What is he best known for?
The fields of study he is best known for:
- Ecology
- Statistics
- Ecosystem
The scientist’s investigation covers issues in Ecology, Nonlinear system, Ecosystem, Series and Convergent cross mapping.
His Ecology study combines topics from a wide range of disciplines, such as Fractal and Extinction.
His research in Extinction focuses on subjects like Mesopredator release hypothesis, which are connected to Zoology.
His work deals with themes such as Stochastic process, Econometrics and System dynamics, which intersect with Nonlinear system.
His Ecosystem research integrates issues from Mechanical equilibrium, Environmental monitoring, Ichthyoplankton and Fishing.
His Statistical physics study incorporates themes from Alternative stable state and Abrupt climate change.
His most cited work include:
- Early-warning signals for critical transitions (2390 citations)
- Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series (1357 citations)
- Indices of landscape pattern (1245 citations)
What are the main themes of his work throughout his whole career to date?
George Sugihara spends much of his time researching Ecology, Nonlinear system, Series, System dynamics and Ecosystem.
His Nonlinear system study combines topics in areas such as Attractor, Econometrics and Time series.
George Sugihara interconnects Dynamical systems theory and Statistical physics in the investigation of issues within Series.
His System dynamics research incorporates elements of Machine learning and Computational science.
His studies examine the connections between Ecosystem and genetics, as well as such issues in Climate change, with regards to Climatology.
His studies in Convergent cross mapping integrate themes in fields like Data mining and Applied mathematics.
He most often published in these fields:
- Ecology (31.16%)
- Nonlinear system (19.57%)
- Series (14.49%)
What were the highlights of his more recent work (between 2016-2021)?
- System dynamics (12.32%)
- Ecology (31.16%)
- Nonlinear system (19.57%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in System dynamics, Ecology, Nonlinear system, Series and Data mining.
His System dynamics study integrates concerns from other disciplines, such as Population level, Computational science and Convergent cross mapping.
His study in Susceptible individual extends to Ecology with its themes.
In Nonlinear system, George Sugihara works on issues like Applied mathematics, which are connected to Chaotic and Dynamical systems theory.
The Series study combines topics in areas such as Stability, Algorithm, Regularization and Inference.
His Ecosystem course of study focuses on Biodiversity and Phytoplankton biomass, Biomass, Climate change and Species richness.
Between 2016 and 2021, his most popular works were:
- Inferring causation from time series in Earth system sciences (114 citations)
- Fluctuating interaction network and time-varying stability of a natural fish community (85 citations)
- Nonlinear dynamics and noise in fisheries recruitment: A global meta‐analysis (29 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Ecology
- Ecosystem
His primary areas of study are Ecology, Series, Econometrics, Nonlinear system and Applied mathematics.
His work on Abundance and Eutrophication as part of general Ecology study is frequently connected to Dynamics, Critical transition and State dependence, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
He combines subjects such as Algorithm, Regularization and Inference with his study of Series.
His research in Nonlinear system is mostly concerned with Convergent cross mapping.
George Sugihara regularly links together related areas like Dynamical systems theory in his Convergent cross mapping studies.
His research investigates the connection between Dynamical systems theory and topics such as Observational study that intersect with problems in Causation.
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