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Spatial scales of variation in lichens: Implications for sampling design in biomonitoring surveys

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Abstract

The variability of biological data is a main constraint affecting the quality and reliability of lichen biomonitoring surveys for estimation of the effects of atmospheric pollution. Although most epiphytic lichen bioindication surveys focus on between-site differences at the landscape level, associated with the large scale effects of atmospheric pollution, current protocols are based on multilevel sampling, thus adding further sources of variation and affecting the error budget. We test the hypothesis that assemblages of lichen communities vary at each spatial scale examined, in order to determine what scales should be included in future monitoring studies. We compared four sites in Italy, along gradients of atmospheric pollution and climate, to test the partitioning of the variance components of lichen diversity across spatial scales (from trunks to landscapes). Despite environmental heterogeneity, we observed comparable spatial variance. However, residuals often overcame between-plot variability, leading to biased estimation of atmospheric pollution effects.

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... Thus, the second step is to qualify, quantify, and control the main ecological factors that can affect our response variable, both including those of our interest and also the ones which may represent a source of noise (Brunialti et al. 2010a). Indeed, the effect of large-scale (such as climate) or local scale (as tree substrate) natural factors may represent relevant sources of variability and noise in relation to the phenomenon we are studying (Giordani et al. 2013; Ellis 2012). Also, some of these effects may be cumulative (Jovan and McCune 2004; Pinho et al. 2004; Giordani 2006; Caruso and Thor 2007). ...
... Controlling the spatial variation at macroscales is necessary but not sufficient , if the variation at more detailed levels (e.g., considering areas <1 km 2 ) remains unknown. A recent study explored the variability of lichen composition throughout the spatial levels using sound sampling protocols, along biogeographic, climatic, and pollution gradients (Giordani et al. 2013). The authors showed that the distribution of variation in lichen diversity was impressively similar across the spatial scales (Giordani et al. 2013). ...
... A recent study explored the variability of lichen composition throughout the spatial levels using sound sampling protocols, along biogeographic, climatic, and pollution gradients (Giordani et al. 2013). The authors showed that the distribution of variation in lichen diversity was impressively similar across the spatial scales (Giordani et al. 2013). In particular, they found that it was fairly constant despite climatic variation, landscape complexity, air pollution, and general anthropogenic pressure. ...
Chapter
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... Lo anterior, corresponde a una situación como consecuencia de las coberturas registradas en las especies toxófilas de dicha área, lo que resta importancia en el IPA a la riqueza de las especies sensibles. Teniendo en cuenta lo mencionado, pueden aplicarse correcciones a través de variaciones a la fórmula, como lo sugieren Kaffer et al. (2011), donde se tiene en cuenta la escala de cobertura de las formas de crecimiento o las escalas espaciales que mencionan Giordani et al. (2013); pues al reducir la escala de los polígonos establecidos puede sugerirse que la estación RFP "el Malmo" corresponde a una estación con baja contaminación, pero que se encuentra inmersa en un área con mayor incidencia de los contaminantes atmosféricos. En el estudio realizado por Rubiano y Chaparro (2006) para la Universidad Nacional Colombia (en Bogotá), se registran coincidencias con esta investigación, en cuanto a la representatividad y toxofilia de especies como Flavopunctelia flaventior, Heterodermia albicans y Parmotrema austrosinense, de igual forma se observa que las zonas de alta contaminación se ubican en el centro del área evaluada como ocurre en la ciudad de Tunja. ...
... Lo anterior, corresponde a una situación como consecuencia de las coberturas registradas en las especies toxófilas de dicha área, lo que resta importancia en el IPA a la riqueza de las especies sensibles. Teniendo en cuenta lo mencionado, pueden aplicarse correcciones a través de variaciones a la fórmula, como lo sugieren Kaffer et al. (2011), donde se tiene en cuenta la escala de cobertura de las formas de crecimiento o las escalas espaciales que mencionan Giordani et al. (2013); pues al reducir la escala de los polígonos establecidos puede sugerirse que la estación RFP "el Malmo" corresponde a una estación con baja contaminación, pero que se encuentra inmersa en un área con mayor incidencia de los contaminantes atmosféricos. En el estudio realizado por Rubiano y Chaparro (2006) para la Universidad Nacional Colombia (en Bogotá), se registran coincidencias con esta investigación, en cuanto a la representatividad y toxofilia de especies como Flavopunctelia flaventior, Heterodermia albicans y Parmotrema austrosinense, de igual forma se observa que las zonas de alta contaminación se ubican en el centro del área evaluada como ocurre en la ciudad de Tunja. ...
