Lysenko 91,92 | Armin Macanović 93 | Parastoo Mahdavi 94 | Peter Manning 35 | Corrado Marcenò 13 | Vassiliy Martynenko 95 | Maurizio Mencuccini 96 | Vanessa Minden 97 | Jesper Erenskjold Moeslund 54 | Marco Moretti 98 | Jonas V. Müller 99 | Abstract Aims: Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level.Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale. K E Y W O R D S biodiversity, community ecology, ecoinformatics, functional diversity, global scale, macroecology, phylogenetic diversity, plot database, sPlot, taxonomic diversity, vascular plant, vegetation relevé 166 |

Aim Alpine ecosystems differ in area, macroenvironment and biogeographical history across the Earth, but the relationship between these factors and plant species richness is still unexplored. Here, we assess the global patterns of plant species richness in alpine ecosystems and their association with environmental, geographical and historical factors at regional and community scales. Location Global. Time period Data collected between 1923 and 2019. Major taxa studied Vascular plants. Methods We used a dataset representative of global alpine vegetation, consisting of 8,928 plots sampled within 26 ecoregions and six biogeographical realms, to estimate regional richness using sample‐based rarefaction and extrapolation. Then, we evaluated latitudinal patterns of regional and community richness with generalized additive models. Using environmental, geographical and historical predictors from global raster layers, we modelled regional and community richness in a mixed‐effect modelling framework. Results The latitudinal pattern of regional richness peaked around the equator and at mid‐latitudes, in response to current and past alpine area, isolation and the variation in soil pH among regions. At the community level, species richness peaked at mid‐latitudes of the Northern Hemisphere, despite a considerable within‐region variation. Community richness was related to macroclimate and historical predictors, with strong effects of other spatially structured factors. Main conclusions In contrast to the well‐known latitudinal diversity gradient, the alpine plant species richness of some temperate regions in Eurasia was comparable to that of hyperdiverse tropical ecosystems, such as the páramo. The species richness of these putative hotspot regions is explained mainly by the extent of alpine area and their glacial history, whereas community richness depends on local environmental factors. Our results highlight hotspots of species richness at mid‐latitudes, indicating that the diversity of alpine plants is linked to regional idiosyncrasies and to the historical prevalence of alpine ecosystems, rather than current macroclimatic gradients.

Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co‐occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open‐access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local‐to‐regional datasets to openly release data. We thus present sPlotOpen, the largest open‐access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co‐occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot‐level data also include community‐weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01–40,000 m². Time period and grain 1888–2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot‐level records. Software format Three main matrices (.csv), relationally linked.

Aims Assessing climate change impacts on biodiversity is a main scientific challenge, especially in the tropics. We predicted the future of plant species and communities on the unique páramo sky islands by implementing the Spatial Explicit Species Assemblage Modelling framework. Specifically we: (a) calculated species’ maximum dispersal distance; (b) modelled species’ present and future distributions up to 2100; and (c) assembled models into plant communities. The final vulnerability assessment was based on a multi‐dimensional evaluation that considered the species, local plant community and sky island levels. Location Ecuadorian super‐páramo (>4,200 m). Methods Using species trait data, the maximum dispersal distance of 435 species was calculated. Species distribution models (SDM) were fitted to obtain current and future distribution predictions based on dispersal and bioclimatic factors. The final current assemblages and those for 2100 were achieved by stacking all probabilistic SDMs and applying the probability ranking rule. The vulnerability of each sky island was evaluated by quantifying richness and composition changes. Results Maximum dispersal distances ranged between 0.008 m/year and 6,027 m/year, and across all scenarios, 70% of models showed a net loss in species distribution, while 9% of all species were predicted to undergo extinction in Ecuador by 2100. Local richness was estimated to decrease by 56.63% on average, and compositional changes in each sky island suggested a mean loss of 64.74% of their original species pool against a 12.97% gain. Finally, 5% of the sky island floras reconverted from high‐elevation to low‐elevation species. These numbers were usually more important for high‐elevation species and the mountains Pichincha, Ilinizas and Antisana. Conclusions This methodological pioneer study provides novel insight into the future of páramo biodiversity. Significant losses in species distribution and changes in community richness and composition suggest drastic impacts and call for further research considering additional factors, such as land use. Finally, we recommend focusing monitoring and conservation strategies on the northern Ecuadorian sky islands as a priority.

