Model of Zooplankton Optimal Current Feeding9
微塑料对大型溞摄食和抗氧化防御系统的影响

Daphnia magna.
Keywords: microplasticsꎻ Daphnia magnaꎻ accumulationꎻ residenceꎻ filtration rateꎻ feeding rateꎻ antioxidant system
control groupꎬ respectively. Furthermoreꎬ the activity of superoxide dismutase and catalaseꎬ and the content of malondialdehyde in
Daphnia magna increased significantlyꎬ and the oxidative system of Daphnia magna was damaged. Overallꎬ the exposure of MPs can cause
. 由于水生生物对
. 因此ꎬ微塑料的生态风险及其对人体健康的
威胁引起了国内外高度关注 [15] .
大型溞( Daphnia magna) 属于浮游甲壳类动物ꎬ
常被用作水生生物毒理学研究的标准测试生物
[16]
ꎬ
作为淡水水体中广泛存在的浮游动物ꎬ又是鱼类等养
殖动物幼苗期的主要饵料ꎬ因此其在水生食物链中占
lifengmin@ ouc.edu.cn
基金项目: 国家重点研发计划项目( No.2018YFC0406304) ꎻ 山东省重大科技创新工程( No.2019JZZY020302)
日本海太平洋褶柔鱼生物学特征的年际变化

2012):W=aLb,式中,W 为体质量(单位 g),L 为胴长(单位 mm),a 和 b 为参数。不 同胴长组内性成熟个体的比例和胴长组数据采用线性回归, 拟合 Logistic 曲线, 推算不同性别 太平洋褶柔鱼的初次性成熟胴长(Tafur et al. 2001): p i
①*
①
ZHANG Heng
①
ZHU
CUI Xue-Sen
①Key Laboratory of East China Sea & Oceanic Fishery Resources Exploitation and Utilization , Ministry of Agriculture, East China Sea fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai ②China Aquatic Products Zhoushan Marine Fisheries Corporation, Zhoushan 316101, China 200090;
太平洋褶柔鱼(Todarodes pacificus)属头足纲枪形目柔鱼科褶柔鱼属,为暖温带种,仅 分布在太平洋西北海域和东太平洋的阿拉斯加湾,是世界上头足类最早被大规模开发利用的 种类之一,主要的捕捞渔场分布在西太平洋的 21° ~50° N 海域,即日本海以及中国的黄海、东 海(郑元甲等 2003,王尧耕等 2005)。日本海海域存在着较为复杂的海流,在太平洋一侧 为黑潮和亲潮,日本海一侧为对马海流、东朝鲜暖流和里曼寒流,相互交汇形成流隔,饵料 生物丰富,为太平洋褶柔鱼聚集索饵形成创造了条件(宋海棠等 2009)。 早在 18 世纪中叶,日本就开发利用了其沿岸水域所有头足类。我国于 1989 年 8 月首次 赴日本海俄管水域进行调查与试捕。1990 年开始,我国的鱿钓船在日本海正式进入商业性生 产。随着专属经济区(Exclusive Economic Zone,简称 EEZ)的划定和流刺网的禁止使用,目 前我国约有几十艘鱿钓船在日本海以购买配额制的方式于每年的 11~12 月在其指定海域进行 生产作业。国外学者在种群变动、资源密度、空间分布等方面对日本海太平洋褶柔鱼做了相 关研究(Bower et al. 1999,Yamamoto et al. 2002,Choi et al. 2008,Hideaki 2008),但国内研 究甚少 (陈新军 1997) 。 日本海海域的太平洋褶柔鱼资源量常出现剧烈变动 (程家骅等 2005) , 同时作为一年生的软体动物,其群体结构时刻更新,资源密度及群体结构状况易受海况变化、 捕捞水平等因素影响,年间波动较大(Kasahara 1978)。本研究利用 2010~2013 年连续 4 年 在日本海海域渔业资源调查取得的样本, 对太平洋褶柔鱼渔获物的群落结构进行了年际分析, 为了解日本海太平洋褶柔鱼渔汛期的群体组成及主要生物学特征,掌握资源的变动规律,实 现资源的合理利用提供基础数据。
东太平洋大眼金枪鱼自由鱼群栖息地偏好的时空分布特征

文章编号:1674-5566(2020)06-0889-10DOI:10.12024/jsou.20191202874东太平洋大眼金枪鱼自由鱼群栖息地偏好的时空分布特征收稿日期:2019-12-10修回日期:2020-02-09基金项目:国家自然科学基金(31902426,41806110);上海市青年科技英才杨帆计划(19YF1419800);中国博士后科学基金面上项目(2019M651475)作者简介:黄金玲(1975—),女,博士研究生,研究方向为渔业资源、法规和管理。
E-mail:jlhuang@shou.edu.cn通信作者:王学昉,E-mail:xfwang@shou.edu.cn黄金玲1,戴黎斌2,王学昉2,3,4,5,6,周成2,3,4,5,6,唐浩2,3,4,5,6(1.上海海洋大学海洋文化与法律学院,上海201306;2.上海海洋大学海洋科学学院,上海201306;3.国家远洋渔业工程技术研究中心,上海201306;4.大洋渔业资源可持续开发教育部重点实验室,上海201306;5.农业农村部大洋渔业开发重点实验室,上海201306;6.农业农村部大洋渔业资源环境科学观测实验站,上海201306)摘要:基于美洲间热带金枪鱼委员会(Inter-American Tropical Tuna Commission,IATTC)收集的2015—2017年东太平洋大眼金枪鱼自由鱼群围网捕捞数据和相匹配的卫星遥感数据,使用二阶提升回归树模型(boosted regression tree,BRT)建立该鱼群的栖息地模型,以探究其时空分布特征。
研究结果表明,相对于环境因子,空间因子对大眼金枪鱼自由鱼群的丰度有更大的影响。
环境因子方面,纬度、经度、混合层深度、月份和海表面温度是影响大眼金枪鱼捕获成功率的主要影响因子,而影响丰度的主要因子为经度和海表面叶绿素a浓度。
空间上,大眼金枪鱼主要处于10ʎS以南,95ʎW以西的海域。
20--阙江龙_new_

中国水产科学 2015年9月, 22(5): 1027-1035 Journal of Fishery Sciences of China研究论文收稿日期: 2014-12-12; 修订日期: 2015-02-10.基金项目: 国家自然科学基金项目(41176131); 国家973计划项目(2010CB428705).作者简介: 阙江龙(1988–), 男, 研究实习员, 从事海洋生态学研究. E-mail: quejianglong@ 通信作者: 徐兆礼, 研究员. Tel: 021-********; E-mail: 1074527784@DOI: 10.3724/SP.J.1118.2015.15099北部湾西北部饵料浮游动物季节变化及其与鱼卵、仔稚鱼的关系阙江龙, 徐兆礼, 孙鲁峰中国水产科学研究院 东海水产研究所, 农业部海洋与河口渔业重点开放实验室, 上海 200090摘要: 根据2012年在北部湾西北部广西近海冬、春、夏和秋4个季节的调查资料, 探讨了该海域浮游动物总丰度的平面分布、季节变化及鱼卵仔稚鱼的丰度的季节变化, 结果表明, 调查水域浮游动物的丰度在春夏、秋冬季变化较大, 而在冬春与夏秋季变化较小, 浮游动物在冬、春、夏、秋四季的平均丰度分别为337.35 ind/m 3、280.01 ind/m 3、4.32 ind/m 3和14.78 ind/m 3, 冬春季明显高于夏秋季, 浮游动物数量高峰季比东海提前了一个季节。
冬春两季, 浮游动物的数量分布特征相近, 在湾内和沿岸水域数量高于近海水域。
相反, 在夏秋季, 丰度在近海水域明显高于沿岸及湾内水域。
浮游动物在各季节不同的分布特征与该海域沿岸水、外海水和混合水的季节性变化有关, 优势种经历了由春季的沿岸暖温种到夏季和秋季的外海暖水种到冬季的沿岸暖水种更替的过程。
该海域的主要优势种, 冬季为溞鸟喙尖头(Penilia avirostris ), 春季为中华哲水蚤(Calanus sinicus ), 夏季和秋季同为肥胖软箭虫(Flaccisagitta enflata ), 主要优势种类的生态适应性决定了浮游动物总数量的分布特征。
4292314625沉积物中浮游有孔虫的分布与海洋环境

第34卷 第5期海 洋 与 湖 沼V ol.34,N o.5 2003年9月OCE ANO LOGIA ET LI MNO LOGIA SINIC A Sep.,2003 冲绳海槽北部表层沉积物中浮游有孔虫的分布与海洋环境3孙荣涛 李铁刚 曹奇原 向 荣(中国科学院海洋研究所 青岛 266071;中国科学院研究生院 北京 100039) (中国科学院海洋研究所 青岛 266071) (中国海洋大学海洋地球科学学院 青岛 266003)提要 为查明冲绳海槽北部浮游有孔虫动物群的分布特征与海洋环境之间的关系,对1992年6月和1999年6月两次采自冲绳海槽北部111个表层沉积物中的浮游有孔虫进行了鉴定和统计,并利用Q型因子分析方法对其群落组合特征进行了分析。
结果表明,冲绳海槽北部浮游有孔虫主要有3个因子组合。
以G lobigerinita glutinata(Egger)为代表的主因子1主要分布在东南侧的黑潮主干和对马暖流控制区内,同时受西侧陆架冷水影响的部分站位也显示了较高的载荷值。
G1glutinata的种群特征显示,黑潮主干和对马暖流控制区以大个体分子为主,而小个体分子主要集中在受冷水影响的陆架浅水区。
因此,G1glutinata很可能是30°N以北海域黑潮及其分支流系的优势种,而其小个体分子在陆架浅水的存在可能与东海冷涡沉积动力环境相关。
以浅生种G lobigerinoides ruber(d’Orbigny)为代表的主因子2主要分布在研究区西侧和北侧水深100—150m之间的陆架浅水区。
以Neogloboquadrina dutertrei(d’Orbigny)和Pulleniatina obliquiloculata(Parker&Jones)为代表的主因子3,主要分布在研究区中部的黑潮和对马暖流与陆架水的混合区内。
因此,冲绳海槽北部浮游有孔虫动物群的分布受到海流、水团、水深等多种海洋环境因素的影响。
光照和营养盐对浮游动物和浮游植物生物量及其营养联系的影响

生态环境学报 2018, 27(6): 1122-1127 Ecology and Environmental Sciences E-mail: editor@基金项目:国家自然科学基金项目(31200361);中南民族大学中央高校专项基金项目(CZY16012;CZY17016) 作者简介:王松波(1979年生),男,副教授,博士,主要从事浮游动物生态学研究。
E-mail: wangsb18@*通信作者收稿日期:2018-02-02光照和营养盐对浮游动物和浮游植物生物量及其营养联系的影响王松波*,余俊爽,曹艳敏,吴来燕中南民族大学资源与环境学院,湖北 武汉 430074摘要:水生态系统中物质(营养盐)和能量(光照)输入的不平衡能影响浮游动物和浮游植物的生长,但两者的交互作用在浮游生物现存量的预测中还较少涉及。
通过对湖北省内14个水体进行春采样,研究了光照和营养盐的交互作用对浮游动植物生物量预测能力的影响,并探讨了两者对浮游动植物间营养联系的影响,以期为湖泊生态系统的监测和管理提供理论依据。
研究结果显示:浮游植物和浮游动物生物量均与营养盐不存在显著相关性;ρChl a 与漫射衰减系数(K d )(r =0.526,P =0.036)和光照×营养盐(r =0.57~0.70,P <0.05)均呈显著正相关;浮游甲壳动物的生物量随着K d 增加而显著减少(r =−0.544,P =0.029)。
浮游动物、植物生物量之比(ρZ /ρP )随着K d (r =−0.651,P =0.006)和营养状态指数(TSI )(R 2=0.64,P <0.001)的增加而显著下降,表明两者之间的营养联系在低光照、高营养盐的环境下变弱。
逐步线性回归分析显示:浮游甲壳动物生物量能够单独被K d 更好地预测(R 2=0.30,P =0.029);光照和总溶解性氮的交互作用提高了多元线性回归模型对ρChl a (R 2=0.47,P =0.003)和ρZ /ρP (R 2=0.45,P =0.004)的预测。
(水生生物学Hydrobiology)第一章浮游动物
第三节 轮虫 ROTIFERA
轮虫(rotifers)是一 类小型、具具完全消 化管、假体腔、前端 具纤毛头冠的低等后 生动物。 头冠纤毛摆动时犹如转 动的车轮,故称为轮 虫。
一、轮虫的主要特征
