汾河源头地区土壤侵蚀时空变化及其空间自相关分析

[目的]汾河源头地区是山西省重要的水源涵养地和供水区,土壤流失严重。研究该区域土壤侵蚀时空变化的目的在于为该流域的水土保持工作提出科学依据。[方法]采用2004和2009年9月的SPOT影像作为数据源,将GIS和USLE结合对汾河源头地区土壤侵蚀的时空变化进行研究,并借助GeoDa软件分析了研究区2009年土壤侵蚀的空间自相关性。[结果](1)从时间变化来看,2009年汾河源头地区土壤侵蚀模数较2004年有所增加,中度以上侵蚀的面积占总侵蚀面积的比例也相应增大,且以极强度侵蚀和剧烈侵蚀增加为主;(2)从空间上看,土壤侵蚀程度高的区域分布在流域的东南部,土壤侵蚀程度低的区域分布在流域的西北部;(3)降雨和植被覆盖是影响汾河源头地区土壤侵蚀的2个主要因子;(4)除了微度侵蚀和剧烈侵蚀外,其他侵蚀强度类型向更高程度的侵蚀强度类型转移的面积都远大于向低程度的侵蚀强度类型转移的面积;(5)空间自相关分析表明,研究区土壤侵蚀存在一定的正相关和空间集聚,主要表现为高值与高值集聚,低值与低值集聚。[结论]研究区内土壤侵蚀现象不断加剧,应加强土壤侵蚀治理力度。     

黑河中游山前平原区土地利用变化对土壤侵蚀的影响

在GIS技术的支持下,利用137Cs含量的分异规律对土壤侵蚀的发生、分布进行了研究,并对不同土地利用背景下土壤侵蚀的空间分布规律进行了定量研究。通过137Cs强度的空间差异,分析了土壤侵蚀的强度及区域差异,及其与区域土地利用、土地覆盖变化的相互关系。结果表明:(1)黑河中游山前平原区属中度侵蚀,其土壤侵蚀强度依次为荒地>耕地>草地,草地开垦为耕地将加剧土壤侵蚀;(2)研究区内每年耕作土地的土壤侵蚀量达0 2亿t,草地的土壤侵蚀量达0.4亿t,荒地的土壤侵蚀量达1 2亿t,区内每年由这3类主要土地利用类型造成的土壤侵蚀量约为1.8亿t;(3)近20年来黑河中游山前平原区土壤侵蚀量总体呈现增加的趋势,其西部为强风蚀地区,荒漠化日益严重,南部沿山洪积扇区土地资源的大规模开发利用,在造成本区域土地恶化的同时,加剧了中部及中北部地区向荒地演化的趋势。     

黄河上游西柳沟流域土壤侵蚀对土地利用变化响应

为科学认识土地利用变化对流域土壤侵蚀的影响,研究基于黄河上游西柳沟流域1980年、2015年两期土地利用变化和相应的土壤侵蚀强度变化,研究了土地利用变化对流域土壤侵蚀的影响。结果表明:(1)西柳沟流域草地、林地和耕地3种主要的土地利用类型转出面积大小为草地>林地>耕地,耕地主要转化为草地,林地大部分转为未利用土地,草地大部分转为耕地和未利用土地;(2)西柳沟流域1980年、2015年平均土壤侵蚀模数分别为1946.56,1 873.55 t/(km²·a),其中草地土壤侵蚀模数最大,其次为林地,土壤侵蚀量主要来自于草地;(3)西柳沟流域35年间微度侵蚀和轻度侵蚀占主导,土壤侵蚀程度总体上呈降低的趋势,具体表现为草地的部分面积向林地和耕地分别转化了4.47,17.54 km²,说明土地利用结构的改变是影响流域土壤侵蚀变化的关键因素。研究成果以期为黄河上游小流域水土流失治理提供参考。     

