基于"量-质-域-流"四维指标体系的水资源荷载状况评价——以黑河流域三地市为例

随着社会经济用水不断增加，水资源供需矛盾加剧，水资源系统出现荷载不均衡现象，制约了区域发展，危及生态环境良性循环。本文从水资源系统的负荷需求和承载能力出发，基于“量、质、域、流”四个维度构建水资源荷载均衡评价指标体系，采用指标规范化的正态云模型，评价2015年黑河流域张掖市、酒泉市、阿拉善盟水资源配置方案的荷载均衡状况，并依据负荷与承载能力评分二维坐标，分出低负荷-高承载能力、低负荷-低承载能力、高负荷-高承载能力和高负荷-低承载能力四个分区。评价结果表明：2015年三地水资源荷载状况均为Ⅳ级，张掖市综合评分为3.697，酒泉市为3.657，阿拉善盟为3.901，三地均处于高负荷-低承载能力区域；三地在水质维度上处于低负荷-高承载能力区间，水质维度评分均处于Ⅱ级，酒泉市水质评分优于张掖市，张掖市水质评分优于阿拉善盟；在水量、水域、水流维度上均处于高负荷-低承载能力区间，水量方面三地处于Ⅳ级，张掖市优于酒泉市，酒泉市优于阿拉善盟；水域方面张掖和阿拉善盟评分均处于Ⅴ级，酒泉评分处于Ⅳ级；水流方面三地均处于Ⅴ级。需要采取调控手段在水量、水域、水流方面上进行“增强承载”和“卸荷”。     

内蒙古高原紫花苜蓿土壤氮素丰缺指标和推荐施氮量

为了给内蒙古高原紫花苜蓿（Medicago sativa L.）测土施氮奠定科学基础，本研究采用“零散实验数据整合法”和“养分平衡-地力差减法”新应用公式，开展了该自然区域紫花苜蓿土壤氮素丰缺指标和推荐施氮量研究。结果表明：内蒙古高原生长第1年紫花苜蓿土壤碱解氮第1~6级丰缺指标为≥48，20~48，8~20，4~8，2~4和<2 mg·kg^-1，土壤全氮第1~5级丰缺指标为≥1.4，0.8~1.4，0.4~0.8，0.2~0.4和<0.2 g·kg^-1，土壤有机质第1~6级丰缺指标为≥17，10~17，6~10，3~6，2~3和<2 g·kg^-1。当紫花苜蓿目标产量9~18 t·hm^-2、氮肥利用率40%时，内蒙古高原紫花苜蓿第1~6级土壤推荐施氮量分别为0，68~135，135~270，203~405，270~540和338~675 kg·hm^-2。     

青海省祁连圆柏天然林单木生物量模型构建

利用祁连圆柏整株生物量与生长指标数据，为估算祁连圆柏林的生物量估算提供参考。通过野外调查，共获取了63株祁连圆柏天然林样木生物量与生长指标实测数据。用其中50株样木数据进行回归模拟，用其余的13株样木数据对模型可靠性进行检验，构建器官生物量与生长指标间的回归模型。结果表明，祁连圆柏单木水平下，树干生物量模型的R²_adj为0.96，均方根、模型有效性和残差系数分别为0.50、0.85和0.05；枝条生物量模型的R²_adj为0.897，均方根、模型有效性和残差系数分别为0.69、0.80和-0.66；叶生物量模型的R²_adj为0.61，均方根、模型有效性和残差系数分别为0.54、0.86和0.15；根生物量模型的R²_adj为0.93，均方根、模型有效性和残差系数分别为0.12、0.997 和-0.01。在调查数据范围内构建的模型较好地反映了祁连圆柏生物量与生长指标间的关系，形式简单、使用方便；与实测值相比，树干与叶生物量模拟值偏小，枝和根偏大。     

