Vegetation Database Research Articles

Vegetation classification in the Neotropics – Novel insights from Latin America and the Caribbean

Our editorial introduces a Special Collection of scientific articles on current vegetation research in the most biodiverse of all biogeographic realms, the Neotropics. It contains nine scientific contributions dedicated to vegetation data, description and classification. Four research papers provide new vegetation classifications of important Neotropical biomes, namely the Arid Chaco in Argentina, Mexican temperate forests, and Andean wetlands in the Argentine Puna and southern Peru. Furthermore, one study provides a novel bioclimatic-vegetation classification approach applied to Mexican vegetation, while another proposes a new synthesis of the South American terrestrial biomes as geocomplexes. Finally, three vegetation databases are presented in the Special Collection: ArgVeg – Database of Central Argentina (GIVD ID: SA-AR-002), CACTUS – Vegetation database of the Dutch Caribbean Islands (GIVD ID: SA-00-004) and VegAndes: the vegetation database for the Latin American highlands (GIVD ID: SA-00-005). The Special Collection provides fundamental data and tools to better understand the diversity and complexity of Neotropical vegetation. Abbreviations: GIVD = Global Index of Vegetation-Plot Databases, IAVS = International Association for Vegetation Science, IAVS-LACS = IAVS Regional Section for the Latin America and the Caribbean, VCS = Vegetation Classification and Survey

A synthesized field survey database of vegetation and active-layer properties for the Alaskan tundra (1972–2020)

Abstract. Studies in recent decades have shown strong evidence of physical and biological changes in the Arctic tundra, largely in response to rapid rates of warming. Given the important implications of these changes for ecosystem services, hydrology, surface energy balance, carbon budgets, and climate feedbacks, research on the trends and patterns of these changes is becoming increasingly important and can help better constrain estimates of local, regional, and global impacts as well as inform mitigation and adaptation strategies. Despite this great need, scientific understanding of tundra ecology and change remains limited, largely due to the inaccessibility of this region and less intensive studies compared to other terrestrial biomes. A synthesis of existing datasets from past field studies can make field data more accessible and open up possibilities for collaborative research as well as for investigating and informing future studies. Here, we synthesize field datasets of vegetation and active-layer properties from the Alaskan tundra, one of the most well-studied tundra regions. Given the potentially increasing intensive fire regimes in the tundra, fire history and severity attributes have been added to data points where available. The resulting database is a resource that future investigators can employ to analyze spatial and temporal patterns in soil, vegetation, and fire disturbance-related environmental variables across the Alaskan tundra. This database, titled the Synthesized Alaskan Tundra Field Database (SATFiD), can be accessed at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for Biogeochemical Dynamics (Chen et al., 2023: https://doi.org/10.3334/ORNLDAAC/2177).

A climate analog approach to evaluate seed transfer and vegetation transitions

IntroductionThere is growing recognition that restoring species diversity is crucial to maintaining ecological functions and services. Increasing the diversity of species used in restoration programs has placed greater emphasis on determining the seed transfer needs for a wider array of plants. However, many plants, outside of commercial forestry, lack information that would provide guidance on seed transfer for current or future climates. Generalized seed transfer approaches use climate partitioning to approximate adaptive differentiation among populations and provide an estimation of seed transfer distance for such species.MethodsHerein, we describe a generalized seed transfer approach that uses Euclidean distance of 19 climate variables within North America (from northern Honduras to the Arctic). Euclidean distances are used to identify climate analogs from vegetation databases of about 685,000 plots, an average density of 1 plot per 32 km2. Analogs are classified into three thresholds (strong, moderate, and weak) that correspond to altitudinal climate gradients and are guided by the scientific literature of observed adaptive variation of natural tree populations and seed transfer limits.ResultsFor strong threshold observations, about 97% of the analogs had climate distances equivalent to ≤300 m elevation, whereas for the weak threshold observations, 53% had an elevation equivalence of ≤300 m. On average 120, 267, and 293 m elevation separated two points under strong, moderate, and weak thresholds, respectively. In total, threshold classification errors were low at 13.9%.DiscussionWe use examples of plot data identified from a reference period (1961–1990) and mid-century (2056–2065) analogs across North American biomes to compare and illustrate the outcomes of projected vegetation change and seed transfer. These examples showcase that mid-century analogs may be located in any cardinal direction and vary greatly in spatial distance and abundance from no analog to hundreds depending on the site. The projected vegetative transitions will have substantial impacts on conservation programs and ecosystem services. Our approach highlights the complexity that climate change presents to managing ecosystems, and the need for predictive tools in guiding land management decisions to mitigate future impacts caused by climate change.

