Biology subjects

Bacaro, G.

Publications and source records attributed to Bacaro, G..

4 recordsLinked to original sources

bioRxiv2023

Plant spectral diversity from high-resolution multispectral imagery detects functional diversity patterns in coastal dune communities.

O_LIRemote sensing is a fundamental tool to monitor biodiversity over large spatial extents. However, it is still not clear whether spectral diversity (SD - variation of spectral response across a set of pixels) may represent a fast and reliable proxy for different biodiversity facets such as taxonomic (TD) and functional diversity (FD) across different spatial scales. C_LIO_LIWe used fine resolution (3 cm) multispectral imagery on coastal dune communities in Italy to explore SD patterns across spatial scales and assess SD relationships with TD and FD along the environmental gradient. C_LIO_LIWe measured TD as species richness, while SD and FD were computed using probability densities functions based on pixels and species position in multivariate spaces based on pixel values and traits, respectively. We assessed how SD is related to TD and FD, we compared SD and FD patterns in multivariate space occupation, and we explored diversity patterns across spatial scales using additive partitioning (i.e., plot, transect, and study area). C_LIO_LIWe found a strong correspondence between the patterns of occupation of the functional and spectral spaces and significant relationships were found along the environmental gradient. TD showed no significant relationships with SD. However, TD and SD showed higher variation at broader scale while most of FD variation occurred at plot level. C_LIO_LIBy measuring FD and SD with a common methodological framework, we demonstrate the potential of SD in approximating functional patterns in plant communities. We show that SD can retrieve information about FD at very small scale, which would otherwise require very intensive sampling efforts. Overall, we show that SD retrieved using high resolution images is able to capture different aspects of FD, so that the occupation of the spectral space is analogous to the occupation of the functional space. Studying the occupation of both spectral and functional space brings a more comprehensive understanding of the factors that influence the distribution and abundance of plant species across environmental gradients. C_LI

ecology↗

bioRxiv2021

rasterdiv - an Information Theory tailored R package for measuring ecosystem heterogeneity from space: to the origin and back

O_LIEcosystem heterogeneity has been widely recognized as a key ecological feature, influencing several ecological functions, since it is strictly related to several ecological functions like diversity patterns and change, metapopulation dynamics, population connectivity, or gene flow. C_LIO_LIIn this paper, we present a new R package - rasterdiv - to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. C_LIO_LIThe rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open source algorithms. C_LI

ecology↗

bioRxiv2021

From zero to infinity: minimum to maximum diversity of the planet by spatio-parametric Rao's quadratic entropy

AimThe majority of work done to gather information on Earth diversity has been carried out by in-situ data, with known issues related to epistemology (e.g., species determination and taxonomy), spatial uncertainty, logistics (time and costs), among others. An alternative way to gather information about spatial ecosystem variability is the use of satellite remote sensing. It works as a powerful tool for attaining rapid and standardized information. Several metrics used to calculate remotely sensed diversity of ecosystems are based on Shannons Information Theory, namely on the differences in relative abundance of pixel reflectances in a certain area. Additional metrics like the Raos quadratic entropy allow the use of spectral distance beside abundance, but they are point descriptors of diversity, namely they can account only for a part of the whole diversity continuum. The aim of this paper is thus to generalize the Raos quadratic entropy by proposing its parameterization for the first time. InnovationThe parametric Raos quadratic entropy, coded in R, i) allows to represent the whole continuum of potential diversity indices in one formula, and ii) starting from the Raos quadratic entropy, allows to explicitly make use of distances among pixel reflectance values, together with relative abundances. Main conclusionsThe proposed unifying measure is an integration between abundance- and distance-based algorithms to map the continuum of diversity given a satellite image at any spatial scale.

ecology↗

bioRxiv2020

Measuring diversity from space: a global view of the free and open source rasterdiv R package under a coding perspective

The variation of species diversity over space and time has been widely recognised as a key challenge in ecology. However, measuring species diversity over large areas might be difficult for logistic reasons related to both time and cost savings for sampling, as well as accessibility of remote ecosystems. In this paper, we present a new R package - rasterdiv - to calculate diversity indices based on remotely sensed data, by discussing the theory beyond the developed algorithms. Obviously, measures of diversity from space should not be viewed as a replacement of in-situ data on biological diversity, but they are rather complementary to existing data and approaches. In practice, they integrate available information of Earth surface properties, including aspects of functional (structural, biophysical and bio-chemical), taxonomic, phylogenetic and genetic diversity. Making use of the rasterdiv package can result useful in making multiple calculations based on reproducible open source algorithms, robustly rooted in Information Theory.

ecology↗