Mark N. Maunder

10.3k total citations · 3 hit papers
153 papers, 7.9k citations indexed

About

Mark N. Maunder is a scholar working on Global and Planetary Change, Nature and Landscape Conservation and Ecology. According to data from OpenAlex, Mark N. Maunder has authored 153 papers receiving a total of 7.9k indexed citations (citations by other indexed papers that have themselves been cited), including 123 papers in Global and Planetary Change, 94 papers in Nature and Landscape Conservation and 35 papers in Ecology. Recurrent topics in Mark N. Maunder's work include Marine and fisheries research (123 papers), Fish Ecology and Management Studies (92 papers) and Marine Bivalve and Aquaculture Studies (66 papers). Mark N. Maunder is often cited by papers focused on Marine and fisheries research (123 papers), Fish Ecology and Management Studies (92 papers) and Marine Bivalve and Aquaculture Studies (66 papers). Mark N. Maunder collaborates with scholars based in United States, Japan and Taiwan. Mark N. Maunder's co-authors include André E. Punt, John Sibert, Kevin R. Piner, James N. Ianelli, Anders Nielsen, Árni Magnússon, Hans J. Skaug, David Fournier, Pierre Kleiber and John Hampton and has published in prestigious journals such as Science, PLoS ONE and Biological Conservation.

In The Last Decade

Mark N. Maunder

149 papers receiving 7.4k citations

Hit Papers

align trajectories

What are hit papers?

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.

AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models

2011 1.5k citations David Fournier, Hans J. Skaug et al. Optimization methods & software profile →
Standardizing catch and effort data: a review of recent approaches

2004 1.1k citations Mark N. Maunder et al. Fisheries Research profile →
A review of integrated analysis in fisheries stock assessment

2012 380 citations Mark N. Maunder et al. Fisheries Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mark N. Maunder United States	41	5.4k	4.3k	3.1k	836	829	153	7.9k
Mikko Heino Norway	49	5.4k 1.0×	5.1k 1.2×	3.5k 1.1×	1.6k 1.9×	1.4k 1.7×	178	9.1k
John Sibert United States	28	3.0k 0.5×	2.2k 0.5×	2.3k 0.8×	496 0.6×	448 0.5×	55	4.8k
Emili García‐Berthou Spain	49	1.8k 0.3×	5.9k 1.4×	5.2k 1.7×	1.2k 1.5×	2.5k 3.1×	172	9.7k
David Mouillot France	42	2.2k 0.4×	3.0k 0.7×	3.8k 1.2×	1.7k 2.1×	383 0.5×	82	6.8k
Les Kaufman United States	42	2.1k 0.4×	1.6k 0.4×	3.9k 1.3×	393 0.5×	1.1k 1.3×	135	6.3k
Russell B. Millar New Zealand	35	3.5k 0.6×	2.6k 0.6×	2.1k 0.7×	271 0.3×	806 1.0×	160	5.1k
Todd A. Crowl United States	34	907 0.2×	2.8k 0.6×	3.2k 1.0×	671 0.8×	561 0.7×	82	4.8k
M. Julian Caley Australia	41	2.8k 0.5×	1.6k 0.4×	4.1k 1.3×	806 1.0×	278 0.3×	122	6.0k
Kai Lorenzen United States	39	3.3k 0.6×	2.9k 0.7×	2.4k 0.8×	329 0.4×	2.1k 2.6×	144	6.6k
Jonathan Baillie United Kingdom	28	1.9k 0.4×	2.6k 0.6×	3.6k 1.2×	946 1.1×	305 0.4×	67	6.4k

Countries citing papers authored by Mark N. Maunder

Since Specialization

Citations

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

Fields of papers citing papers by Mark N. Maunder

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark N. Maunder. 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 Mark N. Maunder. The network helps show where Mark N. Maunder may publish in the future.

Co-authorship network of co-authors of Mark N. Maunder

This figure shows the co-authorship network connecting the top 25 collaborators of Mark N. Maunder. A scholar is included among the top collaborators of Mark N. Maunder 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 Mark N. Maunder. Mark N. Maunder is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Minte‐Vera, Carolina V., Mark N. Maunder, Alexandre Aires‐da‐Silva, et al.. (2024). The use of conceptual models to structure stock assessments: A tool for collaboration and for “modelling what to model”. Fisheries Research. 279. 107135–107135. 5 indexed citations

Lennert‐Cody, Cleridy E., et al.. (2024). Within-well patterns in bigeye tuna catch composition and implications for purse-seine port-sampling and catch estimation for the Eastern Pacific Ocean. Fisheries Research. 277. 107079–107079.