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1、体制:辐射对称 2、两个胚层:其体壁由内外两胚层和中胶层组成。水螅水母中胶层薄,钵
水母中胶层厚。 3、具一个消化循环腔:有消化、排泄、循环功能。 4、腔肠动物有两种基本形态: • 水螅型 polyp: 呈圆筒状,适应固着生活。 • 水母型 medusa: 适应浮游生活,呈伞状。 多数既有水螅型也有水母型,有的只有水螅型(水螅),有的只有水母型
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三、各种轮虫
褶皱臂尾轮虫(Brachionus plicatilis)
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习性分布:生活于淡水、海水、潮湿土壤、以及其它动、 植物体表等多种环境中。 多数轮虫呈世界性分布。 常对极端环境具有很强的耐受力(休眠阶段)。 淡水水体常见的浮游动物,鱼类的重要饵料。
触角(两对) A1 (antennule):第一触角或称小触角 A2 (antenna):第二触角或称大触角 大颚M (mandibula):一对具齿状突起的几丁质板,有咀嚼功
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微生物英文文献及翻译—原文
Dynamic and distribution of ammonia-oxidizing bacteria communities during sludge granulation in an anaerobic e aerobic sequencing batch reactorZhang Bin a ,b ,Chen Zhe a ,b ,Qiu Zhigang a ,b ,Jin Min a ,b ,Chen Zhiqiang a ,b ,Chen Zhaoli a ,b ,Li Junwen a ,b ,Wang Xuan c ,*,Wang Jingfeng a ,b ,**aInstitute of Hygiene and Environmental Medicine,Academy of Military Medical Sciences,Tianjin 300050,PR China bTianjin Key Laboratory of Risk Assessment and Control for Environment and Food Safety,Tianjin 300050,PR China cTianjin Key Laboratory of Hollow Fiber Membrane Material and Membrane Process,Institute of Biological and Chemical Engineering,Tianjin Polytechnical University,Tianjin 300160,PR Chinaa r t i c l e i n f oArticle history:Received 30June 2011Received in revised form 10September 2011Accepted 10September 2011Available online xxx Keywords:Ammonia-oxidizing bacteria Granular sludgeCommunity development Granule sizeNitrifying bacteria distribution Phylogenetic diversitya b s t r a c tThe structure dynamic of ammonia-oxidizing bacteria (AOB)community and the distribution of AOB and nitrite-oxidizing bacteria (NOB)in granular sludge from an anaerobic e aerobic sequencing batch reactor (SBR)were investigated.A combination of process studies,molecular biotechniques and microscale techniques were employed to identify and characterize these organisms.The AOB community structure in granules was substantially different from that of the initial pattern of the inoculants sludge.Along with granules formation,the AOB diversity declined due to the selection pressure imposed by process conditions.Denaturing gradient gel electrophoresis (DGGE)and sequencing results demonstrated that most of Nitrosomonas in the inoculating sludge were remained because of their ability to rapidly adapt to the settling e washing out action.Furthermore,DGGE analysis revealed that larger granules benefit more AOB species surviving in the reactor.In the SBR were various size granules coexisted,granule diameter affected the distribution range of AOB and NOB.Small and medium granules (d <0.6mm)cannot restrict oxygen mass transfer in all spaces of the rger granules (d >0.9mm)can result in smaller aerobic volume fraction and inhibition of NOB growth.All these observations provide support to future studies on the mechanisms responsible for the AOB in granules systems.ª2011Elsevier Ltd.All rights reserved.1.IntroductionAt sufficiently high levels,ammonia in aquatic environments can be toxic to aquatic life and can contribute to eutrophica-tion.Accordingly,biodegradation and elimination of ammonia in wastewater are the primary functions of thewastewater treatment process.Nitrification,the conversion of ammonia to nitrate via nitrite,is an important way to remove ammonia nitrogen.It is a two-step process catalyzed by ammonia-oxidizing and nitrite-oxidizing bacteria (AOB and NOB).Aerobic ammonia-oxidation is often the first,rate-limiting step of nitrification;however,it is essential for the*Corresponding author .**Corresponding author.Institute of Hygiene and Environmental Medicine,Academy of Military Medical Sciences,Tianjin 300050,PR China.Tel.:+862284655498;fax:+862223328809.E-mail addresses:wangxuan0116@ (W.Xuan),jingfengwang@ (W.Jingfeng).Available online atjournal homepage:/locate/watresw a t e r r e s e a r c h x x x (2011)1e 100043-1354/$e see front matter ª2011Elsevier Ltd.All rights reserved.doi:10.1016/j.watres.2011.09.026removal of ammonia from the wastewater(Prosser and Nicol, 2008).Comparative analyses of16S rRNA sequences have revealed that most AOB in activated sludge are phylogeneti-cally closely related to the clade of b-Proteobacteria (Kowalchuk and Stephen,2001).However,a number of studies have suggested that there are physiological and ecological differences between different AOB genera and lineages,and that environmental factors such as process parameter,dis-solved oxygen,salinity,pH,and concentrations of free ammonia can impact certain species of AOB(Erguder et al., 2008;Kim et al.,2006;Koops and Pommerening-Ro¨ser,2001; Kowalchuk and Stephen,2001;Shi et al.,2010).Therefore, the physiological activity and abundance of AOB in waste-water processing is critical in the design and operation of waste treatment systems.For this reason,a better under-standing of the ecology and microbiology of AOB in waste-water treatment systems is necessary to enhance treatment performance.Recently,several developed techniques have served as valuable tools for the characterization of microbial diversity in biological wastewater treatment systems(Li et al., 2008;Yin and Xu,2009).Currently,the application of molec-ular biotechniques can provide clarification of the ammonia-oxidizing community in detail(Haseborg et al.,2010;Tawan et al.,2005;Vlaeminck et al.,2010).In recent years,the aerobic granular sludge process has become an attractive alternative to conventional processes for wastewater treatment mainly due to its cell immobilization strategy(de Bruin et al.,2004;Liu et al.,2009;Schwarzenbeck et al.,2005;Schwarzenbeck et al.,2004a,b;Xavier et al.,2007). Granules