基于CSLE-TLSD耦合模型的近40年洞庭湖流域土壤侵蚀时空分异及归因分析

为了精确模拟洞庭湖流域土壤侵蚀动态过程并定量评估其影响因素贡献,在中国水土流失方程(CSLE)的基础上耦合泥沙输送限制模型(TLSD),实现对土壤分离-搬运-沉积全动态过程分析。在此基础上,采用趋势分析和地理探测器方法探究洞庭湖流域1980-2020年土壤侵蚀时空分异特征与影响机制。结果表明:(1)CSLE-TLSD耦合模型在各水文站的年输沙量模拟值和实测值拟合结果较好(R²=0.56);(2)1980-2020年洞庭湖流域年均土壤侵蚀模数为5.09 t/(hm²·a),侵蚀模数和面积在整体上均呈下降趋势,其中侵蚀显著改善区域占流域总面积的22.60%,而显著加剧区域仅占2.69%;(3)年侵蚀总量以2005年为突变点,呈现出先下降后上升的趋势;(4)2005年前后导致土壤侵蚀变化的主导因子从地类变化转变为年降雨量变化。综上,洞庭湖流域土壤侵蚀总体呈现侵蚀面积收缩、局地恶化的趋势,其中极端降雨事件和经果林开发是侵蚀加剧的主要原因。     

基于USLE模型的重庆生态涵养发展区土壤侵蚀量估算

利用USLE模型估算渝东北生态涵养发展区土壤侵蚀量,并对研究区土壤侵蚀强度进行分级,以此为基础进一步分析不同降雨侵蚀力、坡度、土壤类型下的土壤侵蚀强度分布特征。结果表明:本研究区土壤侵蚀量大致呈东北向西南递减的趋势,东部山地土壤受侵蚀最严重,西部山间丘陵地带土壤侵蚀量相对较小,研究区平均土壤侵蚀模数为30.15t/(hm~2·a),土壤侵蚀量为10 220.85万t/a。研究区各区县土壤侵蚀分布情况可划分为三类:(1)重点预防保护区。土壤侵蚀以微度和轻度侵蚀为主,林草覆盖度较高,但有水土流失加剧的危险,代表区县是忠县、梁平、垫江;(2)重点监督区。土壤侵蚀以中度和强度侵蚀为主,土壤侵蚀相对严重,代表区县为云阳、万州、巫山、奉节、丰都;(3)重点治理区。土壤侵蚀以极强度和剧烈侵蚀为主,土壤侵蚀最严重,代表区县为巫溪、开县、城口。降雨侵蚀力为3 000~4 000(MJ·mm)/(hm~2·h·a),坡度在25°以上,土壤为石灰土、紫色土或黄褐土的地区,土壤侵蚀以强度、极强度和剧烈侵蚀为主,是水土流失治理的重点。     

基于遥感技术的苕溪流域水土流失动态监测研究

以多源遥感影像为信息源，基于ArcGIS平台的空间分析与数据管理等功能，获取苕溪流域土地利用、植被覆盖、水土保持措施等数据，对降雨、土壤、地形、植被、水土保持措施等数据进行处理，提取各土壤侵蚀因子，应用中国土壤流失方程(CSLE)计算土壤侵蚀模数，得到苕溪流域水土流失动态监测成果。监测结果表明，2020年苕溪流域土地利用以林地、建设用地和耕地为主；耕地主要分布在≤2°坡度级；植被覆盖状况良好，九成以上的园、林、草地植被覆盖度大于60%;流域水土流失总面积304.45 km~2,侵蚀强度以轻度侵蚀为主；水土流失主要分布在茶园、人为扰动用地、其他林地及旱地，其中极强烈及以上侵蚀主要分布在人为扰动用地、茶园和坡耕地；整体来看，土壤侵蚀强度改善的区域面积大于加剧的区域面积。     

基于USLE模型的滇池流域土壤侵蚀时空演变分析

掌握滇池流域土壤侵蚀的空间分布规律和演变趋势对优化水土保持措施、开展滇池水污染治理和保障流域可持续发展具有重要意义。该文以降雨量、土壤、DEM和遥感影像为数据源,运用RS、GIS技术,结合土壤侵蚀模型计算滇池流域1999—2014年每隔3 a的土壤侵蚀量,分析流域土壤侵蚀强度的时空演变特征。结果表明,无明显侵蚀区域面积在15 a间呈上升趋势,占比从1999年的70%上升为2014年的82%,说明流域土壤侵蚀状况逐渐好转;1999—2014年期间滇池流域土壤侵蚀面积呈逐年下降趋势,1999年侵蚀面积最大,为776 km2,到2014年下降到为468 km2;土壤侵蚀强度等级转移矩阵显示15 a间近75%区域侵蚀强度保持不变,其中以微度侵蚀为主,有18.23%的区域侵蚀强度降低,8.36%的区域强度上升;空间变化上,侵蚀强度降低的区域主要集中于环滇池的入湖河流一带,侵蚀强度上升区域主要为流域东、南、北端海拔较高的山区。该研究有助于分析滇池流域土壤侵蚀在空间上的演变过程,为提出精准的侵蚀防治措施提供决策依据,为流域生态环境保护提供参考。     

