湿地小叶章叶绿素含量的高光谱遥感估算模型

通过实测不同覆盖度和水深状况下小叶章(Calamagroestis angustifolia)的冠层高光谱反射率与叶绿素a(Chl-a)浓度,采用高光谱可见光-近红外波段及其微分光谱波段(350～1050 nm)逐波段构建FNDVI、FRVI、FDVI、FDNDVI、FDRVI和FDDVI植被指数,分别找出与Chl-a具有最佳相关性波段组合的植被指数,建立小叶章Chl-a含量的最佳估算模型,并对比分析了最佳模型与线性模型的预测精度.结果显示:微分光谱植被指数与Chl-a的最佳预测模型(FDNDVI、FDRVI和FDDVI)比反射率植被指数最佳模型(FNDVI、FRVI和FDVI)的预测精度分别提高了6.86%、4.82%和10.10%;植被指数(FNDVI、FD-VI、FDNDVI和FDRVI)与Chl-a含量具有较好的线性关系,而最佳模型比线性模型预测精度仅仅提高了0.60%、1.40%、1.02%和0.93%,可以用简单的线性模型反演湿地小叶章的Chl-a含量.     

互花米草入侵影响下闽江河口湿地土壤有效硅的时空变化特征

2016年1—12月,选择闽江河口鳝鱼滩的短叶茳芏湿地、互花米草湿地以及二者的交错带湿地为研究对象,采用定位研究方法探讨了互花米草入侵影响下湿地土壤有效硅含量的时空变化特征。结果表明:互花米草入侵影响下3块湿地土壤有效硅含量随时间推移整体呈波动上升趋势;互花米草入侵显著提高了鳝鱼滩湿地30—60 cm土层土壤有效硅含量(P0.01),与短叶茳芏湿地相比,交错带湿地和互花米草湿地30—60 cm土层土壤有效硅含量分别增加了8.56%和19.97%,逐步线性回归分析表明土温和电导是影响其变化的重要因素(P0.01)。研究互花米草入侵影响下湿地土壤有效硅含量的变化特征,对于揭示湿地生态系统生源要素硅生物地球化学循环过程以及互花米草入侵及其扩张机制具有重要意义。     

闽江河口湿地植物与土壤灰分及其影响因子分析

以闽江河口鳝鱼滩湿地生长的芦苇(Phragmitesaustralis)和互花米草(Spartina alterniflora)为研究对象,并对相应的36个土壤剖面进行取样分析,揭示它们的(厂火)分含量分布特征,并对其影响因子进行分析。研究结果表明:闽江河口鳝鱼滩湿地芦苇和互花米草各个器官(厂火)分含量的差异性明显,芦苇各部位(厂火)分含量的平均值大于互花米草;芦苇和互花米草湿地土壤(厂火)分含量的垂直分布较为类似,芦苇湿地土壤(厂火)分合量略高于互花米草湿地土壤(厂火)分含量,但两种植物土壤(厂火)分含量的差异并不显著;芦苇和互花米草湿地土壤(厂火)分含量与土壤有机碳有极其显著的负相关关系,与土壤含水量的相关性也较明显;从单一的植物类型来看,互花米草湿地土壤(厂火)分含量与容重、碳含量、含水量和盐度呈显著的相关关系,芦苇湿地土壤(厂火)分含量与土壤pH值有明显的正相关关系。     

