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

Abstract

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.

Distribution Characteristics and Restoration Application of Vegetation in Chengcun Bay Surrounding Areas of Yangjiang City

“…Reclamation and tidal flat breeding caused serious damage to mangrove wetlands [ 15 ]. In recent years, due to reclamation and tidal flat breeding, a large number of suitable tidal flats of mangrove forest have been occupied [ 3 , 31 , 32 ]. The tidal flats suitable for the settlement and diffusion of mangroves are fenced off and transformed into fishponds and shrimp ponds by villagers and contractors, so the diffusion and development of mangroves are artificially restricted.…”

Macrobenthic community of an anthropogenically influenced mangrove associated estuary on the East coast of India: An approach for ecological assessment

“…The government can enforce authority and share responsibilities with local stakeholders, academic institutions, and nongovernmental organizations as partners (Romañach et al, 2018). Regular monitoring of the environmental conditions and mangrove cover through advanced research (by observing heavy metal concentrations, application of Remote Sensing and GIS, and others) and citizen science approaches are essential (Zauki et al, 2019;Wolswijk et al, 2020;Durango-Cordero et al, 2021;Gopalakrishnan et al, 2021;Wolswijk et al, 2022).…”

Spatiotemporal characteristics of Zhanjiang Mangrove Nature Reserve ecosystem based on remote sensing

“…红树林是指生长在热带和亚热带海岸潮间带， 以红树植物为主的常绿灌木或乔木组成的木本生 物群落， 具有稳固海岸线、 防风护堤、 净化水质等功 能 [1] 。1956-1997 年间， 中国红树林海岸曾遭受大 面积破坏， 面积一度减少了 2/3 [2] 。红树林植被面积 是评估红树林现状的一个重要指标， 传统的调查方 法获取信息周期长， 需要大量人力、 物力， 且存在一 定的危险性。相比传统调查方法， 遥感方法具有覆 盖范围广以及可重复访问的特征 [3] ， 在调查与监测 红树林生态系统方面具有准确、 快速、 成本低等优 势 [4] 。 与其他遥感数据相比， Landsat 系列遥感数据具 有较长的时间尺度特征， 满足宏观尺度红树林面积 监测与分析的需求， 因此得以广泛应用 [5] 。例如， Roy 等 [6] 借助 Landsat 遥感影像绘制和监测印度奥里 萨邦海岸 30 年来的红树林变化， 分析了该地区红树 林保护的有效性； Elmahdy 等 [7] 使用 Landsat 遥感影 http://www.resci.cn 红树林生态系统的有效措施之一 [11][12][13] 。但也有相关 研究发现， 无序地建立保护区并不能有效保护红树 林， 其管理有效性可能随时间逐渐下降， 这一问题在 发展中国家更为突出 [14] 。因此， 如何科学地建立保 护区来保护红树林这一珍贵的生态系统值得探讨。 湛江红树林国家级自然保护区 (后文简称保护 区) 是中国 6 个国家级红树林自然保护区中面积最 大的， 面积占比高达 35.7% [15] 。其红树林沿着雷州 半岛边缘分布， 且分块较多。目前已有不少基于不 同遥感技术或相关算法对湛江红树林自然保护区 面积变化的监测分析研究， 为保护区红树林修复与 管理提供了参考， 并且丰富了红树林遥感分析的方 法， 但监测分析的对象大多是保护区中红树林分布 较为集中的核心区域 [16][17][18] ； 同时， 也缺乏对湛江红树 林自然保护区的时空变化特征分析 林面积长期位居全国第一 [19] ， 湛江红树林占广东省 红树林面积的 60%以上， 为 6500 hm 2 左右 [20] 。保护 区气候为亚热带季风气候， 年平均气温为 23°C， 年 平均降雨量 1417~1802 mm [21] 将向陆一侧 1.5 km 范围划定缓冲区 [16] ， 并对河流密 集区域出现的缓冲区重叠部分进行删除。 使用遥感技术分析红树林分布情况的关键在 于对红树林的识别， 目前常用的方法有监督分类 法、 非监督分类法、 面向对象分类法等 [24][25][26][27] 如， 徐家雄等 [31] 通过对高桥镇的白骨壤群落进行调 查发现， 遭受广州小斑螟的危害会使白骨壤表现出 不同程度枯死现象。此外， 还有其他害虫对不同类 型红树林植被造成影响， 如秋茄牡蛎盾蚧、 栗黄枯 叶蛾和海桑毛虫分别会对秋茄、 无瓣海桑和海桑造 成局部受害 [32] 。 5.1.2 外来生物入侵 互花米草是中国湿地生态系统中常见的外来 入侵物种， 由于其过快的生长速度会对红树林生境 造成侵占。郭欣等 [33] 制， 需严守已划定的生态红线 [35] 。…”