Maunder, Mark N.. (2024). Towards a comprehensive framework for providing management advice from statistical inference using population dynamics models. Ecological Modelling. 498. 110836–110836. 2 indexed citations

Hoyle, Simon, Robert A. Campbell, Arnaud Grüss, et al.. (2023). Catch per unit effort modelling for stock assessment: A summary of good practices. Fisheries Research. 269. 106860–106860. 38 indexed citations

Majumdar, Anandamayee, Cleridy E. Lennert‐Cody, Mark N. Maunder, & Alexandre Aires‐da‐Silva. (2023). spatio-temporal modeling for estimation of bigeye tuna catch in the presence of pandemic-related data loss using parametric adjacency structures. Fisheries Research. 268. 106813–106813. 1 indexed citations

Lennert‐Cody, Cleridy E., Jon López, & Mark N. Maunder. (2023). An automatic purse-seine set type classification algorithm to inform tropical tuna management. Fisheries Research. 262. 106644–106644. 1 indexed citations

Shertzer, Kyle W., et al.. (2023). Process and sampling variance within fisheries stock assessment models: estimability, likelihood choice, and the consequences of incorrect specification. ICES Journal of Marine Science. 80(8). 2125–2149. 8 indexed citations

Maunder, Mark N. & George M. Watters. (2021). A general framework for integrating environmental time series into stock assessment models: model description, simulation testing, and example. AquaDocs (United Nations Educational, Scientific and Cultural Organization). 9 indexed citations

Carvalho, Felipe, Henning Winker, Dean L. Courtney, et al.. (2021). A cookbook for using model diagnostics in integrated stock assessments. Fisheries Research. 240. 105959–105959. 51 indexed citations

10.

Crone, Paul R., Mark N. Maunder, Hui‐Hua Lee, & Kevin R. Piner. (2019). Good practices for including environmental data to inform spawner-recruit dynamics in integrated stock assessments: Small pelagic species case study. Fisheries Research. 217. 122–132. 18 indexed citations

11.

Thorson, James T., et al.. (2017). Spatiotemporal variation in size-structured populations using fishery data: an application to shortfin mako (Isurus oxyrinchus) in the Pacific Ocean. Canadian Journal of Fisheries and Aquatic Sciences. 74(11). 1765–1780. 29 indexed citations

12.

Minte‐Vera, Carolina V., et al.. (2017). Get the biology right, or use size-composition data at your own risk. Fisheries Research. 192. 114–125. 20 indexed citations

13.

Chang, Shui‐Kai, et al.. (2017). Data reconstruction can improve abundance index estimation: An example using Taiwanese longline data for Pacific bluefin tuna. PLoS ONE. 12(10). e0185784–e0185784. 11 indexed citations

14.

Maunder, Mark N., et al.. (2015). Estimation of growth within Stock Synthesis models: Management implications when using length-composition data. Fisheries Research. 180. 87–91. 18 indexed citations

15.

Maunder, Mark N., et al.. (2012). ESTIMATING RELATIVE ABUNDANCE FROM CATCH AND EFFORT DATA, USING NEURAL NETWORKS. AquaDocs (United Nations Educational, Scientific and Cultural Organization). 4 indexed citations

16.

Fournier, David, Hans J. Skaug, James N. Ianelli, et al.. (2011). AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. Optimization methods & software. 27(2). 233–249. 1473 indexed citations breakdown →

17.

Hoyle, Simon, et al.. (2004). A Bayesian integrated population dynamics model to analyze data for protected species. Animal Biodiversity and Conservation. 27(1). 247–266. 37 indexed citations

18.

Maunder, Mark N. & Shelton J. Harley. (2003). Methodological improvements to the EPO tuna stock assessments. 6 indexed citations

19.

Maunder, Mark N. & Paul J. Starr. (2001). Bayesian assessment of the SNA1 snapper ( Pagrus auratus ) stock on the north‐east coast of New Zealand. New Zealand Journal of Marine and Freshwater Research. 35(1). 87–110. 29 indexed citations

20.

Maunder, Mark N., et al.. (2001). The conservation value of botanic garden palm collections. Biological Conservation. 98(3). 259–271. 46 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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