Global mangrove soil organic carbon stocks dataset at 30 m resolution for the year 2020 based on spatiotemporal predictive machine learning.

This dataset presents global soil organic carbon stocks in mangrove forests at 30 m resolution, predicted for 2020. We used spatiotemporal ensemble machine learning to produce predictions of soil organic carbon content and bulk density (BD) to 1 m soil depth, which were then aggregated to calculate soil organic carbon stocks. This was done by using training data points of both SOC (%) and BD in mangroves from a global dataset and from recently published studies, and globally consistent predictive covariate layers. A total of 10,331 soil samples were validated to have SOC (%) measurements and were used for predictive soil mapping. We used time-series remote sensing data specific to time periods when the training data were sampled, as well as long-term (static) layers to train an ensemble of machine learning model. Ensemble models were used to improve performance, robustness and unbiasedness as opposed to just using one learner. In addition, we performed spatial cross-validation by using spatial blocking of training data points to assess model performance. We predicted SOC stocks for the 2020 time period and applied them to a 2020 mangrove extent map, presenting both mean predictions and prediction intervals to represent the uncertainty around our predictions. Predictions are available for download under CC-BY license from 10.5281/zenodo.7729491 and also as Cloud-Optimized GeoTIFFs (global mosaics).

Mangroves provide blue carbon ecological value at a low freshwater cost.

"Blue carbon" wetland vegetation has a limited freshwater requirement. One type, mangroves, utilizes less freshwater during transpiration than adjacent terrestrial ecoregions, equating to only 43% (average) to 57% (potential) of evapotranspiration ([Formula: see text]). Here, we demonstrate that comparative consumptive water use by mangrove vegetation is as much as 2905 kL H2O ha-1 year-1 less than adjacent ecoregions with [Formula: see text]-to-[Formula: see text] ratios of 47-70%. Lower porewater salinity would, however, increase mangrove [Formula: see text]-to-[Formula: see text] ratios by affecting leaf-, tree-, and stand-level eco-physiological controls on transpiration. Restricted water use is also additive to other ecosystem services provided by mangroves, such as high carbon sequestration, coastal protection and support of biodiversity within estuarine and marine environments. Low freshwater demand enables mangroves to sustain ecological values of connected estuarine ecosystems with future reductions in freshwater while not competing with the freshwater needs of humans. Conservative water use may also be a characteristic of other emergent blue carbon wetlands.

High-resolution mapping of losses and gains of Earth's tidal wetlands.

Tidal wetlands are expected to respond dynamically to global environmental change, but the extent to which wetland losses have been offset by gains remains poorly understood. We developed a global analysis of satellite data to simultaneously monitor change in three highly interconnected intertidal ecosystem types-tidal flats, tidal marshes, and mangroves-from 1999 to 2019. Globally, 13,700 square kilometers of tidal wetlands have been lost, but these have been substantially offset by gains of 9700 km2, leading to a net change of -4000 km2 over two decades. We found that 27% of these losses and gains were associated with direct human activities such as conversion to agriculture and restoration of lost wetlands. All other changes were attributed to indirect drivers, including the effects of coastal processes and climate change.

Ambitious global targets for mangrove and seagrass recovery.

There is an urgent need to halt and reverse loss of mangroves and seagrass to protect and increase the ecosystem services they provide to coastal communities, such as enhancing coastal resilience and contributing to climate stability.1,2 Ambitious targets for their recovery can inspire public and private investment in conservation,3 but the expected outcomes of different protection and restoration strategies are unclear. We estimated potential recovery of mangroves and seagrass through gains in ecosystem extent to the year 2070 under a range of protection and restoration strategies implemented until the year 2050. Under a protection-only scenario, the current trajectories of net mangrove loss slowed, and a minor net gain in global seagrass extent (∼1%) was estimated. Protection alone is therefore unlikely to drive sufficient recovery. However, if action is taken to both protect and restore, net gains of up to 5% and 35% of mangroves and seagrasses, respectively, could be achieved by 2050. Further, protection and restoration can be complementary, as protection prevents losses that would otherwise occur post-2050, highlighting the importance of implementing protection measures. Our findings provide the scientific evidence required for setting strategic and ambitious targets to inspire significant global investment and effort in mangrove and seagrass conservation.

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

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 km2) of mangrove systems were deltaic, 27.5% (37,411 km2) were estuarine and 21.0% (28,493 km2) were open coast, with lagoonal mangroves the least abundant (11.0%, 14,993 km2). 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.