Daniel D. Heath

3.7k total citations
99 papers, 2.9k citations indexed

About

Daniel D. Heath is a scholar working on Nature and Landscape Conservation, Genetics and Aquatic Science. According to data from OpenAlex, Daniel D. Heath has authored 99 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Nature and Landscape Conservation, 42 papers in Genetics and 34 papers in Aquatic Science. Recurrent topics in Daniel D. Heath's work include Fish Ecology and Management Studies (80 papers), Genetic diversity and population structure (34 papers) and Aquaculture Nutrition and Growth (24 papers). Daniel D. Heath is often cited by papers focused on Fish Ecology and Management Studies (80 papers), Genetic diversity and population structure (34 papers) and Aquaculture Nutrition and Growth (24 papers). Daniel D. Heath collaborates with scholars based in Canada, United States and Australia. Daniel D. Heath's co-authors include John W. Heath, Charles W. Fox, Colleen A Bryden, J. Mark Shrimpton, George K. Iwama, Rachel M. Johnson, Bryan D. Neff, Kyle W. Wellband, Derek A. Roff and Margaret F. Docker and has published in prestigious journals such as Science, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Daniel D. Heath

95 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel D. Heath Canada 31 1.8k 1.0k 979 882 571 99 2.9k
Bernie May United States 34 1.6k 0.9× 1.8k 1.8× 1.0k 1.1× 645 0.7× 386 0.7× 118 3.5k
Ruth E. Withler Canada 38 2.4k 1.4× 2.3k 2.3× 1.1k 1.1× 726 0.8× 664 1.2× 117 3.9k
Béatrice Chatain France 39 1.4k 0.8× 1.2k 1.2× 588 0.6× 2.4k 2.7× 462 0.8× 101 3.8k
Filip Volckaert Belgium 28 786 0.4× 846 0.8× 914 0.9× 503 0.6× 371 0.6× 74 2.2k
Sofía Consuegra United Kingdom 33 1.4k 0.8× 1.1k 1.1× 1.3k 1.3× 548 0.6× 447 0.8× 116 3.2k
Graham A.E. Gall United States 34 1.5k 0.9× 1.6k 1.6× 639 0.7× 1.4k 1.6× 389 0.7× 101 3.1k
Maria M. Coelho Portugal 34 1.4k 0.8× 1.8k 1.8× 1.0k 1.0× 991 1.1× 248 0.4× 114 3.2k
Pierre‐Alexandre Gagnaire France 29 817 0.5× 1.7k 1.7× 756 0.8× 530 0.6× 457 0.8× 64 2.7k
Seinen Chow Japan 30 901 0.5× 726 0.7× 1.1k 1.1× 956 1.1× 807 1.4× 113 2.7k
Patrick O’Reilly Canada 26 1.7k 1.0× 2.0k 2.0× 566 0.6× 453 0.5× 405 0.7× 39 2.7k

Countries citing papers authored by Daniel D. Heath

Since Specialization
Citations

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

Fields of papers citing papers by Daniel D. Heath

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel D. Heath. 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 D. Heath. The network helps show where Daniel D. Heath may publish in the future.

