Publicação
Using forest structural complexity and topography metrics to characterise vertical microclimatic stratification
| datacite.subject.fos | Ciências Naturais::Ciências da Terra e do Ambiente | |
| dc.contributor.author | Lhoumeau, Sébastien | |
| dc.contributor.author | Seidel, Dominik | |
| dc.contributor.author | Elias, Rui B. | |
| dc.contributor.author | Gabriel, Rosalina | |
| dc.contributor.author | Borges, Paulo A. V. | |
| dc.date.accessioned | 2026-10-20T11:43:32Z | |
| dc.date.available | 2026-10-20T11:43:32Z | |
| dc.date.issued | 2026-10-10 | |
| dc.description.abstract | ABSTRACT: Understanding how topography and forest structure drive the transformation of incoming solar energy into local microclimatic conditions is essential for predicting forest resilience under climate change. Quantifying the importance of such attributes on the stratification of microclimates requires the integration of heterogeneous ecological data streams. Here, we combined satellite-derived solar radiation and topographic data, LiDARderived forest structural metrics and in situ air temperature and relative humidity time series to quantify the interactions between incoming solar energy, forest structure and topography, ultimately driving microclimatic stratification. Focusing on native and exotic forest stands on Terceira Island, Azores, Portugal, we evaluated how forest structural complexity and topography interact with incoming solar energy to jointly shape daily air temperature and vapour pressure deficit dynamics. By explicitly linking terrain complexity and three-dimensional vegetation structure with external energy inputs and sensor-derived microclimatic responses, our approach provides a datadriven basis for identifying the structural attributes that drive microclimatic variability within forests. Our results show that forest structural complexity and topography shape the vertical gradient of air temperature and atmospheric dryness, but with responses differing among canopy, understory, and ground strata. These findings demonstrate the value of integrating remote sensing, environmental sensor networks, and statistical modelling to resolve biologically relevant microclimatic heterogeneity. More broadly, the workflow developed here offers a transferable framework for microclimate monitoring, forest restoration assessment, and the identification of microrefugia in structurally complex ecosystems. | eng |
| dc.description.sponsorship | This research was funded by Biodiversa+, the European Biodiversity Partnership, in the context of the BioMonI – Biodiversity monitoring of island ecosystems project under the 2022–2023 BiodivMon joint call. It was co-funded by the European Commission (GA No. 101052342) and by FCT – Fundação para a Ciência e a Tecnologia, BiodivMon/0003/ 2022 to BioMonI members R.E., R.G. and P.A.V.B. Sensors were funded by the project FCT-UIDB/00329/2020–2024 (DOI 10.54499/UIDB/00 329/2020) and APC was supported by FCT-UID/00329/2025 - Centre for Ecology, Evolution and Environmental Changes (CE3C) DOI https://doi.org/10.54499/UID/00329/2025. S.L. is funded by the Azorean Government Ph.D. grant numbers M3.1.a/F/012/2022. | |
| dc.identifier.citation | Lhoumeau, S., Seidel, D., Elias, R. B., Gabriel, R., & Borges, P. A. (2026). Using forest structural complexity and topography metrics to characterise vertical microclimatic stratification. Ecological Informatics, 99, 104087. https://doi.org/10.1016/j.ecoinf.2026.104087 | |
| dc.identifier.doi | 10.1016/j.ecoinf.2026.104087 | |
| dc.identifier.eissn | 1878-0512 | |
| dc.identifier.issn | 1574-9541 | |
| dc.identifier.uri | http://hdl.handle.net/10400.3/9076 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Elsevier | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Terrestrial laser scanning | |
| dc.subject | Microclimate monitoring | |
| dc.subject | Vegetation architecture | |
| dc.subject | Solar irradiation | |
| dc.subject | Forest island ecosystems | |
| dc.title | Using forest structural complexity and topography metrics to characterise vertical microclimatic stratification | eng |
| dc.type | contribution to journal | |
| dcterms.references | https://github. com/SebEyes/Microclimate_structure_interaction | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 12 | |
| oaire.citation.issue | 104087 | |
| oaire.citation.startPage | 1 | |
| oaire.citation.title | Ecological Informatics | |
| oaire.citation.volume | 99 | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 |