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; Kerchove, Ruben Van De; Honnay, Olivier; Somers, Ben; Garzón‐López, Carol X.; Rocchini, Duccio; Schmidtlein, Sebastian

doi:10.1016/j.ecolind.2019.105882

Cited by 7 publications

(3 citation statements)

References 64 publications

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“…Furthermore, scarcely vegetated patches can also contribute to species numbers. For example, in harsh environments such as coastal dune ecosystems, many focal species are small and occur in a very fine mosaic pattern of bare sand and vegetation (e.g., Ewald et al, 2020). Such areas may face the risk of being masked even though making a notable contribution to the species numbers.…”

Section: High Contrast Land Surfaces Will Increase Spectral Variationmentioning

confidence: 99%

About the link between biodiversity and spectral variation

Fassnacht

Malavasi

Schmidtlein

2022

Applied Vegetation Science

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Aim The spectral variability hypothesis (SVH) suggests a link between spectral variation and plant biodiversity. The underlying assumptions are that higher spectral variation in canopy reflectance (depending on scale) is caused by either (1) variation in habitats or linked vegetation types or plant communities with their specific optical community traits or (2) variation in the species themselves and their specific optical traits. Methods The SVH was examined in several empirical remote‐sensing case studies, which often report some correlation between spectral variation and biodiversity‐related variables (mostly plant species counts); however, the strength of the observed correlations varies between studies. In contrast, studies focussing on understanding the causal relationship between (plant) species counts and spectral variation remain scarce. Here, we discuss these causal relationships and support our perspectives through simulations and experimental data. Results We reveal that in many situations the spectral variation caused by species or functional traits is subtle in comparison to other factors such as seasonality and physiological status. Moreover, the degree of contrast in reflectance has little to do with the number but rather with the identity of the species or communities involved. Hence, spectral variability should not be expressed based on contrast but rather based on metrics expressing manifoldness. While we describe cases where a certain link between spectral variation and plant species diversity can be expected, we believe that as a scientific hypothesis (which suggests a general validity of this assumed relationship) the SVH is flawed and requires refinement. Conclusions To this end we call for more research examining the drivers of spectral variation in vegetation canopies and their link to plant species diversity and biodiversity in general. Such research will allow critically assessing under which conditions spectral variation is a useful indicator for biodiversity monitoring and how it could be integrated into monitoring networks.

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Section: High Contrast Land Surfaces Will Increase Spectral Variationmentioning

confidence: 99%

About the link between biodiversity and spectral variation

Fassnacht

Malavasi

Schmidtlein

2022

Applied Vegetation Science

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“…However, this result should not be neglected as it relates well to the use of remote sensing techniques for monitoring invasive alien plants across vast areas [64]. Many studies have demonstrated the capability of remote sensing approaches to detect invasive plant species and to map their distribution [65][66][67][68][69][70] and certainly the use of the Rao's Q heterogeneity index in anthropogenic landscapes could be a powerful method to identify those areas potentially more prone to biological invasion.…”

Section: Discussionmentioning

confidence: 99%

Use of Remote Sensing Techniques to Estimate Plant Diversity within Ecological Networks: A Worked Example

2022

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As there is an urgent need to protect rapidly declining global diversity, it is important to identify methods to quickly estimate the diversity and heterogeneity of a region and effectively implement monitoring and conservation plans. The combination of remotely sensed and field-collected data, under the paradigm of the Spectral Variation Hypothesis (SVH), represents one of the most promising approaches to boost large-scale and reliable biodiversity monitoring practices. Here, the potential of SVH to capture information on plant diversity at a fine scale in an ecological network (EN) embedded in a complex landscape has been tested using two new and promising methodological approaches: the first estimates α and β spectral diversity and the latter ecosystem spectral heterogeneity expressed as Rao’s Quadratic heterogeneity measure (Rao’s Q). Both approaches are available thanks to two brand-new R packages: “biodivMapR” and “rasterdiv”. Our aims were to investigate if spectral diversity and heterogeneity provide reliable information to assess and monitor over time floristic diversity maintained in an EN selected as an example and located in northeast Italy. We analyzed and compared spectral and taxonomic α and β diversities and spectral and landscape heterogeneity, based on field-based plant data collection and remotely sensed data from Sentinel-2A, using different statistical approaches. We observed a positive relationship between taxonomic and spectral diversity and also between spectral heterogeneity, landscape heterogeneity, and the amount of alien species in relation to the native ones, reaching a value of R2 = 0.36 and R2 = 0.43, respectively. Our results confirmed the effectiveness of estimating and mapping α and β spectral diversity and ecosystem spectral heterogeneity using remotely sensed images. Moreover, we highlighted that spectral diversity values become more effective to identify biodiversity-rich areas, representing the most important diversity hotspots to be preserved. Finally, the spectral heterogeneity index in anthropogenic landscapes could be a powerful method to identify those areas most at risk of biological invasion.

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“…Ecological studies have benefited from UAV-borne remote sensing technology, and its potential is thought to have revolutionized ecology and conservation [13], especially in developing countries where research and cost-effective monitoring schemes are urgently needed. However, high ecosystem complexity results in painstaking and costly fieldwork campaigns.…”

Section: Introductionmentioning

confidence: 99%

Species Classification in a Tropical Alpine Ecosystem Using UAV-Borne RGB and Hyperspectral Imagery

Garzón‐López

Lasso

2020

Drones

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Páramos host more than 3500 vascular plant species and are crucial water providers for millions of people in the northern Andes. Monitoring species distribution at large scales is an urgent conservation priority in the face of ongoing climatic changes and increasing anthropogenic pressure on this ecosystem. For the first time in this ecosystem, we explored the potential of unoccupied aerial vehicles (UAV)-borne red, green, and blue wavelengths (RGB) and hyperspectral imagery for páramo species classification by collecting both types of images in a 10-ha area, and ground vegetation cover data from 10 plots within this area. Five plots were used for calibration and the other five for validation. With the hyperspectral data, we tested our capacity to detect five representative páramo species with different growth forms using support vector machine (SVM) and random forest (RF) classifiers in combination with three feature selection methods and two class groups. Using RGB images, we could classify 21 species with an accuracy greater than 97%. From hyperspectral imaging, the highest accuracy (89%) was found using models built with RF or SVM classifiers combined with a binary grouping method and the sequential floating forward selection feature. Our results demonstrate that páramo species can be accurately mapped using both RGB and hyperspectral imagery.

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Assessing the impact of an invasive bryophyte on plant species richness using high resolution imaging spectroscopy

Cited by 7 publications

References 64 publications

About the link between biodiversity and spectral variation

About the link between biodiversity and spectral variation

Use of Remote Sensing Techniques to Estimate Plant Diversity within Ecological Networks: A Worked Example

Species Classification in a Tropical Alpine Ecosystem Using UAV-Borne RGB and Hyperspectral Imagery

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