Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Fishing Down Marine Food Webs
19983.4k citationsDaniel Pauly, Rainer Froese et al.profile →
This map shows the geographic impact of Daniel Pauly'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 Daniel Pauly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Pauly more than expected).
This network shows the impact of papers produced by Daniel Pauly. 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 Daniel Pauly. The network helps show where Daniel Pauly may publish in the future.
Co-authorship network of co-authors of Daniel Pauly
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Pauly.
A scholar is included among the top collaborators of Daniel Pauly 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 Daniel Pauly. Daniel Pauly is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Harper, Sarah, et al.. (2021). Fisheries catches for the Bay of Bengal Large Marine Ecosystem since 1950. AquaDocs (United Nations Educational, Scientific and Cultural Organization).1 indexed citations
Kleisner, Kristin M., et al.. (2015). Australia: reconstructing estimates of total fisheries removals 1950-2010. eCite Digital Repository (University of Tasmania).1 indexed citations
Jessup, Mariell, Barry Greenberg, Donna Mancini, et al.. (2011). Calcium Upregulation by Percutaneous Administration of Gene Therapy in Cardiac Disease (CUPID). Circulation. 124(3). 304–313.548 indexed citations breakdown →
12.
Cheung, William W. L., Vicky W. Y. Lam, Jorge L. Sarmiento, et al.. (2009). Projecting global marine biodiversity impacts under climate change scenarios. Fish and Fisheries. 10(3). 235–251.1118 indexed citations breakdown →
Jarre, Astrid, et al.. (1992). A user's manual for MAXIMS (version 1.0) a computer program for estimating the food consumption of fishes from diel stomach contents data and population parameters.. Helmholtz-Zentrum für Polar-und Meeresforschung (Alfred-Wegener-Institut).5 indexed citations
16.
Pauly, Daniel. (1992). The Peruvian anchoveta, Charles Darwin and us. AquaDocs (United Nations Educational, Scientific and Cultural Organization). 15(4). 14–15.1 indexed citations
17.
Jarre, Astrid, Peter M. Muck, & Daniel Pauly. (1991). Two approaches for modelling fish stock interactions in the Peruvian upwelling ecosystem. Helmholtz-Zentrum für Polar-und Meeresforschung (Alfred-Wegener-Institut).53 indexed citations
18.
Pauly, Daniel, et al.. (1986). Kuwait's finfish catch three times more shrimp than its trawlers. RePEc: Research Papers in Economics. 9(1). 11–12.2 indexed citations
19.
Pauly, Daniel. (1986). On improving operation and use of the elefan programs. part 3, correcting length-frequency data for the effects of gear selection and/or incomplete recruitment. RePEc: Research Papers in Economics. 4(2). 11–13.6 indexed citations
20.
Pauly, Daniel, et al.. (1981). An annotated bibliography of slipmouths (Pisces : Leiognathidae). RePEc: Research Papers in Economics.2 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.