昆山地区典型池塘虾蟹混养模式对水环境的影响

虾蟹混养是昆山地区主要的池塘养殖模式。为深入研究虾蟹混养式养殖尾水对水环境的影响,对典型养殖区锦溪镇南前村的600×667 m~2虾蟹养殖基地的水源、池水和尾水在2012—2014年养殖期间的水质指标pH、亚硝酸盐、氨氮、总氮、总磷、COD监测。结果表明:在不同季节水源、池水和尾水的pH变化较大,变动范围在7.08~9.26之间;亚硝酸盐和氨氮浓度均处于很低的水平,优于地表水环境标准Ⅲ类水质标准,养殖尾水的氨氮浓度通常较水源和池水更低;除总氮和COD在2014春季高于水源外,其余年份各季节总氮、总磷和COD均接近或低于水源水指标值。除COD外,各项水质指标均符合太湖流域池塘养殖水排放一级标准,且呈现为低于或接近养殖用水源水的水质指标,可以认为池塘虾蟹混养模式对外部水环境影响很小。尾水排放前应加强对COD的控制。     

新疆红花地方种种子含油率与主要农艺性状间的灰色关联分析

为了新疆红花地方种高油品种的选育和改良提供科学数据,本研究采用灰色关联分析法,在新疆农业科学院综合试验场对来自新疆的51份红花材料的种子含油率与主要农艺性状进行分析。结果表明,新疆红花地方种的种子含油率与12个主要农艺性状的关联顺序为单株果球数>株高>三级有效分枝数>顶果球着粒数>节间长度>皮壳率>千粒重>生育期>一级有效分枝数>二级有效分枝数>分枝总数>节间数,表明单株果球数、株高、三级有效分枝数是影响新疆红花地方种种子含油率的重要因素。因此,在新疆红花地方种培育高油品种时,应优先考虑单株果球数,株高和三级有效分枝数等指标。本研究结果为培育高油红花提供科学参考数据。     

Predicting the potential geographic distribution of Bactrocera bryoniae and Bactrocera neohumeralis(Diptera: Tephritidae) in China using MaxEnt ecological niche modeling

Bactrocera bryoniae and Bactrocera neohumeralis are highly destructive and major biosecurity/quarantine pests of fruit and vegetable in the tropical and subtropical regions in the South Pacific and Australia. Although these pests have not established in China, precautions must be taken due to their highly destructive nature. Thus, we predicted the potential geographic distribution of B. bryoniae and B. neohumeralis across the world and in particular China by ecological niche modeling of the Maximum Entropy(Max Ent) model with the occurrence records of these two species. Bactrocera bryoniae and B. neohumeralis exhibit similar potential geographic distribution ranges across the world and in China, and each species was predicted to be able to distribute to over 20% of the globe. Globally, the potential geographic distribution ranges for these two fruit fly species included southern Asia, the central and the southeast coast of Africa, southern North America, northern and central South America, and Australia. While within China, most of the southern Yangtze River area was found suitable for these species. Notably, southern China was considered to have the highest risk of B. bryoniae and B. neohumeralis invasions. Our study identifies the regions at high risk for potential establishment of B. bryoniae and B. neohumeralis in the world and in particular China, and informs the development of inspection and biosecurity/quarantine measures to prevent and control their invasions.     

基于适宜性与发展水平评价的村庄用地类型划分

科学划分村庄用地类型并提出差异化的整治策略,是编制村庄发展规划和建设用地减量规划的基础。该文以北京市密云区为例,基于土地利用、兴趣点和社会统计等数据,从自然条件和用地形态2方面构建村庄用地适宜性评价模型,从区位条件、基础设施、生态条件和资源产业4方面构建村庄发展状况评价模型,系统分析村庄用地适宜性与村庄发展状况及其二者的组合状态,进而划分村庄用地类型。结果表明:1)密云区村庄用地适宜性呈现明显的从西南到东北降低的分布趋势;2)村庄发展指数较高的村庄主要分布在西南区域的环密云城区一带,其次是中部围绕密云水库区域,北部区域村庄发展水平较低;3)基于二者的评价结果将全区村庄用地划分为9种组合,进而合并为4种村庄用地类型。该研究可为村庄用地的高效、有序整治利用提供依据。     

