磷影响陆地生态系统碳循环过程及模型表达方法

全球气候变暖已大大改变了陆地植物碳吸收能力, 提高了全球植被净初级生产力。随着气候变暖的加剧, 磷对植物生长的限制作用逐渐显现且不断增强, 磷影响陆地生态系统碳循环的机理和模型研究已成为研究热点。该文系统分析了磷影响陆地生态系统碳循环的相关机理以及模型对相关过程的定量化表达方法。综合对比分析了国际上的Carnegie- Ames-Stanford Approach-CNP (CASA-CNP)、Community Land Model-CNP (CLM-CNP)和Jena Scheme for Biosphere-Atmosphere Coupling in Hamburg-CNP (JSBACH-CNP)等碳、氮、磷耦合模型中磷影响植物光合作用与同化物分配过程、植物对磷的吸收过程、土壤中磷的转化过程以及生态系统磷输入与输出等过程的相关数学表达方法, 指出了模型算法的局限与不确定性以及未来模型发展与改进的方向。同时综合对比分析了CASA-CNP、CLM-CNP、JSBACH-CNP模型的基本特征, 总结了磷循环模型的建模方法, 为未来开展磷影响陆地生态系统碳循环的模型模拟研究提供了借鉴方法与参考思路。     

陆地生物圈模型的发展与应用

陆地生物圈与大气圈和水圈之间能量、水和碳氮等元素的交换和循环对整个地球系统产生了深刻的影响。陆地生物圈模型(TBM)是研究陆地生态系统如何响应和反馈全球变化的重要方法和工具。通过对从生态系统到区域和全球陆地生物圈不同空间尺度的植被动态、生物地球物理和生物地球化学循环过程、水循环和水文过程、自然干扰和人类活动等过程时间动态的模拟, 陆地生物圈模型被广泛地应用于评估和归因过去陆地生物圈的时空变化和预测陆地生物圈对未来全球变化的响应和反馈。该文简要回顾了陆地生物圈模型的发展, 总结了模型对陆地生态系统主要过程的刻画和模型在生态系统生态学的应用, 并对未来陆地生物圈模型的发展和应用进行了展望。     

磷影响陆地生态系统碳循环过程及模型表达方法

全球气候变暖已大大改变了陆地植物碳吸收能力,提高了全球植被净初级生产力。随着气候变暖的加剧,磷对植物生长的限制作用逐渐显现且不断增强,磷影响陆地生态系统碳循环的机理和模型研究已成为研究热点。该文系统分析了磷影响陆地生态系统碳循环的相关机理以及模型对相关过程的定量化表达方法。综合对比分析了国际上的CarnegieAmes-Stanford Approach-CNP (CASA-CNP)、Community Land Model-CNP (CLM-CNP)和Jena Scheme for Biosphere-Atmosphere Coupling in Hamburg-CNP (JSBACH-CNP)等碳、氮、磷耦合模型中磷影响植物光合作用与同化物分配过程、植物对磷的吸收过程、土壤中磷的转化过程以及生态系统磷输入与输出等过程的相关数学表达方法,指出了模型算法的局限与不确定性以及未来模型发展与改进的方向。同时综合对比分析了CASA-CNP、CLM-CNP、JSBACH-CNP模型的基本特征,总结了磷循环模型的建模方法,为未来开展磷影响陆地生态系统碳循环的模型模拟研究提供了借鉴方法与参考思路。     

气候变化对森林演替的影响

森林演替是森林生态动力源驱动下森林再生的生态学过程,自20世纪初建立群落演替理论以来,演替研究成为生态学研究中的热点．客观准确地认识森林演替规律,研究森林演替动力学机理及其模型,是科学管理森林生态系统的需要;对于天然林保护工程与森林植被的恢复重建,具有重要的理论与实际意义．干扰是森林循环的驱动力,导致森林生态系统时空异质性,是更新格局和生态学过程的主要影响因素．它可改变资源的有效性,干扰导致的林隙是森林循环的起点．回顾了目前演替研究的几种方法,即马尔科夫模型、林窗模型(GAP)、陆地生物圈模型(BIOME)和非线性演替模式．介绍了气候变化对森林演替的影响;并在已有成果的基础上,提出了目前研究存在的问题及未来的发展方向．     

