data_ECOINF-D-25-03375

Fuente: Zenodo
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Autores principales: peng, fan, chen, ling, wen, yi
Formato: Recurso digital
Publicado: Zenodo 2025
Acceso en línea:
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_version_ 1866901747790774272
author peng, fan
chen, ling
wen, yi
author_facet peng, fan
chen, ling
wen, yi
contents <p>This dataset is a comprehensive collection of all supporting data and reproducible experimental materials for the paper <em>“Predicting Productivity and Climatic Resilience of Coniferous–Broadleaved Mixed Plantations with 3-PGmix and Machine Learning.”</em> It includes multi-source data used for model inputs, machine-learning training, and result mapping, covering cartographic (mapping) data, soil and climate data, and machine-learning training datasets. The dataset is intended to support the reproducibility of the paper’s findings and promote transparent data sharing, enabling researchers to conduct comparative studies, reproduce the methods, or extend the analyses in the same or similar regions.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18890755
institution Zenodo
language
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle data_ECOINF-D-25-03375
peng, fan
chen, ling
wen, yi
<p>This dataset is a comprehensive collection of all supporting data and reproducible experimental materials for the paper <em>“Predicting Productivity and Climatic Resilience of Coniferous–Broadleaved Mixed Plantations with 3-PGmix and Machine Learning.”</em> It includes multi-source data used for model inputs, machine-learning training, and result mapping, covering cartographic (mapping) data, soil and climate data, and machine-learning training datasets. The dataset is intended to support the reproducibility of the paper’s findings and promote transparent data sharing, enabling researchers to conduct comparative studies, reproduce the methods, or extend the analyses in the same or similar regions.</p>
title data_ECOINF-D-25-03375
url https://doi.org/10.5281/zenodo.18890755