Sara Landi

VegItaly: The Italian collaborative project for a national vegetation database

Abstract Two years after its official start, the national vegetation database VegItaly, a collaborative project supported by the Italian scientific community and developed by a large group of scientists, is presented. This article offers a concise overview of the content of the database, currently consisting of 31,100 vegetation plot, including published and unpublished data. Some basic statistics are analysed; for example, data distribution in space and time, represented vegetation types expressed as physiognomic categories. Although rather young and still in progress, VegItaly already contains data from all the Italian regions and stands as an optimal candidate for the development of an Italian national vegetation database. Its main goals,theoretical basis, technical features, functionalities and recent progresses are outlined, showing glimpses of future prospects.

Scale dependence of plant species richness in a network of protected areas

Despite the widely recognised importance of reserve networks, their effectiveness in encompassing and maintaining biodiversity is still debated. Species diversity is one of the most affordable measures of biodiversity, but it is difficult to survey such data over large scales. This research aimed to perform a sample-based assessment of species richness of groups of plants with different conservation value (alien species, protected species, and all species) within a reserve network, testing the use of partitioning as a tool for assessing diversity at different spatial scales, from the plot to the entire network. Plant diversity patterns differed for the groups of species for most of the investigated spatial scales. Despite these patterns assumed divergent tendencies when different species groups were considered, most of the species richness within the network was given by larger scale β-diversity for both alien and protected species, as well for all species. Diversity partitioning proved an effective tool to quantify the role of spatial scales in structuring the total species richness of the network, and is helpful in planning reserve networks.

Is floristic quality assessment reliable in human-managed ecosystems?

The Floristic Quality Analysis (FQA) is a method to assess the quality of a flora based on the assignment of scores to plant species and subsequent calculation of indices. This method is widely applied, but inadequate investigation has been devoted to test its potential problems due to human factors. This work is aimed to specifically test how the human factor can affect the calculation of the FQA indices, by addressing three questions: (i) Are the scores given to plant species consistent among different experts?; (ii) Are the floristic quality indices calculated by different experts consistent in ordering individual sites?; and (iii) Does the use of an appropriate statistics change the ordering of individual sites? To answer these questions, a list of species obtained in 136 plots in central Italy was submitted to nine experts, who scored each species. The FQA indices were then calculated from the scores of each of the experts. The results showed that: (i) the scores given to the species by the experts were not consistent and the derived floristic quality indices were statistically different; (ii) the floristic quality indices calculated for each plot were significantly different among experts, but the ranking of these plots based on their floristic quality was rather consistent; and (iii) the use of ordinal statistics, which is more adequate for this type of data, did not change the results. This study demonstrated that the Floristic Quality Analysis does not provide reliable and objective tools to assess the quality of the flora in a human-managed ecosystem. The application of these indices should be preceded with resolution of the methodological problems associated with the use of inappropriate statistics, and by procedures to reduce the degree of subjectivity in assigning the CC scores.

Anthropogenic drivers of plant diversity: perspective on land use change in a dynamic cultural landscape

Changes in land use are among the forces shaping Earth’s surface. In many industrialized areas, the loss of a traditional state of dynamic equilibrium between traditional management and natural dynamics is followed by abandonment to regeneration processes. This can reduce ecological complexity at the landscape scale and negatively affect biodiversity patterns. In this study, we investigate the relation between land use change and plant species diversity in the network of protected areas (PAs) of the province of Siena (Tuscany, Central Italy). This is an area characterized by long-lasting human activities and highly renowned cultural landscapes. We used remotely sensed, mapping and ground based plant compositional data, to investigate the present pattern of plant species diversity, the changes of landscape structure and changes in forest habitats. Most of the plant diversity present in this network of PAs is due to broad scale gradients due to ecological diversity but also to human management. Most of the area is currently covered by forests and analysis of a historical sequence of spatial data reveals that this is largely a consequence of the abandonment of traditional management during the last decades. Finally, focusing on forest succession as a consequence of land use change, we demonstrate that species richness significantly declines with increasing age of forest stands. Taken together, our results confirm that the recent trends of rural abandonment are leading to homogenization and biodiversity loss in traditional landscapes of Mediterranean Europe. We discuss implications for policy, and suggest that PA management in cultural and historical landscapes should pay increasing attention traditional anthropic practices.

