Vera Zizka

2.3k total citations · 1 hit paper
26 papers, 1.1k citations indexed

About

Vera Zizka is a scholar working on Ecology, Molecular Biology and Ecological Modeling. According to data from OpenAlex, Vera Zizka has authored 26 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Ecology, 18 papers in Molecular Biology and 8 papers in Ecological Modeling. Recurrent topics in Vera Zizka's work include Environmental DNA in Biodiversity Studies (21 papers), Microbial Community Ecology and Physiology (11 papers) and Species Distribution and Climate Change (8 papers). Vera Zizka is often cited by papers focused on Environmental DNA in Biodiversity Studies (21 papers), Microbial Community Ecology and Physiology (11 papers) and Species Distribution and Climate Change (8 papers). Vera Zizka collaborates with scholars based in Germany, Italy and Switzerland. Vera Zizka's co-authors include Florian Leese, Alexander Zizka, Camila Duarte Ritter, María Ariza, Andrei Herdean, Ruud Scharn, Sten Svantesson, Tobias Andermann, Daniele Silvestro and Niklas Wengström and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Philosophical Transactions of the Royal Society B Biological Sciences.

In The Last Decade

Vera Zizka

26 papers receiving 1.1k citations

Hit Papers

CoordinateCleaner: Standardized cleaning of occurrence re... 2019 2026 2021 2023 2019 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Vera Zizka Germany 13 628 478 356 346 333 26 1.1k
Jun Ying Lim Singapore 15 469 0.7× 178 0.4× 254 0.7× 342 1.0× 307 0.9× 27 1.0k
Ruud Scharn Sweden 8 306 0.5× 495 1.0× 519 1.5× 626 1.8× 170 0.5× 10 1.3k
Sten Svantesson Sweden 6 259 0.4× 373 0.8× 303 0.9× 348 1.0× 154 0.5× 14 877
María Ariza Norway 6 287 0.5× 411 0.9× 349 1.0× 365 1.1× 94 0.3× 7 870
Valeria Di Cola Argentina 8 461 0.7× 673 1.4× 309 0.9× 317 0.9× 94 0.3× 16 1.0k
Josué A. R. Azevedo Brazil 9 297 0.5× 498 1.0× 438 1.2× 458 1.3× 91 0.3× 21 1.0k
Gleb Tikhonov Finland 11 693 1.1× 531 1.1× 569 1.6× 335 1.0× 98 0.3× 19 1.4k
Julie A. Lee‐Yaw Canada 15 552 0.9× 644 1.3× 473 1.3× 473 1.4× 192 0.6× 23 1.4k
Kathrin Theißinger Germany 18 736 1.2× 276 0.6× 273 0.8× 222 0.6× 142 0.4× 61 1.2k
Jordan B. Bemmels United States 11 359 0.6× 494 1.0× 473 1.3× 316 0.9× 165 0.5× 17 1.2k

Countries citing papers authored by Vera Zizka

Since Specialization
Citations

This map shows the geographic impact of Vera Zizka's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Vera Zizka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vera Zizka more than expected).

Fields of papers citing papers by Vera Zizka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vera Zizka. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Vera Zizka. The network helps show where Vera Zizka may publish in the future.

