Biology subjects

Ricotta, C.

Publications and source records attributed to Ricotta, C..

10 recordsLinked to original sources

bioRxiv2026

Rocking around the pheno-clock: bridging vegetation phenology and chronobiology

Plant phenology controls resource acquisition, survival and reproductive success, yet it is still commonly reduced to a limited set of calendar-based metrics, such as discrete dates of budburst or senescence. By contrast, chronobiology quantifies biological rhythms from full activity profiles using metrics that capture timing, regularity and amplitude of rest-activity cycles. Here, we bridge these two perspectives by developing a pheno-clock framework that translates plant phenology into chrono-ecological properties. We applied actigraphy-inspired metrics to multi-year satellite time series of European beech (Fagus sylvatica) forests across their European range. From daily photothermal activity profiles, we derived indices describing the strength, fragmentation and amplitude of annual rest-activity rhythms and related them to classical phenological metrics and regional climate. Our results reveal a marked asymmetry between spring and autumn phenology, indicating that canopy decline is governed by the cumulative organization of annual energy input, whereas canopy activation is dominated by short-term forcing. Across biogeographical regions, beech forests segregate into distinct pheno-chronotypes that differ in the timing and consolidation of rest and activity phases rather than in growing-season length alone. These chrono-ecological patterns suggest that climate filters not only when forests grow, but also how they structure their annual rhythmicity. By importing chronobiology into plant phenology, the pheno-clock framework provides a transferable approach to describe and compare seasonal strategies in plants, opening new avenues to link phenological diversity, functional traits and ecosystem responses to environmental change.

ecology↗

bioRxiv2024

A new look at functional beta diversity

O_LIThe variability in species composition among a set of sampling sites, or beta diversity, is considered a key signature of the ecological processes that shape the spatial structure of species assemblages. C_LIO_LIIn this paper, we propose to decompose this variability into three additive components: i) the standard compositional similarity between individuals of the same species among sites, ii) the degree of functional dissimilarity between individuals of distinct species among sites, and iii) the degree of functional similarity between individuals of distinct species among sites. These three components can be used to portray the functional resemblance among sites on a ternary diagram. C_LIO_LIThe potential of this method is shown with real data on the functional turnover of Alpine species along a primary succession on glacial deposits in northern Italy. C_LIO_LISynthesis. With the resulting ternary diagram of functional resemblance we can relate various aspects of taxonomic and functional variability among sites to community assembly processes more completely than just looking at individual components. C_LI

ecology↗

bioRxiv2023

Functional and phylogenetic β diversities and their link with clustering/overdispersion and uniqueness/redundancy

In the recent decades, research on biodiversity in community ecology has been marked by the consideration of species evolutionary histories and biological traits, including those said functional as they relate to the functions a species has in ecosystems. Among the different spatial levels at which FP diversity can be quantified, less attention has been given to the definition of the general concept of between-communities ({beta}) FP diversity than to those of local, within-communities () and regional, merged-communities ({gamma}) FP diversities. Here we develop a new way for partitioning FP {beta} diversity into elementary components to underline how and why FP {beta} diversity differs from species {beta} diversity, the latter reflecting only differences in species abundances between communities. As a reference example, we consider two distinct measures of FP {beta} diversity: Raos dissimilarity coefficient (Q{beta}) that expresses an average dissimilarity between communities, and its transformation into an equivalent number of communities (D{beta}). Thanks to analytical partitioning and simulations, we show that Q{beta} and D{beta} are connected differently with typical patterns of community structure. The search for the ecological and evolutionary processes that drive community assembly and the assessment of community resilience and stability have indeed revealed typical community structures: the local clustering of species with similar traits or shared evolutionary histories; and the local () or regional ({gamma}) presence of functionally or phylogenetically redundant versus unique species. While Q{beta} and D{beta} are both increasing functions of species {beta} diversity and {gamma} FP uniqueness, Q{beta} increases with FP clustering while D{beta} increases with FP redundancy. The selection of an index of {beta} diversity for a given study depends on its objective, such as communication to conservation policy makers or theoretical study of the ecological and evolutionary processes of community assembly. To facilitate and secure this selection, we call, through our study, for the development of formal and precise definition(s) for FP {beta} diversity in light of the concepts of clustering versus overdispersion, and redundancy versus uniqueness. In particular, we call for further research on when and why FP {beta} diversity should increase with FP clustering.

