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Pattern to process, research to practice: remote sensing of plant invasions

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Abstract

Processes that drive plant invasions play out across multiple spatial and temporal scales. Understanding individual steps along the introduction-naturalization-invasion continuum and its drivers is crucial for management. This review, targeting the broad audience of invasion scientists, field ecologists and land managers, summarizes the state-of-the-art and potential of remote sensing (RS) in plant invasion science and management. It identifies challenges and research gaps, discusses the discrepancies between technology, science and practice, and suggests ways of addressing some of these issues. Mapping, modelling and predicting invasion processes across scales is a major challenge since they are dynamic and highly complex. Integration of RS data collected at different spatial and temporal scales (“rocking” across scales) has the potential to elucidate the dynamics of invasions and to reveal its drivers, thereby improving the efficiency of control measures. Increasing spatial/temporal resolution of imagery from satellites and drones has much potential to (i) precisely identify even less conspicuous invasive species; (ii) map invasion dynamics; and (iii) provide information on environmental variables and landscape structure at scales fine enough to capture underlying ecological processes. Until now, RS research has focussed primarily on spatio-temporal patterns of plant invasions. Other more challenging topics, such as early monitoring, and revealing the invasion mechanisms and impacts have received less attention. Despite the power of RS technology and recent developments, large discrepancies remain between possibilities and actual implications in research and practical management of invasions. Although recent technological advances, such as powerful algorithms, cloud solutions, and data streams from citizen science, might overcome some limitations, the mutual dialog among field ecologists, managers, invasion scientists and RS specialists remains crucial; our review contributes to such communication.

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Accessed from the SCOPUS database using the search string: (TITLE-ABS-KEY (remote AND sensing) AND TITLE-ABS-KEY (invasive OR invasion*) AND TITLE-ABS-KEY (plant OR vegetation) AND (LIMIT-TO (DOCTYPE,”ar”)))

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Acknowledgements

We thank Fabian Fassnacht for valuable comments on an early draft of the manuscript. JM and AGS were supported under the joint German Academic Exchange Service (DAAD) and Czech Academy of Sciences (CAS) project ”Alien species in a changing world: detection, monitoring and prediction“ (DAAD-21-08, grant no. 57560648). AGS was supported by the Hessian Agency for Nature Conservation, Environment and Geology (HLNUG) under the project “Monitoring von naturschutzrelevanten Arten und Renaturierungsmaßnahmen per Fernerkundung (MonA)”. DMR acknowledges support from the DSI-NRF Centre of Excellence in Invasion Biology, Mobility 2020 project no. CZ.02.2.69/0.0/0.0/18_053/0017850 (Ministry of Education, Youth and Sports of the Czech Republic) and long-term research development project RVO 67985939 (Czech Academy of Sciences). TK was supported by the German Research Foundation (DFG) under the project “BigPlantSens” (DFG grant no. 444524904) and "PANOPS” (DFG grant no. 504978936). GB was funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4—Call for tender No. 3138 of 16 December 2021, rectified by Decree n. 3175 of 18 December 2021 of Italian Ministry of University and Research funded by the European Union—NextGenerationEU, Project code CN_00000033, Concession Decree No. 1034 of 17 June 2022 adopted by the Italian Ministry of University and Research, Project title “National Biodiversity Future Center–NBFC”.

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Authors and Affiliations

  1. Faculty of Environment, Jan Evangelista Purkyně University in Ústí nad Labem, Ústí nad Labem, Czech Republic

    Jana Müllerová

  2. Department of Agricultural Sciences, University of Sassari, Sassari, Italy

    Giuseppe Brundu

  3. National Biodiversity Future Center (NBFC), Palermo, Italy

    Giuseppe Brundu

  4. Division of Landscape Ecology and Landscape Planning, IFZ Research Centre for Biosystems, Land Use and Nutrition, Institute of Landscape Ecology and Resource Management, Justus Liebig University Giessen, Giessen, Germany

    André Große-Stoltenberg

  5. Center for International Development and Environmental Research (ZEU), Justus Liebig University Giessen, Giessen, Germany

    André Große-Stoltenberg

  6. Remote Sensing Centre for Earth System Research (RSC4Earth), Leipzig University, Leipzig, Germany

    Teja Kattenborn

  7. German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Leipzig, Germany

    Teja Kattenborn

  8. Department of Botany & Zoology, Centre for Invasion Biology, Stellenbosch University, Stellenbosch, South Africa

    David M. Richardson

  9. Department of Invasion Ecology, Institute of Botany, Czech Academy of Sciences, Průhonice, Czech Republic

    David M. Richardson

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All authors participated in the formulation of the concepts and the paper outline and contributed to writing. JM conceived and co-ordinated the writing. All authors read and approved the final manuscript.

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Müllerová, J., Brundu, G., Große-Stoltenberg, A. et al. Pattern to process, research to practice: remote sensing of plant invasions. Biol Invasions 25, 3651–3676 (2023). https://doi.org/10.1007/s10530-023-03150-z

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