闽江口湿地土壤全氮含量的高光谱遥感估算

氮是湿地生态系统重要生源要素,基于高光谱(350~2500 nm)遥感数据对其进行估算以实现湿地土壤全氮(TN)含量无损、快速和准确定量化具有重要意义。选取闽江河口湿地为研究区,于2013年5月,沿潮滩(高潮滩到中潮滩)采集16个土壤剖面80个样本,室内测定其光谱反射率和TN含量,并基于原始反射率(R)和光谱指数(比值指数RI、归一化指数NDI和差值指数DI)建立土壤TN含量高光谱估算模型,并进一步分析反射光谱与铵态氮(NH_4~+-N)、硝态氮(NO_3~--N)、有机质(SOM)和电导率(EC)之间的关系,以期揭示河口湿地土壤TN含量估算的机理。结果表明:土壤光谱反射率在350~600 nm,表现为高潮滩中潮滩,而在600~2500 nm,表现为高潮滩中潮滩;闽江河口湿地土壤TN含量与R在500 nm附近相关关系较好,并在490 nm有最大相关系数(-0.508);RI、NDI和DI大大提高了反射光谱与土壤TN含量的相关关系,其相关系数较高区域集中在600~1000 nm的波段组合,以RI(590,640)、RI(610,940)、NDI(940,590)、NDI(940,610)、DI(640,920)和DI(640,940)相关关系表现较好,能较好地实现研究区湿地土壤TN含量反演,其估算与检验模型r~2均大于0.610,RMSE均小于0.208,其中以RI(610,940)估算精度最好,估算与检验模型r~2分别为0.832和0.631,RMSE分别为0.178和0.202;闽江口湿地土壤TN含量与SOM含量密切相关是土壤TN含量估算的重要机理,而NH_4~+-N、NO_3~--N和盐分含量对其估算精度影响不大。     

干旱胁迫下冬小麦(Triticum aestivum)高光谱特征和生理生态响应

2006年于冬小麦(Triticum aestivum)孕穗期、开花期和灌浆期,采用ASD Fieldspec HH光谱仪测定了不同水分胁迫下冬小麦高光谱反射率、红边参数和对应的冬小麦生理生态参数叶绿素a(Chla)、叶绿素b(Chlb)、叶绿素a b(Chla b),叶片水分含量(LWC),叶面积指数(LAI).结果表明,冬小麦生理生态参数随生长发育呈现先上升后下降趋势,Chla、Chlb和Chla b开花期达最大值;LWC和LAI孕穗期达最大值.随干旱胁迫程度增加,Chla、Chlb和Chla b、LWC和LAI减少.不同水分处理下冬小麦高光谱反射率具有绿色植物特征.用红边一阶微分光谱特征参数分析,冬小麦孕穗期和开花期红边(λred)位于728～730nm,灌浆期红边(λred)移到734nm.Chla、Chlb和Chla b与Dλ730:Dλ702、Dλ730:Dλ718,LWC与Dλred、Dλ718以及LAI与Dλ718、Dλred、Sred均呈正相关,相关系数大于0.5(p<0.05).经回归分析,Chl与Dλ730:Dλ702、LWC与Dλred呈线性关系(R2=0.87),LAI与Sred呈二次关系(R2=0.68).因此,用冬小麦高光谱特征及红边参数能判断冬小麦生育后期长势和农田水分胁迫程度.     

不同干旱条件下夏玉米全生育期冠层吸收光合有效辐射比的高光谱遥感反演

冠层吸收光合有效辐射比(fAPAR)是植被生产力遥感模型的重要参数.但关于不同干旱条件下作物全生育期的fAPAR遥感反演研究仍未见报道.本研究利用2015年夏玉米5个灌水处理模拟试验的高光谱反射率和fAPAR观测资料,分析了不同干旱条件下夏玉米关键生育期fAPAR和高光谱反射率变化特征,探讨了fAPAR与反射率、一阶导数光谱反射率和植被指数的关系.结果表明: 轻度水分胁迫和充分供水条件下,fAPAR较高;重度水分胁迫和重度持续干旱条件下,fAPAR较低.冠层可见光、近红外光和短波红外光区的反射率与fAPAR分别呈负相关、正相关和负相关关系.fAPAR与可见光和短波红外光区的383、680和1980 nm附近的反射率的相关性最强,相关系数均达-0.87.一阶导数光谱反射率与fAPAR相关性强且稳定的波段为580、720和1546 nm,相关系数分别为-0.91、0.89和0.88. 9个常用植被指数与fAPAR呈线性或对数关系,其中,增强型植被指数、复归一化植被指数、土壤调节植被指数和修正的土壤调节植被指数与fAPAR的关系模型最好,决定系数(R²)均在0.88以上,平均相对误差分别为16.6%、16.6%、16.7%和16.2%;基于一阶导数光谱反射率与fAPAR的对数关系在(720±5) nm波段处的模拟效果较好,R²达0.86;直接选择反射率数据估算fAPAR的效果较差,R²最高为0.81.研究结果可为fAPAR的准确反演及评估作物干旱状况提供支撑.     

