Research Article
Print
Research Article
A thematic vegetation dataset of SArdinian GRAsslands (SAGRA)*
expand article infoSimonetta Bagella, Maria Carmela Caria, Gianmaria Bonari§|, Marco Malavasi, Raimondo Melis, Giovanna Piga, Giovanni Rivieccio
‡ University of Sassari, Sassari, Italy
§ University of Siena, Siena, Italy
| NBFC, National Biodiversity Future Center, Palermo, Italy
Open Access

Abstract

We present the dataset “SArdinian GRAsslands” (SAGRA), a collection of georeferenced vegetation surveys sourced from different areas of Sardinia (Italy). SAGRA addresses a geographic gap in current databases, as plots from Sardinian grasslands are underrepresented. We collected vegetation data from different projects and organized it within a framework that allows for scalability to larger scales or integration into existing databases. The surveys include three categories of information: general, vegetation and management, and environmental. Overall, SAGRA comprises 1277 vegetation surveys, some of which were performed in different years in the same plots. This dataset encompasses 685 plots and 434 species, primarily therophytes.

Keywords

This georeferenced vegetation dataset can support further scientific research and aid the sustainable management of Mediterranean grasslands. Databases, Grassland management, Mediterranean grasslands, Phytosociological surveys, Plant diversity, Vegetation data, Vegetation plots

Introduction

Large-scale databases offer valuable opportunities to monitor biodiversity across various spatial and temporal scales. Vegetation plots, compared to occurrence data are particularly effective for monitoring vegetation. They provide several advantages, including the identification of co-occurring and missing species (Phillips et al. 2009; Chytrý et al. 2016; Sabatini et al. 2021). Using vegetation plots in plant community ecology is a crucial breakthrough that significantly contributes to understanding distribution patterns and dynamics (Kapfer et al. 2017; Sabatini et al. 2021). Additionally, it helps address emerging issues such as the severe risk of species loss, habitat degradation, and biodiversity decline (Biurrun et al. 2021). Plots also play a key role in classifying vegetation, assessing the conservation status of species and habitats, and monitoring the spread of alien species (Chytrý et al. 2016; Yannelli et al. 2022; Janssen et al. 2023). Although vegetation plot data were historically collected within specific projects or survey campaigns tailored for local and regional objectives, the widespread harmonization and accessibility of this resource started only a few decades ago (Schaminée et al. 2006). Currently, numerous initiatives have established vegetation databases on national, supranational, and global scales (Landucci et al. 2012; Chytrý et al. 2016; Bonari et al. 2019; Bruelheide et al. 2019; Sabatini et al. 2021; Alessi et al. 2022). Besides broad-scale initiatives, some databases focus on specific environments or habitats. For instance, the GrassPlot database concentrates on multi-scale plant diversity in Palaearctic grasslands (Dengler et al. 2018). Thematic databases, like GrassPlot, enhance monitoring effectiveness by providing additional details related to the management of surveyed areas. This is crucial for secondary grasslands, as their existence and floristic composition are strongly associated with specific management practices and grazing livestock (Klimek et al. 2007; Halada et al. 2011; Ribeiro et al. 2014; Perring et al. 2018; Janišová et al. 2021). Monitoring biodiversity vital for identifying trends and drivers of change, guiding policy formulation, sustainable management, and conservation actions. This is especially crucial in the face of a global crisis influenced by land use change and climate change (Lindenmayer and Likens 2009; Watson et al. 2019; Knollová et al. 2024). Moreover, georeferenced plots play a pivotal role in resampling vegetation at the exact locations over time. Therefore, databases with resampled and georeferenced plots are invaluable for consistent vegetation monitoring. Approximating the relocation of plots can potentially exaggerate temporal changes and compromise results (Kopecký and Macek 2015).

Among secondary formations, Mediterranean grasslands are of particular interest due to the biodiversity they host and the ecosystem services they provide, including nutrient cycling, carbon sequestration, water cycle regulation, agricultural goods, and cultural heritage (Unger and Jongen 2014; Ribeiro et al. 2014; Seddaiu et al. 2018; Grenke et al. 2022; Malavasi et al. 2023). However, these grasslands face challenges such as intensive grazing practices, grassland abandonment, and climate change (Dibari et al. 2021). This leads to a decline in surface area and grassland quality, thus posing a severe conservation issue (Klimek et al. 2007).