have a more tightly compact structure(Li et al.,2008; Liu and Tay,2008;Wang et al.,2004)and rapid settling velocity (Kong et al.,2009;Lemaire et al.,2008).Therefore,granular sludge systems have a higher mixed liquid suspended sludge (MLSS)concentration and longer solid retention times(SRT) than conventional activated sludge systems.Longer SRT can provide enough time for the growth of organisms that require a long generation time(e.g.,AOB).Some studies have indicated that nitrifying granules can be cultivated with ammonia-rich inorganic wastewater and the diameter of granules was small (Shi et al.,2010;Tsuneda et al.,2003).Other researchers reported that larger granules have been developed with the synthetic organic wastewater in sequencing batch reactors(SBRs)(Li et al., 2008;Liu and Tay,2008).The diverse populations of microor-ganisms that coexist in granules remove the chemical oxygen demand(COD),nitrogen and phosphate(de Kreuk et al.,2005). However,for larger granules with a particle diameter greater than0.6mm,an outer aerobic shell and an inner anaerobic zone coexist because of restricted oxygen diffusion to the granule core.These properties of granular sludge suggest that the inner environment of granules is unfavorable to AOB growth.Some research has shown that particle size and density induced the different distribution and dominance of AOB,NOB and anam-mox(Winkler et al.,2011b).Although a number of studies have been conducted to assess the ecology and microbiology of AOB in wastewater treatment systems,the information on the dynamics,distribution,and quantification of AOB communities during sludge granulation is still limited up to now.To address these concerns,the main objective of the present work was to investigate the population dynamics of AOB communities during the development of seedingflocs into granules,and the distribution of AOB and NOB in different size granules from an anaerobic e aerobic SBR.A combination of process studies,molecular biotechniques and microscale techniques were employed to identify and char-acterize these organisms.Based on these approaches,we demonstrate the differences in both AOB community evolu-tion and composition of theflocs and granules co-existing in the SBR and further elucidate the relationship between distribution of nitrifying bacteria and granule size.It is ex-pected that the work would be useful to better understand the mechanisms responsible for the AOB in granules and apply them for optimal control and management strategies of granulation systems.2.Material and methods2.1.Reactor set-up and operationThe granules were cultivated in a lab-scale SBR with an effective volume of4L.The effective diameter and height of the reactor was10cm and51cm,respectively.The hydraulic retention time was set at8h.Activated sludge from a full-scale sewage treat-ment plant(Jizhuangzi Sewage Treatment Works,Tianjin, China)was used as the seed sludge for the reactor at an initial sludge concentration of3876mg LÀ1in MLSS.The reactor was operated on6-h cycles,consisting of2-min influent feeding,90-min anaerobic phase(mixing),240-min aeration phase and5-min effluent discharge periods.The sludge settling time was reduced gradually from10to5min after80SBR cycles in20days, and only particles with a settling velocity higher than4.5m hÀ1 were retained in the reactor.The composition of the influent media were NaAc(450mg LÀ1),NH4Cl(100mg LÀ1),(NH4)2SO4 (10mg LÀ1),KH2PO4(20mg LÀ1),MgSO4$7H2O(50mg LÀ1),KCl (20mg LÀ1),CaCl2(20mg LÀ1),FeSO4$7H2O(1mg LÀ1),pH7.0e7.5, and0.1mL LÀ1trace element solution(Li et al.,2007).Analytical methods-The total organic carbon(TOC),NHþ4e N, NOÀ2e N,NOÀ3e N,total nitrogen(TN),total phosphate(TP) concentration,mixed liquid suspended solids(MLSS) concentration,and sludge volume index at10min(SVI10)were measured regularly according to the standard methods (APHA-AWWA-WEF,2005).Sludge size distribution was determined by the sieving method(Laguna et al.,1999).Screening was performed with four stainless steel sieves of5cm diameter having respective mesh openings of0.9,0.6,0.45,and0.2mm.A100mL volume of sludge from the reactor was sampled with a calibrated cylinder and then deposited on the0.9mm mesh sieve.The sample was subsequently washed with distilled water and particles less than0.9mm in diameter passed through this sieve to the sieves with smaller openings.The washing procedure was repeated several times to separate the gran-ules.The granules collected on the different screens were recovered by backwashing with distilled water.Each fraction was collected in a different beaker andfiltered on quantitative filter paper to determine the total suspended solid(TSS).Once the amount of total suspended solid(TSS)retained on each sieve was acquired,it was reasonable to determine for each class of size(<0.2,[0.2e0.45],[0.45e0.6],[0.6e0.9],>0.9mm) the percentage of the total weight that they represent.w a t e r r e s e a r c h x x x(2011)1e10 22.2.DNA extraction and nested PCR e DGGEThe sludge from approximately8mg of MLSS was transferred into a1.5-mL Eppendorf tube and then centrifuged at14,000g for10min.The supernatant was removed,and the pellet was added to1mL of sodium phosphate buffer solution and aseptically mixed with a sterilized pestle in order to detach granules.Genomic DNA was extracted from the pellets using E.Z.N.A.