ecology↗

bioRxiv2022

Identifying functionally distinctive and threatened species

Functional traits determine species responses to environmental change and/or determine species effects on ecosystem functions. When species with distinctive functional traits are threatened, there is a risk that ecosystem properties are also threatened. This is because functionally distinctive species may be those that have irreplaceable roles in an ecosystem and/or those that would be able to survive unusual environmental disturbances. To include functional distinctiveness as a criterion in conservation strategies, we need formal quantification of the degree of distinctiveness and threat a species exhibits. Starting with previous quantification attempts, we develop a framework that links different viewpoints on functional distinctiveness and accounts for all species extinction probabilities. Our framework is particularly relevant at the local scale where species extinctions impact ecosystem functioning and where conservation policies are developed. As a case study, we thus applied our framework to the mammals of Indian dry forests known to be threatened with a drastic decrease in functional diversity. We notably highlight that although some of the functionally distinctive and threatened species we identified, such as the tiger, are charismatic and considered by conservation actions, others are not. This is the case for some rat species and pangolins, whose negative image in the media during the COVID-19 pandemic could be detrimental to attracting public interest in their preservation. From this case study, we note that noncharismatic, less known species that may be key for ecosystems could be revealed by applying our framework to a range of ecosystems and taxa.

ecology↗

bioRxiv2021

An updated framework to account for inter-individual variability when quantifying phenotypic variation

O_LIIn trait-based ecology, phenotypic variation (PVar) is often quantified with measures that express average differences between populations standardized in the range 0-1. A major problem with these measures is that they disregard the within-population trait variability. In addition, most of these measures cannot be decomposed across scales. This can alter their interpretation, thus limiting their applicability. C_LIO_LITo overcome these problems, we propose a new measure, the Phenotypic Dissimilarity Index (PhD) that is insensitive to the within-population interindividual trait variability. Likewise, PhD can be used to quantify PVar between individuals in a population while accounting for the PVar within individuals. C_LIO_LIUsing simulated and real data, we showed that PhD index correctly quantifies PVar when the within-population trait variability is not negligible, as in many ecological studies. By accounting for within-population trait variability, the PhD index generally provides a more parsimonious quantification of PVar across an environmental gradient compared to other estimators. C_LIO_LITraits sampled within a species have an inherent variability. Accounting for such variability is essential to understand species phenotypic responses to environmental cues. As such, the PhD index will provide ecologists with an asset to reliably quantify and compare PVar within and between species across environmental gradients at different scales. We also provide an R function to calculate the PhD index. C_LI

ecology↗

bioRxiv2021

On the relationships between rarity, uniqueness, distinctiveness, originality and functional/phylogenetic diversity

Rarity reflects the low abundance of a species while distinctiveness reflects its quality of being easy to recognize because it has unique functional characteristics and/or an isolated phylogenetic position. As such, the assemblage-level rarity of a species functional and phylogenetic characteristics (that we name effective originality) results from both the rarity and the distinctiveness of this species. The functional and phylogenetic diversity of an assemblage then results from a compromise between the abundances and the effective originalities of the species it contains. Although the distinctiveness of a species itself depends on the abundance of the other species in the assemblage, distinctiveness indices that are available in the ecological literature scarcely consider abundance data. We develop a unifying framework that demonstrates the direct connections between measures of diversity, rarity, distinctiveness and effective originality. While developing our framework, we discovered a family of distinctiveness indices that permit a full control of the influence one wants to give to the strict uniqueness of a species (=its smallest functional or phylogenetic distance to another species in the assemblage). Illustrating our framework with bat phylogenetic diversity along a disturbance gradient in Mexico, we show how each component of rarity, distinctiveness and originality can be controlled to obtain efficient indicators for conservation. Overall our framework is aimed to improve conservation actions directed towards highly diverse areas and/or towards species whose loss would considerably decrease biodiversity by offering flexible quantitative tools where the influence of abundant versus rare, and ordinary versus original, species is understood and controlled.

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↗

bioRxiv2021

Towards a unifying framework for diversity and dissimilarity coefficients

Diversity and dissimilarity within and between species assemblages have now been studied for more than half a century by community ecologists in relation to their connections with ecosystem functioning. However, a generalized framework that puts diversity and dissimilarity coefficients under the same formal umbrella is still lacking. In this paper, we show that generalized means represent an effective tool to develop a unifying formulation for the construction of a large array of parametric diversity and dissimilarity measures. These measures include some of the classical diversity coefficients, such as the Shannon entropy, the Gini-Simpson index or the parametric diversity of Patil and Taillie, together with a large number of dissimilarity coefficients of the Bray-Curtis family and can be further extended to the measurement of functional and phylogenetic differences within and between plots.

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↗