Ulf Hohmann

1.4k total citations · 1 hit paper
21 papers, 1.0k citations indexed

About

Ulf Hohmann is a scholar working on Ecology, Genetics and Small Animals. According to data from OpenAlex, Ulf Hohmann has authored 21 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Ecology, 10 papers in Genetics and 4 papers in Small Animals. Recurrent topics in Ulf Hohmann's work include Wildlife Ecology and Conservation (18 papers), Genetic diversity and population structure (9 papers) and Animal Ecology and Behavior Studies (4 papers). Ulf Hohmann is often cited by papers focused on Wildlife Ecology and Conservation (18 papers), Genetic diversity and population structure (9 papers) and Animal Ecology and Behavior Studies (4 papers). Ulf Hohmann collaborates with scholars based in Germany, Luxembourg and Slovakia. Ulf Hohmann's co-authors include Cornelia Ebert, Tomasz Podgórski, Giovanna Massei, Carlos Fonseca, Dragan Gačić, Boštjan Pokorny, Nikolay Markov, Sandra Cellina, Andrea Monaco and Carme Rosell and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Wildlife Management.

In The Last Decade

Ulf Hohmann

21 papers receiving 993 citations

Hit Papers

Wild boar populations up, numbers of hunters down? A revi... 2014 2026 2018 2022 2014 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ulf Hohmann Germany 13 675 240 231 180 126 21 1.0k
Nikolay Markov Russia 13 523 0.8× 287 1.2× 180 0.8× 164 0.9× 116 0.9× 31 945
Andrea Monaco Italy 15 793 1.2× 227 0.9× 317 1.4× 239 1.3× 178 1.4× 26 1.2k
Carme Rosell Spain 10 618 0.9× 155 0.6× 227 1.0× 175 1.0× 109 0.9× 20 976
Lisa M. Lyren United States 18 729 1.1× 290 1.2× 127 0.5× 150 0.8× 81 0.6× 32 1.1k
Jiřı́ Kamler Czechia 14 616 0.9× 163 0.7× 203 0.9× 195 1.1× 104 0.8× 50 1.0k
Sandra Cellina United Kingdom 3 500 0.7× 420 1.8× 164 0.7× 147 0.8× 141 1.1× 3 941
Kenneth A. Logan United States 16 1.0k 1.5× 302 1.3× 190 0.8× 106 0.6× 128 1.0× 28 1.3k
Scott E. Henke United States 19 575 0.9× 151 0.6× 190 0.8× 150 0.8× 185 1.5× 92 1.2k
T. Winston Vickers United States 23 969 1.4× 321 1.3× 143 0.6× 125 0.7× 140 1.1× 46 1.4k
Nikica Šprem Croatia 18 821 1.2× 469 2.0× 219 0.9× 176 1.0× 142 1.1× 116 1.5k

Countries citing papers authored by Ulf Hohmann

Since Specialization
Citations

This map shows the geographic impact of Ulf Hohmann'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 Ulf Hohmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ulf Hohmann more than expected).

Fields of papers citing papers by Ulf Hohmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ulf Hohmann. 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 Ulf Hohmann. The network helps show where Ulf Hohmann may publish in the future.