äSoil DNA kit(D5625-01,Omega Bio-tek Inc.,USA).To amplify ammonia-oxidizer specific16S rRNA for dena-turing gradient gel electrophoresis(DGGE),a nested PCR approach was performed as described previously(Zhang et al., 2010).30m l of nested PCR amplicons(with5m l6Âloading buffer)were loaded and separated by DGGE on polyacrylamide gels(8%,37.5:1acrylamide e bisacrylamide)with a linear gradient of35%e55%denaturant(100%denaturant¼7M urea plus40%formamide).The gel was run for6.5h at140V in 1ÂTAE buffer(40mM Tris-acetate,20mM sodium acetate, 1mM Na2EDTA,pH7.4)maintained at60 C(DCodeäUniversal Mutation Detection System,Bio-Rad,Hercules,CA, USA).After electrophoresis,silver-staining and development of the gels were performed as described by Sanguinetti et al. (1994).These were followed by air-drying and scanning with a gel imaging analysis system(Image Quant350,GE Inc.,USA). The gel images were analyzed with the software Quantity One,version4.31(Bio-rad).Dice index(Cs)of pair wise community similarity was calculated to evaluate the similarity of the AOB community among DGGE lanes(LaPara et al.,2002).This index ranges from0%(no common band)to100%(identical band patterns) with the assistance of Quantity One.The Shannon diversity index(H)was used to measure the microbial diversity that takes into account the richness and proportion of each species in a population.H was calculatedusing the following equation:H¼ÀPn iNlogn iN,where n i/Nis the proportion of community made up by species i(bright-ness of the band i/total brightness of all bands in the lane).Dendrograms relating band pattern similarities were automatically calculated without band weighting(consider-ation of band density)by the unweighted pair group method with arithmetic mean(UPGMA)algorithms in the Quantity One software.Prominent DGGE bands were excised and dissolved in30m L Milli-Q water overnight,at4 C.DNA was recovered from the gel by freeze e thawing thrice.Cloning and sequencing of the target DNA fragments were conducted following the estab-lished method(Zhang et al.,2010).2.3.Distribution of nitrifying bacteriaThree classes of size([0.2e0.45],[0.45e0.6],>0.9mm)were chosen on day180for FISH analysis in order to investigate the spatial distribution characteristics of AOB and NOB in granules.2mg sludge samples werefixed in4%para-formaldehyde solution for16e24h at4 C and then washed twice with sodium phosphate buffer;the samples were dehydrated in50%,80%and100%ethanol for10min each. Ethanol in the granules was then completely replaced by xylene by serial immersion in ethanol-xylene solutions of3:1, 1:1,and1:3by volume andfinally in100%xylene,for10min periods at room temperature.Subsequently,the granules were embedded in paraffin(m.p.56e58 C)by serial immer-sion in1:1xylene-paraffin for30min at60 C,followed by 100%paraffin.After solidification in paraffin,8-m m-thick sections were prepared and placed on gelatin-coated micro-scopic slides.Paraffin was removed by immersing the slide in xylene and ethanol for30min each,followed by air-drying of the slides.The three oligonucleotide probes were used for hybridiza-tion(Downing and Nerenberg,2008):FITC-labeled Nso190, which targets the majority of AOB;TRITC-labeled NIT3,which targets Nitrobacter sp.;TRITC-labeled NSR1156,which targets Nitrospira sp.All probe sequences,their hybridization condi-tions,and washing conditions are given in Table1.Oligonu-cleotides were synthesized andfluorescently labeled with fluorochomes by Takara,Inc.(Dalian,China).Hybridizations were performed at46 C for2h with a hybridization buffer(0.9M NaCl,formamide at the percentage shown in Table1,20mM Tris/HCl,pH8.0,0.01% SDS)containing each labeled probe(5ng m LÀ1).After hybrid-ization,unbound oligonucleotides were removed by a strin-gent washing step at48 C for15min in washing buffer containing the same components as the hybridization buffer except for the probes.For detection of all DNA,4,6-diamidino-2-phenylindole (DAPI)was diluted with methanol to afinal concentration of1ng m LÀ1.Cover the slides with DAPI e methanol and incubate for15min at37 C.The slides were subsequently washed once with methanol,rinsed briefly with ddH2O and immediately air-dried.Vectashield(Vector Laboratories)was used to prevent photo bleaching.The hybridization images were captured using a confocal laser scanning microscope (CLSM,Zeiss710).A total of10images were captured for each probe at each class of size.The representative images were selected andfinal image evaluation was done in Adobe PhotoShop.w a t e r r e s e a r c h x x x(2011)1e1033.Results3.1.SBR performance and granule characteristicsDuring the startup period,the reactor removed TOC and NH 4þ-N efficiently.98%of NH 4þ-N and 100%of TOC were removed from the influent by day 3and day 5respectively (Figs.S2,S3,Supporting information ).Removal of TN and TP were lower during this period (Figs.S3,S4,Supporting information ),though the removal of TP gradually improved to 100%removal by day 33(Fig.S4,Supporting information ).To determine the sludge volume index of granular sludge,a settling time of 10min was chosen instead of 30min,because granular sludge has a similar SVI after 60min and after 5min of settling (Schwarzenbeck et al.,2004b ).The SVI 10of the inoculating sludge was 108.2mL g À1.The changing patterns of MLSS and SVI 10in the continuous operation of the SBR are illustrated in Fig.1.The sludge settleability increased markedly during the set-up period.Fig.2reflects the slow andgradual process of sludge granulation,i.e.,from flocculentsludge to granules.3.2.DGGE analysis:AOB communities structure changes during sludge granulationThe results of nested PCR were shown in Fig.S1.The well-resolved DGGE bands were obtained at the representative points throughout the GSBR operation and the patterns revealed that the structure of the AOB communities was dynamic during sludge granulation and stabilization (Fig.3).The community structure at the end of experiment was different from that of the initial pattern of the seed sludge.The AOB