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Data from: Zonation of mangrove flora and fauna in a subtropical estuarine wetland based on surface elevation

Citation

Ma, Wei et al. (2020), Data from: Zonation of mangrove flora and fauna in a subtropical estuarine wetland based on surface elevation, Dryad, Dataset, https://doi.org/10.5061/dryad.s1rn8pk45

Abstract

In the context of sea-level rise (SLR), an understanding of the spatial distributions of mangrove flora and fauna is required for effective ecosystem management and conservation. These distributions are greatly affected by tidal inundation, and surface elevation is a reliable quantitative indicator of the effects of tidal inundation. Most recent studies have focused exclusively on the quantitative relationships between mangrove-plant zonation and surface elevation, neglecting mangrove fauna. Here, we measured surface elevation along six transects through the mangrove forests of a subtropical estuarine wetland in Zhenzhu Bay (Guangxi, China), using a real-time kinematic global positioning system. We identified the mangrove plants along each transect and investigated the spatial distributions of arboreal, epifaunal, and infaunal molluscs, as well as infaunal crabs, using traditional quadrats. Our results indicated that 97.3% of all mangrove forests in the bay were distributed within the 400–750 m intertidal zone, between the local mean sea level and mean high water (119 cm above mean sea level). Mangrove plants exhibited obvious zonation patterns, and different species tended to inhabit different niches along the elevation gradient: Aegiceras corniculatum dominated in seaward locations while Lumnitzera racemosa dominated in landward areas. Mangrove molluscs also showed distinct patterns of spatial zonation correlated with surface elevation, independent of life-form and season; the spatial distributions of some molluscs were influenced by the relative abundances of certain mangrove plants. In contrast, the spatial distributions of crabs in the bay were not correlated with surface elevation. To the best of our knowledge, this is the first study to explicitly quantify the influences of surface elevation on the spatial distributions of mangrove fauna in the intertidal zone. This characterization of the vertical ranges of various flora and fauna in mangrove forests provides a basic framework for future studies aimed at predicting changes in the structure and functions of mangrove forests in response to SLR.

Methods

        Six transects (each approximately 400–750 m long) were drawn across the five main mangrove forests, from the seaward forest edge to the shore. In order to fully investigate the mangrove forests of the bay, we ensured that the transects covered a broad geographical area: from the bay mouth to the top of the bay. All transects were at least 1 km apart. Elevation along each transect was measured in 5–10 m surface intervals that were relatively flat, using a Global Navigation Satellite System-Real Time Kinematic GPS unit (G970 GNSS RTK, UniStrong Inc., Beijing, China); this unit has a vertical precision of 15 mm. The elevation of each surface interval was converted to the Chinese Height Datum using point correction, performed based on control points located 3 km from the study area. The elevation of the local MSL relative to the Chinese Height Datum was 0.34 m (EBCBS, 1993). Therefore, surface elevation relative to the local MSL was determined by subtracting 0.34 m from the measured elevation. Next, we established sampling sites at 25 cm vertical increments along each transect from the seaward edge to the landward edge. Because the elevation range varied among transects, the number of sampling sites along each transect also differed. In addition, due to topographic fluctuations, some transects included more than one site at the same height.

      At each sampling site, because there was only one layer in the vegetation canopy, mangrove plant composition and abundance were recorded by number of individual (for specimens >0.5 m tall) in three randomly selected quadrats (5 × 5 m; 10 m apart). We sampled the arboreal, epifaunal, and infaunal molluscan communities, as well as the infaunal crab communities, at each site in July 2017 (rainy season) and in January 2018 (dry season). To collect arboreal molluscs, all specimens attached to trunks, leaves, prop roots, and other tree parts were collected by hand in each mangrove quadrat. To collect epifaunal molluscs, we randomly designated 5 epifaunal-mollusc quadrats (1 m × 1 m; 5 m apart) per sampling site, and all molluscs on the sediment surfaces of these quadrats were collected. To collect infaunal molluscs and crabs, we randomly designated a 25 × 25 cm area in each epifaunal-mollusc quadrat; we then sieved the uppermost 30 cm of the sediment in these areas through a 1-mm mesh (Liu, Wang, Wang, Fu, & Lu, 2016). All specimens were identified to species following Okutani (Okutani, 2000) and Wang et al. (Wang, Zhang, Ma, Cai, & Zhang, 2016), and then counted and weighted. 

Usage Notes

Abbreviations of species: Ac, Aegiceras corniculatum; Am, Avicennia marina; Ko, Kandelia obovata; Bg, Bruguiera gymnorhiza; Eag, Excoecaria agallocha; Lr, Lumnitzera racemosa; Ls, Littoraria scabra; Eae, Enigmonia aenigmatica; Lm, Littoraria melanostoma; Lp, Littoraria pallescens; Lar, Littoraria ardouiniana; Ts, Terebralia sulcata; Co, Cerithidea ornata; Cn, Cassidula nucleus; Cc, Cerithidea cingulata; Bm, Batillaria multiformis; Ab, Assiminea brevicula; Md, Mainwaringia dantaae; Alay, Allochroa layardi; Cm, Cerithidea microptera; Alat, Assiminea latericea; Cl, Cerithidea largillierti; Ss, Salinator sanchezi; Isp, Iravadia sp.; Iq, Iravadia quadrasi; Isa, Iracadia sakaguchii; Nv, Neritina violacea; Sj, Stenothyra japonica; Cdj, Cerithidea djadjariensis; Pcy, Pinguitellina cycladifomis; Lan, Laternula anatina; Isc, Indoaustriella scarlatoi; Gch, Glauconome chinensis; Ip, Indoaustriella plicifera; Gco, Geloina coaxans; Me, Macrophthalmus erato; Pcr, Paracleistostoma cristatum; Cdi, Cleistostoma dilatatum; Sp, Sesarma plicata

Funding

National Natural Science Foundation of China, Award: No. 31670490

National Key Research and Development Program of China, Award: No. 2016YFC0502904