基于CSLE模型的陕北纸坊沟流域土壤侵蚀评价

[目的]对陕北纸坊沟流域土壤侵蚀状况进行评价,为该流域不合理土地利用方式的调整和优化以及水土流失治理措施的合理布设提供科学依据。[方法]以陕西省安塞县纸坊沟流域为研究区,基于ArcGIS技术,利用2005—2016年纸坊沟流域水文站月降雨量数据、DEM数据、土壤类型数据和土地利用数据,率定中国土壤流失方程(CSLE)的相关参数,计算研究区的土壤侵蚀强度,对土地利用变化与坡度和土壤侵蚀强度之间的关系进行分析。[结果](1)研究区内不同坡度带上的土壤侵蚀强度差异较大,15°～25°左右的坡耕地是土壤侵蚀的敏感部位。(2)纸坊沟流域内土地以林地、耕地、草地为主,耕地面积不断减少,林地和草地面积不断增加。该区域实施退耕还林后,土壤侵蚀的面积与强度整体呈现改善趋势;土地利用变化与土壤侵蚀强度具有密切联系,表现为耕地的土壤侵蚀强度较强,林地和草地侵蚀强度相对较弱,说明增加林地和草地面积,减少耕地面积,能够显著减弱土壤侵蚀。[结论]研究区内土壤侵蚀空间分布受土地利用方式和坡度制约,该区今后水土流失治理的重点区域是15°～25°左右的坡耕地。     

基于RUSLE模型的雅鲁藏布江流域土壤侵蚀评价

[目的]研究雅鲁藏布江流域土壤侵蚀时空变化特征,并分析气候和植被覆盖变化对土壤侵蚀的影响,以期为高寒区土壤侵蚀防治、生态系统保护和水土资源开发利用提供理论支撑。[方法]以雅鲁藏布江流域为研究区,采用RUSLE模型定量评估了1980—2017年流域土壤侵蚀的时空变化特征。[结果]1980—2017年,雅江流域土壤侵蚀强度整体呈现先减小后增加的趋势,1980—1999年年均土壤侵蚀模数波动下降,2000—2017年年均土壤侵蚀模数则呈现不显著上升趋势;流域中上游地区土壤侵蚀变化较为显著,下游地区侵蚀强度先增加后减小。年均土壤侵蚀模数与降雨侵蚀力呈显著正相关关系,Pearson相关系数为0.92,而与NDVI关系不显著。不同土地利用类型中,土壤侵蚀最强烈的是未利用地,其次是稀疏草地,由于其面积占比最高,对流域总侵蚀量的贡献比超过54%。[结论]降雨是影响雅江流域土壤侵蚀强度变化的主要因素,未来土壤侵蚀防治的重点区域应为流域东部下游降雨量较大的地区,重点防范极端降雨造成的水土流失。     

水土流失强度及分级

一、水土流失强度的概念水土流失强度是反映水土流失严重程度的重要指标,是水土保持决策的基本依据。常用三种数据来表示：一是水土流失面积率。即某一区域或流域轻度以上水土流失面积占土地总面积的百分比,其值越大表示水土流失越严重;二是土壤侵蚀模数。即单位面积在单位时间内的土壤侵蚀量,计量单位一般用t／km^2·a表示（特殊情况也有用m^3／km^2·a表示的）,其值越大表示水土流失越严重;三是土壤侵蚀厚度。即土壤侵蚀模数与土壤容重的比值,其值越大表示水土流失越严重。前者常用于水土保持规划,为水土保持宏观决策提供依据;后二者常用于水土流失强度界定。我们通常所说的水土流失强度,一般是指后二者。     

Potential of wild species for genetic enhancement of some semi-arid food crops

Discovery and incorporation of genes from wild species provide means to sustain crop improvement, particularly when levels of resistance in the cultigens are low and virulent strains of pests and pathogens overcome the host plant resistance. The extent of utilization and the potential of the wild genepool for genetic enhancement were reviewed in five important food crops viz. sorghum, pearl millet, chickpea, pigeonpea and groundnut grown in the semi-arid tropics. Introgression from compatible wild germplasm in the primary gene pool resulted in transfer of new cytoplasmic male sterility systems in pearl millet and pigeonpea, development of high protein, cleistogamous flower and dwarf pigeonpea lines and foliar disease resistant groundnut cultivars. Utilization of wild species in secondary and tertiary gene pools has been generally limited due to sterility, restricted recombination or cross incompatibility. Nevertheless, these species are extremely important as they contain high levels of resistance to several important biotic and abiotic stresses. Several of them, like those belonging to the Parasorghum section and the rhizomatous Arachis species are sources of multiple resistances and hold great promise to sustain crop productivity.     