How to classify forests? A case study from Central Europe

Aims: Inconsistent treatment of the vegetation layers is one of the main problems in the floristic classification of forests. In this study I investigate whether a classification based solely on woody species leads to units similar to the Braun-Blanquet system or to something completely different. Study area: Austria (Central Europe) and adjacent regions. Methods: 23,681 forest relevés from the Austrian Vegetation Database were classified using TWINSPAN. Spruce and pine plantations and stands with a cover of non-native woody species > 5% were excluded from the dataset. Only native tree and shrub species were used in the classification while herbs, dwarf shrubs, cryptogams and all records of woody species in the herb layer were omitted. Results: The TWINSPAN classification revealed elevation (i.e., climate) as the main floristic gradient in the data set. Within lowland communities, soil moisture was the dominant factor. The higher units of the Braun-Blanquet system were mostly well reproduced. Conclusions: The higher levels of the phytosociological forest classification (class, order, partly also alliance) can basically be defined by taking only the shrub and tree layer into account. However, all past and current classifications suffer from arbitrary exceptions to this rule. This leads to many inconsistencies and blurs the main biogeographical patterns within European forests. Here I argue that using the tree and shrub species for defining the higher levels and the understorey species for defining the lower ones is best suited to meet the properties that users would expect from a good forest classification. Taxonomic reference: Fischer et al. (2008). Syntaxonomic reference: Mucina et al. (2016) if not stated otherwise. Abbreviations: EVC = EuroVegChecklist (Mucina et al. 2016).

Vegetation quality assessment: A sampling-based loss-gain accounting framework for native, disturbed and reclaimed vegetation

Governments and society increasingly are demanding that industrial projects result in a net positive impact (NPI) on biodiversity. Impacts are commonly measured in terms of losses and gains of area and quality of vegetation, where quality refers to how closely a site matches the condition of native vegetation in its undisturbed state. Existing vegetation quality frameworks share a number of limitations, including little or no replication, uncertain scope of inference, vulnerability to bias, and inability to measure error. Here we present the Vegetation Quality Assessment (VQA) framework, a sampling-based extension of Quality Hectares that measures vegetation quality in terms of overlap between the probability distributions of ecological indicators at a project site and in undisturbed (benchmark) vegetation of the same kind. Distribution overlap incorporates natural variation at the landscape scale and provides an intuitive measure of quality that varies between 0 and 1. Indicators are measured using a stratified-random sampling design that minimizes bias and supports inference at the scale of the project landscape. Confidence limits of quality and quality hectares are determined by bootstrapping; power and minimum sample sizes are estimated by Monte Carlo simulation. Multiple assessments track losses and gains of quality hectares and enable accurate accounting of progress to NPI. The VQA framework can be implemented using a variety of vegetation sampling methods, allowing existing vegetation databases to be leveraged as sources of data. We conclude by demonstrating the application of VQA at several mining operations in the Elk Valley of southeastern British Columbia, Canada.

