• Energy Research

AbstractAimsThe rapid increase in the number of species that have naturalized beyond their native range is among the most apparent features of the Anthropocene. How alien species will respond to other processes of future global changes is an emerging concern and remains poorly misunderstood. We therefore ask whether naturalized species will respond to climate and land use change differently than those species not yet naturalized anywhere in the world.LocationGlobal.MethodsWe investigated future changes in the potential alien range of vascular plant species endemic to Europe that are either naturalized (n = 272) or not yet naturalized (1,213) outside of Europe. Potential ranges were estimated based on projections of species distribution models using 20 future climate‐change scenarios. We mapped current and future global centres of naturalization risk. We also analysed expected changes in latitudinal, elevational and areal extent of species’ potential alien ranges.ResultsWe showed a large potential for more worldwide naturalizations of European plants currently and in the future. The centres of naturalization risk for naturalized and non‐naturalized plants largely overlapped, and their location did not change much under projected future climates. Nevertheless, naturalized plants had their potential range shifting poleward over larger distances, whereas the non‐naturalized ones had their potential elevational ranges shifting further upslope under the most severe climate change scenarios. As a result, climate and land use changes are predicted to shrink the potential alien range of European plants, but less so for already naturalized than for non‐naturalized species.Main conclusionsWhile currently non‐naturalized plants originate frequently from mountain ranges or boreal and Mediterranean biomes in Europe, the naturalized ones usually occur at low elevations, close to human centres of activities. As the latter are expected to increase worldwide, this could explain why the potential alien range of already naturalized plants will shrink less.

AbstractAimProtected areas (PAs) play an important role in biodiversity conservation, but remain increasingly threatened by invasive alien plant species (IAPS) in conjunction with global climate change. The latter is modifying the distribution of the former, and the magnitude and direction of distributional changes are predicted to vary depending on species dispersal mode. Here, we address the question of whether clonality is expected to affect the future invasion pattern in PAs.LocationWorldwide.Time period1950–2100.Major taxa studied36 invasive alien plant species.MethodsWe used ensembles of three species distribution models (GLM, GAM and Maxent) based on >70,000 occurrence records to project the distribution of 36 of the world's most invasive clonal and non‐clonal plants in >20,000 PAs. Projections were based on three greenhouse gas concentration scenarios (low, medium and high) for 2080.ResultsClimate change showed little impact on the global invasion pattern in PAs, and clonality showed little effect when all biomes were processed in concert. However, we discerned that the future invasion risk of clonal IAPS markedly increased in biomes located at high elevation and high latitude compared with non‐clonal IAPS, while the risk decreased in lower‐elevation tropical and subtropical biomes where asexual reproduction may be a less successful trait. We also showed that invasion hot spots overlapped with biodiversity hot spots and two realms (i.e. Nearctic and Palearctic), which calls for bridging the gap between invasion and conservation sciences and for more concerted management strategies.Main conclusionsWe suggest that effective management of IAPS in PAs should consider in which biomes PAs are located as well as the reproductive traits of IAPS that are present or may become so.

