Abstract
The objective of this study is to estimate the biomass and carbon of global-level mangroves as a special type of wetland. Mangrove ecosystems play an important role in regulating carbon cycling, thus having a significant impact on global environmental change. Extensive studies have been conducted for the estimation of mangrove biomass and carbon stock. However, this estimation at a global level has been insufficiently investigated because the spatial scale of interest is large and most existing studies are based on physically challenging fieldwork surveys that are limited to local scales. Over the past few decades, high-resolution geospatial data related to mangroves have been increasingly collected and processed using remote sensing and Geographic Information Systems (GIS) technologies. While these geospatial data create potential for the estimation of mangrove biomass and carbon, the processing and analysis of these data represent a big data-driven challenge. In this study, we present a spatially explicit approach that integrates GIS-based geospatial analysis and high-performance parallel computing for the estimation of mangrove biomass and carbon at the global level. This integrated approach provides support for enabling and accelerating the global-level estimation of mangrove biomass and carbon from existing high-resolution geospatial data. With this integrated approach, the total area, biomass (including above- and below-ground), and associated carbon stock of global mangroves are estimated as 130,420 km2, 1.908 Pg, and 0.725 Pg C for the year of 2000. The averaged aboveground biomass density of global mangroves is estimated as 146.3 Mg ha−1. Our analysis results demonstrate that this integrated geospatial analysis approach is efficacious for the computationally challenging estimation of global mangrove metrics based on high-resolution data. This global-level estimation and associated results are of great assistance for promoting our understanding of complex geospatial dynamics in mangrove forests.
Highlights
Large-scale assessments of natural resources provide important information for planning, management and conservation, and context for local or site-specific assessments
ResultsIn this section, we report the results of parallel computing performance and global-level mangrove metrics, including area, biomass, and carbon
The Geographic Information Systems (GIS)-based spatial analysis combined with high-performance and parallel computing provides unique support that enables the estimation of biomass and carbon in mangrove ecosystems at the global level
Summary
Large-scale assessments of natural resources provide important information for planning, management and conservation, and context for local or site-specific assessments. Mangrove forests are important tropical wetland types growing within coastal marine environment [1,2]. They are recognized for having the highest carbon density among terrestrial ecosystems. Considerations about the distribution and extent of carbon associated with mangroves are highly relevant to terrestrial carbon cycling and the associated ecosystem services under global environmental or climate change [1,3]. As a result of land use and land cover change over the past several decades, large losses of mangroves at both the regional and global scales have been reported [2,4]. Biomass and carbon stocks related to mangroves can be a basis for averting degradation through payment for ecosystem service program (e.g., REDD+) and they are important to better understanding the global carbon cycle and the sustainability of mangrove ecosystems [3,5,6]
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