Mid-term changes of dry grasslands with conservation management in the Hainburger Berge Mountains

Our study focused on evaluating plant diversity and vegetation changes in the dry grasslands of the Hainburger Berge Mountains protected within the NATURA 2000 reserve Hundsheimer Berge. Traditionally, these grasslands have been managed through intensive grazing but have experienced significant land-use changes since the 1950′s, including a prolonged period of abandonment. We investigated rocky and xeric grasslands of Festuco-Brometea, and mesic grasslands of Molinio-Arrhenatheretea using six nested plot series of various spatial scales. We also resampled relevés that were initially recorded in 2007 and analyzed them alongside older relevés (1930–2001) from the Austrian Vegetation Database. The compositional data variation was primarily influenced by moisture and nutrient gradients along the first DCA axis, and soil reaction and light availability along the second DCA axis. Grazing intensity had a significant effect on species richness at small spatial scales, while at larger scales, habitat conditions played a more crucial role. A continuous successional development could be detected in grassland composition, leading to a denser vegetation canopy and increased moisture and nutrient availability. However, plot resampling since 2007 revealed only minor changes, primarily due to interannual dynamics rather than a clear directional trend. We conclude that the current conservation management of rocky and xeric grasslands is proving successful in maintaining grassland biodiversity as well as high number and proportion of endangered plant species. Controlling grazing intensity, involving more farmers, and implementing flexible rules for grazing, mowing, and subsidy eligibility, could be instrumental in achieving conservation targets in the future.

A semi-automated hybrid schema matching framework for vegetation data integration

Integrating disparate and distributed vegetation data is critical for consistent and informed national policy development and management. Australia’s National Vegetation Information System (NVIS) under the Department of Climate Change, Energy, the Environment and Water (DCCEEW) is the only nationally consistent vegetation database and hierarchical typology of vegetation types in different locations. Currently, this database employs manual approaches for integrating disparate state and territory datasets which is labour intensive and can be prone to human errors. To cope with the ever-increasing need for up to date vegetation data derived from heterogeneous data sources, a Semi-Automated Hybrid Matcher (SAHM) is proposed in this paper. SAHM utilises both schema level and instance level matching following a two-tier matching framework. A key novel technique in SAHM called Multivariate Statistical Matching is proposed for automated schema scoring which takes advantage of domain knowledge and correlations between attributes to enhance the matching. To verify the effectiveness of the proposed framework, the performance of the individual as well as combined components of SAHM have been evaluated. The empirical evaluation shows the effectiveness of the proposed framework which outperforms existing state of the art methods like Cupid, Coma, Similarity Flooding, Jaccard Leven Matcher, Distribution Based Matcher, and EmbDI. In particular, SAHM achieves between 88% and 100% accuracy with significantly better F1 scores in comparison with state-of-the-art techniques. SAHM is also shown to be several orders of magnitude more efficient than existing techniques.

Transcaucasian Vegetation Database – a phytosociological database of the Southern Caucasus

The Caucasus is a hotspot of global biodiversity. However, even in the era of big data, this region remains underrepresented in public vegetation-plot databases. The Transcaucasian Vegetation Database (GIVD code AS-00-005) is a novel dataset which primarily aims to compile, store and share vegetation-plot records sampled by the Braun-Blanquet approach and originating from Transcaucasia (the Southern Caucasus), i.e. the countries of Armenia, Azerbaijan and Georgia. The database currently contains 2,882 vegetation plots. The oldest plots originate from 1929, the newest from 2022, and their collection is ongoing. The data include mesophilous forests (phytosociological class Carpino-Fagetea) and various alpine and subalpine communities (e.g. Carici-Kobresietea, Loiseleurio-Vaccinietea) – selected other habitats are also represented. Most of the plots (84%) are georeferenced, 36% with high precision of 25 m or less. The database includes 2,500 taxon names; Asteraceae, Poaceae, Fabaceae and Rosaceae represent the most common families. Vascular plants are recorded in all plots, while data on species composition of bryophytes are available for 11% of plots. The database intends to contribute to the complex biodiversity research of this biologically unique territory. The data might be used in diverse projects in botany, biogeography, ecology and nature protection. Taxonomic reference: The Plant List (http://www.theplantlist.org/ [Accessed 10 Jan 2023]). Syntaxonomic reference: Mucina et al. (2016). Abbreviations: TVD = Transcaucasian Vegetation Database.

