Impact of climate change on maize yield in China from 1979 to 2016

Climate change severely impacts agricultural production, which jeopardizes food security. China is the second largest maize producer in the world and also the largest consumer of maize. Analyzing the impact of climate change on maize yields can provide effective guidance to national and international economics and politics. Panel models are unable to determine the group-wise heteroscedasticity, cross-sectional correlation and autocorrelation of datasets, therefore we adopted the feasible generalized least square(FGLS) model to evaluate the impact of climate change on maize yields in China from 1979–2016 and got the following results:(1) During the 1979–2016 period, increases in temperature negatively impacted the maize yield of China. For every 1°C increase in temperature, the maize yield was reduced by 5.19 kg 667 m–2(1.7%). Precipitation increased only marginally during this time, and therefore its impact on the maize yield was negligible. For every 1 mm increase in precipitation, the maize yield increased by an insignificant amount of 0.043 kg 667 m–2(0.014%).(2) The impacts of climate change on maize yield differ spatially, with more significant impacts experienced in southern China. In this region, a 1°C increase in temperature resulted in a 7.49 kg 667 m–2 decrease in the maize yield, while the impact of temperature on the maize yield in northern China was insignificant. For every 1 mm increase in precipitation, the maize yield increased by 0.013 kg 667 m–2 in southern China and 0.066 kg 667 m–2 in northern China.(3) The resilience of the maize crop to climate change is strong. The marginal effect of temperature in both southern and northern China during the 1990–2016 period was smaller than that for the 1979–2016 period.     

数值模型结构不确定性对模拟结果的影响分析

以内蒙古鄂托克旗为例,基于GMS中的MODFLOW模块构建了地下水流数值模拟模型,分析了模型结构(含水层厚度、参数分区)与模型参数不确定性因素对模拟结果的影响.研究结果表明:含水层不确定情景(含水层下边界概化为隔水底板平均值870 m)与实际情况水头差值绝对值的累计和最大为701 m,对模拟结果起了主控作用;当含水层下边界概化为910,940 m时,累计和分别增加为1 013,1 593 m;与仅考虑单个不确定性因素相比,同时考虑模型参数与含水层不确定情景累计和最大为738 m,同时考虑参数分区与含水层不确定情景累计和最大为791 m.因此,在构建地下水流数值模拟模型时,应优先考虑含水层空间结构概化的合理程度,同时考虑多个不确定性因素对模拟结果的综合影响,使地下水数值模拟模型能更精确地反映真实的地下水流状况.     

王正非林火蔓延模型改进研究

王正非林火蔓延模型是目前国内比较先进的森林火灾蔓延模型,但是由于林火行为的复杂性,此模型在准确率和普适性方面仍存在许多不足。本文结合已有的成果进一步改进王正非模型,增加了可燃物湿度对林火蔓延速度的影响,改进了林火初始速度的计算方式。针对各种坡度对林火蔓延行为的影响给出了一个计算公式。与改进前相比,改进后的模型使其对林火蔓延情况的预估更为精准。     

Establishing an eyeball-weight relationship for Litopenaeus vannamei using machine vision technology

This study aimed to establish a shrimp eyeball-weight relationship model for Litopenaeus vannamei using machine vision technology. A total of 295 shrimp were sampled from a recirculating aquaculture system (RAS). The long-axis length (d), body length (L), and body weight (W) of each individual was measured. The long axis length of the shrimp eyeball was identified and measured using machine vision technology. Continuous fitting and piecewise fitting models were used to construct the eyeball-weight relationship model for L. vannamei. The continuous fitting relationship model was described as: W = 38.865d^2.7914, while the piecewise model was described as: d < 2 mm, W = 0.0326d^3.7363, R² = 0.9288; 2 mm ≤ d < 3.9 mm, W = 0.0401d^3.104, R² = 0.9629; 3.9 mm ≤ d < 5.8 mm, W = 0.0421d^3.0311, R² = 0.9216; 5.8 mm < d, W = 0.103d^2.6226, R² = 0.9457. The root mean square error (RMSE) of the piecewise fitting model (0.0244, 0.1575, 0.5034, 0.7072) was smaller than the continuous fitting model (0.8229). The correlation coefficient (R²) of the piecewise model (0.9288, 0.9629, 0.9216, and 0.9457) was similar to that of the continuous fitting model (R² = 0.9621). The results indicated that the piecewise fitting model is suitable for calculating the biomass of L. vannamei in RAS and provides a novel way of estimating the biomass of L. vannamei cultured in RAS. The piecewise fitting model can also provide the foundation of evaluating the production of shrimp using underwater image recognition in intelligent aquaculture systems.     

