基于GIS的滨海盐渍化农田土壤空间变异及其分区管理

针对滨海盐渍化农田盐碱瘠薄、土壤属性空间变异大、粗放管理效益低的现实,研究管理分区精准划分方法,采取差异化措施,提升盐渍化土地利用水平。该文以无棣县农田为研究区,采用网格法结合土地利用现状定点野外采样、室内化验分析获取土壤属性数据,运用ArcGIS 10.2地统计方法分析土壤属性的空间变异特征;在MATLAB R2016a中采用模糊c-均值聚类法（FCM）计算各样点的模糊隶属度,通过插值预测模糊隶属度的空间分布,基于最大隶属度原则进行分区;通过变异性分析和最小极差法（LSR）差异显著性检验,对分区结果进行精度验证。结果表明：无棣县农田土壤总体呈轻中度盐渍化,有效氮含量偏低,有机质、有效磷含量中等,速效钾含量较高;有机质、有效氮、有效磷、速效钾和含盐量呈中等变异性（变异系数25.0%-52.3%）,空间变异性较大,应分区调控;速效钾、含盐量和pH的块金效应值小于25%,主要受土壤质地、地下水矿化度等结构因素影响,有机质、有效氮和有效磷的块金效应值在50%-75%之间,受耕作方式、施肥等人为因素影响较大。将全县农田划分为3类管理区,估算面积分别为2.56万hm²、1.76万hm²、3.24万hm²;各分区土壤养分变异系数分别为23.9%-51.5%、15.9%-50.3%、14.7%-33.0%,检验结果表明各分区间差异显著,而各分区内部变异性明显低于未分区。管理分区与土壤属性空间分布特征具有较高的拟合度,分区结果可以作为差异化管理的作业单元。研究结果为各分区内部统一、不同分区间差异化管理提供了依据,研究有助于推进滨海盐渍化农田精准化管理水平的提高。     

基于光合系统参数建立马铃薯耐荫性综合评价体系

为构建便捷的马铃薯(Solanum tuberosum)耐荫性综合评价体系并发掘耐荫种质, 以35个马铃薯品种(系)为实验材料, 测定块茎膨大期遮荫下植株叶片叶绿素含量、光合能力和叶绿素荧光等光合参数及收获后块茎单株产量和淀粉含量等指标。根据耐荫系数, 利用主成分分析法、隶属函数法、聚类分析法和逐步回归分析法进行综合评价。通过主成分分析将马铃薯耐荫性相关的13个单项光合指标转换为6个综合指标, 代表了全部信息的87.51%。以此计算各种质的隶属函数值, 并以主成分的贡献率进行加权, 最终获得所用材料耐荫性的综合评价值(D值)。根据D值聚类分析结果将35个马铃薯分为4类, 其中Eshu10和Lishu6分别为耐荫性最强和最弱的品种。通过逐步回归分析建立了马铃薯耐荫性评价数学模型: D=0.060+0.106G_s+0.214qP+0.143NPQ。同时, 用该评价体系鉴定为耐荫性强的品种(系)在遮荫后其产量和/或淀粉含量等指标减幅均低于耐荫性弱的种质, 表明该评价体系可用于快速评价和预测马铃薯种质的耐荫性。     

An ANN-GA model based promoter prediction in Arabidopsis thaliana using tilling microarray data

Identification of promoter region is an important part of gene annotation. Identification of promoters in eukaryotes is important as promoters modulate various metabolic functions and cellular stress responses. In this work, a novel approach utilizing intensity values of tilling microarray data for a model eukaryotic plant Arabidopsis thaliana, was used to specify promoter region from non-promoter region. A feed-forward back propagation neural network model supported by genetic algorithm was employed to predict the class of data with a window size of 41. A dataset comprising of 2992 data vectors representing both promoter and non-promoter regions, chosen randomly from probe intensity vectors for whole genome of Arabidopsis thaliana generated through tilling microarray technique was used. The classifier model shows prediction accuracy of 69.73% and 65.36% on training and validation sets, respectively. Further, a concept of distance based class membership was used to validate reliability of classifier, which showed promising results. The study shows the usability of micro-array probe intensities to predict the promoter regions in eukaryotic genomes.     

93份贵州地方辣椒资源品质性状分析

对93份贵州地方辣椒资源的品质性状进行了分析,结果表明:粗纤维含量在22.99%~44.06%之间,牛角椒含量最高,为33.71%;粗脂肪含量在11.49%~27.46%之间,锥形椒含量最高,为21.55%;蛋白质含量在12.81%~22.97%之间,指形椒含量最高,为18.78%;辣椒素含量在0.28~7.61 mg/g之间,指形椒含量最高,为4.47 mg/g;4个指标的平均隶属度值在0.21~0.68之间,超过0.60的辣椒资源有S106、S103、S072和S016;聚类分析表明,93份辣椒资源按平均隶属度大小可分为四大类型,即高品质型、中品质型、一般品质型和特殊品质型。贵州地方辣椒种质资源品质性状分析可为辣椒种质资源的创新利用、新品种的选育奠定基础。     

机械化保护性耕作条件下土壤质量的数值化评价

通过9年的长期田间定位试验研究了陕西关中平原中部冬小麦 夏玉米轮作条件下深松耕（ST）、旋耕（RT）、秸秆还（SR）、免耕（NTS）等保护性耕作措施及传统耕作（TT）对土壤理化性状和作物产量的影响,并采用主成分分析方法进行土壤质量的综合评价.结果表明：与传统耕作相比,保护性耕作模式提高了土壤肥力质量,改善了土壤物理环境条件;显著提高了土壤脲酶和碱性磷酸酶的活性;除秸秆覆盖免耕处理的玉米和小麦产量低于传统耕作外,其他保护性耕作措施均不同程度地提高了作物产量,其中小麦增产13%～28%,玉米增产3%～12%.与传统耕作相比,保护性耕作土壤质量指数提高了19.8%～44.0%.综合考虑经济效应和生态效益,隔年深松、秸秆粉碎联合旋耕作业以及秸秆覆盖联合深松作业不仅能增加作物产量还可改善土壤质量,可在研究区进行推广应用.     

基于多目标灰色局势决策的三峡库区防护林类型空间优化配置

基于2007年Landsat TM遥感影像和影响防护林的主导环境因子,对三峡库区的森林立地进行分类,并通过选取水源涵养量、生物量和林分生产力3个指标,利用多目标灰色局势决策模型对库区现有的针叶林、阔叶林、针阔混交林和灌木林4种防护林类型进行空间优化配置.结果表明： 2007年,三峡库区森林立地可划分为40种类型;空间配置优化后,研究区针叶林、阔叶林、针阔混交林和灌木林的面积比例分别为32.55%、29.43%、34.95%和3.07%.与优化前相比,优化后针叶林和灌木林的面积比例分别减少了8.79%和28.55%,阔叶林和针阔混交林分别增加了10.23%和27.11%.通过防护林类型的空间优化,三峡库区整体的水源涵养能力、生物量和林分生产力分别增加14.09×10⁸ m³、0.35×10⁸ t和1.08×10⁶ t.     

Social modulation of testosterone levels in male black howlers (Alouatta pigra)

The influence of social factors on the modulation of male testosterone levels has been demonstrated among several vertebrate species. In addition to sexual activity, parental care and reproductive competition affect testosterone secretion. We examined variations in testosterone levels among male black howlers (Alouatta pigra) in various social contexts. Fecal samples were collected from nine males living in five different groups in the Mexican state of Campeche. The potential for intragroup and extragroup competition varied among the groups. The number of resident males living in the groups was the only variable that significantly explained variations in testosterone levels. Males living in unimale groups had higher testosterone levels; the highest testosterone levels were recorded for males that had experienced a shift from multimale to unimale group compositions. In this species, the probability of being challenged by extragroup males and evicted from the group during immigration events increases when males live in unimale groups. Therefore, our results suggest that male black howlers respond to competition for group membership by increasing their testosterone levels. In this context, testosterone secretion represents an anticipatory response to reproductive conflicts. Therefore, although males living in unimale groups have exclusive access to females, they face higher physiological costs associated with sustaining high testosterone levels for extended time periods.     

