Analyzing remotely sensed structural and chemical canopy traits of a forest invaded by Prunus serotina over multiple spatial scales. - Ewald, Michael; Skowronek, Sandra; Aerts, Raf; Dolos, Klara; Lenoir, Jonathan; Nicolas, Manuel; Warrie, Jens; Hattab, Tarek; Feilhauer, Hannes; Honnay, Olivier; Garzon-Lopez, Carol; Decocq, Guillaume; et al. (Biological Invasions, 2018)

Assessing the impact of an invasive bryophyte on plant species richness using high resolution imaging spectroscopy - Ewald, Michael; Skowronek, Sandra; Aerts, Raf; Lenoir, Jonathan; Feilhauer, Hannes; Van De Kerchove, Ruben; Honnay, Olivier; Somers, Ben; Garzón-López, Carol X.; Rocchini, Duccio; Schmidtlein, Sebastian (Ecological Indicators, 2020)
Remote sensing is commonly used to map the presence of invasive alien plant species across large areas. However, remote sensing also has potential to predict fractional cover, which is more closely linked to the potential ecosystem impact of invasive alien plant species. Here, we mapped the fractional cover of the invasive bryophyte Campylopus introflexus using high resolution imaging spectroscopy (233 bands, 490–2430 nm, 3 m × 3 m pixel size) in different habitat types within a coastal dune ecosystem. Maps were predicted from generalized partial least squares (gPLS) regression models trained with cover information from 266 field plots (3 m × 3 m). Models were calibrated using different data subsets, following a spatially blocked subsampling design. In addition, the relationship between C. introflexus fractional cover and plant species richness was evaluated using a subset of plot data. Fractional cover estimates from gPLS models resulted in R2 values of 0.64 ± 0.17 and an RMSE of 0.14 ± 0.02 based on independent validation data. Field observations showed a negative relationship between C. introflexus fractional cover and local plant species richness for pixels with a fractional cover above 44%. This threshold was exceeded in 4.3–7.1% of the studied area depending on the habitat type. Our study demonstrates that remote sensing can be used to map the fractional cover of an invasive bryophyte in a coastal dune ecosystem. Combining cover maps with a threshold value derived from an abundance-impact relationship we were able to highlight areas with potential negative impact on local plant species richness. This method can be implemented on other species and other ecosystem properties affected by plant invasions, allowing to highlight potential invasion impacts in a spatially explicit manner.
CRIS-Team Scopus Importer:2019-11-29
Keywords: Abundance-impact curves; Fractional cover threshold; Heath star moss; Hyperspectral remote sensing

A unified framework to model the potential and realized distributions of invasive species within the invaded range - Hattab, Tarek; Garzon-Lopez, Carol; Ewald, Michael; Skowronek, Sandra; Aerts, Raf; Horen, Helene; Brasseur, Boris; Gallet-Moron, Emilie; Spicher, Fabien; Decocq, Guillaume; Feilhauer, Hannes; Honnay, Olivier; et al. (Diversity and Distributions, 2017)
Aim: To propose a species distribution modelling framework and its companion "iSDM" R package for predicting the potential and realized distributions of invasive species within the invaded range.Location: Northern France.Methods: The non-equilibrium distribution of invasive species with the environment within the invaded range affects the environmental representativeness of species presence-absence data collected from the field and introduces uncertainty in observed absences as these may either reflect unsuitable sites or be incidental. To address these issues, we here propose an environmental systematic sampling design to collect presence-absence data from the field and a probability index to sort and subsequently separate environmental absences (EAs: reflecting environmentally unsuitable sites) from dispersal-limited absences (DLAs: reflecting sites out of dispersal reach). We first conducted a comprehensive test based on a virtual species to evaluate the performance of our framework. Then, we applied it on different life stages of a non-native tree species (Prunus serotina Ehrh.) invasive in Europe.Results: Regarding the potential distribution, we found higher model performances for both the virtual species (true skill statistics (TSS) > 0.75) and P. serotina (TSS >= 0.68) after carefully selecting absences with a low probability to be DLAs compared with classical models that incorporate both EAs and DLAs (e.g. TSS = 0.11 for P. serotina with 80% of DLAs). On the contrary, both EAs and DLAs as well as dispersal-related covariates were needed to capture the realized distribution of both the virtual species and P. serotina.Main Conclusions: Our framework helps overcoming the conceptual and methodological limitations of the disequilibrium in species' distribution models inherent to invasive species and enables managers to robustly estimate both the realized and potential distributions of invasive species. Although more relevant for modelling the distribution of non-native species, this framework can also be applied to native species.
Keywords: alien species; biological invasions; dispersal limitations; potential niche; realized niche; species distribution modelling; virtual species

