Carlo Ricotta

Accounting for uncertainty when mapping species distributions: The need for maps of ignorance

Accurate mapping of species distributions is a fundamental goal of modern biogeography, both for basic and applied purposes. This is commonly done by plotting known species occurrences, expert-drawn range maps or geographical estimations derived from species distribution models. However, all three kinds of maps are implicitly subject to uncertainty, due to the quality and bias of raw distributional data, the process of map building, and the dynamic nature of species distributions themselves. Here we review the main sources of uncertainty suggesting a code of good practices in order to minimize their effects. Specifically, we claim that uncertainty should be always explicitly taken into account and we propose the creation of maps of ignorance to provide information on where the mapped distributions are reliable and where they are uncertain.

CWM and Rao's quadratic diversity: a unified framework for functional ecology

Assessing the effects of environmental constraints on community structure often relies on methods that consider changes in species functional traits in response to environmental processes. Various indices have been proposed to measure relevant aspects of community trait composition from different viewpoints and perspectives. Among these, the ‘community-weighted mean trait value’ (CWM) and the Rao coefficient have been widely used in ecological research for summarizing different facets of functional composition and diversity. Analyzing changes in functional diversity of bee communities along a post-fire successional gradient in southern Switzerland we show that these two measures may be used to describe two complementary aspects of community structure, such as the mean and the dispersion of functional traits within a given species assemblage. While CWM can be adequately used to summarize shifts in mean trait values within communities due to environmental selection for certain functional traits, the Rao coefficient can be effectively applied to analyze patterns of trait convergence or divergence compared to a random expectation.

Remotely Sensed Spectral Heterogeneity As a Proxy of Species Diversity: Recent Advances and Open Challenges

Abstract Environmental heterogeneity is considered to be one of the main factors associated with biodiversity given that areas with highly heterogeneous environments can host more species due to their higher number of available niches. In this view, spatial variability extracted from remotely sensed images has been used as a proxy of species diversity, as these data provide an inexpensive means of deriving environmental information for large areas in a consistent and regular manner. The aim of this review is to provide an overview of the state of the art in the use of spectral heterogeneity for estimating species diversity. We will examine a number of issues related to this theme, dealing with: i) the main sensors used for biodiversity monitoring, ii) scale matching problems between remotely sensed and field diversity data, iii) spectral heterogeneity measurement techniques, iv) types of species taxonomic diversity measures and how they influence the relationship between spectral and species diversity, v) spectral versus genetic diversity, and vi) modeling procedures for relating spectral and species diversity. Our review suggests that remotely sensed spectral heterogeneity information provides a crucial baseline for rapid estimation or prediction of biodiversity attributes and hotspots in space and time.

The flaming sandpile: self-organized criticality and wildfires

A large series of wildfire records of the Regional Forest Service of Liguria (northern Italy) from 1986 to 1993 was examined for agreement with power-law behavior between frequency of occurrence and size of the burned area. The statistical analysis shows that the idea of self-organized criticality (SOC) applies well to explain wildfire occurrence on a regional basis.

Evidence of selective burning in Sardinia (Italy) : which land-cover classes do wildfires prefer?

The objective of this paper is to identify land-cover types where fire incidence is higher (preferred) or lower (avoided) than expected from a random null model. Fire selectivity may be characterized by the number of fires expected in a given land-cover class and by the mean surface area each fire will burn. These two components of fire pattern are usually independent of each other. For instance, fire number is usually connected with socioeconomic causes whereas fire size is largely controlled by fuel continuity. Therefore, on the basis of available fire history data for Sardinia (Italy) for the period 2000–2004 we analyzed fire selectivity of given land-cover classes keeping both variables separate from each other. The results obtained from analysis of 13,377 fires show that for most land-cover classes fire behaves selectively, with marked preference (or avoidance) in terms of both fire number and fire size. Fire number is higher than expected by chance alone in urban and agricultural areas. In contrast, in forests, grasslands, and shrublands, fire number is lower than expected. In grasslands and shrublands mean fire size is significantly larger than expected from a random null model whereas in urban areas, permanent crops, and heterogeneous agricultural areas there is significant resistance to fire spread. Finally, as concerns mean fire size, in our study area forests and arable land burn in proportion to their availability without any significant tendency toward fire preference or avoidance. The results obtained in this study contribute to fire risk assessment on the landscape scale, indicating that risk of wildfire is closely related to land cover.

Self-organized criticality of wildfires ecologically revisited

Abstract Wildfire cumulative frequency–area distributions of Mediterranean landscapes are examined for agreement with self-similar (fractal) behavior. Our results support landscape-specific restricted scaling regions of 1.5–3.5 orders of magnitude in size, which are delimited by breakpoints or ‘cut-offs’. By identifying the extent of such regions in the fractal frequency–area distribution of wildfires, fractal statistics may give a deeper insight into the scale-invariant dynamics of fire spread, whereas the observed cut-offs may be related to changes in the process–pattern interactions that control wildfire propagation at the landscape scale.

Diversity partitioning of Rao's quadratic entropy.

Many applications of diversity indices are only valid if they are first transformed into their equivalent number of species. These equivalent numbers of species can be multiplicatively partitioned into independent alpha, beta and gamma components, and can be formed into mathematically consistent similarity measures. The utility of beta diversity and similarity measures that incorporate information about the degree of ecological dissimilarity between species is becoming increasingly recognized. The concept of equivalent number of species is here extended to Raos quadratic entropy, opening the way to methods of diversity partitioning that take into account taxonomic or ecological differences between species.

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

On parametric evenness measures

2 and

The influence of principal component analysis on the spatial structure of a multispectral dataset

3 million/year, respectively.