Spatial variation of sulfur in terrestrial ecosystems in China: Content, density, and storage

Sulfur (S) is an important macronutrient that is widely distributed in nature. Understanding the patterns and mechanisms of S dynamics is of great significance for accurately predicting the geophysical and chemical cycles of S and formulating policies for S emission and management. We systematically investigated and integrated 17,618 natural plots in China's terrestrial ecosystems and built a S density database of vegetation (including leaves, branches, stems, and roots) and surface soil (0–30 cm depth). The biogeographic patterns and environmental drivers of the S content, density, and storage in the vegetation and soil of terrestrial ecosystems were explored. Vegetation and soil were the major components of terrestrial ecosystems, storing a total of 2228.77 ± 121.72 Tg S, with mean S densities of 4.32 ± 0.04 × 10−2, and 267.93 ± 14.94 × 10−2 t hm−2, respectively. The forest was the most important vegetation S pool and their S storage accounted for about 55.28 % of the total vegetation S storage, whereas soil S pools of croplands and other vegetation types (e.g., deserts and wetlands) accounted for about 63.18 % of the total soil S storage. The mean S density (2.18 ± 0.02 × 10−2 t hm−2) and S storage (12.45 ± 0.31 Tg) of plant roots were significantly higher than those of other organs. The spatial variation in the S density was mainly regulated by climate and soil properties, reflecting the physiological adaptation mechanisms of plants by adjusting the S uptake and distribution to cope with climate change. In this study, the spatial patterns of S density and storage in vegetation and soil in terrestrial ecosystems of China and their response to environmental factors on a national scale were systematically studied. The results provide insights into the biological functions of S and its role in plant–environment interactions.

National vegetation database of Montenegro

National vegetation database of Montenegro

Vegetation databases augment but do not replace species distribution atlases in species richness assessment

Mapping of species richness (SR) patterns is pivotal for biogeography and nature conservation. Vegetation plot databases serve as a new source of information, but they are inherently affected by the methodological background of data collection. This background could bias the SR assessment. Here, we compared two different data sources: (1) a vegetation-plot database, the Polish Vegetation Database (PVD), and (2) a species distribution atlas, the Atlas of Distribution of Vascular Plants in Poland (ATPOL). We calculated species richness recorded by the PVD (PVD SR), the ATPOL (ATPOL SR), and the two harmonized databases (total SR). The sampling bias in the PVD (PVD bias) was assessed by calculating the number of species found in the ATPOL, but not recorded by the PVD. Analogically, the ATPOL bias was calculated. We calculated correlation between the PVD bias and both the number of vegetation plots and the number of vegetation classes. Additionally, the completeness of the PVD dataset was assessed using the species accumulation curve approach. The mean slope of the last 1% of plots number was used as a proxy of inventory completeness and correlated with PVD bias. The results show that the SR documented by the PVD is significantly lower than that recorded by the ATPOL, yet it indicates a significantly increased total SR. The PVD SR increased as more plots and vegetation classes were sampled. However, even with the best sampling, the PVD SR was still significantly lower than that in the ATPOL. Further, although the values for the species accumulation curves suggested high sampling completeness in the PVD, the real bias was still substantial, and no correlation was found between PVD bias and species accumulation curve values. In general, the PVD underestimated SR at a landscape level, yet it augmented information stored in the ATPOL. The underestimations could result from limited sampling effort or from focusing on particular vegetation types, as well as the exclusion of transitional vegetation types and/or disturbed patches of vegetation from sampling.

