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\begin{document}

\title{Think globally, measure locally: The MIREN standardized protocol for
monitoring species distributions along elevation gradients}



\author[1]{Sylvia Haider}%
\author[2]{Jonas Lembrechts}%
\author[3]{Keith McDougall}%
\author[4]{Anibal Pauchard}%
\author[5]{Jake M. Alexander}%
\author[6]{Agustina Barros}%
\author[4]{Lohengrin Cavieres}%
\author[7]{Irfan Rashid}%
\author[8]{Lisa Rew}%
\author[9]{Alla Aleksanyan}%
\author[10]{José Arevalo Sierra}%
\author[11]{Valeria Aschero}%
\author[5]{Chelsea Chisholm}%
\author[12]{Vincent Ralph Clark}%
\author[2]{Jan Clavel}%
\author[13]{Curtis Daehler}%
\author[14]{Pervaiz  Dar}%
\author[15]{Hansjoerg Dietz}%
\author[16]{Romina Dimarco}%
\author[17]{Peter Edwards}%
\author[18]{Franz Essl}%
\author[19]{Eduardo Fuentes-Lillo}%
\author[20]{Antoine Guisan}%
\author[21]{Onalenna Gwate}%
\author[22]{Anna Hargreaves}%
\author[5]{Gabi Jakobs}%
\author[23]{Alejandra Jiménez}%
\author[24]{Paul Kardol}%
\author[25]{Cristoph Küffer}%
\author[26]{Christian Larson}%
\author[27]{Jonathan Lenoir}%
\author[18]{Bernd Lenzner}%
\author[28]{Miguel  Padrón Mederos}%
\author[19]{Maritza Mihoc}%
\author[29]{Ann Milbau}%
\author[30]{John Morgan}%
\author[31]{Jana Müllerová}%
\author[32]{Bridgett Naylor}%
\author[2]{Ivan Nijs}%
\author[33]{Martin Nuñez}%
\author[34]{Rüdiger Otto}%
\author[35]{Davnah Payne}%
\author[36]{Niels Preuk}%
\author[36]{Amanda Ratier Backes}%
\author[7]{ZAFAR A.  RESHI}%
\author[20]{Sabine Rumpf}%
\author[37]{Verónica Sandoya}%
\author[38]{Mellesa Schroder}%
\author[39]{Karina Speziale}%
\author[19]{Graciela Valencia}%
\author[40]{Vigdis Vandvik}%
\author[41]{Michaela Vítková}%
\author[18]{Tom Vorstenbosch}%
\author[5]{Tom  Walker}%
\author[42]{Neville Walsh}%
\author[43]{Genevieve Wright}%
\author[44]{Shengwei Zong}%
\author[45]{Tim Seipel}%
\affil[1]{Martin Luther University Halle Wittenberg}%
\affil[2]{University of Antwerp}%
\affil[3]{Research Centre for Applied Alpine Ecology}%
\affil[4]{Universidad de Concepcion}%
\affil[5]{ETH Zürich}%
\affil[6]{Centro Científico Tecnológico Mendoza}%
\affil[7]{University of Kashmir}%
\affil[8]{Montana State University}%
\affil[9]{National Academy of Sciences of the Republic of Armenia}%
\affil[10]{University of La Laguna}%
\affil[11]{Universidad Nacional de Cuyo}%
\affil[12]{University of the Free State - Qwaqwa Campus}%
\affil[13]{University of Hawai'i}%
\affil[14]{Amar Singh PG College}%
\affil[15]{ETH Zurich}%
\affil[16]{Instituto de Investigaciones Forestales y Agropecuarias Bariloche (IFAB)}%
\affil[17]{Swiss Federal Institute of Technology (ETH)}%
\affil[18]{University of Vienna}%
\affil[19]{Universidad de Concepción}%
\affil[20]{University of Lausanne}%
\affil[21]{University of the Free State}%
\affil[22]{McGill University}%
\affil[23]{Universidad de Chile Instituto de Ecología y Biodiversidad}%
\affil[24]{Swedish University of Agricultural Sciences}%
\affil[25]{Institute of Integrative Biology}%
\affil[26]{Montana State University Bozeman}%
\affil[27]{CNRS Delegation Nord Pas-de-Calais et Picardie}%
\affil[28]{Universidad de La Laguna}%
\affil[29]{Research Institute for Nature and Forest}%
\affil[30]{La Trobe University}%
\affil[31]{Institute of Botany Czech Academy of Sciences}%
\affil[32]{US Forest Service}%
\affil[33]{Universidad Nacional del Comahue}%
\affil[34]{University of La Laguna Tenerife}%
\affil[35]{University of Bern}%
\affil[36]{Martin-Luther-Universitat Halle-Wittenberg}%
\affil[37]{University Yachay Tech}%
\affil[38]{New South Wales National Parks \& Wildlife Service}%
\affil[39]{Instituto de Investigaciones en Biodiversidad y Medioambiente}%
\affil[40]{University of Bergen}%
\affil[41]{Czech Academy of Sciences}%
\affil[42]{Royal Botanic Gardens Victoria}%
\affil[43]{New South Wales Department of Planning Industry and Environment}%
\affil[44]{Northeast Normal University}%
\affil[45]{Montana State University System}%