陆地植被净初级生产力计算模型研究进展

植被净初级生产力(NPP)研究是全球变化与陆地生态系统的核心内容之一。在回顾NPP模型研究的基础上,综合分析了气候模型、生态生理过程模型、光能利用率模型各自的优缺点,并对NPP模型研究做出展望。生态生理过程模型是当前陆地NPP估算研究的主要手段,而区域尺度转换则是它所面临的关键问题。近年来光能利用率模型已成为NPP估算的一种全新手段,它利用遥感所获得的全覆盖数据,使区域及全球尺度的NPP估算成为可能,但其生态学机理还有待于进一步研究。已有研究表明,“生态一遥感耦合模型”将是陆地NPP估算的主要发展方向,它融合了生态生理过程模型和光能利用率模型的优点,增强了NPP模型估算的可靠性和可操作性。     

陆地生态系统碳循环模型研究概述

陆地碳循环研究是全球变化研究中的一个重要组成部分,而碳循环模型已成为目前研究陆地碳循环的必要手段.本文针对有关碳循环研究方面的进展,介绍了陆地碳循环模型的基本结构、碳循环过程中涉及的两个基本模型以及目前陆地生态系统碳循环模型的两大类型,并通过对现有主要陆地生态系统碳收支模式的分析,指出了未来陆地碳循环模型的研究方向可能是发展基于动态植被的生物物理模型.这种耦合模型也可能是地球系统模式的重要组成部分.     

中国东北样带的梯度分析及其预测

陆地样带研究已成为国际地圈-生物圈计划(IGBP)全球变化研究的重要手段与热点。中国东北样带(NECT)已被列为IGBP国际全球变化陆地样带之一。该样带在东经112°与130°30＇之间沿北纬43°30＇设置,长约1600km,是一条中纬度温带以降水为驱动因素的梯度,具有由温带针阔叶混交林向温带草原的3个亚地带——草甸草原、典型草原与荒漠草原过渡的空间系列。该样带上有4个生态实验站。在大量的固定样地、实验调查研究资料与数据的基础上给出了样带的初步梯度分析及在全球变化图景下的预测,包括其地理位置、设置意义、地形地貌、气候梯度、土壤类型、植被类型和土地利用格局,一个遥感数据驱动的模型和NPP模型在整个样带上运行过。今后NECT将在生物地球化学循环(水、C、N、P等与痕量气体CO_2、CH_4等)、生态系统结构、功能与动态、生物多样性、土地利用与土地覆盖、动态全球植被模型(DGVM)以及高分辨率遥感数据应用等方面得到加强,将成为我国全球变化与陆地生态系统(GCTE)与其它IGBP核心项目研究的前沿阵地。     

大尺度森林碳循环过程模拟模型综述

森林生态系统碳循环是全球陆地生态系统碳循环的重要组成部分,而碳循环模型已经成为研究森林碳循环的必要手段。森林碳循环模型可以分为统计模型和过程模型,其中过程模型以其完整的理论框架、严谨的结构分析和清晰的过程机理,逐渐占据了主导地位。从地球化学过程模型、陆面物理过程模型和生物过程模型等3个方面综述区域尺度到全球尺度(本文称为大尺度)森林碳循环过程模型研究进展,论述了各类模型的主要特征、优缺点以及应用现状,探讨了森林碳循环模拟研究中存在的问题,并讨论了森林碳循环过程模型的主流研究方向。可为不同空间尺度下森林生态系统碳循环模拟模型的选择提供参考,以及为森林碳循环研究提供借鉴。     

