Urban density does not impact tree growth and canopy cover in native species in Melbourne,Australia

Trees provide multiple ecosystem services in urban centers and increases in tree canopy cover is a key strategy for many municipalities. However, urban trees also experience multiple stresses and tree growth can be impacted by urban density and impervious surfaces. We investigated the impact of differences in urban form on tree growth in the City of Merri-bek, a local government area in metropolitan Melbourne, which is the temperate climate zone. Merri-bek has a gradient in population density and urban greenness from north to south, and we hypothesized that tree growth in the southern areas would be lower because trees were more likely to have less access to water with high levels of impervious surfaces. We selected three common native evergreen species, Eucalyptus leucoxylon, Melaleuca linariifolia, and Lophostemon confertus that exhibit differences in climate vulnerability and assessed the tree canopy expansion in four urban density zones in Merri-bek between 2009 and 2020 using aerial image analysis. The differences in urban form did not significantly influence tree canopy growth and all species showed similar canopy expansion rates. However, smaller trees showed a greater relative canopy increase in the ten years, whereas larger trees had a greater absolute canopy growth. Thus, older and larger trees should be protected and maintained to achieve the canopy expansion. Our study indicated that differences in urban form are unlikely to have major impacts on the growth and canopy expansion of well adapted native tree species in open, suburban centers.     

Designing optimal training sets for genomic prediction using adversarial validation with probit regression

Genomic selection (GS) is a disruptive methodology that is revolutionizing animal and plant breeding. However, its practical implementation is challenging since many times there is a mismatch in the distribution of the training and testing sets. Adversarial validation is an approach popular in machine learning to detect and address the difference between the training and testing distributions. For this reason, the adversarial validation method in this research was implemented using probit regression to detect the mismatch in distributions and also to select an optimal training set. We evaluated the proposed method with 14 datasets, and the results were benchmarked regarding of using the whole reference population and simple random samples. We found that the proposed method is effective for detecting the mismatch in distributions and outperformed in prediction accuracy by 11.67% (in terms of mean square error) and by 5.35% (in terms of normalized mean square error) when the whole reference population was used as training sets. Also, in general, this outperformed some existing methods for optimal training designs in the context of GS.     

叶用芥菜新品种甬高2号的选育

甬高2号是从日本引进的三池赤缩缅（叶用芥菜）的变异株中分离而来,利用系统选育方法育成的叶用芥菜新品种。生长期约190 d（天）,株型较直立,叶全缘,叶面皱褶,有光泽,蜡粉少,无刺毛,正面叶脉紫红色,最大叶叶长约54 cm,叶宽28 cm,叶柄宽6 cm,中肋宽11 cm、厚1 cm,加工性状好,耐寒性和冬性较强,单株质量约1.5 kg,每667 m2产量5 000 kg左右,适宜长江流域及华南、西南地区种植。     

A comparison of the population genetics of Lethrinus miniatus and Lutjanus sebae from the east and west coasts of Australia: Evidence for panmixia and isolation

Lethrinus miniatus and Lutjanus sebae are important commercial and recreational species of reef fish. Within Australian waters the former species is less widespread than the latter and has a discontinuous distribution, whilst the latter is continuously distributed in tropical Australian waters. The demographic attributes of these species (e.g. long life span, low rates of natural mortality) make them vulnerable to over-exploitation. Consequently, conservative harvest strategies including no-take zones for these species have been adopted by fisheries management agencies to control exploitation. Information on the genetic stock structure of these species is important for developing specific management strategies. However, little is known about genetic stock structures within and between east and west Australian populations of these species. The current study used the mitochondrial genome hypervariable region 1 (HVR1) of the control region to examine variation between two sites from both the east and west Australian coasts for each species. HVR1 for L. sebae did not differ genetically either within or between coasts (F_st < 0.018, p > 0.15) at the sites studied, suggesting a panmictic population structure. Similarly, L. miniatus did not differ significantly between sites sampled within coast. However, the west coast HVR1 for L. miniatus east and west coast populations, were discrete (F_st of at least 0.92, p < 0.0001). The degree of genetic sub-division between east and west coast populations indicates that they should be managed as discrete stocks. Further, when considering both species, the lower genetic (both haplotype and nucleotide) diversity in three of the four sites on the west coast of Australia, indicates that this region is genetically impoverished and neutrality tests suggest that selection is responsible. Consequently, west Australian populations will be less resilient to perturbations (e.g. fishing, climate change) than east Australian populations, which have higher genetic diversity.     

松浦镜鲤与德国镜鲤选育系（F4）的可量性状、鳞片数比较

对松浦镜鲤（SP）和德国镜鲤选育系（F4）（DJ）的可量性状及体表鳞片数进行比较,SP与DJ的可量性状与体表鳞被存在差异。SP的体长／体高（2．44±0．15）、头长／眼间距（2．24±0．08）明显小于DJ,体长／头长（3．86±0.20）、头长／吻长（2．99±0．23）明显大于DJ,SP体表的鳞片数明显少于DJ。结果表明,从DJ到SP遗传选育过程中,体型和鳞片的变化已达到了选育目的。     