水稻上部叶片叶绿素含量的高光谱估算模型

叶片叶绿素 (Chl) 状况是评价植株光合效率和营养胁迫的重要指标,实时无损监测Chl状况对作物生长诊断及氮素管理具有重要意义.以不同生态点、不同年份、不同施氮水平、不同类型水稻品种的4个田间试验为基础,于主要生育期同步测定了水稻主茎顶部4张叶片的高光谱反射率及Chl含量,并计算了350～2500 nm范围内任意两波段组合而成的比值(SR[λ1,λ2])和归一化(ND[λ1,λ2])光谱指数以及已报道的对Chl敏感的光谱指数,进一步系统分析了叶片Chl含量与上述光谱指数之间的定量关系.结果表明,红边波段的比值和归一化光谱指数可以较好地预测水稻上部4叶的Chl含量(R~2>0.9),但对于不同Chl指标其最佳组合波段有所差异.估算叶绿素a (Chla)、叶绿素总量(Chla+b)和叶绿素b (Chlb)的最佳比值光谱指数分别为SR(724,709)、SR(728,709)和SR(749,745),方程拟合决定系数R~2分别是0.947、0.946、0.905;最佳归一化光谱指数分别为ND(780,709)、ND(780,712)和ND(749,745),R~2分别是0.944、0.943、0.905.引入445 nm波段反射率对上述光谱指数进行修正,可以降低叶片表面反射差异的影响,提高模型的应用范围.利用不同年份独立的试验资料对所建模型进行了检验,结果表明,修正型比值光谱指数 mSR(724,709)、mSR(728,709) 和 mSR(749,745),以及修正型归一化光谱指数mND(780,709)、mND(780,712) 和 mND(749,745) 预测 Chla、Chla+b 和 Chlb 的效果更好,其测试的RMSE分别为 0.169、0.192、0.052、0.159、0.176、0.052,RE分别为8.18%、7.74%、13.01%、8.26%、7.59%、12.96%,均较修正前降低,说明修正后的光谱指数普适性更好.     

闽江河口湿地土壤全磷高光谱遥感估算

磷是湿地生态系统必需和限制性元素,利用高光谱遥感数据对其进行估算对实现湿地土壤磷素快速和准确定量具有重要意义。选取闽江河口湿地作为研究区,于2013年5月,采集16个土壤剖面80个样本作为估算与验证模型样本;基于光谱指数建立土壤全磷(TP)含量估算模型,其中光谱指数包括原始光谱反射率(R)、比值土壤指数(RSI)、归一化土壤指数(NDSI)和有机质诊断指数(OII)。此外进一步分析反射光谱与不同形态磷,TP与有机质之间关系,以期初步揭示河口湿地土壤TP估算的机理。研究结果表明,闽江河口湿地土壤TP含量与R相关系数较高的区域分布在360-560 nm,并在406 nm处达到最大值-0.816;光谱指数RSI(R_(430),R_(830))、RSI(R_(460),R_(810))、RSI(R_(560),R_(580))、NDSI(R_(430),R_(830))、NDSI(R_(460),R_(830))、NDSI(R_(560),R_(580))和OII(R_(446))与土壤TP含量均有较高的相关系数,能较好的用于TP含量的估算;各估算模型决定系数(r~2)和均方根误差(RMSE)分别在0.657-0.805和0.052-0.067之间;验证模型r~2和RMSE分别在0.606-0.893和0.037-0.044之间。分潮滩建立TP含量估算模型是可行的,并且能提高部分光谱指数的估算精度。土壤TP含量的估算精度与磷素的组成有关,其中与铁吸附态磷关系较为密切,钙吸附态和铝吸附态磷关系较弱。土壤TP与有机质和氧化还原环境的存在密切关系可能是湿地土壤TP含量估算的重要机理。     

