Modelling alternative harvest effects on soil CO and CH fluxes from peatland forests.

Over the last century, many peatlands in northern Europe have been drained for forestry. Forest management with different harvesting regimes has a significant impact on soil water status and consequently on greenhouse gas emissions from peat soils. In this paper, we have used the process-based JSBACH-HIMMELI model to simulate the effects of alternative harvesting regimes, namely non-harvested (NH), selection harvesting (SH; 70 % of stem volume harvested) and clear-cutting (CC; 100 % of stem volume harvested), on soil CH and CO fluxes in peatland forests.

Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates.

The recent rise in atmospheric methane (CH ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH source, estimates of global wetland CH emissions vary widely among approaches taken by bottom-up (BU) process-based biogeochemical models and top-down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi-model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH emission estimates and model performance.

The deglacial forest conundrum.

How fast the Northern Hemisphere (NH) forest biome tracks strongly warming climates is largely unknown. Regional studies reveal lags between decades and millennia. Here we report a conundrum: Deglacial forest expansion in the NH extra-tropics occurs approximately 4000 years earlier in a transient MPI-ESM1.

Regional trends and drivers of the global methane budget.

The ongoing development of the Global Carbon Project (GCP) global methane (CH ) budget shows a continuation of increasing CH emissions and CH accumulation in the atmosphere during 2000-2017. Here, we decompose the global budget into 19 regions (18 land and 1 oceanic) and five key source sectors to spatially attribute the observed global trends. A comparison of top-down (TD) (atmospheric and transport model-based) and bottom-up (BU) (inventory- and process model-based) CH emission estimates demonstrates robust temporal trends with CH emissions increasing in 16 of the 19 regions.