FATES on GALAXY facilitates ecologist and climate modeler collaboration

Field ecologists, environmental scientists and climate modelers need to improve communication and develop co-ordinated research efforts in order to better  represent  typical ecosystems only found at high latitudes. These ecosystems are currently poorly represented in climate models. This co-design effort was made possible by integrating a state-of-the-art demographic vegetation model  FATES (Functionally Assembled Terrestrial Ecosystem Simulator) with the Community Land Model (CLM) in Galaxy, which computing environment is made easily accessible to ecologists. We provide:

• a virtual laboratory (Climate JupyterLab in Galaxy) for developing and testing parameterizations of ecosystems and related processes, making modelling opportunities more available to ecologists, and thereby increase the pace of model improvement from the bottom up through including realistic field data into parameter development and validation;

• workflow management tools for operating these ecosystem models in a reproducible manner to realize their full potential without need for constant technical assistance;

• operational Galaxy tools (under review and to be published in Galaxy Toolshed very soon) to facilitate the exploitation of ecosystem modeling for a wider audience and by non-specialists.

In this presentation, we will explain:

-        How we have integrated FATES/CLM in Galaxy for running single-point simulations at a number of monitored sites where in-situ measurements are available; the number of sites and location is flexible enough so that new sites can be easily added.

-        How Galaxy helps researchers to access and share data collected either during field campaigns or on a regular basis at selected measurement stations;

-        How researchers can analyse data that are not yet published by controlling data access in Galaxy and proceeding to quality control, data preparation and analysis prior to data publication.

-        What tools they can use (both in https://live.usegalaxy.eu/ and https://climate.usegalaxy.eu/ to analyze and visualize the resulting data and in particular make comparisons between observations and model outputs.