What is he best known for?
The fields of study he is best known for:
His primary scientific interests are in Ecology, Ecosystem, Botany, Plant community and Species richness.
Ian A. Dickie performs integrative Ecology and Cenococcum geophilum research in his work.
His Ecosystem research is multidisciplinary, relying on both Ecology and Environmental resource management.
Ian A. Dickie has included themes like Terminal restriction fragment length polymorphism, Restriction fragment length polymorphism and Niche differentiation in his Botany study.
In his study, Canopy, Competition and Disjunct is inextricably linked to Community, which falls within the broad field of Plant community.
His work carried out in the field of Species richness brings together such families of science as Range, Pyrosequencing and Decomposer.
His most cited work include:
- Rooting theories of plant community ecology in microbial interactions (524 citations)
- Redefining fine roots improves understanding of below-ground contributions to terrestrial biosphere processes (478 citations)
- Assembly history dictates ecosystem functioning: evidence from wood decomposer communities. (386 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Ecology, Ecosystem, Botany, Biodiversity and Introduced species.
Invasive species, Species richness, Host, Plant community and Ecological succession are among the areas of Ecology where Ian A. Dickie concentrates his study.
His Ecosystem research focuses on subjects like Biomass, which are linked to Abiotic component.
His Botany research is multidisciplinary, incorporating elements of Terminal restriction fragment length polymorphism and Nutrient.
His research in Biodiversity tackles topics such as Community structure which are related to areas like Decomposer.
His Introduced species study incorporates themes from Lophozonia menziesii and Pinus contorta.
He most often published in these fields:
- Ecology (90.97%)
- Ecosystem (47.92%)
- Botany (34.03%)
What were the highlights of his more recent work (between 2018-2021)?
- Ecology (90.97%)
- Invasive species (19.44%)
- Invertebrate (3.47%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Ecology, Invasive species, Invertebrate, Environmental DNA and Introduced species.
His Ecology research focuses on Mutualism, Ecosystem, Species richness, Land use and Dominance.
As part of his studies on Ecosystem, Ian A. Dickie often connects relevant areas like Ecological succession.
Ian A. Dickie focuses mostly in the field of Invertebrate, narrowing it down to topics relating to Herbivore and, in certain cases, Soil biology and Soil carbon.
In Environmental DNA, Ian A. Dickie works on issues like DNA, which are connected to Computational biology, Replication and Ecology.
The Introduced species study combines topics in areas such as Obligate, Mycorrhizal fungi and Facultative.
Between 2018 and 2021, his most popular works were:
- DNA metabarcoding-Need for robust experimental designs to draw sound ecological conclusions (106 citations)
- Dual-mycorrhizal plants: their ecology and relevance. (27 citations)
- DNA metabarcoding as a tool for invertebrate community monitoring: a case study comparison with conventional techniques (19 citations)
In his most recent research, the most cited papers focused on:
His primary areas of study are Environmental DNA, Ecology, DNA, Invertebrate and Data science.
Ian A. Dickie interconnects Agriculture, Pathogen and Land use in the investigation of issues within Environmental DNA.
His work on Mutualism, Abiotic component and Host as part of general Ecology research is often related to Ectomycorrhiza and Arbuscular mycorrhiza, thus linking different fields of science.
His DNA research incorporates themes from Evolutionary biology, Ecology, Computational biology and Replication.
The various areas that Ian A. Dickie examines in his Invertebrate study include Herbivore, Ecosystem, Biota, Introduced species and Dominance.
Ian A. Dickie merges Data science with Context in his research.
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.
