CO2 fertilization contributed more than half of the observed forest biomass increase in northern extra-tropical land.

The existence of a large-biomass carbon (C) sink in Northern Hemisphere extra-tropical ecosystems (NHee) is well-established, but the relative contribution of different potential drivers remains highly uncertain. Here we isolated the historical role of carbon dioxide (CO2 ) fertilization by integrating estimates from 24 CO2 -enrichment experiments, an ensemble of 10 dynamic global vegetation models (DGVMs) and two observation-based biomass datasets. Application of the emergent constraint technique revealed that DGVMs underestimated the historical response of plant biomass to increasing [CO2 ] in forests ( ß Forest Mod ) but overestimated the response in grasslands ( ß Grass Mod ) since the 1850s. Combining the constrained ß Forest Mod (0.86 ± 0.28 kg C m-2 [100 ppm]-1 ) with observed forest biomass changes derived from inventories and satellites, we identified that CO2 fertilization alone accounted for more than half (54 ± 18% and 64 ± 21%, respectively) of the increase in biomass C storage since the 1990s. Our results indicate that CO2 fertilization dominated the forest biomass C sink over the past decades, and provide an essential step toward better understanding the key role of forests in land-based policies for mitigating climate change.

Cropland abandonment alleviates soil carbon emissions in the North China Plain.

Land use change could profoundly influence the terrestrial ecosystem carbon (C) cycle. However, the effects of agricultural expansion and cropland abandonment on soil microbial respiration remain controversial, and the underlying mechanisms of the land use change effect are lacking. In this study, we conducted a comprehensive survey in four land use types (grassland, cropland, orchard, and old-field grassland) of North China Plain with eight replicates to explore the responses of soil microbial respiration to agricultural expansion and cropland abandonment. We collected surface soil (0-10 cm in depth) in each land use type to measure soil physicochemical property and microbial analysis. Our results showed that soil microbial respiration was significantly increased by 15.10 mg CO2 kg-1 day-1 and 20.06 mg CO2 kg-1 day-1 due to the conversion of grassland to cropland and orchard, respectively. It confirmed that agricultural expansion might exacerbate soil C emissions. On the contrary, the returning of cropland and orchard to old-field grassland significantly decreased soil microbial respiration by 16.51 mg CO2 kg-1 day-1 and 21.47 mg CO2 kg-1 day-1, respectively. Effects of land use change on soil microbial respiration were predominately determined by soil organic and inorganic nitrogen contents, implying that nitrogen fertilizer plays an essential role in soil C loss. These findings highlight that cropland abandonment can effectively mitigate soil CO2 emissions, which should be implemented in agricultural lands with low grain production and high C emissions. Our results improve mechanistic understanding on the response of soil C emission to land use changes.

A global database of plant production and carbon exchange from global change manipulative experiments.

Numerous ecosystem manipulative experiments have been conducted since 1970/80 s to elucidate responses of terrestrial carbon cycling to the changing atmospheric composition (CO2 enrichment and nitrogen deposition) and climate (warming and changing precipitation regimes), which is crucial for model projection and mitigation of future global change effects. Here, we extract data from 2,242 publications that report global change manipulative experiments and build a comprehensive global database with 5,213 pairs of samples for plant production (productivity, biomass, and litter mass) and ecosystem carbon exchange (gross and net ecosystem productivity as well as ecosystem and soil respiration). Information on climate characteristics and vegetation types of experimental sites as well as experimental facilities and manipulation magnitudes subjected to manipulative experiments are also included in this database. This global database can facilitate the estimation of response and sensitivity of key terrestrial carbon-cycling variables under future global change scenarios, and improve the robust projection of global change‒terrestrial carbon feedbacks imposed by Earth System Models.

A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change.

Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in temperature, precipitation, CO2 and nitrogen across major terrestrial vegetation types of the world. Most experiments manipulated single rather than multiple global change drivers in temperate ecosystems of the USA, Europe and China. The magnitudes of warming and elevated CO2 treatments were consistent with the ranges of future projections, whereas those of precipitation changes and nitrogen inputs often exceeded the projected ranges. Increases in global change drivers consistently accelerated, but decreased precipitation slowed down carbon-cycle processes. Nonlinear (including synergistic and antagonistic) effects among global change drivers were rare. Belowground carbon allocation responded negatively to increased precipitation and nitrogen addition and positively to decreased precipitation and elevated CO2. The sensitivities of carbon variables to multiple global change drivers depended on the background climate and ecosystem condition, suggesting that Earth system models should be evaluated using site-specific conditions for best uses of this large dataset. Together, this synthesis underscores an urgent need to explore the interactions among multiple global change drivers in underrepresented regions such as semi-arid ecosystems, forests in the tropics and subtropics, and Arctic tundra when forecasting future terrestrial carbon-climate feedback.