Validity of Ellenberg indicator values judged from physico‐chemical field measurements

Abstract. The relationship between mean Ellenberg indicator values (IV) per vegetation relevé and environmental parameters measured in the field usually shows a large variation. We tested the hypothesis that this variation is caused by bias dependent on the phytosociological class. For this purpose we collected data containing vegetation relevés and measured soil pH (3631 records) or mean spring groundwater level (MSL, 1600 records). The relevés were assigned to vegetation types by an automated procedure. Regression of the mean indicator values for acidity on soil pH and the mean indicator values for moisture on MSL gave percentages explained variance similar to values that were reported earlier in literature. When the phytosociological class was added as an explanatory factor the explained variance increased considerably. Regression lines per vegetation type were estimated, many of which were significantly different from each other. In most cases the intercepts were different, but in some cases their slopes differed as well. The results show that Ellenberg indicator values for acidity and moisture appear to be biased towards the values that experts expect for the various phytosociological classes. On the basis of the results, we advise to use Ellenberg IVs only for comparison within the same vegetation type.     

Changes in vegetation types and Ellenberg indicator values after 65 years of fertilizer application in the Rengen Grassland Experiment,Germany

Question: How does semi-natural grassland diversify after 65 years of differential application of Ca, N, P, and K fertilizers? Is fertilizer application adequately reflected by the Ellenberg indicator values (EIVs)? Location: Eifel Mountains, West Germany. Methods: The Rengen Grassland Experiment (RGE) was established in an oligotrophic grassland in 1941. Six fertilizer treatments (Ca, CaN, CaNP, CaNP-KCl, CaNP-K₂SO₄, and unfertilized control) were applied annually in five complete randomized blocks. Species composition of experimental plots was sampled in 2006 and compared with constancy tables representing grassland types in a phytosociological monograph of a wider area. Each plot was matched to the most similar community type using the Associa method. Mean EIVs were calculated for each treatment. Results: The control plots supported oligotrophic Nardus grassland of the Polygalo-Nardetum association (Violion caninae alliance). Vegetation in the Ca and CaN treatments mostly resembled montane meadow of Geranio-Trisetetum (Polygono-Trisetion). Transitional types between Poo-Trisetetum and Arrhenatheretum (both from the Arrhenatherion alliance) developed in the CaNP treatment. In the CaNP-KCl and CaNP-K₂SO₄ treatments, vegetation corresponded to the mesotrophic Arrhenatheretum meadow. Major discontinuity in species composition was found between control, Ca, and CaN treatments, and all treatments with P application. EIVs for both nutrients and soil reaction were considerably higher in P treatments than in Ca and CaN treatments. Surprisingly, the control plots had the lowest EIVs for continentality and moisture, although these factors had not been manipulated in the experiment. Conclusions: Long-term fertilizer application can create different plant communities belonging to different phytosociological alliances and classes, even within a distance of a few meters. Due to their correlated nature, EIVs can erroneously indicate changes in factors that actually did not change, but co-varied with factors that did change. In P-limited ecosystems, EIVs for nutrients may indicate availability of P rather than N.     

景观格局指数间相关关系对植被覆盖度等级分类数的响应

运用景观指数进行景观格局分析已成为景观生态学的主要研究方法。但是,由于景观本身的复杂性以及景观格局指数之间的相关性,其应用与发展受到制约。选用面积/周长/密度、形状和蔓延度等3类共28个指数,以广州市中心城区为研究区域,以TM遥感影像为数据源形成植被覆盖度等级图,在景观类型水平上探讨各类型内指数之间的相关性及其对景观分类数的敏感程度。相关性分析表明:景观格局指数间都存在一定的相关性,但是相关程度差异较大,其中面积/周长/密度类指数间的相关性最强,蔓延度类指数其次,形状类指数间独立性相对较强。敏感性分析结果显示:117个指数对的相关关系都随景观分类数发生变化,根据其变化类型和程度,可以分为简单型、分段型、复杂型等3种指数关系响应的类型,分别包括12、31和74对指数;敏感曲线还表明4或5是指数对之间相关关系最敏感的分类数;不仅如此,分类数对景观格局指数之间相关关系的影响程度因景观格局指数所属的类别而异,面积/周长/密度类型指数不敏感,其次是蔓延度类指数,最敏感的是形状类指数;最后,研究结果表明景观格局指数间的相关性对分类数的敏感性存在较大的空间变异。     

