World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
40
Citations
8349
World Ranking
2016
National Ranking
854

William A. Link publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where William A. Link sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 88 publications — 6th percentile

6% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

William A. Link D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where William A. Link sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 40 D-Index — 45th percentile

45% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Overview

William A. Link is primarily affiliated with the United States Geological Survey in the United States. Their research spans multiple fields and subfields, with a significant focus on environmental science and social sciences. Their specialized areas of study include ecology, sociology and political science, statistics and probability, nature and landscape conservation, and marketing.

The scientist has contributed to several main research topics, including:

  • Race, History, and American Society
  • Wildlife Ecology and Conservation
  • Marine animal studies overview
  • American History and Culture
  • Ecology and Vegetation Dynamics Studies
  • Marine and fisheries research
  • Higher Education Governance and Development

William A. Link's publication record includes papers published in prominent venues such as Ecological Applications, Journal of Animal Ecology, Journal of Wildlife Management, Marine Mammal Science, and Conservation Letters. Notable recent papers authored or co-authored by Link include:

  • Model selection for the North American Breeding Bird Survey (2020) in Ecological Applications
  • Sources of variation in maternal allocation in a long-lived mammal (2020) in Journal of Animal Ecology
  • Population dynamics and harvest management of eastern mallards (2023) in Journal of Wildlife Management
  • A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity (2020) in Ecological Applications
  • Investigating diverse sources of variation in the amount of time Weddell seal (Leptonychotes weddellii) pups spend in the water during the lactation period (2022) in Marine Mammal Science

The scientist's frequent collaborators include Jay J. Rotella (3 collaborations), John R. Sauer (2 collaborations), Kaitlin R. Macdonald (2 collaborations), Robert A. Garrott (2 collaborations), and Daniel K. Niven (1 collaboration).

In addition to journal articles, William A. Link has contributed to book publications. One such work is titled Frank Porter Graham, published by the University of North Carolina Press in 2021.

Best Publications

  • Suggestions for presenting the results of data analyses

    David R. Anderson;William A. Link;Douglas H. Johnson;Kenneth P. Burnham

  • Observer differences in the North American Breeding Bird Survey

    John R. Sauer;Bruce G. Peterjohn;William A. Link

  • MODEL WEIGHTS AND THE FOUNDATIONS OF MULTIMODEL INFERENCE

    William A. Link;Richard J. Barker

  • Bayesian Inference: With Ecological Applications

    William A. Link;Richard J. Barker

  • Generalized site occupancy models allowing for false positive and false negative errors.

    J. Andrew Royle;William A. Link

  • On thinning of chains in MCMC

    William A. Link;Mitchell J. Eaton

  • Nonidentifiability of population size from capture-recapture data with heterogeneous detection probabilities.

    William A. Link

  • ESTIMATING POPULATION CHANGE FROM COUNT DATA: APPLICATION TO THE NORTH AMERICAN BREEDING BIRD SURVEY

    William A. Link;John R. Sauer

  • Analysis of multinomial models with unknown index using data augmentation

    J. Andrew Royle;Robert M Dorazio;William A Link

  • A HIERARCHICAL ANALYSIS OF POPULATION CHANGE WITH APPLICATION TO CERULEAN WARBLERS

    William A. Link;John R. Sauer

  • On the reliability of N-mixture models for count data.

    Richard J. Barker;Matthew R. Schofield;William A. Link;John R. Sauer

  • OF BUGS AND BIRDS: MARKOV CHAIN MONTE CARLO FOR HIERARCHICAL MODELING IN WILDLIFE RESEARCH

    William A. Link;Emmanuelle Cam;James D. Nichols;Evan G. Cooch

  • Estimating breeding proportions and testing hypotheses about costs of reproduction with capture-recapture data

    James D. Nichols;James E. Hines;Kenneth H. Pollock;Robert L. Hinz

  • On the importance of sampling variance to investigations of temporal variation in animal population size

    William A. Link;James D. Nichols

  • ESTIMATION OF POPULATION TRAJECTORIES FROM COUNT DATA

    William A. Link;John R. Sauer

  • On the robustness of N-mixture models

    William A. Link;Matthew R. Schofield;Richard J. Barker;John R. Sauer

  • HIERARCHICAL MODELING OF POPULATION STABILITY AND SPECIES GROUP ATTRIBUTES FROM SURVEY DATA

    John R. Sauer;William A. Link

  • Modeling association among demographic parameters in analysis of open population capture-recapture data.

    William A. Link;Richard J. Barker

  • Uncovering a Latent Multinomial: Analysis of Mark–Recapture Data with Misidentification

    William A. Link;Jun Yoshizaki;Larissa L. Bailey;Kenneth H. Pollock

  • A Hierarchical Model for Regional Analysis of Population Change Using Christmas Bird Count Data, with Application to the American Black Duck

    William A. Link;John R. Sauer;Daniel K. Niven

  • Invited Paper: SUGGESTIONS FOR PRESENTING THE RESULTS OF DATA ANALYSES

    David R. Anderson;William A. Link;Douglas H. Johnson;Kenneth P. Burnham

Frequent Co-Authors

John R. Sauer
John R. Sauer United States Fish and Wildlife Service
James D. Nichols
James D. Nichols United States Geological Survey
J. Andrew Royle
J. Andrew Royle United States Geological Survey
Emmanuelle Cam
Emmanuelle Cam University of Western Brittany
Jay J. Rotella
Jay J. Rotella Montana State University
Robert A. Garrott
Robert A. Garrott Montana State University
Evan G. Cooch
Evan G. Cooch Cornell University
James E. Hines
James E. Hines United States Geological Survey
Kenneth H. Pollock
Kenneth H. Pollock North Carolina State University
Mark A. Taggart
Mark A. Taggart University of the Highlands and Islands

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying mathematics in the USA opens doors to various interdisciplinary fields and advanced degree options. For those interested in combining quantitative skills with business acumen, pursuing a masters in marketing can be a great choice. This path leverages analytical thinking to optimize marketing strategies and improve business outcomes.

If you’re focused on leadership alongside mathematical expertise, consider exploring 1 year mba programs. These accelerated options enable professionals to quickly enhance managerial skills while integrating data-driven decision-making.

Many students also seek flexible learning options. Online MBA programs that accept transfer credits offer the convenience of tailoring your education around prior experience and credentials. To learn more, check out the online mba programs that accept transfer credits.

For those interested in careers directly related to data, enrolling in a data analytics masters programs can pave the way to roles involving big data, predictive modeling, and statistical analysis. This field highly complements a mathematical background and offers strong employment prospects.

Best Scientists Citing William A. Link

Trending Scientists

Recently Published Articles