The availability of data on vegetation in Mediterranean pastures is crucial for implementing monitoring activities aimed at their management. In this context, our efforts have concentrated on a specific area in the Mediterranean region, Sardinia (Italy), whose territory has been shaped over the centuries by pastoral activities (Malavasi et al. 2023). Sardinia is recognized as a hotspot for plants in the Mediterranean region (Myers et al. 2000). The number of taxa reported for the island varies (Bagella et al. 2020a), with Arrigoni (2006–2015) citing 2810 taxa and Bartolucci et al. (2024) reporting 2479 taxa, considering only native and archeophytes. The island’s diverse climate, topography, and geological substrates contribute to the variety of potential natural vegetation, primarily characterized by Quercus ilex and Q. suber woodlands (Bacchetta et al. 2009). These grasslands, which are of secondary origin, are a crucial component of agro-silvopastoral systems and currently face significant threats from abandonment (Seddaiu et al. 2018; Bagella et al. 2020b). To facilitate the utilization of available data, we have built the dataset “Sardinian Grasslands” (SAGRA), a collection of surveys from different areas of the island and various years, accurately georeferenced. Information about plots are reported in Table 1. SAGRA also addresses a geographic gap, as plots from Sardinian grasslands are underrepresented in existing databases.

Table 1.

Information relative to each survey contained in SAGRA dataset.

General information Vegetation and management Environmental information
Unique Identification Code (ID) Total vegetation cover (%) Elevation
Survey year Vegetation structure Slope
Survey date Management type Aspect
Surveyors’ names Duration Vegetation series
Custodian Grazing animals Bioclimate
Country Geology
Municipality Land use
Site name
Original project name
Original project Identification code
Farm name
Field identification code
Replicate number
Longitude
Latitude
Location uncertainty (m)
Number of resurveys
Plot size

Study area

Sardinia is located in the Mediterranean basin, encompassing an area of approximately 24,000 km2. It boasts a coastline extending about 1900 km (Mori 1966) (Fig. 1).

Figure 1. 

Location of Sardinia in the Mediterranean basin.

The morphology of the island’s terrain is predominantly mountainous, featuring a maximum elevation of 1834 m a.s.l. and an average elevation of 334 m a.s.l. (Mori 1966). Geologically, Sardinia comprises four main units: a Variscan crystalline basement characterized by Paleozoic magmatic intrusive and metamorphic complexes (in the east side); a Permian to Oligocene sedimentary marine succession (in the west side); an Upper Oligocene to Upper Miocene volcano-sedimentary succession, and Plio-Pleistocene basaltic lava flows (on the central part of the island). Additionally, volcanic and terrigenous Quaternary deposits occur in the main plains and along the coasts (Carmignani et al. 2016).

Approximately 28% of the island’s total surface area is marked by outcropping rock and poorly developed soils, with depths not exceeding 10–15 cm. Only 18% of Sardinia’s land area consists of irrigable soil (Vacca 2016). The climate is typically Mediterranean, characterized by dry and hot summers, and relatively rainy and mild winters. In Sardinia, annual precipitation ranges from 411 to over 1215 mm in the inner mountainous regions. The mean annual temperature ranges from 11.7 °C to 18.1 °C. Two macroclimate types have been identified: Mediterranean pluviseasonal oceanic, covering 99.1% of the total area, and Temperate oceanic (Canu et al. 2015).

Data collection

Data on grasslands were gathered from ten projects spanning the years 2011 to 2021 (Bagella et al. 2013, 2014, 2020a, b; Rossetti et al. 2015; Seddaiu et al. 2018), employing a consistent sampling method. We used 2 m × 2 m plots (Angelini et al. 2016). Within homogeneous areas from an environmental and management perspective, referred to as “fields”, we conducted three to five random replications. Within each plot, the abundance-dominance of all present plant species was quantified using the scale proposed by Braun-Blanquet (1932). The scale includes several categories allowing researchers to quantify the presence and relative importance. Surveys were carried out during spring and sometimes occasionally repeated in different years.