Influences of transformation of cover values on classification and ordination of lake vegetation

Summary Numerical ordination (Program ORDINA) and classification (Program TABORD) have been applied to vegetation data from a lake in south Sweden.Full percentage values and different transformations of the estimated percented cover scale have been tested on relevés with nymphaeids (+ elodeids) and on relevés containing obly helophytes. The used scales have been: percentage (P), Hult-Sernander-Du Rietz (HSD), Log (%+1) (LP), 1+ log% (L), 100+ % (HP) and Presence/Absence (P/A). The main aim has been to find if there is an optimal transformation regarding both quantitative and qualitative information in vegetation data.In the classification of helophytes a dataset with 87 relevés and 20 species have been used applying P-and L-scales and P/A. The similarity between the different scales has been compared in relation to common relevés between every two corresponding clusters. L and P/A give very similar results, more similar than L and P or PA and P. It is also interesting that the result with P-scale is more similar to L than to P/A. The P-scale neglects with the species with a low cover value, whilst the L-scale takes notice of both quantity and quality.In the classification of 90 nymphaeid relevés containing only 6 species P, HSD, L, HP and P/A were applied. The L-scale (and partly PH-scale) gave a result similar to the most quantitative P-and HSD-scales. P/A-values gave a very deviating result. In the ordination of helophytes only 38 relevés with 18 species, taken along a transcect, were used and P, P/A and 4 different transformations were applied. The similarity between order of relevés in the graphs and real order of relevés along the transect was used as an objective test of the effectiveness of the scale applied. The P-scale gave a bad result, whilst P/A gave the best result. The intermediate scales L and HP gave acceptable results.In the ordination of nymphaeids (+ elodeids) 90 relevés, where only pattern was studied, the L-scale gave the best result most similar to P-and HSD, but applying the two extremes, P-scale and P/A, resulted in large reduction of information.In the submitted ordinations and classifications the applied L-scale (and HP-scale) always gave ecologically interpretable results, but the extreme transformation were less reliable.This work has been supported by grants from the University of Lund, for which I am duty grateful.Nomenclature follows Lid (1974).I am grateful to Professor Nils Malmer, head of the Department of Plant Ecology, Lund, Sweden, Dr. Eddy van der Maarel, University of Nijmegen, Holland, and my colleague Fil. Kand. Stefan Persson for valuable advice and discussions. I also thank my wife Fil. Kand. Eva Waldemarsson Jensén, Institute of Ecological Botany, Uppsala, for valuable discussions, Mr. Tommy Olsson for valuable technical advice, Dr. R.S. Clymo for advice with DIVINF and PCA and correction of the language, Mrs. Mimmi Varga for drawing the figures and Mrs. Brita Billstein for typewriting the text and the tables.     

罕山土壤微生物群落组成对植被类型的响应

选取分布在中国东北部地区的阔叶林-针叶林-亚高山草甸这一明显的植被垂直带谱来研究植被类型对土壤微生物群落组成的影响。选取5种植被类型-山杨(Populus davidiana)(1250—1300 m),山杨(P.davidiana)与白桦(Betula platyphylla)的混交林(1370—1550 m),白桦(B.platyphylla)(1550—1720 m),落叶松(Larix principis-rupprechtii)(1840—1890 m),亚高山草甸(1900—1951 m),采用磷脂脂肪酸(Phopholipid Fatty Acids,PLFAs)分析方法测定不同植被类型下的土壤微生物群落组成。分别采用主成分分析(Principal Components Analysis,PCA)以及冗余分析(Redundancy Analysis,RDA)来解释单种特征PLFAs的分异以及土壤理化指标与微生物PLFAs指标间的相关性。结果表明不同植被类型下土壤有机碳(SOC)对土壤微生物PLFAs总量,各类群(真菌(f)、细菌(b)、革兰氏阳性菌(G+)、革兰氏阴性菌(G-))生物量以及群落结构影响显著;土壤微生物PLFAs总量及各类群的生物量随土层加深总体上表现降低趋势,G+/G-和f/b分别随土层加深总体上表现升高趋势。不同植被类型下,阔叶混交林土壤PLFAs总量及各类群生物量总体上最高;针叶林比阔叶林下的f/b和G+/G-高;亚高山草甸下低的p H值对有机碳的可利用性有一定的抑制作用,导致f/b和G+/G-的值相对较高。总之,不同植被类型下SOC对土壤微生物群落组成的影响最为显著,而较低的p H对有机碳的可利用性有一定的抑制作用;真菌对植被类型的变化比细菌更敏感,而细菌更易受可利用性养分和p H变异的影响,这对预测不同林型下的土壤微生物群落组成有重要的启示作用。     

