Robert G. Latta

3.5k total citations · 1 hit paper
51 papers, 2.9k citations indexed

About

Robert G. Latta is a scholar working on Genetics, Ecology, Evolution, Behavior and Systematics and Plant Science. According to data from OpenAlex, Robert G. Latta has authored 51 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Genetics, 22 papers in Ecology, Evolution, Behavior and Systematics and 13 papers in Plant Science. Recurrent topics in Robert G. Latta's work include Genetic diversity and population structure (28 papers), Plant and animal studies (21 papers) and Genetic Mapping and Diversity in Plants and Animals (15 papers). Robert G. Latta is often cited by papers focused on Genetic diversity and population structure (28 papers), Plant and animal studies (21 papers) and Genetic Mapping and Diversity in Plants and Animals (15 papers). Robert G. Latta collaborates with scholars based in Canada, United States and France. Robert G. Latta's co-authors include John McKay, Jeffry B. Mitton, Kyle M. Gardner, Yan B. Linhart, Kermit Ritland, Daniel J. Schoen, J. B. Mitton, Hafiz Maherali, Mark E. Sherrard and Rachid Cheddadi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Trends in Ecology & Evolution and Scientific Reports.

In The Last Decade

Robert G. Latta

51 papers receiving 2.7k citations

Hit Papers

Adaptive population divergence: markers, QTL and traits 2002 2026 2010 2018 2002 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robert G. Latta Canada 28 1.7k 1.1k 858 794 594 51 2.9k
Ivana Stehlik Canada 22 1.7k 1.0× 1.5k 1.3× 1.1k 1.3× 755 1.0× 618 1.0× 26 3.2k
Birgit Ziegenhagen Germany 29 1.2k 0.7× 752 0.7× 997 1.2× 684 0.9× 488 0.8× 71 2.5k
Anna Palmé Sweden 19 1.9k 1.1× 981 0.9× 923 1.1× 686 0.9× 660 1.1× 44 3.0k
Jarosław Burczyk Poland 27 1.4k 0.8× 1.2k 1.1× 891 1.0× 928 1.2× 674 1.1× 80 2.6k
Myriam Heuertz France 33 2.3k 1.3× 1.4k 1.3× 1.1k 1.3× 895 1.1× 811 1.4× 94 3.7k
Juan José Robledo‐Arnuncio Spain 23 1.1k 0.6× 918 0.8× 487 0.6× 986 1.2× 574 1.0× 52 2.1k
Ladislav Paule Slovakia 25 1.2k 0.7× 788 0.7× 982 1.1× 706 0.9× 720 1.2× 83 2.7k
Andrew J. Eckert United States 29 2.0k 1.1× 706 0.6× 953 1.1× 840 1.1× 691 1.2× 66 3.6k
Stephen R. Keller United States 25 1.5k 0.8× 892 0.8× 611 0.7× 768 1.0× 824 1.4× 63 2.8k
Christophe Thébaud France 32 1.2k 0.7× 1.7k 1.5× 758 0.9× 1.1k 1.3× 1.1k 1.9× 92 3.7k

Countries citing papers authored by Robert G. Latta

Since Specialization
Citations

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

Fields of papers citing papers by Robert G. Latta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robert G. Latta