The surveyed vegetation can be mainly referred to the classses Papaveretea rhoeadis S. Brullo et al. 2001, Polygono-Poetea annuae Rivas-Mart. 1975, Poetea bulbosae Rivas Goday et Rivas-Martínez ex Navarro Andrés et Valle Gutiérrez 1984, and Tuberarietea guttatae Braun-Blanquet 1973 (Terzi et al. 2024).

Structure and content of the dataset

The data obtained from the ten projects were consolidated into a single file using Turboveg v. 2.135b (Hennekens and Schaminée 2001). To ensure consistency, plant names were standardized following Euro+Med (2006–2024). Additionally, the biological form of each species, as outlined by Pignatti (1982), was included in the dataset. Family classifications adhere to the APG IV (2016).

The vegetation surveys are associated with three categories of information: general, vegetation and management, and environmental (Table 1). The categories of vegetation structure and management. are detailed in Table 2. Environmental information was derived from open-source facilities (Table 3).

The geographic locations of the plots, either initially recorded in the field or later derived remotely, were then standardized to the same coordinate system, World Geodetic System 1984 (WGS84 - EPSG:4326).

SAGRA comprises 1277 surveys performed in 685 vegetation plots primarily located in the central-western and northeastern regions of the island of Sardinia. The plots were permanent and several surveys were repeated in different years. A total of 434 species were found, with the most represented families being Fabaceae, Poaceae and Asteraceae (Fig. 2A). Annual species (therophytes; T) outnumbered perennial species (Fig. 2B).

Most species were rarely recorded (Fig. 3). By contrast, seven species were recorded in more than 500 surveys (Fig. 4).

Open grasslands are the most represented vegetation type, followed by wooded grasslands, while the other types are sparsely represented across a few plots (Fig. 5A). The majority of plots are subjected to grazing activities (Fig. 5B). In terms of duration, the temporary type prevails (Fig. 5C). Lastly, there is a nearly equal representation of beef cattle and dairy sheep among grazing animals (Fig. 5D), with mixed categories primarily consisting of dairy sheep/beef cattle and dairy sheep/goats.

The plots span a broad elevation range, from 3 to 995 m a.s.l. They are predominantly located on granitic and effusive substrates, with a prevailing northwest-oriented aspect.

Twelve distinct isobioclimates are represented, with a prevalence of the Lower Mesomediterranean, mainly Lower Mesomediterranean, lower subhumid, weak euoceanic.

Concerning the plant landscape, the vegetation series more present correspond to those of the Sardinian, calcifuge cork oak forests of the associations Galio scabri-Quercetum suberis (thermo-mesomediterranean) and Violo dehnhardtii-Quercetum suberis (mesomediterranean).

Based on the Corine land use classification, the plots are predominantly categorized as Non-irrigated arable land, followed by Artificial meadows.

Table 2.

Categories of vegetation structure, management, duration and grazing animals considered in SAGRA dataset.

Vegetation structure Open grasslands Bushed grasslands Wooded grasslands Clearings
Herbaceous grasslands Herbaceous grasslands with scattered bushes Herbaceous grasslands with scattered trees Clearings in the woodlands 500–1000 m2
Two subunits: underneath the tree canopy and beyond the tree canopy
Management Grazed Mown Mown-grazed
Duration Temporary Permanent Mixed
Less than 5 years of age, included in a crop rotation Naturally (self-seeded) or through cultivation (sown) and not included in the crop rotation of the holding for five years or longer (Commission Regulation EU No 796/2004). Combination of the previous two categories
Grazing animals Dairy sheep Dairy cattle Beef cattle Mixed
Figure 2. 

Percentage of plant families (A) and life forms (B) of the species listed in SAGRA dataset (Ch = Chamaephytes; G = Geophytes; H = Hemicryptophytes; P = Phanerophytes; T = Therophytes).

Table 3.

Sources of the environmental information.

Information Source
Elevation Digital Elevation Model with a resolution of 25 m and vertical accuracy of +/- 7 m RMSE (Copernicus Land Monitoring Service – EU-DEM graziv1.1)
Slope
Aspect
Vegetation series Bacchetta et al. (2009)
Bioclimate Canu et al. (2015)
Geology Sardegna Geoportale (2024)
Land use Corine land use classification up to five levels
Figure 3. 

Frequency distribution of the species presence in the surveys.

Figure 4. 