“绿色革命”以来大气CO2浓度升高对C3作物营养品质的影响

自20世纪60年代"绿色革命"以来,育种技术和农耕技术的发展促进了农作物产量的大幅提升,然而作物的营养品质出现下降趋势。在相似的遗传背景下,大气CO_2浓度升高会使单位体积农作物产品的营养元素含量下降,因此"绿色革命"至今,农作物产品的营养元素下降可能受大气CO_2浓度升高影响。通过植物生长箱模拟"绿色革命"初期和目前的大气CO_2浓度水平(310μmol/mol和400μmol/mol),针对主要C_3作物水稻、小麦和大豆,研究"绿色革命"以来大气CO_2浓度升高对其籽粒的C、N、Fe、Zn元素含量的影响,结果表明:CO_2浓度升高对3种作物籽粒的C元素含量几乎没有影响,变化幅度在±1.5%之间;籽粒的N、Fe、Zn元素含量普遍呈现下降趋势,但均未达到显著水平。     

Faculty positions:Center for Agricultural Resources Research,Chinese Academy of Sciences

正The Center for Agricultural Resources Research(CARR),the Institute of Genetics and Developmental Biology(IGDB),Chinese Academy of Sciences,invites applicants for several research group leader positions.CARR is one of the research organizations in Chinese Academy of Sciences(CAS).We seek nominations and applications     

低氮和干旱胁迫对富士和秦冠生长及氮素利用的影响

【目的】以富士（Fuji）、 秦冠（Qinguan）嫁接在平邑甜茶（Malus hupehensis Rehd.）上的当年生盆栽苗为试验材料,采用砂培方法,研究了缺氮胁迫和干旱对富士和秦冠生长情况、 光合参数、 植株各部位氮磷钾含量及氮素利用效率的影响,分析比较了低氮干旱条件下富士和秦冠生长及氮素利用的差异,以期为果树生产高效肥水利用提供理论指导。【方法】试验共设四个处理: 正常氮正常水（ZZ）、 低氮正常水（DZ）、 正常氮干旱（ZG）、 低氮干旱（DG）。氮素和水分均设置两个水平,分别为正常氮（6 mmol/L NO-3-N）、 低氮（0.3 mmol/LNO-3-N）、 正常供水（保持盆中砂子相对含水量为饱和含水量的80%~85%）、 干旱处理（保持盆中砂子相对含水量为饱和含水量的60%~65%）。【结果】富士和秦冠的生物量（茎和叶）、 株高茎粗等生长指标以及光合速率、 气孔导度、 蒸腾速率均为正常氮正常水（ZZ）＞低氮正常水（DZ）＞正常氮干旱（ZG）＞低氮干旱（DG）,并且相对应处理下秦冠的以上指标均高于富士;正常供水下,缺氮处理使富士、 秦冠的根冠比比正常氮处理均有所增加,富士提高了2.05%,秦冠提高了22.40%。富士和秦冠的氮、 磷、 钾含量均表现出正常氮正常水（ZZ）＞低氮正常水（DZ）＞正常氮干旱（ZG）＞低氮干旱（DG）; 氮、 钾元素含量在植株各部位的分布顺序依次是叶＞根＞茎,磷元素则是根＞叶＞茎;光合氮素利用效率（PNUE）和氮素利用效率表现为秦冠处理之间差异极显著,富士处理之间差异不显著;秦冠的PNUE和NUE明显高于富士,在低氮正常水（DZ）处理下,秦冠氮肥利用率比富士高42.07%,在低氮干旱（DG）处理下高64.14%;低氮胁迫下富士和秦冠的NUE显著提高,并且秦冠提高的幅度高于富士。【结论】施用氮肥能够显著提高富士与秦冠的干物质量,同等水肥条件下,秦冠生长优于富士;水分亏缺会减少叶片对氮的吸收,干旱条件下适度增施氮肥,可提高果树的抗旱能力;低氮干旱胁迫下秦冠的生长指标、 光合指标及氮素利用效率指标均优于富士,表现出较强的抗低氮干旱胁迫的能力。     