基于浑浊度监测山区河流悬浮泥沙含量的试验研究

针对山区河流悬浮泥沙含量监测缺乏实时性的问题,对浑浊度及悬浮泥沙含量进行监测,分析光照强度、流速、颗粒粒径和水体含沙量对浑浊度的影响,建立浑浊度与悬浮泥沙含量的关系模型式。结果表明： 1）光照强度对浑浊度的影响最大,根据二者之间的关系,将光照强度（E）划分为3个区间：E≤6 800 lx、6 800 lx <E≤22 000 lx、E>22 000 lx,对应于3个区间,确定了浑浊度与悬浮泥沙含量的关系模型; 2）水流流速主要影响上层泥沙颗粒的分布,流速为0.16 m/s时测量区域的浑浊度大于流速为0.018 m/s时的浑浊度; 3）泥沙颗粒的粒径大于扬动流速能带动的临界粒径时,其会沉积在渠底,因此,泥沙级配中大于临界粒径的颗粒占比越大,悬浮泥沙含量越小,浑浊度越小; 4）水体含沙量越大,水沙输移过程中携带悬浮泥沙的量也越多,测量区域上层水样的浑浊度越大; 5）采用本研究确定的浑浊度与悬浮泥沙含量的3个关系模型,预测得到的悬浮泥沙含量与实际悬浮泥沙含量的平均相对误差分别为7.22%、10.00%、8.58%。根据在自然条件下不同光照强度区间测得的浑浊度,可以得出该测量区域的悬浮泥沙含量。由于浑浊度可以现场连续、快速测得,所以将此方法引入山区河流悬浮含沙量实时监测是可行的。     

基于有机质特征谱段的土壤Cd含量高光谱遥感反演

针对土壤Cd高光谱遥感定量反演中的机理性不足及数据冗余问题,提出一种基于有机质特征谱段的反演方法。该方法首先提取土壤光谱中对重金属Cd具有吸附作用的有机质特征谱段,进而通过竞争性自适应重加权采样法（Competitive adaptive reweighted sampling,CARS）优选特征谱段,采用偏最小二乘回归法（Partial least squares regression,PLSR）建立重金属Cd的反演模型,并利用郴州矿区土壤实验室光谱数据和哈密黄山南矿区野外光谱数据进行方法验证。研究表明：有机质特征谱段提取在降低数据冗余的同时提高了重金属Cd的反演精度,CARS算法相对于相关系数法（Correlation coefficient,CC）和遗传算法(Genetic algorithm,GA)特征选择具有更高的反演精度,基于有机质特征谱段的CARS-PLSR算法在土壤实验室光谱和野外实测光谱所得验证精度R2分别为0.94和0.80,表明该算法对于实验室和野外光谱均具有一定适用性。研究可为土壤重金属含量高光谱反演的特征波段选择和算法优选提供参考。     

基于地相位优化估计的RVoG三阶段森林冠层高度反演

极化干涉合成孔径雷达（PolInSAR）估测森林结构参数中,数据受基线长度、信噪比、环境地形以及雷达波长的影响,尤其在复杂森林环境条件下,会导致观测到的复相干存在误差,从而影响最终的反演结果。为解决此问题,首先探讨了体相干选择对RVoG三阶段森林冠层高度反演的影响,以地相位为参考逐像素选择距离地相位最远的相干性作为体相干。其次改进了地相位估计方法,采用戴明回归（DMR）和正交回归（OGR）2种相干直线拟合方法来改进地相位的估计,并在DMR拟合方法中设置了不同的误差比（0.3和0.6）来比较地相位估计方法对RVoG三阶段森林冠层高度反演的影响。研究结果表明：以地相位为参考逐像素选择体相干的反演结果相较于直接使用HV极化通道的复相干γ_HV为体相干的反演精度有明显提升,决定系数（R²）由0.349增加到0.383,均方误差由7.097 m²降低到5.755 m²。在体相干优化选择的基础上,采用了戴明回归和正交回归对地相位估计方法进行了改进。表明基于最小二乘回归（LSR）地相位估计的RVoG三阶段反演精度最...     

软枣猕猴桃新品系—‘蜜玉’的选育

‘蜜玉’是从混合实生后代中筛选出的优良资源,经无性繁殖系统选育出的软枣猕猴桃新品系。果实椭圆形,果皮绿色,光滑无毛,平均单果重12.1 g。果肉绿色,可溶性固形22.5 %,总糖13.4 %,总酸1.06 %,维生素C1050.0 mg?kg-1。口感较甜,香气浓郁,抗寒、抗病能力较强。在吉林左家地区,6月中旬开花,9月初成熟。果实在常温条件下第7天开始软熟,低温（2～4℃）条件下第24天开始软熟。     

基于序相关的作物育种评价性状特征选择方法

将育种家对作物性状表现的综合评价融入作物育种评价中,提出了一种基于序相关的作物育种评价性状特征选择方法。首先,从育种数据中筛选训练样本集及候选性状特征集合,计算候选性状特征集合中各性状与育种材料评价结果的相关性和作物在性状特征间表现的相似性,然后,利用计算的相关系数同时综合考虑性状表现的相似性系数,以期望选择的性状特征的相关性最大、相似性最小为目标,建立基于序相关的作物育种评价性状特征选择模型。该模型可为不同育种目标提供重点关注的性状特征集合,为数据化育种提供支持及依据。利用该方法对2013年大豆品系鉴定试验中早熟、中熟、毛豆3类育种材料进行了性状特征选择试验,结果验证了方法的有效性。该方法可以作为育种评价方法的前置步骤,与现有的综合评价、模糊综合评价等方法结合作为性状特征权重的确定手段,提高权重确定的科学性。