10 research outputs found
Handbook of Good Practices - How to Bring Entrepreneurial Spirit at Your University?
info:eu-repo/semantics/publishedVersio
The classification of some plants subjected to disturbance factors (grazing and cutting) based on ecological strategies in Turkey
WOS: 000427112700010The effect of disturbance factors such as grazing and cutting were investigated in some plants in central Black Sea Region of Turkey using Grime's CSR strategies and Ellenberg's indicator values (EIVs). Grime's CSR strategies were also determined by Pierce et al.'s (Funct Ecol 27:1002-1010, 2013) scheme because there were some inconsistencies between Grime's and Pierce et al.'s schemes. Secondary strategies in the study area found to be dominant and the dominance of secondary strategies are consistent with "intermediate disturbance hypothesis". All the EIVs were found to be significantly different in grazed vs non-ungrazed and cutted vs uncutted areas. PCA diagram showed that ungrazed and cutted areas are associated with EIVR, while grazed and uncutted plots are associated with EIVL, EIVM, EIVN and EIVT.Amasya UniversityAmasya University [FMB-BAP-14-067]; Amasya University Research FundAmasya UniversityThis study is supported by Amasya University Project number (FMB-BAP-14-067). Thank you Amasya University Research Fund for their support
Benchmarking plant diversity of Palaearctic grasslands and other open habitats
Aims: Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location: Palaearctic biogeographic realm. Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m2 and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions: The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology