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Forest soil acidification caused by acid deposition is a serious threat to the forest ecosystem. To investigate the liming effects of biomass ash (BA) and alkaline slag (AS) on the acidic topsoil and subsoil, a three-year field experiment under artificial Masson pine was conducted at Langxi, Anhui province in Southern China. The surface application of BA and AS significantly increased the soil pH, and thus decreased exchangeable acidity and active Al in the topsoil. Soil exchangeable Ca2+ and Mg2+ in topsoil were significantly increased by the surface application of BA and AS, while an increase in soil exchangeable K+ was only observed in BA treatments. The soil acidity and active Al in subsoil were decreased by the surface application of AS. Compared with the control, soluble monomeric and exchangeable Al in the subsoil was decreased by 38.0% and 29.4% after 3 years of AS surface application. There was a minimal effect on soluble monomeric and exchangeable Al after the application of BA. The soil exchangeable Ca2+ and Mg2+ in the subsoil increased respectively by 54% and 141% after surface application of 10 t ha-1 AS. The decrease of soil active Al and increase of base cations in subsoil were mainly attributed to the high migration capacity of base cations in AS. In conclusion, the effect of surface application of AS was superior to BA in ameliorating soil acidity and alleviating soil Al toxicity in the subsoil of this Ultisol.

AbstractForest growth is sensitive to interannual climatic change in the alpine treeline ecotone (ATE). Whether the alpine treeline ecotone shares a similar pattern of forest growth with lower elevational closed forest belt (CFB) under changing climate remains unclear. Here, we reported an unprecedented acceleration ofPicea schrenkianaforest growth since 1960s in theATEof Tianshan Mountains, northwestern China by a stand‐total sampling along six altitudinal transects with three plots in each transect: one from theATEbetween the treeline and the forest line, and the other two from theCFB. All the sampledP.schrenkianaforest patches show a higher growth speed after 1960 and, comparatively, forest growth in theCFBhas sped up much slower than that in theATE. The speedup of forest growth at theATEis mainly accounted for by climate factors, with increasing temperature suggested to be the primary driver. Stronger water deficit as well as more competition withinthe CFBmight have restricted forest growth there more than that within theATE, implying biotic factors were also significant for the accelerated forest growth in theATE, which should be excluded from simulations and predictions of warming‐induced treeline dynamics.

A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of sizes and trophic states. Using these data, we built a Bayesian network to (1) analyze the sensitivity of cyanobacterial bloom development to different environmental factors and (2) determine the probability that cyanobacterial blooms would occur. Blooms were classified in three categories of hazard (low, moderate, and high) based on cell abundances. The most important factors determining cyanobacterial bloom occurrence were water temperature, nutrient availability, and the ratio of mixing depth to euphotic depth. The probability of cyanobacterial blooms was evaluated under different combinations of total phosphorus and water temperature. The Bayesian network was then applied to quantify the probability of blooms under a future climate warming scenario. The probability of the “high hazardous” category of cyanobacterial blooms increased 5% in response to either an increase in water temperature of 0.8°C (initial water temperature above 24°C) or an increase in total phosphorus from 0.01 mg/L to 0.02 mg/L. Mesotrophic lakes were particularly vulnerable to warming. Reducing nutrient concentrations counteracts the increased cyanobacterial risk associated with higher temperatures.

Water use efficiency (WUE) plays important role in understanding the interaction between carbon and water cycles in the plant-soil-atmosphere system. However, little is known regarding the impact of altered precipitation on plant WUE in arid and semi-arid regions. The study examined the effects of altered precipitation [i.e., ambient precipitation (100% of natural precipitation), decreased precipitation (DP, −50%) and increased precipitation (IP, +50%)] on the WUE of grass species (Stipa grandis and Stipa bungeana) and forb species (Artemisia gmelinii) in a temperate grassland. The results found that WUE was significantly affected by growth stages, precipitation and plant species. DP increased the WUE of S. grandis and S. bungeana generally, but IP decreased WUE especially in A. gmelinii. And the grasses had the higher WUE than forbs. For different growth stages, the WUE in the initial growth stage was lower than that in the middle and late growth stages. Soil temperature, available nutrients (i.e., NO3–, NH4+, and AP) and microorganisms under the altered precipitations were the main factors affecting plant WUE. These findings highlighted that the grasses have higher WUE than forbs, which can be given priority to vegetation restoration in arid and semi-arid areas.