communities on day 1showed 40%similarity only to that at the end of the GSBR operation (Table S1,Supporting information ),indicating the considerable difference of AOB communities structures between inoculated sludge and granular sludge.Biodiversity based on the DGGE patterns was analyzed by calculating the Shannon diversity index H as204060801001201401254159738494104115125135147160172188Time (d)S V I 10 (m L .g -1)10002000300040005000600070008000900010000M L S S (m g .L -1)Fig.1e Change in biomass content and SVI 10during whole operation.SVI,sludge volume index;MLSS,mixed liquid suspendedsolids.Fig.2e Variation in granule size distribution in the sludge during operation.d,particle diameter;TSS,total suspended solids.w a t e r r e s e a r c h x x x (2011)1e 104shown in Fig.S5.In the phase of sludge inoculation (before day 38),H decreased remarkably (from 0.94to 0.75)due to the absence of some species in the reactor.Though several dominant species (bands2,7,10,11)in the inoculating sludge were preserved,many bands disappeared or weakened (bands 3,4,6,8,13,14,15).After day 45,the diversity index tended to be stable and showed small fluctuation (from 0.72to 0.82).Banding pattern similarity was analyzed by applying UPGMA (Fig.4)algorithms.The UPGMA analysis showed three groups with intragroup similarity at approximately 67%e 78%and intergroup similarity at 44e 62%.Generally,the clustering followed the time course;and the algorithms showed a closer clustering of groups II and III.In the analysis,group I was associated with sludge inoculation and washout,group IIwithFig.3e DGGE profile of the AOB communities in the SBR during the sludge granulation process (lane labels along the top show the sampling time (days)from startup of the bioreactor).The major bands were labeled with the numbers (bands 1e15).Fig.4e UPGMA analysis dendrograms of AOB community DGGE banding patterns,showing schematics of banding patterns.Roman numerals indicate major clusters.w a t e r r e s e a r c h x x x (2011)1e 105startup sludge granulation and decreasing SVI 10,and group III with a stable system and excellent biomass settleability.In Fig.3,the locations of the predominant bands were excised from the gel.DNA in these bands were reamplified,cloned and sequenced.The comparative analysis of these partial 16S rRNA sequences (Table 2and Fig.S6)revealed the phylogenetic affiliation of 13sequences retrieved.The majority of the bacteria in seed sludge grouped with members of Nitrosomonas and Nitrosospira .Along with sludge granula-tion,most of Nitrosomonas (Bands 2,5,7,9,10,11)were remained or eventually became dominant in GSBR;however,all of Nitrosospira (Bands 6,13,15)were gradually eliminated from the reactor.3.3.Distribution of AOB and NOB in different sized granulesFISH was performed on the granule sections mainly to deter-mine the location of AOB and NOB within the different size classes of granules,and the images were not further analyzed for quantification of cell counts.As shown in Fig.6,in small granules (0.2mm <d <0.45mm),AOB located mainly in the outer part of granular space,whereas NOB were detected only in the core of granules.In medium granules (0.45mm <d <0.6mm),AOB distributed evenly throughout the whole granular space,whereas NOB still existed in the inner part.In the larger granules (d >0.9mm),AOB and NOB were mostly located in the surface area of the granules,and moreover,NOB became rare.4.Discussion4.1.Relationship between granule formation and reactor performanceAfter day 32,the SVI 10stabilized at 20e 35mL g À1,which is very low compared to the values measured for activated sludge (100e 150mL g À1).However,the size distribution of the granules measured on day 32(Fig.2)indicated that only 22%of the biomass was made of granular sludge with diameter largerthan 0.2mm.These results suggest that sludge settleability increased prior to granule formation and was not affected by different particle sizes in the sludge during the GSBR operation.It was observed,however,that the diameter of the granules fluctuated over longer durations.The large granules tended to destabilize due to endogenous respiration,and broke into smaller granules that could seed the formation of large granules again.Pochana and Keller reported that physically broken sludge flocs contribute to lower denitrification rates,due to their reduced anoxic zone (Pochana and Keller,1999).Therefore,TN removal efficiency raises fluctuantly throughout the experiment.Some previous research had demonstrated that bigger,more dense granules favored the enrichment of PAO (Winkler et al.,2011a ).Hence,after day 77,removal efficiency of TP was higher and relatively stable because the granules mass fraction was over 90%and more larger granules formed.4.2.Relationship between AOB communities dynamic and sludge granulationFor granule formation,a short settling time was set,and only particles with a settling velocity higher than 4.5m h À1were retained in the reactor.Moreover,as shown in Fig.1,the variation in SVI 10was greater before day 41(from 108.2mL g À1e 34.1mL g À1).During this phase,large amounts of biomass could not survive in the reactor.A clear shift in pop-ulations was evident,with 58%similarity between days 8and 18(Table S1).In the SBR system fed with acetate-based synthetic wastewater,heterotrophic bacteria can produce much larger amounts of extracellular polysaccharides than autotrophic bacteria (Tsuneda et al.,2003).Some researchers found that microorganisms in high shear environments adhered by extracellular polymeric substances (EPS)to resist the damage of suspended cells by environmental forces (Trinet et al.,1991).Additionally,it had been proved that the dominant