基于产量反应的东北一季稻推荐施肥方法的可行性

  【目的】  推荐施肥是提高作物产量和肥料利用率的有效措施。基于产量反应的养分专家系统 (Nutrient Expert for Rice，NE) 易于操作，便于推广。通过大量田间试验，验证了其在东北一季稻上的应用效果。  【方法】  于2013—2018年在东北水稻主产区黑龙江省和吉林省共开展了115个田间试验，每个试验包括6个处理:1) 基于水稻养分专家系统推荐施肥处理 (NE)；2) 农民习惯施肥措施处理 (FP)；3) 基于测土配方施肥或当地农技部门推荐施肥的处理 (ST)；4)～6) 分别为基于NE的不施氮 (N)、不施磷 (P) 和不施钾 (K) 处理，用于计算养分利用率。水稻收获期调查产量，依据肥料成本，计算净效益和肥料利用率。  【结果】  NE、FP和ST处理间的水稻产量无显著差异 (P = 0.185)，但以NE处理的产量较高，平均为9068 kg/hm2，与FP和ST处理相比，分别增加了344和196 kg/hm2，其产量差随着NE系统不断优化趋于稳定。虽然NE处理的肥料成本 (TFC) 最高，但其净效益 (GRF) 比FP和ST处理分别高1043和537元/hm2，这部分效益都来自于产量的增量。养分回收率 (RE) 均以NE处理最高，与FP和ST处理相比，氮素回收率分别提高了3.3和2.3个百分点，磷素回收率分别提高了3.5和3.6个百分点，钾素回收率分别提高了7.3和4.6个百分点。与FP处理相比，NE处理的氮和磷的农学效率 (AE) 分别显著提高2.7 kg/kg (P = 0.022) 和4.1 kg/kg(P = 0.030)，3个处理的钾素农学效率无显著差异。肥料偏生产力 (PFP) 的大小与施肥量呈显著负相关，NE和ST处理N的偏生产力显著高于FP处理 (P = 0.004)，ST处理磷素偏生产力显著高于NE和FP处理 (P = 0.001)，但FP处理钾素偏生产力高于NE和ST处理，并与NE处理差异达到了显著水平 (P = 0.028)。  【结论】  与以常规测土施肥为基础的推荐施肥相比，基于产量反应的养分专家系统 (NE系统) 的推荐施肥量和比例更符合作物对养分的需求，在吉林和黑龙江两个省份的大田试验中均获得了相同或更高的水稻产量。由于NE系统无论是否进行土壤测试都可用来进行推荐施肥，因而是更加方便和可行的一季稻施肥推荐方法。     

Biochar addition mitigates nitrogen loss induced by straw incorporation and nitrogen fertilizer application

Biochar has been shown to be potentially beneficial for enhancing yields and soil properties, and diminishing nitrogen (N) losses. However, it remains unclear how biochar regulates soil carbon (C) and N to mitigate N losses induced by straw mixing with N fertilizer in dryland soils. Therefore, we investigated the effects of straw mixing (S₁), S₁ with biochar (SB) and no straw inputs (S₀), and routine urea application rates (N₁) and 70% of routine rates (N_0.7) on yields and N losses, and identify the relationship between N losses and soil C and N compounds. Results showed that N_0.7 and N₁ were suitable for the maize and wheat seasons, respectively, contributing to mitigating N losses without reducing crop yields. Moreover, in the maize season, N_0.7-SB significantly mitigated the straw-induced NH₃-N and N₂O-N emissions by 106% and 81%, respectively. In the wheat season, N₁-SB reduced the straw-induced NH₃-N and N₂O-N emissions by 35% and 66%, respectively. In addition, N_0.7-SB sharply reduced soil inorganic N (SIN) storage in the maize season. Furthermore, the NH₃-N and N₂O-N emission rates were negatively correlated with dissolved organic carbon/SIN content (0–20 cm) (DOC/SIN_0-20). N losses (N₂O-N and NH₃-N emissions and SIN storage) were positively correlated with SIN_0-20, but negatively correlated with soil organic carbon / SIN_0-20 (SOC/ SIN_0-20). This study provides further evidence that biochar with an appropriate N application rate decreased SIN_0-20 and increased DOC/SIN_0-20, thus reducing SIN storage and the straw-induced gaseous N emissions without decreasing crop yields.     

