Components of functional diversity revisited: A new classification and its theoretical and practical implications.

Functional diversity is regarded as a key concept for understanding the link between ecosystem function and biodiversity. The different and ecologically well-defined aspects of the concept are reflected by the so-called functional components, for example, functional richness and divergence. Many authors proposed that components be distinguished according to the multivariate technique on which they rely, but more recent studies suggest that several multivariate techniques, providing different functional representations (such as dendrograms and ordinations) of the community can in fact express the same functional component. Here, we review the relevant literature and find that (1) general ecological acceptance of the field is hampered by ambiguous terminology and (2) our understanding of the role of multivariate techniques in defining components is unclear. To address these issues, we provide new definitions for the three basic functional diversity components namely functional richness, functional divergence and functional regularity. In addition, we present a classification of presence-/absence-based approaches suitable for quantifying these components. We focus exclusively on the binary case for its relative simplicity. We find illogical, as well as logical but unused combinations of components and representations; and reveal that components can be quantified almost independently from the functional representation of the community. Finally, theoretical and practical implications of the new classification are discussed.

The Spectral Species Concept in Living Color.

Biodiversity monitoring is an almost inconceivable challenge at the scale of the entire Earth. The current (and soon to be flown) generation of spaceborne and airborne optical sensors (i.e., imaging spectrometers) can collect detailed information at unprecedented spatial, temporal, and spectral resolutions. These new data streams are preceded by a revolution in modeling and analytics that can utilize the richness of these datasets to measure a wide range of plant traits, community composition, and ecosystem functions. At the heart of this framework for monitoring plant biodiversity is the idea of remotely identifying species by making use of the 'spectral species' concept. In theory, the spectral species concept can be defined as a species characterized by a unique spectral signature and thus remotely detectable within pixel units of a spectral image. In reality, depending on spatial resolution, pixels may contain several species which renders species-specific assignment of spectral information more challenging. The aim of this paper is to review the spectral species concept and relate it to underlying ecological principles, while also discussing the complexities, challenges and opportunities to apply this concept given current and future scientific advances in remote sensing.

Phenotypic dissimilarity index: Correcting for intra- and interindividual variability when quantifying phenotypic variation.

In trait-based ecology, phenotypic variation (PVar) is often quantified with measures expressing average differences between populations standardized in the range 0-1. However, these measures disregard the within-population trait variability. In addition, some of them cannot be partitioned between populations. These aspects can either alter their interpretation or limit their applicability. To overcome these problems, we propose a new measure, the phenotypic dissimilarity (PhD) index, to quantify PVar between populations in scenarios of varying within-population interindividual trait variability. PhD can also quantify within-population PVar while accounting for intraindividual trait variability. Using simulated and real data, we show that using the PhD index becomes important when the within-population trait variability is not negligible, as in all ecological studies. By accounting for within-population trait variability, the PhD index does not overestimate PVar across an environmental gradient compared to other estimators. Traits inherently vary within species. Accounting for such variability is essential to understanding species' phenotypic responses to environmental cues. The proposed PhD index will provide ecologists with a tool for quantifying PVar within species and compare it between species at different levels of biological organization. We provide an R function to calculate the PhD index.

rasterdiv-An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back.

Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow.In 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.The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms.

The worldwide impact of urbanisation on avian functional diversity.

Urbanisation is driving rapid declines in species richness and abundance worldwide, but the general implications for ecosystem function and services remain poorly understood. Here, we integrate global data on bird communities with comprehensive information on traits associated with ecological processes to show that assemblages in highly urbanised environments have substantially different functional composition and 20% less functional diversity on average than surrounding natural habitats. These changes occur without significant decreases in functional dissimilarity between species; instead, they are caused by a decrease in species richness and abundance evenness, leading to declines in functional redundancy. The reconfiguration and decline of native functional diversity in cities are not compensated by the presence of exotic species but are less severe under moderate levels of urbanisation. Thus, urbanisation has substantial negative impacts on functional diversity, potentially resulting in impaired provision of ecosystem services, but these impacts can be reduced by less intensive urbanisation practices.

Quantifying evenness and linking it to diversity, beta diversity, and similarity.

