Yuhe Ji

The maximizing of water use efficiency (WUE) and radiation use efficiency (RUE) is vital to improving crop production in dryland farming systems. However, the fundamental question as to the association of WUE with RUE and its underlying mechanism under limited-water availability remains contentious. Here, a two-year field trial for maize designed with five progressive soil drying regimes applied at two different growth stages (three-leaf stage and seven-leaf stage) was conducted during the 2013–2014 growing seasons. Both environmental variables and maize growth traits at the leaf and canopy levels were measured during the soil drying process. The results showed that leaf WUE increased with irrigation reduction at the early stage, while it decreased with irrigation reduction at the later stage. Leaf RUE thoroughly decreased with irrigation reduction during the progressive soil drying process. Aboveground biomass (AGB), leaf area index (LAI), a fraction of absorbed photosynthetically active radiation (fAPAR), and light extinction coefficient (k) of the maize canopy were significantly decreased by water deficits regardless of the growth stages when soil drying applied. The interrelationships between WUE and RUE were linear across the leaf and canopy scales under different soil drying patterns. Specifically, a positive linear relationship between WUE and RUE are unexpectedly found when soil drying was applied at the three-leaf stage, while it turned out to be negative when soil drying was applied at the seven-leaf stage. Moreover, the interaction between canopy WUE and RUE was more regulated by fAPAR than LAI under soil drying. Our findings suggest that more attention must be paid to fAPAR in evaluating the effect of drought on crops and may bring new insights into the interrelationships of water and radiation use processes in dryland agricultural ecosystems.

Global vegetation has been reported to be turning greener, especially in China and India. The Yellow River Basin is one of the most prominent greening areas in China. While some studies have attributed vegetation greening to large-scale ecological restoration efforts, our study focuses on the role of climate change in vegetation greening. We selected a time series of annual vegetation net primary productivity (NPP) and vegetation coverage from satellite data to quantify the vegetation greening trend. Annual temperature and precipitation were selected to examine the climate trend from 2000 to 2019. The results showed that the Yellow River Basin experienced a rapid increase in temperature and precipitation during this period. Annual temperature increased with an average speed of 0.905 °C per decade, approximately 4.5 times larger than that of global warming. Annual precipitation increased by 82.8%, with an average speed of 9.17 mm per year. There was widespread vegetation greening in the Yellow River Basin during 2000–2019. This was demonstrated by an increase in vegetation NPP and vegetation coverage in the Yellow River Basin. The increase of annual NPP and coverage from 2000 to 1019 was 26.6% and 30.8%, respectively. Even while considering the effects of conservation and restoration efforts, the rapid increases in temperature and precipitation allowed vegetation to flourish, as evidenced by significant positive correlations between climate variables and vegetation variables. Therefore, climate change played an important positive role in vegetation greening, rather than an undesirable disturbance.

Spring maize (Zea mays L.) is a thermophilic C₄ crop which is sensitive to climate change. This paper provides a detailed assessment of the effect of climate change on the crop from a new perspective, by predicting the probability of the potential distribution of spring maize across China. The affected area of spring maize suitability was identified, and then the affected area was subdivided into the improved area and the deteriorated area. Our results confirmed that there was a detrimental consequence for spring maize suitability under observed climate change from 1961–1990 to 1981–2010. However, our results revealed that warming scenarios of 1.5 °C and 2 °C were helpful for the suitable area expansion of spring maize. The affected area was smaller under warming scenarios than under historical climate change, revealing that temperature rise alone was not enough to trigger a “tipping point” (a threshold value after which abrupt shifts occur) for spring maize, even if warming is 2 °C above the level of 1961–1990. Our results not only benefit China in the design of mitigation and adaptation strategies, but also provide a theoretical judgement that the impact of global warming on the crop ecosystem is not serious if other climate factors remain unchanged.

It is widely recognized that the long-term growth of forests benefits biomass carbon (C) sequestration, but it is not known whether the long-term growth of forests would also benefit soil C sequestration. We selected 79 representative soil profiles and investigated the influence of the forest stand age on the soil C dynamics of three soil layers (0–10, 10–20 and 20–30 cm) in temperate broadleaved forests in East China. The results suggest that the soil C density in temperature broadleaved forests significantly changes with the stand age, following a convex parabolic curve. At an early stand age, the soil C density usually increases, reaching its peak value at a pre-mature stand age (approximately 50 years old). At later stand ages, the soil C density usually decreases. Therefore, our results reveal a turning point in the soil C density at a pre-mature stand age. The long-term growth of temperate broadleaved forests after pre-mature stand age no longer benefits soil C accumulation, probably promotes topsoil C loss. In addition, we found that the soil C density in the upper soil layer usually changes with the forest stand development more significantly than that in deeper soil layers.

There is a growing concern about the ecological conditions in the Haihe River which have been profoundly impacted by the growing human population and intensifying development over the past several decades. By identifying the spatial characteristics of terrestrial and fluvial landscapes, we propose the guidelines and criterions for regionalizing the freshwater ecosystems in the Haihe River basin. The first-level and second-level zones reflect the spatial patterns of the natural backgrounds which could impact the surface water quantity and quality. The 6 first-level zones are regionalized according to topographic characteristics, runoff depth, annual precipitation and evaporation. They represent the spatial pattern of water resource quantity. The 16 second-level zones are regionalized according to the vegetation and soil types overlaid by the first-level zones. They represent the spatial patterns of eco-hydrological processes and water purifying functions of terrestrial landscapes. Finally, the eco-regions are evaluated by the field survey data including water quality, aquatic vegetation and zoobenthos communities. This study could potentially be used to guide the decision-making process for the management of water resources and local ecological projects in the Haihe River basin. The methods formulated in this research can possibly provide important references for other watersheds in China.

Using Håkanson potential ecological risk index, the paper assesses heavy metal risk levels in northern parts of Haihe River basin based on 39 sampling sites. The results indicate that, the concentrations of Cu, Zn, Cd, and Cr in Haihe River basin are higher than the background values of heavy metals in China mainland, while the concentration of Pb is close to the background value in China mainland. Based on the potential ecological risk index for single heavy metal, the risk of Cu, Pb, Zn and Cr belongs to the "slight" level, while Cd has various risk levels at different sampling sites. Generally, the risk order of the heavy metals is Cd > Pb > Cu > Cr > Zn. According to Håkanson potential ecological risk index, 32 monitoring sites belong to "slight" level, 5 sampling sites belong to "middle" level, and 2 monitoring sites belong to "very strong" level. The most polluted sites are Tang River and Dashi River of Beijing, Juma River in Baoding. Therefore, these rivers should be taken more considerations in the river management.