A probabilistic approach for plant diversity monitoring in a European Natura2000 network Alessandro Chiarucci, Giovanni Bacaro, Duccio Rocchini* Department of Environmental Science “G. Sarfatti” University of Siena, Italy *TerraData Environmetrics,

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Nature Reserve Networks A high number of protected areas is spread in European countries, often arranged in territorial networks. In Europe, the Natura 2000 is the most important network pf protected areas and it is supposed to preserve almost all the terrestrial species and habitats. The following specific objective has been set: “to achieve by 2010 a significant reduction of the current rate of biodiversity loss at the global, regional and national level". To understand if the existing reserve networks can achieveme of this objective we need to quantify in an affordable way how much biodiversity is present within it and how it is changing through time!

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Plant species diversity Vascular plants are the most important component of most terrestrial ecosystems because of their functional and structural role. The quantification and the monitoring of plant species diversity represents thus essential steps for the management of protected areas and for understanding how these are changing through time. With this project we aimed to develop and test a method for evaluating and monitoring plant species diversity within a territorial Natura2000 Network, based on a sample approach. This method is based on a constrained sampling effort and a high potential for spatial inference.

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Assessment of plant species diversity Assessing and monitoring plant species diversity over very large and fragmented areas is a really difficult task. Large databases are presently available but they present many problems for spatial and temporal inference. Some national and local monitoring programs use remote sensing, mapping or structural indicators. Taxonomic information is still an essential data source for describing and monitoring, biodiversity, at least until the potential use of other indicators will be clearer. However, it is virtually impossible to get complete lists of species for large areas. It is also very difficult to use the records when they are collected on non-homogeneous criteria.

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Study Area As study area we used the network of SCIs present in the province of Siena, Tuscany. Descriptive data: ► 20 SCIs ► ≈ 593 km 2 ► km 2 each ► Altitudinal range:

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Existing Networks The whole country was divided into cells of 1x1 km In each cell a random point was selected Data were collected by using a three- stage sampling design I. N. F. C.

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Sampling design In each point vascular plants were sampled by using a 10x10 m plot, divided into 16 subplots. In preliminary tests, this plot size was found to represent the best compromise between local species richness and sampling accuracy.

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Points were localised with a high precision GPS system and the spatial data then submitted to differential correction. Each plot was sampled by a team made by at two experienced botanists and herbarium specimens were collected. Data Collection

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Floristic data were stored on a web-based relational database that guarantees the preservation of the data and their easy access to all the authorised users, for both research and management aims. Data storage

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Sampling Summary SCIs in Siena Province SCIs sampled in 2006 SCIs sampled in 2005

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Data Summary N° of sampled SCIs 44 N° of plots N° of field days 1642 N° of field operators per field day N° of days * teams 1973 N° recorded species 364≈800

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Results

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Results

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Additive partitioning of diversity Inventory DiversityDifferentiation diversityScale of sampling Alpha 1 Plots SCI Beta 3 among sites Alpha 2 Alpha 3 Network Alpha 4 Beta 2 (among stands) Subplots Beta 1 (within stands) To test the significance of alfa i and beta i components, samples at level i-1 were randomly allocated among those samples at level i that belong to the same sample unit at i+1.

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Results Alfa 1 Beta 1 Beta 2 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% AMIALUCCPIGERIPA Proportion of species diversity Obs Ran

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Results α 2 = 25.5 sp. α 3 = sp. β 2 = sp. β 3 = sp. α 4 = 362 sp.

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Results

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb Conclusions Species composition data collected by a probabilistic sample were useful in evaluating the partitioning of species diversity in a network of protected areas and gave useful insights for its future monitoring. Species diversity is largely due to large scale variation, both at the within-site and the among sites levels. The monitoring of plant species diversity in a network of protected areas should be performed by using a high number of plots, rather using few larger sites. To provide spatial and temporal inference of plant species diversity, a limited number of plots selected with a probabilistic approach should be preferred over larger databases of preferentially selected plots. Additive partitioning of species diversity combined with rarefaction curves can provide a useful method to quantify and monitoring plant species diversity.

49° IAVS Annual Conference - Palmerston North, New Zealand, Feb We acknowledge all the students and colleagues that contributed to the project: Andrea Billi, Arianna Vannini, Elisa Baragatti, Elisa Santi, Fernando Cortés Selva, Francesco Geri, Giulia Bennati, Lia Pignotti, Mauro Taormina, Patrizia Mosca, Sara Ghisleni.