Is Switzerland Suitable for the Invasion of Aedes albopictus?

Background

Over the last 30 years, the Asian tiger mosquito, Aedes albopictus, has rapidly spread around the world. The European distribution comprises the Mediterranean basin with a first appearance in Switzerland in 2003. Early identification of the most suitable areas in Switzerland allowing progressive invasion by this species is considered crucial to suggest adequate surveillance and control plans.

Methodology/Principal Findings

We identified the most suitable areas for invasion and establishment of Ae. albopictus in Switzerland. The potential distribution areas linked to the current climatic suitability were assessed using remotely sensed land surface temperature data recorded by the MODIS satellite sensors. Suitable areas for adult survival and overwintering of diapausing eggs were also identified for future climatic conditions, considering two different climate change scenarios (A1B, A2) for the periods 2020–2049 and 2045–2074. At present, the areas around Lake Geneva in western Switzerland provide suitable climatic conditions for Ae. albopictus. In northern Switzerland, parts of the Rhine valley, around Lake Constance, as well as the surroundings of Lake Neuchâtel, appear to be suitable for the survival at least of adult Ae. albopictus. However, these areas are characterized by winters currently being too cold for survival and development of diapausing eggs. In southern Switzerland, Ae. albopictus is already well-established, especially in the Canton of Ticino. For the years 2020–2049, the predicted possible spread of the tiger mosquito does not differ significantly from its potential current distribution. However, important expansions are obtained if the period is extended to the years 2045–2074, when Ae. albopictus may invade large new areas.

Conclusions/Significance

Several parts of Switzerland provide suitable climatic conditions for invasion and establishment of Ae. albopictus. The current distribution and rapid spread in other European countries suggest that the tiger mosquito will colonize new areas in Switzerland in the near future.     

Is spectral distance a proxy of beta diversity at different taxonomic ranks? A test using quantile regression

Beta diversity represents a powerful indicator of ecological conditions because of its intrinsic relation with environmental gradients. In this view, remote sensing may be profitably used to derive models characterizing or estimating species turnover over an area. While several examples exist using spectral variability to estimate species diversity at several spatial scales, most of these have relied on standard correlation or regression approaches like the common Ordinary Least Square (OLS) regression which are problematic with noisy data. Moreover, very few attempts were made to derive beta diversity characterization models at different taxonomic ranks. In this paper, we performed quantile regression to test if spectral distance represents a good proxy of beta diversity considering different data thresholds and taxonomic ranks. We used plant distribution data from the North and South Carolina including 146 counties and covering a variety of vegetation formations. The dissimilarity in species composition at different taxonomic ranks (using Sørensen distance) among pairs of counties was compared with their distance in NDVI values derived from 23 yearly MODIS images. Our results indicate that (i) spectral variability represents a good proxy of beta diversity when appropriate statistics are applied and (ii) a lower taxonomic rank is important when changes in species composition are examined spatially using remotely sensed data.     

Are CORINE land cover classes reliable proxies of plant species assemblages? A test in Mediterranean forest landscapes

In land cover mapping, the complexity of landscapes is fitted into classes that may limit the recognition of natural variability. In this study, we tested the power of land cover classes (defined on the CORINE land cover classification scheme, a standardized legend set by EU for land cover inventory) to separate different vascular plant assemblages in forest ecosystems. In order to separately identify the role of different sources of inconsistency between land cover classes and species composition, we compared three different inventory processes, based on (i) dominant tree species as observed in the field, (ii) visual interpretation of remotely sensed images and (iii) semi-automatic supervised classification of satellite images. Our results underline that classifying forest ecosystems on the basis of their canopy species produces an over-simplification of habitat variability. Consequently, land cover maps based on non-specialized classification schemes should not be regarded as good proxies for plant biodiversity. If land cover maps are intended to describe and manage landscapes and their associated biodiversity, it is necessary to improve their capacity to represent the complexity of ecosystems.     

Climate-related adaptive genetic variation and population structure in natural stands of Norway spruce in the South-Eastern Alps

Forest trees dominate many Alpine landscapes that are currently exposed to changing climate. Norway spruce is one of the most important conifer species of the Italian Alps, and natural populations are found across steep environmental gradients with large differences in temperature and moisture availability. This study seeks to determine and quantify patterns of genetic diversity in natural populations toward understanding adaptive responses to changing climate. Across the Italian species range, 24 natural stands were sampled with a major focus on the Eastern Italian Alps. Sampled trees were genotyped for 384 selected single nucleotide polymorphisms (SNPs) from 285 genes. A wide array of potential candidate genes was tested for correlation with climatic parameters. To minimize false-positive association between genotype and climate, population structure was investigated. Pairwise F _ST estimates between sampled populations ranged between 0.000 and 0.075, with the highest values involving the two disjoint populations, Valdieri, on the western Italian Alps, and Campolino, the most southern population on the Apennines. Despite considerable genetic admixture among populations, both Bayesian and multivariate approach identified four genetic clusters. Selection scans revealed five F _ST outliers, and the environmental association analysis detected ten SNPs associated to one or more climatic variables. Overall, 13 potentially adaptive loci were identified, three of which have been reported in a previous study on the same species conducted on a broader geographical scale. In our study, precipitation, more than temperature, was often associated with genotype; therefore, it appears as the most important environmental variable associated with the high sensitivity of Norway spruce to soil water supply. These findings provide relevant information for understanding and quantifying climate change effects on this species and its ability to genetically adapt.     

