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Integrals of life: Tracking ecosystem spatial heterogeneity from space through the area under the curve of the parametric Rao’s Q index

Elisa ThouveraiBIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126 Bologna, ItalyMatteo MarcantonioEvolutionary Ecology and Genetics Group, Earth & Life Institute, UCLouvain, 1348 Louvain-la-Neuve, BelgiumJonathan LenoirUMR CNRS 7058, Ecologie et Dynamique des Systèmes Anthropisés (EDYSAN), Université de Picardie Jules Verne, 1 rue des Louvels, F–80037 Amiens Cedex 1, FranceMariasole GalfréBIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126 Bologna, ItalyElisa MarchettoBIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126 Bologna, ItalyGiovanni BacaroDepartment of Life Sciences, University of Trieste, via Giorgieri 10, 34127 Trieste, ItalyRoberto Cazzolla GattiBIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126 Bologna, ItalyDaniele Da ReEvolutionary Ecology and Genetics Group, Earth & Life Institute, UCLouvain, 1348 Louvain-la-Neuve, BelgiumMichele Di MuscianoBIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126 Bologna, ItalyReinhard FurrerDepartment of Mathematics and Institute of Computational Science, University of Zürich, Zürich, SwitzerlandMarco MalavasiDepartment of Chemistry, Physics, Mathematics and Natural Sciences, University of Sassari, Sassari, ItalyVítězslav MoudrýDepartment of Spatial Sciences, Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Praha - Suchdol, Czech RepublicJakub NowosadInstitute of Geoecology and Geoinformation, Adam Mickiewicz University, Krygowskiego 10, 61-680 Poznan, PolandFranco PedrottiUniversity of Camerino, Camerino, ItalyRaffaele PelorossoDAFNE Department, Tuscia University, 01100 Viterbo, ItalyGiovanna PezziBIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126 Bologna, ItalyPetra ŠímováDepartment of Chemistry, Physics, Mathematics and Natural Sciences, University of Sassari, Sassari, ItalyCarlo RicottaDepartment of Environmental Biology, Sapienza University, Piazzale Moro, 5, 00185, Rome, ItalySonia SilvestriDepartment of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126 Bologna, ItalyEnrico TordoniDepartment of Botany, Institute of Ecology and Earth Sciences, University of Tartu, J. Liivi 2, 50409 Tartu, EstoniaMichele TorresaniDepartment of Life, Health and Environmental Sciences, University of L'Aquila, Piazzale Salvatore Tommasi 1, 67100, L'Aquila, ItalyGiorgio VacchianoDepartment of Agricultural and Environmental Sciences (DiSAA), Università degli Studi di Milano, Via Celoria 2, 20133 Milano, ItalyPiero ZanniniLifeWatch Italy, LecceDuccio RocchiniDepartment of Chemistry, Physics, Mathematics and Natural Sciences, University of Sassari, Sassari, Italy

2022en

ABI

Annotatsiya

Spatio-ecological heterogeneity is strongly linked to many ecological processes and functions such as plant species diversity patterns and change, metapopulation dynamics, and gene flow. Remote sensing is particularly useful for measuring spatial heterogeneity of ecosystems over wide regions with repeated measurements in space and time. Besides, developing free and open source algorithms for ecological modelling from space is vital to allow to prove workflows of analysis reproducible. From this point of view, NASA developed programs like the Surface Biology and Geology (SBG) to support the development of algorithms for exploiting spaceborne remotely sensed data to provide a relatively fast but accurate estimate of ecological properties in vast areas over time. Most of the indices to measure heterogeneity from space are point descriptors : they catch only part of the whole heterogeneity spectrum. Under the SBG umbrella, in this paper we provide a new R function part of the rasterdiv R package which allows to calculate spatio-ecological heterogeneity and its variation over time by considering all its possible facets. The new function was tested on two different case studies, on multi- and hyperspectral images, proving to be an effective tool to measure heterogeneity and detect its changes over time.

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DOI: 10.1016/j.ecocom.2023.101029

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