An enormous number of measures based on different criteria have been proposed to quantify evenness or unevenness among species relative abundances in an assemblage. However, a unified approach that can encompass most of the widely used indices is still lacking. Here, we first present some basic requirements for an evenness measure. We then propose that unevenness among species relative abundances in an assemblage can be measured by a normalized divergence between the vector of species relative abundances and the mean vector, where the mean vector represents the species relative abundances of a completely even assemblage. Thus, evenness among species relative abundances is measured by the corresponding normalized extent of closeness between these two vectors. We consider five divergence measures, leading to five classes of evenness indices. All our evenness measures are in terms of diversity (Hill number) of order q > 0 (here q controls the weighting of species relative abundances) and species richness (diversity of order q = 0). We propose quantifying evenness through a continuous profile that depicts evenness as a function of diversity order q > 0. The profiles can be easily and visually compared across multiple assemblages. Our evenness indices satisfy all the requirements presented in this paper and encompass many widely used evenness measures as special cases. When there are multiple assemblages, the abundance-based Jaccard- and Sørensen-type dissimilarity measures (which are monotonic functions of beta diversity) can be expressed as weighted averages of the individual species' compositional unevenness values; here, each individual species' compositional unevenness is calculated based on that species' abundances among assemblages. The contribution of a species to each dissimilarity measure can be clearly disentangled and quantified in terms of this single species' compositional unevenness among assemblages. Thus, our framework links the concepts of evenness, diversity, beta diversity, and similarity. Moreover, the framework can be readily extended to a phylogenetic version. A real data example is used to illustrate our approach. We also discuss some criteria and other measures that were previously proposed in the literature.

A new method for quantifying the phylogenetic redundancy of biological communities.

The increasing use of phylogenetic methods in community ecology recognizes that accumulated evolutionary differences among species mirror, to some extent, ecological processes. The scope of this work is thus to propose a new method for the measurement of community-level phylogenetic redundancy, which takes into account the branching pattern of the underlying phylogeny. Like for functional redundancy, a measure of phylogenetic redundancy can be described as a normalized measure in the range (0-1) that relates the observed community-level phylogenetic diversity to the value of a hypothetical assemblage with the same abundance distribution of the focal community in which all species had independent evolution. Therefore, phylogenetic redundancy can be interpreted as the diversity decrease that is obtained by taking into account the evolutionary relationships among species in the calculation of diversity. The behavior of the proposed method, for which we provide a simple R function called 'phyloredundancy', was evaluated with published data on Alpine plant communities along a primary succession on a glacier foreland in northern Italy. As shown by our results, the method accounts for the length of shared branches in the phylogeny, producing a coherent framework for describing the evolutionary relationships within a species assemblage. Being based on classical diversity measures, which have been used in ecology for decades, it also has a great potential for future research in phylogenetic community ecology.

Of beta diversity, variance, evenness, and dissimilarity.

The amount of variation in species composition among sampling units or beta diversity has become a primary tool for connecting the spatial structure of species assemblages to ecological processes. Many different measures of beta diversity have been developed. Among them, the total variance in the community composition matrix has been proposed as a single-number estimate of beta diversity. In this study, I first show that this measure summarizes the compositional variation among sampling units after nonlinear transformation of species abundances. Therefore, it is not always adequate for estimating beta diversity. Next, I propose an alternative approach for calculating beta diversity in which variance is substituted by a weighted measure of concentration (i.e., an inverse measure of evenness). The relationship between this new measure of beta diversity and so-called multiple-site dissimilarity measures is also discussed.

Anticipating species distributions: Handling sampling effort bias under a Bayesian framework.

Anticipating species distributions in space and time is necessary for effective biodiversity conservation and for prioritising management interventions. This is especially true when considering invasive species. In such a case, anticipating their spread is important to effectively plan management actions. However, considering uncertainty in the output of species distribution models is critical for correctly interpreting results and avoiding inappropriate decision-making. In particular, when dealing with species inventories, the bias resulting from sampling effort may lead to an over- or under-estimation of the local density of occurrences of a species. In this paper we propose an innovative method to i) map sampling effort bias using cartogram models and ii) explicitly consider such uncertainty in the modeling procedure under a Bayesian framework, which allows the integration of multilevel input data with prior information to improve the anticipation species distributions.

A family of functional dissimilarity measures for presence and absence data.

Plot-to-plot dissimilarity measures are considered a valuable tool for understanding the complex ecological mechanisms that drive community composition. Traditional presence/absence coefficients are usually based on different combinations of the matching/mismatching components of the 2 × 2 contingency table. However, more recently, dissimilarity measures that incorporate information about the degree of functional differences between the species in both plots have received increasing attention. This is because such "functional dissimilarity measures" capture information on the species' functional traits, which is ignored by traditional coefficients. Therefore, functional dissimilarity measures tend to correlate more strongly with ecosystem-level processes, as species influence these processes via their traits. In this study, we introduce a new family of dissimilarity measures for presence and absence data, which consider functional dissimilarities among species in the calculation of the matching/mismatching components of the 2 × 2 contingency table. Within this family, the behavior of the Jaccard coefficient, together with its additive components, species replacement, and richness difference, is examined by graphical comparisons and ordinations based on simulated data.

A multivariate approach for mapping fire ignition risk: the example of the National Park of Cilento (southern Italy).