Commonness and rarity of plants in a reserve network: just two faces of the same coin

Occurrence of protected and rare species is regarded as a strong argument for establishing protected areas and monitoring biodiversity, but while protected species are clearly identified, some problems exist to define rare species. It is thus important to know whether common and unprotected native species are reliable indicators for protected and rare species. The aims of this paper were to: (a) analyse the distribution of rarity and commonness of species, by using different criteria and (b) test if groups of species with different conservation value (aliens, unprotected natives and protected natives) differ in terms of their rarity distribution, using the data collected in 604 plots sampled within 21 protected areas of the central Italy. Three different criteria were used to classify species as rare or common. Pearson correlation, least-squares regressions and Chi-square test were used to compare the species richness patterns or rare and common species as well as protected, unprotected native, and alien species. The number of species classified as common and rare widely differ according to the adopted criterion. The number of common and rare species were statistically correlated at both the plot and protected area scales, even if at the plot scale the predictive capacity was rather low. Protected species were significantly rarer than expected, while unprotected species were significantly more common than expected; alien species confirmed to be particularly rare in our study area, with some major alien species being totally absent in the recorded flora. The richness patterns of common and rare species defined according to different criteria have been found to be correlated one to the other, and both are well related to the richness of protected and alien species at both the plot and PA scales. Protected species were better related to common species, while alien species were better related to rare species. Despite rare species were numerically more than common species, and the richness pattern of total species was better predicted by common species than rare species. Common species confirmed to be good indicators of species richness patterns and also of protected species.

Plant recording across two centuries reveals dramatic changes in species diversity of a Mediterranean archipelago

Although islands are model systems for investigating assembly of biological communities, long-term changes in archipelago communities are not well understood because of the lack of reliable data. By using a vast amount of floristic data we assembled a dataset of the plant species occurring on 16 islands of the Tuscan Archipelago, Italy, across two periods, 1830–1950 and 1951–2015. We collected 10,892 occurrence records for 1,831 species. We found major changes in the island plant assemblages between the two periods, with native flora significantly decreasing (−10.7%) and alien flora doubling (+132.1%) in richness. The species–area relationships demonstrated the scale-dependence of the observed changes for native and alien species. The observed floristic changes were dependent on island area, with smaller islands displaying high variability in richness and compositional changes and larger islands having more stable species assemblages. The richness of species associated with open landscapes, that had been maintained for centuries by traditional practices, markedly reduced while the number of woody species, associated with afforestation processes and invasion by alien woody plants, significantly incresed. These results demonstrate the great power of floristic studies, often available in grey literature, for understanding long-term biotic changes in insular ecosystems.

The Influence of Vegetation and Landscape Structural Connectivity on Butterflies (Lepidoptera: Papilionoidea and Hesperiidae), Carabids (Coleoptera: Carabidae), Syrphids (Diptera: Syrphidae), and Sawflies (Hymenoptera: Symphyta) in Northern Italy Farmland

ABSTRACT Landscape structure as well as local vegetation influence biodiversity in agroecosystems. A study was performed to evaluate the effect of floristic diversity, vegetation patterns, and landscape structural connectivity on butterflies (Lepidoptera: Papilionoidea and Hesperiidae), carabids (Coleoptera: Carabidae), syrphids (Diptera: Syrphidae), and sawflies (Hymenoptera: Symphyta). Vegetation analysis and insect samplings were carried out in nine sites within an intensively farmed landscape in northern Italy. Plant species richness and the percentage of tree, shrub, and herb cover were determined by means of the phytosociological method of Braun-Blanquet. Landscape structural connectivity was measured as the total length of hedgerow network (LHN) in a radius of 500 m around the center of each sampling transect. Butterflies species richness and abundance were positively associated both to herb cover and to plant species richness, but responded negatively to tree and shrub cover. Shrub cover was strictly correlated to both species richness and activity density of carabids. The species richness of syrphids was positively influenced by herb cover and plant richness, whereas their abundance was dependent on ligneous vegetation and LHN. Rarefaction analysis revealed that sawfly sampling was not robust and no relationship could be drawn with either vegetation parameters or structural connectivity. The specific responses of each insect group to the environmental factors should be considered in order to refine and optimize landscape management interventions targeting specific conservation endpoints.

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

Abstract 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.