Managing plant invasions through the lens of remote sensing: A review of progress and the way forward.

Biological invasions are a challenging driver of global environmental change and a fingerprint of the Anthropocene. Remote sensing has gradually become a fundamental tool for understanding invasion patterns, processes and impacts. Nevertheless, a quantitative overview of the progress and extent of remote sensing applications to the management of plant invasions is lacking. This overview is particularly necessary to support the development of more operational frameworks based on remote sensing that can effectively improve the management of invasions. Here, we evaluate and discuss the progress, current state and future opportunities of remote sensing for the research and management of plant invasions. Supported on a systematic literature review, our study shows that, since the 1970s, remote sensing was mainly used to map and identify invasive plants, evolving, around the mid-2000s, towards a tool for assessing invasion impacts. Although remote sensing studies often focus on detecting plant invaders at advanced invasion stages, they can also contribute to the prediction of early invasion stages and to the assessment of their impacts. Despite the growing awareness of technical limitations, remote sensing offers many opportunities to further improve the management of plant invasions. These opportunities relate to the capacity of remote sensing to: (a) detect and evaluate the extent of invasions, assisting on any management option aiming at mitigating plant invasions and their impacts; (b) consider modelling frameworks that anticipate future invasions, supporting the prevention and eradication at early invasion stages and protecting ecosystems and the services they provide; and (c) monitor changes in invasion dominance, as well as the resulting impacts, supporting mitigation, restoration and adaptation actions. Finally, we discuss the way forward to make remote sensing more effective in the scope of invasion management, considering current and future Earth observation missions.

[1]  R. Ehrlich,et al.  Mapping the invasive species, Chinese tallow, with EO1 satellite Hyperion hyperspectral image data and relating tallow occurrences to a classified Landsat Thematic Mapper land cover map , 2005 .

[2]  David M. Richardson,et al.  The (bio)diversity of science reflects the interests of society , 2007 .

[3]  Richard M. Lucas,et al.  an we predict habitat quality from space ? A multi-indicator ssessment based on an automated knowledge-driven system , 2014 .

[4]  David J. Hill,et al.  Utility of unmanned aerial vehicles for mapping invasive plant species: a case study on yellow flag iris (Iris pseudacorus L.) , 2017 .

[5]  Gregory Asner,et al.  Applications of Remote Sensing to Alien Invasive Plant Studies , 2009, Sensors.

[6]  Roberta E. Martin,et al.  Effects of Morella faya tree invasion on aboveground carbon storage in Hawaii , 2010, Biological Invasions.

[7]  C. A. Mücher,et al.  Environmental science: Agree on biodiversity metrics to track from space , 2015, Nature.

[8]  André Große-Stoltenberg,et al.  Heterogeneous environments shape invader impacts: integrating environmental, structural and functional effects by isoscapes and remote sensing , 2017, Scientific Reports.

[9]  Onisimo Mutanga,et al.  Mapping Solanum mauritianum plant invasions using WorldView-2 imagery and unsupervised random forests , 2016 .

[10]  S. Ustin,et al.  The role of environmental context in mapping invasive plants with hyperspectral image data , 2008 .

[11]  Laura Chasmer,et al.  Multisensor and Multispectral LiDAR Characterization and Classification of a Forest Environment , 2016 .

[12]  M. Neteler,et al.  Benefits of hyperspectral remote sensing for tracking plant invasions , 2011 .

[13]  Miguel Delibes,et al.  The ecosystem functioning dimension in conservation: insights from remote sensing , 2012, Biodiversity and Conservation.

[14]  David M. Richardson,et al.  Unlocking the potential of Google Earth as a tool in invasion science , 2013, Biological Invasions.

[15]  Jana Müllerová,et al.  UNMANNED AERIAL VEHICLES FOR ALIEN PLANT SPECIES DETECTION AND MONITORING , 2015 .

[16]  Giorgos Mallinis,et al.  On the Use of Unmanned Aerial Systems for Environmental Monitoring , 2018, Remote. Sens..

