气候变暖背景下河南省夏玉米花期高温灾害风险预估

为预估未来气候变暖背景下夏玉米花期高温灾害风险,根据河南省19个农业气象观测站夏玉米抽雄期常年观测资料和未来RCPs(representativeconcentrationpathways)气候变化情景数据,构建夏玉米花期高温风险评价指标,开展河南省夏玉米花期高温灾害时空特征及风险演变分析。其中RCPs气候情景数据包括基准气候条件(1951—2005年, RCP-rf)和未来(2006—2050年)RCP 4.5(中)、RCP 8.5(高)两种浓度路径数据。以抽雄普遍期及之后7d确定为夏玉米花期,并内插匹配气候情景格点数据。以花期最高气温≥32℃和≥35℃作为轻度和重度高温灾害发生阈值,根据轻、重度夏玉米花期高温发生频率和高温积害,建立风险评价指标并分级。结果表明, RCP-rf情景下全省夏玉米花期高温发生频率在20.5%～81.0%(≥32℃)和3.9%～51.9%(≥35℃)。与基准条件相比,≥32℃高温发生频率增加9.1%(RCP4.5)和11.0%(RCP8.5),≥35℃高温发生频率增加8.7%(RCP4.5)和8.3%(RCP8.5)。RCP-rf情景下全省夏玉米花期高温积害在48.5～200.9℃·d(≥32℃)和9.8～138.5℃·d(≥35℃)。与基准条件相比,≥32℃高温积害增加25.4℃·d (RCP 4.5)和25.6℃·d (RCP 8.5),≥35℃高温积害增加25.8℃·d (RCP 4.5)和31.4℃·d (RCP 8.5)。由综合风险分析可知, RCP-rf情景下夏玉米花期高温灾害高值风险区主要分布在新乡、郑州、许昌、漯河、周口及其以东以北的地区(商丘除外),约占夏玉米主栽区面积的30.1%;RCP4.5情景下高值风险区扩大至洛阳和南阳以东的大部分地区,约占夏玉米主栽区面积的63.4%; RCP 8.5情景下高值风险区面积进一步向西扩大,约占夏玉米主栽区面积的占76.3%。     

Soil carbon change across ten New South Wales farms under different farm management regimes in Australia

This paper examines the potential influence of soil management and land use on soil carbon on cropping farms in New South Wales (NSW), Australia. Soil organic carbon (SOC) data from ten farms spatially distributed across NSW were examined on two occasions. Soil cores to a depth 0–30 cm were measured for SOC and, as expected, SOC in the A horizon (1.16%) was significantly (p < .001) greater than in the B horizon (0.74%) of all profiles. Analysis of the 2013 and 2015 SOC data indicated that in many ways, the results runs counter to other SOC studies in Australia. Importantly, the mean SOC concentration in these agricultural soils was significantly (p < .001) less under cropping (2013-1.05%, 2015-0.97%) than in native sites (2013-1.20%, 2015-1.16%). Out of the total of 35 sites sampled from 10 farms, SOC in 49% of sites did not change significantly over 2 years, in 17% it increased significantly, whereas in 34% it decreased. Further, a clear implication of drought on SOC was seen on sites that were uncropped based on a critical value for a 95% confidence interval (p < .05) and complemented by the significant correlation (p < .05) between average annual precipitation deficit (ANPD) and SOC across the state with R² = 0.39. The mean SOC was found to be directly proportional to standard deviation and standard error. In terms of spatial variability, the C0 (nugget) value was greatest for farms with a large mean SOC and the average variogram in this study has a range of approximately 200 m which is potentially useful in determining sampling spacing for soil carbon auditing purpose. Similar empirical data over more years are required to better estimate SOC levels and to determine whether at a farm scale, factors such as land management, land use and climate can be related to soil carbon change and variability.     