Spatial patterns of vascular plant species richness in Poland - a data set

Recognition of species richness spatial patterns is important for nature conservation and theoretical studies. Inventorying species richness, especially at a larger spatial extent is challenging, thus different data sources are joined and harmonized to obtain a comprehensive data set. Here we present a new data set showing vascular plant species richness in Poland based on a grid of 10 × 10 km squares. The data set was created using data from two sources: the Atlas of Distribution of Vascular Plants in Poland and the Polish Vegetation Database. Using this data set, we analysed 2,160 species with taxonomical nomenclature according to the Euro + Med PlantBase checklist in 3,283 squares covering the entire territory of Poland (ca. 312,000 km2). The species were divided into groups according to their status and frequency of distribution, and the statistics for each square were obtained. For purposes of analysis, sampling bias was assessed. The data set promotes theoretical analysis on species richness and reinforces the planning of nature conservations.

CACTUS – Vegetation database of the Dutch Caribbean Islands

The vegetation database CACTUS (registered in GIVD under SA-00-004) aims to bring together all plot-based relevés from the Dutch Caribbean Islands that are available from literature, unpublished resources, and recent field surveys. The database currently contains 2,701 vegetation descriptions. The database is used for vegetation classification, to investigate vegetation change over time, to assist in the planning of vegetation surveys, as a source for plant species distribution maps, and to inform nature conservation and policy. Taxonomic references: Van Proosdij (2012) for the Leeward Islands, Axelrod (2017, 2021) for the Windward Islands, except for St. Martin (Howard 1974-1989).

Classification of European oak–hornbeam forests and related vegetation types

AbstractAimsOak–hornbeam forests and related vegetation types (phytosociological order Carpinetalia betuli) are widespread in temperate western Eurasia. However, their national classification systems are poorly compatible, and a broad‐scale classification based on numerical analyses is lacking. Therefore, we aimed to establish a unified formalized classification system based on a large data set of vegetation plots covering the entire range of these forests.LocationEurope, Anatolia, Caucasus and northern Iran.MethodsWe compiled a data set of 15,817 vegetation plots from the European Vegetation Archive and the Hyrcanian Forest Vegetation Database, using the formal definition of the EUNIS habitat type T1E Carpinus and Quercus mesic deciduous forest. We classified the data set using TWINSPAN. Biogeographically and ecologically similar plot clusters were merged into oak–hornbeam forest types, which were interpreted as alliances. We also developed expert systems for automatically classifying vegetation at the alliance level for both the EuroVegChecklist (EVC) system and the revised classification. In addition, we calculated ordinations to show the major gradients in the species composition of the data set.ResultsWe present a revised classification system of the order Carpinetalia betuli with nine alliances, including basic descriptions of their species composition, distribution, ecology and syntaxonomy. The analyses largely supported the biogeographic concept of classification, analogous to EVC. Compared to EVC, we recognized an additional alliance Physospermo verticillati‐Quercion cerridis (southern Italy) but found no support for the alliances Astrantio‐Carpinion, Erythronio‐Carpinion and Scillo‐Quercion. The greatest difference in species composition was found between the southern and northern‐northeastern Carpinetalia types. Expert systems for the revised classification system (~89% of plots classified) and the EVC system (~72%) are also included.ConclusionsWe provide the first comprehensive overview of alliances of the order Carpinetalia betuli across its whole distribution range. The associated expert systems allow consistent application of the classification of these forests in nature conservation, habitat monitoring, and biodiversity and ecological research.

VegAndes: the vegetation database for the Latin American highlands

In the era of Big Data, Latin American countries and biomes remain underrepresented. To remediate this issue, promoting repositories for biodiversity data focused on Latin America is a main priority. VegAndes -Dpt the vegetation database for the Latin American highlands (GIVD: SA-00-005), is a novel dataset for georeferenced and standardized information on vascular pants in the region. The database compiles 5,340 vegetation plots sampled above the montane treeline and below the permanent snowline in 11 Latin American countries and spanning over seven decades. VegAndes currently encompasses 5,804 taxon names, corresponding to 3,858 accepted names, as well as 136 syntaxon names. The database is nested within a scientific consortium of Latin American experts on highland vegetation and piloted from the University of the Andes (Colombia). Because the VegAndes data can support multi-scale studies in botany, ecology and biogeography, the database makes an essential contribution to biodiversity research and management perspectives in Latin America. Taxonomic reference: TROPICOS (preferential source, www.tropicos.org/), World Flora Online (secondary source, www.worldfloraonline.org/).

