    Zhu C M, Zhang X and Huang Q H. 2018. Four decades of estuarine wetland changes in the yellow river delta based on Landsat observations between 1973 and 2013. Water, 10(7): 933
  34. 34.
    Zhu J F, Zhou Y, Wang S X, Wang L T, Liu W L, Li H T and Mei J J. 2019. Analysis of changes of Baiyangdian wetland from 1975 to 2018 based on remote sensing. National Remote Sensing Bulletin, 23(5): 971-986

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