花椒叶黄酮含量的变化及其与气象因子的关系研究

采用超声波辅助提取法和紫外分光光度法分析测定了狮子头、美凤椒、秦安1号花椒叶片5-9月总黄酮含量。结果表明，不同品种的花椒叶片总黄酮含量存在差异（P＜0.05），表现出狮子头＞美凤椒＞秦安1号。花椒叶总黄酮存在显著的季节变化和年际变化（P＜0.05）。在生长季，6-8月总黄酮含量较高，狮子头、美凤椒和秦安1号平均含量分别为18.02、15.35、12.06 mg·g^-1。同时，花椒叶总黄酮含量与日照百分率、降水量和空气湿度相关显著（P＜0.05），与当月的日照百分率呈负相关，与上月的降水量和当月的空气湿度呈正相关。     

气候变化适应及其影响因素研究——山东胶州湾地区居民的实证分析

为探索气候变化感知在适应决策过程中的作用机理，本研究以深度访谈数据为基础，基于“感知－适应”分析框架，采用二元Probit模型和泊松回归模型，分析胶州湾地区居民气候变化适应决策和适应选择的影响因素。研究表明，胶州湾地区绝大多数居民已经感知到气候变化，半数以上居民采取了一定的适应措施，大多数居民对适应措施效果的感到满意。居民采取适应措施介于0-4项，平均为1.07项，适应措施的普及率和多样化仍有提升空间。影响胶州湾地区居民气候变化适应决策与适应选择的主要因素存在一定差异性，但“居民对气候变化的感知”不论是对适应决策还是对适应选择的影响都较大，其中又以“对降水变化的感知”和“对气象灾害损失的感知”最为显著。     

Variation in glomalin in soil profiles and its association with climatic conditions,shelterbelt characteristics,and soil properties in poplar shelterbelts of Northeast China

Glomalin-related soil protein(GRSP)sequesters large amounts of carbon and plays important roles in maintaining terrestrial soil ecosystem functions and ecological restoration;however,little is known about GRSP variation in 1-m soil profiles and its association with stand characteristics,soil properties,and climatic conditions,hindering GRSP-related degraded soil improvement and GRSP evaluation.In this study,we sampled soils from 1-m profiles from poplar(Populus spp.)shelterbelts in Northeast China.GRSP contents were 1.8–2.0 times higher in the upper 40 cm soil layers than at 40–100 cm.GRSP-related soil organic carbon(SOC)sequestration in deeper soil layers was*1.2 times higher than in surface layers.The amounts of GRSP-related nutrients were similar throughout the soil profile.A redundancy analysis showed that in both surface and deeper layers,soil properties(pH,electrical conductivity,water,SOC,and soil nutrients)explained the majority of the GRSP variation(59.5–84.2%);the second-most-important factor in GRSP regulation was climatic conditions(temperature,precipitation,and altitude),while specific shelterbelt characteristics had negligible effects(<5%).Soil depth and climate indirectly affected GRSP features via soil properties,as manifested by structural equation model analysis.Our findings demonstrate that GRSP is important for carbon storage in deep soils,regardless of shelterbelt characteristics.Future glomalin assessments should consider these vertical patterns and possible regulating mechanisms that are related to soil properties and climatic changes.     

基于CLIMEX和ArcGIS的灰茶尺蠖在中国的潜在适生区预测

基于中国820个气象站点数据、灰茶尺蠖已知地理分布资料和生物学数据,结合CLIMEX模型与ArcGIS软件模拟预测灰茶尺蠖在中国目前及未来的潜在分布范围,评估灰茶尺蠖的潜在分布范围及气候变暖对其分布的潜在影响。结果表明,灰茶尺蠖在中国目前的适生区主要分布在3°51′N~40°6′N,适生区面积占全国总面积的34.27%。中国大部分省份的气候条件均适合灰茶尺蠖种群生长。随着气候的变化,灰茶尺蠖在中国的潜在适生区面积总体增幅不大,但其组成变化较大。至2050年,预测灰茶尺蠖高度适生区面积占比达最大（22.23%）。相比各种能源之间的平衡情景（A1B）,较高能源需求情景（A2）下灰茶尺蠖在陕甘宁地区向内陆扩张更快。灰茶尺蠖在中国适生区分布广泛,应加强灰茶尺蠖预测预报,趁早采取防控措施,以保障茶叶优质安全生产。     

