What is he best known for?
The fields of study he is best known for:
- Ecology
- Statistics
- Genetics
Peter E. Smouse spends much of his time researching Ecology, Genetics, Genetic structure, Population genetics and Statistics.
His studies deal with areas such as Genetic variability, Biological dispersal and Genetic variation as well as Ecology.
He interconnects F-statistics, Econometrics, Allele frequency and Population biology in the investigation of issues within Genetics.
The various areas that Peter E. Smouse examines in his F-statistics study include mtDNA control region, Nucleotide diversity, Haplotype, Fixation index and Conservation genetics.
Peter E. Smouse has researched Genetic structure in several fields, including Genetic distance and Spatial analysis.
His work on Asymptotic distribution as part of general Statistics research is often related to Visual Basic for Applications, Distance matrices in phylogeny and Distance measures, thus linking different fields of science.
His most cited work include:
- genalex 6: genetic analysis in Excel. Population genetic software for teaching and research (13050 citations)
- Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. (11785 citations)
- GenAlEx 6.5 (6278 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Ecology, Genetics, Pollen, Evolutionary biology and Genetic structure.
His Ecology study combines topics in areas such as Biological dispersal, Seed dispersal and Genetic variation.
His Genetics research includes elements of Population genetics, Allele frequency, Statistics, Loss of heterozygosity and Haplotype.
Specifically, his work in Statistics is concerned with the study of Estimator.
His work on Pollination and Outcrossing as part of general Pollen research is frequently linked to Estimation, thereby connecting diverse disciplines of science.
The Genetic structure study combines topics in areas such as Spatial analysis and Gene flow.
He most often published in these fields:
- Ecology (42.95%)
- Genetics (30.77%)
- Pollen (16.67%)
What were the highlights of his more recent work (between 2009-2021)?
- Ecology (42.95%)
- Biological dispersal (12.82%)
- Genetic structure (15.38%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Ecology, Biological dispersal, Genetic structure, Evolutionary biology and Genetics.
His Ecology research integrates issues from Seed dispersal and Genetic variation.
His work deals with themes such as Range and Propagule, Botany, which intersect with Biological dispersal.
His Genetic structure research is multidisciplinary, relying on both Gene flow and Pollen.
His Genetics research incorporates elements of Chiloglottis, Statistics, Inbreeding and Reproductive isolation.
His Statistics research is multidisciplinary, incorporating elements of Biotechnology and Linkage disequilibrium.
Between 2009 and 2021, his most popular works were:
- GenAlEx 6.5 (6278 citations)
- Stochastic modelling of animal movement (174 citations)
- Developing a broader scientific foundation for river restoration: Columbia River food webs. (90 citations)
In his most recent research, the most cited papers focused on:
- Ecology
- Statistics
- Genetics
Ecology, Genetics, Statistics, Population genetics and Effective population size are his primary areas of study.
His studies in Ecology integrate themes in fields like Zoology, Biological dispersal, Seed dispersal, Genetic structure and Phylogeography.
His Genetic structure study incorporates themes from Tropical and subtropical dry broadleaf forests, Population density, Ecosystem and Enterolobium.
His research in Statistics intersects with topics in Linkage disequilibrium, Inbreeding and Null allele.
His study in Population genetics is interdisciplinary in nature, drawing from both mtDNA control region, Coral reef and Spatial ecology.
His work deals with themes such as Genetic Speciation, Chiloglottis, Genetic algorithm and Reproductive isolation, which intersect with Effective population size.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
