Received: 26 May 2021 | Revised: 30 November 2021 | Accepted: 14 January 2022 DOI: 10.1002/ece3.8590 RESEARCH ARTICLE Think globally, measure locally: The MIREN standardized protocol for monitoring plant species distributions along elevation gradients Sylvia Haider1,2 | Jonas J. Lembrechts3 | Keith McDougall4 | Aníbal Pauchard5,6 | Jake M. Alexander7 | Agustina Barros8 | Lohengrin A. Cavieres9,6 | Irfan Rashid10 | Lisa J. Rew11 | Alla Aleksanyan12,13 | José R. Arévalo14 | Valeria Aschero8 | 7 15 3 16 Chelsea Chisholm | V. Ralph Clark | Jan Clavel | Curtis Daehler | Pervaiz A. Dar17 | Hansjörg Dietz7 | Romina D. Dimarco18,19 | Peter Edwards7 | Franz Essl20 | Eduardo Fuentes-­Lillo5,6,3,21 | Antoine Guisan22 | Onalenna Gwate15 | Anna L. Hargreaves23 | Gabi Jakobs7 | Alejandra Jiménez5,6 | Paul Kardol24 | 7,25 11 26 Christoph Kueffer | Christian Larson | Jonathan Lenoir | Bernd Lenzner20 | Miguel A. Padrón Mederos14 | Maritza Mihoc9,6 | Ann Milbau27 | John W. Morgan28 | Jana Müllerová29 | Bridgett J. Naylor30 | Ivan Nijs3 | Martin A. Nuñez19,31 | Rüdiger Otto14 | Niels Preuk1 | Amanda Ratier Backes1,2 | Zafar A. Reshi10 | Sabine B. Rumpf32,33 | Verónica Sandoya34,35,36 | Mellesa Schroder37 | Karina L. Speziale38 | Davnah Urbach39 | Graciela Valencia9,6 | Vigdis Vandvik40 | 41 20,42 7,43 44 Michaela Vitková | Tom Vorstenbosch | Tom W. N. Walker | Neville Walsh | Genevieve Wright45 | Shengwei Zong46 | Tim Seipel11 1 Institute of Biology/Geobotany and Botanical Garden, Martin Luther University Halle-­Wittenberg, Halle, Germany 2 German Centre for Integrative Biodiversity Research (iDiv) Halle-­Jena-­Leipzig, Leipzig, Germany 3 Research group Plants and Ecosystems (PLECO), University of Antwerp, Wilrijk, Belgium 4 Department of Planning, Industry and Environment, Queanbeyan, New South Wales, Australia 5 Laboratorio de Invasiones Biologicas (LIB), Facultad de Ciencias Forestales, Universidad de Concepción, Concepción, Chile 6 Institute of Ecology and Biodiversity (IEB), Santiago, Chile 7 Institute of Integrative Biology, ETH Zürich, Zürich, Switzerland 8 Instituto Argentino de Nivología y Glaciología y Ciencias Ambientales (IANIGLA), Centro Científico Tecnológico (CCT), CONICET Mendoza, Mendoza, Argentina 9 Departamento de Botánica, Facultad de Ciencias Naturales y Oceanográficas, Universidad de Concepción, Concepción, Chile 10 Department of Botany, University of Kashmir, Srinagar, India 11 Department of Land Resource and Environmental Sciences, Montana State University, Bozeman, Montana, USA 12 Department of Geobotany and Plant Ecophysiology, Institute of Botany aft. A.L. Takhtajyan NAS RA, Yerevan, Armenia 13 Chair of Biology and Biotechnologies, Armenian National Agrarian University, Yerevan, Armenia 14 Department of Botany, Ecology and Plant Physiology, University of La Laguna, La Laguna, Spain 15 Afromontane Research Unit & Department of Geography, University of the Free State: Qwaqwa Campus, Phuthaditjhaba, South Africa Sylvia Haider and Jonas J. Lembrechts contributed equally to this manuscript and wish to be considered joint first authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. Ecology and Evolution. 2022;12:e8590.  www.ecolevol.org | 1 of 16 https://doi.org/10.1002/ece3.8590 2 of 16 | HAIDER et al. 16 School of Life Sciences, University of Hawai'i at Manoa, Honolulu, Hawaii, USA 17 Department of Botany, Amar Singh College, Srinagar, India 18 Grupo de Ecología de Poblaciones de Insectos, IFAB (INTA-­CONICET), Bariloche, Argentina 19 Department of Biology and Biochemistry, University of Houston, Houston, Texas, USA 20 Bioinvasions, Global Change, Macroecology Group, Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria 21 School of Education and Social Sciences, Adventist University of Chile, Chillán, Chile 22 Institute of Earth Surface Dynamics & Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland 23 Department of Biology, McGill University, Montreal, Quebec, Canada 24 Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, Sweden 25 Department of Botany and Zoology, Centre for Invasion Biology, Stellenbosch University, Matieland, South Africa 26 UR “Ecologie et Dynamique des Systèmes Anthropisés” (EDYSAN, UMR 7058 CNRS), Université de Picardie Jules Verne, Amiens, France 27 Research Institute for Nature and Forest –­ INBO, Brussels, Belgium 28 Department of Ecology, Environment and Evolution, La Trobe University, Bundoora, Victoria, Australia 29 Department of GIS and Remote Sensing, Institute of Botany of the Czech Academy of Sciences, Průhonice, Czech Republic 30 US Forest Service, PNW Research Station, La Grande, Oregon, USA 31 Grupo Ecología de Invasiones, Instituto de Investigaciones en Biodiversidad y Medio Ambiente, CONICET -­ Universidad Nacional del Comahue, Bariloche, Argentina 32 Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland 33 Department of Environmental Sciences, University of Basel, Basel, Switzerland 34 School of Life Sciences and Biotechnology, Yachay Tech University, Urcuquí, Ecuador 35 CREAF, Cerdanyola del Vallès, Spain 36 Unitat d'Ecologia, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain 37 Department of Planning, Industry and Environment, Jindabyne, New South Wales, Australia 38 Laboratorio Ecotono, INIBIOMA (CONICET-­UNCOMA), Bariloche, Argentina 39 Global Mountain Biodiversity Assessment, Institute of Plant Sciences, University of Bern, Bern, Switzerland 40 Department of Biological Sciences, University of Bergen, Bergen, Norway 41 Department of Invasion Ecology, Institute of Botany of the Czech Academy of Sciences, Průhonice, Czech Republic 42 Institute of Biology Leiden, Leiden University, Leiden, The Netherlands 43 Institute of Biology, University of Neuchâtel, Neuchâtel, Switzerland 44 Royal Botanic Gardens Victoria, Melbourne, Victoria, Australia 45 Department of Planning, Industry and Environment, NSW Government, Biodiversity and Conservation, Queanbeyan, New South Wales, Australia 46 Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, School of Geographical Sciences, Northeast Normal University, Changchun, China Correspondence Sylvia Haider, Martin Luther University Abstract Halle-­Wittenberg, Institute of Biology/ Climate change and other global change drivers threaten plant diversity in mountains Geobotany and Botanical Garden, Am Kirchtor 1, 06108 Halle, Germany. worldwide. A widely documented response to such environmental modifications is for Email: sylvia.haider@botanik.uni-halle.de plant species to change their elevational ranges. Range shifts are often idiosyncratic Funding information and difficult to generalize, partly due to variation in sampling methods. There is thus Horizon 2020 Framework Programme, a need for a standardized monitoring strategy that can be applied across mountain Grant/Award Number: 678841; ANID PIA/ BASAL, Grant/Award Number: FB210006; regions to assess distribution changes and community turnover of native and non-­ Instituto de Ecología y Biodiversidad native plant species over space and time. Here, we present a conceptually intuitive (IEB); BiodivClim Call 2019, Grant/ Award Number: TACR SS70010001; and standardized protocol developed by the Mountain Invasion Research Network Deutsche Forschungsgemeinschaft, (MIREN) to systematically quantify global patterns of native and non-­native species Grant/Award Number: DFG–­ FZT 118 and 202548816; Fondo Nacional de distributions along elevation gradients and shifts arising from interactive effects of Desarrollo Científico y Tecnológico, climate change and human disturbance. Usually repeated every five years, surveys Grant/Award Number: 1171005 and 1180205; Swedish Research Council consist of 20 sample sites located at equal elevation increments along three replicate (Vetenskåpsrådet), Grant/Award Number: roads per sampling region. At each site, three plots extend from the side of a mountain 2015-­0 4214; Fonds Wetenschappelijk Onderzoek, Grant/Award Number: road into surrounding natural vegetation. The protocol has been successfully used in 12P1819N and G018919N; Austrian HAIDER et al. | 3 of 16 Science Foundation FWF, Grant/Award Number: I 3757-­B29; Akademie Věd 18 regions worldwide from 2007 to present. Analyses of one point in time already České Republiky, Grant/Award Number: generated some salient results, and revealed region-­specific elevational patterns of RVO 67985939; Fondation Herbette; Laboratorio de Ecología, Biogeografía y native plant species richness, but a globally consistent elevational decline in non-­ Sistemática (ECOBIOSIS) de la Universidad native species richness. Non-­native plants were also more abundant directly adjacent de Concepción; Comisión Nacional de Investigación Científica y Tecnológica, to road edges, suggesting that disturbed roadsides serve as a vector for invasions into Grant/Award Number: PFB-­023 and mountains. From the upcoming analyses of time series, even more exciting results PIA CCTE AFB170008; INTERACT Transnational Access; Universiteit van can be expected, especially about range shifts. Implementing the protocol in more die Vrystaat; Laboratorio de Invasiones mountain regions globally would help to generate a more complete picture of how Biológicas (LIB) de la Universidad de Concepción; U.S. Forest Service; global change alters species distributions. This would inform conservation policy in Missouri Botanical Garden; CONICET: PIP mountain ecosystems, where some conservation policies remain poorly implemented. 0758/2014; ANPCYT: PICT 1623/2018; Universidad Nacional de Cuyo, Grant/ Award Number: SIIP 2019 UNCUYO; KEYWORDS Secretaría de Educación Superior, climate change, invasive species, long-­term ecological monitoring, MIREN, mountain Ciencia, Tecnología e Innovación; Rufford biodiversity, Mountain Invasion Research Network, range dynamics, range expansions Foundation TA X O N O M Y C L A S S I F I C AT I O N Biodiversity ecology; Biogeography; Botany; Community ecology; Global change ecology; Invasion ecology 1 | I NTRO D U C TI O N of natural resources and ever-­increasing demands for agricultural land (e.g., Gillet et al., 2016; Ross et al., 2017). The abandonment of Mountains are biodiversity hotspots and provide a wealth of eco- traditional cutting and grazing practices has also occurred in some system functions and benefits to people (Körner & Spehn, 2002; mountain regions (e.g., MacDonald et al., 2000). Both land use inten- Martín-­López et al., 2019; Mengist et al., 2020). At the same time, sification and abandonment can alter plant species distributions and mountain ecosystems are particularly susceptible to global change. diversity alone (Alexander et al., 2016; Pellissier et al., 2013) and by For instance, temperatures are increasing faster at high eleva- interacting with climate change (Elsen et al., 2020; Guo et al., 2018). tion than at low elevation (Nogués-­Bravo et al., 2007; Pepin et al., Further, previously remote areas are becoming increasingly ac- 2015). In the alpine zone of the European Alps, temperatures have cessible due to construction of new roads and trails, which not only increased approximately twice as much as the northern hemisphere cause a direct disturbance but also act as corridors for plant species average over the past 100 years (Gobiet et al., 2014). Importantly, movements (Ansong & Pickering, 2013; Lembrechts et al., 2017; Rew amplified