Impacts of land use,restoration, and climate change on tropical peat carbon stocks in the twenty-first century: implications for climate mitigation

The climate mitigation potential of tropical peatlands has gained increased attention as Southeast Asian peatlands are being deforested, drained and burned at very high rates, causing globally significant carbon dioxide (CO₂) emissions to the atmosphere. We used a process-based dynamic tropical peatland model to explore peat carbon (C) dynamics of several management scenarios within the context of simulated twenty-first century climate change. Simulations of all scenarios with land use, including restoration, indicated net C losses over the twenty-first century ranging from 10 to 100 % of pre-disturbance values. Fire can be the dominant C-loss pathway, particularly in the drier climate scenario we tested. Simulated 100 years of oil palm (Elaeis guineensis) cultivation with an initial prescribed burn resulted in 2400–3000 Mg CO₂?ha^?1 total emissions. Simulated restoration following one 25-year oil palm rotation reduced total emissions to 440–1200 Mg CO₂?ha^?1, depending on climate. These results suggest that even under a very optimistic scenario of hydrological and forest restoration and the wettest climate regime, only about one third of the peat C lost to the atmosphere from 25 years of oil palm cultivation can be recovered in the following 75 years if the site is restored. Emissions from a simulated land degradation scenario were most sensitive to climate, with total emissions ranging from 230 to 10,600 Mg CO₂?ha^?1 over 100 years for the wettest and driest dry season scenarios, respectively. The large difference was driven by increased fire probability. Therefore, peat fire suppression is an effective management tool to maintain tropical peatland C stocks in the near term and should be a high priority for climate mitigation efforts. In total, we estimate emissions from current cleared peatlands and peatlands converted to oil palm in Southeast Asia to be 8.7 Gt CO₂ over 100 years with a moderate twenty-first century climate. These emissions could be minimized by effective fire suppression and hydrological restoration.     

The influence of land-cover changes on the variability of saturated hydraulic conductivity in tropical peatlands

Mitigation and Adaptation Strategies for Global Change - Understanding the movement of water through peat is essential for effective conservation and management strategies for peatlands. Saturated...     

Removal of bacterial indicators in on-site two-stage multi-soil-layering plant under arid climate (Morocco): prediction of total coliform content using K-nearest neighbor algorithm

This study aims to evaluate and monitor the efficacy of a full-scale two-stage multi-soil-layering (TS-MSL) plant in removing fecal contamination from domestic wastewater. The TS-MSL plant under investigation consisted of two units in series, one with a vertical flow regime (VF-MSL) and the other with a horizontal flow regime (HF-MSL). Furthermore, this study attempts to see whether linear model (LM) and K-nearest neighbor (KNN) model can be used to predict total coliform (TC) removal in the TS-MSL system. For 24 months, the TS-MSL system was monitored, with bimonthly measurements recorded at the inlet and outlet of each compartment. Obtained results show removal of 85% of COD, 67% of TP, 27% of TN, and 3 log units of coliforms with good system stability. Thus, the effluent meets the Moroccan water quality code for reuse in the irrigation of green spaces. In addition, as compared to LM, the KNN model (R² = 0.988) may be considered as an effective method for predicting TC removal in the TS-MSL system. Finally, sensitivity analysis has shown that TC and dissolved oxygen level in the influent were the most influential parameters for predicting TC removal in the TS-MSL system.