Invasion by the Alien Tree Prunus serotina Alters Ecosystem Functions in a Temperate Deciduous Forest - Aerts, Raf; Ewald, Michael; Nicolas, Manuel; Piat, Jerome; Skowronek, Sandra; Lenoir, Jonathan; Hattab, Tarek; Garzon-Lopez, Carol; Feilhauer, Hannes; Schmidtlein, Sebastian; Rocchini, Duccio; Decocq, Guillaume; et al. (Frontiers in Plant Science, 2017)
Alien invasive species can affect large areas, often with wide-ranging impacts on ecosystem structure, function, and services. Prunus serotina is a widespread invader of European temperate forests, where it tends to form homogeneous stands and limits recruitment of indigenous trees. We hypotesized that invasion by P. serotina would be reflected in the nutrient contents of the native species' leaves and in the respiration of invaded plots as efficient resource uptake and changes in nutrient cycling by P. serotina probably underly its aggressive invasiveness. We combined data from 48 field plots in the forest of Compiegne, France, and data from an experiment using 96 microcosms derived from those field plots. We used general linear models to separate effects of invasion by P. serotina on heterotrophic soil and litter respiration rates and on canopy foliar nutrient content from effects of soil chemical properties, litter quantity, litter species composition, and tree species composition. In invaded stands, average respiration rates were 5.6% higher for soil (without litter) and 32% higher for soil and litter combined. Compared to indigenous tree species, P. serotina exhibited higher foliar N (+24.0%), foliar P (+50.7%), and lower foliar C:N (-22.4%) and N:P (-10.1%) ratios. P. serotina affected foliar nutrient contents of co-occuring indigenous tree species leading to decreased foliar N (-8.7 %) and increased C: N ratio (+9.5%) in Fagus sylvatica, decreased foliar N: P ratio in Carpinus betulus (-13.5%) and F. sylvatica (-11.8%), and increased foliar P in Pinus sylvestris (+12.3%) in invaded vs. uninvaded stands. Our results suggest that P. serotina is changing nitrogen, phosphorus, and carbon cycles to its own advantage, hereby increasing carbon turnover via labile litter, affecting the relative nutrient contents in the overstory leaves, and potentially altering the photosynthetic capacity of the long-lived indigenous broadleaved species. Uncontrolled invasion of European temperate forests by P. serotina may affect the climate change mitigation potential of these forests in the long term, through additive effects on local nutrient cycles.
Keywords: American black cherry; biological invasion; biogeochemical cycles; canopy foliar nutrients; heterotrophic respiration; litter; exotic species; invasive species

LiDAR derived forest structure data improves predictions of canopy N and P concentrations from imaging spectroscopy. - Ewald, Michael; Aerts, Raf; Lenoir, Jonathan; Fassnacht, Fabian; Nicolas, Manuel; Skowronek, Sandra; Piat, Jerome; Honnay, Olivier; Garzon-Lopez, Carol; Feilhauer, Hannes; Van De Kerchove, Ruben; Somers, Ben; et al. (Remote Sensing of Environment, 2018)

Mapping an invasive bryophyte species using hyperspectral remote sensing data - Skowronek, Sandra; Ewald, Michael; Isermann, Maike; Van De Kerchove, Ruben; Lenoir, Jonathan; Aerts, Raf; Warrie, Jens; Hattab, Tarek; Honnay, Olivier; Schmidtlein, Sebastian; Rocchini, Duccio; Somers, Ben; et al. (Biological Invasions, 2017)
Reliable distribution maps are crucial for the management of invasive plant species. An alternative to traditional field surveys is the use of remote sensing data, which allows coverage of large areas. However, most remote sensing studies on invasive plant species focus on mapping large stands of easily detectable study species. In this study, we used hyperspectral remote sensing data in combination with field data to derive a distribution map of an invasive bryophyte species, Campylopus introflexus, on the island of Sylt in Northern Germany. We collected plant cover data on 57 plots to calibrate the model and presence/absence data of C. introflexus on another 150 plots for independent validation. We simultaneously acquired airborne hyperspectral (APEX) images during summer 2014, providing 285 spectral bands. We used a Maxent modelling approach to map the distribution of C. introflexus. Although C. introflexus is a small and inconspicuous species, we were able to map its distribution with an overall accuracy of 75 %. Reducing the sampling effort from 57 to 7 plots, our models performed fairly well until sampling effort dropped below 12 plots. The model predicts that C. introflexus is present in about one quarter of the pixels in our study area. The highest percentage of C. introflexus is predicted in the dune grassland. Our findings suggest that hyperspectral remote sensing data have the potential to provide reliable information about the degree of bryophyte invasion, and thus provide an alternative to traditional field mapping approaches over large areas.
Keywords: Campylopus introflexus; Dunes; Heathland; Imaging spectroscopy; Maxent; Moss