warming has enabled many plant species to move to higher et al., 2018). The role of roads as dispersal corridors is amplified due elevation (Lenoir et al., 2008; Pauli et al., 2012; Steinbauer et al., to increased vehicle traffic, often as a result of recreation and tour- 2018). For instance, between 1971 and 1993, native plant species ism (e.g., Müllerová et al., 2011). Roadside habitats also provide ideal from the forest understorey in the French mountains shifted their spaces for non-­native plants, which generally benefit from reduced elevational range uphill at an average rate of 38 m per decade (Lenoir competition, increased soil nutrients, more favorable microclimatic et al., 2008). Another prominent example is the observed upward and hydrological conditions, and intermediate disturbance (Averett shift of most vascular taxa at Chimborazo in Ecuador since Alexander et al., 2016; Müllerová et al., 2011). Thus, both native and non-­native von Humboldt's visit more than two centuries ago (Morueta-­Holme plant species are known to disperse along mountain roads, from low et al., 2015). An expected consequence of such uphill migrations of to high elevation and vice versa (Dainese et al., 2017; Guo et al., more competitive lowland species is that less competitive alpine spe- 2018; Lembrechts et al., 2017). Indeed, many high elevation areas cies might locally become extinct on mountain summits (Alexander once free of lowland and non-­native species but connected to low- et al., 2018; Dullinger et al., 2012; Guisan et al., 2019; Rumpf et al., lands by road networks are now harboring lowland and non-­native 2019). Such local extinctions were recently documented for birds plant species. Examples for this are the volcanoes of the Hawaiian (e.g., Freeman et al., 2018). archipelago (Jakobs et al., 2010), the high Andes (Barros et al., 2020) In addition to temperature increase, human activities in moun- and the Teide National Park on Tenerife (Dickson et al., 1987). tain areas have changed markedly over the last decades (e.g., Peters Roadside habitats are also conduits for non-­native plants to spread et al., 2019; Wang et al., 2019; for an overview see Payne et al., into natural vegetation once established along roadsides (Alexander 2020). Mountain land use has intensified in many places across the et al., 2011; Seipel et al., 2012). globe (Spehn et al., 2006), driven by booming tourism industries The elevational redistribution of plant species, especially non-­ (Debarbieux et al., 2014; Pickering & Barros, 2012), overexploitation native species (Dainese et al., 2017), has already significantly 4 of 16 | HAIDER et al. impacted mountain ecosystems (Guo et al., 2018) and will con- on mountain plant biodiversity and the distribution of species. The tinue to do so in the future (Petitpierre et al., 2016). For exam- protocol provides a conceptually intuitive yet comprehensive and ple, non-­native plants can cause biotic homogenization (Haider standardized way to record and monitor native and non-­native spe- et al., 2018), reduce the diversity of local native species (Daehler, cies along elevation gradients. The survey has been running in some 2005), and affect important ecosystem functions and services mountain regions of the world since 2007 (Alexander et al., 2011; (McDougall, Khuroo, et al., 2011; Pecl et al., 2017). In the moun- Seipel et al., 2012) and continues to be implemented in new regions. tains of Iceland, non-­native Lupinus nootkatensis competes strongly In this paper, we summarize the most important findings gained over with native plant species and modifies soil properties through ni- the time by using this protocol, discuss its strengths and limitations, trogen fixation (Wasowicz, 2016). In the alpine zone of the central and outline opportunities and challenges for future work. To achieve Chilean Andes, non-­native Taraxacum officinale shares pollinators broad reach and long-­term maintenance of sites, monitoring proto- with several native Asteraceae species (Muñoz & Cavieres, 2019), cols must be simple, efficient, and inexpensive. Our intention is to reducing pollinator-­v isitation rates and seed-­s et where T. officinale promote the use of the MIREN road survey protocol to monitor bio- is at high abundances (Muñoz & Cavieres, 2008). Finally, uphill diversity change in mountains, and to generate global, regional, and migration of non-­native trees and shrubs can increase fire risk at local insights into how plant species and communities are respond- high elevation (Cóbar-­C arranza et al., 2014), and transform plant ing to rapid global change in mountains. communities through competition (Nuñez et al., 2017; Zong et al., 2016). While human-­driven vegetation change can happen relatively 2 | M ATE R I A L S A N D M E TH O DS quickly in mountains, it often only becomes apparent at temporal scales beyond the few years covered by most ecological experi- 2.1 | The mountain invasion research network ments (Mirtl et al., 2018). Thus, data from long-­term time series in mountains are essential to identify and follow changes in plant com- The Mountain Invasion Research Network (MIREN, www.mount​ munities (Pauli et al., 2012). There are currently two main types of ainin​vasio​ns.org) was founded in 2005 as a first global effort to apply initiatives which monitor high-­elevation vegetation change. At the the known principles from plant invasion ecology in mountainous local or regional scale, some well-­established long-­term monitor- environments (Kueffer et al., 2008, 2009). From the start, the main ing sites follow a holistic approach and document not only floris- goal has been to link detailed observations at the local-­scale from a tic changes but also modifications for example of soil, hydrology, or broad range of mountain regions, to come to global conclusions on atmospheric conditions. Examples are Niwot Ridge in the Colorado common patterns (and divergence from them) regarding mountain Rocky Mountains (www.nwt.ltern​et.edu) or the Sierra Nevada plant biodiversity (Kueffer et al., 2014). The core of the network has Global Change Observatory in Spain (https://obsnev.es/en/). At the been the underlying road survey protocol, which allowed flexible global scale, the Global Observation Research Initiative in Alpine application all across the world, yet a standardized baseline of data Environments (GLORIA, www.gloria.ac.at; Pauli et al., 2015) is a net- collection that could be maintained for a long time. While research work monitoring floristic change on mountain summits with a stan- topics and techniques have diverged throughout the years, the core dardized approach. What would complement these highly valuable business of MIREN remains to increase the spatial and temporal ex- approaches, is a global long-­term monitoring network that covers tent of the road survey. the full vertical extents of different mountain regions and that al- lows the detection of species responses to both climate and other human activities. 2.2 | Survey design Here, we present a standardized protocol for monitoring changes in the elevational distribution, abundance, and composi- The MIREN road survey is conducted by region. In each region, the tion of plant biodiversity in mountains as a result of the interaction participants select three sample roads that extend over a broad between climate and human pressures. Importantly, the protocol elevation gradient, ideally reaching elevations beyond the treeline focuses on large elevation gradients (>1700 m on average; ranging (for examples, see Figure 1). We define a region as an area in the from c. 700 m to >4000 m), allowing vegetation change to be mon- same biogeographical unit containing similar flora, geology, and el- itored across a broad range of climates and plant community types. evational ranges, usually with distances between roads of less than It explicitly contrasts anthropogenically disturbed and (semi-­)natural 150 km (Figure 2). Selected roads should begin at the bottom of vegetation within sampling sites, thus increasing detection of rapid the mountain region, in a valley, at sea level, or where no further community changes and providing greater insight into the drivers of elevation change occurs, and reach the highest elevation typical change. The protocol has been developed by the Mountain Invasion for roads in the region. Roads can be gravel or paved but should Research Network (MIREN, www.mount​ainin​vasio​ns.org) (Kueffer be open for public vehicle traffic for at least some part of the year. et al., 2014), a network initially founded in 2005 to study patterns and Once roads have been selected, the elevational range of each road processes of non-­native plant invasions in mountains and recently is divided into 19 equally wide elevational bands from the lowest to expanded to more widely understand the effects of global change highest possible sampling location, giving a total of 20 sample sites HAIDER et al. | 5 of 16 (a) (b) (c) (d) (e) (f) F I G U R E 1 Examples of roads in the landscape (a–­c) and key non-­native species (d–­f ) across a range of MIREN regions. (a) Harsh mountain climates (here the Cañadas del Teide on Tenerife (Canary Islands, Spain) have traditionally been seen as an adequate barrier against non-­ native plant invasion; (b) the direct local impact of roadside disturbance on mountain plants is visible on native Azorella cushion plants along a road in the dry Andes near Mendoza, Argentina; (c) interactive effects of climate and land use, exemplified by dramatic differences in snow cover on versus beside a mountain road in northern Norway; (d) Taraxacum officinale, one of the most widespread non-­native plant species along MIREN mountain roads (Seipel et al., 2012), in a sample plot on a volcanic gravel slope in the Argentine Andes; (e) non-­native Verbascum thapsus on a roadside in the highly invaded lowlands of the Andes in central Chile; (f) Trifolium pratense in northern Norway, where the species is rapidly moving uphill along mountain roadsides per road located at the splits between elevational bands. Sample 2.3 | Plant species surveys sites are determined prior to going into the field and located as precisely as possible using a global positioning system (GPS). At Within each of the three plots at all 20 sample sites along the three each sample site, three 2 m × 50 m plots are laid out in the form of roads, observers record all vascular plant species (including both na- a “T”: one plot (the top of the “T”) is parallel to the road. The other tive and non-­native species) and visually estimate vegetation cover two plots extend end-­to-­end and perpendicular to the road, start- (eight percentage cover classes with 1 = <0.1%, 2 = 0.1–­1%, 3 = 2–­ ing from the center of the first plot, with midpoints at 25 and 75 m 5%, 4 = 6–­10%, 5 = 11–­25%, 6 = 26–­50%, 7 = 51–­75%, 8 = 76–­ from the roadside plot (Figure 3). The same plots are resurveyed 100%) and record abundance (number of individuals in three classes; every five years. If the plot locations have to be changed due to 1 = 1–­10 individuals (or ramets), 2 = 11–­100 individuals, 3 = >100 unforeseen circumstances, new sites are placed as near as possible individuals) of each species. The detailed sampling protocol is pro- and again geolocated. vided in