heterotrophic species in the inoculating sludge were preserved throughout the process in our previous research (Zhang et al.,2011).It is well known that AOB are chemoau-totrophic and slow-growing;accordingly,numerous AOBw a t e r r e s e a r c h x x x (2011)1e 106populations that cannot become big and dense enough to settle fast were washed out from the system.As a result,the variation in AOB was remarkable in the period of sludge inoculation,and the diversity index of population decreased rapidly.After day 45,AOB communities’structure became stable due to the improvement of sludge settleability and the retention of more biomass.These results suggest that the short settling time (selection pressure)apparently stressed the biomass,leading to a violent dynamic of AOB communities.Further,these results suggest that certain populations may have been responsible for the operational success of the GSBR and were able to persist despite the large fluctuations in pop-ulation similarity.This bacterial population instability,coupled with a generally acceptable bioreactor performance,is congruent with the results obtained from a membrane biore-actor (MBR)for graywater treatment (Stamper et al.,2003).Nitrosomonas e like and Nitrosospira e like populations are the dominant AOB populations in wastewater treatment systems (Kowalchuk and Stephen,2001).A few previous studies revealed that the predominant populations in AOB communities are different in various wastewater treatment processes (Tawan et al.,2005;Thomas et al.,2010).Some researchers found that the community was dominated by AOB from the genus Nitrosospira in MBRs (Zhang et al.,2010),whereas Nitrosomonas sp.is the predominant population in biofilter sludge (Yin and Xu,2009).In the currentstudy,Fig.5e DGGE profile of the AOB communities in different size of granules (lane labels along the top show the range of particle diameter (d,mm)).Values along the bottom indicate the Shannon diversity index (H ).Bands labeled with the numbers were consistent with the bands in Fig.3.w a t e r r e s e a r c h x x x (2011)1e 107sequence analysis revealed that selection pressure evidently effect on the survival of Nitrosospira in granular sludge.Almost all of Nitrosospira were washed out initially and had no chance to evolve with the environmental changes.However,some members of Nitrosomonas sp.have been shown to produce more amounts of EPS than Nitrosospira ,especially under limited ammonia conditions (Stehr et al.,1995);and this feature has also been observed for other members of the same lineage.Accordingly,these EPS are helpful to communicate cells with each other and granulate sludge (Adav et al.,2008).Therefore,most of Nitrosomonas could adapt to this challenge (to become big and dense enough to settle fast)and were retained in the reactor.At the end of reactor operation (day 180),granules with different particle size were sieved.The effects of variation in granules size on the composition of the AOBcommunitiesFig.6e Micrographs of FISH performed on three size classes of granule sections.DAPI stain micrographs (A,D,G);AOB appear as green fluorescence (B,E,H),and NOB appear as red fluorescence (C,F,I).Bar [100m m in (A)e (C)and (G)e (I).d,particle diameter.(For interpretation of the references to colour in this figure legend,the reader is referred to the web version of this article.)w a t e r r e s e a r c h x x x (2011)1e 108were investigated.As shown in Fig.5,AOB communities structures in different size of granules were varied.Although several predominant bands(bands2,5,11)were present in all samples,only bands3and6appeared in the granules with diameters larger than0.6mm.Additionally,bands7and10 were intense in the granules larger than0.45mm.According to Table2,it can be clearly indicated that Nitrosospira could be retained merely in the granules larger than0.6mm.Therefore, Nitrosospira was not present at a high level in Fig.3due to the lower proportion of larger granules(d>0.6mm)in TSS along with reactor operation.DGGE analysis also revealed that larger granules had a greater microbial diversity than smaller ones. This result also demonstrates that more organisms can survive in larger granules as a result of more space,which can provide the suitable environment for the growth of microbes(Fig.6).4.3.Effect of variance in particle size on the distribution of AOB and NOB in granulesAlthough an influence of granule size has been observed in experiments and simulations for simultaneous N-and P-removal(de Kreuk et al.,2007),the effect of granule size on the distribution of different biomass species need be revealed further with the assistance of visible experimental results, especially in the same granular sludge reactors.Related studies on the diversity of bacterial communities in granular sludge often focus on the distribution of important functional bacteria populations in single-size granules(Matsumoto et al., 2010).In the present study,different size granules were sieved,and the distribution patterns of AOB and NOB were explored.In the nitrification processes considered,AOB and NOB compete for space and oxygen in the granules(Volcke et al.,2010).Since ammonium oxidizers have a higheroxygen affinity(K AOBO2<K NOBO2)and accumulate more rapidly inthe reactor than nitrite oxidizers(Volcke et al.,2010),NOB are located just below the layer of AOB,where still some oxygen is present and allows ready access to the nitrite produced.In smaller granules,the location boundaries of the both biomass species were distinct due to the limited existence space provided by granules for both microorganism’s growth.AOB exist outside of the granules where oxygen and ammonia are present.Medium granules can provide broader space for microbe multiplying;accordingly,AOB spread out in the whole granules.This result also confirms that oxygen could penetrate deep into the granule’s core without restriction when particle diameter is less than0.6mm.Some mathematic model also supposed that NOBs are favored to grow in smaller granules because of the higher fractional aerobic volume (Volcke et al.,2010).As shown in the results of the batch experiments(Zhang et al.,2011),nitrite accumulation temporarily occurred,accompanied by the more large gran-ules(d>0.9mm)forming.This phenomenon can be attrib-uted to the increased ammonium surface load associated with larger granules and smaller aerobic volume fraction,resulting in outcompetes of NOB.It also suggests that the core areas of large granules(d>0.9mm)could provide anoxic environment for the growth of anaerobic denitrificans(such as Tb.deni-trificans or Tb.thioparus in Fig.S7,Supporting information).As shown in Fig.2and Fig.S3,the removal efficiency of total nitrogen increased with formation of larger granules.5.ConclusionsThe variation in AOB communities’structure was remarkable during sludge inoculation,and the diversity index of pop-ulation decreased rapidly.Most of Nitrosomonas in the inocu-lating sludge were retained because of their capability to rapidly adapt to the settling e washing out action.DGGE anal-ysis also revealed that larger granules had greater AOB diversity than that of smaller ones.Oxygen penetration was not restricted in the granules of less than0.6mm particle diameter.However,the larger granules(d>0.9mm)can result in the smaller aerobic volume fraction and inhibition of NOB growth.Henceforth,further studies on controlling and opti-mizing distribution of granule size could be beneficial to the nitrogen removal and expansive application of granular sludge technology.AcknowledgmentsThis work was supported by grants from the National Natural Science Foundation of China(No.51108456,50908227)and the National High Technology Research and Development Program of China(No.2009AA06Z312).Appendix.Supplementary dataSupplementary data associated with this article can be found in online version at doi:10.1016/j.watres.2011.09.026.r e f e r e n c e sAdav,S.S.,Lee, D.J.,Show,K.Y.,2008.Aerobic granular sludge:recent advances.Biotechnology Advances26,411e423.APHA-AWWA-WEF,2005.Standard Methods for the Examination of Water and Wastewater,first ed.American Public Health Association/American Water Works Association/WaterEnvironment Federation,Washington,DC.de Bruin,L.M.,de Kreuk,M.,van der Roest,H.F.,Uijterlinde,C., van Loosdrecht,M.C.M.,2004.Aerobic granular sludgetechnology:an alternative to activated sludge?Water Science and Technology49,1e7.de Kreuk,M.,Heijnen,J.J.,van Loosdrecht,M.C.M.,2005.Simultaneous COD,nitrogen,and phosphate removal byaerobic granular sludge.Biotechnology and Bioengineering90, 761e769.de Kreuk,M.,Picioreanu,C.,Hosseini,M.,Xavier,J.B.,van Loosdrecht,M.C.M.,2007.Kinetic model of a granular sludge SBR:influences on nutrient removal.Biotechnology andBioengineering97,801e815.Downing,L.S.,Nerenberg,R.,2008.Total nitrogen removal ina hybrid,membrane-aerated activated sludge process.WaterResearch42,3697e3708.Erguder,T.H.,Boon,N.,Vlaeminck,S.E.,Verstraete,W.,2008.Partial nitrification achieved by pulse sulfide doses ina sequential batch reactor.Environmental Science andTechnology42,8715e8720.w a t e r r e s e a r c h x x x(2011)1e109。
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MARINE ECOLOGY PROGRESS SERIESMar Ecol Prog SerVol. 403: 129–144, 2010
doi: 10.3354/meps08466Published March 22
INTRODUCTIONMarine zooplankton forms the first gateway in theprocessing of organic matter derived from primaryproduction in the surface ocean. The fate of thisorganic matter is thus to a large part a function of 3quantities which define zooplankton feeding behav-iour and growth: (1) specific ingestion rateIis the totalfood intake, (2) assimilation efficiency Edefines theassimilated and excreted fractions of the ingestedmaterial, and (3) respiration and exudation separateremineralisation from growth, i.e. accumulation of bio-mass available for utilisation by higher trophic levels.Net growth rate gcan be defined as the balancebetween assimilation EIand respiration R:g= EI– R(1)where Rrepresents respiration of CO2and exudationof nutrients (all symbols are summarised in Table 1).Sloppy feeding and risk of higher predation will not beconsidered in the present study. Excretion in the formof faecal pellets can be exported to the deep ocean andthereby contribute to the biological carbon pump. Con-sequently, the zooplankton formulation strongly af-fects the behaviour of plankton models both directlyvia its role in the food web and indirectly via its impacton vertical nutrient profiles (Steele & Henderson 1992).Nevertheless, although many zooplankton modelsexist (Gentleman et al. 2003), they focus almost exclu-sively on ingestion and do not usually allow fordynamic adjustments in feeding behaviour (Paffen-höfer et al. 2007).Behaviours effecting prey encounter can broadly becategorised into several foraging strategies. The sim-
© Inter-Research 2010 · www.int-res.com*Email: mpahlow@ifm-geomar.de
Model of optimal current feeding in zooplanktonMarkus Pahlow*, A. E. Friederike ProweIFM-GEOMAR, Düsternbrooker Weg 20, 24105 Kiel, Germany