基于无人机高清数码影像和高光谱遥感数据反演大豆典型生育期氮平衡指数

氮平衡指数(NBI)是反映作物长势的重要指标之一.通过测量NBI可以快速监测作物氮肥盈亏状况,为农业生产和管理提供精准信息.本文以无人机高清数码影像和高光谱遥感数据,以及地面实测大豆NBI数据为基础,分析大豆从开花期到成熟期,原始光谱和红外、近红外波段的导数光谱与NBI的相关性,筛选敏感波段并计算植被指数.采用经验模型法构建NBI反演模型,通过分析验证模型的决定系数(R^2)和均方根误差(RMSE),得出最佳反演模型.结果表明:大豆NBI与导数光谱反射率的相关性好于与原始光谱反射率的相关性;本文筛选的14个植被指数中,除了导数光谱光化学植被指数与大豆NBI呈不显著相关外,其余13个植被指数与大豆NBI呈极显著相关;利用13个植被指数构建NBI反演模型,并分析模型反演精度,结果显示,利用导数光谱差值植被指数构建NBI反演模型的精度最高,R^2和RMSE分别为0.771和3.077,利用该模型生成大豆典型生育期NBI分布图,能够反映大豆的长势状况.通过多载荷无人机获取的高清数码影像和高光谱遥感数据进行NBI估算,能够实时、动态、非破坏性、快速有效地监测大豆氮素营养状况,可为大豆氮肥精确管理提供简便实用的方法.     

互花米草入侵对黄河三角洲湿地表层沉积物金属元素分布格局的影响

互花米草被引入后迅速生长蔓延,已成为黄河三角洲河口湿地主要入侵物种,极大影响了河口湿地沉积物表层重金属元素分布格局。本研究选取不同入侵年限(3、5、7、10、15和20年)的互花米草湿地以及芦苇湿地、盐地碱蓬湿地、柽柳湿地和光滩湿地,采集表层沉积物并测定Ca、Fe、Mg、Mn、Zn、Ni、Pb、Cr、Cd、Cu和Li元素含量,采用富集系数及地累积指数法对污染水平进行评价,分析互花米草入侵对元素分布格局的影响。结果表明：(1)随入侵时间推进,互花米草湿地表层沉积物有机碳(SOC)和总氮(TN)含量要大于本土植被覆盖湿地表层沉积物含量。本土植物所在湿地沉积物重金属含量要高于互花米草入侵湿地沉积物重金属含量。(2)Ca处于中度富集状态,而Cd可能造成本地区中度污染。(3)重金属元素之间具有显著相关关系,尤其是Fe、Mn元素与Mg、Zn、Cu元素相关性较大,互花米草湿地中的大多数元素变化主要受岩石圈基岩风化和泥沙搬运沉积影响。     

Best hyperspectral indices for assessing leaf chlorophyll content in a degraded temperate vegetation

Extensive studies have focused on assessing leaf chlorophyll content through spectral indices; however, the accuracy is weakened by limited wavebands and coarse resolution. With hundreds of wavebands, hyperspectral data can substantially capture the essential absorption features of leaf chlorophyll; however, few such studies have been conducted on same species in various degraded vegetations. In this investigation, complete combinations of either original reflectance or first‐order derivative spectra we conducted a complete combination on either original reflectance or its first‐order derivative value from 350 to 1000 nm to quantify leaf total chlorophyll (Chll), chlorophyll‐a (Chla), and chlorophyll‐b (Chlb) contents. This was performed using three hyperspectral datasets collected in situ from lightly, moderately, and severely degraded vegetations in temperate Helin County, China. Suitable combinations were selected by comparing the numbers of significant correlation coefficients with leaf Chll, Chla, and Chlb contents. The combinations of reflectance difference (D_ij), normalized differences (ND), first‐order derivative (FD), and first‐order derivative difference (FD(D)) were found to be the most effective. These sensitive band‐based combinations were further optimized by means of a stepwise linear regression analysis and were compared with 43 empirical spectral indices, frequently used in the literature. These sensitive band‐based combinations on hyperspectral data proved to be the most effective indices for quantifying leaf chlorophyll content (R² > 0.7, p < 0.01), demonstrating great potential for the use of hyperspectral data in monitoring degraded vegetation at a fine scale.     