This figure shows the co-authorship network connecting the top 25 collaborators of Robert G. Latta. A scholar is included among the top collaborators of Robert G. Latta 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 Robert G. Latta. Robert G. Latta 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.
Latta, Robert G., Wubishet A. Bekele, Charlene P. Wight, & Nicholas A. Tinker. (2019). Comparative linkage mapping of diploid, tetraploid, and hexaploid Avena species suggests extensive chromosome rearrangement in ancestral diploids. Scientific Reports. 9(1). 12298–12298. 20 indexed citations
2.
Yan, Honghai, Wubishet A. Bekele, Charlene P. Wight, et al.. (2016). High-density marker profiling confirms ancestral genomes of Avena species and identifies D-genome chromosomes of hexaploid oat. Theoretical and Applied Genetics. 129(11). 2133–2149. 49 indexed citations
5.
Latta, Robert G.. (2009). Testing for local adaptation in Avena barbata: a classic example of ecotypic divergence. Molecular Ecology. 18(18). 3781–3791. 29 indexed citations
6.
Latta, Robert G. & Christy M. McCain. (2009). Path analysis of natural selection via survival and fecundity across contrasting environments in Avena barbata. Journal of Evolutionary Biology. 22(12). 2458–2469. 22 indexed citations
7.
Latta, Robert G., et al.. (2008). GENOTYPE BY ENVIRONMENT INTERACTIONS FOR FITNESS IN HYBRID GENOTYPES OFAVENA BARBATA. Evolution. 62(3). 573–585. 21 indexed citations
8.
Latta, Robert G.. (2008). Conservation genetics as applied evolution: from genetic pattern to evolutionary process. Evolutionary Applications. 1(1). 84–94. 37 indexed citations
9.
Maherali, Hafiz, et al.. (2008). Leaf hydraulic conductivity and photosynthesis are genetically correlated in an annual grass. New Phytologist. 180(1). 240–247. 42 indexed citations
10.
Sherrard, Mark E., Hafiz Maherali, & Robert G. Latta. (2008). WATER STRESS ALTERS THE GENETIC ARCHITECTURE OF FUNCTIONAL TRAITS ASSOCIATED WITH DROUGHT ADAPTATION INAVENA BARBATA. Evolution. 63(3). 702–715. 38 indexed citations
11.
Gardner, Kyle M. & Robert G. Latta. (2008). Heritable variation and genetic correlation of quantitative traits within and between ecotypes ofAvena barbata. Journal of Evolutionary Biology. 21(3). 737–748. 21 indexed citations
12.
Gardner, Kyle M. & Robert G. Latta. (2006). Identifying loci under selection across contrasting environments inAvena barbatausing quantitative trait locus mapping. Molecular Ecology. 15(5). 1321–1333. 93 indexed citations
13.
Latta, Robert G. & John McKay. (2002). Genetic population divergence: markers and traits.: markers and traits.. Trends in Ecology & Evolution. 17(11). 501. 1 indexed citations
14.
Latta, Robert G., et al.. (2002). Mitochondrial haplotype distribution, seed dispersal and patterns of postglacial expansion of ponderosa pine. Molecular Ecology. 12(1). 293–298. 53 indexed citations
15.
Mitton, J. B., et al.. (2000). Glacial refugia of limber pine (Pinus flexilisJames) inferred from the population structure of mitochondrial DNA. Molecular Ecology. 9(1). 91–97. 90 indexed citations
16.
Latta, Robert G. & Jeffry B. Mitton. (1999). Historical Separation and Present Gene Flow Through a Zone of Secondary Contact in Ponderosa Pine. Evolution. 53(3). 769–769. 32 indexed citations
17.
Latta, Robert G.. (1998). Differentiation of Allelic Frequencies at Quantitative Trait Loci Affecting Locally Adaptive Traits. The American Naturalist. 151(3). 283–292. 149 indexed citations
18.
Latta, Robert G. & Yan B. Linhart. (1997). Path analysis of natural selection on plant chemistry: the xylem resin of ponderosa pine. Oecologia. 109(2). 251–258. 19 indexed citations
19.
Latta, Robert G. & Jeffry B. Mitton. (1997). A Comparison of Population Differentiation Across Four Classes of Gene Marker in Limber Pine (Pinus flexilis James). Genetics. 146(3). 1153–1163. 140 indexed citations
20.
Schoen, Daniel J. & Robert G. Latta. (1989). Spatial autocorrelation of genotypes in populations of Impatiens pallida and Impatiens capensis. Heredity. 63(2). 181–189. 65 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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