[17]  Thomas P. Albright,et al.  The rise and fall of water hyacinth in Lake Victoria and the Kagera River basin, 1989-2001 , 2004 .

[18]  Shyama Pagad,et al.  Introducing the Global Register of Introduced and Invasive Species , 2018, Scientific Data.

[19]  Anne Bowser,et al.  Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale , 2018, Biological reviews of the Cambridge Philosophical Society.

[20]  Charles K. Toth,et al.  Remote sensing platforms and sensors: A survey , 2016 .

[21]  P. Pyšek,et al.  Timing Is Important: Unmanned Aircraft vs. Satellite Imagery in Plant Invasion Monitoring , 2017, Front. Plant Sci..

[22]  Catherine S. Jarnevich,et al.  Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM) , 2016, Journal of visualized experiments : JoVE.

[23]  Margaret Kosmala,et al.  Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery , 2018, Scientific Data.

[24]  John A. Silander,et al.  Invasion Dynamics , 2017 .

[25]  R. L. Myers,et al.  REMOTE SENSING SURVEY OF MELALEUCA , 1977 .

[26]  Roi Méndez-Rial,et al.  Alien Plant Monitoring with Ultralight Airborne Imaging Spectroscopy , 2014, PloS one.

[27]  Francisco Herrera,et al.  Deep-learning Versus OBIA for Scattered Shrub Detection with Google Earth Imagery: Ziziphus lotus as Case Study , 2017, Remote. Sens..

[28]  Charles Figuieres,et al.  A cost-benefit approach for prioritizing invasive species , 2018 .

[29]  Harini Nagendra,et al.  Remote sensing of invasive plants: incorporating functional traits into the picture , 2016 .

[30]  C. Frankenberg,et al.  OCO-2 advances photosynthesis observation from space via solar-induced chlorophyll fluorescence , 2017, Science.

[31]  Mark A. Davis.  Invasion Biology 1958-2005: The Pursuit of Science and Conservation , 2004 .

[32]  Daniel Simberloff,et al.  Eradication of island invasives: practical actions and results achieved , 2001 .

[33]  Martin Bachmann,et al.  Image Products from a new German Hyperspectral Mission EnMAP , 2017 .

[34]  Lian Pin Koh,et al.  Free and open-access satellite data are key to biodiversity conservation , 2015 .

[35]  Thomas J. Stohlgren,et al.  Improving National-Scale Invasion Maps: Tamarisk in the Western United States , 2011 .

[36]  Ned Horning,et al.  Ten ways remote sensing can contribute to conservation , 2015, Conservation biology : the journal of the Society for Conservation Biology.

[37]  Emily Nicholson,et al.  The role of satellite remote sensing in structured ecosystem risk assessments. , 2018, The Science of the total environment.

[38]  Francis Juanes,et al.  Visual and acoustic sensors for early detection of biological invasions: Current uses and future potential , 2018 .

[39]  Issg.  100 of the World’s Worst Invasive Alien Species: A Selection From The Global Invasive Species Database , 2000 .

[40]  María Flor Álvarez-Taboada,et al.  Mapping of the Invasive Species Hakea sericea Using Unmanned Aerial Vehicle (UAV) and WorldView-2 Imagery and an Object-Oriented Approach , 2017, Remote. Sens..

[41]  Y. Ho,et al.  A review of published wetland research, 1991-2008: ecological engineering and ecosystem restoration. , 2010 .

[42]  N. Pettorelli,et al.  Framing the concept of satellite remote sensing essential biodiversity variables: challenges and future directions , 2016 .

[43]  Paulo Alves,et al.  Potential of satellite-derived ecosystem functional attributes to anticipate species range shifts , 2017, Int. J. Appl. Earth Obs. Geoinformation.

[44]  Moses Azong Cho,et al.  Quantifying potential water savings from clearing invasive alien Eucalyptus camaldulensis using in situ and high resolution remote sensing data in the Berg River Catchment, Western Cape, South Africa , 2016 .

[45]  J. Aronson,et al.  Impacts of biological invasions: what's what and the way forward. , 2013, Trends in ecology & evolution.