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1 fig. [Correction of figure from article in Lichenologist 35(4): 347-359 (2003).]
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“Design”, “sampling” and “quality” are highly relevant to the subject of this book for different reasons. First, although there is a wealth of experience in monitoring the effects of atmospheric pollution by plants (e.g. [35, 61, 62, 87]), it seems that the importance of an appropriate sampling design is often underestimated [63, 112]. Indeed subjectivity in sampling procedures was found to be the main source of data variability in bioindication studies based on lichens (e.g. [88]). Similarly, field sampling of plants for chemical analyses was proven to introduce errors exceeding 1000%, whereas all the subsequent steps (e.g. storage, drying, homogenisation and chemical decomposition) may cause errors of up to 100–300% (e.g. [5, 63, 112]).
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It is argued that the problem of pattern and scale is the central problem in ecology, unifying population biology and ecosystems science, and marrying basic and applied ecology. Applied challenges, such as the prediction of the ecological causes and consequences of global climate change, require the interfacing of phenomena that occur on very different scales of space, time, and ecological organization. Furthermore, there is no single natural scale at which ecological phenomena should be studied; systems generally show characteristic variability on a range of spatial, temporal, and organizational scales. The observer imposes a perceptual bias, a filter through which the system is viewed. This has fundamental evolutionary significance, since every organism is an "observer" of the environment, and life history adaptations such as dispersal and dormancy alter the perceptual scales of the species, and the observed variability. It likewise has fundamental significance for our own study of ecological systems, since the patterns that are unique to any range of scales will have unique causes and biological consequences. The key to prediction and understanding lies in the elucidation of mechanisms underlying observed patterns. Typically, these mechanisms operate at different scales than those on which the patterns are observed; in some cases, the patterns must be understood as emerging form the collective behaviors of large ensembles of smaller scale units. In other cases, the pattern is imposed by larger scale constraints. Examination of such phenomena requires the study of how pattern and variability change with the scale of description, and the development of laws for simplification, aggregation, and scaling. Examples are given from the marine and terrestrial literatures.
Article
The most appropriate strategy to be used to create a permutation distribution for tests of individual terms in complex experimental designs is currently unclear. There are often many possibilities, including restricted permutation or permutation of some form of residuals. This paper provides a summary of recent empirical and theoretical results concerning available methods and gives recommendations for their use in univariate and multivariate applications. The focus of the paper is on complex designs in analysis of variance and multiple regression (i.e., linear models). The assumption of exchangeability required for a permutation test is assured by random allocation of treatments to units in experimental work. For observational data, exchangeability is tantamount to the assumption of independent and identically distributed errors under a null hypothesis. For partial regression, the method of permutation of residuals under a reduced model has been shown to provide the best test. For analysis of variance, one must first identify exchangeable units by considering expected mean squares. Then, one may generally produce either (i) an exact test by restricting permutations or (ii) an approximate test by permuting raw data or some form of residuals. The latter can provide a more powerful test in many situations.La stratégie la plus appropriée pour générer une distribution de permutation en vue de tester les termes individuels d'un plan expérimental complexe n'est pas évidente à l'heure actuelle. Il y a souvent plusieurs options, dont la permutation restreinte et la permutation d'une quelconque forme des résiduels. On trouvera ici un résumé d'informations récentes empiriques et théoriques sur les méthodes disponibles, ainsi que des recommandations pour leur utilisation dans des applications unidimensionnelles et multidimensionnelles. L'emphase est mise sur les plans complexes d'analyse de variance et de régression multiple (i.e. les modèles linéaires). Dans un travail expérimental, la supposition d'échangeabilité requise pour un test par permutation est assurée par l'assignation au hasard à des unités des divers traitements. Dans le cas d'observations, l'échangeabilité équivaut à supposer que les erreurs, dans une hypothèse nulle, sont indépendantes et distribuées de façon identique. Pour la régression partielle, la méthode de permutation des résiduels dans un modèle réduit s'est avérée la meilleure. Pour l'analyse de variance, il faut d'abord identifier les unités échangeables à l'examen des carrés moyens attendus. Ensuite, il est généralement possible de produire (i) un test exact en restreignant les permutations ou alors (ii) un test approximatif en permutant les données brutes ou une forme quelconque des résiduels. Cette dernière méthode fournit, dans plusieurs situations, un test plus puissant.[Traduit par la Rédaction]
Article
Several permutation strategies are often possible for tests of individual terms in analysis-of-variance (ANOVA) designs. These include restricted permutations, permutation of whole groups of units, permutation of some form of residuals or some combination of these. It is unclear, especially for complex designs involving random factors, mixed models or nested hierarchies, just which permutation strategy should be used for any particular test. The purpose of this paper is two-fold: (i) we provide a guideline for constructing an exact permutation strategy, where possible, for any individual term in any ANOVA design; and (ii) we provide results of Monte Carlo simulations to compare the level accuracy and power of different permutation strategies in two-way ANOVA, including random and mixed models, nested hierarchies and tests of interaction terms. Simulation results showed that permutation of residuals under a reduced model generally had greater power than the exact test or alternative approximate permutation methods (such as permutation of raw data). In several cases, restricted permutations, in particular, suffered more than other procedures, in terms of loss of power, challenging the conventional wisdom of using this approach. Our simulations also demonstrated that the choice of correct exchangeable units under the null hypothesis, in accordance with the guideline we provide, is essential for any permutation test, whether it be an exact test or an approximate test. For reference, we also provide appropriate permutation strategies for individual terms in any two-way or three-way ANOVA for the exact test (where possible) and for the approximate test using permutation of residuals.