\vspace{-1em}



  
  \date{May 15, 2024}


\begingroup
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\endgroup





\selectlanguage{english}
\begin{abstract}
Climate change and other global change drivers threaten plant diversity
in mountains worldwide. A widely documented response to such
environmental modifications is for plant species to change their
elevational ranges. Range shifts are often idiosyncratic and difficult
to generalize, partly due to variation in sampling methods. There is
thus a need for a standardized monitoring strategy that can be applied
across mountain regions to assess distribution changes and community
turnover of native and non-native plant species over space and time.
Here, we present a conceptually intuitive and standardized protocol
developed by the Mountain Invasion Research Network (MIREN) to
systematically quantify global patterns of native and non-native species
distributions along elevation gradients and shifts arising from
interactive effects of climate change and human disturbance. Usually
repeated every five years, surveys consist of 20 sample sites located at
equal elevation increments along three replicate roads per sampling
region. At each site, three plots extend from the side of a mountain
road into surrounding natural vegetation. The protocol has been
successfully used in 18 regions worldwide from 2007 to present. Analyses
of one point in time already generated some salient results, and
revealed region-specific elevational patterns of native plant species
richness, but a globally consistent elevational decline in non-native
species richness. Non-native plants were also more abundant directly
adjacent to road edges, suggesting that disturbed roadsides serve as a
vector for invasions into mountains. From the upcoming analyses of time
series even more exciting results especially about range shifts can be
expected. Implementing the protocol in more mountain regions globally
would help to generate a more complete picture of how global change
alters species distributions. This would inform conservation policy in
mountain ecosystems, where some conservation policies remain poorly
implemented.%
\end{abstract}%



\sloppy


\textbf{Think globally, measure locally:The MIREN standardized protocol
for monitoring species distributions along elevation gradients}