Supporting Information S1 and can also be downloaded For each plot, a few basic environmental variables have to be from the MIREN website (www.mount​ainin​vasio​ns.org). Taxa should collected in the field (e.g., tree cover; see Supporting Information be identified to species level using up-­to-­date local floras. Before S1). However, we aim to keep the protocol as simple as possible, and being included in the global database, submitted regional species therefore additional variables of interest can be either extracted lists undergo taxonomic harmonization to detect synonyms for from online resources (e.g., soil characteristics, Hengl et al., 2017) the same species in different regions, and to correct spelling prob- or topographic variables (Amatulli et al., 2018) or through optional lems. This procedure is done by the MIREN data managers, using add-­on studies (see section below). the R-­packages “taxize” (Chamberlain & Szöcs, 2013; Chamberlain 6 of 16 | HAIDER et al. F I G U R E 2 Overview of the workflow from region selection and data collection to inclusion of the data in the global MIREN database et al., 2020) and “WorldFlora” (Kindt, 2020). First, species names be relocated with a metal detector or colored sticks or plastic seal are matched with World Flora Online (http://www.world​flora​online. security tags in remote areas where their removal is unlikely. In ad- org), and if not found there, they are searched via the additional da- dition, precise sub-­meter GPS coordinates should be taken at least tabases included in the Taxonomic Names Resolution Service (Boyle once. Photographs should also be taken of each transect to visualize et al., 2013). All changes of species names are transmitted to the changes over time, document data collection, and facilitate reloca- submitting region for verification or correction, before the dataset tion of plots. Surveys and resurveys should always be done at peak enters the global database (Figure 2). biomass or flowering to minimize the risk of missing species with Each taxon should be classified as native or non-­native to that re- early or late phenology. For repeated surveys, this means that timing gion by the participant using local floras and databases. As a general should be kept constant relative to the onset of spring, rather than rule, plant species introduced into the country or mountain range to a fixed date, while sampling within season is recommended from after AD 1500 are considered as non-­native, although regional de- valley bottom to top. viations are welcome if properly justified. For noteworthy records (e.g., first records or new high/low elevation records of native or non-­native species), specimens should be collected outside of the 2.5 | Add-­ons to the standardized protocol plots (when possible) and placed in a herbarium to facilitate identifi- cation and to inform local floras (Walsh & McDougall, 2018). In addition to long-­term monitoring of plant communities, the MIREN survey design is well suited for additional projects (“add-­on” projects) that test more detailed or region-­specific questions about the drivers 2.4 | Repeated monitoring of plant species redistributions. For example, soil temperatures have been recorded with a high temporal resolution for a year or longer To understand long-­term dynamics of redistributions of native in several MIREN regions to document how disturbance along road- and non-­native plant species, all regions should strive for regular sides affects microclimate, including consequences for species redis- long-­term monitoring, preferably with a periodicity of five years tributions (for the first regional results, see Lembrechts et al., 2019). (and ideally with at least partial overlap in observers, to reduce ob- Plant functional traits have additionally been collected for species in server bias). To facilitate monitoring, all plots should be permanently Tenerife, Canary Islands, to assess contrasting patterns of intraspe- marked in the field, for instance with magnets or metal tags that can cific trait variability of native and non-­native species and the change of HAIDER et al. | 7 of 16 scaled ecological questions. To be included in MIREN’s global road survey database, regional data must be submitted to the MIREN data managers using a standard data format. An overview of how the da- tabase is structured and which metadata are stored is provided in Supporting Information S2. While in the first survey in 2007, only non-­native species were monitored, we now only accept data sub- missions from new regions that surveyed all vascular plant species, both native and non-­native, as partial species pools drastically limit the amount of research questions that can be answered with the data. All data will be made public in a data repository in the context of paper publications, or at the very latest five years after the survey is undertaken (Figure 2). To date, all survey data collected before 2016 are available through Zenodo (https://doi.org/10.5281/ze- nodo.5529072). Any researcher can also request the full MIREN da- tabase from MIREN data managers for global analyses. The structure of the database, with its plot-­level table with accurate coordinates, and easy linkable species information, allows smooth integration into larger global integrative projects (e.g., data is currently inte- grated into the SoilTemp-­database; Lembrechts et al., 2020). Details regarding data accessibility and publication, the submission of paper proposals, and guidelines for co-­authorship are given in MIREN’s data-­sharing agreement (see Supporting Information S3), which can also be downloaded from the MIREN website (www.mount​ainin​ vasio​ns.org). F I G U R E 3 Layout of the MIREN survey design. (a) Equal elevational distribution of 20 sample sites along a mountain road, of which three are selected in each region; (b) Each sample site consists of 3 plots of 2 m × 50 m, plot 1—­parallel to the roadside (starting at 3 | R E S U LT S the first occurrence of roadside vegetation), plot 2—­centered 25 m from the roadside plot, plot 3—­centered 75 m from the roadside The standardized protocol for recording plant species communities plot; (c) exemplary photograph of monitoring a mountain roadside in along mountain roads has been thoroughly tested in the field on all Tenerife, Canary Islands, Spain, depicting a survey of plot 1 continents except Antarctica (Figure 4). The first survey was car- ried out in eight regions in 2007 and has been repeated every five community mean traits and functional diversity with elevation (Kühn years since, resulting in one baseline historical survey (2007) and up et al., 2021). Another add-­on project has focused on soil chemical to two resurveys (2012 and 2017). The number of regions has in- properties and mycorrhization of native and non-­native species in the creased since 2007, with 18 regions performing the survey by 2018 mountains of Norway (Clavel et al., 2021), and survey plots have also (Figure 4). The global database currently includes circa 2700 plots been used to assess the distribution of plant pathogens (Phytophthora and >100,000 observations of >5,000 vascular plant species. species) in Australia (Khaliq, 2019). Once the participants begin con- One of the most striking findings of the global MIREN surveys tributing data to the MIREN global road survey database, they can to date has been to document the importance of roads in facilitating suggest add-­on studies to apply across all regions that go beyond the mountain invasions. Specifically, we found that non-­native species existing scope of the survey protocol—­as long as it is based on a stand- richness in roadsides decreases with increasing elevation, but gen- ardized protocol that can be implemented fast, simply, and at low cost erally peaks in the lower third of the elevation gradient (Alexander by collaborators. To maximize participation and to discuss new pro- et al., 2011). In a review including among others the MIREN road posals, data quality, and complementarity, ideas for add-­on projects survey data, we found that only 2.1% of the non-­native species should be developed together with the MIREN steering committee. found in alpine areas can be considered as true alpine or mountain plants based on their temperature affinity (Alexander et al., 2016). Moreover, the vast majority of non-­native species found at high 2.6 | Data submission and accessibility elevation along the MIREN roads are also present at low elevation (Alexander et al., 2011). These findings indicate that non-­native The MIREN survey design is a robust and standardized field survey species are first introduced and become established at low eleva- protocol that provides data contributors among others an oppor- tion sites, from where they spread to higher elevations (Alexander tunity to include regional data in research that addresses globally et al., 2011). At higher elevation sites, non-­native species generally 8 of 16 | HAIDER et al. F I G U R E 4 Regions worldwide participating in the vegetation survey along mountain roads according to the standardized protocol of the Mountain Invasion Research Network (MIREN). Red symbols indicate the founding regions from the first survey in 2007. In regions with unfilled symbols, only roadside plots, but not intermediate and interior plots in natural vegetation were sampled. For each region, the name of the mountain range, the sampled elevation gradient and the year(s) of sampling are given. Years in bold indicate that both native and non-­native species were recorded, while in years with normal font only non-­native species were recorded. Note that some regions did not follow the 5-­year sampling frequency. In the last row, the total number of species and in parentheses the proportion of non-­native species are summarized become increasingly filtered out by environmental pressures, so few 2018). Further, we have observed a reduction in community dissim- warm-­adapted perennials and mainly generalist species reach higher ilarity (beta-­diversity) along roadsides relative to more distant plots, elevations (McDougall et al., 2018). Recently introduced species may which is amplified by the arrival of non-­native species along moun- also not have reached their elevational maximum. However, a study tain roadsides homogenizing plant community composition (Haider from Switzerland demonstrated that non-­native species did not rap- et al., 2018). The MIREN surveys have also provided insight into the idly expand at their high elevation range limits over a period of six vulnerability of habitats regionally (Pollnac et al., 2012), the genetic years (Seipel et al., 2016). We have also revealed that the number of background of successful invasions (Haider et al., 2012) and the non-­native species declines with increasing distance from the road impact and management of local invasions (McDougall, Alexander, (Haider et al., 2018; Seipel et al., 2012), indicating that the native et al., 2011). For example, in the Greater Yellowstone Ecosystem plant community serves as a second environmental filter that selects in the United States, we found that non-­native species emergence for more shade-­ and moisture-­tolerant perennials (McDougall et al., varies with elevation and habitat type, which provided land man- 