中国热带森林植被类型研究历史和划分探讨

热带森林是我国森林植被的重要组成部分,明确其森林植被类型分类对于生物多样性维持机制研究和保护管理等都具有重要意义。该文以中国热带森林植被分类研究中存在的问题为出发点,通过阐述我国各省区植被类型分类的研究历史,在综合考虑多种生物和非生物影响因素的基础上,提出一个新的热带森林植被类型分类框架以供探讨。结果表明:(1)尽管针对我国热带森林的分布范围和群落特征等都已开展了诸多研究,但对我国热带森林植被类型的划分依据和分类体系仍存在争议。(2)尽管我国的热带森林都处于季风气候区带内,但许多热带地区的森林植被类型并不只是受季风影响,而是气候带、关键气候因子、地形、土壤反馈和物种适应等多种因素共同作用的结果。(3)我国的热带森林植被包括5个植被型,即非典型性热带雨林、热带季雨林、热带山地雨林、热带山顶苔藓矮林(热带云雾林)和热带针叶林,其中热带季雨林植被型包含4种植被亚型[热带落叶季雨林、热带半落叶(半常绿)季雨林、热带常绿季雨林和热带石灰岩(石山)季雨林]。(4)阐明了上述热带森林植被型和植被亚型在我国各省区的分布情况,并提出未来有必要对人工恢复后的热带森林进行评估和植被类型划分。综上所述,该文提出一个新的热带森林植被类型分类框架,以期为今后基于不同地区开展热带森林比较研究提供参考。     

不同参考温度取值对三温模型反演植被蒸腾精度的影响

参考温度的参数化过程一直是三温模型反演蒸散发及其蒸发、蒸腾组分的关键和难点。该研究基于典型城市草坪的波文比与热红外观测数据, 对三温模型植被蒸腾子模型中涉及的输入变量进行敏感性分析和误差分析, 确定对三温模型反演植被蒸腾精度最为关键的变量, 而后量化和对比输入变量参数化方法对三温模型计算草坪蒸腾的影响, 由此确定最佳的参考温度取值。结果表明: 1)参考叶片温度选择为整个纸片温度的最大值时反演效果最好(R² = 0.91, 均方根误差(RMSE) = 0.078 mm·h^-1); 2)采用植被冠层温度的最大值为参考温度时, 直接假定了植被最高温度冠层蒸腾为0 (实际存在一定的蒸腾速率), 所以容易低估实际蒸腾量, 造成三温模型反演精度略低于取值参考叶片温度最大值的方法, 但反演效果仍然较好(R² = 0.87, RMSE = 0.080 mm·h^-1)。因此, 考虑到参考叶片设置的局限性, 如果在实际应用中无法或者没有实际测量参考叶片温度时, 使用植被最大温度为参考温度也可达到较好的反演效果。     

A dynamic global vegetation model for use with climate models: concepts and description of simulated vegetation dynamics

