Abstract
Peatlands are important ecosystems that store approximately one third of terrestrial organic carbon. Non-growing season carbon fluxes significantly contribute to annual carbon budgets in peatlands, yet their response to climate change is poorly understood. Here, we investigate the governing environmental variables of non-growing season carbon emissions in a northern peatland. We develop a support-vector regression model using a continuous 13-year dataset of eddy covariance flux measurements from the Mer Blue Bog, Canada. We determine that only seven variables were needed to reproduce carbon fluxes, which were most sensitive to net radiation above the canopy, soil temperature, wind speed and soil moisture. We find that changes in soil temperature and photosynthesis drove changes in net carbon flux. Assessing net ecosystem carbon exchange under three representative concentration pathways, we project a 103% increase in peatland carbon loss by 2100 under a high emissions scenario. We suggest that peatland carbon losses constitute a strong positive climate feedback loop.
Highlights
Peatlands are important ecosystems that store approximately one third of terrestrial organic carbon
Averaged over n = 1000 model training cycles, the cross-validation results showed a mean root-meansquare error (RMSE) = 0.09 and mean r2 = 0.60, implying that the model explained most of the observed variability of nongrowing season (NGS)–net ecosystem CO2 exchange (NEE)
The effects of each of the seven predictor variables on the modeled nongrowing season net ecosystem exchanges (NGS–NEE) are shown in the partial dependence and individual conditional expectation plots of Fig. 2
Summary
Peatlands are important ecosystems that store approximately one third of terrestrial organic carbon. A growing body of literature shows that net ecosystem CO2 exchange (NEE) from various landscapes during the NGS is nontrivial and may contribute significantly to annual ecosystem C budgets[12,13,14,15,16,17,18,19,20] Despite these efforts, there is a lack of predictive understanding of how NGS CO2 emissions from northern peatlands will change under an evolving and uncertain 21st-century climate. A few studies have projected future NGS–NEE of peatland ecosystems under representative climate concentration pathways (RCPs) for northern regions[12,21,22,23] In part, this reflects an incomplete understanding of the key drivers of NGS soil respiration. We train an ML model for NGS-NEE on a 13-year (1998–2010) continuous record of EC flux measurements at the
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