Article
The forest canopy is fundamentally important in biodiversity conservation and ecosystem function. Cryptogamic epiphytes are dominant tree bole and canopy elements in temperate and boreal forests, though remain neglected by mainstream forest ecology. This review makes ecological information on cryptogamic epiphytes available to a non-specialist audience, to facilitate their integration in forest biodiversity and ecosystem studies more generally. The review focuses specifically on lichen epiphytes, highlighting their diversity and ecosystem role. A principal task is to explore pattern and process in lichen epiphyte diversity – species composition and richness – therefore demonstrating the utility of lichens as an ecological model system. The review examines key themes in previous research. First, the extensive literature used to resolve species response to, and community turnover along environmental/resource gradients, consistent with the habitat niche. Second, the evidence for dispersal-limitation, which may constrain community composition and richness in isolated habitats. Third, these two processes – the habitat niche and dispersal-limitation – are used to explain stand-scale diversity, in addition to the role of neutral effects (habitat area). Fourth, the review moves from a taxonomic (pattern) to a functional (process) perspective, considering evidence for autogenic succession evidenced by competition and/or facilitation, and non-random trends in life-history traits. This functional approach provides a counter-point to an assumption that lichen epiphyte communities are unsaturated and non-competitive, a situation which would allow the long-term accumulation of species richness with temporal continuity. Finally, the review explores landscape-scale impacts on lichen epiphytes, with recommendations for conservation.
Article
The most appropriate strategy to be used to create a permutation distribution for tests of individual terms in complex experimental designs is currently unclear. There are often many possibilities, including restricted permutation or permutation of some form of residuals. This paper provides a summary of recent empirical and theoretical results concerning available methods and gives recommendations for their use in univariate and multivariate applications. The focus of the paper is on complex designs in analysis of variance and multiple regression (i.e., linear models). The assumption of exchangeability required for a permutation test is assured by random allocation of treatments to units in experimental work. For observational data, exchangeability is tantamount to the assumption of independent and identically distributed errors under a null hypothesis. For partial regression, the method of permutation of residuals under a reduced model has been shown to provide the best test. For analysis of variance, one must first identify exchangeable units by considering expected mean squares. Then, one may generally produce either (i) an exact test by restricting permutations or (ii) an approximate test by permuting raw data or some form of residuals. The latter can provide a more powerful test in many situations.
Article
Nonparametric multivariate analysis of ecological data using permutation tests has two main challenges: (1) to partition the variability in the data according to a complex design or model, as is often required in ecological experiments, and (2) to base the analysis on a multivariate distance measure (such as the semimetric Bray-Curtis measure) that is reasonable for ecological data sets. Previous nonparametric methods have succeeded in one or other of these areas, but not in both. A recent contribution to Ecological Monographs by Legendre and Anderson, called distance-based redundancy analysis (db-RDA), does achieve both. It does this by calculating principal coordinates and subsequently correcting for negative eigenvalues, if they are present, by adding a constant to squared distances. We show here that such a correction is not necessary. Partitioning can be achieved directly from the distance matrix itself, with no corrections and no eigenanalysis, even if the distance measure used is semimetric. An ecological example is given to show the differences in these statistical methods. Empirical simulations, based on parameters estimated from real ecological species abundance data, showed that db-RDA done on multifactorial designs (using the correction) does not have type 1 error consistent with the significance level chosen for the analysis (i.e., does not provide an exact test), whereas the direct method described and advocated here does.