Modelling the potential alien ranges of plant species under current climatic and land-use conditions Species selection We focused exclusively on vascular plant species endemic to Europe. Here, ‘Europe’ is used in a geographical sense and defined as bordered by the Arctic Ocean to the north, the Atlantic Ocean to the west (the Macaronesian archipelagos were excluded), the Ural Mountains and the Caspian Sea to the east, and the Lesser Caucasus and the Mediterranean Sea to the south (Mediterranean islands included, Anatolia excluded). The most recent version of the database ‘Endemic vascular plants in Europe’ (EvaplantE; Hobohm, 2014), containing > 6,200 endemic plant taxa, was used here as a baseline for species selection. Scientific names were standardized based on The Plant List (http://www.theplantlist.org/). This taxonomic standardization was done with the R package ‘Taxonstand’ (Cayuela et al., 2017). Infraspecific taxa were excluded from the list, resulting in 4,985 species. Compilation of occurrence records To comprehensively compile the distribution of our studied set of endemic species in their native continent, we combined occurrence data in Europe from five sources. The first source was the ‘Global Biodiversity Information Facility’ (GBIF), one of the largest and most widely used biodiversity databases (https://www.gbif.org/). Currently, GBIF provides access to more than 600,000 distributional records for European endemic plant species. Records of European endemic plants deemed erroneous were discarded. All occurrences from GBIF were downloaded using the R package ‘rgbif’ (Chamberlain et al., 2019). The second source was the ‘EU-Forest’ dataset, providing information on European tree species distribution, including more than half a million occurrences at a 1 km (~ 50 arcsec at 50° latitude) resolution (Mauri et al., 2017). The third source we used was the ‘European Vegetation Archive’ (EVA), which assembles observations from more than one million vegetation plots across Europe (Chytrý et al., 2016). The fourth source was the digital version of the Atlas Florae Europaeae offering gridded maps. The fifth source was the ‘Plant Functional Diversity of Grasslands’ network (DIVGRASS), combining data on plant diversity across ~ 70,000 vegetation plots in French permanent grasslands (Violle et al., 2015). When several occurrences from these different sources were duplicated on the same 0.42° × 0.42° grid cell, only one record was kept to avoid pseudoreplication. After removing duplicate records, species with fewer than 10 occurrences were not further considered since the resulting SDM might be insufficiently accurate. The final dataset comprised 104,313 occurrences for 1,485 European endemic species. Environmental variables We selected six environmental predictors related to climate, soil physico-chemical properties and land use, commonly considered to shape the spatial distribution of plants (Gurevitch et al., 2006). Annual mean temperature (°C), annual sum of precipitation (mm) and precipitation seasonality representing the period 1979-2013 were extracted from the CHELSA climate model at a 30 arcsec resolution (Karger et al., 2017). Organic carbon content (g per kg) and soil pH in the first 15 cm of topsoil were extracted at a 1 km resolution from the global gridded soil information database SoilGrids (Hengl et al., 2014). The proportion of primary land-cover (land with natural vegetation that has not been subject to human activity since 1500) averaged over the period 1979-2013 in each 0.5° resolution grid cell (variable ‘gothr’) based on the Harmonized Global Land Use dataset was also used (Chini et al., 2014). Environmental variables were aggregated at a spatial resolution of 0.42° × 0.42° to approach the cell size of the occurrence records with the coarsest resolution (i.e. the Atlas Florae Europaeae). Species distribution modelling The potential distribution of 1,485 European endemic plant species was predicted by estimating environmental similarity to the sites of occurrence in Europe. To increase robustness of the predictions, we used six methods to generate species distribution models (SDMs): generalized additive models; generalized linear models; generalized boosting trees; maximum entropy; multivariate adaptive regression splines; and random forests. We evaluated the predictive performance of each SDM using a repeated split sampling approach in which SDMs were calibrated over 75% of the data and evaluated over the remaining 25%. This procedure was repeated 10 times. The evaluation was performed by measuring the area under the receiver operating characteristic (ROC) curve (AUC) and the true skill statistic (TSS). Continuous model predictions were transformed into binary ones by selecting the threshold maximizing TSS to ensure the most accurate predictions since it is based on both sensitivity and specificity. Results of the different SDM methods were aggregated into a single consensus projection (i.e. map) to reduce uncertainties associated with each technique. To ensure the quality of the ensemble SDMs, we only kept the projections for which the accuracy estimated by AUC and TSS were higher than 0.8 and 0.6, respectively, and assembled the selected SDMs using a committee-average approach with a weight proportional to their TSS evaluation. The entire species distribution modelling process was performed within the ‘biomod2’ R platform (Thuiller et al., 2009). Modelling the potential alien ranges of plant species under future climatic conditions To model the potential spread of the European endemic flora outside of Europe in the future (period 2061-2080), we used projections for the four representative concentration pathways (RCPs) of both climate and land cover data for the years 2061-2080. Due to substantial climatic differences predicted by different general circulation models (GCMs), which result in concomitant differences in species range projections, simulations of future climate variables were based on five different GCMs: CCSM4, CESM1-CAM5, CSIRO-mk3-6-0, IPSL-CM5A-LR and MIROC5. References Cayuela, L., Stein, A., & Oksanen, J. (2017). Taxonstand: taxonomic standardization of plant species names v.2.1. R Foundation for Statistical Computing. Available at https://cran.r-project.org/web/packages/Taxonstand/index.html. Chamberlain, S., Barve, V., Desmet, P., Geffert, L., Mcglinn, D., Oldoni, D., & Ram, K. (2019). rgbif: interface to the Global 'Biodiversity' Information Facility API v.1.3.0. R Foundation for Statistical Computing. Available at https://cran.r-project.org/web/packages/rgbif/index.html. Chini, L.P., Hurtt, G.C., & Frolking, S. (2014). Harmonized Global Land Use for Years 1500 – 2100, V1. Data set. Oak Ridge National Laboratory Distributed Active Archive Center, USA. Available at http://daac.ornl.gov Chytrý, M., Hennekens, S. M., Jiménez-Alfaro, B., Knollová, I., Dengler, J., Jansen, F., … Yamalov, S. (2016). European Vegetation Archive (EVA): an integrated database of European vegetation plots. Applied Vegetation Science, 19, 173–180. Hengl, T., de Jesus, J. M., MacMillan, R. A., Batjes, N. H., Heuvelink, G. B. M., Ribeiro, E., … Gonzalez, M. R. (2014). SoilGrids1km — Global Soil Information Based on Automated Mapping. PLoS ONE, 9, e105992. Hobohm, C. (Ed.) (2014). Endemism in Vascular Plants. [Plant and Vegetation 9]. Dordrecht, The Netherlands: Springer. Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., … Kessler, M. (2017). Climatologies at high resolution for the earth’s land surface areas. Scientific Data, 4, 170122. Mauri, A., Strona, G., & San-Miguel-Ayanz, J. (2017). EU-Forest, a high-resolution tree occurrence dataset for Europe. Scientific Data, 4, 160123. Violle, C., Choler, P., Borgy, B., Garnier, E., Amiaud, B., Debarros, G., … Viovy, N. (2015). Vegetation ecology meets ecosystem science: permanent grasslands as a functional biogeography case study. Science of the Total Environment, 534, 43–51. Aims: The rapid increase in the number of species that have naturalized beyond their native range is among the most apparent features of the Anthropocene. How alien species will respond to other processes of future global changes is an emerging concern and remains largely misunderstood. We therefore ask whether naturalized species will respond to climate and land-use change differently than those species not yet naturalized anywhere in the world. Location: Global Methods: We investigated future changes in the potential alien range of vascular plant species endemic to Europe that are either naturalized (n = 272) or not yet naturalized (1,213) outside of Europe. Potential ranges were estimated based on projections of species distribution models using 20 future climate-change scenarios. We mapped current and future global centres of naturalization risk. We also analyzed expected changes in latitudinal, elevational and areal extent of species’ potential alien ranges. Results: We showed a large potential for more worldwide naturalizations of European plants currently and in the future. The centres of naturalization risk for naturalized and non-naturalized plants largely overlapped, and their location did not change much under projected future climates. Nevertheless, naturalized plants had their potential range shifting poleward over larger distances, whereas the non-naturalized ones had their potential elevational ranges shifting further upslope under the most severe climate change scenarios. As a result, climate and land-use changes are predicted to shrink the potential alien range of European plants, but less so for already naturalized than for non-naturalized species. Main conclusions: While currently non-naturalized plants originate frequently from mountain ranges or boreal and Mediterranean biomes in Europe, the naturalized ones usually occur at low elevations, close to human centres of activities. As the latter are expected to increase worldwide, this could explain why the potential alien range of already naturalized plants will shrink less. This dataset includes raster files (.gri format) representing global maps of habitat suitability probability for the 1,485 most widespread European endemic plant species under current conditions (folder '1979-2013') and 20 future scenarios (folder '2061-2080'). Future scenarios have been generated for four representative concentration pathways (RCP) of both climate and land cover data (folder '26' for RCP 2.6, '45' for RCP 4.5, '60' for RCP 6.0, '85' for RCP 8.5) and five different general circulation models (CCSM4, CESM1-CAM5, CSIRO-mk3-6-0, IPSL-CM5A-LR and MIROC5). The spatial resolution of these maps is 0.4166667° × 0.4166667°. The geographic coordinate system is World Geodetic System 1984 (EPSG: 4326). 