利用高光谱参数反演水稻叶片类胡萝卜素含量

为了探讨快速、准确预测水稻(Oryza sativa)叶片类胡萝卜素(Car)含量的敏感光谱波段和光谱指数, 通过实施涉及不同年份、不同生态点、不同施氮水平和不同品种类型的4个田间试验, 于主要生育期同步测定了水稻顶部4张叶片的光谱反射率及Car含量, 系统分析了350-2 500 nm范围内任意两波段组合而成的比值(SR (λ1, λ2))、归一化(ND (λ1, λ2))及已报道的对Car敏感的光谱指数与水稻叶片Car含量间的定量关系。结果表明, 不同Car含量水平下水稻叶片光谱反射率存在着明显变化, 以绿光及红边波段对水稻叶片Car含量变化最为敏感。723 nm附近的波段与近红外波段的比值组合以及713 nm附近的波段与近红外波段的归一化组合可以较好地预测水稻叶片Car含量, 以SR (723, 770)和ND (770, 713)表现最好, 线性拟合R²分别达到0.897和0.898。基于独立的试验资料的检验表明, 预测值和实测值的拟合R²分别为0.856和0.858, 均方根差RMSE均为0.072, 平均相对误差RE分别为11.9%和12.0%, 表明SR (723,770)和ND (770, 713)可有效地估算水稻上部叶片的Car含量。     

叶冠尺度野鸭湖湿地植物群落含水量的高光谱估算模型

利用高光谱遥感技术定量估测野鸭湖湿地植被含水量,对于监测和诊断野鸭湖湿地植被的生理状况及生长趋势具有重要意义,也能够为高光谱遥感影像在野鸭湖湿地植被含水量诊断中的实际应用提供理论依据和技术支持.采用Field Spec 3野外高光谱辐射仪,获取了野鸭湖典型湿地植被冠层和叶片的光谱,并测定了对应的含水量.以上述实测数据为基础,首先以芦苇为例初步探明了不同含水量水平下典型湿地植被冠层和叶片光谱反射率的响应模式,然后采用相关性及单变量线性与非线性拟合分析技术,从冠层和叶片两种层次,对不同尺度下的含水量与“三边”参数及高光谱植被指数进行了分析拟合,并采用交叉检验中的3K-CV方法对估算模型进行了测试和检验,确立了不同尺度下野鸭湖湿地植被含水量的定量监测模型.结果表明:(1)随着含水量水平的增加,芦苇冠层与叶片光谱在可见光波段(350-760 nm)和红外波段(760-2500 nm)的反射率均呈逐渐降低趋势.(2)不同尺度含水量与选取的光谱特征参数整体上相关性较强,与“三边”参数基本上都呈极显著相关,相关系数最大达到0.906;与高光谱指数全部呈极显著相关,相关系数最小为0.455,最大达到0.919,并通过选取不同尺度上相关性最佳的光谱特征参数,分别基于“三边”参数和高光谱植被指数构建了不同尺度下的含水量估算模型.其中,冠层尺度下,黄边面积(SDy)与SRWI( Simple Ratio Water Index)的估算效果最好,估算模型分别为y=-9.462x2 -2.671x+0.608和y=0.219e1.010x;叶片尺度下,红边面积(SDr)与WI( Water Index)的估算效果最好,估算模型分别为y=0.562x+0.376和y=2.028x2 -0.476x-1.009.通过3K-CV的交叉验证,不同尺度下的含水量估算模型均取得了较为理想的预测精度,预测精度的最小值为94.92％,最大值为97.06％,表明估测模型具有较高的可靠性与普适性.(3)高光谱植被指数与含水量拟合方程的拟合度相对高于“三边”参数与之建立方程的拟合度,说明多波段组合的光谱特征参数更适合含水量的判别.     

基于实地调查和高光谱数据的浑善达克沙地中部植物alpha多样性遥感估测

植物群落物种多样性的快速无损估测一直是近几十年生态学领域的热点研究问题。相对于大尺度的卫星遥感数据,高光谱遥感数据具有光谱和空间分辨率高的优势。采用ASD HH2便携式高光谱仪,收集浑善达克沙地中部120个样方的高光谱数据,并对样方的alpha多样性指数进行同步测定。对高光谱遥感数据进行预处理,采用相关性分析、主成分分析和经验波段筛选法,从数百个波段中选择敏感波段。采用90个样方的高光谱数据作为训练样本,对筛选的敏感波段进行多元线性逐步回归分析,获得12个回归模型。采用另外30个样方的高光谱数据作为验证样本,对回归模型的拟合效果进行检验。结果发现,采用主成分分析法提取敏感波段的回归模型拟合效果最好,Pielou指数、Shannon-Wiener指数和Simpson指数拟合均达到显著水平。对我国植物物种多样性微尺度的快速评估和高光谱遥感具有一定参考意义,并对未来植物多样性高光谱遥感研究提出了建议。     

