基于Shuttleworth-Wallace模型的科尔沁沙地流动半流动沙丘蒸散发模拟

陆面蒸散发在气候调节和维持区域水量平衡中起关键作用.量化蒸散发及其各组分项,对深刻揭示干旱半干旱地区的生态水文过程具有重要意义.本研究基于科尔沁沙地流动半流动沙丘2017年生长季气象监测系统的原位监测数据,利用Shuttleworth-Wallace(S-W)模型对沙丘蒸散发进行模拟,在此基础上,对蒸散各组分进行拆分,并利用涡度相关对模拟蒸散发值进行验证.结果表明: 整个生长季模型模拟蒸散发值为308 mm,涡度相关实测值为296 mm,偏差较小,证明S-W模型适用于该地区的蒸散发模拟.蒸散发整体呈生长旺盛期>生长后期>生长初期,分别为192、71和45 mm,分别占总量的62.3%、23.1%和14.6%.日尺度上模型模拟值与实测蒸散发值一致性较高,模型模拟精度大体表现为: 晴天>阴天>雨天,且阴雨天模型模拟值较涡度相关实测值偏低.经拆分,土壤蒸发和植被蒸腾分别为176和132 mm,分别占总量的57.1%和42.9%,表明沙地水分利用效率较低.持续干旱和降水后,蒸散发规律明显不同,且土壤蒸发对降水的敏感性强于植被蒸腾.     

陕甘宁地区降水稳定同位素特征及水汽来源

依据全球大气降水稳定同位素观测网络(GNIP)和已有研究中陕甘宁地区的大气降水氢氧稳定同位素资料,并结合相关气象数据,分析了陕甘宁地区大气降水氧稳定同位素的时空分布特征及其影响因子,并建立了大气降水线方程.结果表明:3省大气降水线的斜率、截距由小到大依次为:甘肃、陕西、宁夏,且均小于全球大气降水线方程的斜率、截距,表明3省的降水过程受蒸发作用影响程度沿宁夏、陕西、甘肃增强;陕甘宁地区大气降水中δ18O值在时间变化上,表现为夏秋季节富集、冬春季节贫化,从空间分布来看,由西北至东南,加权平均δ18O值呈减小趋势;3省降水中δ18O温度效应显著,但不存在降水量效应,这体现了中高纬度大陆性气候的特征;高程效应的定量关系为-0.12‰·(100 m)^-1,纬度效应更显著(纬度每增加1°,降水中δ18O相应贫化0.27‰);采用HYSPLIT模型对各站点的水汽来源进行追踪,气团聚类轨迹表明,夏半年主要有来自孟加拉湾的水汽、东南季风水汽和西风带水汽,冬半年以西风带水汽为主.     

Effect of interannual precipitation variability on dryland productivity: A global synthesis

Climate‐change assessments project increasing precipitation variability through increased frequency of extreme events. However, the effects of interannual precipitation variance per se on ecosystem functioning have been largely understudied. Here, we report on the effects of interannual precipitation variability on the primary production of global drylands, which include deserts, steppes, shrublands, grasslands, and prairies and cover about 40% of the terrestrial earth surface. We used a global database that has 43 datasets, which are uniformly distributed in parameter space and each has at least 10 years of data. We found (a) that at the global scale, precipitation variability has a negative effect on aboveground net primary production. (b) Expected increases in interannual precipitation variability for the year 2,100 may result in a decrease of up to 12% of the global terrestrial carbon sink. (c) The effect of precipitation interannual variability on dryland productivity changes from positive to negative along a precipitation gradient. Arid sites with mean precipitation under 300 mm/year responded positively to increases in precipitation variability, whereas sites with mean precipitation over 300 mm/year responded negatively. We propose three complementary mechanisms to explain this result: (a) concave‐up and concave‐down precipitation–production relationships in arid vs. humid systems, (b) shift in the distribution of water in the soil profile, and (c) altered frequency of positive and negative legacies. Our results demonstrated that enhanced precipitation variability will have direct impacts on global drylands that can potentially affect the future terrestrial carbon sink.     

