Miguel Lurgi

3.4k citations
52 papers · 1.8k indexed · 1 hit paper · h-index 18

Miguel Lurgi

50 papers receiving 1.7k citations

Hit Papers

Navigating the complexity of ecological stability4312016202620192022100200300400

Peers

Miguel Lurgi
Comparison fields: 5 of 119
  • Ecological Modeling 351
  • Nature and Landscape Conservation 641
  • Ecology 839
  • Ecology, Evolution, Behavior and Systematics 478
  • Global and Planetary Change 501
Replace Ricardo Dobrovolski with:
Ricardo Dobrovolski Brazil
M. J. Crawley United Kingdom
Danny A. P. Hooftman United Kingdom
Keith R. Hayes Australia
Chris Yesson United Kingdom
Chun‐Huo Chiu Taiwan
Scott D. Foster Australia
Christian Damgaard Denmark
Katrin Meyer Germany
Chang Xuan Mao United States
Miguel Lurgi relative to Ricardo Dobrovolski Brazil Ricardo Dobrovolski's profile →
Citations per field
00.5×
Ricardo Dobrovolski · 1×
Citations per year

Countries citing papers authored by Miguel Lurgi

Since Specialization
Citations

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

Fields of papers citing papers by Miguel Lurgi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Miguel Lurgi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Miguel Lurgi Line = papers co-authored together Miguel Lurgi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20260
2 20251
3 20251
4 20256
5 20241
6 20245
7 20239
8 202310
9 202116
10 202122
11 20212
12 202013
13 202011
14 201916
15 20197
16 201934
17 201946
18 201994
19 201835
20 2013311

About Miguel Lurgi

Miguel Lurgi is a scholar working on Ecological Modeling, Nature and Landscape Conservation and Ecology, Evolution, Behavior and Systematics, having authored 52 papers that have together received 1.8k indexed citations. Recurring topics across this work include Ecology and Vegetation Dynamics Studies (17 papers), Plant and animal studies (15 papers), Species Distribution and Climate Change (13 papers), Wildlife Ecology and Conservation (12 papers), Evolutionary Game Theory and Cooperation (8 papers), Animal Ecology and Behavior Studies (6 papers), Complex Network Analysis Techniques (4 papers) and Coral and Marine Ecosystems Studies (3 papers). The work is most often cited by research in Ecological Modeling (351 citations), Nature and Landscape Conservation (641 citations) and Ecology (839 citations). Miguel Lurgi has collaborated with scholars based in United Kingdom, France and Australia. Frequent co-authors include José M. Montoya, Bernat Claramunt López, Kevin Healy, Andrew L. Jackson, Owen L. Petchey, Nessa E. O’Connor, Ian Donohue, Damien A. Fordham, Núria Galiana and Deirdre McClean. Their work appears in journals such as Nature Communications, PLoS ONE and Ecology.

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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