Sylvia Haider\textsuperscript{1,2,x}, Jonas J.
Lembrechts\textsuperscript{3,x}, Keith McDougall\textsuperscript{4},
An\selectlanguage{ngerman}íbal Pauchard\textsuperscript{5,6}, Jake M.
Alexander\textsuperscript{7}, Agustina Barros\textsuperscript{8},
Lohengrin A. Cavieres\textsuperscript{9,6}, Irfan
Rashid\textsuperscript{10}, Lisa J. Rew\textsuperscript{11}, Alla
Aleksanyan\textsuperscript{12,13}, José R. Arévalo\textsuperscript{14},
Valeria Aschero\textsuperscript{8}, Chelsea Chisholm\textsuperscript{7},
V. Ralph Clark\textsuperscript{15}, Jan Clavel\textsuperscript{3},
Curtis Daehler\textsuperscript{16}, Pervaiz A. Dar\textsuperscript{17},
Hansjörg Dietz\textsuperscript{7}, Romina D.
Dimarco\textsuperscript{18}, Peter Edwards\textsuperscript{7}, Franz
Essl\textsuperscript{19}, Eduardo
Fuentes-Lillo\textsuperscript{5,20,21}, Antoine
Guisan\textsuperscript{22}, Onalenna Gwate\textsuperscript{15}, Anna
Hargreaves\textsuperscript{23}, Gabi Jakobs\textsuperscript{7},
Alejandra Jiménez\textsuperscript{24}, Paul
Kardol\textsuperscript{25,26}, Christoph Kueffer\textsuperscript{7,27},
Christian Larson\textsuperscript{11}, Jonathan
Lenoir\textsuperscript{28}, Bernd Lenzner\textsuperscript{19}, Miguel A.
Padrón Mederos\textsuperscript{29}, Maritza Mihoc\textsuperscript{30},
Ann Milbau\textsuperscript{31}, John W. Morgan\textsuperscript{32}, Jana
Müllerová\textsuperscript{33}, Bridgett Naylor\textsuperscript{34}, Ivan
Nijs\textsuperscript{3}, Martin A. Nuñez\textsuperscript{35}, Rüdiger
Otto\textsuperscript{14}, Davnah Payne\textsuperscript{36}, Niels
Preuk\textsuperscript{1}, Amanda Ratier Backes\textsuperscript{1,2},
Zafar A. Reshi\textsuperscript{10}, Sabine B. Rumpf\textsuperscript{37},
Verónica Sandoya\textsuperscript{38,39,40}, Mellesa
Schroder\textsuperscript{41}, Karina L. Speziale\textsuperscript{42},
Graciela Valencia\textsuperscript{30}, Vigdis
Vandvik\textsuperscript{43}, Michaela Vitková\textsuperscript{44}, Tom
Vorstenbosch\textsuperscript{19,45}, Tom W.N. Walker\textsuperscript{7},
Neville Walsh\textsuperscript{46}, Genevieve Wright\textsuperscript{47},
Shengwei Zong\textsuperscript{48}, Tim Seipel\textsuperscript{11}

\textsuperscript{x}SH and JJL contributed equally to this manuscript and
wish to be considered joint first authors.

*Corresponding author: sylvia.haider@botanik.uni-halle.de

Affiliations:

1) Martin Luther University Halle-Wittenberg, Institute of Biology /
Geobotany and Botanical Garden, Am Kirchtor 1, 06108 Halle, Germany,

2) German Centre for Integrative Biodiversity Research (iDiv)
Halle-Jena-Leipzig, Puschstr. 4, 04103 Leipzig, Germany,

3) Research group Plants and Ecosystems (PLECO), University of Antwerp,
Universiteitsplein 1, 2610 Wilrijk, Belgium,

4) Department of Planning, Industry and Environment, PO Box 733,
Queanbeyan, NSW, 2620 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, 8092 Zürich,
Switzerland,

8) Instituto Argentino de Nivología y Glaciología y Ciencias Ambientales
(IANIGLA), Centro Científico Tecnológico (CCT), CONICET Mendoza, Av.
Ruiz Leal s/n, C.C 330, 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 - 190006,
Jammu and Kashmir, 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, Acharyan 1, 0040, Yerevan Armenia,

13) Chair of Biology and Biotechnologies, Armenian National Agrarian
University, Teryan 74, 0009, Yerevan Armenia,

14) Department of Botany, Ecology and Plant Physiology, University of La
Laguna, La Laguna 38202, Spain,

15) Afromontane Research Unit \& Department of Geography, University of
the Free State: Qwaqwa Campus, Phuthaditjhaba, Free State, South Africa,

16) University of Hawai'i at Manoa, School of Life Sciences, 3190 Maile
Way Honolulu, HI 96822,

17) Department of Botany, Amar Singh College Srinagar, India-190008,

18) Grupo de Ecología de Poblaciones de Insectos, IFAB (INTA\selectlanguage{english}-CONICET),
Bariloche, Rio Negro, Argentina,

19) Bioinvasions, Global Change, Macroecology-Group, Department of
Botany and Biodiversity Research, University Vienna, Rennweg 14, 1030
Vienna, Austria,

20) Plants and Ecosystems Research Center (PLECO), University of
Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium,

21) School of Education and Social Sciences, Adventist University of
Chile, Chile,

22) Institute of Earth Surface Dynamics \& Department of Ecology and
Evolution, University of Lausanne, 1015 Lausanne, Switzerland,

23) Department of Biology, McGill University, 1205 Av Dr Penfield,
Montreal QC, Canada H3A 1B1,

24) Laboratorio de Invasiones Biologicas (IEB). Instituto de Ecologia y
Biodiversidad (IEB), Santiago, Chile,

