Abstract
In spite of the great popularity of Ellenberg’s Indicator Values (EIVs) in plant ecology, animal ecologists seldom use EIVs to address ecological questions. In this study we used EIVs to test their potential usefulness for the prediction of suitable habitat for pre-diapause larvae of the endangered butterfly species Euphydryas aurinia. Nine transects crossing grasslands in SW Poland with abundant populations of E. aurinia were designed. We sampled 76 vegetation plots along the transects. In addition, the presence of the larval webs of E. aurinia in sampled plots was also recorded. We then calculated the mean community EIVs of light, nitrogen, soil reaction, moisture and temperature for each sample plots. Generalized linear mixed-effects models (GLMMs) were used to assess which factors determine the local occurrence of larval webs of E. aurinia. We found the larval webs only in 12 plots, while the host plant was present in 39 of the examined plots. The presence of the host plant was the most important predictor in both models including all plots or including only plots with host plants. The other significant predictor was the mean EIV of light, and its importance increased in models considering all plots. We attributed the importance of the EIV of light to the site openness and density of the vegetation layer. A positive relationship between this predictor and the presence of larval webs indicates that sites with looser vegetation, a lower contribution of shrubs and tall herbs and better penetration of photosynthetically active radiation to lower vegetation layers are preferred by E. aurinia for oviposition. Moreover, the significance of EIV of light may be linked with management practices. Many light-demanding species decline after cessation of mowing as a result of litter accumulation and the dominance of tall herbs. An absence of light-demanding species decreases the community’s mean EIV of light and thus indicates the influence of meadow abandonment.
Highlights
Since its introduction in the mid-70s, Ellenberg’s Indicator Values (EIVs) have become an extensively used tool in ecological studies
The key importance of the presence of S. pratensis for the occurrence of larval webs of E. aurinia was confirmed by the results of the Generalized linear mixed-effects models (GLMMs)
The abundance of the S. pratensis was the most important variable explaining the presence of larval webs, followed by “light” and “temperature” factors (Fig 1)
Summary
Since its introduction in the mid-70s, Ellenberg’s Indicator Values (EIVs) have become an extensively used tool in ecological studies It is especially popular in plant ecology, where EIVs are used to characterize environmental conditions when detailed site-specific measurements are absent. Some authors have claimed that the interpretation of analyses based on EIVs may be biased due to circular reasoning [10], weak correlations with field measurements [11,12,13] or inter-correlations between different EIVs [14] In spite of these reservations, EIVs have enjoyed great popularity and are generally believed to be an important tool in applied plant ecology [15]. EIVs are sometimes used to characterize the ecological properties of habitats of studied animal assemblages, e.g. ants [22] or molluscs [23]. Some of these studies have highlighted the advantages of the utilization of EIVs in the study of animal autoecology, but this approach is still underexplored and needs more detailed examination
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
