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In the Anthropocene, the world’s plant diversity is threatened with extinction and the erosion of the genetic diversity of natural populations. According to the State of the World’s Plants and Fungi 2020 of the Royal Botanic Gardens, Kew, two out of five of the ~350,000 known vascular plant species are at risk of extinction. Despite the considerable toolkit of biodiversity conservation practices, usually it is hard to choose the best option to stop biodiversity loss. Ex situ conservation has seen massive development due to radical losses of natural ecosystems, and its incrementing necessity has been underscored by Target 8 of the 2011-2020 Global Strategy for Plant Conservation. As we crossed the finish line of this strategy in 2020, a review of the accumulated knowledge on the ex situ living collections has become particularly important. Despite the increasing attention received by ex situ conservation, studies on the sustainability, quality, and usability of the plant material prior to establishing the garden collections are few, leaving major gaps unfilled in terms of best ex situ conservation practices. Here we present an overview of the results and experiences in ex situ conservation focusing on living plant collections, with the aim of guiding conservation practitioners towards the most efficient working methods. We evaluate the future needs and perspectives of this conservation technique, based on case studies on both woody and herb species. Possible conservation applications and priorities suggested for future works are summarized.

Phenotypic plasticity can mask population genetic differentiation, reducing the predictability of trait-environment relationships. In short-lived plants, reproductive traits may be more genetically determined due to their direct impact on fitness, whereas vegetative traits may show higher plasticity to buffer short-term perturbations. Combining a multi-treatment greenhouse experiment with global field observations for the short-lived Plantago lanceolata, we 1) disentangled the genetic and plastic responses of functional traits to a set of environmental drivers and 2) assessed the utility of trait-environment relationshisps inferred from observational data for predicting genetic differentiation. Reproductive traits showed distinct genetic differentiation that was highly predictable from observational data, but only when correcting traits for differences in their (labile) biomass component. Vegetative traits showed higher plasticity and contrasting genetic and plastic responses, leading to unpredictable trait patterns. Our study suggests that genetic differentiation may be inferred from observational data only for the traits most closely related with fitness.

© 2021 The Authors., Aims: Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location: Palaearctic biogeographic realm. Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions: The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology., GrassPlot development has been supported by the Bavarian Research Alliance (BayIntAn_UBT_2017_58), the Eurasian Dry Grassland Group (EDGG) and the International Association for Vegetation Science (IAVS); IB, CorM, JAC, IGM, DGM, MHe, DL and MTo were supported by the Basque Government (IT936‐16); CorM, IAx, MCh, JDa, PD, MHá, ZL, ZPr, EŠ and LT were supported by the Czech Science Foundation (19‐28491X); TR was supported by the Estonian Research Council (PUT1173); RJP was funded by the Strategic Research Programme of the Scottish Government’s Rural and Environmental Science and Analytical Services Division”; SBa was supported by the GINOP‐2.3.2‐15‐2016‐00019 project; GFi was partially supported by the MIUR initiative “Department of excellence” (Law 232/2016)"; BJA was funded by the Spanish Research Agency (grant AEI/ 10.13039/501100011033); AK, VB, IM, DS, IV and DV were supported by the National Research Foundation of Ukraine (2020.01/0140); MP and AH were supported by the Estonian Research Council (PRG874, PRG609), and the European Regional Development Fund (Centre of Excellence EcolChange); Data collection of HCP was funded by FORMAS (Swedish Research Council for Environment, Agricultural Science and Spatial Planning) and The Swedish Institute; JR was supported by the Czech Science Foundation (grant No. 20‐09895S) and the long‐term developmental project of the Czech Academy of Sciences (RVO 67985939); ATRA was funded by the Grant of Excellence Departments, MIUR‐Italy (ARTICOLO 1, COMMI 314 – 337 LEGGE 232/2016); JMA was supported by Carl Tryggers stiftelse för vetenskaplig forskning and Qatar Petroleum; AAli was supported by the Jiangsu Science and Technology Special Project (Grant No. BX2019084), and Metasequoia Faculty Research Startup Funding at Nanjing Forestry University (Grant No. 163010230), and he is currently supported by Hebei University through Faculty Research Startup Funding Program; ZB was supported by the NKFI K 124796 grant; The GLORIA‐ Aragón project of JLBA was funded by the Dirección General de Cambio Climático del Gobierno de Aragón (Spain); MCs and LDem were supported by DG Environment through the European Forum on Nature Conservation and Pastoralism and Barbara Knowles Fund, in collaboration with Pogány‐havas Association, Romania; JDa was partially supported by long‐term research development project no. RVO 67985939 of the Czech Academy of Sciences; BD and OV were supported by the NKFI KH 126476, NKFI KH 130338, NKFI FK 124404 and NKFI FK 135329 grants; BD, OV and AKe were supported by the Bolyai János Scholarship of the Hungarian Academy of Sciences; BE was funded by the Environmental Department of the Tyrolean Federal State Government, the MAB Programme of the Austrian Academy of Science, the Mountain Agriculture Research Unit and the Alpine Research Centre Obergurgl of Innsbruck University. The GLORIA projects of BE were funded by the EU project no. EVK2‐CT‐2000‐00056, the Earth System Sciences Program of the Austrian Academy of Sciences (project MEDIALPS), the Amt für Naturparke, Autonome Provinz Bozen‐Südtirol, the Südtiroler Wissenschaftsfonds and the Tiroler Wissenschaftsfonds; RGG was supported by the Spanish Ministry of Research to sample GLORIA sites in central Spain (CGL 2008‐00901/BOS) and present works by the Autonomous Region of Madrid (REMEDINAL TE‐CM, S2018/EMT‐4338); MJ was supporteLatviaed by Latvia Grant No. 194051; NP and SŠ were partly supported by the Slovenian Research Agency, core fundings P1‐0403 and J7‐1822.