25) Department of Forest Ecology and Management, Swedish University of
Agricultural Sciences, 901-83, Umea, Sweden,

26) Instituto de Ecologia y Biodiversidad (IEB), Santiago, Chile,

27) Department of Botany and Zoology, Centre for Invasion Biology,
Stellenbosch University, Matieland, South Africa,

28) UR ``Ecologie et Dynamique des Systemes Anthropises'' (EDYSAN, UMR
7058 CNRS), Universite de Picardie Jules Verne, 1 Rue des Louvels, 80000
Amiens, France,

29) Departamento de Botanica, Ecologia y Fisiologia Vegetal-Area de
Ecologia (Universidad de La Laguna). Avenida Astrofisico Francisco
Sanchez, s/n. 38200. San Cristobal de La Laguna. S/C de Tenerife,

30) Instituto de Ecologia y Biodiversidad (IEB). Chile,

31) Research Institute for Nature and Forest -- INBO, 1000 Brussels,
Belgium,

32) Department of Ecology, Environment and Evolution, La Trobe
University, Bundoora VIC 3086, Australia,

33) Department of GIS and Remote Sensing, Institute of Botany of the
Czech Academy of Sciences, Zamek 1, 25243 Pruhonice, Czech Republic,

34) US Forest Service, PNW Research Station, 1401 Gekeler Lane, La
Grande OR 97850,

35) Grupo Ecologia de Invasiones. Instituto de Investigaciones en
Biodiversidad y Medio Ambiente, CONICET - Universidad Nacional del
Comahue, Bariloche, Rio Negro, Argentina,

36) Global Mountain Biodiversity Assessment, University of Bern,
Institute of Plant Sciences, Altenbergrain 21, CH -- 3013 Bern,
Switzerland,

37) Department of Ecology and Evolution, University of Lausanne,
Biophore, 1015 Lausanne, Switzerland,

38) Yachay Tech University, School of Life Sciences and Biotechnology,
Hda. San Jose s/n y Proyecto Yachay, 100119, Urcuqui, Ecuador,

39) CREAF, Cerdanyola del Valles 08193, Spain,

40) Unitat d'Ecologia, Universitat Autonoma de Barcelona, Cerdanyola del
Valles 08193, Spain,

41) Department of Planning, Industry and Environment, Jindabyne,
Kosciuszko Rd (PO Box 2228), Jindabyne 2627,

42) Laboratorio Ecotono, INIBIOMA (CONICET-UNCOMA), Pasaje Gutierrez
1125 (8400), Bariloche, Argentina,

43) Department of Biological Sciences, University of Bergen,
Tormohlensgate 53A, Bergen, Norway,

44) Department of Invasion Ecology, Institute of Botany of the Czech
Academy of Sciences, Zamek 1, CZ-252 43 Pr\selectlanguage{polish}ů\selectlanguage{english}honice, Czech Republic,

45) Institute of Biology Leiden, Leiden University, Sylviusweg 72, 2333
BE, Leiden, Netherlands,

46) Royal Botanic Gardens Victoria, Birdwood Avenue, Melbourne Victoria
3004,

47) NSW Government, Biodiversity and Conservation, Department of
Planning, Industry and Environment, PO Box 514, 11 Farrer Place,
Queanbeyan NSW 2620,

48) Key Laboratory of Geographical Processes and Ecological Security in
Changbai Mountains, Ministry of Education, School of Geographical
Sciences, Northeast Normal University, Changchun 130024, China

\textbf{Introduction}

Mountains are biodiversity hotspots and provide a wealth of ecosystem
functions and benefits to people (K\selectlanguage{ngerman}örner \& Spehn, 2002; Martín-López et
al., 2019; Mengist et al., 2020). At the same time, mountain ecosystems
are particularly susceptible to global change. For instance,
temperatures are increasing faster at high elevation than at low
elevation (Nogués-Bravo et al., 2007; Pepin et al., 2015). In the alpine
zone of the European Alps, temperatures have increased approximately
twice as much as the northern hemisphere average over the past 100 years
(Gobiet et al., 2014). Importantly, amplified warming has enabled many
plant species to move to higher elevation (Lenoir et al., 2008; Pauli et
al., 2012; Steinbauer et al., 2018). For instance, between 1971 and 1993
native plant species from the forest understorey in the French mountains
shifted their elevational range uphill at an average rate of 38 m per
decade (Lenoir et al. 2008). Another prominent example is the observed
upward shift of most vascular taxa at Chimborazo in Ecuador since
Alexander von Humboldt's visit more than two centuries ago
(Morueta-Holme et al., 2015). An expected consequence of such uphill
migrations of more competitive lowland species is that less competitive
alpine species might locally extinct on mountain summits (Dullinger et
al., 2012; Alexander et al., 2018; Guisan et al., 2019; Rumpf et al.,
2019). Such local extinctions were recently documented for birds (e.g.
Freeman et al., 2018).