陆地碳循环研究中的模型方法

陆地碳循环是全球变化研究中的重要内容,碳循环模型已成为研究陆地碳循环的必要方法．其中气候变化、大气ＣＯ２浓度上升以及人类活动引起的土地利用和土地覆盖变化导致陆地生态系统在结构、功能、组成和分布等方面的变化及其反馈关系对陆地碳循环的影响是模型模拟的关键问题．生物地理模型和生物地球化学模型是碳循环模型的两大类型,建模方法、模型性质、特点和应用范围各异．碳循环模型的发展方向是综合两类模型的特点,建立全球动态碳循环模型．     

陆地生态系统类型转变与碳循环

 土地利用变化引起的陆地生态系统类型转变对于全球碳循环有着极其重要的作用。　通过总结国内外有关森林砍伐以及森林、草地转变成农田对于碳循环的影响,阐述了可能引起全球“未知汇”现象的重要原因,强调未来中国陆地生态系统碳循环研究应充分重视陆地生态系统类型转变对于全球碳循环的影响研究,包括研究陆地生态系统的不同发展阶段(自然与退化生态系统)、利用方式的改变(森林转化为人工林或农田,草地转化为农田、退耕还林草等)所引起的碳库类型转换的增汇机理及其对全球变化响应,并指出了建立统一观测方法与规范的陆地生态系统碳通量观测网     

Flow cytometric analysis of European flat oyster, Ostrea edulis, haemocytes using a monoclonal antibody specific for granulocytes

The importance of haemocytes in mollusc defence mechanisms can be inferred from their functions. They participate in pathogen elimination by phagocytosis (Cheng, 1981; Fisher, 1986). Hydrolytic enzymes and cytotoxic molecules produced by haemocytes contribute to the destruction of pathogenic organisms (Cheng, 1983; Leippe & Renwrantz, 1988; Charlet et al., 1996; Hubert et al., 1996; Roch et al., 1996). Haemocytes may also be involved in immunity modulation by the production of cytokines and neuropeptides (Hughes et al., 1990; Stefano et al., 1991; Ottaviani et al., 1996). As a result, the literature dealing with bivalve haemocyte studies has increased during the last two decades. Most of these publications use microscopy for morphological analysis (Seiler & Morse, 1988; Auffret, 1989; Hine & Wesney, 1994; Giamberini et al., 1996; Carballal et al., 1997; Lopez et al., 1997; Nakayama et al., 1997), and functional analysis (e.g. phagocytosis) (Hinsch & Hunte, 1990; Tripp, 1992; Mourton et al., 1992; Fryer & Bayne, 1996; Mortensen & Glette, 1996). Flow cytometry represents a rapid technique applicable to both morphological and functional studies of cells in suspension. While the measurements based on autofluorescence provide information on cell morphology, the analyses with fluorescent markers including labelled antibodies, offer data on phenotyping and cell functions. As a result, its application has greatly contributed to the investigation of immunocyte functions and differentiation in vertebrates (Stewart et al., 1986; Rothe & Valet, 1988; Ashmore et al., 1989; Koumans-van Diepen et al., 1994; Rombout et al., 1996; Caruso et al., 1997). Some authors studied oyster haemocyte populations by flow cytometry based on cellular autofluorescence (Friedl et al., 1988; Fisher & Ford, 1988; Ford et al., 1994). However, no analysis using specific monoclonal antibodies has been reported to date. In this study, a protocol for studying European flat oyster, Ostrea edulis, haemocytes by flow cytometry using a monoclonal antibody specific for granulocytes and an indirect immunofluorescence technique have been developed. European flat oysters, Ostrea edulis, 7-9 cm in shell length were obtained from shellfish farms in Marenne Oléron bay (Charente Maritime, France) on the French Atlantic coast. All individuals were purchased just before each experiment and processed without any previous treatment.     