Extreme events normally have negative effects on crop growth. Many studies have reported findings on drought and flood events, while only sparse studies have focused on new types of extreme events, such as drought-flood abrupt alternation (DFAA). We attempted to gain an insight on the effects of DFAA over two-year field experiment on biomass, grain yield and quality, then simulated the yield loss to DFAA in history and future in summer maize planting area in the Northern Anhui Plain. Results show that DFAA significantly reduced root biomass and shoot biomass by 77.1% and 60.1% compared with that in the control systems. The negative effect lasted until mature stage. The grain yield loss was 14.1%–38.4% in different DFAA treatments. The numerical simulation reveals that the average annual yield loss due to DFAA has been increasing in the Northern Anhui Plain, with 21.19%–30.98% during 1964–2017, 14.10%–33.40% during 2020–2050. The spatial distribution of yield loss changed as well. This study increases our knowledge of the effects of DFAA on crop production and highlights the need to consider the targeted countermeasures.

Climatic warming is often predicted to reduce wheat yield and grain quality in China. However, direct evidence is still lacking. We conducted a three-year experiment with a Free Air Temperature Increase (FATI) facility to examine the responses of winter wheat growth and plant N accumulation to a moderate temperature increase of 1.5°C predicted to prevail by 2050 in East China. Three warming treatments (AW: all-day warming; DW: daytime warming; NW: nighttime warming) were applied for an entire growth period. Consistent warming effects on wheat plant were recorded across the experimental years. An increase of ca. 1.5°C in daily, daytime and nighttime mean temperatures shortened the length of pre-anthesis period averagely by 12.7, 8.3 and 10.7 d (P<0.05), respectively, but had no significant impact on the length of the post-anthesis period. Warming did not significantly alter the aboveground biomass production, but the grain yield was 16.3, 18.1 and 19.6% (P<0.05) higher in the AW, DW and NW plots than the non-warmed plot, respectively. Warming also significantly increased plant N uptake and total biomass N accumulation. However, warming significantly reduced grain N concentrations while increased N concentrations in the leaves and stems. Together, our results demonstrate differential impacts of warming on the depositions of grain starch and protein, highlighting the needs to further understand the mechanisms that underlie warming impacts on plant C and N metabolism in wheat.

Half the population of China live in coastal zones where 70% of large cities are also located. Intensive human activities pose significant environmental and ecological hazards to these cities that are already vulnerable to natural hazards and climate change. The sustainable development of coastal cities is thus both a national and international issue. Rongcheng is a typical coastal city in east China. It is a national marine ranch demonstration area that is subjected to multi-stressors from human activities and climate change. The dominant economic sectors include aquaculture and fisheries, agriculture, shipping and tourism. A multitude of resulting pressures come mainly from intensified human activities, such as intensive aquaculture, overfishing, industrial pollutants, agricultural runoff, land reclamation and port expansion. In addition, Rongcheng is also facing exogenic pressures from extreme climate events such as intensified storms, storm surges, droughts and sea ice. A growing awareness of these problems brought together a trans-disciplinary group from local government, research institutions, local practitioners and coastal representatives to jointly explore and co-design adaptive coastal management options. In this transdisciplinary study, a social-ecological analysis based on a combination of the Systems Approach Framework and the Drivers-Pressures-States-Impacts-Responses framework was used to analyze and formulate an adaptive management plan for the sustainability of Rongcheng. More than 40 stakeholders including government, companies, civil society and institutions participated in the study through questionnaires and on-site meetings. A statistical analysis of the results identified urgent issues impeding the sustainable development of Rongcheng. The issues identified were poorly regulated aquaculture, loss of shoreline, and the decline of seagrass and cultural heritage. The study identified management options and measures, some of which were adopted by the local government in a co-designed management plan. The measures included upgrading of aquaculture industry, habitat conservation and restoration, and the development of cultural tourism. Another outcome was the increased knowledge exchange between stakeholders to inform management, policy, and decision making, as well as raised awareness of vulnerability to natural hazards and climate change. The success of this case study provides a reference for the adaptive management of other coastal cities and their sustainable development in a changing climate.

AbstractIndirect climate effects on tree fecundity that come through variation in size and growth (climate-condition interactions) are not currently part of models used to predict future forests. Trends in species abundances predicted from meta-analyses and species distribution models will be misleading if they depend on the conditions of individuals. Here we find from a synthesis of tree species in North America that climate-condition interactions dominate responses through two pathways, i) effects of growth that depend on climate, and ii) effects of climate that depend on tree size. Because tree fecundity first increases and then declines with size, climate change that stimulates growth promotes a shift of small trees to more fecund sizes, but the opposite can be true for large sizes. Change the depresses growth also affects fecundity. We find a biogeographic divide, with these interactions reducing fecundity in the West and increasing it in the East. Continental-scale responses of these forests are thus driven largely by indirect effects, recommending management for climate change that considers multiple demographic rates.