延迟收获对长江中游春玉米农艺性状及机收质量的影响

为探明长江中游玉米籽粒机械直收适宜品种与配套农艺措施，2018—2019年选用不同玉米品种，测定不同机收时间下玉米关键农艺性状、产量及机收质量指标。结果表明，收获时间对春玉米机收产量与机收质量均有显著影响。延迟1周收获后籽粒容重显著增加，机收产量显著提高，2年平均提高9.72%；而延迟2周收获则有降低机收产量的趋势。2年收获时杂质率总体≤3%，而机收籽粒破碎率与损失率均>5%，是该区域春玉米籽粒机收面临的主要问题。籽粒厚度、籽粒含水率和百粒重是影响机收籽粒破碎率的关键性状，三者与机收籽粒破碎率均呈显著的倒二次曲线关系；玉米的倒伏率、穗位高和重心高度是影响机收损失率的关键性状，倒伏率与机收损失率呈显著正相关，而穗位高和重心高度与机收损失率均呈显著的二次曲线关系。延迟收获能显著降低籽粒含水量，从而降低籽粒破碎率，但继续延迟收获有增加倒伏的风险。综上，长江中游春玉米成熟后适时延迟7~10 d收获，可有效降低籽粒含水量与机收籽粒破碎率，提高玉米籽粒机收产量。     

Determination of critical nitrogen dilution curve based on leaf area index for winter wheat in the Guanzhong Plain,Northwest China

Excessive use of nitrogen(N) fertilizers in agricultural systems increases the cost of production and risk of environmental pollution. Therefore, determination of optimum N requirements for plant growth is necessary. Previous studies mostly established critical N dilution curves based on aboveground dry matter(DM) or leaf dry matter(LDM) and stem dry matter(SDM), to diagnose the N nutrition status of the whole plant. As these methods are time consuming, we investigated the more rapidly determined leaf area index(LAI) method to establish the critical nitrogen(N_c) dilution curve, and the curve was used to diagnose plant N status for winter wheat in Guanzhong Plain in Northwest China. Field experiments were conducted using four N fertilization levels(0, 105, 210 and 315 kg ha-1) applied to six wheat cultivars in the 2013–2014 and 2014–2015 growing seasons. LAI, DM, plant N concentration(PNC) and grain yield were determined. Data points from four cultivars were used for establishing the N_c curve and data points from the remaining two cultivars were used for validating the curve. The N_c dilution curve was validated for N-limiting and non-N-limiting growth conditions and there was good agreement between estimated and observed values. The N nutrition index(NNI) ranged from 0.41 to 1.25 and the accumulated plant N deficit(N_(and)) ranged from 60.38 to –17.92 kg ha~(-1) during the growing season. The relative grain yield was significantly affected by NNI and was adequately described with a parabolic function. The N_c curve based on LAI can be adopted as an alternative and more rapid approach to diagnose plant N status to support N fertilization decisions during the vegetative growth of winter wheat in Guanzhong Plain in Northwest China.     

基于科技文献社会网络分析的"一带一路"科技情报安全研究

为明确中国在"一带一路"沿线国家所形成的科技网络中处于怎样的位置,面临怎样的科技情报风险,需要采取哪些措施维护中国科技情报安全,应用智库DIIS理论方法,对科学引文索引中2013年-2017年"一带一路"沿线国家论文合作数据进行社会网络分析,应用管理机制设计"七元组"理论开展科技情报安全机制设计。研究结果显示,中国科技情报的暴露程度较高,科技应用的不可控因素、知识产权保护的挑战、科技情报资源流失的风险同时存在,并与各种非传统安全问题相叠加。切实掌握核心技术,维护知识产权,加强政府、社会对科技交流的监管,防止科技情报被非法利用,是保障科技情报安全的主要途径。     

不同基因型燕麦苗期耐盐碱性分析 及其鉴定指标的筛选

为探讨不同基因型燕麦苗期的耐盐碱性，筛选适宜松嫩平原种植的燕麦品种，本研究采用Hoagland营养液水培法，以250 mmol·L^-1高浓度NaHCO₃胁迫模拟松嫩平原盐碱环境，对49份来自国内外不同地区的主栽燕麦品种进行研究。试验测定了250 mmol·L^-1 NaHCO₃胁迫下燕麦的株高（X₁）、根长（X₂）、地上部鲜重（X₃）、地下部鲜重（X₄）、地上部干重（X₅）、地下部干重（X₆）、地上部含水量（X₇）、地下部含水量（X₈）、根冠比（X₉）9个指标，以各单项指标的耐盐碱系数(SATC) 作为衡量耐盐碱性的依据，利用多元分析方法对不同燕麦品种耐盐碱能力进行了综合评价。结果表明：通过对各指标的耐盐碱系数进行主成分分析，得到X₄、X₇、X₈ 3个综合指标，涵盖了全部数据86.155%的信息量；通过隶属函数分析和聚类分析将49份燕麦品种分为3类，其中草莜1号、张燕7、T7等3个品种为耐盐碱品种，HLJ 1、白燕2号等41个品种为中度耐盐碱品种，三分三、坝莜13号等5个品种为盐碱敏感品种。     