Genetic differentiation and phenotypic plasticity jointly shape intraspecific trait variation, but their roles differ among traits. In short- lived plants, reproductive traits may be more genetically determined due to their impact on fitness, whereas vegetative traits may show higher plasticity to buffer short- term perturbations. Combining a multi- treatment greenhouse experiment with observational field data throughout the range of a widespread short- lived herb, Plantago lanceolata, we (1) disentangled genetic and plastic responses of functional traits to a set of environmental drivers and (2) assessed how genetic differentiation and plasticity shape observational trait– environment relationships. Reproductive traits showed distinct genetic differentiation that largely determined observational patterns, but only when correcting traits for differences in biomass. Vegetative traits showed higher plasticity and opposite genetic and plastic responses, masking the genetic component underlying field- observed trait variation. Our study suggests that genetic differentiation may be inferred from observational data only for the traits most closely related to fitness.

AimTo assess if and how species’ range size relates to range structure, if the observed geographic range properties can be retrieved from predicted maps based on species distribution modeling, and whether range properties are predictable from biogeophysical factors.LocationEuropeTime periodCurrentMajor taxa studied813 vascular plant species endemic to EuropeMethodsWe quantified the size and spatial structure of species’ geographic ranges and compared ranges currently occupied with those predicted by species distribution models (SDMs). SDMs were constructed using complete occurrence data from the Atlas Florae Europaeae and climatic, soil and topographic predictors. We used landscape metrics to characterize range size, range division and patch shape structure, and analysed the phylogenetic, geographic and ecological drivers of species’ range size and structure using phylogenetic generalized least squares (pGLS).ResultsRange structure metrics were mostly decoupled from species’ range size. We found large differences in range metrics between observed and predicted ranges, in particular for species with intermediate observed range size and occupied area, and species with low and high observed patch size distribution, geographic range filling, patch shape complexity and geographic range fractality. Elevation heterogeneity, proximity to continental coasts, Southerly or Easterly geographic range positions and narrow ecological niche breadth constrained species’ observed range size and range structure to different extents. The strength and direction of the relationships differed between observed and predicted ranges.Main conclusionsSeveral range structure metrics, in addition to range size, are needed to adequately describe and understand species’ ranges. Species’ range structure can be well explained by geophysical factors and species niche width, albeit not consistently for observed and predicted ranges. As range structure can have important ecological and evolutionary consequences, we highlight the need to develop better predictive models of range structure than provided by current SDMs, and we identify the kinds of species for which this is most necessary.