Co-authorship network of co-authors of Daniel D. Heath

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel D. Heath. A scholar is included among the top collaborators of Daniel D. Heath 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 D. Heath. Daniel D. Heath 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.
Best, Carol, et al.. (2025). Transcriptional profiling provides insights into sublethal thermal stress thresholds in juvenile bull trout. Canadian Journal of Fisheries and Aquatic Sciences. 82. 1–17. 1 indexed citations
2.
Chaganti, Subba Rao, et al.. (2024). Comprehensive evaluation of UV inactivation of E. coli using multiple gene targets and real-time quantitative PCR. Water Research X. 26. 100285–100285.
3.
Semeniuk, Christina A. D., Ken M. Jeffries, Steven J. Cooke, et al.. (2022). Innovating transcriptomics for practitioners in freshwater fish management and conservation: best practices across diverse resource-sector users. Reviews in Fish Biology and Fisheries. 32(3). 921–939. 11 indexed citations
4.
Jeffries, Ken M., et al.. (2021). The use of non-lethal sampling for transcriptomics to assess the physiological status of wild fishes. Comparative Biochemistry and Physiology Part B Biochemistry and Molecular Biology. 256. 110629–110629. 43 indexed citations
5.
Johansson, Mattias L., et al.. (2018). Molecular Insights Into the Ctenophore Genus Beroe in Europe: New Species, Spreading Invaders. Journal of Heredity. 109(5). 520–529. 18 indexed citations
6.
Vo, Nguyen T. K., et al.. (2018). Extracellular dsRNA induces a type I interferon response mediated via class A scavenger receptors in a novel Chinook salmon derived spleen cell line. Developmental & Comparative Immunology. 89. 93–101. 20 indexed citations
7.
Semeniuk, Christina A. D., et al.. (2016). Additive and non-additive genetic components of the jack male life history in Chinook salmon (Oncorhynchus tshawytscha). Genetica. 144(4). 477–485. 6 indexed citations
8.
9.
Lehnert, Sarah J., Oliver P. Love, Trevor E. Pitcher, Dennis M. Higgs, & Daniel D. Heath. (2014). Multigenerational outbreeding effects in Chinook salmon (Oncorhynchus tshawytscha). Genetica. 142(4). 281–293. 10 indexed citations
10.
Aykanat, Tutku, Colleen A Bryden, & Daniel D. Heath. (2012). Sex‐biased genetic component distribution among populations: additive genetic and maternal contributions to phenotypic differences among populations of Chinook salmon. Journal of Evolutionary Biology. 25(4). 682–690. 18 indexed citations
11.
12.
Garner, Shawn R., et al.. (2009). Sexual conflict inhibits female mate choice for major histocompatibility complex dissimilarity in Chinook salmon. Proceedings of the Royal Society B Biological Sciences. 277(1683). 885–894. 38 indexed citations
13.
Heath, Daniel D., et al.. (2009). Environmental factors associated with reproductive barrier breakdown in sympatric trout populations on Vancouver Island. Evolutionary Applications. 3(1). 77–90. 29 indexed citations
14.
Letcher, Robert J., et al.. (2008). Why are salmon eggs red? Egg carotenoids and early life survival of Chinook salmon (Oncorhynchus tshawytscha). Evolutionary ecology research. 10(8). 1187–1199. 29 indexed citations
15.
Neff, Bryan D., Shawn R. Garner, John W. Heath, & Daniel D. Heath. (2008). The MHC and non-random mating in a captive population of Chinook salmon. Heredity. 101(2). 175–185. 82 indexed citations
16.
Morgan, George Emir, et al.. (2005). Inbreeding, outbreeding and environmental effects on genetic diversity in 46 walleye (Sander vitreus) populations. Molecular Ecology. 15(2). 303–320. 44 indexed citations
17.
Colautti, Robert I., Marina Manca, Markku Viljanen, et al.. (2005). Invasion genetics of the Eurasian spiny waterflea: evidence for bottlenecks and gene flow using microsatellites. Molecular Ecology. 14(7). 1869–1879. 71 indexed citations
18.
Docker, Margaret F., et al.. (2003). Erosion of interspecific reproductive barriers resulting from hatchery supplementation of rainbow trout sympatric with cutthroat trout. Molecular Ecology. 12(12). 3515–3521. 39 indexed citations
19.
Mousseau, Timothy A., Kermit Ritland, & Daniel D. Heath. (1998). A novel method for estimating heritability using molecular markers. Heredity. 80(2). 218–224. 7 indexed citations
20.
Heath, Daniel D. & Thomas J. Hilbish. (1998). Mytilus protamine-like sperm-specific protein genes are multicopy, dispersed, and closely associated with hypervariable RFLP regions. Genome. 41(4). 587–596. 8 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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