Article
The lichen monitoring programme included in the Dutch National Air Quality Survey was used to explore the utility of these organisms as indicators for atmospheric ammonia. Over the period 1977–1990 the “nitrophytic” species (assumed to occur optimally in N-rich habitats) strongly increased at the 150 monitoring stations of the network. Furthermore, a positive correlation was found between the occurrence of these species and local NH3 concentrations. Earlier reports therefore proposed the use of nitrophytic lichens as bioindicators for NH3 and considered their increase as an indication for increasing NH3 concentrations. However, a more careful statistical analysis of the available data shows a strong impact of decreasing SO2 levels on all epiphytic lichens, including the nitrophytic species. It is now clear that the “nitrophytic” species do respond to atmospheric NH3, but their response to SO2 is far stronger. Furthermore, chemical analysis of tree bark shows that nitrophytic lichen species do not respond directly to N levels, but are rather favoured by the high bark pH associated with high NH3 levels. Three mechanisms are presented to explain the strong response of the nitrophytic lichens to decreasing SO2 levels.
Article
Several permutation strategies are often possible for tests of individual terms in analysis-of-variance (ANOVA) designs. These include restricted permutations, permutation of whole groups of units, permutation of some form of residuals or some combination of these. It is unclear, especially for complex designs involving random factors, mixed models or nested hierarchies, just which permutation strategy should be used for any particular test. The purpose of this paper is two-fold: (i) we provide a guideline for constructing an exact permutation strategy, where possible, for any individual term in any ANOVA design; and (ii) we provide results of Monte Carlo simulations to compare the level accuracy and power of different permutation strategies in two-way ANOVA, including random and mixed models, nested hierarchies and tests of interaction terms. Simulation results showed that permutation of residuals under a reduced model generally had greater power than the exact test or alternative approximate permutation methods (such as permutation of raw data). In several cases, restricted permutations, in particular, suffered more than other procedures, in terms of loss of power, challenging the conventional wisdom of using this approach. Our simulations also demonstrated that the choice of correct exchangeable units under the null hypothesis, in accordance with the guideline we provide, is essential for any permutation test, whether it be an exact test or an approximate test. For reference, we also provide appropriate permutation strategies for individual terms in any two-way or three-way ANOVA for the exact test (where possible) and for the approximate test using permutation of residuals.
Article
a b s t r a c t This paper aimed to compare epiphyte assemblages of leaves and rhizomes of Posidonia oceanica exposed to different levels of concentration of nutrients. The same design including a potentially impacted meadow and two reference meadows was used in each of two locations, characterized by the presence of a city or of suspended cages of a fish farm, respectively. This allowed to test for the consistency of re-sponses of epiphytic assemblages to different sources of eutrophication. In both studies, results docu-mented differences in patterns of composition and abundance of epiphytic assemblages on leaves between disturbed and reference meadows, while assemblages on rhizomes did not appear sensitive to this kind of disturbance. Moreover, in potentially impacted meadows, both assemblages showed different patterns of spatial variability compared to reference assemblages. Species composition and abundance of epiphyte assemblages seemed suitable for detecting moderate nutrient increases, even if adequate sampling designs are needed to separate patterns related to the large natural spatial variability of these systems from those related to changes in environmental conditions.
Article
A recent survey of epiphytic lichens in the Jardin du Luxembourg has shown there to be a marked improvement in the air quality of Paris over the past decade. Recolonization by at least 11 lichen species has occurred during that period. It has taken almost 100 years for epiphytic lichens to re-establish in the Jardin du Luxembourg, where William Nylander in the 1890s was able to amply confirm his far reaching hypothesis, made 30 years earlier, on the direct relationship between lichen survival and air pollution.
Article
Sampling requirements related to lichen biomonitoring include optimal sampling density for obtaining precise and unbiased estimates of population parameters and maps of known reliability. Two available datasets on a sub-national scale in Italy were used to determine a cost-effective sampling density to be adopted in medium-to-large-scale biomonitoring studies. As expected, the relative error in the mean Lichen Biodiversity (Italian acronym: BL) values and the error associated with the interpolation of BL values for (unmeasured) grid cells increased as the sampling density decreased. However, the increase in size of the error was not linear and even a considerable reduction (up to 50%) in the original sampling effort led to a far smaller increase in errors in the mean estimates (<6%) and in mapping (<18%) as compared with the original sampling densities. A reduction in the sampling effort can result in considerable savings of resources, which can then be used for a more detailed investigation of potentially problematic areas. It is, however, necessary to decide the acceptable level of precision at the design stage of the investigation, so as to select the proper sampling density.
Article
Epiphytic lichens are one of the taxonomic groups most sensitive to forest management. Nevertheless, they have not yet been exhaustively included in the assessment of Sustainable Forest Management. This work aimed at evaluating the effects of forest management on epiphytic lichens in coppiced forests, exploring the spatial patterns of diversity and the composition of communities. Moreover, the goal was to compare the performance of four potential indicators for monitoring the effects of forest management on epiphytic lichens: total lichen diversity, species associated with intensive management, species associated with aged coppiced woodlands and Indicator Species Ratio (ISR). In humid Mediterranean Liguria, 50 sampling units were chosen in Castanea sativa and deciduous Quercus spp. forests subjected to different forest management practices: intensively managed coppice and aged coppice/high forest. The effect of forest management was evident in terms of species composition, since it was possible to find significantly associated species for each of the two management types. At each sampling site, the four indicators were calculated using Indicator Value Analysis and compared through correspondence analysis. The ISR was shown to be a more effective indicator, being independent of floristic composition and the occurrence of rare species.
Article
2002. A balanced view of scale in spatial statistical analysis. – Ecography 25: 626– 640. Concepts of spatial scale, such as extent, grain, resolution, range, footprint, support and cartographic ratio are not interchangeable. Because of the potential confusion among the definitions of these terms, we suggest that authors avoid the term ''scale'' and instead refer to specific concepts. In particular, we are careful to discriminate between observation scales, scales of ecological phenomena and scales used in spatial statistical analysis. When scales of observation or analysis change, that is, when the unit size, shape, spacing or extent are altered, statistical results are expected to change. The kinds of results that may change include estimates of the population mean and variance, the strength and character of spatial autocorrelation and spatial anisotropy, patch and gap sizes and multivariate relationships. The first three of these results (precision of the mean, variance and spatial autocorrelation) can sometimes be estimated using geostatistical support-effect models. We present four case studies of organism abundance and cover illustrating some of these changes and how conclu-sions about ecological phenomena (process and structure) may be affected. We identify the influence of observational scale on statistical results as a subset of what geographers call the Modifiable Area Unit Problem (MAUP). The way to avoid the MAUP is by careful construction of sampling design and analysis. We recommend a set of considerations for sampling design to allow useful tests for specific scales of a phenomenon under study. We further recommend that ecological studies completely report all components of observation and analysis scales to increase the possibility of cross-study comparisons.
Article
Air-quality monitoring in the United States is typically focused on urban areas even though the detrimental effects of pollution often extend into surrounding eco-systems. The purpose of this study was to construct a model, based upon epiphytic ma-crolichen community data, to indicate air-quality and climate in forested areas throughout the greater Central Valley of California (USA). The structure of epiphytic lichen com-munities is widely recognized as an effective biological indicator of air-quality as sensi-tivities to common anthropogenic pollutants vary by species. We used nonmetric multi-dimensional-scaling ordination to analyze lichen community data from 98 plots. To calibrate the model, a subset of plots was co-located with air-quality monitors that measured ambient levels of ozone, sulfur dioxide, and nitrogen dioxide. Two estimates of ammonia deposition, which is not regularly monitored by any state or federal agency in California, were ap-proximated for all plots using land-use maps and emissions estimates derived from the California Gridded Ammonia Inventory Modeling System. Two prominent gradients in community composition were found. One ordination axis corresponded with an air-quality gradient relating to ammonia deposition. Ammonia deposition estimates (r 0.63 and 0.51), percentage nitrophilous lichen richness (r 0.76), and percentage nitrophile abundance (r 0.78) were correlated with the air-quality axis. Plots from large cities and small, highly agricultural towns had relatively poor air-quality scores, indicating similar levels of ammonia deposition between urban and agrarian land uses. The second axis was correlated with humidity (r 0.58), distance from the coast (r 0.62), kriged estimates of cumulative ozone exposure (r 0.57), maximum one-hour measurements of ozone (r 0.58), and annual means of nitrogen dioxide (r 0.63). Compared to ammonia, ozone and nitrogen dioxide impacts on lichen communities are poorly known, making it difficult to determine whether the second axis represents a response to climate, pollution, or both. Additionally, nitric acid may be influencing lichen communities although the lack of de-position data and research describing indicator species prevented us from evaluating po-tential impacts.