Co-authorship network of co-authors of Vera Zizka

This figure shows the co-authorship network connecting the top 25 collaborators of Vera Zizka. A scholar is included among the top collaborators of Vera Zizka based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Vera Zizka. Vera Zizka is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Scherber, Christoph, et al.. (2025). The clockwork of insect activity: Advancing ecological understanding through automation. Journal of Animal Ecology. 94(4). 597–610. 1 indexed citations
2.
3.
Zizka, Vera, et al.. (2024). Three steps towards comparability and standardization among molecular methods for characterizing insect communities. Philosophical Transactions of the Royal Society B Biological Sciences. 379(1904). 20230118–20230118. 7 indexed citations
5.
Laini, Alex, Rachel Stubbington, Arne J. Beermann, et al.. (2023). Dissecting biodiversity: assessing the taxonomic, functional and phylogenetic structure of an insect metacommunity in a river network using morphological and metabarcoding data. The European Zoological Journal. 90(1). 320–332. 4 indexed citations
6.
Schneider, Florian D., Nikita Bakanov, Carsten A. Brühl, et al.. (2022). Improving insect conservation management through insect monitoring and stakeholder involvement. Biodiversity and Conservation. 32(2). 691–713. 13 indexed citations
7.
Zizka, Vera, et al.. (2022). Repeated subsamples during DNA extraction reveal increased diversity estimates in DNA metabarcoding of Malaise traps. Ecology and Evolution. 12(11). e9502–e9502. 8 indexed citations
8.
Beermann, Arne J., Dominik Buchner, Vasco Elbrecht, et al.. (2021). Improved freshwater macroinvertebrate detection from environmental DNA through minimized nontarget amplification. Zenodo (CERN European Organization for Nuclear Research). 4. 1 indexed citations
9.
Elbrecht, Vasco, Sarah J. Bourlat, Thomas Hörren, et al.. (2021). Pooling size sorted Malaise trap fractions to maximize taxon recovery with metabarcoding. PeerJ. 9. e12177–e12177. 18 indexed citations
10.
Zizka, Vera, Martina Weiss, & Florian Leese. (2020). Can metabarcoding resolve intraspecific genetic diversity changes to environmental stressors? A test case using river macrozoobenthos. SHILAP Revista de lepidopterología. 4. 23 indexed citations
11.
Laini, Alex, Arne J. Beermann, Rossano Bolpagni, et al.. (2020). Exploring the potential of metabarcoding to disentangle macroinvertebrate community dynamics in intermittent streams. SHILAP Revista de lepidopterología. 4. 12 indexed citations
12.
Zizka, Vera, Matthias F. Geiger, & Florian Leese. (2020). DNA metabarcoding of stream invertebrates reveals spatio-temporal variation but consistent status class assessments in a natural and urban river. Ecological Indicators. 115. 106383–106383. 25 indexed citations
13.
Leese, Florian, et al.. (2020). Improved freshwater macroinvertebrate detection from environmental DNA through minimized nontarget amplification. Environmental DNA. 3(1). 261–276. 85 indexed citations
14.
Beermann, Arne J., et al.. (2020). DNA metabarcoding improves the detection of multiple stressor responses of stream invertebrates to increased salinity, fine sediment deposition and reduced flow velocity. The Science of The Total Environment. 750. 141969–141969. 16 indexed citations
15.
Zizka, Vera, Vasco Elbrecht, Jan‐Niklas Macher, & Florian Leese. (2019). Assessing the influence of sample tagging and library preparation on DNA metabarcoding. Molecular Ecology Resources. 19(4). 893–899. 39 indexed citations
16.
Zizka, Vera, et al.. (2018). DNA metabarcoding from sample fixative as a quick and voucher-preserving biodiversity assessment method. Genome. 62(3). 122–136. 62 indexed citations
18.
Beermann, Arne J., Vera Zizka, Vasco Elbrecht, Viktor Baranov, & Florian Leese. (2018). DNA metabarcoding reveals the complex and hidden responses of chironomids to multiple stressors. Environmental Sciences Europe. 30(1). 59 indexed citations
19.
Macher, Jan‐Niklas, Vera Zizka, Alexander Weigand, & Florian Leese. (2017). A simple centrifugation protocol for metagenomic studies increases mitochondrial DNA yield by two orders of magnitude. Methods in Ecology and Evolution. 9(4). 1070–1074. 9 indexed citations
20.
Lammers, Fritjof, et al.. (2017). Screening for the ancient polar bear mitochondrial genome reveals low integration of mitochondrial pseudogenes ( numts ) in bears. Mitochondrial DNA Part B. 2(1). 251–254. 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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