Number of occurrences of the seven Mediterranean therophytes recorded in more than 500 surveys (A. barbata = Avena barbata Link; L. rigidum = Lolium rigidum Gaudin; T. subterraneum = Trifolium subterraneum L.; S. arvensis = Sherardia arvensis L.; A. arvensis = Anthemis arvensis L.; V. ligustica = Vulpia ligustica (All.) Link; M. polymorpha = Medicago polymorpha L.).

Figure 5. 

Plot characteristics: vegetation structure (A), management (B), duration (C), grazing animals (D).

Conclusions and future perspectives

The compilation of the SAGRA dataset resulted from rigorous data collection efforts and a meticulous process of data organization, digitalization, and structuring. Initially emerging as a collection of local projects, its organizational framework enables scalability or integration into existing vegetation databases. The species predominantly represented in the surveys are Mediterranean therophytes, adapted to seasonal precipitation patterns and exhibiting tolerance to disturbances (Tárrega et al. 2009; Fernández-Moya et al. 2011). The distribution of species within the three most abundant families mirrors the characteristics of these grasslands. Poaceae and Fabaceae encompass numerous good and excellent forage species (Verdinelli et al. 2022), whereas Asteraceae comprise thorny and prickly species highlighting the encroachment of grasslands and thereby reducing vegetation cover of palatable species for livestock (Bagella et al. 2019). The vegetation plots are located in sectors representative of various common environmental conditions on the island and different parts of the Mediterranean basin (Caballero et al. 2009; Rossetti et al. 2015; Seddaiu et al. 2018). SAGRA represents a dataset with numerous perspectives of application. The use of species-specific information can address questions related to responses to diverse environmental gradients, and exploring species and community responses, as well as their relationships with ecosystem services linked to specific management types (Garnier et al. 2016; Chelli et al. 2019). The availability of this georeferenced dataset will be useful to define spatial models of grassland diversity in Sardinia. A forthcoming step for SAGRA involves establishing an accessible structure to enhance data management. It will be made accessible through vegetation databases for broader-scale analyses. The dataset will support future studies on Mediterranean grasslands.

Data request

Data can be obtained through the official vegetation database of the Italian Association for Vegetation Science VegItaly by contacting the VegItaly Steering Committee (https://www.scienzadellavegetazione.it/en/vegitaly-3/) or by contacting the dataset custodian directly (Simonetta Bagella: sbagella@uniss.it).

Acknowledgements

This paper has been developed within the framework of the project e.INS – Ecosystem of Innovation for Next Generation Sardinia (cod. ECS 00000038) funded by the Italian Ministry for Research and Education (MUR) under the National Recovery and Resilience Plan (NRRP) - MISSION 4 COMPONENT 2, “From research to business” INVESTMENT 1.5, “Creation and strengthening of Ecosystems of innovation” and construction of “Territorial R&D Leaders”.

The dataset SaGRA was built based on the data provided by the following projects: EcoFINDERS (FP7-264465); PASCUUM (Regione Sardegna, CRP-25599); Ichnusa Bubula (Regional Rural Development Program 2007–2013- Misura 124); Prati Fioriti (GAL Marghine, 2014); Convenzione LAORE (between the LAORE Agency in Sardinia and the Research Center on Desertification at the University of Sassari, 2017); LIFE Regenerate (LIFE16 ENV/ES/000276); BioMilkChina (POR FESR Sardegna 2014–2020); Convenzione Asinara (in the context of the review of the plan for the National Park of Asinara, 2021); auto financed project (2021); GASPAM (Regione Sardegna, L. 7/2007, 2019–2021).

G. Bonari was funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4 - Call for tender No. 3138 of 16 December 2021, rectified by Decree n.3175 of 18 December 2021 of Italian Ministry of University and Research funded by the European Union – NextGenerationEU; Award Number: Project code CN_00000033, Concession Decree No. 1034 of 17 June 2022 adopted by the Italian Ministry of University and Research, CUP B63C22000650007, Project title “National Biodiversity Future Center - NBFC”.

S. Bagella and M.C. Caria acknowledge the support of NBFC to the University of Sassari, funded by the Italian Ministry of University and Research, PNRR, Missione 4 Componente 2, “Dalla ricerca all’impresa”, Investimento 1.4, Project CN00000033.