Article
Hypothesis-testing methods for multivariate data are needed to make rigorous probability statements about the effects of factors and their interactions in experiments. Analysis of variance is particularly powerful for the analysis of univariate data. The traditional multivariate analogues, however, are too stringent in their assumptions for most ecological multivariate data sets. Non-parametric methods, based on permutation tests, are preferable. This paper describes a new non-parametric method for multivariate analysis of variance, after McArdle and Anderson (in press). It is given here, with several applications in ecology, to provide an alternative and perhaps more intuitive formulation for ANOVA (based on sums of squared distances) to complement the description provided by McArdle and Anderson (in press) for the analysis of any linear model. It is an improvement on previous non-parametric methods because it allows a direct additive partitioning of variation for complex models. It does this while maintaining the flexibility and lack of formal assumptions of other non-parametric methods. The test-statistic is a multivariate analogue to Fisher’s F-ratio and is calculated directly from any symmetric distance or dissimilarity matrix. P-values are then obtained using permutations. Some examples of the method are given for tests involving several factors, including factorial and hierarchical (nested) designs and tests of interactions.
Article
Question: How consistent are relationships of forest lichen community composition with environmental variables across geographic scales within region and across regions?Location: Northwestern continental USA and east central continental USA.Method: Four macrolichen data sets were compiled using identical plot sample protocol: species abundance estimated in 0.4-ha permanent plots on a systematic grid, as part of government (USDA-FS) forest inventory programs. One data set in each region represented a large area; the other represented part of the large area. We used global NMS ordination of plots based on species abundance to extract major axes of variation in community composition. Correlations of species, guilds, and environmental variables with ordination axes were compared between geographic scales for the two regions.Results: Primary axes of community variation at larger scales were correlated with climate variables and related geographic variables such as latitude and elevation, and with pollution. Forest vegetation variables such as stand age and tree species composition became more important at small scales. Community variation unexplained by macro-environment variables also became more important at small scales. Of several hundred species tested, ten lichen species showed consistent behaviour between scales within region (one also across regions) and are thus potential general indicators of ecological conditions in forests. Of six lichen guilds tested, several show strong patterns not consistently related to environmental conditionsConclusions: Interpretation of lichen species and community composition as indicating particular environmental conditions is context-dependent in most cases. Observed relationships should not be generalized beyond the geographic and ecological scale of observation.
Article
Epiphytic lichen vegetation onFagus sylvatica sas studied in 4 sites along an altitudinal gradient from 930 to 1500 m on SE facing slopes of Mount Olympos (Greece). The crucial factor determining the spatial heterogeneity of epiphytic lichens onF. sylvatica is the altitude and not the height on the trunk at which lichen community is established. 17 out of 26 taxa are confined to a particular elevation range, while another three are clearly ubiquitous in their distribution. The number of lichen species at breast height is higher than at the base of the trunks. The results were compared with those gathered earlier in an analogous study on the vertical distribution of epiphytic lichens onPinus nigra along an altitudinal gradient from 750 to 1510 m of the same mountain. Comparison suggests that spatial heterogeneity of epiphytic lichens onF. sylvatica is different from the one onP. nigra.
Article
Four commonly used clustering methods (UPGMA, Ward Linkage,Complete Linkage and TWINSPAN) were compared in their abilitytorecognise the structure of three river macroinvertebratesdatasetswhich were pre-determined based on habitat and biologicalcharacteristics or chemical water quality of sampling sites.DCA,NMDS and ANOSIM were applied to the same datasets to providefurther information about data structure, and nonparametrictestswere also undertaken on major chemical variables to justifythepredeterminations. The modified Rand Index was used to measuretheagreement between a particular solution and the pre-determinedclassification. The results showed that Ward Linkage performedbestwhen its use was broadened and used with the CY DissimilarityMeasure, followed by TWINSPAN and Complete Linkage with UPGMAbeingleast successful. There was evidence to suggest that theeffectiveness of some clustering methods (e.g. UPGMA) may varyatdifferent clustering levels, and simulation techniques whichhavebeen used to assess clustering methods could leave somepropertiesof clustering methods unexamined.
Article
The evaluation of air quality is an important topic. It is well known that lichens have a set of characteristics that make them well suited for biomonitoring purposes. Sampling lichen diversity is not as expensive as chemical analysis, allowing a dense sampling grid and reducing the costs. Lichen diversity can be used to identify more disturbed areas, resulting from pollution, land use or ecological variables. In recent years, in order to enable extended use of lichens and to reduce ambiguities, i.e., variations due to unwanted environmental variables, efforts have been made to develop a feasible protocol for lichen sampling for biomonitoring purposes. This work aims at providing the information needed a priori for an air quality assessment study, in the form of a map showing areas where lichen diversity and abundance is lower. This study was done by sampling foliose and fruticulose lichen diversity and frequency, in a region in southwest Portugal (Sines) with large industrial facilities. A long-term study has been underway in the same area since the 1970s using lichens as bioindicators to evaluate air quality. In this work, we used a standard protocol to determine a lichen diversity value (LDV), to be used as an indicator of environmental quality. In order to reduce uncertainty concerning the type of disturbance affecting lichens, sampling sites were restricted using well-defined criteria. Whenever possible, sampling site variables were quantified. This method allowed us to reduce the many sources of variability affecting lichen diversity.