Impact of land‐use intensity on the relationships between vegetation indices,photosynthesis and biomass of intensively and extensively managed grassland fens

Vegetation indices are widely used as model inputs and for non‐destructive estimation of biomass and photosynthesis, but there have been few validation studies of the underlying relationships. To test their applicability on temperate fens and the impact of management intensity, we investigated the relationships between normalized difference vegetation index (NDVI), leaf area index (LAI), brown and green above‐ground biomass and photosynthesis potential (PP). Only the linear relationship between NDVI and PP was management independent (R² = 0·53). LAI to PP was described by a site‐specific and negative logarithmic function (R² = 0·07–0·68). The hyperbolic relationship of LAI versus NDVI showed a high residual standard error (s.e.) of 1·71–1·84 and differed between extensive and intensive meadows. Biomass and LAI correlated poorly (R² = 0·30), with high species‐specific variability. Intensive meadows had a higher ratio of LAI to biomass than extensive grasslands. The fraction of green to total biomass versus NDVI showed considerable noise (s.e. = 0·13). These relationships were relatively weak compared with results from other ecosystems. A likely explanation could be the high amount of standing litter, which was unevenly distributed within the vegetation canopy depending on the season and on the timing of cutting events. Our results show there is high uncertainty in the application of the relationships on temperate fen meadows. For reliable estimations, management intensity needs to be taken into account and several direct measurements throughout the year are required for site‐specific correction of the relationships, especially under extensive management. Using NDVI instead of LAI could reduce uncertainty in photosynthesis models.     

基于数据包络分析模型下的食用菌产业发展策略

为了科学评价食用菌产业发展策略的有效性,建立了食用菌产业发展策略DEA效率评价指标体系,以食用菌产业发展策略中的一系列投入型策略作为输入指标,以食用菌企业的规模、消费者满意度、科技创新能力和市场竞争力等各种产出效益和效果作为输出指标,采用DEA评价方法对食用菌产业的发展策略的效率进行模拟评价。评价结果显示,对食用菌发展策略产生影响的各种因素是有效的,结果也为为食用菌发展策略的资源投入方向和数量提供了参考。     

The Use of a Metabolic Disorder Index as a Predictor for Metabolic Eliminations in Endurance Horses

The equine endurance race involves both aerobic and anaerobic metabolisms of the horse. The intense physical activity over an extended period often causes susceptible horses to develop metabolic signs or problems resulting in elimination from races. Thus, the objective of this study was to develop a method for prediction and validation of a metabolic disorder index (MDI) to be used before endurance races. Three hundred seventy-five Arabian (n = 152) and Arabian cross (n = 223) endurance horses aged from 6 to 15 years and weighing between 350 and 450 kg were selected for the study in Malaysia. Blood samples were collected at pre- and post-race periods. The significant (P < .05) findings in horses with metabolic disorder were packed cell volume (0.50 ± 0.06 LL−1), creatine kinase (1,275.89 ± 121.45 UL−1), interleukin-6 (2.01 ± 0.89 ng/mL), decreased glutathione reductase (26.57 ± 3.95 ng/mL), and chloride (94.98 ± 8.12 mmol/L). A new method called MDI was developed as a predictor for horses with the potential to develop metabolic disorders in endurance races. The MDI indicated a higher value greater than 5.5 for those eliminated and lower value below 5.5 for those that completed the race successfully, this proved to be accurate in the prediction of metabolic disorder in endurance horses. The MDI is an innovative and simple method used as a prediction method that will assist the equine endurance society to reduce the rate of elimination and to safeguard against serious medical problems during endurance races in the tropics.