In addition to temperature increase, human activities in mountain areas
have changed markedly over the last decades (e.g. Peters et al., 2019;
Wang et al., 2019; for an overview see Payne et al., 2020). Mountain
land use has intensified in many places across the globe (Spehn et al.,
2006), driven by booming tourism industries (Pickering \& Barros, 2012;
Debarbieux et al., 2014), overexploitation of natural resources and
ever-increasing demands for agricultural land (e.g. Gillet et al., 2016;
Ross et al., 2017). The abandonment of traditional cutting and grazing
practices has also occurred in some mountain regions (e.g. MacDonald et
al., 2000). Both land use intensification and abandonment can alter
plant species distributions and diversity alone (Pellissier et al.,
2013; Alexander et al., 2016) and by interacting with climate change
(Guo et al., 2018; Elsen et al., 2020).

Further, previously remote areas are becoming increasingly accessible
due to construction of new roads and trails, which not only cause a
direct disturbance, but also act as corridors for plant species
movements (Ansong \& Pickering, 2013; Lembrechts et al., 2017; Rew et
al., 2018). The role of roads as dispersal corridors is amplified due to
increased vehicle traffic, often as a result of recreation and tourism
(e.g. Müllerová et al., 2011). Roadside habitats also provide ideal
spaces for non-native plants, which generally benefit from reduced
competition, increased soil nutrients, more favourable microclimatic and
hydrological conditions and intermediate disturbance (Müllerová et al.,
2011; Averett et al., 2016). Thus, both native and non-native plant
species are known to disperse along mountain roads, from low to high
elevation and \emph{vice versa} (Dainese et al., 2017; Lembrechts et
al., 2017; Guo et al., 2018). Indeed, many high elevation areas once
free of lowland and non-native species but connected to lowlands by road
networks are now harbouring lowland and non-native plant species.
Examples for this are the volcanoes of the Hawaiian archipelago (Jakobs
et al., 2010), the high Andes (Barros et al., 2020) and the Teide
National Park on Tenerife (Dickson et al., 1987). Roadside habitats are
also conduits for non-native plants to spread into natural vegetation
once established along roadsides (Alexander et al., 2011; Seipel et al.,
2012).

The elevational redistribution of plant species, especially non-native
species (Dainese et al., 2017), has already significantly impacted
mountain ecosystems (Guo et al., 2018) and will continue to do so in the
future (Petitpierre et al., 2016). For example, non-native plants can
cause biotic homogenization (Haider et al., 2018), reduce the diversity
of local native species (Daehler, 2005) and affect important ecosystem
functions and services (McDougall et al., 2011b; Pecl et al., 2017). In
the mountains of Iceland, non-native \emph{Lupinus nootkatensis}competes
strongly with native plant species and modifies soil properties through
nitrogen fixation (Wasowicz, 2016). In the alpine zone of the central
Chilean Andes, non-native \emph{Taraxacum officinale} shares pollinators
with several native Asteraceae species (Muñoz \& Cavieres, 2019),
reducing pollinator-visitation rates and seed-set where \emph{T.
officinale} is at high abundances (Muñoz \& Cavieres, 2008). Finally,
uphill migration of non-native trees and shrubs can increase fire risk
at high elevation (Cóbar-Carranza et al., 2014), and transform plant
communities through competition (Zong et al., 2016; Nuñez et al., 2017).