ArgVeg – Database of Central Argentina

The ArgVeg is a repository of vegetation-plots data registered in the Global Index of Vegetation Databases (GIVD ID: SA-AR-002). This report presents its main characteristics, potential uses, and future perspectives. In September 2022, the database contained 1092 vegetation-plot records, including 1184 valid native and non-native vascular plants. The database covers the main vegetation types of nine vegetation units of the Chaco, Espinal and Pampean phytogeographic provinces in central Argentina. Those types include native forests, shrublands, grasslands, halophytic vegetation and non-native woody communities present in either lowlands or mountain areas. This database represents a significant improvement in the availability of floristic information from subtropical and warm temperate areas in South America, which still represents a major knowledge gap worldwide. ArgVeg reflects the outstanding plant diversity of central Argentina and it is managed by the Plant Ecology and Phytogeography Group at the Multidisciplinary Institute of Plant Biology (Córdoba, Argentina). Not only the high biodiversity but also the complex landscape heterogeneity are the most important characteristics of the vegetation in this region. We hope to increase the number of plots in the near future and to strengthen regional and global networks to enhance the conservation and management of these endangered ecosystems.

The dynamics of the perennial grass crops communities on the restoration succession gradient

The trends of the coenoflora structure dynamics of the perennial grass crops communities were characterized on the gradient of restorative succession in the conditions of the steppe and forest-steppe zones of the Southern Urals. Using an agglomerative cluster analysis, four community groups have been identified, which corresponds to the stages of succession and reflecting the age of the communities (from 1 to 16 years or more). It is demonstrated that the succession gradient complicates the species composition, the species richness of the communities increases by almost 2 times. An analysis of the activity index change for the coenoflora core species at each stage has been carried out. It has been revealed that the activity of sown herbs species decreases, while the total activity of well-eaten species as well as the feed value of the whole phytocoenoses increases with the age of communities. A community of each stage of succession is marked by a group of highly active species, the functional composition and coenotic affinity of which changes. The activity of apophyte species increases while the activity of synanthropic ones decreases. There is a natural complication of the phytosociological spectrum from species of affine to classes of synanthropic vegetation Sisymbrietea and Artemisietea to species of classes of natural vegetation meadows (Molinio-Arrhenatheretea) and steppes (Festuco-Brometea). At the same time, the most active substitution of synanthropic species for natural ones occurs after the second stage of succession, i.e. its significant acceleration is observed after the age of 11 years. According to the results of the ordination analysis (DCA-ordination) with an additional assessment of the contribution of environmental variables, the leading in the differentiation of the species composition of communities is the factor of the age of communities, the factor of humidification of habitats makes a smaller contribution. According to the results of the comparison of the studied phytocoenoses with the data of weed, meadow and steppe communities from the database of non-forest vegetation of the Southern Urals (1660 releves), the central position of perennial grass crop communities on the gradient of restorative succession from disturbed arable land vegetation to natural (steppes) (steppes) and quasi-natural (meadows) vegetation types is demonstrated. Thus, a high importance of perennial grass crops for the creation of stable phytocoenoses of high forage value, which can be used for the restoration of biodiversity in the forest-steppe and steppe regions, is revealed.