Deep neural network algorithm for estimating maize biomass based on simulated Sentinel 2A vegetation indices and leaf area index

Accurate estimation of biomass is necessary for evaluating crop growth and predicting crop yield.Biomass is also a key trait in increasing grain yield by crop breeding.The aims of this study were(i)to identify the best vegetation indices for estimating maize biomass,(ii)to investigate the relationship between biomass and leaf area index(LAI)at several growth stages,and(iii)to evaluate a biomass model using measured vegetation indices or simulated vegetation indices of Sentinel 2A and LAI using a deep neural network(DNN)algorithm.The results showed that biomass was associated with all vegetation indices.The three-band water index(TBWI)was the best vegetation index for estimating biomass and the corresponding R2,RMSE,and RRMSE were 0.76,2.84 t ha−1,and 38.22%respectively.LAI was highly correlated with biomass(R2=0.89,RMSE=2.27 t ha−1,and RRMSE=30.55%).Estimated biomass based on 15 hyperspectral vegetation indices was in a high agreement with measured biomass using the DNN algorithm(R2=0.83,RMSE=1.96 t ha−1,and RRMSE=26.43%).Biomass estimation accuracy was further increased when LAI was combined with the 15 vegetation indices(R2=0.91,RMSE=1.49 t ha−1,and RRMSE=20.05%).Relationships between the hyperspectral vegetation indices and biomass differed from relationships between simulated Sentinel 2A vegetation indices and biomass.Biomass estimation from the hyperspectral vegetation indices was more accurate than that from the simulated Sentinel 2A vegetation indices(R2=0.87,RMSE=1.84 t ha−1,and RRMSE=24.76%).The DNN algorithm was effective in improving the estimation accuracy of biomass.It provides a guideline for estimating biomass of maize using remote sensing technology and the DNN algorithm in this region.     

新乡贤队伍建设与乡村振兴:来自绍兴的调查与研究

作为"乡贤研究会"首创之地和"新乡贤"概念诞生之地,绍兴市自然也是新乡贤队伍建设的先行之地,已经成为全国乡贤文化之乡和新乡贤队伍建设的标杆。绍兴市的新乡贤队伍建设,肇始于2001年上虞乡贤研究会的成立,在2015年的乡贤政策年臻于高峰。经过多年培育和发展,定位为"村民自治的有益补充"、起"补位和辅助作用"的近2万新乡贤队伍,在乡村经济、文化、公益、自治等方面发挥着积极作用,但与此同时也显现了新乡贤队伍建设流于形式、结构相对失衡,以及党政介入过度、党政机构与新乡贤组织职责和权力边界不清晰等问题。解剖这一领先全国的典型个案,对于其他地区的新乡贤队伍建设和现代乡村振兴,无疑具有较好的理论意义和现实价值。     

基于有限混合模型的山东海域口虾蛄群体体长结构分析

个体大小是渔业资源种群的重要结构特征,一般研究中采用平均个体体长或平均体质量等分析指标,难以充分反应具有多年龄结构和个体生长速度差异的种群组成差异。为研究口虾蛄个体大小组成的时空变化,实验根据山东海域2016年10月和2017年1、5、8月的底拖网调查数据,应用有限混合模型分析了不同性别、不同时间、不同水深口虾蛄个体大小的频率分布特征。结果发现,除秋季外,山东海域口虾蛄均可区分为高、低两个年龄组,同时雌雄体长分布具有一定的差异。从冬季到夏季,雌性口虾蛄中低龄组个体比例先下降后上升,雄性口虾蛄低龄比例则逐渐下降。就不同水深而言,口虾蛄低龄组个体主要集中在近海海域,其比例由近海向远海逐渐减小。各年龄组的近远海分布表现出季节性差异,春季高龄口虾蛄在近海比例最大,由近海向远海比例逐渐减小;夏季高龄组口虾蛄在20～30 m水深比例最大;冬季高龄组口虾蛄比例则由近海向远海逐渐增加。有限混合模型能够较好地对口虾蛄的体长结构进行分析,解析口虾蛄不同年龄组在山东海域的时空分布,对于深入了解口虾蛄种群分布动态和科学的渔业管理具有重要意义。