Ellenberg-type indicator values for the Czech flora

Chytrý, Milan; Tichý, Lubomír; Dřevojan, Pavel; Sádlo, Jiřı́; Zelený, David

doi:10.23855/preslia.2018.083

Cited by 136 publications

(134 citation statements)

References 32 publications

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“…Ellenberg indicator values consist of a simple ordinal classification (0–9) of plants according to the position of their realised ecological niches along an environmental gradient. For details on the principles and use of the method see Chytrý, Tichý, Dřevojan, Sádlo, and Zelený ().…”

Section: Methodsmentioning

confidence: 99%

Does predator abundance influence species diversity of equilibrium macroinvertebrate assemblages in spring fens?

et al. 2020

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Predation may significantly control number and density of coexisting species. The effects of predation on species diversity have traditionally been tested in experiments and theoretical models of simple trophic systems. In complex natural ecosystems, however, disentangling multiple sources of variation is difficult. In groundwater‐fed environments, a significant effect of predation can be expected due to the relatively stable environmental conditions; however, it has never been properly examined. We analysed species diversity and total abundance of macroinvertebrate assemblages in 48 Western Carpathian spring fens, separately for whole sites and mesohabitat/season, and partitioned the effects of predation intensity from those of environmental variables in robust models using a bootstrapping technique. We verified our results by accounting for taxa resistant to predation. The assumption that predation‐mediated coexistence of species is the main mechanism responsible for the relatively species‐rich assemblages in the Western Carpathian spring fens was not supported. However, predation may significantly influence abundance of non‐predatory species and, under some conditions, it may contribute to explaining patterns in species diversity. The effect of predation did not differ between the mesohabitats with different stability. However, we found higher environmental control in spring and a stronger effect of predators in autumn, which suggests that different mechanisms influence fen assemblages in different seasons. Our study provides a new robust approach how to test the effect of predation on natural macroinvertebrate assemblages. The importance of predation was lower than expected in equilibrium assemblages but it may vary in time.

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Section: Methodsmentioning

confidence: 99%

Does predator abundance influence species diversity of equilibrium macroinvertebrate assemblages in spring fens?

et al. 2020

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“…For the analysis here, as sample attributes I selected a subset of 11 environmental variables measured or estimated for each plot in the field (details in Zelený & Chytrý, ). As species attributes, I used the Czech indicator values for light, temperature, moisture, reaction and nutrients, which are Ellenberg‐type species indicator values recalibrated for the territory of the Czech Republic (Chytrý, Tichý, Dřevojan, Sádlo, & Zelený, ). As the species composition data, I included only herbs sampled in the forest understorey, since indicator values for light are defined only for herbs and juveniles of woody species.…”

Section: Theory and Methodsmentioning

confidence: 99%

Which results of the standard test for community‐weighted mean approach are too optimistic?

Zelený

2018

J Vegetation Science

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Aims The community‐weighted mean (CWM) approach is used to analyse the relationship between species attributes (traits, Ellenberg‐type indicator values) and sample attributes (environmental variables, richness) via the community matrix. It has recently been shown to suffer from inflated Type I error rate if tested by a standard test and the results of many published studies are probably affected. I review the current knowledge about this problem, and clarify which studies are likely affected and by how much. Methods I suggest classifying hypotheses commonly tested by CWM approach into three categories, which differ in the formulation of the null hypothesis. I use simulated and real data to show how the Type I error rate of the standard test is affected by data characteristics. Results The CWM approach with the standard test returns a correct Type I error rate for hypotheses assuming a link between species attributes and composition (Category A). However, for hypotheses assuming a link between composition and sample attributes (Category B) or not assuming any link (Category C), the standard test is inflated, and alternative tests are needed to control for this. The inflation of standard tests for Category C is negatively related to the compositional β‐diversity, and positively to the strength of the composition–sample attributes relationship and data set sample size. These results apply to CWM analyses with extrinsic sample attributes (not derived from the compositional matrix). CWM analysis with intrinsic sample attributes (derived from the composition, such as species richness) is a case of spurious correlation and can be tested using a column‐based (modified) permutation test. Conclusions The concept of three hypothesis categories offers a simple tool to evaluate which hypothesis has been tested and whether the results have correct or inflated Type I error rate. In the case of inflated results, the level of inflation can be estimated from the data characteristics.

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“…Q. rubra was not classified by Ellenberg Indicator Values (Ellenberg & Leuschner, 2010) nor by indicators in PLANTATT (Hill, Preston, & Roy, 2004). However, it was classified by Ellenberg‐type indicator values for the Czech flora (Chytrý et al, 2018) in terms of soil reaction as 6, that is, occurring on moderately acid to slightly basic soils, with a neutral optimum. For soil nutrients it was classified as 5, that is, occurring on moderately nutrient‐rich sites, and less frequently on poor and rich sites, and for soil moisture also as 5, that is, occurring on moist soils, focused on soils of average moisture, absent from wet soils and soils that frequently dry out.…”

Section: Habitatmentioning

confidence: 99%

Biological Flora of the British Isles:Quercus rubra

et al. 2020

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1. This account presents information on all aspects of the biology of Quercus rubra L.(Red Oak, Northern Red Oak; syn. Q. borealis, Q. maxima) that are relevant to understanding its ecological characteristics and behaviour. The main topics are presented within the standard framework of the Biological Flora of the British Isles: distribution; habitat; communities; responses to biotic factors; responses to environment; structure and physiology; phenology; floral and seed characters; herbivores and disease; history; and conservation.2. Quercus rubra is a large deciduous tree native to eastern North America. In its native range this species is one of the most important mid-successional tree species.Since the 18th century Q. rubra has been introduced into forest management in Europe and elsewhere. Currently, Q. rubra is a naturalized species in 23 countries.

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Ellenberg-type indicator values for the Czech flora

Cited by 136 publications

References 32 publications

Does predator abundance influence species diversity of equilibrium macroinvertebrate assemblages in spring fens?

Does predator abundance influence species diversity of equilibrium macroinvertebrate assemblages in spring fens?

Which results of the standard test for community‐weighted mean approach are too optimistic?

Biological Flora of the British Isles:Quercus rubra

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