Spatially-explicit, temporally dynamic model of wetland methane emissions from prairie wetland of central North America. Bansal, S., Post van der Burg, M., Lo, R., Fern, R. R., McKenna, O. P., & Jones, J. W. In volume 2020, pages B066–0009, December, 2020. Conference Name: AGU Fall Meeting Abstracts ADS Bibcode: 2020AGUFMB066.0009B![Spatially-explicit, temporally dynamic model of wetland methane emissions from prairie wetland of central North America [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex Almost half of all biogenically-produced methane is emitted to the atmosphere from small lakes and wetlands. The Prairie Pothole Region (PPR) of central North America contains 5-8 million small lakes and wetlands, which can influence continental and global methane budgets. However, there is considerable uncertainty of past, current, and future emissions of methane from PPR wetlands due to a lack of landscape-scale models based on robust, empirical data. We used a bottom-up approach to develop a spatially-explicit, temporally-dynamic model of wetland methane emissions from PPR wetlands. Using one of the largest datasets in the world with more than 20,000 static-chamber flux measurements, we developed a plot-scale model of methane flux using generalized additive modeling, and then upscaled to the landscape using GIS and remotely sensed information. Predictors variables in the plot-scale model included water-filled pore space, soil temperature, wetland size, hydroperiod, land cover, and normalized difference vegetation index (NDVI). Data for upscaling included the Dynamic Surface Water Extent based on Landsat, ClimateNA, NDVI, and the North American Land Change Monitoring System. Our plot-scale model had reasonable predictive power (deviance explained = 62%). Methane flux followed non-linear, positive relationships with most predictors. Wetland area had a quadratic-shaped relationship with methane flux, with the highest fluxes from mid-sized (~4 ha) wetlands, with lower emissions from smaller wetlands with short hydroperiod and from larger wetlands and lakes with high salinity. Wetland extent varied by an order of magnitude between the driest year (1991) and wettest year (2011). Total emissions from the PPR ranged from 0.1 to 1 Tg CH4 per year during these historically dry and wet years. Future warm temperature scenarios (RCP 8.5) indicate methane emissions from the PPR could increase significantly, although wetland extent is the primary driver of regional emissions.
@inproceedings{bansal_spatially-explicit_2020,
title = {Spatially-explicit, temporally dynamic model of wetland methane emissions from prairie wetland of central {North} {America}},
volume = {2020},
url = {https://ui.adsabs.harvard.edu/abs/2020AGUFMB066.0009B},
abstract = {Almost half of all biogenically-produced methane is emitted to the atmosphere from small lakes and wetlands. The Prairie Pothole Region (PPR) of central North America contains 5-8 million small lakes and wetlands, which can influence continental and global methane budgets. However, there is considerable uncertainty of past, current, and future emissions of methane from PPR wetlands due to a lack of landscape-scale models based on robust, empirical data. We used a bottom-up approach to develop a spatially-explicit, temporally-dynamic model of wetland methane emissions from PPR wetlands. Using one of the largest datasets in the world with more than 20,000 static-chamber flux measurements, we developed a plot-scale model of methane flux using generalized additive modeling, and then upscaled to the landscape using GIS and remotely sensed information. Predictors variables in the plot-scale model included water-filled pore space, soil temperature, wetland size, hydroperiod, land cover, and normalized difference vegetation index (NDVI). Data for upscaling included the Dynamic Surface Water Extent based on Landsat, ClimateNA, NDVI, and the North American Land Change Monitoring System. Our plot-scale model had reasonable predictive power (deviance explained = 62\%). Methane flux followed non-linear, positive relationships with most predictors. Wetland area had a quadratic-shaped relationship with methane flux, with the highest fluxes from mid-sized ({\textasciitilde}4 ha) wetlands, with lower emissions from smaller wetlands with short hydroperiod and from larger wetlands and lakes with high salinity. Wetland extent varied by an order of magnitude between the driest year (1991) and wettest year (2011). Total emissions from the PPR ranged from 0.1 to 1 Tg CH4 per year during these historically dry and wet years. Future warm temperature scenarios (RCP 8.5) indicate methane emissions from the PPR could increase significantly, although wetland extent is the primary driver of regional emissions.},
urldate = {2023-06-09},
author = {Bansal, S. and Post van der Burg, M. and Lo, R. and Fern, R. R. and McKenna, O. P. and Jones, J. W.},
month = dec,
year = {2020},
note = {Conference Name: AGU Fall Meeting Abstracts
ADS Bibcode: 2020AGUFMB066.0009B},
keywords = {NALCMS},
pages = {B066--0009},
}
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However, there is considerable uncertainty of past, current, and future emissions of methane from PPR wetlands due to a lack of landscape-scale models based on robust, empirical data. We used a bottom-up approach to develop a spatially-explicit, temporally-dynamic model of wetland methane emissions from PPR wetlands. Using one of the largest datasets in the world with more than 20,000 static-chamber flux measurements, we developed a plot-scale model of methane flux using generalized additive modeling, and then upscaled to the landscape using GIS and remotely sensed information. Predictors variables in the plot-scale model included water-filled pore space, soil temperature, wetland size, hydroperiod, land cover, and normalized difference vegetation index (NDVI). Data for upscaling included the Dynamic Surface Water Extent based on Landsat, ClimateNA, NDVI, and the North American Land Change Monitoring System. 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The Prairie Pothole Region (PPR) of central North America contains 5-8 million small lakes and wetlands, which can influence continental and global methane budgets. However, there is considerable uncertainty of past, current, and future emissions of methane from PPR wetlands due to a lack of landscape-scale models based on robust, empirical data. We used a bottom-up approach to develop a spatially-explicit, temporally-dynamic model of wetland methane emissions from PPR wetlands. Using one of the largest datasets in the world with more than 20,000 static-chamber flux measurements, we developed a plot-scale model of methane flux using generalized additive modeling, and then upscaled to the landscape using GIS and remotely sensed information. Predictors variables in the plot-scale model included water-filled pore space, soil temperature, wetland size, hydroperiod, land cover, and normalized difference vegetation index (NDVI). 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