Invasiveness of alien plants in Brussels is related to their phylogenetic similarity to native species

Aim Understanding the processes that drive invasion success of alien species has received considerable attention in current ecological research. From an evolutionary point of view, many studies have shown that the phylogenetic similarity between the invader species and the members of the native community may be an important aspect of invasiveness. In this study, using a coarse‐scale systematic sampling grid of 1 km², we explore whether the occupancy frequency of two groups of alien species, archaeophytes and neophytes, in the urban angiosperm flora of Brussels is influenced by their phylogenetic relatedness to native species. Location The city of Brussels (Belgium). Methods We used ordinary least‐squares regressions and quantile regressions for analysing the relationship between the occupancy frequency of alien species in the sampled grid and their phylogenetic distance to the native species pool. Results Alien species with high occupancy frequency in the sampled grid are, on average, more phylogenetically related to native species than are less frequent aliens, although this relationship is significant only for archaeophytes. In addition, as shown by the quantile regressions, the relationship between phylogenetic relatedness to the native flora and occupancy frequency is much stronger for the most frequent aliens than for rare aliens. Main conclusions Our data suggest that it is unlikely that species with very low phylogenetic relatedness to natives will become successful invaders with very high distribution in the area studied. To the contrary, under future climate warming scenarios, present‐day urban aliens of high occupancy frequency are likely to become successful invaders even outside urban areas.     

Does using species abundance data improve estimates of species diversity from remotely sensed spectral heterogeneity?

Different approaches for the assessment of biodiversity by means of remote sensing were developed over the last decades. A new approach, based on the spectral variation hypothesis, proposes that the spectral heterogeneity of a remotely sensed image is correlated with landscape structure and complexity which also reflects habitat heterogeneity which itself is known to enhance species diversity. In this context, previous studies only applied species richness as a measure of diversity. The aim of this paper was to analyze the relationship of richness and abundance-based diversity measures with spectral variability and compare the results at two scales. At three different test sites in Central Namibia, measures of vascular plant diversity was sampled at two scales – 100 m² and 1000 m². Hyperspectral remote sensing data were collected for the study sites and spectral variability, was calculated at plot level. Ordinary least square regression was used to test the relationship between species richness and the abundance-based Shannon Index and spectral variability. We found that Shannon Index permanently achieved better results at all test sites especially at 1000 m², Even when all sites where pooled together, Shannon Index was still significantly related with spectral variability at 1000 m². We suggest incorporating abundance-based diversity measures in studies of relationships between ecological and spectral variability. The contribution made by the high spectral and spatial resolution of the hyperspectral sensor is discussed.     

While Boolean sets non-gently rip: A theoretical framework on fuzzy sets for mapping landscape patterns

Boolean logic is frequently applied in order to map landscape patterns. Nonetheless this implies to divide the gradual variability of the earth's surface into a finite number of non-overlapping classes, which are considered exhaustive and mutually exclusive. On the contrary, landscapes are expected to be spatially continuous. Fuzzy membership seems to better fit such an issue, by associating for each entity the degree of membership to a class thus maintaining uncertainty information. In this paper, I will disentangle, from a theoretical point of view, the potential of fuzzy set theory for mapping landscape patterns, particularly focusing on those properties of the fuzzy membership concept which are crucial when aiming at extracting the whole information over a landscape.     

Invasive fountain grass (Pennisetum setaceum (Forssk.) Chiov.) increases its potential area of distribution in Tenerife island under future climatic scenarios

Mapping the distribution of invasive species under current and future climate conditions is crucial to implement sustainable and effective conservation strategies. Several studies showed how invasive species may benefit from climate change fostering their invasion rate and, consequently, affecting the native species community. In the Canary Islands and on Tenerife in particular, previous research mostly focused on climate change impacts on the native communities, whereas less attention has been paid on alien species distribution under climate change scenarios. In this study, we modelled the habitat distribution of Pennisetum setaceum, one of the most invasive alien species on Tenerife. In addition, we described the species’ potential distribution shift in the light of two climate change scenarios (RCP2.6, RCP8.5), highlighting the areas that should be prioritized during management and eradication programs. P. setaceum’s suitable areas are located in the coastal area, with higher habitat suitability near cities and below 800 m asl. In both future climate change scenarios, the geographic distribution of P. setaceum suitable areas is characterized by an elevational shift, which is more pronounced in the RCP8.5 scenario. Despite being drought resistant, water supply is crucial for the species’ seed germination, thus supporting future species’ shift to higher elevation and in the north–north–west part of the island, where it could benefit from the combined effect of orographic precipitations and humidity carried by trade winds.

     

Geostatistical modelling of regional bird species richness: exploring environmental proxies for conservation purpose

Identifying spatial patterns in species diversity represents an essential task to be accounted for when establishing conservation strategies or monitoring programs. Predicting patterns of species richness by a model-based approach has recently been recognised as a significant component of conservation planning. Finding those environmental predictors which are related to these patterns is crucial since they may represent surrogates of biodiversity, indicating in a fast and cheap way the spatial location of biodiversity hotspots and, consequently, where conservation efforts should be addressed. Predictive models based on classical multiple linear regression or generalised linear models crowded the recent ecological literature. However, very often, problems related with spatial autocorrelation in observed data were not adequately considered. Here, a spatially-explicit data-set on birds presence and distribution across the whole Tuscany region was analysed. Species richness was calculated within 1 × 1 km grid cells and 10 environmental predictors (e.g. altitude, habitat diversity and satellite-derived landscape heterogeneity indices) were included in the analysis. Integrating spatial components of variation with predictive ecological factors, i.e. using geostatistical models, a general model of bird species richness was developed and used to obtain predictive regional maps of bird diversity hotspots. A meaningful subset of environmental predictors, namely habitat productivity, habitat heterogeneity, combined with topographic and geographic information, were included in the final geostatistical model. Conservation strategies based on the predicted hotspots as well as directions for increasing sampling effort efficiency could be extrapolated by the proposed model.