Summary Weed species loss due to intensive agricultural land use has raised the need to understand how traditional cropland management has sustained a diverse weed flora. We evaluated to what extent cultivation practices and environmental conditions affect the weed species composition of a small-scale farmland mosaic in Central Transylvania (Romania). We recorded the abundance of weed species and 28 environmental, management and site context variables in 299 fields of maize, cereal and stubble. Using redundancy analysis, we revealed 22 variables with significant net effects, which explained 19.2% of the total variation in species composition. Cropland type had the most pronounced effect on weed composition with a clear distinction between cereal crops, cereal stubble and maize crops. Beyond these differences, the environmental context of croplands was a major driver of weed composition, with significant effects of geographic position, altitude, soil parameters (soil pH, texture, salt and humus content, CaCO3, P2O5, K2O, Na and Mg), as well as plot location (edge vs. core position) and surrounding habitat types (arable field, road margin, meadow, fallow, ditch). Performing a variation partitioning for the cropland types one by one, the environmental variables explained most of the variance compared with crop management. In contrast, when all sites were combined across different cropland types, the crop-specific factors were more important in explaining variance in weed community composition.

Land management practices directly impact on the occurrence and condition of natural capital stocks, which can be measured using species diversity and abundance metrics. Species identity and abundance drive ecosystem service supply, either through effects of local diversity and/or through the presence of service providing species. However, the influence of management practices on the provision of ecosystem services is not adequately understood. We grouped grassland plant species into six groups according to desirable attributes (palatability and nutritional value to livestock; medicinal or aromatic compounds; nectar production; pollen production; nitrogen fixation; and endemic and red listed species), which we recognise as ecosystem service ‘provider groups’, and tested the influence of three land management practices (abandonment of mowing, grazing, and mowing) on diversity and abundance within these groups in upland temperate grasslands of Transylvania (Romania). All three management practices favoured at least one provider group, but hay making in upland grasslands favoured more provider groups than abandonment of mowing or grazing. The effects of management on diversity and abundance within several provider groups diverged from the effects on overall species diversity and abundance. Management, through changes in species composition, favours certain provider groups, and hence ecosystem services, over others. The provider group approach is more useful than overall species diversity metrics for assessing the provision of ecosystem services from landscapes and can be used to inform the development of agri-environment schemes and conservation policies aimed at meeting priorities for ecosystem service provision.

Correlative species distribution models are based on the observed relationship between species’ occurrence and macroclimate or other environmental variables. In climates predicted less favourable populations are expected to decline, and in favourable climates they are expected to persist. However, little comparative empirical support exists for a relationship between predicted climate suitability and population performance. We found that the performance of 93 populations of 34 plant species worldwide – as measured by in situ population growth rate, its temporal variation and extinction risk – was not correlated with climate suitability. However, correlations of demographic processes underpinning population performance with climate suitability indicated both resistance and vulnerability pathways of population responses to climate: in less suitable climates, plants experienced greater retrogression (resistance pathway) and greater variability in some demographic rates (vulnerability pathway). While a range of demographic strategies occur within species’ climatic niches, demographic strategies are more constrained in climates predicted to be less suitable.

Significance We found that long-distance dispersal and repeated introductions by humans have shaped adaptive potential in a globally distributed invasive species. Some plant species, therefore, do not need strong demographic changes to overcome environmental constraints that exist in the native range; simply mixing genetic stock from multiple populations can provide an adaptive advantage. This work highlights the value of preventing future introduction events for problematic invasive species, even if the species already exists in an area., When plants establish outside their native range, their ability to adapt to the new environment is influenced by both demography and dispersal. However, the relative importance of these two factors is poorly understood. To quantify the influence of demography and dispersal on patterns of genetic diversity underlying adaptation, we used data from a globally distributed demographic research network comprising 35 native and 18 nonnative populations of Plantago lanceolata. Species-specific simulation experiments showed that dispersal would dilute demographic influences on genetic diversity at local scales. Populations in the native European range had strong spatial genetic structure associated with geographic distance and precipitation seasonality. In contrast, nonnative populations had weaker spatial genetic structure that was not associated with environmental gradients but with higher within-population genetic diversity. Our findings show that dispersal caused by repeated, long-distance, human-mediated introductions has allowed invasive plant populations to overcome environmental constraints on genetic diversity, even without strong demographic changes. The impact of invasive plants may, therefore, increase with repeated introductions, highlighting the need to constrain future introductions of species even if they already exist in an area.

GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). Following a previous Long Database Report (Dengler et al. 2018, Phyto- coenologia 48, 331–347), we provide here the first update on content and functionality of GrassPlot. The current version (GrassPlot v. 2.00) contains a total of 190,673 plots of different grain sizes across 28,171 independent plots, with 4,654 nested-plot series including at least four grain sizes. The database has improved its content as well as its functionality, including addition and harmonization of header data (land use, information on nestedness, structure and ecology) and preparation of species composition data. Currently, GrassPlot data are intensively used for broad-scale analyses of different aspects of alpha and beta diversity in grassland ecosystems.

Plant population responses are key to understanding the effects of threats such as climate change and invasions. However, we lack demographic data for most species, and the data we have are often geographically aggregated. We determined to what extent existing data can be extrapolated to predict population performance across larger sets of species and spatial areas. We used 550 matrix models, across 210 species, sourced from the COMPADRE Plant Matrix Database, to model how climate, geographic proximity and phylogeny predicted population performance. Models including only geographic proximity and phylogeny explained 5–40% of the variation in four key metrics of population performance. However, there was poor extrapolation between species and extrapolation was limited to geographic scales smaller than those at which landscape scale threats typically occur. Thus, demographic information should only be extrapolated with caution. Capturing demography at scales relevant to landscape level threats will require more geographically extensive sampling.\ud

A Frivaldszky-bibircsvirág a Délkeleti-Kárpátok orchideaflórájának egyik ritkasága, amelynek fajneve híres Balkán kutatónk, Frivaldszky Imre (1799–1870) emlékét őrzi. Hegyvidéki lápokon, vízszivárgós, üde helyeken fordul elő a Balkán-félsziget hegyvidékein (Bulgária, Románia, Görögország, Macedónia, Montenegró, Albánia). A fajra a Kárpátokban először Heuffel János bukkant rá a Szárkő-hegységben. Habár a fajt Simonkai 1874-ben gyűjtötte a Retyezátban (Zenóga- és Bukura-tó), a példánya (BP33967) azonosságában bizonytalan volt, ezért az a halvány bibircsvirág (Gymnadenia albida) alá sorolva szerepel monográfiájában. Azóta több helyről előkerült a Retyezátból, így a Peleaga-havasról, a Zănoaga-, Zănoguţa-, Ana- és Bucura-tavak mellől és a Judele-völgyből, továbbá a Szárkő-hegység egy-két pontjáról is. Az utolsó szerzőnek a faj egy öt évtizeddel korábbi, csupán egy fitocönológiai tabellában dokumentált előfordulását sikerült megerősítenie a Hargita hegységben (Keleti-Kárpátok). Ez a lelőhely a faj areájának északi határán helyezkedik el, ezért növényföldrajzi szempontból igazán fontos adat. A közlemény bemutatja a faj felfedezésének történetét és jelenleg ismert elterjedését és veszélyeztetettségi státuszát a Kárpátokban, továbbá a Hargita hegységi élőhelyét.

Global change has made it important to understand the factors that shape species' distributions. Central to this area of research is the question of whether species' range limits primarily reflect the distribution of suitable habitat (i.e. niche limits) or arise as a result of dispersal limitation. Over-the-edge transplant experiments and ecological niche models are commonly used to address this question, yet few studies have taken advantage of a combined approach for inferring the causes of range limits. Here, we synthesise results from existing transplant experiments with new information on the predicted suitability of sites based on niche models. We found that individual performance and habitat suitability independently decline beyond range limits across multiple species. Furthermore, inferences from transplant experiments and niche models were generally concordant within species, with 31 out of 40 cases fully supporting the hypothesis that range limits are niche limits. These results suggest that range limits are often niche limits and that the factors constraining species' ranges operate at scales detectable by both transplant experiments and niche models. In light of these findings, we outline an integrative framework for addressing the causes of range limits in individual species.