The páramo region in the northern Andes is very biodiverse, presents high endemism and provides many ecosystem services. Unfortunately, the páramo is critically threatened by anthropogenic activities and climate change. Further research and development of efficient conservation strategies are therefore needed for the region, but they are often limited by the lack of consistent biological data-sources. Here we present VegPáramo (GIVD ID: SA-00-002, http://www.givd.info/ID/SA-00-002), a flora and vegetation database for the páramo based on phytosociological vegetation plots. VegPáramo contains data from 3,000 georeferenced vegetation plots with updated nomenclature. The database is accessible through the webportal http://www.vegparamo.com, from which floristic and vegetation data can be freely consulted and downloaded. This new tool should make future botanical and ecological páramo studies easier. VegPáramo is already geographically and floristically representative for the páramo region, but we hope it will continue to grow in scientific significance via new data addition and revision.

BackgroundThe páramo is a high-elevation biogeographical province in the northern Andes, known for its great biodiversity and ecosystem services. Because there have been very few biogeographic studies encompassing the entire province to date, this study aimed at conducting a phytogeographical regionalisation of the páramo. Specifically, (1) clustering analyses were conducted to identify the main phytogeographical units in the three altitudinal belts: sub-páramo, mid-páramo and super-páramo, and examine their diagnostic flora, (2) an ordination complemented the geo-climatic characterization of the obtained units and (3) a hierarchical classification transformation was obtained to evaluate the relationships between units.MethodsThe study area included the entire Andean páramo range in northern Peru, Ecuador, Colombia and Venezuela. The analyses were based on 1,647 phytosociological plots from the VegPáramo database. The K-means non-hierarchical clustering technique was used to obtain clusters identifiable as phytogeographical units, and the Ochiai fidelity index was calculated to identify their diagnostic species. A principal component analysis was conducted to obtain the geo-climatic characterization of each unit. Finally, the relationships between clusters were traced using a hierarchical plot-based classification.ResultsFifteen clusters were obtained, 13 natural and two artificial, of which two represented the sub-páramo, nine the mid-páramo and four the super-páramo. Even though data representativeness was a potential limitation to segregate certain sub-páramo and super-páramo units, the overall bioregionalisation was robust and represented important latitudinal, altitudinal and climatic gradients.DiscussionThis study is the first to bioregionalise the páramo province based on a substantial widely distributed biological dataset, and therefore provides important novel scientific insight on its biogeography. The obtained phytogeographical units can be used to support further research on the páramo at smaller scale and on the humid Neotropical high-elevation ecosystems at broader-scale. Finally, several units were highlighted in our results as particularly worthy of further scientific and conservation focus.

Questions: What are the functional trade-offs of vascular plant species in global alpine ecosystems? How is functional variation related to vegetation zones, climatic groups and biogeographic realms? What is the relative contribution of macroclimate and evolutionary history in shaping the functional variation of alpine plant communities? Location: Global. Methods:We compiled a data set of alpine vegetation with 5,532 geo-referenced plots, 1,933 species and six plant functional traits. We used principal component analysis to quantify functional trade-offs among species and trait probability density to assess the functional dissimilarity of alpine vegetation in different vegetation zones, climatic groups and biogeographic realms. We used multiple regression on distance matrices to model community functional dissimilarity against environmental and phylogenetic dissimilarity, controlling for geographic distance. Results:The first two PCA axes explained 66% of the species' functional variation and were related to the leaf and stem economic spectra, respectively. Trait probability density was largely independent of vegetation zone and macroclimate but differed across biogeographic realms. The same pattern emerged for both species pool and community levels. The effects of environmental and phylogenetic dissimilarities on community functional dissimilarity had similar magnitude, while the effect of geographic distance was negligible.Conclusions: Plant species in alpine areas reflect the global variation of plant function, but with a predominant role of resource use strategies. Current macroclimate exerts a limited effect on alpine vegetation, mostly acting at the community level in combination with evolutionary history. Global alpine vegetation is functionally unrelated to the vegetation zones in which it is embedded, exhibiting strong functional convergence across regions.

Most of the world’s mountain glaciers have been retreating for more than a century in response to climate change. Glacier retreat is evident on all continents, and the rate of retreat has accelerated during recent decades. Accurate, spatially explicit information on the position of glacier margins over time is useful for analyzing patterns of glacier retreat and measuring reductions in glacier surface area. This information is also essential for evaluating how mountain ecosystems are evolving due to climate warming and the attendant glacier retreat. Here, we present a non-comprehensive spatially explicit dataset showing multiple positions of glacier fronts since the Little Ice Age (LIA) maxima, including many data from the pre-satellite era. The dataset is based on multiple historical archival records including topographical maps; repeated photographs, paintings, and aerial or satellite images with a supplement of geochronology; and own field data. We provide ESRI shapefiles showing 728 past positions of 94 glacier fronts from all continents, except Antarctica, covering the period between the Little Ice Age maxima and the present. On average, the time series span the past 190 years. From 2 to 46 past positions per glacier are depicted (on average: 7.8).