Effects of iron on growth and reflectance spectrum of the bloom‐forming cyanobacterium Microcystis viridis

Iron is an important factor in algal blooms because it is involved in cyanobacterial pigment biosynthesis and therefore has the ability to influence the pigment status of algal cells. This role in pigment biosynthesis offers the opportunity for rapid monitoring of iron availability to cyanobacteria through spectral reflectance characterization. In the present study, the freshwater cyanobacterium Microcystis viridis was cultured with different levels of iron. Cell density, cellular content of iron and photosynthetic pigments, and spectral reflectivity of M. viridis were determined daily during the course of the culture experiment. The results showed that at the lowest iron concentration (0.01 μM) the growth of M. viridis was seriously limited, and the maximal cell density was only approximately 6.4% of the density observed with an iron concentration of 18 μM. Iron availability dramatically affected chlorophyll a, carotenoid and phycocyanin content, with the greatest impact on chlorophyll a. The iron‐induced changes in content and ratios of pigments were detectable through spectral reflectance. Eleven spectral indices previously developed for the estimation of concentrations and/or ratios of pigments and a newly proposed chlorophyll a/phycocyanin index were found to be suitable for generating sensitive regression models between cellular iron content and spectral parameters. The comprehensive application of key sensitive spectral indices and regression equations should help to support monitoring and diagnosis of iron availability to cyanobacteria via remote sensing.     

桉树叶片光合色素含量高光谱估算模型

色素在植物的生理生态过程中非常重要,利用高光谱数据,揭示光谱反射率上特征波段与光合色素含量间的关系将有助于理解光合色素光谱反射特征的规律,同时为利用高光谱遥感技术快速无损监测植物叶片光合色素提供了技术支持.利用野外采集的桉树叶片样本,在实验室内测定了叶片的高光谱反射率及对应的叶绿素、类胡萝卜素含量.利用光谱分析技术和统计学方法对光谱数据进行处理分析,提取了光谱特征参量,并建立叶绿素、类胡萝卜素含量与光谱特征参量间的估算模型.通过精度检验,研究结果表明以(SDr-SDb)/(SDr+SDb)为变量建立的指数模型估算效果最佳.     

基于高光谱遥感的小麦冠层叶片色素密度监测

作物叶片色素状况是评价植株光合效率和营养胁迫的重要指标,冠层叶片色素密度（单位土地面积叶片色素总量）的实时无损监测对作物生长诊断、产量估算及氮素管理具有重要意义。以包括不同品质类型（高蛋白、中蛋白和低蛋白）的多个小麦品种在不同施氮水平下的连续2a大田试验为基础,研究了小麦叶片色素密度与冠层高光谱参数的定量关系。结果表明,叶片色素（叶绿素a、叶绿素b、叶绿素a＋b和类胡萝卜素）密度随施氮水平增加而提高,不施氮处理的叶片色素密度随生育进程而下降,施氮处理的叶片色素密度呈单峰曲线,品种间存在明显差异。群体叶片色素密度的敏感波段主要分布在可见光区,而红边区域导数光谱表现更显著。光谱参数VOG2、VOG3、RVI（810,560）、SRE／SBE和SDr／SDb等与叶绿素密度关系较为密切,线性方程决定系数R^2均在0．858以上,而与类胡萝卜素密度关系减弱,决定系数R^2低于0．780,且参数间差异较小。经独立试验资料的检验表明,VOG2、VOG3、SRE／SBE和SDr／SDb对不同色素的估测结果较好,预测相对误差RE低于17．6％,虽然对叶绿素b的准确性稍低。总体上,光谱参数VOG2、VOG3、SRE／SBE和SDr／SDb与小麦群体叶片色素密度关系密切,特别是对叶片叶绿素a和叶绿素a＋b的密度可以进行准确可靠的实时监测。     

Spectral reflectance indices and pigment functions during leaf ontogenesis in six subtropical landscape plants