Recent advances in fire management led landscape managers to adopt an integrated fire fighting strategy in which fire suppression is supported by prevention actions and by knowledge of local fire history and ecology. In this framework, an accurate evaluation of fire ignition risk and its environmental drivers constitutes a basic step toward the optimization of fire management measures. In this paper, we propose a multivariate method for identifying and spatially portraying fire ignition risk across a complex and heterogeneous landscape such as the National Park of Cilento, Vallo di Diano, and Alburni (southern Italy). The proposed approach consists first in calculating the fire selectivity of several landscape features that are usually related to fire ignition, such as land cover or topography. Next, the fire selectivity values of single landscape features are combined with multivariate segmentation tools. The resulting fire risk map may constitute a valuable tool for optimizing fire prevention strategies and for efficiently allocating fire fighting resources.

Mapping forest fuels through vegetation phenology: the role of coarse-resolution satellite time-series.

Traditionally fuel maps are built in terms of 'fuel types', thus considering the structural characteristics of vegetation only. The aim of this work is to derive a phenological fuel map based on the functional attributes of coarse-scale vegetation phenology, such as seasonality and productivity. MODIS NDVI 250 m images of Sardinia (Italy), a large Mediterranean island with high frequency of fire incidence, were acquired for the period 2000-2012 to construct a mean annual NDVI profile of the vegetation at the pixel-level. Next, the following procedure was used to develop the phenological fuel map: (i) image segmentation on the Fourier components of the NDVI profiles to identify phenologically homogeneous landscape units, (ii) cluster analysis of the phenological units and post-hoc analysis of the fire-proneness of the phenological fuel classes (PFCs) obtained, (iii) environmental characterization (in terms of land cover and climate) of the PFCs. Our results showed the ability of coarse-resolution satellite time-series to characterize the fire-proneness of Sardinia with an adequate level of accuracy. The remotely sensed phenological framework presented may represent a suitable basis for the development of fire distribution prediction models, coarse-scale fuel maps and for various biogeographic studies.

Modelling the meteorological forest fire niche in heterogeneous pyrologic conditions.

Fire regimes are strongly related to weather conditions that directly and indirectly influence fire ignition and propagation. Identifying the most important meteorological fire drivers is thus fundamental for daily fire risk forecasting. In this context, several fire weather indices have been developed focussing mainly on fire-related local weather conditions and fuel characteristics. The specificity of the conditions for which fire danger indices are developed makes its direct transfer and applicability problematic in different areas or with other fuel types. In this paper we used the low-to-intermediate fire-prone region of Canton Ticino as a case study to develop a new daily fire danger index by implementing a niche modelling approach (Maxent). In order to identify the most suitable weather conditions for fires, different combinations of input variables were tested (meteorological variables, existing fire danger indices or a combination of both). Our findings demonstrate that such combinations of input variables increase the predictive power of the resulting index and surprisingly even using meteorological variables only allows similar or better performances than using the complex Canadian Fire Weather Index (FWI). Furthermore, the niche modelling approach based on Maxent resulted in slightly improved model performance and in a reduced number of selected variables with respect to the classical logistic approach. Factors influencing final model robustness were the number of fire events considered and the specificity of the meteorological conditions leading to fire ignition.

A new measure of functional evenness and some of its properties.

Functional evenness is increasingly considered an important facet of functional diversity that sheds light on the complex relationships between community assembly and ecosystem functioning. Nonetheless, in spite of its relevant role for ecosystem functioning, only a few measures of functional evenness have been proposed. In this paper we introduce a new measure of functional evenness that reflects the regularity in the distribution of species abundances, together with the evenness in their pairwise functional dissimilarities. To show how the proposed measure works, we focus on changes in functional evenness calculated from Grime's classification of plant strategies as competitors (C), stress-tolerators (S) and ruderals (R) along a post-fire successional gradient in temperate chestnut forests of southern Switzerland.

Modeling the landscape drivers of fire recurrence in Sardinia (Italy).

Although recurrent fire events with very short return periods have the most dangerous effects on landscape degradation, only a few papers have explored the landscape ecological factors that drive the probability of fire recurrence. In this paper we apply a habitat suitability model for analyzing the spatial relationship between a selected set of landscape factors (mainly land use types) and fire recurrence in Sardinia (Italy) in the years 2005-2010. Our results point out that fire occurrence in already burned areas is lower than expected in natural and semi-natural land cover types, like forest and shrublands. To the contrary, like in all regions where human activity is the main source of fire ignitions, the probability of fire recurrence is higher at low altitudes and close to roads and to urban and agricultural land cover types, thus showing marked preference for those landscape factors denoting higher anthropogenic ignition risk.

Geographical constraints are stronger than invasion patterns for European urban floras.