磷和钾对大灰藓植株生长生理和营养元素的影响

大灰藓(Hypnum plumaeforme)具有良好的景观效果和应用前景,但生长缓慢且缺少系统的栽培技术研究,对其推广应用有一定影响。该研究分别将磷肥(P)、钾肥(K)、PK复合肥作为一次性基肥使用,研究不同施肥处理下大灰藓的生长生理和营养元素的变化,并用模糊隶属函数法选出最佳施肥处理。结果表明,施肥能显著增加大灰藓的覆盖度,K₁₈处理的植株覆盖度较对照(CK)提高了53.9%。施肥能显著增加植株类胡萝卜素、叶绿素(除K₁₂)、可溶性蛋白(P₂₄、PK₁₂、PK₃₀除外)含量,降低植株可溶性糖含量(除P₂₄、PK₆),P₁₈处理的植株类胡萝卜素和叶绿素含量最高,分别为CK的3.42和2倍。P肥显著增加了植株P含量,以P₁₈的影响最大,为CK的1.33倍;K肥对植株K含量积累的促进作用最好,K₁₈处理的植株K含量最高(为CK的1.62倍)。模糊综合评价表明K_1...     

基于人水关系的京津冀城市群水资源安全格局评价

京津冀城市群是我国乃至全世界人类活动对水循环扰动强度最大的地区之一,水资源过度开发利用不仅严重影响生态环境安全,而且制约着经济社会的可持续发展。基于人水关系协调视角,从水资源本底条件、水资源开发利用程度、水资源开发利用效率等3个方面建立了水资源安全综合评价指标体系,并根据国内外发展经验和相关标准确定了评价标准阈值,使得评价结果在不同的时空尺度上均具有可比性。然后通过熵技术支持下的层次分析法和多目标模糊隶属度函数,对2000—2014年京津冀城市群水资源安全的时空格局进行了定量评价。结果表明:(1)整个京津冀城市群的水资源安全指数多在0.2—0.4之间,属于不安全类型,但总体向临界安全类型转变;(2)各城市的水资源安全指数在时空尺度上表现出较大差异,总体表现为南低北高且随着时间的推移普遍提高的格局;(3)整个京津冀城市群及各城市水资源安全指数的次级指标在时空尺度上也表现出一定的差异性和地域一致性,它们交互作用,最终综合决定着水资源安全指数的时空变化。     

FuzzyID2: A software package for large data set species identification via barcoding and metabarcoding using hidden Markov models and fuzzy set methods

Species identification through DNA barcoding or metabarcoding has become a key approach for biodiversity evaluation and ecological studies. However, the rapid accumulation of barcoding data has created some difficulties: for instance, global enquiries to a large reference library can take a very long time. We here devise a two‐step searching strategy to speed identification procedures of such queries. This firstly uses a Hidden Markov Model (HMM) algorithm to narrow the searching scope to genus level and then determines the corresponding species using minimum genetic distance. Moreover, using a fuzzy membership function, our approach also estimates the credibility of assignment results for each query. To perform this task, we developed a new software pipeline, FuzzyID2, using Python and C++. Performance of the new method was assessed using eight empirical data sets ranging from 70 to 234,535 barcodes. Five data sets (four animal, one plant) deployed the conventional barcode approach, one used metabarcodes, and two were eDNA‐based. The results showed mean accuracies of generic and species identification of 98.60% (with a minimum of 95.00% and a maximum of 100.00%) and 94.17% (with a range of 84.40%–100.00%), respectively. Tests with simulated NGS sequences based on realistic eDNA and metabarcode data demonstrated that FuzzyID2 achieved a significantly higher identification success rate than the commonly used Blast method, and the TIPP method tends to find many fewer species than either FuzztID2 or Blast. Furthermore, data sets with tens of thousands of barcodes need only a few seconds for each query assignment using FuzzyID2. Our approach provides an efficient and accurate species identification protocol for biodiversity‐related projects with large DNA sequence data sets.