While human-driven vegetation change can happen relatively quickly in
mountains, it often only becomes apparent at temporal scales beyond the
few years covered by most ecological experiments (Mirtl et al., 2018).
Thus, data from long-term time series in mountains are essential to
identify and follow changes in plant communities (Pauli et al., 2012).
There are currently two main types of initiatives which monitor
high-elevation vegetation change. At the local or regional scale, some
well-established long-term monitoring sites follow a holistic approach
and document not only floristic changes, but also modifications for
example of soil, hydrology or atmospheric conditions. Examples are Niwot
Ridge in the Colorado Rocky Mountains (\emph{www.nwt.lternet.edu}) or
the Sierra Nevada Global Change Observatory in Spain
(\emph{https://obsnev.es/en/}). At the global scale, the Global
Observation Research Initiative in Alpine Environments (GLORIA,
www.gloria.ac.at; Pauli et al., 2015) is a network monitoring floristic
change on mountain summits with a standardized approach. What would
complement these highly valuable approaches, is a global long-term
monitoring network that covers the full vertical extents of different
mountain regions and that allows the detection of species responses to
both climate and other human activities.

Here, we present a standardized protocol for monitoring changes in the
elevational distribution, abundance and composition of plant
biodiversity in mountains as a result of the interaction between climate
and human pressures. Importantly, the protocol focuses on large
elevation gradients (\textgreater{}1700 m on average; ranging from c.
700 m to \textgreater{}4000 m), allowing vegetation change to be
monitored across a broad range of climates and plant community types. It
explicitly contrasts anthropogenically disturbed and (semi-)natural
vegetation within sampling sites, thus increasing detection of rapid
community changes and providing greater insight into the drivers of
change. The protocol has been developed by the Mountain Invasion
Research Network (MIREN,\emph{www.mountaininvasions.org}) (Kueffer et
al., 2014), a network initially founded in 2005 to study patterns and
processes of non-native plant invasions in mountains and recently
expanded to more widely understand the effects of global change on
mountain plant biodiversity and the distribution of species. The
protocol provides a conceptually intuitive yet comprehensive and
standardized way to record and monitor native and non-native species
along elevation gradients. The survey has been running in some mountain
regions of the world since 2007 (Alexander et al., 2011; Seipel et al.,
2012) and continues to be implemented in new regions. In this paper, we
summarize the most important findings gained over the time of using this
protocol, discuss its strengths and weaknesses and outline opportunities
and challenges for future work. To achieve broad reach and long-term
maintenance of sites, monitoring protocols must be simple, efficient,
and inexpensive. Our intention is to promote the use of the MIREN road
survey protocol to monitor biodiversity change in mountains, and to
generate global, regional and local insights into how plant species and
communities are responding to rapid global change in mountains.

\textbf{Materials and Methods}

\emph{Survey design}

The MIREN road survey is conducted by region. In each region,
participants select three sample roads that extend over a broad
elevation gradient, ideally reaching elevations beyond the treeline (for
examples, see Figure 1). We define a region as an area in the same
biogeographical unit containing similar flora, geology and elevational
ranges, usually with distances between roads of less than 150 km (Figure
2). Selected roads should begin at the bottom of the mountain region, in
a valley, at sea level or where no further elevation change occurs, and
reach the highest elevation typical for roads in the region. Roads can
be gravel or paved but should be open for public vehicle traffic for at
least some part of the year. Once roads have been selected, the
elevational range of each road is divided into 19 equally wide
elevational bands from the lowest to highest possible sampling location,
giving a total of 20 sample sites per road located at the splits between
elevational bands. Sample sites are determined prior to going into the
field and located as precisely as possible using a global positioning
system (GPS). At each sample site, three 2~m × 50 m plots are laid out
in the form of a ``T'': one plot (the top of the ``T'') is parallel to
the road. The other two plots extend end-to-end and perpendicular to the
road, starting from the centre of the first plot, with midpoints at 25 m
and 75 m from the roadside plot (Figure 3). The same plots are
resurveyed every five years. If the plot locations have to be changed
due to unforeseen circumstances, new sites are placed as near as
possible and geolocated.

