Disentangling effects of natural and anthropogenic drivers on forest net ecosystem production. Wang, Y., Buchmann, N., Hessen, D. O, Stordal, F., Erisman, J. W., Vollsnes, A. V., Andersen, T., & Dolman, H. Science of The Total Environment, 839:156326, 2022. ![Disentangling effects of natural and anthropogenic drivers on forest net ecosystem production [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Net Ecosystem Production (NEP) of forests is the net carbon dioxide (CO2) fluxes between land and the atmosphere due to forests' biogeochemical processes. NEP varies with natural drivers such as precipitation, air temperature, solar radiation, plant functional type (PFT), and soil texture, which affect the gross primary production and ecosystem respiration, and thus the net C sequestration. It is also known that deposition of sulphur and nitrogen influences NEP in forest ecosystems. These drivers' respective, unique effects on NEP, however, are often difficult to be individually identified by conventional bivariate analysis. Here we show that by analyzing 22 forest sites with 231 site-year data acquired from FLUXNET database across Europe for the years 2000–2014, the individual, unique effects of these drivers on annual forest CO2 fluxes can be disentangled using Generalized Additive Models (GAM) for nonlinear regression analysis. We show that S and N deposition have substantial impacts on NEP, where S deposition above 5 kg S ha−1 yr−1 can significantly reduce NEP, and N deposition around 22 kg N ha−1 yr−1 has the highest positive effect on NEP. Our results suggest that air quality management of S and N is crucial for maintaining healthy biogeochemical functions of forests to mitigate climate change. Furthermore, the empirical models we developed for estimating NEP of forests can serve as a forest management tool in the context of climate change mitigation. Potential applications include the assessment of forest carbon fluxes in the REDD+ framework of the UNFCCC.
@Article{WANG2022156326,
author = {Wang, You-Ren and Buchmann, Nina and Hessen, Dag O and Stordal, Frode and Erisman, Jan Willem and Vollsnes, Ane Victoria and Andersen, Tom and Dolman, Han},
journal = {Science of The Total Environment},
title = {{Disentangling effects of natural and anthropogenic drivers on forest net ecosystem production}},
year = {2022},
issn = {0048-9697},
pages = {156326},
volume = {839},
abstract = {Net Ecosystem Production (NEP) of forests is the net carbon dioxide (CO2) fluxes between land and the atmosphere due to forests' biogeochemical processes. NEP varies with natural drivers such as precipitation, air temperature, solar radiation, plant functional type (PFT), and soil texture, which affect the gross primary production and ecosystem respiration, and thus the net C sequestration. It is also known that deposition of sulphur and nitrogen influences NEP in forest ecosystems. These drivers' respective, unique effects on NEP, however, are often difficult to be individually identified by conventional bivariate analysis. Here we show that by analyzing 22 forest sites with 231 site-year data acquired from FLUXNET database across Europe for the years 2000–2014, the individual, unique effects of these drivers on annual forest CO2 fluxes can be disentangled using Generalized Additive Models (GAM) for nonlinear regression analysis. We show that S and N deposition have substantial impacts on NEP, where S deposition above 5 kg S ha−1 yr−1 can significantly reduce NEP, and N deposition around 22 kg N ha−1 yr−1 has the highest positive effect on NEP. Our results suggest that air quality management of S and N is crucial for maintaining healthy biogeochemical functions of forests to mitigate climate change. Furthermore, the empirical models we developed for estimating NEP of forests can serve as a forest management tool in the context of climate change mitigation. Potential applications include the assessment of forest carbon fluxes in the REDD+ framework of the UNFCCC.},
doi = {https://doi.org/10.1016/j.scitotenv.2022.156326},
keywords = {Empirical biogeochemical models, GAM, GPP, NEE, RECO,Forest carbon uptake},
url = {https://www.sciencedirect.com/science/article/pii/S0048969722034234},
}
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NEP varies with natural drivers such as precipitation, air temperature, solar radiation, plant functional type (PFT), and soil texture, which affect the gross primary production and ecosystem respiration, and thus the net C sequestration. It is also known that deposition of sulphur and nitrogen influences NEP in forest ecosystems. These drivers' respective, unique effects on NEP, however, are often difficult to be individually identified by conventional bivariate analysis. Here we show that by analyzing 22 forest sites with 231 site-year data acquired from FLUXNET database across Europe for the years 2000–2014, the individual, unique effects of these drivers on annual forest CO2 fluxes can be disentangled using Generalized Additive Models (GAM) for nonlinear regression analysis. We show that S and N deposition have substantial impacts on NEP, where S deposition above 5 kg S ha−1 yr−1 can significantly reduce NEP, and N deposition around 22 kg N ha−1 yr−1 has the highest positive effect on NEP. Our results suggest that air quality management of S and N is crucial for maintaining healthy biogeochemical functions of forests to mitigate climate change. Furthermore, the empirical models we developed for estimating NEP of forests can serve as a forest management tool in the context of climate change mitigation. 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NEP varies with natural drivers such as precipitation, air temperature, solar radiation, plant functional type (PFT), and soil texture, which affect the gross primary production and ecosystem respiration, and thus the net C sequestration. It is also known that deposition of sulphur and nitrogen influences NEP in forest ecosystems. These drivers' respective, unique effects on NEP, however, are often difficult to be individually identified by conventional bivariate analysis. Here we show that by analyzing 22 forest sites with 231 site-year data acquired from FLUXNET database across Europe for the years 2000–2014, the individual, unique effects of these drivers on annual forest CO2 fluxes can be disentangled using Generalized Additive Models (GAM) for nonlinear regression analysis. 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