Collection and preliminary evaluation of native turfgrass accessions in Italy

Despite a raising interest on turfs in Italy, all theavailable varieties of this kind in the Country are of foreign origin, and areoften poorly adapted to the prevailing climatic conditions. This prompted tobegin a collection activity of indigenous turfgrass species, with the ultimategoal of identifying promising materials for future breeding based on localgenetic resources. The collection was carried out in three areas of Italy, viz.the northern Po Plain, the coastal region of Liguria, and the island of Sardiniathat are characterised, respectively, by subcontinental, warm temperate, andtypical Mediterranean climate. Altogether, 141 sites were visited, yielding 226accessions belonging to eight species of potential interest for turfs:Poa pratensis, Poa trivialis,Festuca rubra, Festuca arundinacea,Lolium perenne, Agrostis stolonifera,Agrostis tenuis, and Cynodon dactylon,this last being a warm-season grass. Poa pratensis andCynodon dactylon were mostly collected in northern Italyand Sardinia, respectively, whereas Festuca arundinacea andLolium perenne were rather ubiquitous. The collection sitesranged from 0 to 1040 m asl, but sites over 750 m wereonly visited in the inner part of Sardinia. All the accessions, collected aswhole plants, were transplanted at Lodi, northern Italy, where they are beingevaluated. Their preliminary evaluation for traits of importance for turf use,such as sward colour and overall quality, highlighted the great variation andthe occurrence of interesting accessions in all species. Other characters wererecorded, bearing specific importance in individual species, and in all casespromising accessions were identified. The germplasm of Festucarubra, Festuca arundinacea, and Loliumperenne proved highly infected by endophytic (symbiotic) fungi of thegenus Neotyphodium.     

Pasture Vegetation Elemental Analysis by Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy (LIBS) is a new technique for the analysis of plant material. This study investigates the application of LIBS to pasture-based plant samples. The LIBS measurements were obtained from pelletized pasture samples (100 samples) that had been also analyzed by inductively coupled plasma–optical emission spectroscopy (ICP-OES) following microwave digestion for calibration and comparison purposes. Comparisons for elements sodium (Na), potassium (K), magnesium (Mg), calcium (Ca), manganese (Mn), iron (Fe), copper (Cu), zinc (Zn), boron (B), phosphorus (P), and sulfur (S) showed that LIBS could be used for almost all the standard profile total elements with concentrations down to low mg/kg levels (observed error of Na: 0.024 percent, K: 0.18 percent, Mg: 0.016 percent, Ca: 0.073 percent, P: 0.017 percent, Mn: 31 mg/kg, Fe: 150 mg/kg, Zn: 6.6 mg/kg, and B: 1.1 mg/kg). Elemental analysis at less than mg/kg levels was not possible using LIBS. The elements S and Cu were particularly difficult to analyze with reliability using LIBS at the concentration levels found in the plant samples. Replacing microwave digestion and subsequent ICP analysis with a direct analysis of dried plant samples using LIBS has the potential to improve the productivity and reduce the cost of testing.     

Leaf position and genotype differences for mineral element concentrations in sorghum grown on tropical acid soil 1

Mineral element deficiencies and toxicities are common problems associated with sorghum [Sorghum bicolor (L.) Moench] production on acid soils. To better understand some of the mineral element problems and the analysis of plant tissue of sorghum plants grown on acid soils, four sorghum genotypes were grown on an acid Oxisol at Carimagua, Colombia limed with dolomite at 2 and 6 Mg ha^‐1.

Samples for mineral element analyses were obtained from leaves at different positions on the four genotypes. Concentrations of P and Mg were highest in the flag leaf (Leaf No. 1) and decreased as the position on the plant declined from the top of the plant for plants grown at 2 Mg lime ha^‐1. Similar decreases in P, Mg, K, and Zn concentrations occurred in plants grown with 6 Mg lime ha^‐1. Concentrations of Ca, S, Si, Mn, Fe, Cu, and Al increased as leaf position declined from the flag leaf for plants grown at 2 and 6 Mg lime ha^‐1. The higher lime supply enhanced Ca and reduced Mn and Fe concentrations in leaves. Differences in mineral element concentrations for the four genotypes used were fairly extensive. The elements to show the greatest range among genotypes were Al and Si and the elements to show the least range among genotypes were P, K, and S. Care should be used in collecting leaf samples for plant analysis and genotypic differences for accumulation of mineral elements should be considered in interpretation of results.     