蔬菜中农药残留检测方法变更的验证方法探析

检测标准发生变更时,检验检测机构应做好新方法的验证工作。以水果和蔬菜中阿维菌素残留量测定标准变更为实例,详述了如何开展方法验证,以期为大家开展化学分析方法发生变更时的验证工作提供参考。     

Performance and uncertainty analysis of a short-term climate reconstruction based on multi-source data in the Tianshan Mountains region,China

Short-term climate reconstruction, i.e., the reproduction of short-term(several decades) historical climatic time series based on the relationship between observed data and available longer-term reference data in a certain area, can extend the length of climatic time series and offset the shortage of observations. This can be used to assess regional climate change over a much longer time scale. Based on monthly grid climate data from a Coupled Model Inter-comparison Project phase 5(CMIP5) dataset for the period of 1850–2000, the Climatic Research Unit(CRU) dataset for the period of 1901–2000 and the observed data from 53 meteorological stations located in the Tianshan Mountains region(TMR) of China during the period of 1961–2011, we calibrated and validated monthly average temperature(MAT) and monthly accumulated precipitation(MAP) in the TMR using the delta, physical scaling(SP) and artificial neural network(ANN) methods. Performance and uncertainty during the calibration(1971–1999) and verification(1961–1970) periods were assessed and compared using traditional performance indices and a revised set pair analysis(RSPA) method. The calibration and verification processes were subjected to various sources of uncertainty due to the influence of different reconstructed variables, different data sources, and/or different methods used. According to traditional performance indices, both the CRU and CMIP5 datasets resulted in satisfactory calibrated and verified MAT time series at 53 meteorological stations and MAP time series at 20 meteorological stations using the delta and SP methods for the period of 1961–1999. However, the results differed from those obtained by the RSPA method. This showed that the CRU dataset produced a low degree of uncertainty(positive connection degree) during the calibration and verification of MAT using the delta and SP methods compared to the CMIP5 dataset. Overall, the calibrated and verified MAP had a high degree of uncertainty(negative connection degree) regardless of the dataset or reconstruction method used. Therefore, the reconstructed time series of MAT for the period of 1850(or 1901)–1960 based on the CRU and CMIP5 datasets using the delta and SP methods could be used for further study. The results of this study will be useful for short-term(several decades) regional climate reconstruction and longer-term(100 a or more) assessments of regional climate change.     

Changes in the carbon concentrations and other soil properties of some Scottish agricultural soils: Evidence from a resampling campaign

The change in soil carbon (C) concentration, soil pH and major nutrients for approximately 1,000 topsoil sampled from on-farm experimental sites over a thirty-year period from 1950 to 1980 in north-east Scotland are summarized. This period coincided with increased agricultural intensification, which included regular liming and fertilizer additions. During 2017, 37 of these sites were resampled and reanlaysed. While pH and extractable phosphorus (P) and potassium (K) increased over this period, there was no detectable change in the percentage loss on ignition. Composite soil samples were taken by auger from a depth of 0–15 cm and compared with the corresponding archived samples collected at the initiation of each experiment. Analysis of these resampled soils indicated no significant change in soil carbon (C), although soil pH, extractable magnesium (Mg) and K and Nitrogen (N) concentrations were significantly greater (p < .001) but extractable soil P concentration was significantly less (p = .015) compared with the original samples. Even though measuring C concentration alone is a poor indicator of overall changes in soil C stocks, it does provide a relative quick “early warning” of C losses that would justify a more comprehensive measure of stocks.     

二氧化碳浓度升高对茶树生理代谢的影响及应对技术

大气中的二氧化碳(CO2)浓度升高是工业革命以来全球范围内最重要的生态变化之一,将直接影响植物的生长发育和代谢过程。尽管CO2浓度升高对粮食作物的影响已经得到了广泛的研究,但其对茶树等重要经济作物的影响却很少受到关注。本文回顾和总结了CO2浓度升高对茶树的初级代谢(包括光合作用、呼吸作用和碳氮代谢)和次级代谢的影响,并探讨了CO2浓度升高环境下茶叶生产过程中的应对技术,旨在为CO2浓度升高背景下茶树优质高产栽培提供一定的理论基础和科学依据。