A global biophysical typology of mangroves and its relevance for ecosystem structure and deforestation

Abstract

Mangrove forests provide many ecosystem services but are among the world's most threatened ecosystems. Mangroves vary substantially according to their geomorphic and sedimentary setting; while several conceptual frameworks describe these settings, their spatial distribution has not been quantified. Here, we present a new global mangrove biophysical typology and show that, based on their 2016 extent, 40.5% (54,972 km 2) of mangrove systems were deltaic, 27.5% (37,411 km 2) were estuarine and 21.0% (28,493 km 2) were open coast, with lagoonal mangroves the least abundant (11.0%, 14,993 km 2). Mangroves were also classified based on their sedimentary setting, with carbonate mangroves being less abundant than terrigenous, representing just 9.6% of global coverage. our typology provides a basis for future research to incorporate geomorphic and sedimentary setting in analyses. We present two examples of such applications. Firstly, based on change in extent between 1996 and 2016, we show while all types exhibited considerable declines in area, losses of lagoonal mangroves (− 6.9%) were nearly twice that of other types. Secondly, we quantify differences in aboveground biomass between mangroves of different types, with it being significantly lower in lagoonal mangroves. Overall, our biophysical typology provides a baseline for assessing restoration potential and for quantifying mangrove ecosystem service provision. Mangrove forests provide valuable ecosystem functions and services including carbon storage, coastal protection, fisheries enhancement and tourism 1-4 ; however, large declines in global mangrove area have historically been estimated 5. Recent high-resolution assessments of mangrove change suggest considerable slowing of losses 6 , likely driven by growing wealth, increasing clarity of ownership, national efforts to sustainably manage forest estates and increased awareness of the ecosystem services they provide 7 .

First Assessment of the Benthic Meiofauna Sensitivity to Low Human-Impacted Mangroves in French Guiana

“…Over the past two decades, 35% of the world's mangrove was degraded and lost [1], mainly due to deforestation, erosion, urbanization/pollution, shrimp aquaculture, and tropical cyclones [2]. Mangroves of tropical developing countries with a high demographic pressure are the most degraded [3][4][5]. Key ecological functions are thus weakened (i.e., feeding areas, nurseries, blue carbon, sediment and contaminants retention [6,7]).…”

“…Mean values of the three cores over the entire sedimentary column from each station for the physical, chemical, and biological parameters (mean ± SD; n = 3). ×10 3 ± 1.87×103 1.18 ×104 ± 5.46×10 3 4.37 ×10 3 ± 2.56×10 3 BAC 16S 3.89 ×10 6 ± 1.40×10 6 5.76 ×10 5 ± 1.99×10 4 3.83 ×10 5 ± 6.80×10 Cont. Cont.…”

Mapping the Extent of Mangrove Ecosystem Degradation by Integrating an Ecological Conceptual Model with Satellite Data

“…Our second study region is a small area of intensively-studied lagoonal mangroves along Shark River, Everglades National Park, Florida, USA (Figure 1) [41]. This ecosystem is dominated by only three mangrove species: Avicennia germinans, Laguncularia racemosa, The Rakhine mangroves ecosystem is one of four mangrove ecosystem types in Myanmar (Rakhine mangroves forest on mud) [39].…”

“…This ecosystem is dominated by only three mangrove species: Avicennia germinans, Laguncularia racemosa, The Rakhine mangroves ecosystem is one of four mangrove ecosystem types in Myanmar (Rakhine mangroves forest on mud) [39]. The ecosystem consists of at least 28 mangrove species, including the critically endangered Bruguiera hainseii and Sonneratia griffithii [40], and occurs across four geomorphic settings [41]. In Rakhine, anthropogenic activities including the construction of artificial sea walls, tree harvesting, and conversion to rice paddies, aquaculture, and oil palm plantations lead to extensive degradation of mangroves.…”

A Large-Scale Deep-Learning Approach for Multi-Temporal Aqua and Salt-Culture Mapping

“…Due to their water-dependent nature, coastal aquaculture and saline activity require special attention, being directly associated with the loss of natural coastal wetlands and pollution of waters and soils [4]. Other studies have relayed on remote sensing images to understand the dynamics of classical coastal features such as mangroves, beaches, estuaries, and shoreline analysis [5][6][7][8][9][10][11][12][13]. However, there are fewer large-scale studies exhaustively identifying coastal aquaculture and salines, whether on the global or regional scale and yet, none rely on deep-learning algorithms [14,15].…”