2018). In addition to non-­native species, the MIREN surveys have agers valuable information for mitigating biological invasions shown that native species also use roads as corridors (Lembrechts (Pollnac et al., 2012). Moreover, in the dry Mediterranean Andes in et al., 2017). Interestingly, Lembrechts et al. (2017) found that oc- Argentina, which are characterized by treeless vegetation, the sur- currence optima are located higher in roadside habitats than faraway vey demonstrated how non-­native plant species can successfully habitats, and moreover that some alpine species have shifted their spread from the roadside into natural vegetation at low and interme- ranges downward due to altered abiotic conditions and competitive diate elevations, thus highlighting the susceptibility of these types release in roadside habitats (see also e.g. Lenoir et al., 2010). of ecosystems to invasion (Aschero et al., 2017). By contrast, the Globally, the MIREN surveys have demonstrated that native alpine vegetation of northern Norway has been shown to be more plant species richness does not follow a consistent pattern in non-­ vulnerable to invasion than its low elevation counterpart, indicating roadside (semi-­) natural habitat along elevation gradients, suggest- that vegetation structure plays an important role in community in- ing the existence of additional region-­specific mechanisms, driven vasibility (Lembrechts et al., 2014). Finally, the MIREN surveys have by differences in biome, vegetation type, and human activity. These already generated information about regional floras. An excellent mechanisms are now the subject of further study. In contrast, a example is the discovery of a new species of Poaceae during MIREN clearer elevation signal is present on roadside plots, with total spe- monitoring in Kosciuszko National Park, Australia—­this species was cies richness peaking at mid-­elevations in most regions (Haider et al., named after the network: Poa mireniana (Walsh & McDougall, 2018). HAIDER et al. | 9 of 16 4 | DISCUSSION 4.2 | Limitations of the protocol 4.1 | Strengths of the protocol The focus of the protocol on mountain roads provides excellent op- portunities to disentangle the effects of climate and road construc- The MIREN road survey protocol is unique for its focus on two tion on plant species and community redistributions. However, the critical co-­occurring global change drivers of biodiversity and protocol also has four important limitations, which we encourage species redistributions in mountains: climate change and road users to keep in mind when applying the protocol to their study sys- construction (Figure 5). Road construction represents one of the tem (Figure 5). most prominent and increasing land-­use changes in many remote First, the protocol excludes the most pristine environments regions (Meijer et al., 2018), leading to physical disturbance, dis- that exist far from roads and at elevations above where roads persal corridors, and vectors for plant species (Gelbard & Belnap, reach, so does not monitor mountain biodiversity as a whole. As 2003). Coupled with this, elevation gradients are good proxies for such, the protocol is a complement to the GLORIA protocol, which temperature and can be used as space-­for-­time model systems for focuses on long-­term climate change-­related vegetation shifts on simulating climate change-­induced temperature increase, where undisturbed mountain summits (Pauli et al., 2015). Nevertheless, low elevation systems to a certain extent represent future sce- one regional study has shown that, at least in northern Scandinavia, narios for higher elevations in a warming climate (Blois et al., 2013; the effect of roads on mountain plant diversity could disappear Lembrechts et al., 2017). Given this, combining elevation-­based beyond 25 m from the roadside (Lembrechts et al., 2014), and the climate gradients with road effects allows researchers to disen- direct impacts of road disturbance (e.g., construction, mainte- tangle the interactive effects of climate and road construction—­as nance, and vehicle use) are often firmly restricted to the road itself an example of human land-­use change—­on biodiversity, includ- and its shoulders. This suggests that the vegetation monitored in ing their relative importance as drivers of species redistributions. the MIREN survey plot furthest from the roadside (Figure 3b; 50–­ Indeed, it is along clear linear dispersal pathways like roads that 100 m distance) may indeed at least be free of direct road effects. changes in species distributions—­and especially those of non-­ Yet, using these data beyond the 100 m reach of the sample site native species—­b ecome apparent (Lembrechts et al., 2017). This could bring issues for some applications, such as spatial modeling, is particularly relevant when considering the repeated survey ap- where extrapolations for locations away from the road will suf- proach of the MIREN design, which makes it possible to study the fer from increased uncertainty (Kadmon et al., 2004). Coupled to temporal dynamics of plant species distributions in response to this, the restriction of the protocol to mountain roads means that, natural (e.g., succession after natural disturbances, such as fire), depending on the heterogeneity of the landscape, not all habitat as well as anthropogenic disturbances (e.g., land-­use changes, such types are necessarily covered relative to their distribution in the as increasing urbanization or domestic grazing, or the introduction ecosystem. Plot locations may be biased toward valleys and less of non-­native species), allowing to assess how such disturbances steep terrain if road construction favors such areas. Additionally, affect the space-­for-­time proxy as would exist along gradients of while roads represent the most prominent dispersal pathway pres- climatic harshness only. ent in mountains, they are not the only one (e.g., rivers, moun- A final advantage is that along each road, sites are selected at tain trails, powerline cuttings, cable cars; Foxcroft et al., 2019). predetermined elevations and capture all habitats found along an However, the protocol could be easily adapted for other pathways elevation gradient, equally covering all elevational belts. The pro- (as done for trails (Liedtke et al., 2020), railroads (Rashid et al., tocol provides a methodological standardization that is straightfor- 2021), and rivers (Vorstenbosch et al., 2020)), and we suggest that ward to replicate globally and yet still yields sufficient explanatory this would be of particular interest in regions with sparse roads power for regional case studies due to its relationship to the el- and/or where most of the common non-­native species are wind or evation gradient and its within-­region replication (i.e., sampling water dispersed. along three mountain roads in each region; e.g., Arévalo et al., Second, MIREN adopts a discrete temporal and spatial sampling 2010; Pollnac et al., 2012; Ratier Backes et al., 2021). In doing so, approach. Specifically, since the protocol focuses on community the protocol remains simple, for example with plots close to roads dynamics and large-­s cale patterns it has a coarse spatio-­temporal remaining easy to reach, and thus applicable in many mountain re- resolution, limited to monitor simple plant community composi- gions even when fieldwork sites need to be easily accessible. This tion estimates over time. The relatively low spatial sampling in- provides another strength of the protocol: it can be repeated in tensity (i.e., few plots for each elevational belt) and sometimes many places, so that general patterns at the global scale can be large distances between elevational increments (on average c. detected through multi-­region replication (Alexander et al., 2011; 75 m steps across current MIREN regions, but up to c. 160 m in Lembrechts et al., 2017; Seipel et al., 2012). In summary, data col- the Indian Himalayas) can limit understanding of local processes, lected within the MIREN survey framework can be useful for re- while also biasing sampling against rarer plant species or habitats. gional and global studies in a large variety of fields, ranging from Furthermore, while repeated surveys facilitate investigation of classical biogeography and community ecology to ecological mod- species range dynamics under global change, the complete design eling and global change research. does not explicitly consider dispersal dynamics (e.g., through seed 10 of 16 | HAIDER et al. 4.3 | External limitations Application of the MIREN road survey protocol might be hindered in some regions, most obviously due to the lack of roads spanning suf- ficiently large elevation or climatic gradients. Additionally, local land ownership, safety issues, or administrative complexities may com- plicate establishment and monitoring, for example, on private land or in protected areas (Figure 5). Such issues might be of particular relevance in the MIREN survey design, as MIREN strives to cover a large elevation gradient spanning multiple vegetation zones. At the same time, the proximity of survey plots to roads increases the risk of damage over time (e.g., through road widening, mowing, pesticide use, expanding urbanization, or occasional vandalism). The simplicity of the plot set-­up nevertheless greatly reduces the impact of such damage or vandalism in the long term. Long-­term monitoring itself comes at a risk of funding insecu- rities, as the timeframe of 5-­year intervals is beyond what is cov- ered by most grants. Even though maintaining the observational sites themselves comes at virtually no financial cost, the monitoring F I G U R E 5 Summary of the strengths and opportunities of the involves considerable input of field labor, for which costs will vary MIREN road survey protocol as well as limitations of the protocol between regions (Figure 5). itself and those resulting from external circumstances 4.4 | Opportunities rain or seed bank sampling, or seed tracking), instead assessing such dynamics indirectly through repeated snapshots of plant Many drivers of global change act rapidly and interactively, and in- community composition. Additionally, with only one observa- tensify over time, so assessing their impact on global biodiversity tional moment in a year, the phenological window of observation urgently requires comparable data collected on a truly global scale. is small, with the risk of (1) excluding species flowering early or late The MIREN road survey protocol has already demonstrated its po- in the season (Schultz et al., 2014), and (2) confounding phenolog- tential to explain crucial patterns in native and non-­native species re- ical shifts over time with distributional shifts (CaraDonna et al., distributions along mountain roads, but there are a range of further 2014). Whenever possible, we thus encourage regions to survey applications that can be explored. For example, due to its simplicity (a subset of) the plots at three time steps in the season. The latter the protocol can readily be implemented in many more mountain would also allow for assessing detection probability. ranges and regions. Increasing the number of participating regions, Third, the standard protocol emphasizes simplicity to be as in- all with their unique combination of climatic conditions and anthro- clusive as possible and to keep resource use to a minimum. The ap- pogenic pressures, would further increase the potential to draw gen- proach thus focuses chiefly on plant community composition and eral conclusions about the interacting effects of climate change and coarse estimates of species abundance (see Supporting Information roads as anthropogenic disturbance on mountain plant communities S1). Other important variables such as biomass, functional traits, (Guo et al., 2018). This is particularly important for regions currently community 3D-­structure, species interactions, and other abiotic and under-­represented by the existing MIREN survey sites (Figure 4), biotic variables thus require additional sampling effort. For the same such as Africa, Eastern Asia, and central America, regions for which reason, the protocol is limited to vascular plants, excluding bryo- long-­term biodiversity data are often lacking (Maestre & Eisenhauer, phytes and other taxonomic groups of potential interest. 