\emph{Plant species surveys}

Within each of the three plots at all 20 sample sites along the three
roads, observers record all vascular plant species (including both
native and non-native species) and visually estimate vegetation cover
and record abundance classes of each species. The detailed sampling
protocol is provided in Supporting Information S1 and can also be
downloaded from the MIREN website (\emph{www.mountaininvasions.org}).
Taxa should be identified to species level using up-to-date local
floras. Before being included in the global database, submitted regional
species lists undergo taxonomic harmonization to detect synonyms for the
same species in different regions, and to correct spelling problems.
This procedure is done by the MIREN data managers, using the R-packages
``taxize'' (Chamberlain \& Szöcs, 2013; Chamberlain et al., 2020) and
``WorldFlora'' (Kindt, 2020). Firstly, species names are matched with
World Flora Online (http://www.worldfloraonline.org), and if not found
there, they are searched via the additional databases included in the
Taxonomic Names Resolution Service (Boyle et al., 2013). All changes of
species names are transmitted to the submitting region for verification
or correction, before the dataset enters the global database (Figure 2).

Each taxon should be classified as native or non-native to that region
by the participant using local floras and databases. As a general rule,
plant species introduced into the country or mountain range after AD
1500 are considered as non-native, although regional deviations 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 plots (when
possible) and placed in a herbarium to facilitate identification and to
inform local floras (Walsh \& McDougall, 2018).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 1: Examples of roads in the landscape (a-c) and key invasive
species (d-f) across a range of MIREN regions. (a) Harsh mountain
climates (here the Ca\selectlanguage{ngerman}ñadas 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 \emph{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)\emph{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\emph{Verbascum thapsus} on a roadside in the highly invaded
lowlands of the Andes in central Chile; (f) \emph{Trifolium pratense} in
northern Norway, where the species is rapidly moving uphill along
mountain roadsides.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Figure 2. Overview of the workflow from region selection and data
collection to inclusion of the data in the global MIREN database.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

Figure 3: Layout of the MIREN sampling 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 x 50 m, plot 1 -- parallel to the roadside (starting at the first
occurrence of roadside vegetation), plot 2 -- centred 25 m from the
roadside plot, plot 3 -- centred 75 m from the roadside plot; (c)
exemplary photograph of monitoring a mountain roadside in Tenerife,
Canary Islands, Spain, depicting a survey of plot 1.

\emph{Repeated monitoring}

To understand long-term dynamics of redistributions of native and
non-native plant species, all regions should strive for regular
long-term monitoring, preferably with a periodicity of five years. To
facilitate monitoring, all plots should be permanently marked in the
field, for instance with magnets or metal tags that can be relocated
with a metal detector or coloured sticks or plastic seal security tags
in remote areas where their removal is unlikely. In addition, precise
sub-meter GPS coordinates should be taken at least once. Photographs
should also be taken of each transect to visualize changes over time,
document data collection and facilitate relocation of plots.

\emph{Add-ons to the standardized protocol}

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
of plant species redistributions. For example, soil temperatures have
been recorded with a high temporal resolution for a year or longer in
several MIREN regions to document how disturbance along roadsides
affects microclimate, including consequences for species redistributions
(for the first regional results see Lembrechts et al., 2019). Plant
functional traits have additionally been collected for species in
Tenerife, Canary Islands, to assess contrasting patterns of
intraspecific trait variability of native and non-native species and the
change of community mean traits and functional diversity with elevation
(K\selectlanguage{ngerman}ühn et al., 2020). Another add-on project has focused on soil chemical
properties and mycorrhization of native and non-native species in the
mountains of Norway (Clavel et al., 2021), and survey plots have also
been used to assess the distribution of plant pathogens
(\emph{Phytophthora} species) in Australia (Khaliq, 2019). Once
participants begin contributing data to the MIREN global road survey
database, they can suggest add-on studies to apply across all regions
that go beyond the existing scope of the survey protocol -- as long as
it is based on a standardized protocol that is fast, simple and low cost
to implement by collaborators. To maximize participation and to discuss
new proposals, data quality and complementarity, ideas for add-on
projects should be developed together with the MIREN steering committee.

\emph{Data submission and accessibility}

The MIREN survey design is a robust and standardized field survey
protocol that provides data contributors amongst others an opportunity
to include regional data in research that addresses globally 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. All data will be made public in the Dryad
data repository in the context of paper publications, or at the very
latest five years after the survey is undertaken (Figure 2). Any
researcher can also request the full MIREN database from MIREN data
managers for global analyses. 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 S2), which can also be downloaded from the MIREN
website (\emph{www.mountaininvasions.org}).