Short-term variation in the concentration of selected ions within individual tropical rainstorms

Rainwater was collected at the campus of the University of Brunei Darussalam in Bandar Seri Begawan, Brunei Darussalam, using a funnel-in-bottle sampler. Polypropylene bottles were changed at intervals during rainstorm events. The pH and conductivity were determined immediately after collection on aliquots of the sample. Samples were refrigerated at 5°C for subsequent chemical analysis. Analyses for Na, Mg, Ca, Zn and Fe were carried out by means of inductively coupled plasma atomic emission spectroscopy (ICP-AES); Cu and Mn were analysed by graphite furnace atomic absorption spectroscopy (GFAAS); K was analysed using flame atomic emission spectroscopy (FAES); and Cl^–, NO₃ ^– and SO₄ ^2– were analysed by ion chromatography (IC). Concentration versus time profiles are reported for three rainstorm events. All ions exhibited a decrease in concentration during the rainstorm. The first sample contained the highest concentration of ions, consistent with a first-flush effect. The contribution of the initial stages of the shower to the total quantity of ion deposited during the entire rainstorm is quite overwhelming; in many cases 20 to 30% of the mass was deposited in less than 5% of rainstorm duration. On the other hand, the pH and conductivity variation during rainstorms did not exhibit a consistent pattern.     

Leaf litter selection by detritivore and geophagous earthworms

Summary Litterbag experiments with 10 different kinds of leaf litter showed that detritivore (Lumbricus species) and geophagous (Aporrectodea species) earthworms prefer certain litter types over others, since different numbers of worms were found below the litter after 50–52 days of exposure in a pasture. The detritivores preferred Fraxinus, Tilia, and predecomposed Ulmus and Fagus litter to Fagus litter and paper, while geophages preferred Tilia litter to Alnus and Ulmus litter, so that the two groups of earthworms showed different preferences. The detritivores seemed to be more selective than the geophages. The palatability of the litter was examined in relation to the C: N ratio, the lignin concentration and the initial and final polyphenol concentration. The numbers of detritivores were significantly correlated with the C: N ratio and the final polyphenol concentration, so that selection of litter seems to be related to palatability. The numbers of geophages were not significantly correlated with any of the parameters for palatability. The disappearance of litter after 50–52 days appeared to be due to detritivore activity, since the numbers found below the litter were positively and significantly correlated with the litter disappearance. There was no significant correlation with geophage activity. This indicates that detritivores use litter as food, and therefore influence the composition of the litter layer.     

The 5S rRNA gene diversity in the genus <Emphasis Type="Italic">Secale</Emphasis> and determination of its closest haplomes

We analyzed 127 rDNA sequences (5S DNA units) obtained from 23 seed accession samples from more or less 10 taxa in wild and cultivated rye, genus Secale L. The sequences fell into two known groups, here assigned to two unit classes, viz. long R1 and short R1 (designations to reflect on R haplome of rye). The different taxa could not be fully differentiated based on the 5S DNA units. We searched for 5S DNA sequences from known unit classes most closely similar to the long R1 and the short R1. One set with the long R1 unit class contained sequences of the long P1 unit class from Agropyron (P haplome) and from Kengyilia (StYP haplome), long J1 from Thinopyrum (J haplome), whereas the set with the short R1 included the long S1 from Pseudoroegneria (St haplome) and Kengyilia (StYP haplome), the short J1 from Thinopyrum (J haplome) and the short V1 from Dasypyrum (V haplome). Each of the two sets was analyzed separately by maximum likelihood (ML) phylogenetic analysis from which we were able to infer that the 5S DNA units of Secale differentiated in a non-clock fashion and followed the HKY substitution model in the gene tree with the long R1 unit class and the HKY + G in the gene tree with the short R1 unit class. A complementary Bayesian analysis yielded identical tree topologies to the ML ones for each of the two sequence sets. In the tree with the long R1 units the long P1 and long J1 unit classes were closest to the long R1 unit class, whereas in the tree with the short R1 units the long S1 and short J1 unit classes were closest to the short R1 unit class, indicating possibly a close relationship between the St, J and R haplomes.