2019). Despite these spatial gaps, MIREN has already more than Finally, the assumption that elevation can serve as a proxy doubled in size on its road to becoming a global-­scale network since for climate is of particular relevance here. Testing how the ele- it was first established in eight regions. New participants would thus vation gradient correlates with fine-­grained climatic gradients be able to place their region into a much larger spatio-­temporal pic- requires validation using high-­resolution climate data produced ture and, as time passes, get an increasingly strong grasp of how spe- either using in-­situ measurements or downscaling of climate cies distributions are changing dynamically, regionally, and across models (Lembrechts et al., 2019). We therefore recommend the the world. participants to include at least one add-­on study that deploys tem- With its potential to answer important local questions, and feed perature data loggers to allow linking of vegetation patterns with into the growing multi-­region database, we hope that the MIREN microclimatic gradients (Lembrechts et al., 2019)—­although this road survey protocol will become the protocol of choice for those would already add cost. interested in native and non-­native plant biodiversity dynamics HAIDER et al. | 11 of 16 in mountain regions. At the local scale, it can provide good base- number of questions related to species redistributions in the fields line data on biodiversity changes along elevation gradients in dis- of biogeography, ecology, and conservation biology. The protocol turbed regions, with opportunities to inform management decisions is low-­tech, straightforward, and standardized, and can therefore (McDougall, Alexander, et al., 2011). For example, it can inform be implemented immediately to fill global gaps in biodiversity data, policy makers on some of the impacts of urban expansion and new especially in areas that are traditionally underrepresented in global infrastructure projects in mountains, as well as identify new non-­ biodiversity studies (Nuñez et al., 2019) or in regions with scarce native species before they become problematic. The protocol can or fluctuating government support for scientific research. In short, also provide essential biodiversity variables for global monitor- this on-­the-­ground, multi-­region, simple yet effective monitoring ing efforts (Jetz et al., 2019), since it provides insight into species scheme is a perfect example of “Think globally, measure locally,” abundance change over space and time and can further enrich the and has clear capacity to bring together ecologists from around the mountain biodiversity data provided on the online data portal of the world to generate an even more complete picture of ongoing species Global Mountain Biodiversity Assessment (GMBA). In doing so, it redistributions in mountains. We invite you all to join us! has the capacity to inform global biodiversity policy initiatives, such as the Intergovernmental Science-­Policy Platform on Biodiversity AC K N OW L E D G M E N T S and Ecosystem Services (IPBES). We gratefully acknowledge the immense effort and time that numer- Further opportunities include add-­o ns and expansions ous professionals, field assistants, and students have contributed to to the protocol design, for example to measure microclimate the collection of these data. SH and ARB gratefully acknowledge the (Lembrechts et al., 2019), dispersal dynamics (e.g., with seed support of iDiv funded by the German Research Foundation (DFG–­ traps), soil biodiversity (e.g., analyses of the soil microbiome or FZT 118, 202548816). JJL received a postdoctoral fellowship from mycorrhizal colonization of roots), or plant-­a nimal interactions the Research Foundation Flanders (FWO, grant nr. 12P1819N). The (e.g., pollinator records, herbivore abundance). Collecting such work from JJL, JC, and IN is supported by a research grant from the data would be important not only in isolation, but also for help- FWO (grant nr. G018919N). Fieldwork in the Northern Scandes is ing to create explicit links between descriptive and predictive achieved using INTERACT Transnational Access funding. LAC and species distribution models, both at local and global scales. Such AP acknowledge support from FONDECYT 1171005, 1180205, efforts could even facilitate modeling of (changes in) the distri- CONICYT PIA CCTE AFB170008 and Grant ANID PIA/BASAL butions and habitat occupation of mountain plant species, for FB210006. JMA received funding from the European Commission instance by coupling georeferenced long-­term survey plots with Horizon 2020 research and innovation program under grant agree- high-­r esolution remotely sensed and modeled environmental ment 678841. VA was supported by the Universidad Nacional de data (Randin et al., 2020). The survey approach can similarly be Cuyo (SIIP 2019 UNCUYO). FE, BL, and TV acknowledge funding expanded by adapting it for use along other linear introduction by the Austrian Science Foundation FWF (grant I 3757-­B29). OG re- pathways for non-­n ative species, such as rivers, railroads or hik- ceived a postdoctoral research fellowship through the Afromontane ing trails (see 4.2 above), or by connecting it with other standard- Research Unit, University of the Free State. PK acknowledges sup- ized global biodiversity surveys and assessments, such as GLORIA port from the Swedish Research Council (Vetenskåpsrådet) (pro- (Pauli et al., 2015), sPlot (Bruelheide et al., 2019), the Global ject grant 2015-­0 4214) and the Swedish Research Council Formas Inventory of Floras and Traits (GIFT; Weigelt et al., 2020), the (project grant 2020-­02348). BN was supported by the US Forest Global Naturalized Alien Flora (GloNAF) database (van Kleunen Service and direct mentorship from C. Parks. VS was supported by et al., 2015), and the BioTIME database (Dornelas et al., 2018). SENESCYT-­Ecuador, Instituto de Ecología y Biodiversidad (IEB) and The connection to other datasets can be done either via the exact Laboratorio de Ecología, Biogeografía y Sistemática (ECOBIOSIS) de geographic location submitted with the MIREN plot-­level data, or la Universidad de Concepción, Laboratorio de Invasiones Biológicas via the species names which have been standardized with major (LIB) de la Universidad de Concepción, Herbario QCA and QCNE-­ taxonomic backbones, such as World Flora Online (http://www. Ecuador, Missouri Botanical Garden, and CONICYT (PFB-­023). world​f lora​o nline.org). Finally, the protocol has already shown to KLS thanks funding received from ANPCYT: PICT 1623/2018 and have great potential for teaching, for instance by training under- CONICET: PIP 0758/2014. MV was supported by a research grant graduate and graduate students in vegetation sampling, while from the BiodivClim Call 2019 (grant nr. TACR SS70010001) and also having relevance for local policy and management, for exam- together with JM by long-­term research development project RVO ple as demonstration sites (Figure 5). 67985939 from the Czech Academy of Sciences. We also thank the Fondation Herbette, University of Lausanne, for financial support to JMA for the workshop “Distributed ecological observatories and 5 | CO N C LU S I O N S long-­term monitoring of mountain biodiversity” held in September 2019 that lead up to this paper. Finally, we are grateful to the editor The MIREN road survey protocol started in 2007 with a specific pur- and two anonymous reviewers for providing helpful comments to pose—­to monitor non-­native plant species invasions along mountain improve the manuscript. Open Access funding enabled and organ- roads—­but has since then proven to be well-­suited for an increasing ized by ProjektDEAL. 12 of 16 | HAIDER et al. C O N FL I C T O F I N T E R E S T (equal); Writing –­ review & editing (equal). Martin A. Nuñez: The authors declare no conflict of interest. Methodology (equal); Writing –­ review & editing (equal). Rüdiger Otto: Methodology (equal); Writing –­ review & editing (equal). Niels AU T H O R C O N T R I B U T I O N Preuk: Methodology (equal); Writing –­ review & editing (equal). Sylvia Haider: Conceptualization (lead); Data curation (lead); Amanda Ratier Backes: Methodology (equal); Writing –­ review & ed- Methodology (equal); Writing –­ original draft (lead); Writing –­ re- iting (equal). Zafar A. Reshi: Methodology (equal); Writing –­ review view & editing (lead). Jonas J. Lembrechts: Conceptualization (lead); & editing (equal). Sabine B. Rumpf: Methodology (equal); Writing –­ Methodology (equal); Writing –­ original draft (lead); Writing –­ review review & editing (equal). Verónica Sandoya: Methodology (equal); & editing (lead). Keith McDougall: Methodology (equal); Writing –­ Writing –­ review & editing (equal). Mellesa Schroder: Methodology original draft (equal); Writing –­ review & editing (equal). Aníbal (equal); Writing –­ review & editing (equal). Karina Lilian Speziale: Pauchard: Methodology (equal); Writing –­ original draft (equal); Methodology (equal); Writing –­ review & editing (equal). Davnah Writing –­ review & editing (equal). Jake M. Alexander: Methodology Urbach: Methodology (equal); Writing –­ review & editing (equal). (equal); Writing –­ original draft (equal); Writing –­ review & editing Graciela Valencia: Methodology (equal); Writing –­ review & edit- (equal). Agustina Barros: Methodology (equal); Writing –­ origi- ing (equal). Vigdis Vandvik: Methodology (equal); Writing –­ re- nal draft (equal); Writing –­ review & editing (equal). Lohengrin A. view & editing (equal). Michaela Vítková: Methodology (equal); Cavieres: Methodology (equal); Writing –­ original draft (equal); Writing –­ review & editing (equal). Tom Vorstenbosch: Methodology Writing –­ review & editing (equal). Irfan Rashid: Methodology (equal); Writing –­ review & editing (equal). Tom W. N. Walker: (equal); Writing –­ original draft (equal); Writing –­ review & edit- Methodology (equal); Writing –­ review & editing (equal). Neville ing (equal). Lisa J. Rew: Methodology (equal); Writing –­ original Walsh: Methodology (equal); Writing –­ review & editing (equal). draft (equal); Writing –­ review & editing (equal). Alla Aleksanyan: Genevieve Wright: Methodology (equal); Writing –­ review & edit- Methodology (equal); Writing –­ review & editing (equal). José R. ing (equal). Shengwei Zong: Methodology (equal); Writing –­ review Arévalo: Methodology (equal); Writing –­ review & editing (equal). & editing (equal). Tim Seipel: Conceptualization (supporting); Data Valeria Aschero: Methodology (equal); Writing –­ review & editing curation (lead); Methodology (equal); Writing –­ original draft (equal); (equal). Chelsea Chisholm: Methodology (equal); Writing –­ review & Writing –­ review & editing (lead). editing (equal). Vincent Ralph Clark: Methodology (equal); Writing –­ review & editing (equal). Jan Clavel: Methodology (equal); Writing –­ DATA AVA I L A B I L I T Y S TAT E M E N T review & editing (equal). Curtis Daehler: Methodology (equal); MIREN road survey data from 2007 to 2015 are available on Zenodo Writing –­ review & editing (equal). Pervaiz A. Dar: Methodology (Seipel, Tim, Haider, Sylvia, & MIREN consortium (2021). MIREN sur- (equal); Writing –­ review & editing (equal). Hansjörg Dietz: vey of plant species in mountains (v0.1) [Data set]. Zenodo. https:// Methodology (equal); Writing –­ review & editing (equal). Romina D. doi.org/10.5281/zenodo.5529072) and through GBIF (https://www. Dimarco: Methodology (equal); Writing –­ review & editing (equal). gbif.org/publi​sher/76388​ab6-­61ca-­439a-­ab09-­e1fe7​3eb224a). Peter Edwards: Methodology (equal); Writing –­ review & editing (equal). Franz Essl: Methodology (equal); Writing –­ review & edit- ORCID ing (equal). Eduardo Fuentes-­Lillo: Methodology (equal); Writing –­ Sylvia Haider https://orcid.org/0000-0002-2966-0534 review & editing (equal). Antoine Guisan: Methodology (equal); Jonas J. Lembrechts https://orcid.org/0000-0002-1933-0750 Writing –­ review & editing (equal). Onalenna Gwate: Methodology Keith McDougall https://orcid.org/0000-0002-8288-6444 (equal); Writing –­ review & editing (equal). Anna Hargreaves: Aníbal Pauchard https://orcid.org/0000-0003-1284-3163 Methodology (equal); Writing –­ review & editing (equal). Gabi Jake M. Alexander https://orcid.org/0000-0003-2226-7913 Jakobs: Methodology (equal); Writing –­ review & editing (equal). Agustina Barros https://orcid.org/0000-0002-6810-2391 Alejandra Jiménez: Methodology (equal); Writing –­ review & edit- Lohengrin A. Cavieres http://orcid.org/0000-0001-9122-3020 ing (equal). Paul Kardol: Methodology (equal); Writing –­ review & Irfan Rashid https://orcid.org/0000-0002-9304-228X editing (equal). Christoph Kueffer: Methodology (equal); Writing –­ Lisa J. Rew http://orcid.org/0000-0002-2818-3991 review & editing (equal). Christian Larson: Methodology (equal); José R. Arévalo https://orcid.org/0000-0003-2152-5212 Writing –­ review & editing (equal). Jonathan Lenoir: Methodology Valeria Aschero https://orcid.org/0000-0003-3865-4133 (equal); Writing –­ review & editing (equal). Bernd Lenzner: V. Ralph Clark https://orcid.org/0000-0001-5058-0742 Methodology (equal); Writing –­ review & editing (equal). Miguel A. Jan Clavel https://orcid.org/0000-0002-7062-5589 Padrón Mederos: Methodology (equal); Writing –­ review & editing Curtis Daehler https://orcid.org/0000-0003-1193-3634 (equal). Maritza Mihoc: Methodology (equal); Writing –­ review & Peter Edwards https://orcid.org/0000-0001-9422-3149 editing (equal). Ann Milbau: Methodology (equal); Writing –­ review Franz Essl https://orcid.org/0000-0001-8253-2112 & editing (equal). John W. Morgan: Methodology (equal); Writing –­ Eduardo Fuentes-­Lillo https://orcid.org/0000-0001-5657-954X review & editing (equal). Jana Müllerová: Methodology (equal); Antoine Guisan http://orcid.org/0000-0002-3998-4815 Writing –­ review & editing (equal). Bridgett Naylor: Methodology Onalenna Gwate http://orcid.org/0000-0003-0237-4316 (equal); Writing –­ review & editing (equal). Ivan Nijs: Methodology Anna L. Hargreaves https://orcid.org/0000-0001-9680-9696 HAIDER et al. | 13 of 16 Paul Kardol https://orcid.org/0000-0001-7065-3435 Averett, J. P., McCune, B., Parks, C. G., Naylor, B. J., DelCurto, T., & Mata-­Gonzalez, R. (2016). Non-­native plant invasion along ele- Christoph Kueffer https://orcid.org/0000-0001-6701-0703 vation and canopy closure gradients in a middle Rocky Mountain Christian Larson https://orcid.org/0000-0002-7567-4953 ecosystem. PLoS One, 11, e0147826. https://doi.org/10.1371/journ​ Jonathan Lenoir https://orcid.org/0000-0003-0638-9582 al.pone.0147826 Bernd Lenzner https://orcid.org/0000-0002-2616-3479 Barros, A., Aschero, V., Mazzolari, A., Cavieres, L. A., & Pickering, C. M. (2020). Going off trails: How dispersed visitor use affects alpine Miguel A. Padrón Mederos https://orcid. vegetation. Journal of Environmental Management, 267, 110546. org/0000-0001-5872-6937 https://doi.org/10.1016/j.jenvm​an.2020.110546 Jana Müllerová https://orcid.org/0000-0001-7331-3479 Blois, J. L., Williams, J. W., Fitzpatrick, M. C., Jackson, S. T., & Ferrier, S. Ivan Nijs https://orcid.org/0000-0003-3111-680X (2013). Space can substitute for time in predicting climate-­change effects on biodiversity. Proceedings of the National Academy of Martin A. Nuñez https://orcid.org/0000-0003-0324-5479 Sciences of the United States of America, 110, 9374–­9379. https:// Rüdiger Otto https://orcid.org/0000-0002-2764-8443 doi.org/10.1073/pnas.12202​28110 Niels Preuk https://orcid.org/0000-0002-7914-8010 Boyle, B., Hopkins, N., Lu, Z., Raygoza Garay, J. A., Mozzherin, D., Rees, Amanda Ratier Backes https://orcid.org/0000-0002-7229-578X T., Matasci, N., Narro, M. L., Piel, W. H., McKay, S. J., Lowry, S., Sabine B. Rumpf https://orcid.org/0000-0001-5909-9568 Freeland, C., Peet, R. K., & Enquist, B. J. (2013). The taxonomic name resolution service: an online tool for automated standard- Verónica Sandoya https://orcid.org/0000-0002-8288-1475 ization of plant names. BMC Bioinformatics, 14, 16. https://doi. Mellesa Schroder https://orcid.org/0000-0001-6178-0109 org/10.1186/1471-­2105-­14-­16 Karina L. Speziale https://orcid.org/0000-0003-2224-2097 Bruelheide, H., Dengler, J., Jiménez-­Alfaro, B., Purschke, O., Hennekens, Davnah Urbach https://orcid.org/0000-0001-9170-7834 S. M., Chytrý, M., Pillar, V. D., Jansen, F., Kattge, J., Sandel, B., Aubin, I., Biurrun, I., Field, R., Haider, S., Jandt, U., Lenoir, J., Peet, R. K., Graciela Valencia https://orcid.org/0000-0002-1551-9345 Peyre, G., Sabatini, F. M., … Zverev, A. (2019). sPlot –­ A new tool for Vigdis Vandvik https://orcid.org/0000-0003-4651-4798 global vegetation analyses. Journal of Vegetation Science, 30, 161–­ Michaela Vitková https://orcid.org/0000-0002-2848-7725 186. https://doi.org/10.1111/jvs.12710 Tom W. N. Walker https://orcid.org/0000-0001-8095-6026 CaraDonna, P. J., Iler, A. M., & Inouye, D. W. (2014). Shifts in flowering phenology reshape a subalpine plant community. Proceedings of the Shengwei Zong https://orcid.org/0000-0002-3583-6110 National Academy of Sciences of the United States of America, 111, Tim Seipel https://orcid.org/0000-0001-6472-2975 4916–­4921. https://doi.org/10.1073/pnas.13230​73111 Chamberlain, S. A., & Szöcs, E. (2013). taxize: taxonomic search and re- REFERENCES trieval in R [version 2; peer review: 3 approved]. F1000Research, 2, 191. https://doi.org/10.12688/​f1000​resea​rch.2-­191.v2 Alexander, J. M., Chalmandrier, L., Lenoir, J., Burgess, T. I., Essl, F., Haider, Chamberlain, S., Szoecs, E., Foster, Z., Arendsee, Z., Boettiger, C., Ram, S., Kueffer, C., McDougall, K., Milbau, A., Nuñez, M. A., Pauchard, K., Bartomeus, I., Baumgartner, J., O'Donnell, J., Oksanen, J., A., Rabitsch, W., Rew, L. J., Sanders, N. J., & Pellissier, L. (2018). Lags Tzovaras, B. G., Marchand, P., Tran, V., Salmon, M., Li, G., & Grenié, in the response of mountain plant communities to climate change. M. (2020). taxize: Taxonomic information from around the web. R Global Change Biology, 24, 563–­579. https://doi.org/10.1111/ package version 0.9.98. Retrieved from https://github.com/ropen​ gcb.13976 sci/taxize Alexander, J. M., Kueffer, C., Daehler, C. C., Edwards, P. J., Pauchard, Clavel, J., Lembrechts, J., Alexander, J., Haider, S., Lenoir, J., Milbau, A., A., Seipel, T., & MIREN Consortium (2011). Assembly of nonnative Nuñez, M. A., Pauchard, A., Nijs, I., & Verbruggen, E. (2021). The floras along elevational gradients explained by directional ecolog- role of arbuscular mycorrhizal fungi in nonnative plant invasion ical filtering. Proceedings of the National Academy of Sciences of the along mountain roads. New Phytologist, 230(3), 1156–­1168. https:// United States of America, 108, 656–­661. https://doi.org/10.1073/ doi.org/10.1111/nph.16954 pnas.10131​36108 Cóbar-­C arranza, A. J., García, R. A., Pauchard, A., & Peña, E. (2014). Alexander, J. M., Lembrechts, J. J., Cavieres, L. A., Daehler, C., Haider, S., Effect of Pinus contorta invasion on forest fuel properties and its Kueffer, C., Liu, G., McDougall, K., Milbau, A., Pauchard, A., Rew, potential implications on the fire regime of Araucaria araucana and L. J., & Seipel, T. (2016). Plant invasions into mountains and alpine Nothofagus antarctica forests. Biological Invasions, 16, 2273–­2291. ecosystems: Current status and future challenges. Alpine Botany, https://doi.org/10.1007/s1053​0 -­014-­0663-­8 126, 89–­103. https://doi.org/10.1007/s0003​5-­016-­0172-­8 Daehler, C. C. (2005). Upper-­montane plant invasions in the Hawaiian Amatulli, G., Domisch, S., Tuanmu, M.-­N., Parmentier, B., Ranipeta, A., Islands: patterns and opportunities. Perspectives in Plant Ecology, Malczyk, J., & Jetz, W. (2018). A suite of global, cross-­scale topo- Evolution and Systematics, 7, 203–­216. https://doi.org/10.1016/j. graphic variables for environmental and biodiversity modeling. ppees.2005.08.002 Scientific Data, 5, 180040. https://doi.org/10.1038/sdata.2018.40 Dainese, M., Aikio, S., Hulme, P. E., Bertolli, A., Prosser, F., & Marini, L. Ansong, M., & Pickering, C. (2013). Are weeds hitchhiking a ride on your (2017). Human disturbance and upward expansion of plants in a car? A systematic review of seed dispersal on cars. PLoS One, 8, warming climate. Nature Climate Change, 7, 577–­580. https://doi. e80275. https://doi.org/10.1371/journ​al.pone.0080275 org/10.1038/nclim​ate3337 Arévalo, J. R., Otto, R., Escudero, C., Fernández Lugo, S., Arteaga, M. A., Debarbieux, B., Oiry Varacca, M., Rudaz, G., Maselli, D., Kohler, T., & Delgado, J. D., & Fernández Palacios, J. M. (2010). Do anthropo- Jurek, M. (Eds.). (2014). Tourism in mountain regions: Hopes, fears genic corridors homogenize plant communities at a local scale? A and realities. Sustainable mountain development series (pp. 108). case studied in Tenerife (Canary Islands). Plant Ecology, 209, 23–­35. UNIGE, CDE, SDC. https://doi.org/10.1007/s1125​8-­0 09-­9716-­y Dickson, J. H., Rodriguez, J. C., & Machado, A. (1987). Invading plants Aschero, V., Barros, A., Bonjour, L. J., & Pérez Sosa, M. C. (2017). at high altitudes on Tenerife especially in the Teide National Park. Invasiones de plantas en caminos vehículares de montaña de Botanical Journal of the Linnean Society, 95, 155–­179. https://doi. los Andes centrales: ¿sobre patas o sobre ruedas? Boletín De La org/10.1111/j.1095-­8339.1987.tb019​95.x Sociedad Argentina De Botanica, 52(Supl), 97. 