Co-authorship network of co-authors of Ulf Hohmann

This figure shows the co-authorship network connecting the top 25 collaborators of Ulf Hohmann. A scholar is included among the top collaborators of Ulf Hohmann 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 Ulf Hohmann. Ulf Hohmann 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.
Port, Markus, et al.. (2024). Status assessment of a recently reintroduced eurasian lynx (Lynx lynx) population in the Palatinate Forest, South-West Germany. European Journal of Wildlife Research. 70(3). 2 indexed citations
2.
Dupont, Pierre, Richard Bischof, Cyril Milleret, et al.. (2023). An evaluation of spatial capture‐recapture models applied to ungulate non‐invasive genetic sampling data. Journal of Wildlife Management. 87(3). 3 indexed citations
4.
Ebert, Cornelia, et al.. (2021). Estimating red deer (Cervus elaphus) population size based on non-invasive genetic sampling. European Journal of Wildlife Research. 67(2). 11 indexed citations
5.
Probst, Carolina, Jörn Gethmann, Ulf Hohmann, et al.. (2020). Zersetzungsstadien bei Wildschweinkadavern - und wie die Liegezeit geschätzt werden kann. 27(2). 85–94. 1 indexed citations
6.
Hochkirch, Axel, Mike Heddergott, Christoph Schulze, et al.. (2015). Historical Invasion Records Can Be Misleading: Genetic Evidence for Multiple Introductions of Invasive Raccoons (Procyon lotor) in Germany. PLoS ONE. 10(5). e0125441–e0125441. 52 indexed citations
7.
Sullivan, Martin J. P., José Guerrero‐Casado, Mike Heddergott, et al.. (2015). Assessing and predicting the spread of non-native raccoons in Germany using hunting bag data and dispersal weighted models. Biological Invasions. 18(1). 57–71. 36 indexed citations
8.
Massei, Giovanna, Jonas Kindberg, Alain Licoppe, et al.. (2014). Wild boar populations up, numbers of hunters down? A review of trends and implications for Europe. Pest Management Science. 71(4). 492–500. 561 indexed citations breakdown →
9.
Frantz, Alain C., Mike Heddergott, Johannes Lang, et al.. (2013). Limited mitochondrial DNA diversity is indicative of a small number of founders of the German raccoon (Procyon lotor) population. European Journal of Wildlife Research. 59(5). 665–674. 26 indexed citations
10.
Ebert, Cornelia, et al.. (2012). Estimating wild boar Sus scrofa population size using faecal DNA and capture‐recapture modelling. Wildlife Biology. 18(2). 142–152. 44 indexed citations
11.
Ebert, Cornelia, et al.. (2012). Non-invasive genetic approaches for estimation of ungulate population size: a study on roe deer (Capreolus capreolus) based on faeces. SHILAP Revista de lepidopterología. 35(2). 267–275. 23 indexed citations
12.
Schindler, Stefan, et al.. (2012). Territoriality and Habitat Use of Common Buzzards (Buteo buteo) During Late Autumn in Northern Germany. Journal of Raptor Research. 46(2). 149–157. 16 indexed citations
13.
Schulz, Holger K., et al.. (2012). Comparison of established methods for quantifying genotyping error rates in wildlife forensics. Conservation Genetics Resources. 5(1). 287–292. 5 indexed citations
14.
Franke, Uwe, et al.. (2012). Aerial ungulate surveys with a combination of infrared and high–resolution natural colour images. SHILAP Revista de lepidopterología. 35(2). 285–293. 42 indexed citations
15.
Ebert, Cornelia, Felix Knauer, Ilse Storch, & Ulf Hohmann. (2010). Individual heterogeneity as a pitfall in population estimates based on non‐invasive genetic sampling: a review and recommendations. Wildlife Biology. 16(3). 225–240. 38 indexed citations
17.
Ebert, Cornelia, et al.. (2009). Can hair traps sample wild boar (Sus scrofa) randomly for the purpose of non-invasive population estimation?. European Journal of Wildlife Research. 56(4). 583–590. 23 indexed citations
18.
Hohmann, Ulf, et al.. (2005). Investigations on the radiocaesium contamination of wild boar (Sus scrofa) meat in Rhineland-Palatinate: a stomach content analysis. European Journal of Wildlife Research. 51(4). 263–270. 43 indexed citations
19.
Fickel, Joerns & Ulf Hohmann. (2005). A methodological approach for non-invasive sampling for population size estimates in wild boars (Sus scrofa). European Journal of Wildlife Research. 52(1). 28–33. 31 indexed citations
20.
Hohmann, Ulf, et al.. (2000). Home range size of adult raccoons (Procyon lotor) in Germany. Biodiversity Heritage Library (Smithsonian Institution). 11 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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