ABSTRACT: Zooplankton feeding formulations in plankton models have exclusively focused on therelation between food concentration and ingestion, with respiration and excretion being treated sep-arately, despite experimental evidence for strong links among these processes. We present an opti-mal current-feeding model linking ingestion, respiration, and assimilation efficiency to foragingactivity. The Ivlev model is a special case of our optimal current-feeding model, which applies tostatic feeding behaviour. We validate our model with experimental data for copepods, ciliates, anddinoflagellates. Parameter estimates suggest that phylogenetic grouping is more important than pre-dator size in determining feeding behaviour. Respiratory costs of foraging, e.g. for generating a feed-ing current, may be much larger than previously thought, are larger in smaller organisms, and mightexplain the independent development of feeding thresholds in different micro- and mesozooplank-ton groups. Both preferential feeding on, and lower feeding thresholds for, larger food particles arepredicted to derive from greater capture efficiency owing to enhanced detectability of larger parti-cles. The relation between feeding threshold and prey size appears to depend on feeding strategy butnot on predator size, as a common relationship seems to apply for current feeders (ciliates and cope-pods) spanning a vast size range. Our model exhibits an inverse relationship between ingestion andassimilation efficiency, reducing the contribution of copepods to exportof organic matter relative toremineralisation at low food concentrations. Export ratio variations previously thought to requirestrong shifts in community composition can be generated by changes in feeding behaviour predictedby our model.
KEY WORDS: Zooplankton · Optimal foraging · Current-feeding modelResale or republication not permitted without written consent of the publisherMar Ecol Prog Ser 403: 129–144, 2010plest possible behaviour is simply waiting for randomprey encounters (ambush feeding), which is efficientfor moving prey only (Gerritsen & Strickler 1977). Themost effective means of increasing prey encounters iscruise feeding, i.e. swimming in various patterns, butin addition to metabolic costs, this strategy also in-evitably increases encounters with higher predators(Visser et al. 2009). A feeding current can enhanceprey encounters as well, albeit somewhat less effec-tively, owing to its limited spatial extent. However,because the predator itself is not moving, this strategydoes not suffer the increased risk of higher predationincurred by cruise feeding. Filter feeders direct theirfeeding currents through a filter, sieving out prey par-ticles, which works most efficiently with very large fil-ters (Gerritsen et al. 1988). Suspension-feeding cope-pods have often been considered filter feeders (e.g.Conover 1968, Frost 1972, Lehman 1976, Vidal 1980a),but one important yet still often ignored aspect of thisfeeding mode is that a copepod’s feeding current doesnot pass through but actually around its feeding ap-pendages (Koehl & Strickler 1981), which actto detect and capture prey organisms from thefeeding current (Visser & Stips 2002). There-fore, we refer to this feeding mode as currentfeeding.Grazing functions commonly applied inplankton models include the Holling types,based on the disk equation, which in turn wasderived for insect feeding (Holling 1959, 1973),and the Ivlev equation, derived for fish (Ivlev1961). Their application to zooplankton wasempirically motivated (Conover 1968, Fujii etal. 1986) and had no mechanistic basis. Asidefrom the inappropriateness of the term filterfeeder to describe suspension feeding by cope-pods, this lack of a mechanistic foundationmeans that it is difficult to generalise thesemodels and analyse disagreements betweenmodels and observations. For example, Parsonset al. (1967) noted the necessity to introduce afeeding threshold into the Ivlev equation in or-der to describe the behaviour of copepods. Vi-dal (1980a) and Kiørboe et al. (1982, 1985) in-troduced entirely new empirical formulationsto describe their observations, which fit theirdata better but could ‘not be interpreted in bio-logical terms’ (Kiørboe et al. 1982, p. 185).Almost all existing zooplankton feedingmodels describe ingestion as a function of foodconcentration, without any inherent link torespiration or assimilation efficiency, despitemany observations that these processes covaryin a systematic manner (e.g. Landry et al. 1984,Kiørboe et al. 1985). Respiration can be consid-ered the sum of 3 components: (1) a constant mainte-nance respiration thought to sustain standard (resting)metabolism, (2) the cost of foraging, and (3) the meta-bolic cost of assimilation, termed specific dynamicaction (Steele & Mullin 1977). The increase of respira-tion with increasing growth rate is usually attributedmostly to specific dynamic action (Steele & Mullin1977, Kiørboe et al. 1985), whereas the cost of foraginghas been suggested to give rise to feeding thresholdsin order to save energy in the absence of food (Frost1975). Zooplankton assimilation efficiency appears todecrease with increasing growth rate (Steele & Mullin1977, Kiørboe et al. 1985), yet it is usually treated asconstant in plankton models (Lam & Frost 1976, Steele1998). The only existing feeding model utilising mech-anistic relationships among ingestion, respiration, andassimilation efficiency is the optimal foraging descrip-tion of filter feeding by Lehman (1976). However, thismodel has never been validated and, because it cannotbe written in closed form, is not suitable for use inlarger plankton models.130SymbolStandard unitsDescriptionAfd–1Specificforaging activityAf,maxd–1Maximum specific foraging activityAtd–1Maximum total specific activityα–Prey handling coefficientβ–Digestion (assimilation) coefficientca–Cost of assimilation coefficientcf, cf*–Cost of foraging activity coefficientaE–Assimilation efficiency~Eg–Modified gross growth efficiency