Cohort‐specific variation in juvenile coho salmon habitat use

In this study, we examined summer and fall freshwater rearing habitat use by juvenile coho salmon (Oncorhynchus kisutch) in the quickly urbanising Big Lake drainage in south‐central Alaska. Habitat use was assessed by regressing fish count data against habitat survey information across thirty study sites using generalised linear mixed models. Habitat associations were examined by age‐0 and age‐1+ cohorts separately, providing an opportunity to compare habitat use across different juvenile coho salmon life stages during freshwater rearing. Regression results indicated that the age‐0 cohorts were strongly associated with shallow, wide stream reaches with in‐stream vegetation, whereas age‐1+ cohorts were associated with deeper stream reaches. Furthermore, associations between fork length and habitat characteristics suggest cohort‐specific habitat use patterns are distinct from those attributable to fish size. Habitat use information generated from this study is being used to guide optimal fish passage restoration planning in the Big Lake drainage. Evidence for habitat use partitioning by age cohort during freshwater juvenile rearing indicates that pooling age cohorts into a single “juvenile” stage for the purposes of watershed management may mask important habitat use dynamics.     

中国粮食进口安全综合评价研究——基于超效率DEA模型

在对粮食及粮食进口安全内涵加以界定的基础上,从粮食数量、粮食质量、粮食价格、粮食贸易、国家经济、生态环境6个方面分析中国粮食进口安全的影响因素,基于超效率DEA模型构建中国粮食进口安全评价模型。对1992—2015年中国粮食进口安全状况进行评价,结果表明,1992—2015年中国粮食进口处于安全状态,粮食进口对我国粮食价格安全和生态安全的影响程度较小,对数量安全、质量安全、贸易安全和经济安全的影响程度较大。     

落叶松人工林地位指数级导向曲线模型的研究

本文用约1000块样地资抖,系统地研究了黑龙江省落叶松人工林的地位指数级导向曲线模型。通过林业统计分析软件Statistica6.0对各落叶松人工林数据进行拟合、分析比较,结果为：从拟合精度、曲线走向与散点分布趋势、残差分布等综合考虑,舒马切尔曲线函数比较适合落叶松人工林地位指数级导向曲线模型的拟合。     

复合图书馆的信息服务探讨

复合图书馆作为图书馆的一种发展形态，有其自身的特点和要求，有许多值得研究的内容。复合图书馆的读者服务工作是图书馆工作的出发点和各项业务工作的最终价值体现。文章分析了目前图书馆读者服务工作面临的形势，探讨了我们应采取的措施。     

黄淮夏大豆超高产育种模式的探讨

通过不同品种（系）和密度的超高产栽培试验，分析四因子和二因子的产量效应，各因子对产量贡献的大小为：亩荚数＞百粒重＞荚粒数。超高产育种和栽培的主攻方向是提高亩荚数，同步增加百粒重。黄淮超高产育种模式：亩荚数４６．７±５．３万，百粒重２２．４±２．６克，每荚粒数２．１８±０．１１个。     

大豆灰斑病Fuzzy测报模型

本文运用模糊数学理论建立了大豆灰斑病预测预报模型。经对国营350农场种植的大豆中熟品种“合丰25”十年的资料拟合,符合率达90%,对中熟品种“黑农26”九年的资料拟合,符合率达89%,对早熟品种“黑河3号”九年的资料拟合,符合率达78%。