Dunes under attack: untangling the effects of landscape changes on Iceplant invasion (Carpobrotus spp., Aizoaceae) in Mediterranean coasts

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Abstract

Invasive alien plants (IAPs) are a great challenge for biodiversity conservation and management. Multi-temporal landscape analysis has a great potential for describing plant invasion, however conservation solutions accounting of landscape dynamics are still limited. This research aims to explore the spatial-temporal pattern of the IAP Carpobrotus spp. in relation with landscape changes on Mediterranean coastal dunes. Based on detailed multi-temporal Carpobrotus spp. and local land cover maps, we described coastal dune landscape changes of invaded areas using transition matrices. We then calculated a set of non-redundant class and landscape pattern metrics for the compared data maps and explored invasion trends through trajectory analysis. We analyzed the relationship between the spatial pattern of alien invasion over time (e.g., expansion or reduction) and landscape pattern trends by examining the temporal delta values of Carpobrotus spp. pattern indices in relation to the delta values of landscape pattern metrics, using a machine learning technique followed by Partial Dependence analysis. The spatial-temporal characteristics of Carpobrotus spp. patches and the contextual landscape varied across coastal tracts experiencing IAP expansion and reduction. Carpobrotus spp. invasion expanded with more numerous, bigger and more connected patches in tracts with stable seashore and increasing artificial surfaces. In coastal tracts affected by coastal erosion, Carpobrotus spp declined, /remaining in few, small and regularly shaped patches. Multi-temporal landscape analysis provides a sound framework for understanding invasion dynamics across landscapes influenced by a variety of factors such as seashore dynamics and urban sprawl. This approach offers valuable insights for developing tailored management strategies that account for specific contextual nuances and enables informed planning of recovery actions.
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Preprint ARPHA Preprints https://doi.org/10.3897/arphapreprints.e133102 (26 Jul 2024) https://doi.org/10.3897/arphapreprints.e133102 (26 Jul 2024) Published in: NeoBiota https://doi.org/10.3897/neobiota.98.132805 Other versions: - Preprint InfoPreprint Info - CiteCite - MetricsMetrics - CommentComment - RelatedRelated - CitedCited ARPHA Preprints doi: 10.3897/arphapreprints.e133102 First posted 26 Jul 2024 Authors Flavio Marzialetti - Corresponding author Department of Agricultural Sciences, University of Sassari, Viale Italia 39/A, 07100, Sassari, Italy Department of Ecological and Biological Science, Tuscia University, Largo dell’Università s.n.c., 01100, Viterbo, Italy Alicia Teresa Rosario Acosta - Corresponding author Department of Sciences, University of Roma Tre, Viale Guglielmo Marconi 446, 00146, Rome, Italy Department of Chemistry, Physics, Mathematics and Natural Sciences, University of Sassari, Via Vienna 2, 07100, Sassari, Italy University of Glasgow, School of Mathematics and Statistics, Glasgow, United Kingdom School of Plant Sciences and Food Security, George S. Wise Faculty of Life Science, Tel Aviv University, Tel Aviv, Israel Department Monitoring and Exploration Technologies, Helmholtz-Centre for Environmental Research- UFZ, Permoserstraße 15, 04318, Leipzig, Germany Department of Agricultural Sciences, University of Sassari, Viale Italia 39/A, 07100, Sassari, Italy Envixlab, Department of Biosciences and Territory, University of Molise, Contrada Fonte Lappone, 86090, Pesche (IS), Italy Conflict of interest The authors have declared that no competing interests exist. This is an open access preprint distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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