References

  • Alessi N, Bruzzaniti V, Buldrini F, Centomo E, Cervellini M, … Chiarucci A (2022) AMS-VegBank: A new database of vegetation plots for the Italian territory. Vegetation Classification and Survey 3: 177–185. https://doi.org/10.3897/VCS.85083
  • Angelini P, Casella L, Grignetti A, Genovesi P (2016) Manuali per il monitoraggio di specie e habitat di interesse comunitario (Direttiva 92/43/CEE) in Italia: habitat. ISPRA, Serie Manuali e linee guida 142/2016.
  • APG IV (2016) An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Botanical Journal of the Linnean Society 181(1): 1–20. https://doi.org/10.1111/boj.12385
  • Arrigoni PV (2006–2015) Flora dell’isola di Sardegna, Carlo Delfino, Sassari.
  • Bacchetta G, Bagella S, Biondi E, Farris E, Filigheddu RS, Mossa L (2009) Vegetazione forestale e serie di vegetazione della Sardegna (con rappresentazione cartografica alla scala 1: 350.000). Società Italiana di Fitosociologia 46: 1–82.
  • Bagella S, Salis L, Marrosu GM, Rossetti I, Fanni S, … Roggero PP (2013) Effects of long-term management practices on grassland plant assemblages in Mediterranean cork oak silvo-pastoral systems. Plant Ecology 214(4): 621–631. https://doi.org/10.1007/s11258-013-0194-x
  • Bagella S, Filigheddu R, Caria MC, Girlanda M, Roggero PP (2014) Contrasting land uses in Mediterranean agro-silvo-pastoral systems generated patchy diversity patterns of vascular plants and below-ground microorganisms. Comptes Rendus Biologies 337(12): 717–724. https://doi.org/10.1016/j.crvi.2014.09.005
  • Bagella S, Becca G, Bedini G, Caria MC, Pisanu S, … Filigheddu R (2020a) Why so different? A case study about Floras from a Mediterranean island. Phytotaxa 440(2): 129–158. https://doi.org/10.11646/phytotaxa.440.2.4
  • Bagella S, Caria MC, Seddaiu G, Leites L, Roggero PP (2020b) Patchy landscapes support more plant diversity and ecosystem services than wood grasslands in Mediterranean silvopastoral agroforestry systems. Agricultural Systems 185: 102945. https://doi.org/10.1016/j.agsy.2020.102945
  • Bartolucci F, Peruzzi L, Galasso G, Alessandrini A, Ardenghi NMG, … Conti F (2024) A second update to the checklist of the vascular flora native to Italy. Plant Biosystems 158(2): 219–296. https://doi.org/10.1080/11263504.2024.2320126
  • Biurrun I, Pielech R, Dembicz I, Gillet F, Kozub Ł, … Dengler J (2021) Benchmarking plant diversity of Palaearctic grasslands and other open habitats. Journal of Vegetation Science 32(4): e13050. https://doi.org/10.1111/jvs.13050
  • Bonari G, Knollová I, Vlčková P, Xystrakis F, Çoban S, Rosati L, … Chytrý M (2019) CircumMed Pine Forest Database: An electronic archive for Mediterranean and Submediterranean pine forest vegetation data. Phytocoenologia 49(3): 311–318. https://doi.org/10.1127/phyto/2019/0311
  • Braun-Blanquet J (1932) Plant sociology. The study of plant communities. McGraw Hill, London.
  • Bruelheide H, Dengler J, Jiménez‐Alfaro B, Purschke O, Hennekens SM, … Zverev A (2019) sPlot–A new tool for global vegetation analyses. Journal of Vegetation Science 30(2): 161–186. https://doi.org/10.1111/jvs.12710
  • Caballero R, Fernandez-Gonzalez F, Badia RP, Molle G, Roggero PP, … Ispikoudis I (2009) Grazing systems and biodiversity in Mediterranean areas: Spain, Italy and Greece. Pastos 39(1): 9–154. https://doi.org/10.1111/j.1365-2494.2011.00820.x
  • Chelli S, Marignani M, Barni E, Petraglia A, Puglielli G, … Cerabolini BEL (2019) Plant–environment interactions through a functional traits perspective: A review of Italian studies. Plant Biosystems 153(6): 853–869. https://doi.org/10.1080/11263504.2018.1559250
