景谷县森林蓄积量遥感估测及其动态变化分析

以云南省景谷县为研究区,基于Landsat5和Landsat8遥感数据,利用2012年和2017年两期全国森林资源连续清查实地调查数据,建立多元逐步回归和随机森林模型对景谷县森林蓄积量进行遥感估测对比研究。结果显示:综合建模精度来看,随机森林法在相同样地数量条件下具有更好的估测效果;从估测结果与林地保护利用规划和林地变更数据结果相比较,随机森林法估测值接近真实值,估测精度较高。     

基于GF-1和Sentinel-2时序数据的茶园识别

由于茶园大多分布在地形复杂的山区,地块破碎,分布零散,形状差异大、植被混杂且茶园所处环境长期受到云雨的影响,增加了茶园遥感识别的难度与不确定性,针对这一问题,该研究提出了利用高分1号(GF-1)和哨兵2号(Sentinel-2)时序数据提取茶园的方法,以浙江省武义县王宅镇为研究区,采用GF-1号为主要数据源,并利用MODIS地表反射率产品和Sentinel-2反射率数据,基于时空融合算法得到时间分辨率5 d的10 m Sentinel-2完整的时序数据。综合利用GF-1在空间细节方面的优势和重建的Sentinel-2高观测频率时序数据在反映茶树生长过程方面的优势,分别基于GF-1的光谱和纹理特征及GF-1的光谱、纹理特征和Sentinel-2时序特征两种特征组合方式,采用随机森林算法提取茶园。结果表明,GF-1光谱、纹理信息结合Sentinel-2时序信息分类结果的准确率、错误率、精确率、召回率和F1分数分别为96.91%、3.09%、89.00%、83.09%和0.86,仅基于GF-1光谱和纹理信息的分类准确率、错误率、精确率、召回率和F1分数分别为94.72%、5.28%、73.09%、84.61%和0.78,添加时序信息分类结果总体优于未添加时序信息的分类结果。表明高空间分辨率结合高频率时序遥感数据是提高茶园分类精度的有效手段。     

两种光照下低海拔引种云锦杜鹃的光合作用日变化

以移栽的野生云锦杜鹃Rhododendron fortunei为材料,使用LI-6400便携式光合作用仪,分析10%光照和全光照下低海拔区域引种云锦杜鹃的光合日变化,结果显示10%光照下生长的云锦杜鹃蒸腾速率低于全光照下生长的云锦杜鹃,而水分利用效率高于全光照下云锦杜鹃的60.17%。两种光照下的云锦杜鹃净光合速率和蒸腾速率日变化呈现"单峰"型。全光照下净光合速率下降是非气孔限制引起的,而10%光照下则为气孔限制引起。研究说明种植在低海拔环境的云锦杜鹃喜光的特性并不因为温度高而改变,但夏季遮荫措施还是有必要的。     

湖北三峡库区晚熟脐橙不同海拔果实品质变化及枯水防控技术研究

以湖北三峡库区秭归地区不同海拔伦晚脐橙（Citrus sinensis Osbeck ‘Lane late’ Navel）果实为试验材料，探讨了湖北三峡库区晚熟脐橙果实枯水防控栽培技术，进行了晚熟脐橙种植区域布局研究，结果表明，在湖北三峡库区，江南晚熟脐橙适宜区域化种植在海拔360 m以下，江北在海拔350 m以下。在适宜范围外，随海拔升高，晚熟脐橙果实品质下降，可食率、果汁率降低，酸下降快，化渣性变差，果实枯水加重。其次，探讨了晚熟脐橙果实枯水防控生产技术，冬季套袋试验效果好，果实枯水比率控制在5%以下，显著低于对照果实（枯水率50%），可有效减轻和防止晚熟脐橙果实枯水，而且套袋果实外观好，品质优。覆膜技术效果其次，果实枯水比率可以控制在20%以下，而且该技术简便、劳动量小且成本较低，可以在生产中应用。     

Screening and identification of soybean varieties with high phosphorus efficiency at seedling stage

In order to simplify the workload and find a reliable method for screening soybeans with different phosphorus(P)efficiencies,47 soybean varieties were screened from 90 varieties according to yield under normal phosphorus,and 10 indicators including root phenotype,phosphorus utilization efficiency at the seedling stage and yield were measured.Through single-index cluster analysis,the performance value and relative value of the abovementioned indexes under low-phosphorus conditions were analyzed,and then,the combined indexes were analyzed by principal components method.The membership function method and the cluster analysis method was used to calculate and analyze the comprehensive score value.Three indexes of root P utilization efficiency(X₁),relative value of root P utilization efficiency(X₂),and root volume(X₃)under low P at the seedling stage were selected as the most consistent with the yield screening results under low P condition,and the mathematical model of the comprehensive score value was obtained:D=1.218X₁t 0.320X₂t 0.007X₃-0.664(P=0.000,R²=1.000).The comprehensive score can screen and identify the P efficiency of soybeans with fewer indexes in the early growth stages,which provides a more rapid and reliable mathematical model for screening and identifying a larger number of germplasm resources for P efficiency.     