Changes in vegetation structure and biogeography due to climate change feedback to alter climate by changing fluxes of energy, moisture, and momentum between land and atmosphere. While the current class of land process models used with climate models parameterizes these fluxes in detail, these models prescribe surface vegetation and leaf area from data sets. In this paper, we describe an approach in which ecological concepts from a global vegetation dynamics model are added to the land component of a climate model to grow plants interactively. The vegetation dynamics model is the Lund–Potsdam–Jena (LPJ) dynamic global vegetation model. The land model is the National Center for Atmospheric Research (NCAR) Land Surface Model (LSM). Vegetation is defined in terms of plant functional types. Each plant functional type is represented by an individual plant with the average biomass, crown area, height, and stem diameter (trees only) of its population, by the number of individuals in the population, and by the fractional cover in the grid cell. Three time‐scales (minutes, days, and years) govern the processes. Energy fluxes, the hydrologic cycle, and carbon assimilation, core processes in LSM, occur at a 20 min time step. Instantaneous net assimilated carbon is accumulated annually to update vegetation once a year. This is carried out with the addition of establishment, resource competition, growth, mortality, and fire parameterizations from LPJ. The leaf area index is updated daily based on prevailing environmental conditions, but the maximum value depends on the annual vegetation dynamics. The coupling approach is successful. The model simulates global biogeography, net primary production, and dynamics of tundra, boreal forest, northern hardwood forest, tropical rainforest, and savanna ecosystems, which are consistent with observations. This suggests that the model can be used with a climate model to study biogeophysical feedbacks in the climate system related to vegetation dynamics.     

黄土高原不同植被覆被类型NDVI对气候变化的响应

植被与气候是目前研究生态与环境的重要内容。为探究黄土高原地区植被与气候因子之间的响应机制,利用线性趋势分析、Pearson相关分析、多元线性回归模型以及通径分析的方法,对黄土高原2000—2015年全区和不同植被覆被类型区内NDVI与气候因子的变化趋势以及相互作用关系进行分析。植被覆被分类数据和植被指数数据分别来源于ESA CCI-LC(The European Space Agency Climate Change Initiative Land Cover)以及MODND1T/NDVI(Normalized Difference Vegetation Index)。结果表明:(1) 2000—2015年黄土高原全区植被年NDVI_(max)显著增加的区域占总面积的74.25%,不同植被覆被类型年NDVI_(max)分别为常绿阔叶林常绿针叶林落叶阔叶林落叶针叶林镶嵌草地农田镶嵌林地草地灌木,并且都呈显著增加趋势,其中常绿阔叶林和农田增加幅度最大,为0.012/a。(2)黄土高原全区NDVI与气温、日照、降水和相对湿度等气候因子之间没有显著相关性,但在不同植被覆被类型区,气候因子对NDVI存在显著作用,且不同植被覆被类型差异明显。(3)在全区和不同植被覆被类型区NDVI仅对降水的响应比较一致,气温无论在整个区域尺度还是不同植被覆被类型区对植被的影响均不显著。(4)常绿阔叶林、落叶阔叶林、常绿针叶林及镶嵌林地等以乔木为主的植被覆被类型受年均相对湿度和年总日照时数的显著负效应驱动,草地、镶嵌草地等以草本为主的植被覆被类型则受到年总降水量的显著正效应影响。这说明对植被类型进行区分,更有利于揭示气候对植被的作用机制。     

Improving predictive mapping in Swiss mire ecosystems through re‐calibration of indicator values

Question: How may Landolt indicator values be re‐calibrated to improve the performance of predictive models? Location: Mires Gross Moos Schwändital (1250 m a.s.l.) in the Prealps, Burgmoos (465 m. a.s.l.) on the Central Plateau and La Burtignière (1000 m a.s.l.) in the Jura, Switzerland. Methods: Habitat distribution models based on high resolution remotely sensed data and vegetation field data are applied to monitor 130 mires. Instead of plant species or communities we used mean indicator values of vegetation records as response variables. To improve the differential power of indicator values for wetland habitat conditions, we calibrated these values using field data. Different methods were tested with our predictive models in three mires to see which calibration method is best in enhancing model performance. To assess the effect of the uneven distribution of vegetation records along environmental gradients, calibrations based on random and evenly distributed samples were compared. As a test of the predictive power of the models we used r² between ground truth and model prediction. This approach is illustrated through an application with nutrient indicator values in the mire La Burtignière. Results: Model performances were not the same for the three mires. The predictive power was better for the nutrient values, soil reaction and humus values than for light and moisture values. 2000 records were sufficient as basis for re‐calibration. Models based on original Landolt indicator values were overall the weakest compared with re‐calibrated values. By comparing the predictive power of Models based on randomly or evenly selected records were about equally predictive. Conclusions: 1. Ahabitat‐specific re‐calibration of the Landolt indicator values enhances the predictive mapping of the Swiss mire ecosystems. 2. The re‐calibration based on weighted averaging gives a better performance than the one based on Gaussian logistic regression. 3. The uneven distribution of indicator values due to the over‐representation of mire habitats does not hamper model performance. 4. 2000 vegetation records are a sufficient basis for an optimal re‐calibration of the vegetation types. An illustration of the method is given by using the soil fertility pattern of the mire La Burtignière.     