  • Chytrý M, Hennekens SM, Jiménez‐Alfaro B, Knollová I, Dengler J, … Yamalov S (2016) European Vegetation Archive (EVA): An integrated database of European vegetation plots. Applied Vegetation Science 19(1): 173–180. https://doi.org/10.1111/avsc.12191
  • Dengler J, Wagner V, Dembicz I, García-Mijangos I, Naqinezhad A, … Campos JA (2018) GrassPlot–a database of multi-scale plant diversity in Palaearctic grasslands. Phytocoenologia 48(3): 331–347. https://doi.org/10.1127/phyto/2018/0267
  • Dibari C, Pulina A, Argenti G, Aglietti C, Bindi M, … Roggero PR (2021) Climate change impacts on the Alpine, Continental and Mediterranean grassland systems of Italy: A review. Italian Journal of Agronomy 16(3): 1843. https://doi.org/10.4081/ija.2021.1843
  • Euro+Med (2006–2024) Euro+Med PlantBase – The Information Resource for Euro-Mediterranean Plant Diversity. http://ww2.bgbm.org/EuroPlusMed/ [Accessed on 15 July 2024]
  • Fernández-Moya J, San Miguel-Ayanz A, Cañellas I, Gea-Izquierdo G (2011) Variability in Mediterranean annual grassland diversity driven by small-scale changes in fertility and radiation. Plant Ecology 212(5): 865–877. https://doi.org/10.1007/s11258-010-9869-8
  • Grenke JS, Bork EW, Carlyle CN, Boyce MS, Cahill JF (2022) Limited impacts of adaptive multi‐paddock grazing systems on plant diversity in the Northern Great Plains. Journal of Applied Ecology 59(7): 1734–1744. https://doi.org/10.1111/1365-2664.14181
  • Halada L, Evans D, Romão C, Petersen J-E (2011) Which habitats of European importance depend on agricultural practices? Biodiversity and Conservation 20(11): 2365–2378. https://doi.org/10.1007/s10531-011-9989-z
  • Hennekens SM, Schaminée JH (2001) TURBOVEG, a comprehensive data base management system for vegetation data. Journal of Vegetation Science 12(4): 589–591. https://doi.org/10.2307/3237010
  • Janišová M, Iuga A, Ivașcu CM, Magnes M (2021) Grassland with tradition: Sampling across several scientific disciplines. Vegetation Classification and Survey 2: 19–35. https://doi.org/10.3897/VCS/2021/60739
  • Janssen J, Houtepen E, van Proosdij A, Hennekens S (2023) CACTUS–Vegetation database of the Dutch Caribbean Islands. Vegetation Classification and Survey 4: 69–74. https://doi.org/10.3897/VCS.101114
  • Kapfer J, Hédl R, Jurasinski G, Kopecký M, Schei FH, Grytnes JA (2017) Resurveying historical vegetation data–opportunities and challenges. Applied Vegetation Science 20(2): 164–171. https://doi.org/10.1111/avsc.12269
  • Klimek S, Kemmermann AR, Hofmann M, Isselstein J (2007) Plant species richness and composition in managed grasslands: The relative importance of field management and environmental factors. Biological Conservation 134(4): 559–570. https://doi.org/10.1016/j.biocon.2006.09.007
  • Knollová I, Chytrý M, Bruelheide H, Dullinger S, Jandt U, … Essl F (2024) ReSurveyEurope: A database of resurveyed vegetation plots in Europe. Journal of Vegetation Science 35(2): e13235. https://doi.org/10.1111/jvs.13235
  • Kopecký M, Macek M (2015) Vegetation resurvey is robust to plot location uncertainty. Diversity & Distributions 21(3): 322–330. https://doi.org/10.1111/ddi.12299
  • Landucci F, Acosta A, Agrillo E, Attorre F, Biondi E, … Venanzoni R (2012) VegItaly: The Italian collaborative project for a national vegetation database. Plant Biosystems 146(4): 756–763. https://doi.org/10.1080/11263504.2012.740093
  • Malavasi M, Bazzichetto M, Bagella S, Barták V, Depalmas A, … Bagella S (2023) Ecology meets archaeology: Past, present and future vegetation‐derived ecosystems services from the Nuragic Sardinia (1700–580 BCE). People and Nature 5(3): 938–949. https://doi.org/10.1002/pan3.10461
  • Mori A (1966) Sardegna. UTET, Torino.