Pigment combinations are regulated during leaf ontogenesis. To better understand pigment function, alterations in chlorophyll, carotenoid and anthocyanin concentrations were investigated during different leaf development stages in six subtropical landscape plants, namely Ixora chinensis Lam, Camellia japonica Linn, Eugenia oleina Wight, Mangifera indica L., Osmanthus fragrans Lowr and Saraca dives Pierre. High concentrations of anthocyanin were associated with reduced chlorophyll in juvenile leaves. As leaves developed, the photosynthetic pigments (chlorophyll and carotenoid) of all six species increased while anthocyanin concentration declined. Chlorophyll fluorescence imaging of Φ_PSII (effective quantum yield of PSII) and of NPQ (non-photochemical fluorescence quenching) and determination of electron transport rate-rapid light curve (RLC) showed that maximum ETR (leaf electron transport rate), Φ_PSII and the saturation point in RLC increased during leaf development but declined as they aged. Juvenile leaves displayed higher values of NPQ and Car/Chl ratios than leaves at other developmental stages. Leaf reflectance spectra (400–800 nm) were measured to provide an in vivo non-destructive assessment of pigments in leaves during ontogenesis. Four reflectance indices, related to pigment characters, were compared with data obtained quantitatively from biochemical analysis. The results showed that the ARI (anthocyanin reflectance index) was linearly correlated to anthocyanin concentration in juvenile leaves, while a positive correlation of Chl NDI (chlorophyll normalized difference vegetation index) to chlorophyll a concentration was species dependent. Photosynthetic reflectance index was not closely related to Car/Chl ratio, while a structural-independent pigment index was not greatly altered by leaf development or species. Accordingly, it is suggested that the high concentration of anthocyanin, higher NPQ and Car/Chl ratio in juvenile leaves are important functional responses to cope with high radiation when the photosynthetic apparatus is not fully developed. Another two leaf reflectance indices, ARI and Chl NDI, are valuable for in vivo pigment evaluation during leaf development.     

Bio-optical modeling of photosynthetic pigments in corals

The spectral reflectance of coral is inherently related to the amounts of photosynthetic pigments present in the zooxanthellae. There are no studies, however, showing that the suite of major photosynthetic pigments can be predicted from optical reflectance spectra. In this study, we measured cm-scale in vivo and in situ spectral reflectance for several colonies of the massive corals Porites lobata and Porites lutea, two colonies of the branching coral Porites compressa, and one colony of the encrusting coral Montipora flabellata in Kaneohe Bay, Oahu, Hawaii. For each reflectance spectrum, we collected a tissue sample and utilized high-performance liquid chromatography to quantify six major photosynthetic pigments, located in the zooxanthellae. We used multivariate multiple regression analysis with cross-validation to build and test an empirical linear model for predicting pigment concentrations from optical reflectance spectra. The model accurately predicted concentrations of chlorophyll a, chlorophyll c ₂, peridinin, diadinoxanthin, diatoxanthin and β-carotene, with correlation coefficients of 0.997, 0.941, 0.995, 0.996, 0.980 and 0.984, respectively. The relationship between predicted and actual concentrations was 1:1 for each pigment, except chlorophyll c ₂. This simple empirical model demonstrates the potential for routine, rapid, non-invasive monitoring of coral-zooxanthellae status, and ultimately for remote sensing of reef biogeochemical processes.     

Surface reflectance properties of Antarctic moss and their relationship to plant species, pigment composition and photosynthetic function

In this study the variations in surface reflectance properties and pigment concentrations of Antarctic moss over species, sites, microtopography and with water content were investigated. It was found that species had significantly different surface reflectance properties, particularly in the region of the red edge (approximately 700 nm), but this did not correlate strongly with pigment concentrations. Surface reflectance of moss also varied in the visible region and in the characteristics of the red edge over different sites. Reflectance parameters, such as the photochemical reflectance index (PRI) and cold hard band were useful discriminators of site, microtopographic position and water content. The PRI was correlated both with the concentrations of active xanthophyll‐cycle pigments and the photosynthetic light use efficiency, F_v/F_m, measured using chlorophyll fluorescence. Water content of moss strongly influenced the amplitude and position of the red‐edge as well as the PRI, and may be responsible for observed differences in reflectance properties for different species and sites. All moss showed sustained high levels of photoprotective xanthophyll pigments, especially at exposed sites, indicating moss is experiencing continual high levels of photochemical stress.