We assess progress toward the protection of 50% of the terrestrial biosphere to address the species-extinction crisis and conserve a global ecological heritage for future generations. Using a map of Earth's 846 terrestrial ecoregions, we show that 98 ecoregions (12%) exceed Half Protected; 313 ecoregions (37%) fall short of Half Protected but have sufficient unaltered habitat remaining to reach the target; and 207 ecoregions (24%) are in peril, where an average of only 4% of natural habitat remains. We propose a Global Deal for Nature—a companion to the Paris Climate Deal—to promote increased habitat protection and restoration, national- and ecoregion-scale conservation strategies, and the empowerment of indigenous peoples to protect their sovereign lands. The goal of such an accord would be to protect half the terrestrial realm by 2050 to halt the extinction crisis while sustaining human livelihoods.

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(2017): Naturalized alien flora of the world: species diversity, taxonomic and phylogenetic patterns, geographic distribution and global hotspots of plant invasion. Using the recently built Global Naturalized Alien Flora (GloNAF) database, containing data on the distribution of naturalized alien plants in 483 mainland and 361 island regions of the world, we describe patterns in diversity and geographic distribution of naturalized and invasive plant species, taxonomic, phylogenetic and life-history structure of the global naturalized flora as well 204 Preslia 89: 203-274, 2017 as levels of naturalization and their determinants. The mainland regions with the highest numbers of naturalized aliens are some Australian states (with New South Wales being the richest on this continent) and several North American regions (of which California with 1753 naturalized plant species represents the world's richest region in terms of naturalized alien vascular plants). England, Japan, New Zealand and the Hawaiian archipelago harbour most naturalized plants among islands or island groups. These regions also form the main hotspots of the regional levels of naturalization, measured as the percentage of naturalized aliens in the total flora of the region. Such hotspots of relative naturalized species richness appear on both the western and eastern coasts of North America, in north-western Europe, South Africa, south-eastern Australia, New Zealand, and India. High levels of island invasions by naturalized plants are concentrated in the Pacific, but also occur on individual islands across all oceans. The numbers of naturalized species are closely correlated with those of native species, with a stronger correlation and steeper increase for islands than mainland regions, indicating a greater vulnerability of islands to invasion by species that become successfully naturalized. South Africa, India, California, Cuba, Florida, Queensland and Japan have the highest numbers of invasive species. Regions in temperate and tropical zonobiomes harbour in total 9036 and 6774 naturalized species, respectively, followed by 3280 species naturalized in the Mediterranean zonobiome, 3057 in the subtropical zonobiome and 321 in the Arctic. The New World is richer in naturalized alien plants, with 9905 species compared to 7923 recorded in the Old World. While isolation is the key factor driving the level of naturalization on islands, zonobiomes differing in climatic regimes, and socioeconomy represented by per capita GDP, are central for mainland regions. The 11 most widely distributed species each occur in regions covering about one third of the globe or more in terms of the number of regions where they are naturalized and at least 35% of the Earth's land surface in terms of those regions' areas, with the most widely distributed species Sonchus oleraceus occuring in 48% of the regions that cover 42% of the world area. Other widely distributed species are Ricinus communis, Oxalis corniculata, Portulaca oleracea, Eleusine indica, Chenopodium album, Cap...

This dataset provides the Global Naturalized Alien Flora (GloNAF) database, version 1.2. GloNAF represents a data compendium on the occurrence and identity of naturalized alien vascular plant taxa across geographic regions (e.g. countries, states, provinces, districts, islands) around the globe. The dataset includes 13,939 taxa and covers 1,029 regions (including 381 islands). The dataset is based on 210 data sources. For each taxon‐by‐region combination, we provide information on whether the taxon is considered to be naturalized in the specific region (i.e. has established self‐sustaining populations in the wild). Non‐native taxa are marked as “alien”, when it is not clear whether they are naturalized. To facilitate alignment with other plant databases, we provide for each taxon the name as given in the original data source and the standardized taxon and family names used by The Plant List Version 1.1 (http://www.theplantlist.org/). We provide an ESRI shapefile including polygons for each region and information on whether it is an island or a mainland region, the country and the Taxonomic Databases Working Group (TDWG) regions it is part of (TDWG levels 1–4). We also provide several variables that can be used to filter the data according to quality and completeness of alien taxon lists, which vary among the combinations of regions and data sources. A previous version of the GloNAF dataset (version 1.1) has already been used in several studies on, for example, historical spatial flows of taxa between continents and geographical patterns and determinants of naturalization across different taxonomic groups. We intend the updated and expanded GloNAF version presented here to be a global resource useful for studying plant invasions and changes in biodiversity from regional to global scales. We release these data into the public domain under a Creative Commons Zero license waiver (https://creativecommons.org/share-your-work/public-domain/cc0/). When you use the data in your publication, we request that you cite this data paper. If GloNAF is a major part of the data analyzed in your study, you should consider inviting the GloNAF core team (see Metadata S1: Originators in the Overall project description) as collaborators. If you plan to use the GloNAF dataset, we encourage you to contact the GloNAF core team to check whether there have been recent updates of the dataset, and whether similar analyses are already ongoing.

