Wetland Carbon and Environmental Management. Группа авторов
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developing sub‐grid representation of hydrology dynamics, and coupling of these to carbon cycle models, as in Kleinen et al. (2012). The high degree of fine‐scale heterogeneity in wetland carbon stocks, and the difficulty in representing these at global scales, has limited the applicability of such approaches. However, many land surface models are resolving hillslope to valley hydrological gradients, which will better enable them to represent wetland processes and the dynamics of wetland carbon within the Earth system (Fan et al., 2019).
In permafrost‐affected ecosystems, where flooding and anoxia are driven mainly by an impermeable permafrost layer, coupling of the hydrology and climate is more direct; results of such models suggest that with warming and loss of near‐surface permafrost, increased drainage may rapidly lead to loss of anoxia and increase in resulting soil decomposition rates, though such losses may trade off with reductions in CH4 emissions, also due to the loss of anoxia (Lawrence et al., 2015). Interactions between warming trends and abrupt permafrost thaw, fire, hydrologic shifts, and resulting ecosystem changes in response to these drivers suggest additional high latitude carbon losses beyond these simple one‐dimensional vertical soil column permafrost thaw models (Turetsky et al., 2020).
In tropical peatlands, the dominant driver to carbon losses are agricultural drainage of peat forests, and increases to fire and enhance respiration that result from drainage, which are projected to generate enormous losses of carbon over the 21st century (Warren et al., 2015). Adoption of management practices on anthropogenically disturbed peatlands to encourage anoxic conditions may strongly mitigate future carbon losses from peatlands, and such practices would be only partially offset by increases in CH4 accompanying restoration (Gunther et al., 2020). Further feedbacks to tropical peatland carbon stocks may arise from climate change even in undisturbed peatlands, which are likely to have particularly high sensitivity to changes in precipitation and thus seasonal losses of near‐surface anoxia (Cobb et al., 2017). Linking all of these processes into mechanistic models that can be used to project interacting effects of climate, CO2, and land use on wetland carbon stocks remains a major challenge for developing more accurate simulation models.
1.7. UNCERTAINTIES AND FUTURE DIRECTIONS
Wetlands provide many ecosystem services that benefit biodiversity, hydrology, climate stability, and food, fiber, and storm‐resiliency. A scientific basis for wetland management requires a consistent application of terminology, detailed inventories, tracking how wetlands change seasonally, year‐to‐year, and at longer timescales, and studies on the flora, fauna, hydrology, and soil, and how these influence biogeochemical processes. At global scales, these requirements are challenging given limited resources that require models to help with scaling uncertain measurements, complex processes, and multiple temporal and spatial scales. Given this review of global wetland carbon stocks, we show that a large range of uncertainty exists with a minimum of 520 PgC (1792 PgC with permafrost) and maximum of 710 PgC (1882 PgC with permafrost). The main conclusions we draw are that wetlands remain a key component of climate‐carbon feedbacks given that they store more carbon than is currently in the atmosphere. Another conclusion is that at local scales, blue carbon stocks can have multiple roles in sequestering and storing carbon, while providing multiple co‐benefits.
Reducing these uncertainties will require continued investments in field campaigns that directly measure above and belowground carbon stocks and in long‐term instruments monitoring of fluxes of different types of wetlands. These investments, combined with new airborne and spaceborne measuring instruments, in particular LIDAR, radar, and hyperspectral imagers, will make it increasingly possible to map wetland carbon stocks and their changes over time at high, 15–30 meter, spatial resolution. Advances in prognostic models, through the inclusion of wetland‐specific biogeochemical processes, taking advantage of improved computational resources and data assimilation methods, will in part reduce uncertainties in how we interpret historical changes and predict future changes in wetland carbon stocks.
ACKNOWLEDGMENTS
BP and EC acknowledge support from the Gordon and Betty Moore Foundation through Grant GBMF5439 “Advancing Understanding of the Global Methane Cycle” supporting the Methane Budget activity for the Global Carbon Project (globalcarbonproject.org). BP, LF, and NT acknowledge the NASA Carbon Monitoring System. BP, PJT, and LS acknowledge support from the North Carolina State University College of Natural Resources and the Department of the Interior Southeast Climate Adaptation Science Center.
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