  • Myers N, Mittermeier RA, Mittermeier CG, Da Fonseca GA, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403(6772): 853–858. https://doi.org/10.1038/35002501
  • Perring MP, Bernhardt‐Römermann M, Baeten L, Midolo G, Blondeel H, … Verheyen K (2018) Global environmental change effects on plant community composition trajectories depend upon management legacies. Global Change Biology 24(4): 1722–1740. https://doi.org/10.1111/gcb.14030
  • Phillips SJ, Dudík M, Elith J, Graham CH, Lehmann A, … Ferrier S (2009) Sample selection bias and presence‐only distribution models: Implications for background and pseudo‐absence data. Ecological Applications 19(1): 181–197. https://doi.org/10.1890/07-2153.1
  • Pignatti S (1982) Flora d’Italia, Edagricole, Bologna.
  • Ribeiro S, Fernandes JP, Espírito-Santo MD (2014) Diversity and floristic patterns of mediterranean grasslands: The relative influence of environmental and land management factors. Biodiversity and Conservation 23(12): 2903–2921. https://doi.org/10.1007/s10531-014-0754-y
  • Rossetti I, Bagella S, Cappai C, Caria MC, Lai R, … Seddaiu G (2015) Isolated cork oak trees affect soil properties and biodiversity in a Mediterranean wooded grassland. Agriculture, Ecosystems & Environment 202: 203–216. https://doi.org/10.1016/j.agee.2015.01.008
  • Sabatini FM, Lenoir J, Hattab T, Arnst EA, Chytrý M, … Bruelheide H (2021) sPlotOpen–An environmentally balanced, open‐access, global dataset of vegetation plots. Global Ecology and Biogeography 30(9): 1740–1764. https://doi.org/10.1111/geb.13346
  • Schaminée J, Janssen J, Haveman R, Hennekens S, Heuvelink G, … Weeda E (2006) Schatten voor de natuur: achtergronden, inventaris en toepassingen van de Landelijke Vegetatie Databank. Alterra.
  • Seddaiu G, Bagella S, Pulina A, Cappai C, Salis L, … Roggero PP (2018) Mediterranean cork oak wooded grasslands: Synergies and trade-offs between plant diversity, pasture production and soil carbon. Agroforestry Systems 92(4): 893–908. https://doi.org/10.1007/s10457-018-0225-7
  • Tárrega R, Calvo L, Taboada Á, García-Tejero S, Marcos E (2009) Abandonment and management in Spanish dehesa systems: Effects on soil features and plant species richness and composition. Forest Ecology and Management 257(2): 731–738. https://doi.org/10.1016/j.foreco.2008.10.004
  • Terzi M, Fernández-González F, Di Pietro R, Theurillat J-P (2024) Phytosociological nomenclature of the class names Helianthemetea guttati, Poetea bulbosae and Stipo giganteae-Agrostietea castellanae. Plant Biosystems 158(1): 70–83. https://doi.org/10.1080/11263504.2023.2287539
  • Vacca A (2016) Characteristics and properties. In: Corsale A, Sistu G (Eds) Surrounded by Water: Landscapes, Seascapes and Cityscapes of Sardinia. Cambridge Scholar Publishing, Cambridge, 48–61.
  • Verdinelli M, Pittarello M, Caria MC, Piga G, Roggero PP, … Bagella S (2022) Congruent responses of vascular plant and ant communities to pastoral land-use abandonment in mountain areas throughout different biogeographic regions. Ecological Processes 11(1): 35. https://doi.org/10.1186/s13717-022-00379-9
  • Watson R, Baste I, Larigauderie A, Leadley P, Pascual U, … Fazel A (2019) Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. IPBES Secretariat, Bonn, Germany, 22–47. https://doi.org/10.1111/padr.12283
  • Yannelli FA, Bazzichetto M, Conradi T, Pattison Z, Andrade BO, … Sperandii MG (2022) Fifteen emerging challenges and opportunities for vegetation science: A horizon scan by early career researchers. Journal of Vegetation Science 33(1): e13119. https://doi.org/10.1111/jvs.13119

Topical Collection: “Vegetation databases: enhancing data integration and accessibility for ecological research”.
login to comment