Convergent Cross Mapping: Theory and an Example

In this review paper we present the basic principles behind convergent cross mapping, a new causality detection method, as well as an example to demonstrate it.

Reply to Baskerville and Cobey: Misconceptions about causation with synchrony and seasonal drivers

Causal inference

Identifying causal interactions among time series.

Empirical Dynamic Modeling

Inferring system dynamics from time series

Distinguishing time-delayed causal interactions using convergent cross mapping

An important problem across many scientific fields is the identification of causal effects from observational data alone. Recent methods (convergent cross mapping, CCM) have made substantial progress on this problem by applying the idea of nonlinear …

Reply to Luo et al.: Robustness of causal effects of galactic cosmic rays on interannual variation in global temperature

Spatial convergent cross mapping to detect causal relationships from short time series

Recent developments in complex systems analysis have led to new techniques for detecting causal relationships using relatively short time series, on the order of 30 sequential observations. Although many ecological observation series are even …

Causal feedbacks in climate change

The statistical association between temperature and greenhouse gases over glacial cycles is well documented[1], but causality behind this correlation remains difficult to extract directly from the data. A time lag of CO_2 behind Antarctic …

Predicting climate effects on Pacific sardine

For many marine species and habitats, climate change and overfishing present a double threat. To manage marine resources effectively, it is necessary to adapt management to changes in the physical environment. Simple relationships between …

Detecting causality in complex ecosystems

Identifying causal networks is important for effective policy and management recommendations on climate, epidemiology, financial regulation, and much else. Here, we introduce a method, based on nonlinear state space reconstruction, that can …