Evaluating ecosystem effects of climate change on tropical island streams using high spatial and temporal resolution sampling regimes

Climate change is expected to alter precipitation patterns worldwide, which will affect streamflow in riverine ecosystems. It is vital to understand the impacts of projected flow variations, especially in tropical regions where the effects of climate change are expected to be one of the earliest to emerge. Space‐for‐time substitutions have been successful at predicting effects of climate change in terrestrial systems by using a spatial gradient to mimic the projected temporal change. However, concerns have been raised that the spatial variability in these models might not reflect the temporal variability. We utilized a well‐constrained rainfall gradient on Hawaii Island to determine (a) how predicted decreases in flow and increases in flow variability affect stream food resources and consumers and (b) if using a high temporal (monthly, four streams) or a high spatial (annual, eight streams) resolution sampling scheme would alter the results of a space‐for‐time substitution. Declines in benthic and suspended resource quantity (10‐ to 40‐fold) and quality (shift from macrophyte to leaf litter dominated) contributed to 35‐fold decreases in macroinvertebrate biomass with predicted changes in the magnitude and variability in the flow. Invertebrate composition switched from caddisflies and damselflies to taxa with faster turnover rates (mosquitoes, copepods). Changes in resource and consumer composition patterns were stronger with high temporal resolution sampling. However, trends and ranges of results did not differ between the two sampling regimes, indicating that a suitable, well‐constrained spatial gradient is an appropriate tool for examining temporal change. Our study is the first to investigate resource to community wide effects of climate change on tropical streams on a spatial and temporal scale. We determined that predicted flow alterations would decrease stream resource and consumer quantity and quality, which can alter stream function, as well as biomass and habitat for freshwater, marine, and terrestrial consumers dependent on these resources.     

The adaptive potential of plant populations in response to extreme climate events

The frequency and magnitude of extreme climate events are increasing with global change, yet we lack predictions and empirical evidence for the ability of wild populations to persist and adapt in response to these events. Here, we used Fisher's Fundamental Theorem of Natural Selection to evaluate the adaptive potential of Lasthenia fremontii, a herbaceous winter annual that is endemic to seasonally flooded wetlands in California, to alternative flooding regimes that occur during El Niño Southern Oscillation (ENSO) events. The results indicate that populations may exhibit greater adaptive potential in response to dry years than wet years, and that the relative performance of populations will change across climate scenarios. More generally, our findings show that extreme climate events can substantially change the potential for populations to adapt to climate change by modulating the expression of standing genetic variation and mean fitness.     

Protein structure prediction assisted with sparse NMR data in CASP13

CASP13 has investigated the impact of sparse NMR data on the accuracy of protein structure prediction. NOESY and ¹⁵N-¹H residual dipolar coupling data, typical of that obtained for ¹⁵N,¹³C-enriched, perdeuterated proteins up to about 40 kDa, were simulated for 11 CASP13 targets ranging in size from 80 to 326 residues. For several targets, two prediction groups generated models that are more accurate than those produced using baseline methods. Real NMR data collected for a de novo designed protein were also provided to predictors, including one data set in which only backbone resonance assignments were available. Some NMR-assisted prediction groups also did very well with these data. CASP13 also assessed whether incorporation of sparse NMR data improves the accuracy of protein structure prediction relative to nonassisted regular methods. In most cases, incorporation of sparse, noisy NMR data results in models with higher accuracy. The best NMR-assisted models were also compared with the best regular predictions of any CASP13 group for the same target. For six of 13 targets, the most accurate model provided by any NMR-assisted prediction group was more accurate than the most accurate model provided by any regular prediction group; however, for the remaining seven targets, one or more regular prediction method provided a more accurate model than even the best NMR-assisted model. These results suggest a novel approach for protein structure determination, in which advanced prediction methods are first used to generate structural models, and sparse NMR data is then used to validate and/or refine these models.     

Comparison of microbially induced calcium carbonate precipitation eligibility using sporosarcina pasteurii and bacillus licheniformis on two different sands

The use of biological means for ground improvement have become popular, which generally works through the process called microbially-induced calcium carbonate precipitation (MICP). Many studies indicate successful application of MICP based improvement with multiple bacteria and on several soils. Given the proven performance of MICP, this study aims to examine the MICP process by comparing the calcium carbonate precipitation ability of widely studied bacteria, i.e., Sporosarcina pasteurii and relatively under-recognized bacteria, i.e., Bacillus licheniformis to outline the formation success. For this purpose, two different sands were tested for observing precipitation behavior using a series of syringe tests. Furthermore, the effect of concentration and inclusion of calcium chloride for nutrition of bacteria, saturation with water, and hybrid use of two bacteria were investigated in some tests for diversification. X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive x-ray spectroscopy (EDS) were used for the interpretation of results. Results indicated that Sporosarcina pasteurii had performed superior over Bacillus licheniformis when achieving calcium carbonate precipitation in tests for both sands. In addition, many intriguing SEM images contributed to the literature of MICP monitoring, highlighting the effects of the variables investigated.