DOI: 10.25927/fmnp5-j4454
title: BAYSICS Citizen Science Data (ecoclimatological observations, here: treeline observations, focused on Bavaria)

description: This is the first dataset released from the BAYSICS project (Bayerisches Synthese-Informations-Citizen Science Portal für Klimaforschung und Wissenschaftskommunikation – Bavarian Citizen Science Information Synthesis Portal for Climate Research and Science Communication). The data in this release cover the core project phase and extend from April 2020 to March 2024. The dataset includes observations (quantities and images as submitted) and additional metadata (e.g. time and place).
The BAYSICS web portal has been collecting citizen scientists’ observations on four main research topics:

Plants - investigating the phenology of plants to track the effects of climate change.
Allergenic Species - investigating changes in pollen loads as a result of climate change.
Animals - exploring changes in animal distribution and behavior as a response to climate change in both urban and rural areas.
Tree Lines - investigating the altitudinal limits of tree species in mountainous regions to understand the impacts of climate change.
The datasets are organized to contain:

one main recording table (as .xlsx and .csv)
one .zip file with observation pictures, sorted by submission year/month/day and referenced from the table (in the “Photo” field)
This sub-dataset comprises observations of tree specimens at the treeline. The observation pictures are in baysics_treeline_by202403.zip. The fields in the recording table (baysics_treeline_by202403.xlsx/.csv) for TREELINES (German: BAUMGRENZEN) are as follows:

TreeSpecies: Identified tree species
Certainty: Confidence in identification
TreeHeight: Height of the tree
Latitude: Latitude coordinates
Longitude: Longitude coordinates
Position: How the position was recorded
AccuracyGPS: (In)accuracy of GPS in meters (automatically determined when using GPS features of a smartphone)
Distance_m: Distance from the tree in meters
AltitudeDGM_m: Altitude automatically calculated based on the Digital Elevation Model
AltitudeMeasured: Whether the sea level altitude was measured in the field (if no, the sea level altitude is determined based on the coordinates)
MethodAltitudeMeasured: If measured, how the sea level altitude was determined
AltitudeMeasured_m: Measured sea level altitude in meters
MountainRange: Any of eight regions/ranges of the Bavarian Alps
ObservationDate: Date of the observation
Photo: Path to the image

Observation data has been submitted via an online form on the BAYSICS portal, where additional guidance and information has been provided to support the observation process. Data quality has been managed through a reporting system that can be used by users to flag inappropriate data. Reported data, in particular images, have been temporarily hidden and only made public after a successful verification by the project team.
The BAYSICS data set is valuable for integrating with other climate data, such as temperature and precipitation records, to assess the impact of climate change. It also serves as ground-truth data that can be combined with remote sensing data and other sensor networks. Furthermore, the project has been promoting the FAIR principles (Findable, Accessible, Interoperable, Reusable) for citizen science data, including the availability of data to a wider community of researchers. BAYSICS has been highlighting the growing importance of citizen-generated data in scientific research.
The project has been carried out from 2018 on in partnership by the Technical University of Munich, the Leibniz Supercomputing Center of the Bavarian Academy of Sciences and Humanities (LRZ), the Catholic University Eichstätt-Ingolstadt, the University of Applied Sciences Weihenstephan-Triesdorf, the University of Augsburg, the University of Regensburg and the Ludwig-Maximilians-Universität München. Based in Bavaria, Germany, BAYSICS has engaged citizens in research on nature dynamics, conservation, and climate change.
Access to the dataset:
Please visit https://webservices.rdm.lab.lrz.de/data/baysics/baysics_treeline_by202403; for clarifying any questions or problems please contact the authors.