14 of 16 | HAIDER et al. Dornelas, M., Antão, L. H., Moyes, F., Bates, A. E., Magurran, A. E., Adam, water-­energy dynamics. Biological Invasions, 12, 4019–­4 031. D., Akhmetzhanova, A. A., Appeltans, W., Arcos, J. M., Arnold, https://doi.org/10.1007/s1053​0 -­010-­9816-­6 H., Ayyappan, N., Badihi, G., Baird, A. H., Barbosa, M., Barreto, T. Jetz, W., McGeoch, M. A., Guralnick, R., Ferrier, S., Beck, J., Costello, E., Bässler, C., Bellgrove, A., Belmaker, J., Benedetti-­Cecchi, L., … M. J., Fernandez, M., Geller, G. N., Keil, P., Merow, C., Meyer, C., Hickler, T. (2018). BioTIME: A database of biodiversity time series Muller-­Karger, F. E., Pereira, H. M., Regan, E. C., Schmeller, D. S., & for the Anthropocene. Global Ecology and Biogeography, 27, 760–­ Turak, E. (2019). Essential biodiversity variables for mapping and 786. https://doi.org/10.1111/geb.12729 monitoring species populations. Nature Ecology & Evolution, 3, 539–­ Dullinger, S., Gattringer, A., Thuiller, W., Moser, D., Zimmermann, N. E., 551. https://doi.org/10.1038/s4155​9-­019-­0 826-­1 Guisan, A., Willner, W., Plutzar, C., Leitner, M., Mang, T., Caccianiga, Kadmon, R., Farber, O., & Danin, A. (2004). Effect of roadside M., Dirnbock, T., Ertl, S., Fischer, A., Lenoir, J., Svenning, J. C., Psomas, bias on the accuracy of predictive maps produced by biocli- A., Schmatz, D. R., Silc, U., … Hulber, K. (2012). Extinction debt of high-­ matic models. Ecological Applications, 14, 401–­413. https://doi. mountain plants under twenty-­first-­century climate change. Nature org/10.1890/02-­5364 Climate Change, 2, 619–­622. https://doi.org/10.1038/nclim​ate1514 Khaliq, I. (2019). Range expansion of Phytophthora, particularly Elsen, P. R., Monahan, W. B., & Merenlender, A. M. (2020). Topography Phytophthora cinnamomi into colder environments: adaptation, a and human pressure in mountain ranges alter expected species changing environment or both? PhD thesis, Murdoch University. responses to climate change. Nature Communications, 11, 1974. Kindt, R. (2020). WorldFlora: An R package for exact and fuzzy matching https://doi.org/10.1038/s4146​7-­020-­15881​-­x of plant names against the World Flora Online taxonomic back- Foxcroft, L. C., Spear, D., van Wilgen, N. J., & McGeoch, M. A. (2019). bone data. Applications in Plant Sciences, 8, e11388. https://doi. Assessing the association between pathways of alien plant invaders org/10.1002/aps3.11388 and their impacts in protected areas. NeoBiota, 43, 1–­25. https:// Körner, C., & Spehn, E. (2002). Mountain biodiversity. A global assessment. doi.org/10.3897/neobi​ota.43.29644 The Parthenon Publishing Group. Freeman, B. G., Scholer, M. N., Ruiz-­Gutierrez, V., & Fitzpatrick, J. W. Kueffer, C., Alexander, J., Daehler, C. C., McDougall, K., Pauchard, A., (2018). Climate change causes upslope shifts and mountaintop ex- & MIREN Consortium (2008). The Mountain Invasion Research tirpations in a tropical bird community. Proceedings of the National Network (MIREN). Mountain Research Initiative Newsletter, 1, 12–­14. Academy of Sciences of the United States of America, 115, 11982–­ Kueffer, C., Alexander, J. M., Daehler, C. C., McDougall, K. L., Pauchard, 11987. https://doi.org/10.1073/pnas.18042​24115 A., & Consortium, M. (2009). The Mountain Invasion Research Gelbard, J. L., & Belnap, J. (2003). Roads as conduits for exotic plant in- Network (MIREN)—­A boundary organization bridging research and vasions in a semiarid landscape. Conservation Biology, 17, 420–­432. management for addressing plant invasions in mountains. Mountain https://doi.org/10.1046/j.1523-­1739.2003.01408.x Views, 3, 28–­3 0. Gillet, F., Mauchamp, L., Badot, P.-­M., & Mouly, A. (2016). Recent changes Kueffer, C., Daehler, C., Dietz, H., McDougall, K., Parks, C., Pauchard, A., in mountain grasslands: A vegetation resampling study. Ecology and Rew, L., & Consortium, M. (2014). The Mountain Invasion Research Evolution, 6, 2333–­2345. https://doi.org/10.1002/ece3.1987 Network (MIREN). Linking local and global scales for address- Gobiet, A., Kotlarski, S., Beniston, M., Heinrich, G., Rajczak, J., & Stoffel, ing an ecological consequence of global change. Gaia-­Ecological M. (2014). 21st century climate change in the European Alps—­A re- Perspectives for Science and Society, 23, 263–­265. https://doi. view. Science of the Total Environment, 493, 1138–­1151. https://doi. org/10.14512/​gaia.23.3.11 org/10.1016/j.scito​tenv.2013.07.050 Kühn, P., Ratier Backes, A., Römermann, C., Bruelheide, H., & Haider, S. Guisan, A., Broennimann, O., Buri, A., Cianfrani, C., D'Amen, M., Di Cola, (2021). Contrasting patterns of intraspecific trait variability in na- V., Fernandes, R., Gray, S., Mateo, R. G., Pinto, E., Pradervand, J.-­ tive and non-­native plant species along an elevational gradient on N., Scherrer, D., von Däniken, I., Yashiro, E., & Vittoz, P. (2019). Tenerife, Canary Islands. Annals of Botany, 127, 565–­576. https:// Climate change impact on mountain biodiversity. In T. E. Lovejoy, doi.org/10.1093/aob/mcaa067 & L. Hannah (Eds.), Biodiversity and climate change: Transforming the Lembrechts, J. J., Aalto, J., Ashcroft, M. B., De Frenne, P., Kopecký, M., biosphere (pp. 221–­223). Yale University Press. Lenoir, J., Luoto, M., Maclean, I. M. D., Roupsard, O., Fuentes-­Lillo, Guo, F., Lenoir, J., & Bonebrake, T. C. (2018). Land-­use change interacts E., García, R. A., Pellissier, L., Pitteloud, C., Alatalo, J. M., Smith, S. with climate to determine elevational species redistribution. Nature W., Björk, R. G., Muffler, L., Ratier Backes, A., Cesarz, S., … Nijs, I. Communications, 9, 1315. https://doi.org/10.1038/s4146​7-­018-­ (2020). SoilTemp: A global database of near-­surface temperature. 03786​-­9 Global Change Biology, 26, 6616–­6629. https://doi.org/10.1111/ Haider, S., Kueffer, C., Bruelheide, H., Seipel, T., Alexander, J. M., Rew, L. gcb.15123 J., Arévalo, J. R., Cavieres, L. A., McDougall, K. L., Milbau, A., Naylor, Lembrechts, J. J., Alexander, J. M., Cavieres, L. A., Haider, S., Lenoir, J., B. J., Speziale, K., & Pauchard, A. (2018). Mountain roads and non-­ Kueffer, C., McDougall, K., Naylor, B. J., Nuñez, M. A., Pauchard, native species modify elevational patterns of plant diversity. Global A., Rew, L. J., Nijs, I., & Milbau, A. (2017). Mountain roads shift na- Ecology and Biogeography, 27, 667–­678. https://doi.org/10.1111/ tive and non-­native plant species’ ranges. Ecography, 40, 353–­364. geb.12727 https://doi.org/10.1111/ecog.02200 Haider, S., Kueffer, C., Edwards, P. J., & Alexander, J. M. (2012). Lembrechts, J. J., Lenoir, J., Roth, N., Hattab, T., Milbau, A., Haider, S., Genetically based differentiation in growth of multiple non-­native Pellissier, L., Pauchard, A., Ratier Backes, A., Dimarco, R. D., Nuñez, plant species along a steep environmental gradient. Oecologia, 170, M. A., Aalto, J., & Nijs, I. (2019). Comparing temperature data 89–­99. https://doi.org/10.1007/s0044​2-­012-­2291-­2 sources for use in species distribution models: From in-­situ logging Hengl, T., Mendes de Jesus, J., Heuvelink, G. B. M., Ruiperez Gonzalez, to remote sensing. Global Ecology and Biogeography, 28, 1578–­1596. M., Kilibarda, M., Blagotić, A., Shangguan, W., Wright, M. N., Geng, https://doi.org/10.1111/geb.12974 X., Bauer-­Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, Lembrechts, J. J., Milbau, A., & Nijs, I. (2014). Alien roadside species R. A., Batjes, N. H., Leenaars, J. G. B., Ribeiro, E., Wheeler, I., more easily invade alpine than lowland plant communities in a Mantel, S., & Kempen, B. (2017). SoilGrids250m: Global gridded soil subarctic mountain ecosystem. PLoS One, 9, e89664. https://doi. information based on machine learning. PLoS One, 12, e0169748. org/10.1371/journ​al.pone.00896​6 4.g001 https://doi.org/10.1371/journ​al.pone.0169748 Lenoir, J., Gégout, J.-­C ., Guisan, A., Vittoz, P., Wohlgemuth, T., Jakobs, G., Kueffer, C., & Daehler, C. C. (2010). Introduced weed rich- Zimmermann, N. E., Dullinger, S., Pauli, H., Willner, W., & Svenning, ness across altitudinal gradients in Hawai‘i: Humps, humans and J.-­C . (2010). Going against the flow: potential mechanisms for HAIDER et al. | 15 of 16 unexpected downslope range shifts in a warming climate. Ecography, Science of the Total Environment, 409, 3839–­3849. https://doi. 33, 295–­3 03. https://doi.org/10.1111/j.1600-­0587.2010.06279.x org/10.1016/j.scito​tenv.2011.06.056 Lenoir, J., Gégout, J. C., Marquet, P. A., de Ruffray, P., & Brisse, H. Muñoz, A. A., & Cavieres, L. A. (2008). The presence of a showy invasive (2008). A significant upward shift in plant species optimum eleva- plant disrupts pollinator service and reproductive output in native tion during the 20th century. Science, 320, 1768–­1771. https://doi. alpine species only at high densities. Journal of Ecology, 96, 459–­ org/10.1126/scien​ce.1156831 467. https://doi.org/10.1111/j.1365-­2745.2008.01361.x Liedtke, R., Barros, A., Essl, F., Lembrechts, J. J., Wedegärtner, R. E. M., Muñoz, A. A., & Cavieres, L. A. (2019). Sharing of pollinators between the Pauchard, A., & Dullinger, S. (2020). Hiking trails as conduits for the invasive Taraxacum officinale and co-­flowering natives is not related spread of non-­native species in mountain areas. Biological Invasions, to floral similarity in the high-­Andes. Flora, 261, 151491. https://doi. 22, 1121–­1134. https://doi.org/10.1007/s1053​0 -­019-­02165​-­9 org/10.1016/j.flora.2019.151491 MacDonald, D., Crabtree, J. R., Wiesinger, G., Dax, T., Stamou, N., Fleury, Nogués-­Bravo, D., Araújo, M. B., Errea, M. P., & Martínez-­Rica, J. P. P., Gutierrez Lazpita, J., & Gibon, A. (2000). Agricultural abandon- (2007). Exposure of global mountain systems to climate warming ment in mountain areas of Europe: Environmental consequences during the 21st century. Global Environmental Change, 17, 420–­428. and policy response. Journal of Environmental Management, 59, 47–­ https://doi.org/10.1016/j.gloen​vcha.2006.11.007 69. https://doi.org/10.1006/jema.1999.0335 Nuñez, M. A., Barlow, J., Cadotte, M., Lucas, K., Newton, E., Pettorelli, Maestre, F. T., & Eisenhauer, N. (2019). Recommendations for establish- N., & Stephens, P. A. (2019). Assessing the uneven global distribu- ing global collaborative networks in soil ecology. Soil Organisms, 91, tion of readership, submissions and publications in applied ecology: 73–­85. https://doi.org/10.25674/​so91i​ss3pp73 Obvious problems without obvious solutions. Journal of Applied Martín-­López, B., Leister, I., Lorenzo Cruz, P., Palomo, I., Grêt-­Regamey, Ecology, 56, 4–­9. https://doi.org/10.1111/1365-­2664.13319 A., Harrison, P. A., Lavorel, S., Locatelli, B., Luque, S., & Walz, A. Nuñez, M. A., Chiuffo, M. C., Torres, A., Paul, T., Dimarco, R. D., Raal, P., (2019). Nature’s contributions to people in mountains: A re- Policelli, N., Moyano, J., García, R. A., van Wilgen, B. W., Pauchard, view. PLoS One, 14, e0217847. https://doi.org/10.1371/journ​ A., & Richardson, D. M. (2017). Ecology and management of in- al.pone.0217847 vasive Pinaceae around the world: progress and challenges. McDougall, K. L., Alexander, J. M., Haider, S., Pauchard, A., Walsh, N. Biological Invasions, 19, 3099–­3120. https://doi.org/10.1007/s1053​ G., & Kueffer, C. (2011). Alien flora of mountains: Global compar- 0-­017-­1483-­4 isons for the development of local preventive measures against Pauli, H., Gottfried, M., Dullinger, S., Abdaladze, O., Akhalkatsi, M., plant invasions. Diversity and Distributions, 17, 