G. M. Macbeth

2.3k total citations · 1 hit paper
13 papers, 1.8k citations indexed

About

G. M. Macbeth is a scholar working on Genetics, Nature and Landscape Conservation and Small Animals. According to data from OpenAlex, G. M. Macbeth has authored 13 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Genetics, 6 papers in Nature and Landscape Conservation and 3 papers in Small Animals. Recurrent topics in G. M. Macbeth's work include Fish Ecology and Management Studies (6 papers), Genetic and phenotypic traits in livestock (6 papers) and Genetic diversity and population structure (5 papers). G. M. Macbeth is often cited by papers focused on Fish Ecology and Management Studies (6 papers), Genetic and phenotypic traits in livestock (6 papers) and Genetic diversity and population structure (5 papers). G. M. Macbeth collaborates with scholars based in Australia and United States. G. M. Macbeth's co-authors include Jennifer R. Ovenden, Robin S. Waples, Chi Do, David Peel, Bree J. Tillett, Damien Broderick, Rik C. Buckworth, Paul J. Palmer, C.P. McPhee and Lisa C. Pope and has published in prestigious journals such as Aquaculture, Agricultural Systems and Molecular Ecology Resources.

In The Last Decade

G. M. Macbeth

13 papers receiving 1.7k 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.

NeEstimator v2: re‐implementation of software for the estimation of contemporary effective population size (N_e) from genetic data

2013 1.6k citations Chi Do, Robin S. Waples et al. Molecular Ecology Resources profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
G. M. Macbeth Australia	7	1.3k	713	596	283	237	13	1.8k
Kornelia Rassmann Germany	11	930 0.7×	572 0.8×	371 0.6×	320 1.1×	192 0.8×	15	1.4k
E. G. Williamson United States	3	1.3k 1.0×	670 0.9×	435 0.7×	273 1.0×	181 0.8×	6	1.6k
Tom F. Cross Ireland	13	1.2k 0.9×	829 1.2×	985 1.7×	285 1.0×	436 1.8×	19	2.2k
Bree J. Tillett Australia	11	1.3k 1.0×	776 1.1×	978 1.6×	499 1.8×	353 1.5×	18	2.2k
Stephen J. Amish United States	15	1.1k 0.8×	701 1.0×	478 0.8×	535 1.9×	258 1.1×	31	1.6k
P. L. Leberg United States	12	810 0.6×	620 0.9×	372 0.6×	158 0.6×	160 0.7×	18	1.3k
Emily K. Latch United States	21	1.3k 1.0×	845 1.2×	373 0.6×	261 0.9×	170 0.7×	52	1.8k
Michael Burden United Kingdom	4	887 0.7×	635 0.9×	332 0.6×	199 0.7×	162 0.7×	21	1.3k
Devon E. Pearse United States	26	1.2k 0.9×	661 0.9×	1.2k 2.0×	300 1.1×	526 2.2×	51	2.1k
Jonathan B. Puritz United States	18	847 0.6×	662 0.9×	291 0.5×	548 1.9×	337 1.4×	30	1.6k

Countries citing papers authored by G. M. Macbeth

Since Specialization

Citations

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

Fields of papers citing papers by G. M. Macbeth

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G. M. Macbeth. 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 G. M. Macbeth. The network helps show where G. M. Macbeth may publish in the future.

Co-authorship network of co-authors of G. M. Macbeth

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

All Works

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13 of 13 papers shown

Ovenden, Jennifer R., et al.. (2014). Translocation between freshwater catchments has facilitated the spread of tilapia in eastern Australia. Biological Invasions. 17(2). 637–650. 6 indexed citations

Macbeth, G. M. & You‐Gan Wang. (2014). Rapid assessment of genotype-by-environment interactions and heritability for growth rate in aquaculture species using in vitro fertilisation and DNA tagging. Aquaculture. 434. 397–402. 1 indexed citations

Macbeth, G. M., Damien Broderick, Rik C. Buckworth, & Jennifer R. Ovenden. (2013). Linkage Disequilibrium Estimation of Effective Population Size with Immigrants from Divergent Populations: A Case Study on Spanish Mackerel (Scomberomorus commerson). G3 Genes Genomes Genetics. 3(4). 709–717. 15 indexed citations

Do, Chi, Robin S. Waples, David Peel, et al.. (2013). NeEstimator v2: re‐implementation of software for the estimation of contemporary effective population size (N_e) from genetic data. Molecular Ecology Resources. 14(1). 209–214. 1609 indexed citations breakdown →

Peel, David, Robin S. Waples, G. M. Macbeth, Chi Do, & Jennifer R. Ovenden. (2012). Accounting for missing data in the estimation of contemporary genetic effective population size (N_e). Molecular Ecology Resources. 13(2). 243–253. 63 indexed citations

Buckworth, Rik C., et al.. (2012). Genetag: Genetic mark-recapture for real-time harvest rate monitoring: pilot studies in Northern Australia spanish marckerel fisheries. 7 indexed citations

Macbeth, G. M., Damien Broderick, Jennifer R. Ovenden, & Rik C. Buckworth. (2011). Likelihood-based genetic mark–recapture estimates when genotype samples are incomplete and contain typing errors. Theoretical Population Biology. 80(3). 185–196. 21 indexed citations

Macbeth, G. M. & Paul J. Palmer. (2011). A novel breeding programme for improved growth in barramundi Lates calcarifer (Bloch) using foundation stock from progeny-tested parents. Aquaculture. 318(3-4). 325–334. 17 indexed citations

Macbeth, G. M.. (1994). Robustness of selection response predicted from BLUP breeding values.. Proceedings of the World Congress on Genetics applied to Livestock Production. 159–162. 1 indexed citations

10.

Macbeth, G. M.. (1994). Utilizing the accuracy of estimated breeding values to improve selection response. Journal of Animal Breeding and Genetics. 111(1-6). 189–198. 1 indexed citations

11.

McPhee, C.P., et al.. (1994). The effects of selection for lean growth and the halothane allele on growth performance and mortality of pigs in a tropical environment. Livestock Production Science. 38(2). 117–123. 17 indexed citations

12.

Macbeth, G. M. & C.P. McPhee. (1986). An economic evaluation of breeding systems with selection and crossing of large white and landrace pigs in a closed herd. Agricultural Systems. 20(3). 219–239. 3 indexed citations

13.

McPhee, C.P. & G. M. Macbeth. (1984). Profit in a pig herd from performance testing and selection of breeding stock. The effect of variation in the accuracy and cost of testing. Agricultural Systems. 15(3). 137–151. 6 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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