Understanding the mechanisms that affect invasion success of alien species is an important prerequisite for the effective management of present and future aliens. To gain insight into this matter we asked the following questions: Are the geographical patterns of species distributions in urban floras different for native compared with alien plant species? Does the introduction of alien species contribute to the homogenization of urban floras? We used a Mantel test on Jaccard dissimilarity matrices of 30 urban floras across the British Isles, Italy and central Europe to compare the spatial distribution of native species with four classes of alien species: archaeophytes, all neophytes, non-invasive neophytes, and invasive neophytes. Archaeophytes and neophytes are species that were introduced into Europe before and after 1500 AD, respectively. To analyze the homogenizing effect of alien species on the native urban floras, we tested for differences in the average dissimilarity of individual cities from their group centroid in ordination space. Our results show that the compositional patterns of native and alien species seem to respond to the same environmental drivers, such that all four classes of alien species were significantly related to native species across urban floras. In this framework, alien species may have an impact on biogeographic patterns of urban floras in ways that reflect their history of introduction and expansion: archaeophytes and invasive neophytes tended to homogenize, while non-invasive neophytes tended to differentiate urban floras.

Testing for phylogenetic signal in biological traits: the ubiquity of cross-product statistics.

To evaluate rates of evolution, to establish tests of correlation between two traits, or to investigate to what degree the phylogeny of a species assemblage is predictive of a trait value so-called tests for phylogenetic signal are used. Being based on different approaches, these tests are generally thought to possess quite different statistical performances. In this article, we show that the Blomberg et al. K and K*, the Abouheif index, the Moran's I, and the Mantel correlation are all based on a cross-product statistic, and are thus all related to each other when they are associated to a permutation test of phylogenetic signal. What changes is only the way phylogenetic and trait similarities (or dissimilarities) among the tips of a phylogeny are computed. The definitions of the phylogenetic and trait-based (dis)similarities among tips thus determines the performance of the tests. We shortly discuss the biological and statistical consequences (in terms of power and type I error of the tests) of the observed relatedness among the statistics that allow tests for phylogenetic signal. Blomberg et al. K* statistic appears as one on the most efficient approaches to test for phylogenetic signal. When branch lengths are not available or not accurate, Abouheif's Cmean statistic is a powerful alternative to K*.

Urban ecosystem services: tree diversity and stability of tropospheric ozone removal.

Urban forests provide important ecosystem services, such as urban air quality improvement by removing pollutants. While robust evidence exists that plant physiology, abundance, and distribution within cities are basic parameters affecting the magnitude and efficiency of air pollution removal, little is known about effects of plant diversity on the stability of this ecosystem service. Here, by means of a spatial analysis integrating system dynamic modeling and geostatistics, we assessed the effects of tree diversity on the removal of tropospheric ozone (O3) in Rome, Italy, in two years (2003 and 2004) that were very different for climatic conditions and ozone levels. Different tree functional groups showed complementary uptake patterns, related to tree physiology and phenology, maintaining a stable community function across different climatic conditions. Our results, although depending on the city-specific conditions of the studied area, suggest a higher function stability at increasing diversity levels in urban ecosystems. In Rome, such ecosystem services, based on published unitary costs of externalities and of mortality associated with O3, can be prudently valued to roughly US$2 and $3 million/year, respectively.

Computing diversity from dated phylogenies and taxonomic hierarchies: does it make a difference to the conclusions?

Recently, dated phylogenies have been increasingly used for ecological studies on community structure and conservation planning. There is, however, a major impediment to a systematic application of phylogenetic methods in ecology: reliable phylogenies with time-calibrated branch lengths are lacking for a large number of taxonomic groups and this condition is likely to continue for a long time. A solution for this problem consists in using undated phylogenies or taxonomic hierarchies as proxies for dated phylogenies. Nonetheless, little is known on the potential loss of information of these approaches compared to studies using dated phylogenies with time-calibrated branch lengths. The aim of this study is to ask how the use of undated phylogenies and taxonomic hierarchies biases a very simple measure of diversity, the mean pairwise phylogenetic distance between community species, compared to the diversity of dated phylogenies derived from the freely available software Phylomatic. This is illustrated with three sets of data on plant species sampled at different scales. Our results show that: (1) surprisingly, the diversity computed from dated phylogenies derived from Phylomatic is more strongly related to the diversity computed from taxonomic hierarchies than to the diversity computed from undated phylogenies, while (2) less surprisingly, the strength of this relationship increases if we consider only angiosperm species.

A partial ordering approach for functional diversity.

Functional diversity is generally regarded as the constituent of biological diversity that considers how the species functional traits affect ecosystem processes. Due to its ecological relevance, a number of indices of functional diversity have been proposed to date based on distinct objectives and motivations. Such proliferation of indices can be at least partially overcome by a more fundamental mathematical approach. In this paper we propose an intrinsic ordering approach for abundance-weighted measures of functional diversity that is similar to the Lorenz curves used by ecologists for ordering evenness measures. We then discuss the relevance of a number of functional diversity indices that have a behavior compatible with the proposed partial ordering.