Article (Scientific journals)
Distinguishing original and non-original stands at the zhanjiang mangrove national nature reserve (P.r. china): Remote sensing and gis for conservation and ecological research
Durango-Cordero, Juan; Satyanarayana, Behara; Chan, Jonathan Cheung-Wai et al.
2021In Remote Sensing, 13 (14), p. 2781
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Keywords :
GIS; Original forest; Remote sensing; Spatial distribution; Vegetation structure; Distribution patterns; Indo-West Pacific; Methodological frameworks; Remote sensing and GIS; Remote sensing data; Species composition; Structural parameter; Vegetation dynamics; Earth and Planetary Sciences (all); General Earth and Planetary Sciences
Abstract :
[en] The present research developed a novel methodological framework to differentiate natural mangrove stands (i.e., original), from stands which were planted and stands naturally established after interaction between planted and non-planted stands (e.g., through pollination, i.e., non-original). Ground-truth and remote sensing data were collected for Zhanjiang Mangrove National Nature Reserve (ZMNNR) in P.R. China. First, satellite images of Corona (1967) and GeoEye-1 (2009) were overlaid to identify original (1967) and non-original (2009) mangrove stands. Second, in both stands a total of 75 in situ plots (25 m2) were measured for ground-truthing of tree structural parameters including height, density, basal area and Complexity Index (CI). From temporal satellite data, we identify 236.12 ha of original mangrove and 567.88 ha of non-original mangrove in the reserve. Averaged measurements of the original mangrove stands, i.e., stem density (1164 nos. 0.1 ha−1), basal area (90.3 m2 0.1 ha−1) and CI (100.59), indicated that they were in a state of maturity and less disturbed compared to the non-original mangroves (density, 1241 nos. 0.1 ha−1; basal area, 4.92 m2 0.1 ha−1 and CI, 55.65). The Kruskal–Wallis test showed significant differentiation between the original and non-original mangrove tree structural parameters: Kandelia obovata’s density, X2 = 34.78, d.f. = 1, p = 0.001; basal area, X2 = 108.15, d.f. = 1, p = 0.001; Rizhopora stylosa’s density, X2 = 64.03, d.f. = 1, p = 0.001; basal area, X2 = 117.96, d.f. = 1, p = 0.001. The latter is also evident from the clustering plots generated from the Principal Component Analysis (PCA). Vegetation dynamics at the ZMNNR also enabled us to compare the species composition and distribution patterns with other Indo-West Pacific regions. Overall, the present study not only highlights the advantage of >50 years old satellite data but also provide a benchmark for future ecological research, conservation and management of the ZMNNR.
Disciplines :
Environmental sciences & ecology
Author, co-author :
Durango-Cordero, Juan;  Research Center for the Territory and Sustainable Habitat, Universidad Tecnológica Indoamérica, Machalay Sabanilla, Quito, Ecuador ; Facultad de Arquitectura, Artes y Diseño, Universidad Tecnológica Indoamérica, Ambato, Ecuador ; Ecology & Biodiversity, Laboratory of Plant Biology and Nature Management, Vrije Universiteit Brussel—VUB, Brussels, Belgium
Satyanarayana, Behara;  Mangrove Research Unit (MARU), Institute of Oceanography and Environment (INOS), Universiti Malaysia Terengganu—UMT, Kuala Terengganu Terengganu, Malaysia ; Laboratory of Systems Ecology and Resource Management, Université Libre de Bruxelles-ULB, Brussels, Belgium
Chan, Jonathan Cheung-Wai ;  Department of Electronics and Informatics, Vrije Universiteit Brussel—VUB, Brussels, Belgium
Bogaert, Jan  ;  Université de Liège - ULiège > Département GxABT > Biodiversité et Paysage
Dahdouh-Guebas, Farid ;  Ecology & Biodiversity, Laboratory of Plant Biology and Nature Management, Vrije Universiteit Brussel—VUB, Brussels, Belgium ; Laboratory of Systems Ecology and Resource Management, Université Libre de Bruxelles-ULB, Brussels, Belgium
Language :
English
Title :
Distinguishing original and non-original stands at the zhanjiang mangrove national nature reserve (P.r. china): Remote sensing and gis for conservation and ecological research
Publication date :
02 July 2021
Journal title :
Remote Sensing
eISSN :
2072-4292
Publisher :
MDPI AG
Volume :
13
Issue :
14
Pages :
2781
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE]
Funding text :
Funding: J.D.-C. was supported by the VLIR scholarship. This research was funded by the F.R.S.-F.N.R.S. Fonds de la Recherche Scientifique, Brussels, Belgium (Contract N◦ 2.4532.09, and F.4508.11).
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