103–­111. https://doi. Alonso, J. L. B., Coldea, G., Dick, J., Erschbamer, B., Calzado, R. F., org/10.1111/j.1472-­4642.2010.00713.x Ghosn, D., Holten, J. I., Kanka, R., Kazakis, G., Kollár, J., Larsson, P., McDougall, K. L., Khuroo, A. A., Loope, L. L., Parks, C. G., Pauchard, A., Moiseev, P., Moiseev, D., Molau, U., … Grabherr, G. (2012). Recent Reshi, Z. A., Rushworth, I., & Kueffer, C. (2011). Plant invasions plant diversity changes on Europe's mountain summits. Science, in mountains: Global lessons for better management. Mountain 336, 353–­355. https://doi.org/10.1126/scien​ce.1219033 Research and Development, 31, 380–­387. https://doi.org/10.1659/ Pauli, H., Gottfried, M., Lamprecht, A., Niessner, S., Rumpf, S., Winkler, MRD-­JOURN​AL-­D-­11-­0 0082.1 M., Steinbauer, K., & Grabherr, G. (2015). The GLORIA field man- McDougall, K. L., Lembrechts, J., Rew, L. J., Haider, S., Cavieres, L. A., ual –­ standard Multi-­ Summit approach, supplementary methods Kueffer, C., Milbau, A., Naylor, B. J., Nuñez, M. A., Pauchard, A., and extra approaches (pp. 137). GLORIA-­C oordination, Austrian Seipel, T., Speziale, K. L., Wright, G. T., & Alexander, J. M. (2018). Academy of Sciences & University of Natural Resources and Life Running off the road: Roadside non-­native plants invading moun- Sciences. tain vegetation. Biological Invasions, 20, 3461–­3 473. https://doi. Payne, D., Spehn, E. M., Prescott, G. W., Geschke, J., Snethlage, M. A., & org/10.1007/s1053​0 -­018-­1787-­z Fischer, M. (2020). Mountain biodiversity is central to sustainable Meijer, J. R., Huijbregts, M. A. J., Schotten, K. C. G. J., & Schipper, A. development in mountains and beyond. One Earth, 3, 530–­533. M. (2018). Global patterns of current and future road infrastruc- https://doi.org/10.1016/j.oneear.2020.10.013 ture. Environmental Research Letters, 13, 064006. https://doi. Pecl, G. T., Araújo, M. B., Bell, J. D., Blanchard, J., Bonebrake, T. C., Chen, org/10.1088/1748-­9326/aabd42 I.-­C ., Clark, T. D., Colwell, R. K., Danielsen, F., Evengård, B., Falconi, Mengist, W., Soromessa, T., & Legese, G. (2020). Ecosystem services L., Ferrier, S., Frusher, S., Garcia, R. A., Griffis, R. B., Hobday, A. J., research in mountainous regions: A systematic literature re- Janion-­Scheepers, C., Jarzyna, M. A., Jennings, S., … Williams, S. E. view on current knowledge and research gaps. Science of the (2017). Biodiversity redistribution under climate change: Impacts Total Environment, 702, 134581. https://doi.org/10.1016/j.scito​ on ecosystems and human well-­being. Science, 355, eaai9214. tenv.2019.134581 https://doi.org/10.1126/scien​ce.aai9214 Mirtl, M., T. Borer, E., Djukic, I., Forsius, M., Haubold, H., Hugo, W., Pellissier, L., Anzini, M., Maiorano, L., Dubuis, A., Pottier, J., Vittoz, P., & Jourdan, J., Lindenmayer, D., McDowell, W. H., Muraoka, H., Guisan, A. (2013). Spatial predictions of land-­use transitions and Orenstein, D. E., Pauw, J. C., Peterseil, J., Shibata, H., Wohner, associated threats to biodiversity: The case of forest regrowth C., Yu, X., & Haase, P. (2018). Genesis, goals and achievements in mountain grasslands. Applied Vegetation Science, 16, 227–­236. of Long-­Term Ecological Research at the global scale: A criti- https://doi.org/10.1111/j.1654-­109X.2012.01215.x cal review of ILTER and future directions. Science of the Total Pepin, N., Bradley, R. S., Diaz, H. F., Baraer, M., Caceres, E. B., Forsythe, Environment, 626, 1439–­1462. https://doi.org/10.1016/j.scito​ N., Fowler, H., Greenwood, G., Hashmi, M. Z., Liu, X. D., Miller, J. tenv.2017.12.001 R., Ning, L., Ohmura, A., Palazzi, E., Rangwala, I., Schoener, W., Morueta-­Holme, N., Engemann, K., Sandoval-­Acuna, P., Jonas, J. D., Severskiy, I., Shahgedanova, M., Wang, M. B., … Yang, D. Q. (2015). Segnitz, R. M., & Svenning, J.-­C . (2015). Strong upslope shifts in Elevation-­dependent warming in mountain regions of the world. Chimborazo's vegetation over two centuries since Humboldt. Nature Climate Change, 5, 424–­430. https://doi.org/10.1038/nclim​ Proceedings of the National Academy of Sciences of the United States ate2563 of America, 112, 12741–­12745. https://doi.org/10.1073/pnas.15099​ Peters, M. K., Hemp, A., Appelhans, T., Becker, J. N., Behler, C., Classen, 38112 A., Detsch, F., Ensslin, A., Ferger, S. W., Frederiksen, S. B., Gebert, F., Müllerová, J., Vítková, M., & Vítek, O. (2011). The impacts of road and Gerschlauer, F., Gütlein, A., Helbig-­Bonitz, M., Hemp, C., Kindeketa, walking trails upon adjacent vegetation: Effects of road building W. J., Kühnel, A., Mayr, A. V., Mwangomo, E., … Steffan-­Dewenter, materials on species composition in a nutrient poor environment. I. (2019). Climate–­land-­use interactions shape tropical mountain 16 of 16 | HAIDER et al. biodiversity and ecosystem functions. Nature, 568, 88–­92. https:// Spehn, E. M., Libermann, M., & Körner, C. (2006). Land use change and doi.org/10.1038/s4158​6-­019-­1048-­z mountain biodiversity. CRC Press. Petitpierre, B., McDougall, K., Seipel, T., Broennimann, O., Guisan, A., Steinbauer, M. J., Grytnes, J.-­A ., Jurasinski, G., Kulonen, A., Lenoir, J., & Kueffer, C. (2016). Will climate change increase the risk of plant Pauli, H., Rixen, C., Winkler, M., Bardy-­Durchhalter, M., Barni, E., invasions into mountains? Ecological Applications, 26, 530–­544. Bjorkman, A. D., Breiner, F. T., Burg, S., Czortek, P., Dawes, M. A., https://doi.org/10.1890/14-­1871.1 Delimat, A., Dullinger, S., Erschbamer, B., Felde, V. A., … Wipf, S. Pickering, C., & Barros, A. (2012). Mountain environments and tourism. (2018). Accelerated increase in plant species richness on mountain In A. Holden, & D. Fennell (Eds.), The Routledge handbook of tourism summits is linked to warming. Nature, 556, 231–­234. https://doi. and the environment (pp. 183–­191). Routledge. org/10.1038/s4158​6-­018-­0 005-­6 Pollnac, F., Seipel, T., Repath, C., & Rew, L. J. (2012). Plant invasion at van Kleunen, M., Dawson, W., Essl, F., Pergl, J., Winter, M., Weber, E., landscape and local scales along roadways in the mountainous re- Kreft, H., Weigelt, P., Kartesz, J., Nishino, M., Antonova, L. A., gion of the Greater Yellowstone Ecosystem. Biological Invasions, 14, Barcelona, J. F., Cabezas, F. J., Cárdenas, D., Cárdenas-­Toro, J., 1753–­1763. https://doi.org/10.1007/s1053​0 -­012-­0188-­y Castaño, N., Chacón, E., Chatelain, C., Ebel, A. L., … Pyšek, P. (2015). Randin, C. F., Ashcroft, M. B., Bolliger, J., Cavender-­Bares, J., Coops, N. Global exchange and accumulation of non-­native plants. Nature, C., Dullinger, S., Dirnböck, T., Eckert, S., Ellis, E., Fernández, N., 525, 100–­103. https://doi.org/10.1038/natur​e14910 Giuliani, G., Guisan, A., Jetz, W., Joost, S., Karger, D., Lembrechts, Vorstenbosch, T., Essl, F., & Lenzner, B. (2020). An uphill battle? The el- J., Lenoir, J., Luoto, M., Morin, X., … Payne, D. (2020). Monitoring evational distribution of alien plant species along rivers and roads biodiversity in the Anthropocene using remote sensing in species in the Austrian Alps. NeoBiota, 63, 1–­24. https://doi.org/10.3897/ distribution models. Remote Sensing of Environment, 239, 111626. neobi​ota.63.55096 https://doi.org/10.1016/j.rse.2019.111626 Walsh, N. G., & McDougall, K. L. (2018). A new species of Poa L. (Poaceae) Rashid, I., Haq, S. M., Lembrechts, J. J., Khuroo, A. A., Pauchard, A., & from Kosciuszko National Park, New South Wales. Muelleria, 36, 92–­96. Dukes, J. S. (2021). Railways redistribute plant species in mountain Wang, Y., Wu, N., Kunze, C., Long, R., & Perlik, M. (2019). Drivers of landscapes. Journal of Applied Ecology, 58(9), 1967–­1980. https:// change to mountain sustainability in the Hindu Kush Himalaya. In doi.org/10.1111/1365-­2664.13961 P. Wester, A. Mishra, A. Mukherji, & A. B. Shrestha (Eds.), The Hindu Ratier Backes, A., Frey, L., Arévalo, J. R., & Haider, S. (2021). Effects of Kush Himalaya Assessment: Mountains, climate change, sustainability soil properties, temperature and disturbance on diversity and func- and people (pp. 17–­56). Springer International Publishing. tional composition of plant communities along a Steep elevational Wasowicz, P. (2016). Non-­native species in the vascular flora of highlands gradient on Tenerife. Frontiers in Ecology and Evolution, 9, Article and mountains of Iceland. PeerJ, 4, e1559. https://doi.org/10.7717/ 758160. https://doi.org/10.3389/fevo.2021.758160 peerj.1559 Rew, L. J., Brummer, T. J., Pollnac, F. W., Larson, C. D., Taylor, K. T., Taper, Weigelt, P., König, C., & Kreft, H. (2020). GIFT –­ A Global Inventory of M. L., Fleming, J. D., & Balbach, H. E. (2018). Hitching a ride: Seed Floras and Traits for macroecology and biogeography. Journal of accrual rates on different types of vehicles. Journal of Environmental Biogeography, 47, 16–­43. https://doi.org/10.1111/jbi.13623 Management, 206, 547–­555. https://doi.org/10.1016/j.jenvm​ Zong, S., Jin, Y., Xu, J., Wu, Z., He, H., Du, H., & Wang, L. (2016). Nitrogen an.2017.10.060 deposition but not climate warming promotes Deyeuxia angusti- Ross, C., Fildes, S., & Millington, A. (2017). Land-­use and land-­cover folia encroachment in alpine tundra of the Changbai Mountains, change in the Páramo of South-­Central Ecuador, 1979–­2014. Land, Northeast China. Science of the Total Environment, 544, 85–­93. 6, 46. https://doi.org/10.3390/land6​030046 https://doi.org/10.1016/j.scito​tenv.2015.11.144 Rumpf, S. B., Hülber, K., Wessely, J., Willner, W., Moser, D., Gattringer, A., Klonner, G., Zimmermann, N. E., & Dullinger, S. (2019). Extinction debts and colonization credits of non-­forest plants in the European S U P P O R T I N G I N FO R M AT I O N Alps. Nature Communications, 10, 4293. https://doi.org/10.1038/ Additional supporting information may be found in the online s4146​7-­019-­12343​-­x version of the article at the publisher’s website. Schultz, N. L., Reid, N., Lodge, G., & Hunter, J. T. (2014). Seasonal and interannual variation in vegetation composition: Implications for survey design and data interpretation. Austral Ecology, 39, 755–­766. https://doi.org/10.1111/aec.12141 How to cite this article: Haider, S., Lembrechts, J. J., Seipel, T., Alexander, J. M., Edwards, P. J., & Kueffer, C. (2016). Range McDougall, K., Pauchard, A., Alexander, J. M., Barros, A., limits and population dynamics of non-­native plants spread- Cavieres, L. A., Rashid, I., Rew, L. J., Aleksanyan, A., ing along elevation gradients. Perspectives in Plant Ecology, Arévalo, J. R., Aschero, V., Chisholm, C., Clark, V. R., Clavel, J., Evolution and Systematics, 20, 46–­55. https://doi.org/10.1016/j. ppees.2016.04.001 Daehler, C., Dar, P. A., Dietz, H., Dimarco, R. D., … Seipel, T. Seipel, T., Kueffer, C., Rew, L. J., Daehler, C. C., Pauchard, A., Naylor, (2022). Think globally, measure locally: The MIREN B. J., Alexander, J. M., Edwards, P. J., Parks, C. G., Arévalo, J. R., standardized protocol for monitoring plant species Cavieres, L. A., Dietz, H., Jakobs, G., McDougall, K., Otto, R., & distributions along elevation gradients. Ecology and Evolution, Walsh, N. (2012). Processes at multiple scales affect richness and similarity of non-­native plant species in mountains around the 12, e8590. https://doi.org/10.1002/ece3.8590 world. Global Ecology and Biogeography, 21, 236–­246. https://doi. org/10.1111/j.1466-­8238.2011.00664.x