An application case of ecological indicator values (Zeigerwerte) calculated with a simple algorithmic approach

Abstract

The vegetation of the study site near Rome (Castelporziano Estate), where different woodland types occur, was analysed on the basis of ecological indicator values (Zeigerwerte) for light, temperature, continentality of climate, soil moisture, soil pH and nitrogen. Indicator values were estimated with Hill's reprediction algorithm for the flora of Central-Southern Italy relying on a database of 4,207 original relevés representing a balanced survey of the vegetation of this and surrounding areas. It was possible to obtain indicator values for an important fraction of the Italian Mediterranean flora. Results are ecologically reasonable, and it was possible to find strong correlation between the recalculated values and a few environmental variables. These correlations were not significant in an analogous test with subjectively derived scores of Ellenberg indicator values.     

Towards a more transparent use of the potential natural vegetation concept – an answer to Chiarucci et al.

In this paper, the concerns of Chiarucci et al. ( 2010 ) regarding use of the potential natural vegetation (PNV) concept are addressed, as voiced in the forum section of the Journal of Vegetation Science. First, we rectify some unfounded expectations concerning PNV, including a relationship with prehuman vegetation and phytosociology. Second, we point out issues that pose considerable challenges in PNV and require common agreement. Here, we address the issue of time and disturbance. We propose to use the static PNV concept as a baseline, a null model for landscape assessment and in comparisons. Instead of changing the PNV concept itself, we introduce a new term, potential future natural vegetation (PFV) to cover estimations of potential successional outcomes. Finally, we offer a new view of PNV with which we intend to make the use of PNV estimates more transparent. We formalize the PNV theory into a partial cause‐effect model of vegetation that clearly states which effects on vegetation are factored out during its estimation. Further, we also propose to assess PNV in a probabilistic setting, rather than providing a single estimate for one location. This multiple PNV would reflect our uncertainty about the vegetation entity that could persist at the locality concerned. Such uncertainty arises from the overlap of environmental preferences of different mature vegetation types. Thus reformulated, we argue that the PNV concept has much to offer as a null model, especially in landscape ecology and in site comparisons in space and time.     

基于Hyperion的锡林郭勒草原光合植被、非光合植被覆盖度估算

掌握草原生态系统光合植被覆盖度(fPV)与非光合植被覆盖度(fNPV)时空动态对了解干旱半干旱草原生态系统特征(覆盖状况、火灾负载、载畜量、干扰及恢复等)及进行科学、有效地草地资源管理具有重要的意义。选取锡林郭勒典型草原为试验区,以Hypeiron高光谱数据为数据源,利用NDVI-CAI三元线性混合模型对试验区fPV和fNPV的时空动态分布进行了估算,并对不同端元选择方法(最小包含端元特征法、纯净象元指数法和实测法)对估算结果的影响进行了比较分析。研究结果表明,NDVI-CAI三元线性混合模型是同时估测锡林郭勒草原fPV和fNPV的有效方法,且估算的fPV和fNPV的季节变化与牧草的物候发育特征相吻合。不同端元选择方法对估算精度具有一定的影响,其中基于最小包含端元特征法提取端元进行估算的精度最高,fPV估算的均方根误差RMSE=4.57,估算精度EA=91.2%;fNPV估算的RMSE=5.90,EA=67.91%(样本数N=52)。