How vegetation classification and mapping may influence conservation: The example of Brazil’s Native Vegetation Protection Law

The way vegetation is officially named, classified, and identified has critical implications for ecosystems and biodiversity conservation. Yet little attention is given to how such issues hinder the efficacy of laws mandating environmental conservation on private land. In the Brazilian Amazon where half of the land is now already under private tenure or is available for future land-uses, differences in vegetation mapping and interpretation directly affect the level of protection in private rural properties, especially in transition areas where forest and savanna areas intermingle. Since Brazil’s Native Vegetation Protection Law (NVPL) attaches a higher percentage of protection to forest-located properties, landowners may be tempted to use conflicting mappings and different vegetation classifications to claim their properties are located in areas other than forests to reduce their conservation requirements. In this paper, we compare three official vegetation databases and examine different law interpretation scenarios to assess the extent to which the level of private conservation may fluctuate. We found a difference of up to 430,000 km2 of protected vegetation (an area the size of Iraq) according to the database and vegetation characteristics chosen. This technical ambiguity may lead to make additional deforestation legal or reduce sharply the amount of vegetation to be restored for these areas, if left unaddressed. Clarifying the database and criteria used to define forest is critical, especially as Brazilian states may make different choices in that regard, and cases in which loopholes are exploited occurred in the recent past. Given the importance of this region for global biodiversity conservation and climate, we highlight the urgent need to: (1) support additional research to clarify vegetation characteristics and location; (2) agree on a harmonized methodology to determine forests for NVPL implementation, and (3) explore alternative criteria for defining forests when databases conflict.

Detailed Mapping and Modeling of Urban Vegetation: What Are the Benefits for Microclimatic Simulations with Town Energy Balance (TEB) at Neighborhood Scale?

Abstract Cities develop a specific climate related to their morphology and the materials that constitute them. The addition of vegetation in urban areas induces cooling and shading effects that can modify local climate and thermal comfort conditions. The Town Energy Balance (TEB) urban canopy model offers several configurations for a more or less fine-tuned consideration of natural covers and associated physical processes in the urban environment. This study aims to evaluate the sensitivity of TEB to the representation of vegetation and the resolution of the chosen databases in the simulation of microclimatic variables, at the scale of a heterogeneous urban neighborhood located in Toulouse, France. First, the effect of the improved description of the vegetation input to the model is highlighted by comparing the results obtained with a readily available national database and then with a very-high-resolution satellite-derived vegetation database. Second, the two vegetation parameterizations, with or without explicit tree stratum, that are available in the TEB model are evaluated and compared. Measurements carried out on specific routes and stop points in a neighborhood of Toulouse allowed microclimatic variables to be evaluated. Results show that refining the vegetation database can somehow improve the modeling of air temperature. As a result of enhancing the vegetation description in the model, that is, physical processes associated with the presence of trees in urban canyons, the air temperature, but also the wind and the thermal comfort index, are better simulated. These results are encouraging for the use of TEB as a decision support tool for urban planning purposes.

AMS-VegBank: a new database of vegetation plots for the Italian territory

The importance of collection, storage and exchange of georeferenced vegetation plot-based data has significantly grown in the recent decades, because of the new potentialities offered by ecoinformatics. In this article we introduce the Alma Mater Studiorum – University of Bologna vegetation database (AMS-VegBank; GIVD code EU-IT-021) compiling 17,505 georeferenced vegetation-plot observations within a time span of 90 years. This database includes 337,799 occurrence data of vascular plant species, belonging to many different habitat types. The historical relevance of the presented database is highlighted by the presence of some of the most ancient vegetation-plot observations in Europe (years 1930–1938). The geographic coverage of the database is mostly for Italian territory but it includes also data from other countries. The thematic focuses represented in the database are various, such as small Mediterranean islands, the Dolomite Mountains and the Italian National Parks. The large amount of historical plots available for the country not previously included in existing databases, combined with the constant action to improve the georeferencing of existing data and the addition of new data, highlight the uniqueness of this database. AMS-VegBank represents thus an important tool for studying plant biodiversity within the context of continental and global vegetation plot databases. Taxonomic reference: All plant names reported in this article follow the nomenclature by Pignatti et al. (2017–2019). Abbreviations: EVA = European Vegetation Archive; GIVD = Global Index of Vegetation-Plot Databases.