[46]  Jeffrey A. Pedelty,et al.  A tamarisk habitat suitability map for the continental United States , 2006 .

[47]  N. Pettorelli,et al.  Satellite remote sensing of ecosystem functions: opportunities, challenges and way forward , 2018 .

[48]  M. Neteler,et al.  Potential of remote sensing to predict species invasions , 2015 .

[49]  D. L. Stokes,et al.  Modeling the Invasion of Holly (Ilex aquifolium): Spatial Relationships and Spread Trajectories , 2016 .

[50]  Laura E. Dee,et al.  Remote sensing of species dominance and the value for quantifying ecosystem services , 2016 .

[51]  Andrew P. Norton,et al.  Linaria dalmatica invades south-facing slopes and less grazed areas in grazing-tolerant mixed-grass prairie , 2012, Biological Invasions.

[52]  Brian Woodward,et al.  Mapping native and non-native riparian vegetation in the Colorado River Watershed , 2018 .

[53]  S. Ustin,et al.  Mapping nonnative plants using hyperspectral imagery , 2003 .

[54]  André Große-Stoltenberg,et al.  Early detection of GPP-related regime shifts after plant invasion by integrating imaging spectroscopy with airborne LiDAR , 2018 .

[55]  Kenneth Grogan,et al.  A Review of the Application of Optical and Radar Remote Sensing Data Fusion to Land Use Mapping and Monitoring , 2016, Remote. Sens..

[56]  H. Mooney,et al.  Invasive Alien Species in an Era of Globalization , 2007 .

[57]  Le Wang,et al.  Detection of the spatiotemporal patterns of beetle-induced tamarisk ( Tamarix spp.) defoliation along the Lower Rio Grande using Landsat TM images , 2017 .

[58]  João P. Honrado,et al.  Integrating ecosystem services and disservices: insights from plant invasions , 2017 .

[59]  David Morin,et al.  Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem , 2017, Remote. Sens..

[60]  Jana Müllerová,et al.  Remote sensing as a tool for monitoring plant invasions: Testing the effects of data resolution and image classification approach on the detection of a model plant species Heracleum mantegazzianum (giant hogweed) , 2013, Int. J. Appl. Earth Obs. Geoinformation.

[61]  J. Higgins.  Cochrane handbook for systematic reviews of interventions. Version 5.1.0 [updated March 2011]. The Cochrane Collaboration , 2011 .

[62]  S. Lowe,et al.  100 of the world's worst invasive alien species. A selection from the global invasive species database , 2004 .

[63]  Tomoaki Miura,et al.  Invasive grasses change landscape structure and fire behaviour in Hawaii , 2014 .

[64]  T. Dube,et al.  Remote sensing of invasive water hyacinth (Eichhornia crassipes): A review on applications and challenges , 2018 .

[65]  Duccio Rocchini,et al.  Will remote sensing shape the next generation of species distribution models? , 2015 .

[66]  Heiko Balzter,et al.  Connecting Earth observation to high-throughput biodiversity data , 2017, Nature Ecology &Evolution.

[67]  Roberta Kwok,et al.  Ecology’s remote-sensing revolution , 2018, Nature.

[68]  Charles C. Elton,et al.  The Ecology of Invasions by Animals and Plants. , 1959 .

[69]  André Große-Stoltenberg,et al.  Field Spectroscopy in the VNIR-SWIR Region to Discriminate between Mediterranean Native Plants and Exotic-Invasive Shrubs Based on Leaf Tannin Content , 2015, Remote. Sens..

[70]  Margaret E. Andrew,et al.  Contemporary Remotely Sensed Data Products Refine Invasive Plants Risk Mapping in Data Poor Regions , 2017, Front. Plant Sci..

[71]  Ricardo Díaz-Delgado,et al.  Linking Azolla filiculoides invasion to increased winter temperatures in the Doñana marshland (SW Spain). , 2015 .

[72]  Petr Pyšek,et al.  Fifty years of invasion ecology – the legacy of Charles Elton , 2008 .