Plant-herbivore models, where more grass means fewer grazers

Classical theory has led us to believe that where more grazing is available herbivores will inflict heavier pressure on the grass, thus keeping its height low. This approach is hotly debated, although still widely accepted. Based on field data collected, van der Koppel et al. [van der Koppel, J., Huisman, J., van der Wal, R., Olff, H., 1996. Patterns of herbivory along a productivity gradient: an empirical and theoretical investigation. Ecology 77, 736–745] contest the standard plant-herbivore models, arguing that herbivores do not ‘control’ the plant growth entirely, and propose two differential equation models. In this paper we describe briefly how van der Koppel et al. (1996) derive their uncontrolled plant-herbivore interaction models, and then expand on the specific mathematical results cited in their paper to provide a global overview of the dynamics of such systems, for a broad range of parameter values.     

Pollen Tubes: a Model System for Plant Cell Growth*

Recent observations of pollen tubes show that these tubes may grow in a pulsatory fashion (Pierson et al., 1995; Plyushch et al., 1995; Li et al., 1996; Geitmann et al., 1996a, 1996b), in which phases of fast and slow growth alternate regularly. The occurrence of pulsatory growth has been used by Geitmann and coworkers (1996b) to study factors that might control growth. Their results emphasize the role of the cell wall and secretory events in regulating pollen tube growth. Here we will briefly review recent results related to the role of exocytosis, cytoskeleton, calcium and the cell wall in pollen tube growth.     

Assessing model accuracy using the homology modeling automatically software

Homology modeling is a powerful technique that greatly increases the value of experimental structure determination by using the structural information of one protein to predict the structures of homologous proteins. We have previously described a method of homology modeling by satisfaction of spatial restraints (Li et al., Protein Sci 1997;6:956-970). The Homology Modeling Automatically (HOMA) web site, , is a new tool, using this method to predict 3D structure of a target protein based on the sequence alignment of the target protein to a template protein and the structure coordinates of the template. The user is presented with the resulting models, together with an extensive structure validation report providing critical assessments of the quality of the resulting homology models. The homology modeling method employed by HOMA was assessed and validated using twenty-four groups of homologous proteins. Using HOMA, homology models were generated for 510 proteins, including 264 proteins modeled with correct folds and 246 modeled with incorrect folds. Accuracies of these models were assessed by superimposition on the corresponding experimentally determined structures. A subset of these results was compared with parallel studies of modeling accuracy using several other automated homology modeling approaches. Overall, HOMA provides prediction accuracies similar to other state-of-the-art homology modeling methods. We also provide an evaluation of several structure quality validation tools in assessing the accuracy of homology models generated with HOMA. This study demonstrates that Verify3D (Luthy et al., Nature 1992;356:83-85) and ProsaII (Sippl, Proteins 1993;17:355-362) are most sensitive in distinguishing between homology models with correct or incorrect folds. For homology models that have the correct fold, the steric conformational energy (including primarily the Van der Waals energy), MolProbity clashscore (Word et al., Protein Sci 2000;9:2251-2259), and the PROCHECK G-factors (Laskowski et al., J Biomol NMR 1996;8:477-486) provide sensitive and consistent methods for assessing accuracy and can distinguish between homology models of higher and lower accuracy. As demonstrated in the accompanying paper (Bhattacharya et al., accompanying paper), combinations of these scores for models generated with HOMA provide a basis for distinguishing low from high accuracy models.     

Quantification of the prentice criteria for surrogate endpoints

In a recent discussion on the Prentice criteria for surrogate endpoints (1989) and the role of meta analyses in this context, Alonso et al. expand on a number of points. Among these is a suggestion to base a measure of the degree at which an endpoint meets the Prentice criteria on a likelihood reduction factor. Although new in this context, the suggestion has been studied elsewhere and the measure of Alonso et al., as presented, requires some modification if it is to be useful in general situations. As it stands it depends upon the censoring mechanism, even when independent of the failure mechanism. This is, however, easily fixed. The measure suggested by Alonso et al. can be seen to fit in with a well-established theory so that, once corrected for the presence of censoring, it can be employed with confidence. Of particular interest is the wide availability of a standard SAS program producing a coefficient which can be immediately transformed to provide an estimate of the population quantity behind the Alonso et al. proposal.     

