Tidal and Meteorological Influences on the Growth of Invasive Spartina alterniflora: Evidence from UAV Remote Sensing

被引:65
作者
Zhu, Xudong [1 ]
Meng, Lingxuan [1 ]
Zhang, Yihui [1 ]
Weng, Qihao [2 ]
Morris, James [1 ,3 ,4 ]
机构
[1] Xiamen Univ, Key Lab Coastal & Wetland Ecosyst, Minist Educ, Coastal & Ocean Management Inst,Coll Environm &, Xiamen 361102, Fujian, Peoples R China
[2] Indiana State Univ, Ctr Urban & Environm Change, Dept Earth & Environm Syst, Terre Haute, IN 47809 USA
[3] Univ South Carolina, Baruch Inst, Columbia, SC 29208 USA
[4] Univ South Carolina, Dept Biol Sci, Columbia, SC 29208 USA
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
unmanned aerial vehicle; LiDAR; Spartina alterniflora; biological invasion; coastal wetland; tidal inundation; lateral expansion; greenness index; CORDGRASS SPARTINA; PLANT-COMMUNITIES; SMOOTH CORDGRASS; LIDAR DATA; MANGROVE; INUNDATION; CHINA; RECRUITMENT; PHENOLOGY; RESPONSES;
D O I
10.3390/rs11101208
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Rapid invasion of Spartina alterniflora into Chinese coastal wetlands has attracted much attention. Many field and remote sensing studies have examined the spatio-temporal dynamics of S. alterniflora invasion; however, spatially explicit quantitative analyses of S. alterniflora invasion and its underlying mechanisms at both patch and landscape scales are seldom reported. To fill this knowledge gap, we integrated multi-temporal unmanned aerial vehicle (UAV) imagery, light detection and ranging (LiDAR)-derived elevation data, and tidal and meteorological time series to explore the growth potential (lateral expansion rates and canopy greenness) of S. alterniflora over the intertidal zone in a subtropical coastal wetland (Zhangjiang estuarine wetland, Fujian, China). Our analyses of patch expansion indicated that isolated S. alterniflora patches in this wetland experienced high lateral expansion over the past several years (averaged at 4.28 m/year in patch diameter during 2014-2017), and lateral expansion rates (y, m/year) showed a statistically significant declining trend with increasing inundation (x, h/day; 3 <= x <= 18): y=-0.17x+5.91, R2=0.78. Our analyses of canopy greenness showed that the seasonality of the growth potential of S. alterniflora was driven by temperature (Pearson correlation coefficient r=0.76) and precipitation (r=0.68), with the growth potential peaking in early/middle summer with high temperature and adequate precipitation. Together, we concluded that the growth potential of S. alterniflora was co-regulated by tidal and meteorological regimes, in which spatial heterogeneity is controlled by tidal inundation while temporal variation is controlled by both temperature and precipitation. To the best of our knowledge, this is the first spatially explicit quantitative study to examine the influences of tidal and meteorological regimes on both spatial heterogeneity (over the intertidal zone) and temporal variation (intra- and inter-annual) of S. alterniflora at both patch and landscape scales. These findings could serve critical empirical evidence to help answer how coastal salt marshes respond to climate change and assess the vulnerability and resilience of coastal salt marshes to rising sea level. Our UAV-based methodology could be applied to many types of plant community distributions.
引用
收藏
页数:17
相关论文
共 50 条
  • [31] BUILDING EXTRACTION FROM UAV REMOTE SENSING DATA BASED ON PHOTOGRAMMETRY METHOD
    Fan, Xiwei
    Nie, Gaozhong
    Gao, Na
    Deng, Yan
    An, Jiwen
    Li, Huayue
    2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 3317 - 3320
  • [32] Capacity Estimation of Irrigation Tanks Through Remote Sensing From UAV Platform
    Bharath Kumar Reddy Kadapala
    K. Abdul Hakeem
    K. Raghavendra
    Shivi Patel
    K. Pramod Kumar
    Journal of the Indian Society of Remote Sensing, 2020, 48 : 1403 - 1411
  • [33] Extraction of cotton seedling growth information using UAV visible light remote sensing images
    Dai J.
    Xue J.
    Zhao Q.
    Wang Q.
    Chen B.
    Zhang G.
    Jiang N.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2020, 36 (04): : 63 - 71
  • [34] Analysis of Jiangsu tidal flats reclamation from 1974 to 2012 using remote sensing
    Zhao Sai-shuai
    Liu Yong-xue
    Li Man-chun
    Sun Chao
    Zhou Min-xi
    Zhang He-xia
    CHINA OCEAN ENGINEERING, 2015, 29 (01) : 143 - 154
  • [35] Mapping Invasive Phragmites australis in the Old Woman Creek Estuary Using UAV Remote Sensing and Machine Learning Classifiers
    Abeysinghe, Tharindu
    Milas, Anita Simic
    Arend, Kristin
    Hohman, Breann
    Reil, Patrick
    Gregory, Andrew
    Vazquez-Ortega, Angelica
    REMOTE SENSING, 2019, 11 (11)
  • [36] Remote-Sensing Based Winter Wheat Growth Dynamic Changes and the Spatial-Temporal Relationship with Meteorological Factor
    Huang Qing
    Zhou Qingbo
    Wu Wenbin
    Li Dandan
    THIRD INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS 2014), 2014, : 384 - 389
  • [37] Recognition of the invasive species Robinia pseudacacia from combined remote sensing and GIS sources
    Somodi, Imelda
    Carni, Andraz
    Ribeiro, Daniela
    Podobnikar, Tomaz
    BIOLOGICAL CONSERVATION, 2012, 150 (01) : 59 - 67
  • [38] Spatio-Temporal Evolution Monitoring and Analysis of Tidal Flats in Beibu Gulf From 1987 to 2021 Using Multisource Remote Sensing
    Gao, Ertao
    Zhou, Guoqing
    Li, Shuxian
    Fu, Bolin
    Xiao, Yunzhi
    Lan, Yanping
    Wang, Feng
    Xu, Jiasheng
    Zhu, Qiang
    Bai, Yuhang
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2024, 17 : 6099 - 6114
  • [39] Prediction of the Nitrogen, Phosphorus and Potassium Contents in Grape Leaves at Different Growth Stages Based on UAV Multispectral Remote Sensing
    Peng, Xuelian
    Chen, Dianyu
    Zhou, Zhenjiang
    Zhang, Zhitao
    Xu, Can
    Zha, Qing
    Wang, Fang
    Hu, Xiaotao
    REMOTE SENSING, 2022, 14 (11)
  • [40] A remote sensing based analysis of climate change in Sikkim supported by evidence from the field
    Basu, Rumia
    Misra, Gourav
    Sarkar, Dipto
    JOURNAL OF MOUNTAIN SCIENCE, 2021, 18 (05) : 1256 - 1267