[73]  Venkat Lakshmi,et al.  Soil Moisture Remote Sensing: State‐of‐the‐Science , 2017 .

[74]  Pamela L. Nagler,et al.  Rapid dispersal of saltcedar (Tamarix spp.) biocontrol beetles (Diorhabda carinulata) on a desert river detected by phenocams, MODIS imagery and ground observations , 2014 .

[75]  H. B. Musick.  Assessment of MSS spectral indexes for monitoring arid rangeland , 1983 .

[76]  Miguel Delibes,et al.  Use of Descriptors of Ecosystem Functioning for Monitoring a National Park Network: A Remote Sensing Approach , 2009, Environmental management.

[77]  Antoine Guisan,et al.  Predictive habitat distribution models in ecology , 2000 .

[78]  N. Pettorelli,et al.  Satellite remote sensing for applied ecologists: opportunities and challenges , 2014 .

[79]  Trisalyn A. Nelson,et al.  Potential contributions of remote sensing to ecosystem service assessments , 2014 .

[80]  João P. Honrado,et al.  An indicator-based approach to analyse the effects of non-native tree species on multiple cultural ecosystem services , 2018 .

[81]  Christoph Aubrecht,et al.  Earth Observation Open Science and Innovation , 2018 .

[82]  Domingo Alcaraz-Segura,et al.  Earth Observation of Ecosystem Services , 2013 .

[83]  Joel B. Sankey,et al.  Remote sensing of tamarisk beetle (Diorhabda carinulata) impacts along 412 km of the Colorado River in the Grand Canyon, Arizona, USA , 2018, Ecological Indicators.

[84]  João P. Honrado,et al.  The progress of interdisciplinarity in invasion science , 2017, Ambio.

[85]  John S. Kimball,et al.  Evidence of a robust relationship between solar-induced chlorophyll fluorescence and gross primary productivity across dryland ecosystems of southwestern North America , 2017 .

[86]  Adrien Michez,et al.  Mapping of riparian invasive species with supervised classification of Unmanned Aerial System (UAS) imagery , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[87]  B. Bradley.  Remote detection of invasive plants: a review of spectral, textural and phenological approaches , 2014, Biological Invasions.

[88]  Petr Pyšek,et al.  A compendium of essential concepts and terminology in invasion ecology , 2010 .

[89]  Jan Pergl,et al.  Geographical and taxonomic biases in invasion ecology. , 2008, Trends in ecology & evolution.

[90]  Christoph Kueffer,et al.  Plant invasions in the Anthropocene , 2017, Science.

[91]  Jonathon J. Donager,et al.  UAV lidar and hyperspectral fusion for forest monitoring in the southwestern USA , 2017 .

[92]  Hans Ole Ørka,et al.  Discriminating between Native Norway Spruce and Invasive Sitka Spruce - A Comparison of Multitemporal Landsat 8 Imagery, Aerial Images and Airborne Laser Scanner Data , 2016, Remote. Sens..

[93]  Jana Müllerová,et al.  Unmanned aircraft in nature conservation: an example from plant invasions , 2017 .

[94]  Mário Santos,et al.  Dynamic models in research and management of biological invasions. , 2017, Journal of environmental management.

[95]  Oscar J. Abelleira Martínez,et al.  Scaling up functional traits for ecosystem services with remote sensing: concepts and methods , 2016, Ecology and evolution.

[96]  Richard J. Hobbs,et al.  Invasion ecology and restoration ecology: Parallel evolution in two fields of endeavour. , 2011 .

[97]  André Große-Stoltenberg,et al.  Evaluation of Continuous VNIR-SWIR Spectra versus Narrowband Hyperspectral Indices to Discriminate the Invasive Acacia longifolia within a Mediterranean Dune Ecosystem , 2016, Remote. Sens..

[98]  Brett G. Dickson,et al.  Cross-jurisdictional monitoring for nonnative plant invasions using ndvi change detection indices in walnut canyon national monument, Arizona, USA , 2015 .