Article
Argues that the problem of pattern and scale is the central problem in ecology, unifying population biology and ecosystems science, and marrying basic and applied ecology. Applied challenges, such as the prediction of the ecological causes and consequences of global climate change, require the interfacing of phenomena that occur on very different scales of space, time, and ecological organization. Systems generally show characteristic variability on a range of spatial, temporal, and organizational scales. The observer imposes a perceptual bias, a filter through which the system is viewed. This has fundamental evolutionary significance, since every organism is an "observer' of the environment, and life history adaptations such as dispersal and dormancy alter the perceptual scales of the species, and the observed variability. The key to prediction and understanding lies in the elucidation of mechanisms underlying observed patterns. Typically, these mechanisms operate at different scales than those on which the patterns are observed; in some cases, the patterns must be understood as emerging from the collective behaviors of large ensembles of smaller scale units. In other cases, the pattern is imposed by larger scale constraints. Examination of such phenomena requires the study of how pattern and variability change with the scale of description, and the development of laws for simplification, aggregation, and scaling. -from Author
Article
What are the most relevant environmental variables influencing the distribution and the species richness of epiphytic lichens in heterogeneous areas of the Mediterranean region? What is the relative importance of substrate- vs. environmental-related variables? How do climatic and disturbance factors interact? The study was carried out in the Liguria region (northwestern Italy). This is a complex region where steep environmental gradients occur over a few kilometres of longitude and latitude. Data on lichen species frequencies, collected on the basis of stratified random sampling, were analyzed using non-metric multidimensional scaling (NMS) and DCA. Indicator Value Analysis (IVA) analysis was used to find indicator species for the environmental predictors. In the survey area, epiphytic lichen distribution depends on both substrate- and environment-related factors. Climatic variables (in particular average yearly temperature and rainfall), anthropogenic pressures (particularly harvesting and atmospheric pollution), bark pH and texture were associated with the main axes of variability in the dataset. Mean annual rainfall is the best predictor for epiphytic lichen richness in the survey area. The particular effects of the Mediterranean region (e.g. the influence of forest fires) and of heterogeneous areas (the variability of diversity in relation to habitat) were pointed out. Several indicator species, closely linked to particular ecological conditions, were found for both substrate-and environment-related variables. The main variables involved seemed to be the same reported for other areas, but their relative importance and their spatial scale of action were in some cases different, probably due to the geomorphological and climatic heterogeneity of the survey area. The significant influence of climatic predictors and disturbance factors on epiphytic lichens was confirmed, suggesting that these organisms may be used successfully to describe ecological trends in natural environments, also providing practical information at ecosystem level.
Article
The influence of environmental variables on epiphytic lichens in Liguria (NW Italy) was examined using two complementary approaches. Firstly, the variability of lichen vegetation in relation to environmental variables was investigated. Secondly, the variability of Lichen Biodiversity (LB) counts, used in biomonitoring studies, was analysed in relation to bioclimatic areas. Geomorphology strongly affects lichen vegetation. The coastal mountain ridge and the Tyrrhenian-Po valley watershed limit the distribution range of three different communities: a Parmelion community with a high frequency of coastal suboceanic species, a Parmelion community rich in oak wood species and the Parmelietum acetabuli association, situated beyond the Po Valley watershed. Substantial differences in the distribution of lichen communities related to a climatic gradient (from humid Mediterranean to dry sub-Mediterranean regions) are not matched by corresponding statistically significant differences in LB counts. More accurate studies are necessary to define homogeneous bioclimatic areas, in which LB values can be compared for biomonitoring purposes.
Article
We detect the response of lichens to air pollution, against the background of other ecological predictors. Abstract We investigated the response of epiphytic lichens to air pollution, against the background of other ecological predictors in a prealpine heterogeneous area, using Non-Parametric Multiplicative Regression (NPMR). The best NPMR model for total lichen diversity according to N environmental predictors at tree level has a cross R 2 ¼ 0.709. It includes 10 variables, belonging to three different subsets of factors: two pollution related factors (distance in meters from the road and from the cement factory); four stand-related (habitat, heat index, LAI and elevation) and four substrate-related factors (inclination, circumference and texture and tree species). Considering separately the effects of each subset on lichen diversity, substrate-and stand-related factors produce good models with similar cross R 2 (0.490 and 0.500, respectively), whereas pollution related factors produce a model with a lower cross R 2 (0.340). Hence, we provide information to investigate the applicability of lichen biomonitoring to complex heterogeneous areas where standardized protocols are not reliable.