The present investigation was part of a fen restoration project, which deals with the rehabilitation of a deeply drained peat land used for intensive agriculture for more than 200 years. Consequently, the conditions for restoration are unfavorable. The hay of well‐developed fen meadows from nature reserves in the region appeared to contain enough viable seeds to act as a source for the development of target communities when spread out on bare peat after topsoil removal. Repeated vegetation analysis showed that a combination of topsoil removal and hay transfer resulted in the establishment of new populations in the target area for 70% of the species of the donor area. Germination conditions of fen species were investigated to determine the optimal combination for stimulating germination rates. Most fen species were found to be dormant, and it was shown that dormancy could be broken with fluctuating light and temperature cycles and stratification pre‐treatment.

Despite the paramount role of plant diversity for ecosystem functioning, biogeochemical cycles, and human welfare, knowledge of its global distribution is still incomplete, hampering basic research and biodiversity conservation.Here, we used machine learning (random forests, extreme gradient boosting, and neural networks) and conventional statistical methods (generalized linear models and generalized additive models) to test environment-related hypotheses of broad-scale vascular plant diversity gradients and to model and predict species richness and phylogenetic richness worldwide. To this end, we used 830 regional plant inventories including c. 300 000 species and predictors of past and present environmental conditions.Machine learning showed a superior performance, explaining up to 80.9% of species richness and 83.3% of phylogenetic richness, illustrating the great potential of such techniques for disentangling complex and interacting associations between the environment and plant diversity. Current climate and environmental heterogeneity emerged as the primary drivers, while past environmental conditions left only small but detectable imprints on plant diversity.Finally, we combined predictions from multiple modeling techniques (ensemble predictions) to reveal global patterns and centers of plant diversity at multiple resolutions down to 7774 km 2 . Our predictive maps provide accurate estimates of global plant diversity available at grain sizes relevant for conservation and macroecology.

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Question: Can we predict the spatial distribution of plant communities in semi‐arid rangelands based on a limited set of environmental variables? Where are priority areas for conservation located? Location: Al Jabal al Akhdar, Sultanate of Oman. Methods: A Classification Tree Analysis (CTA) was used to model the presence/absence of seven rangeland communities and agricultural areas based on seven selected environmental predictor variables. The latter were either obtained from existing digital datasets or derived from a digital elevation model and satellite images, whereas the grazing intensity was spatially modelled with the kernel density estimation technique. The resulting decision rules of a CTA were applied for predictive mapping within the study area (400 km2, resolution of 5 m) by means of ENVI's decision tree classifier. Plant communities of natural rangelands were subsequently evaluated to determine priority areas for nature conservation. Results: Altitude, grazing intensity and landform revealed the highest predictive power. Most of the rangelands were predicted as Sideroxylon–Oleetum. The overall classification accuracy was 89%, whereby agricultural areas and the Ziziphus spina‐christi‐Nerium oleander community at wadi sites had no misclassification. Inaccuracies occurred mainly because of low sample numbers and errors in available maps of predictor variables. The highest rank for nature conservation was observed for the Teucrio‐Juniperetum occupying 20% of the study area. Conclusions: Vegetation mapping using CTA is a valuable tool for rangeland monitoring and identification of key representative areas for nature conservation. An extrapolation of the model used might be feasible to regions adjacent to the central Hajar Mountains.