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4 Mapping spectral traits (ST) and spectral trait variations (STV) and their interactions with drivers and processes to monitor status, stress, and disturbances of vegetation diversity with hyperspectral remote sensing techniques. (From Lausch A. et al., 2016b. Remote Sens. 8, 1029. doi: 10.3390/RS8121029)
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In order to understand the significance of hyperspectral remote sensing (HRS) techniques and thus the spectral traits (ST) and spectral trait variations (STV) approach for recording, monitoring, and
assessing the status, stress, disturbances, or resource limitations of vegetation, it is first necessary to define both vegetation diversity and vegeta...
Citations
... First, this approach has potential for scaling up functional traits (Abelleira Martínez et al. 2016). During the last decade huge technological advancements have been made to measure CWM trait values and functional diversity from air-and spaceborne platforms (Jetz et al. 2016;Lausch and Leitão 2018), overcoming field work constraints. Especially the development of hyperspectral sensors has boosted this ability as they enable recording subtle differences in spectral features that are driven by traits and trait variation. ...
Worldwide, invasive alien plant species (IAS) threaten the biodiversity and the functioning of ecosystems. Most invasion research so far has focused on the properties underlying species invasiveness and community invasibility, yet IAS impact and the underlying causal pathways remain largely unknown. Here we dealt with this knowledge gap by extending the traditional functional trait framework to spectral data, by using traits estimated from reflectance measurements obtained through proximal field spectroscopy, as a surrogate for conventionally measured traits. We focused on two functionally distinct species that are invasive in Belgium: the annual forb Impatiens glandulifera Royle, and the rhizomatous perennial forb Solidago gigantea Ait. By means of trait-based linear mixed models and structural equation models we studied their impact on six ecosystem functions involved in the cycling of carbon and nutrients, and the mechanisms mediating these changes. Analyses based on either conventionally or optically measured traits revealed similar results: the IAS altered aboveground biomass (decrease and increase under I. glandulifera and S. gigantea respectively), litter stabilization (decrease under both IAS) and soil available phosphorus (increase under both IAS) through mass ratio effects, rather than through decreasing the functional diversity of the community. Whereas S. gigantea did so by shifting the community towards more conservative traits, I. glandulifera achieved this by making the community taller and richer in leaf nutrients. The use of remote sensing through optically measured traits, is not only useful to advance our understanding of the mechanisms and consequences of plant invasion, but may also be valuable to the broader field linking plant community composition to ecosystem functioning. Its potential for studying larger spatial scales over time may contribute to even more comprehensive insights.
Worldwide, grasslands form important ecosystems, providing essential habitats to a wide variety of species. However, these ecosystems experience various pressures, such as climate change and plant invasion, potentially affecting their functioning and thus jeopardizing the services and benefits they provide to humanity. Grassland conservation and restoration initiatives are thus important, and various policy frameworks have been set up. In support of such programs, it is essential to understand how these ecosystems function so that, based on scientific insights, effective management practices can be implemented, and progress towards policy goals can be monitored. The concept of plant functional traits highly contributes to such understanding. In fact, plant functional traits, being the morphological, physiological, biochemical and phenological characteristics that determine a plant’s fitness and function in general, indicate how plant communities respond to pressures and management actions on the one hand, and determine how such modifications result in changes in the functioning of, and services provided by, the ecosystem. However, the use of functional traits is to a great extent constrained by its limited potential for generalization across time and space. Therefore, promising alternative, or at least complementary, approaches deserve further study. In this dissertation, we investigated the potential of hyperspectral remote sensing technology to measure functional traits, also referred to as “optical traits”, and advance our understanding of the dynamics in grassland ecosystems. The research consisted of two parts: in a first, methodological, part (Chapters 2 and 3) we aimed to provide and recommend technical tools that enable grassland optical trait measurements; in a second, applied, part (Chapters 4 and 5) our intention was to demonstrate how these optical traits can in turn be adopted to assess plant community functioning and address more conceptual questions at the forefront of functional ecological research.
Reflectance can be recorded from various platforms, with different spatial and spectral resolutions, and subsequent quantification of optical traits can be accomplished using various signal processing techniques, with different technical strengths and weaknesses. Driven by a lack of knowledge on the reliability of these approaches, we performed a global meta-analysis, summarizing trait estimation accuracies reported in 77 studies (Chapter 2). We found that most studies have focused on a few traits only (chlorophyll, carotenoid, phosphorus, nitrogen, LAI, water and lignin), and estimation accuracy was generally high (R² ranged between 0.64 and 0.80, nRMSE ranged between 0.09 and 0.26). Our findings supported the increasing use of multivariate signal processing because they generally performed better than univariate approaches. Moreover, we found that the upscaling of existing methods to airborne and satellite data is promising, and may allow for functional mapping at broader spatial scales. Despite these technical recommendations and encouraging outlook, in practice, spectral measurements of individual herbaceous species in the field turned out challenging, because these species generally have tiny leaves and grow in ecosystems with small scale heterogeneity. Such information is highly valuable for many ecological applications, policy targets and species mapping exercises. Therefore, we developed a novel in situ measurement procedure (Chapter 3). The procedure consists of measuring monospecific arrangements of plant individuals on a black, light absorbing table, as such preserving structural plant properties, while avoiding confounding effects of other species, soil or non-photosynthetically active vegetation. In a case study, we demonstrated that the procedure enables an accurate representation of the spectral shape and amplitude of species, as well as functional trait differences between species.
Having clarified and advanced the technological and methodological capabilities of hyperspectral remote sensing for the quantification of grassland traits, this dissertation aimed at taking this know-how one step further to address two leading issues in functional and community ecology. The central idea was to deploy the combined strengths of functional traits and spectral reflectance, by integrating optical trait measurements in ecological analysis frameworks. First, we showed that emergent plant optical types (POTs), obtained through agglomerative hierarchical clustering of optical traits, are well suited to represent trait variation among locally co-occurring species (Chapter 4). Indeed, the resulting POTs better captured multidimensional trait variation among species than four commonly used pre-defined conventional plant functional types. Second, we demonstrated that optical traits can contribute to an enhanced understanding of the causal pathways of environmental and anthropogenic pressures on ecosystem functioning, more specifically by studying the case of plant invasion (Chapter 5). We focused on two functionally distinct species that are non-native and invasive in Belgium: the annual forb Impatiens glandulifera Royle, and the rhizomatous perennial forb Solidago gigantea Ait. We revealed that both invasive alien species (IAS) altered aboveground biomass (decrease and increase under I. glandulifera and S. gigantea respectively), litter stabilization (decrease under both IAS) and soil available phosphorus (increase under both IAS) through selection effects, rather than through decreasing the functional diversity of the community.
Together, our results indicate that hyperspectral remote sensing may lead to important insights into vegetation diversity and ecosystem dynamics. We propose that an interdisciplinary framework, coupling ecosystem functioning and remote sensing through optical traits, allows for a mechanistic understanding of ecological processes. The presented concepts can be easily extended to study various ecological cutting-edge issues, e.g. by including explicit links to ecosystem services or studying other drivers of change such climate change and fertilization. Moreover, the developed concepts entail promising perspectives for upscaling to larger spatial scales.