The purple bacterial photosynthetic unit

Now is a very exciting time for researchers in the area of the primary reactions of purple bacterial photosynthesis. Detailed structural information is now available for not only the reaction center (Lancaster et al. 1995, in: Blankenship RE et al. (eds) Anoxygenic Photosynthetic Bacteria, pp 503–526), but also LH2 from Rhodopseudomonas acidophila (McDermott et al. 1995, Nature 374: 517–521) and LH1 from Rhodospirillum rubrum (Karrasch et al. 1995. EMBO J 14: 631–638). These structures can now be integrated to produce models of the complete photosynthetic unit (PSU) (Papiz et al., 1996, Trends Plant Sci, in press), which opens the door to a much more detailed understanding of the energy transfer events occurring within the PSU.Abbreviations Bchl bacteriochlorophyll - LH light-harvesting - PSU photosynthetic unit Division of Biochemistry and Molecular Biology, Institute of Biomedical and Life Sciences     

Metal hyperaccumulation: a model system for coevolutionary studies

Recent years have seen a flurry of research activity concerning the hyperaccumulation of heavy metals by plants. Much of the interest in hyperaccumulation has been fueled by the commercial potential of phytoremediation, the use of plants to clean up contaminated soils (Baker et al ., 1994; Salt et al ., 1995; Chaney et al ., 1997, 2000). These applications have in turn spurred many studies of the genetics and physiology of metal uptake (e.g. Krämer et al ., 1996; Lasat et al ., 1996; Salt & Krämer, 1999; Baker et al ., 2000; see also Krämer, 2000; Lombi et al ., 2000). Although phytoremediation provides an intriguing and potentially profitable backdrop, the ecology and evolution of hyperaccumulation in natural populations are interesting subjects in their own right. Two papers in this issue (Ghaderian et al ., pp. 219–224; Davis & Boyd, pp. 211–217) are exciting contributions to the growing consensus that hyperaccumulation may act as a defense against herbivores and pathogens, and suggest that hyperaccumulation may become a model system for research in this area.     

An efficient conformational sampling method for homology modeling

The structural refinement of protein models is a challenging problem in protein structure prediction (Moult et al., Proteins 2003;53(Suppl 6):334-339). Most attempts to refine comparative models lead to degradation rather than improvement in model quality, so most current comparative modeling procedures omit the refinement step. However, it has been shown that even in the absence of alignment errors and using optimal templates, methods based on a single template have intrinsic limitations, and that refinement is needed to improve model accuracy. It is thought that failure of current methods originates on one hand from the inaccuracy of the effective free energy functions adopted, which do not represent properly the energetic balance in the native state, and on the other hand from the difficulty to sample the high dimensional and rugged free energy landscape of protein folding, in the search for the global minimum. Here, we address this second issue. We define the evolutionary and vibrational armonics subspace (EVA), a reduced sampling subspace that consists of a combination of evolutionarily favored directions, defined by the principal components of the structural variation within a homologous family, plus topologically favored directions, derived from the low frequency normal modes of the vibrational dynamics, up to 50 dimensions. This subspace is accurate enough so that the cores of most proteins can be represented within 1 A accuracy, and reduced enough so that Replica Exchange Monte Carlo (Hukushima and Nemoto, J Phys Soc Jpn 1996;65:1604-1608; Hukushima et al., Int J Mod Phys C: Phys Comput 1996;7:337-344; Mitsutake et al., J Chem Phys 2003;118:6664-6675; Mitsutake et al., J Chem Phys 2003;118:6676-6688) (REMC) can be applied. REMC is one of the best sampling methods currently available, but its applicability is restricted to spaces of small dimensionality. We show that the combination of the EVA subspace and REMC can essentially solve the optimization problem for backbone atoms in the reduced sampling subspace, even for rather rugged free energy landscapes. Applications and limitations of this methodology are finally discussed.