Performance of one-class classifiers for invasive species mapping using airborne imaging spectroscopy - Skowronek, Sandra; Asner, Gregory P.; Feilhauer, Hannes (Ecological Informatics, 2017)
Most remote sensing approaches for mapping invasive plant species focus on species in a prominent phenological stage, such as during flowering, and do not systematically evaluate the performance for mapping lower cover fractions. In this study, we used airborne imaging spectroscopy (also known as hyperspectral imaging) to detect the invasive grass Phalaris aquatica and the invasive herb Centaurea solstitialis in a pre-flowering stage in the Jasper Ridge Biological Preserve, California, and compared the performance of three different one-class classifiers: Maxent, biased support vector machines and boosted regression trees. We collected presence data for C. solstitialis and P. aquatica to calibrate each approach and additional presence-absence data to validate model performance on 3 m × 3 m plots. The imaging spectroscopy data were acquired using the Carnegie Airborne Observatory Visible-to-Shortwave Infrared (VSWIR) imaging spectrometer (400–2500 nm range) with a pixel size of 1 m × 1 m. The resulting overall accuracies were 72–74% for C. solstitialis, and 83–88% for P. aquatica. For both species, the overall performance was slightly better for Maxent and BRT than for biased SVM. The detection rates for low cover plots were considerably higher for C. solstitialis than for P. aquatica. The models relied on different areas of the reflectance spectrum, but still produced the same general pattern of predicted species occurrences. We conclude that the different one-class classifiers allow for the detection and monitoring of target species with similar success rates.
Keywords: Biased support vector machine; Boosted regression trees; Carnegie airborne observatory; Centaurea solstitialis; Hyperspectral; Imaging spectroscopy; Maxent; Phalaris aquatica; Species distribution model; Vegetation; Yellow starthistle

Transferability of species distribution models for the detection of an invasive alien bryophyte using imaging spectroscopy data - Skowronek, Sandra; Van De Kerchove, Ruben; Rombouts, Bjorn; Aerts, Raf; Ewald, Michael; Warrie, Jens; Schiefer, Felix; Garzon-Lopez, Carol; Hattab, Tarek; Honnay, Olivier; Lenoir, Jonathan; Rocchini, Duccio; et al. (International Journal of Applied Earth Observation and Geoinformation, 2018)
Remote sensing is a promising tool for detecting invasive alien plant species. Mapping and monitoring those species requires accurate detection. So far, most studies relied on models that are locally calibrated and validated against available field data. Consequently, detecting invasive alien species at new study areas requires the acquisition of additional field data which can be expensive and time-consuming. Model transfer might thus provide a viable alternative. Here, we mapped the distribution of the invasive alien bryophyte Campyl opus introflexus to i) assess the feasibility of spatially transferring locally calibrated models for species detection between four different heathland areas in Germany and Belgium and ii) test the potential of combining calibration data from different sites in one species distribution model (SDM). In a first step, four different SDMs were locally calibrated and validated by combining field data and airborne imaging spectroscopy data with a spatial resolution ranging from 1.8 m to 4 m and a spectral resolution of about 10 nm (244 bands). A one-class classifier, Maxent, which is based on the comparison of probability densities, was used to generate all SDMs. In a second step, each model was transferred to the three other study areas and the performance of the models for predicting C. introfiexus occurrences was assessed. Finally, models combining calibration data from three study areas were built and tested on the remaining fourth site. In this step, different combinations of Maxent modelling parameters were tested. For the local models, the area under the curve for a test dataset (test AUC) was between 0.57-0.78, while the test AUC for the single transfer models ranged between 0.45-0.89. For the combined models the test AUC was between 0.54-0.9. The success of transferring models calibrated in one site to another site highly depended on the respective study site; the combined models provided higher test AUC values than the locally calibrated models for three out of four study sites. Furthermore, we also demonstrated the importance of optimizing the Maxent modelling parameters. Overall, our results indicate the potential of a combined model to map C. introf/exus without the need for new calibration data.
Keywords: Campylopus introflexus; Heath star moss; Hyperspectral; Maxent; Dune ecosystem; Model transfer