This report describes the Romanian Grassland Database (RGD), registered under EU-RO-008 in the Global Index of Vegetation-Plot Databases (GIVD). This collaborative initiative aims to collect all available vegetationplot data (relevés) of grasslands and other open habitats from the territory of Romania to provide them for science, nationally and internationally, e.g. via the European Vegetation Archive (EVA) and the global database "sPlot". The database mainly contains vegetation-plots from not only wet, mesic, dry, saline, alpine and rocky grasslands, but also other vegetation types like heathlands, mires, ruderal, segetal, aquatic and cryptogamdominated vegetation. Currently, 21,685 relevés have mainly been digitised from literature sources (90%), while the remainder comes from individual unpublished sources (10%). We report on the background and history of the RGD, explain its "Data Property and Governance Rules" under which data are contributed and retrieved, and outline how the RGD can contribute to research in the fields of vegetation ecology, macroecology and conservation.

Invasive plant species are human-introduced, nonnative, and damaging. They can restructure natural habitats, change community composition, disrupt food webs, and degrade ecosystem services. Global climatic changes are often thought to exacerbate invasions (1), but no consensus exists over the generality of this phenomenon (2). As a consequence, anticipating areas of high invasion risk or decreased impact in the future is still uncertain. By combining experimental biogeography with demographic models, Merow et al. (3) develop climate driven process-based models to predict population growth or decline under current and future climate scenarios for two established and damaging invasive plant species in New England, United States. They find that one invasive species will likely perform better, whereas the other will do worse in areas that are currently occupied. Forecasting the distribution and performance of invasive species under a changing climate comes with particular challenges. Invasive species have not had time to colonize all favorable habitats available in the nonnative range. This nonequilibrium situation is problematic for correlative species distribution models, which may then use incomplete occurrences in the nonnative range as inputs for predicting suitable climatic conditions. However, predictions can be improved by using occurrence data from the native range (4). A more concerning challenge is that invasives may be able to establish in environmental conditions the species has not encountered in the native range (4⇓⇓–7), even if those conditions occur but are unoccupied in the native range (6). Niche … [↵][1]1To whom correspondence should be addressed. Email: buckleyy{at}tcd.ie. [1]: #xref-corresp-1-1

Tredennick et al. criticize one of our statistical analyses and emphasize the low explanatory power of models relating productivity to diversity. These criticisms do not detract from our key findings, including evidence consistent with the unimodal constraint relationship predicted by the humped-back model and evidence of scale sensitivities in the form and strength of the relationship. Fil: Pither, Jason. University of British Columbia; Canadá Fil: Fraser, Lauchlan H.. Thompson Rivers University; Canadá Fil: Jentsch, Anke. University of Bayreuth; Alemania Fil: Sternberg, Marcelo. Tel Aviv University; Israel Fil: Zobel, Martín. University of Tartu; Estonia Fil: Cahill, James. University of Alberta; Canadá Fil: Cabido, Marcelo Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina Fil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina Fil: Enrico, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina Fil: Carlyle, Cameron N.. University of Alberta; Canadá Fil: Chelli, Stefano. University of Camerino; Italia Fil: Cserg, Anna Maria. The University of Dublin; Irlanda Fil: Ensing, David. Queen’s University; Canadá Fil: Fidelis, Alessandra. Universidade Estadual Paulista; Brasil Fil: Garris, Heath W.. Thompson Rivers University; Canadá Fil: Henry, Hugh A. L.. University of Western Ontario; Canadá Fil: Höhn, Maria. Corvinus University of Budapest; Hungría Fil: Klironomos, John. University of British Columbia; Canadá Fil: Koorem, Kadri. University of Tartu; Estonia Fil: Lawrence Lodge, Rachel. University of Otago; Nueva Zelanda Fil: Manning, Peter. Senckenberg Gesellschaft für Naturforschung; Alemania Fil: Mitchell, Randall J.. University of Akron; Estados Unidos Fil: Moora, Mary. University of Tartu; Estonia Fil: Pillar, Valerio D.. Federal University of Rio Grande do Sul; Brasil Fil: Stotz, Gisela C.. University of Alberta; Canadá Fil: Sugiyama, Shu-ichi. Hirosaki University; Japón Fil: Szentes, Szilárd. Szent István University; Hungría Fil: Tungalag, Radnaakhand. National University of Mongolia; Mongolia Fil: Undrakhbold, Sainbileg. Free University of Bozen-Bolzano; Italia Fil: Wellstein, Camila. Free University of Bozen-Bolzano; Italia Fil: Zupo, Talita. Universidade Estadual Paulista; Brasil