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Direct and biodiversity-mediated effects of climate on grassland productivity across the Alps

Direct and biodiversity-mediated effects of climate on grassland productivity across the Alps

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Authors

Pierre Gauzere, Maria Hällfors, Jussi Mäkinen, Philippe Choler, Risto K. Heikkinen, Romain Goury, Joaquim Estopinan, Cyrille Violle, Franziska Schrodt, Sara Si Moussi, Mickael Hedde, Luca Santini, Wilfried Thuiller

Abstract

Understanding how climate shapes ecosystem productivity through both energetic constraints and biodiversity‑mediated pathways remains a major challenge in global change ecology, particularly in mountain grasslands where rapid warming and strong environmental gradients interact. Here, we disentangle and map direct climatic controls on productivity from indirect effects mediated by canopy functional structure across the European Alps. Using Sentinel‑2 time series (2017–2024), we quantified canopy functional structure from spectral proxies of pigment investment and water status, functional richness, and vegetation productivity using near‑infrared reflectance of vegetation (NIRv). We combined causal inference with piecewise structural equation modelling to partition total climate effects into direct and trait‑mediated components and used varying‑coefficient models to evaluate how these pathways vary along environmental gradients.
We identified two concurrent pathways linking climate to productivity. Warmer growing seasons directly increased productivity but simultaneously reduced canopy pigment investment and water status, generating negative indirect effects that partly offset direct gains. Greater winter snow accumulation reduced productivity both directly, by shortening the effective growing season, and indirectly, through increases in canopy water content associated with lower productivity. Climatic water deficit produced opposing effects, with weakly positive direct impacts counteracted by negative indirect effects mediated by pigment‑related traits, resulting in minimal net productivity change. Trait diversity showed relatively weak climate responses and modest contributions to indirect effects.
Environmental context strongly modulated climate–vegetation relationships. Baseline temperature and moisture availability most strongly shaped climate effects on canopy traits and productivity, whereas biodiversity–functioning relationships varied little across space. Strongest positive productivity responses to warming occurred in moist, mid‑elevation regions, while responses weakened or became neutral at high elevations, snow‑rich areas, and dry sites.

DOI

https://doi.org/10.32942/X23T0T

Subjects

Ecology and Evolutionary Biology, Life Sciences

Keywords

ecosystem productivity, climate variability, alpine grasslands, functional traits, biodiversity–ecosystem functioning, remote sensing, causal inference, environmental heterogeneity

Dates

Published: 2026-03-23 16:24

Last Updated: 2026-03-23 16:24

License

CC BY Attribution 4.0 International

Additional Metadata

Data and Code Availability Statement:
All raw data used in this study are publicly available and were accessed and processed in Google Earth Engine (GEE). The spatial mask defining natural alpine grasslands above 1,000 m a.s.l. across the European Alps is available as a GEE asset at: https://code.earthengine.google.com/?asset=users/pierregauzere/natural_grasslands_1000m_europe The set of 10,000 randomly selected grassland plots (60 m radius buffers) used as units of analysis is available as a GEE vector asset at: https://code.earthengine.google.com/?asset=users/pierregauzere/NatGrass_Alps_buffers60m_10000 Sentinel-2 Level-2A surface reflectance imagery (COPERNICUS/S2_SR_HARMONIZED), climate reanalysis products (ERA5-Land and TerraClimate), and static environmental layers (Copernicus DEM, WorldClim, OpenLandMap, HydroATLAS) are all publicly available datasets accessed directly within GEE. All processing steps used to derive plot-level spectral traits (CIre, CCI, NDII), vegetation productivity (NIRv), interannual climate anomalies (GDD, CWD, SWE), and static environmental variables are fully documented and reproducible via the GEE scripts provided by the authors. The main scripts can be accessed and executed at the following links: Script for computing spectral traits and productivity from Sentinel-2 imagery: https://code.earthengine.google.com/045dff0eec966c841f443feb4bd1eb7c?accept_repo=users%2Fgisizw%2FGEE-PICX Script for computing interannual climate time series (GDD, CWD, SWE): https://code.earthengine.google.com/9e8314e07b23d0fab6fcc8eb3aaf83d2?accept_repo=users%2Fgisizw%2FGEE-PICX Script for compiling static environmental variables: https://code.earthengine.google.com/9e8314e07b23d0fab6fcc8eb3aaf83d2?accept_repo=users%2Fgisizw%2FGEE-PICX All analyses were conducted using derived plot-level time series exported from GEE; no proprietary data were used. The full workflow therefore allows independent reproduction of all results starting from publicly available raw data.

Language:
English