Protected areas are the cornerstone on which conservation strategies are often built. Adapting systems of protected areas to rapid global changes is critical to meet the challenge of conservation in biodiversity hotspots. Twenty years ago, Jaffre et al. (Biodivers Conserv 7:109–135, 1998) warned that the system of protected areas in the global biodiversity hotspot of New Caledonia was not adequate to conserve the threatened plant species. Here, we examine changes in major threats to the New Caledonian flora and whether the system of protected areas has been improved to address these threats. While some improvements have been made, many key shortcomings identified by Jaffre et al. (Biodivers Conserv 7:109–135, 1998) have not been addressed and the majority of threatened species remain outside protected area. During the same time, thousands of hectares of vegetation have burned outside and inside protected areas, a hundred new mining concessions were issued and the rate of nickel mining has doubled. Better protection of remaining natural vegetation on ultramafic substrates, which are severely impacted by both mining activities and fires, is urgently needed. Further convergence between research and conservation actions is needed to tackle increasing threats to the unique New Caledonian flora.

AbstractAimIsland tropical montane cloud forests (TMCFs) host a disproportionally high share of the global biodiversity and provide critical ecosystem services to vulnerable insular societies. However, this ecosystem is imperilled by anthropogenic impacts including climate change that might push TMCFs towards higher elevations. The elevation at which TMCFs start varies greatly among islands and may depend on topographically driven local climate, which may in turn be influenced by large‐scale climate. Thus, a necessary prerequisite to assessing the vulnerability of island TMCFs to climate change is to determine the role of island features versus regional climate in influencing local climate at the lower TMCF ecotone.LocationTropical islands.MethodsAn extensive literature review of the elevation at which island TMCFs start was undertaken. This elevation was modelled as a function of the altitude of the lifting condensation level (LCL) imposed by regional climate, island maximum elevation and upwind forest loss over the past 15 years.ResultsThe elevation of the lower TMCF boundary was found to have been reported for 93 islands worldwide. TMCFs starts from as low as 300 m on the small islands of Kosrae (Micronesia; maximum elevation = 628 m) and Aneityum (Vanuatu; 852 m) to a maximum of 1,600 m on the large islands of Cuba (1,974 m) and Hispaniola (3,175 m), providing a spectacular example of the ‘Massenerhebung effect’. Both regional climate (LCL altitude) and island features (maximum elevation) influenced the elevation of the lower TMCF boundary, and these variables together accounted for 79% of the variance.Main conclusionsOn islands, climate change is likely to cause significant but small upslope shifts of the LCL and subsequently of TMCF lower boundary elevation in the future (+4.4 m for each 1°C increase in temperature). TMCF clearing and biological invasions might appear to be more pressing threats.