Article
In Europe, epiphytic lichens are incorporated in forest diversity monitoring projects in which sampling at the tree level is carried out on 4 grids on the 4 cardinal points (N, S, E, W) of the trunk. Our results, based on the analysis of a dataset referring to six forest sites in NE-Italy and including 264 trees, indicate that a lichen assessment based on sampling at the tree level less than four cardinal points might be effective in estimating species richness across different forest types, showing very high rates of species capture. Similar results were achieved if the reduction of sampling effort is applied to the number of trees sampled within each area. This effect can be explained taking into account the redundant information collected on the same tree. In the framework of forest monitoring programs, the main perspective of our results is related to the possibility of investing saved resources for improving lichen inventories by including in the surveys currently neglected microhabitats. Further studies would be welcome to identify an optimal balance between sampling effort and information gathered, as economic resources are often a constraint to activate and maintain large-scale and long-term monitoring projects.
Article
Abstract. Present discussions on competitive interactions and the occurrence of predictable patterns in species composition – including assembly rules – are likely to benefit from appropriate analyses of the spatial structure in plant communities. We suggest such an analysis when we specifically want to detect scale regions where fine-scale local processes may affect the spatial pattern of species composition. We combine indirect ordination in the form of Detrended Correspondence Analysis (DCA) and geostatistics in the form of variography. The species abundance data in the sampled quadrats are summarized as positions on the axes in the ordination. Each axis is used as a regionalized variable in the variography to obtain the spatial dependence of the quadrats. The spatial pattern found will suggest the relevant scale region in which to perform an analysis of species associations. A significant spatial dependence (the ‘range’ in geostatistical jargon) will define the size of a sampling plot that will minimize both the problem of being too small and thus having the risk of oversampling of e.g. clonal individuals and of being too large which will risk including individuals that do not interact. We also suggest that plots are spaced at least a ‘range’ apart to insure spatial and statistical independence. Comparisons of species compositions in such plots will reveal any positive or negative associations between species on a scale where these should reflect species-species interactions. To illustrate the method it is applied to three different data sets from two different plant communities.
Article
To a first approximation, the distribution of biodiversity across the Earth can be described in terms of a relatively small number of broad-scale spatial patterns. Although these patterns are increasingly well documented, understanding why they exist constitutes one of the most significant intellectual challenges to ecologists and biogeographers. Theory is, however, developing rapidly, improving in its internal consistency, and more readily subjected to empirical challenge.
Article
Coastal marine ecology is, quite properly, increasingly focussed on experimental tests of hypotheses about processes. These are, however, done to explain observations and patterns. It is therefore appropriate to be able to publish quantitative observations to provide the context and basis for studying mechanisms and processes. Ecologists are concerned about very different types of observations. Some areas of study are still totally dependent on observational, descriptive evidence; some depend on mensurative tests of hypotheses about patterns. Tests of hypotheses about patterns are also needed to validate casual or qualitative observations. Guide-lines for what constitutes appropriate or publishable ecological descriptions are discussed here. These recognize the experimental, hypothesis-testing nature of many descriptive studies and consider the relevance of sound logic and experimental design in the planning, collection and interpretation of observations.
Article
A study was conducted to determine the joint effect of gaseous atmospheric pollutants and trace elements on epiphytic lichens. We used our data to test the hypothesis that lichens are generally insensitive to toxic effects of trace elements, and can therefore be used as accumulator organisms to estimate concentrations of these elements in the environment. In a field study in The Netherlands the abundance of epiphytic lichen species was estimated, and their supporting bark was collected. Concentrations of a range of trace elements were determined in the bark, and concentrations of atmospheric trace gases were estimated at the sites of collection. Multivariate statistics were used to determine the relation between the abundance of the species and pollutant concentrations. Atmospheric SO2 and NO2 appeared to be the most important factors determining lichen biodiversity. Nearly all species were sensitive to these compounds. The effect of the other trace elements was very slight; only Sb had a significantly negative effect on the abundance of a few species. It is concluded that lichens can safely be used as accumulator organisms in pollution studies, provided that concentration in lichen thalli reflect atmospheric concentrations.