Empirical evidence suggests that variations in climate affect the net primary productivity (NPP) across sandy areas over time. However, little is known about the relative impacts of climate change on NPP with global warming of 1.5 and 2.0 °C (GW_1.5 °C_2.0 °C) relative to pre-industrial levels. Here, we used a new set of climate simulations from four Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP 2b) datasets, modified the Carnegie-Ames-Stanford approach (CASA) model and assessed the spatio-temporal variation in NPP in sandy areas of northern China (SAONC). Compared with the reference period (RP, 1986–2005), the NPP variation under four emission scenarios showed clear rising trends and increased most significantly under RCP8.5 with an annual average increase of 2.34 g C/m2. The estimated annual NPP under global warming of 1.5 °C (GW_1.5 °C) increased by 14.17, 10.72, 8.57, and 26.68% in different emission scenarios, and under global warming of 2.0 °C (GW_2.0 °C) it increased by 20.87, 24.01, 29.31, and 39.94%, respectively. In terms of seasonal change, the NPP value under the four emission scenarios changed most significantly in the summer relative to RP, exhibiting a growth of 16.48%. Temperature changes (p > 0.614) had a greater impact on NPP growth than precipitation (p > 0.017), but solar radiation showed a certain negative impact in the middle- and low-latitude regions. NPP showed an increasing trend that changed from the southeast to the central and western regions at GW_1.5 to GW_2.0 °C. NPP was consistent with the spatial change in climate factors and had a promoting role in high latitudes in SAONC, but it was characterized by a certain inhibitory effect at middle and low latitudes in SAONC. The uncertainty of NPP under the four models ranged from 16.29 to 26.52%. Our findings suggest that the impact of GW_1.5 °C is relatively high compared with the current conditions, whereas GW_2.0 °C implies significantly lower projected NPP growth in all areas.
Soils are important carbon (C) reservoirs and play a critical role in regulating the global C cycle. Soil water potential (SWP) measures the energy with which water is retained in the soil and is one of the most vital factors that constrain the decomposition of soil organic C (SOC). The measurements for soil water retention curve (SWRC), on which the estimation of SWP depends, are usually carried out above −1.5 MPa (i.e., the wilting point for many plants). However, the average moisture threshold at which soil microbial activity ceases is usually below −10 MPa in mineral soils. Beyond the measurement range, the SWP estimation has to be derived from extrapolating the SWRC, which violates the statistical principle, resulting in possibly inaccurate SWP estimations. To date, it is unclear to what extent the extrapolated SWP estimation deviates from the "true value" and how it impacts the modeling of SOC decomposition. This study combined SWRC measurements down to −43.7 MPa, a 72-day soil incubation experiment with four moisture levels, and an SOC decomposition model. In addition to the complete SWRC (SWRC all ), we fitted two more SWRCs by using measurements above −0.5 MPa (SWRC 0.5 ) and −1.7 MPa (SWRC 1.7 ), respectively, to quantify the deviations of extrapolated SWPs from the complete SWRC. Results showed that extrapolating the SWRC beyond its measurement range significantly underestimated the SWP. Incorporating the extrapolated SWP in the model significantly underestimated the SOC decomposition under relatively dry conditions. With the extrapolated SWP, the model predicted no SOC decomposition in the driest treatment, while the experiment observed a significant CO 2 emission. The results emphasize that accurate SWP estimations beyond the wilting point are critically needed to improve the modeling of SOC decomposition.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.