不同氮效率油菜种质苗期氮吸收转运与利用差异研究

氮效率研究是油菜营养性状遗传改良的前提,为探究不同氮效率油菜种质苗期氮吸收、转运和利用的异同,以2个氮效率差异油菜种质H6（氮高效）和L18（氮低效）为供试材料,利用水培营养液设置正常氮（CK）和低氮（LN）2个氮浓度处理,培养14d后检测植株氮含量,计算氮累积量、氮转运系数和氮利用效率。结果显示,不同氮浓度处理对油菜苗期氮的吸收、转运和利用效率影响的差异达到极显著水平（P＜0.01）。与CK相比,LN处理的油菜生物量、氮含量和氮累积量均显著降低,而氮利用效率和根冠比显著提高;氮高效油菜种质H6的生物量、氮累积量、氮转运系数和氮生理利用效率均显著大于氮低效种质L18,分别为L18的2.07、1.42、3.23和1.56倍。从氮的吸收、转运和利用3个方面探讨了低氮胁迫处理下油菜种质苗期氮效率差异的原因,对深入开展油菜氮高效机理研究及油菜品种氮效率改良具有一定的指导意义。     

Estimation of biomass change in montane forests in Norway along a 1200 km latitudinal gradient using airborne laser scanning: a comparison of direct and indirect prediction of change under a model-based inferential approach

The current study compared two approaches for estimating change of aboveground biomass (AGB) in montane forests in Norway using field- and remotely sensed data from airborne laser scanning (ALS) from two points in time (four-year interval). The first was an indirect method that involved modeling and prediction of AGB at two points in time using ALS metrics as predictors, estimating the change from differences between AGB predictions. The second was a direct method, where change was modeled and predicted directly using differences between corresponding ALS metrics derived at the two measurement occasions as predictors, and the estimate was based on the predicted differences. Both methods were applied over a 1500?km long and 250?m wide transect from south to north in Norway comprising 250?m² grid cells. The results showed that the indirect method was more precise than the direct method. The indirect method estimated 0.65?Mg?ha^?1 change in AGB over the observation period, with a corresponding 95% confidence interval of ±0.27?Mg?ha^?1. The corresponding figures for the direct method was 0.54 and ±0.51?Mg?ha^?1. The direct method has been recommended previously. We conclude that the indirect method is both more precise and versatile.     

基于温度植被干旱指数的兖州煤田煤炭开采影响边界遥感提取

为识别植被覆盖区煤炭开采的生态影响边界,该文以兖州煤田为研究区域,应用温度植被干旱指数TVDI(temperature vegetation drought index)反演沉陷积水区外围的土壤湿度空间分布特征,利用MATLAB拟合TVDI变化趋势并依据其趋于稳定的渐近线,反解煤炭开采活动对矿区生态的影响边界,将其与采用MSCS(mining subsidence prediction system,MSCS)软件预计获得的下沉10 mm沉陷边界进行对比。结果表明:不同距离的TVDI中位数随距积水区边缘距离的变化表现为先增加后趋于平稳、呈指数变化特征;基于TVDI分析得到的煤炭开采的非积水影响范围,仅相当于沉陷积水面积的2.07倍,预计沉陷非积水面积与预计沉陷积水面积之比为4.63倍。通过模型拟合遥感指数随距离的变化特征,能够获得煤炭开采的影响边界;兖州煤田基于TVDI获取的煤炭开采影响面积,相对小于预计的开采沉陷面积。该研究可为确定煤炭开采对生态影响的边界提供参考。     

细菌群体感应抑制剂研究进展

多重耐药菌的出现已成为农业防治植物病害的一大难题，目前急需发展新的防治策略。群体感应 (quorum sensing, QS) 是一种微生物之间普遍存在的依赖于菌体密度的沟通协调机制，控制着细菌的生长、增殖、致病性、生物被膜形成及相关群体活动行为。群体感应抑制剂在抑制细菌毒性基因表达时不会对细菌生长产生压力，从而避免了细菌耐药性的产生。这一新颖的抑菌机制使其在开发新型农药方面有很大潜力。本文着重介绍了细菌群体感应机制、天然的及合成的细菌群体感应抑制剂种类及其应用。     

Comparison of estimators and feature selection procedures in forest inventory based on airborne laser scanning and digital aerial imagery

Digital maps of forest resources are a crucial factor in successful forestry applications. Since manual measurement of this data on large areas is infeasible, maps must be constructed using a sample field data set and a prediction model constructed from remote sensing materials, of which airborne laser scanning (ALS) data and aerial images are currently widely used in management planning inventories. ALS data is suitable for the prediction of variables related to the size and volume of trees, whereas optical imagery helps in improving distinction between tree species. We studied the prediction of forest attributes using field data from National Forest Inventory complemented with ad hoc field plots in combination with ALS and aerial imagery data in Aland province, Finland. We applied feature selection with genetic algorithm and greedy forward selection and compared multiple linear and nonlinear estimators. Maximally around 40 features from a total of 154 were required to achieve the best prediction performances. Tree height was predicted with normalized root mean squared error value of 0.1 and tree volume with a value around 0.25. Predicting the volumes of spruce and broadleaved trees was the most challenging due to small proportions of these tree species in the study area.