On the importance of soil texture for predicting future global soil respiration

Dear researchers and interested parties,

We are pleased to announce the publication of our recent research on Zenodo, which explores the role of soil texture in predicting future global soil respiration under climate change scenarios. Using a machine learning approach, we provide high-resolution (1 km) spatial models estimating total and heterotrophic soil respiration (Rs and Rh) up to the year 2100 across different Shared Socioeconomic Pathways (SSPs). Our findings highlight the importance of incorporating soil texture to improve the accuracy of soil carbon-climate feedback projections.

Available resources:

Soil respiration predictions:

We provide spatially explicit estimates of Rs and Rh, including associated uncertainties, under multiple IPCC SSP scenarios. The dataset includes mean values (g C m^-2 year^-1) and coefficients of variation (%). All maps are available in "tif" format, using the Goode Homolosine - Land projection system (ESRI:54052).

Open-Source Code and Data: The entire analytical workflow, developed in R, is accessible through our GitHub repository, ensuring full reproducibility and transparency. Additional methodological details can be found in our publication:

Gomes, L. C., Moquedace, C. M., Souza, I. F., Bond-Lamberty, B., Vargas, R., Vesterdal, L., Veloso, G. V., Francelino, M. R., Schaefer, C. E. G. R., Morris, K. A., & Fernandes-Filho, E. I. (2026). On the importance of soil texture for predicting future global soil respiration. Science of the Total Environment, 1027, 181663. DOI: 10.1016/j.scitotenv.2026.181663

Availability objectives:

Advancing scientific collaboration:

We invite researchers and organizations to utilize our dataset to enhance studies on soil carbon dynamics and climate change feedbacks.

Supporting environmental understanding:

By providing open access to these models, we aim to contribute to the global understanding of future soil carbon fluxes and support the development of more accurate climate projections.

Fostering innovation:

Sharing our results and methodologies aims to stimulate advancements in spatial modeling and predictive capabilities for soil respiration under changing climatic conditions.

We appreciate your interest and collaboration. We look forward to fostering scientific exchange and contributing to a more comprehensive understanding of soil-climate interactions in the 21st century.