The dynamics of biochemical processes in terrestrial ecosystems are tightly coupled to local meteorological conditions. Understanding these interactions is an essential prerequisite for predicting, e.g. the response of the terrestrial carbon cycle to climate change. However, many empirical studies in this field rely on correlative approaches and only very few studies apply causal discovery methods. Here we explore the potential for a recently proposed causal graph discovery algorithm to reconstruct the causal dependency structure underlying biosphere-atmosphere interactions. Using artificial time series with known dependencies that mimic real-world biosphere-atmosphere interactions we address the influence of non-stationarities, i.e. period...
The primary research issue in understanding the role of terrestrial ecosystems in global change is a...
Global climate models are central tools for understanding past and future climate change. The assess...
We evaluate causal dependencies between thirteen indices that represent large-scale climate patterns...
The dynamics of biochemical processes in terrestrial ecosystems are tightly coupled to local meteoro...
Local meteorological conditions and biospheric activity are tightly coupled. Understanding these lin...
Biosphere--atmosphere interactions determine a large fraction of the observed variability in carbon ...
Understanding the dependencies of the terrestrial carbon and water cycle with meteorological conditi...
Attribution in ecosystems aims to identify the cause-effect relationships between the variables invo...
Satellite Earth observation has led to the creation of global climate data records of many important...
Improving the skill of Earth system models (ESMs) in representing climate-vegetation interactions is...
Ecological multivariate systems offer a suitable data set on which to apply recent advances in infor...
We propose a spatiotemporal model system to evaluate methods of causal discovery. The use of causal ...
This paper suggests new methods for the development of network models in climate research. Current...
Identifying causal relationships and quantifying their strength fromobservational time series data a...
Characterizing ecosystem-atmosphere interactions in terms of carbon and water exchange on different ...
The primary research issue in understanding the role of terrestrial ecosystems in global change is a...
Global climate models are central tools for understanding past and future climate change. The assess...
We evaluate causal dependencies between thirteen indices that represent large-scale climate patterns...
The dynamics of biochemical processes in terrestrial ecosystems are tightly coupled to local meteoro...
Local meteorological conditions and biospheric activity are tightly coupled. Understanding these lin...
Biosphere--atmosphere interactions determine a large fraction of the observed variability in carbon ...
Understanding the dependencies of the terrestrial carbon and water cycle with meteorological conditi...
Attribution in ecosystems aims to identify the cause-effect relationships between the variables invo...
Satellite Earth observation has led to the creation of global climate data records of many important...
Improving the skill of Earth system models (ESMs) in representing climate-vegetation interactions is...
Ecological multivariate systems offer a suitable data set on which to apply recent advances in infor...
We propose a spatiotemporal model system to evaluate methods of causal discovery. The use of causal ...
This paper suggests new methods for the development of network models in climate research. Current...
Identifying causal relationships and quantifying their strength fromobservational time series data a...
Characterizing ecosystem-atmosphere interactions in terms of carbon and water exchange on different ...
The primary research issue in understanding the role of terrestrial ecosystems in global change is a...
Global climate models are central tools for understanding past and future climate change. The assess...
We evaluate causal dependencies between thirteen indices that represent large-scale climate patterns...