Detecting Causality in Complex Ecosystems

By George Sugihara, R. May, H. Ye, C. Hsieh, Ethan R. Deyle, Michael Fogarty, Stephan B. Munch. 2012

2,341 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Environmental Engineering, Global and Planetary Change

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Environmental Engineering

In Global and Planetary Change

Citations in the corpus

Discovering governing equations from data by sparse identification of nonlinear dynamical systems (2015, methodology): “These include methods to discover governing equations from time-series data (6), equation-free modeling (7), empirical dynamic modeling (8, 9), modeling emergent behavior (10), and automated inference of dynamics (11–13); ref.”
Distinguishing time-delayed causal interactions using convergent cross mapping (2015, neutral): “1 [3 6 0 4 3 6 ] 1 [3 6 0 4 3 6 ] 1 [3 8 0 35 3 8 ] 3 1 1 1”
Small pelagic fish in the new millennium: A bottom-up view of global research effort (2020, background): “Additionally, the decades of regular observations to quantify physical and biological conditions in the CalCS has facilitated one of the more unique aspects of research the region: application of theoretical numerical approaches to explore causal relationships in long time series of observational da”
Is There Really Granger Causality between Energy Use and Output? (2014, methodology): “…in measurement—including measuring energy using heat equivalents rather than quality-adjusted measures (Stern and Enﬂo, 2013), non-linearity of the energy-output relationship (Stern and Enﬂo, 2013; Sugihara et al., 2012), and other model misspeciﬁcations that go beyond omitted-variables bias.”
Projecting changes in the distribution and productivity of living marine resources: A critical review of the suite of modelling approaches used in the large European project VECTORS (2016, background): “In that case, the strength of the effect of temperature on sardine depended on the state of the system, and, therefore, current management decisions using a fixed temperature index for sardines appear inadequate (Sugihara et al., 2012).”
Inferring causation from time series in Earth system sciences (2019, background): “Causal inferences are degraded due to measurement errors (11) such as”
Management by proxy?:the use of indices in applied ecology (2015, background): “Meaningful spatial and temporal scales for ecological processes often defy experiments, controlled manipulations and adequate replication; most modern ecological science is reliant on observational data and correlation is far easier to demonstrate than causation (cf. Sugihara et al. 2012).”
Equation-free mechanistic ecosystem forecasting using empirical dynamic modeling (2015, methodology): “(5) found that the Ricker model fit better when constrained by climate regimes, suggesting that the spawner–recruit relationship does vary in time, a fact consistent with the general notion of nonlinear state dependence (6, 7).”
Empirical dynamic modeling for beginners (2017, methodology): “Importantly, for a dynamical system, variables are interdependent and cannot be analyzed separately (Sugihara et al. 2012).”
Testing for Causality in Continuous Time Bayesian Network Models of High-Frequency Data (2016, methodology): “Sugihara et al. (2012) perform inference using the causal time series perspective in an eco-system.”
Data Based Identification and Prediction of Nonlinear and Complex Dynamical Systems (2016, methodology): “The nonlinear dynamics based CCM method was proposed [328] to detect and quantify causal influence between a pair of dynamical variables through the corresponding time series.”
Geophysics From Terrestrial Time‐Variable Gravity Measurements (2017, background): “The combination of different instruments also requires developing statistical and processing techniques, to elucidate cause-effect relationships between the multiple time series, taking into account that correlation does not imply causation (Sugihara et al., 2012).”