Forest disturbance regimes and trends in continental Spain (1985-2023) using dense landsat time series.

Autor: Miguel S; Environmental Remote Sensing Research Group, Department of Geography and Geology, Universidad de Alcalá, Colegios 2, Alcalá de Henares, 28801, Spain. Electronic address: sofia.miguelr@uah.es., Ruiz-Benito P; Environmental Remote Sensing Research Group, Department of Geography and Geology, Universidad de Alcalá, Colegios 2, Alcalá de Henares, 28801, Spain; Universidad de Alcalá, Grupo de Ecología y Restauración Forestal (FORECO), Departamento de Ciencias de la Vida, 28805, Alcalá de Henares, Madrid, Spain., Rebollo P; Universidad de Alcalá, Grupo de Ecología y Restauración Forestal (FORECO), Departamento de Ciencias de la Vida, 28805, Alcalá de Henares, Madrid, Spain; Departamento de Biodiversidad, Ecología y Evolución, Facultad de Ciencias Biológicas, Universidad Complutense de Madrid, C/ José Antonio Novais 12, 28040, Madrid, Spain., Viana-Soto A; Technical University of Munich, School of Life Sciences, Earth Observation for Ecosystem Management, Hans-Carl-von-Carlowitz-Platz 2, 85354, Freising, Germany., Mihai MC; Environmental Remote Sensing Research Group, Department of Geography and Geology, Universidad de Alcalá, Colegios 2, Alcalá de Henares, 28801, Spain., García-Martín A; Centro Universitario de la Defensa de Zaragoza, Academia General Militar, Ctra. de Huesca s/n, 50090, Zaragoza, Spain; Geoforest-IUCA, Department of Geography and Land Management, University of 6 Zaragoza, Pedro Cerbuna 12, 50009, Zaragoza, Spain., Tanase M; Environmental Remote Sensing Research Group, Department of Geography and Geology, Universidad de Alcalá, Colegios 2, Alcalá de Henares, 28801, Spain.
Jazyk: angličtina
Zdroj: Environmental research [Environ Res] 2024 Dec 01; Vol. 262 (Pt 1), pp. 119802. Date of Electronic Publication: 2024 Aug 13.
DOI: 10.1016/j.envres.2024.119802
Abstrakt: Forest disturbance regimes across biomes are being altered by interactive effects of global change. Establishing baselines for assessing change requires detailed quantitative data on past disturbance events, but such data are scarce and difficult to obtain over large spatial and temporal scales. The integration of remote sensing with dense time series analysis and cloud computing platforms is enhancing the ability to monitor historical disturbances, and especially non-stand replacing events along climatic gradients. Since the integration of such tools is still scarce in Mediterranean regions, here, we combine dense Landsat time series and the Continuous Change Detection and Classification - Spectral Mixture Analysis (CCDC-SMA) method to monitor forest disturbance in continental Spain from 1985 to 2023. We adapted the CCDC-SMA method for improved disturbance detection creating new spectral libraries representative of the study region, and quantified the year, month, severity, return interval, and type of disturbance (stand replacing, non-stand replacing) at a 30 m resolution. In addition, we characterised forest disturbance regimes and trends (patch size and severity, and frequency of events) of events larger than 0.5 ha at the national scale by biome (Mediterranean and temperate) and forest type (broadleaf, needleleaf and mixed). We quantified more than 2.9 million patches of disturbed forest, covering 4.6 Mha over the region and period studied. Forest disturbances were on average larger but less severe in the Mediterranean than in the temperate biome, and significantly larger and more severe in needleleaf than in mixed and broadleaf forests. Since the late 1980s, forest disturbances have decreased in size and severity while increasing in frequency across all biomes and forest types. These results have important implications as they confirm that disturbance regimes in continental Spain are changing and should therefore be considered in forest strategic planning for policy development and implementation.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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