\textbf{Results}

The standardized protocol for recording plant species communities along
mountain roads has been thoroughly tested in the field on all continents
except Antarctica (Figure 4). The first survey was carried out in eight
regions in 2007 and has been repeated every five years since, resulting
in one baseline historical survey (2007) and up to two resurveys (2012
and 2017). The number of regions has increased since 2007, with 18
regions performing the survey by 2018 (Figure 4). The global database
currently includes circa 2,700 plots and \textgreater{}100,000
observations of \textgreater{}5,000 vascular plant species.

One of the most striking findings of the global MIREN surveys to date
has been to document the importance of roads in facilitating mountain
invasions. Specifically, we have found that non-native species richness
in roadsides decreases with increasing elevation, but generally peaks in
the lower third of the elevation gradient (Alexander et al., 2011).
Moreover, the vast majority of non-native species found at high
elevation are also present at low elevation, with only 2.3\% of
high-elevation non-native species being specifically adapted to alpine
environments (Alexander et al., 2016). These findings indicate that
non-native species are first introduced and become established at low
elevation sites, following this they spread to higher elevations
(Alexander et al., 2011). At higher elevation sites, non-native species
generally become increasingly filtered out by environmental pressures,
so fewer warm-adapted perennials reach higher elevations (McDougall et
al., 2018). We have also revealed that the number of non-native species
declines with increasing distance from the road (Seipel et al., 2012;
Haider et al., 2018), indicating that the native plant community serves
as a second environmental filter that selects for more shade- and
moisture-tolerant perennials (McDougall et al., 2018). In addition to
non-native species, the MIREN surveys have shown that native species
also use roads as corridors (Lembrechts et al., 2017). Interestingly,
Lembrechts et al. (2017) found that occurrence optima are higher in
roadside habitats than faraway habitats, and moreover that some alpine
species have shifted their ranges downwards due to altered abiotic
conditions and competitive release in roadside habitats (see also e.g.
Lenoir et al., 2010).

Globally, the MIREN surveys have demonstrated that native plant species
richness does not follow a consistent pattern in non-roadside
(semi-)natural habitat along elevation gradients, suggesting the
existence of additional region-specific mechanisms, such as biome,
vegetation type and human activity. These mechanisms are now the subject
of further study. In contrast, a clearer elevation signal is present on
roadside plots, with total species richness peaking at mid-elevations in
most regions (Haider et al., 2018). Further, we have observed a
reduction in community dissimilarity (beta-diversity) along roadsides
relative to more distant plots, which is amplified by the arrival of
non-native species along mountain roadsides homogenizing plant community
composition (Haider et al., 2018). The MIREN surveys have also provided
insight into the vulnerability of habitats regionally (Pollnac et al.,
2012), the genetic background of successful invasions (Haider et al.,
2012) and the impact and management of local invasions (McDougall et
al., 2011a). For example, in the Greater Yellowstone Ecosystem in the
United States, we found that non-native species emergence varies with
elevation and habitat type, which provided land managers valuable
information for mitigating biological invasions (Pollnac et al., 2012).
Moreover, in the dry Mediterranean Andes in Argentina, which are
characterized by treeless vegetation, the survey demonstrated how
non-native plant species can successfully spread from the roadside into
natural vegetation at low and intermediate elevations, thus highlighting
the susceptibility of these types of ecosystems to invasion (Aschero et
al., 2017). By contrast, the alpine vegetation of northern Norway has
been shown to be more vulnerable to invasion than its low elevation
counterpart, indicating that vegetation structure plays an important
role in community invasibility (Lembrechts et al., 2014). Finally, the
MIREN surveys have already generated information about regional floras.
An excellent example is the discovery of a new species of Poaceae during
MIREN monitoring in Kosciuszko National Park, Australia -- this species
was named after the network: \emph{Poa mireniana} (Walsh \& McDougall,
2018).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

Figure 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.

\textbf{Discussion}

\emph{Strengths of the protocol}

The MIREN road survey protocol is unique for its focus on two critical
co-occurring global change drivers on biodiversity and species
redistributions in mountains: climate change and road construction
(Figure 5). Road construction represents one of the most prominent and
increasing land-use changes in many remote regions (Meijer et al.,
2018), leading to physical disturbance, dispersal corridors and vectors
for plant species (Gelbard \& Belnap, 2003). Coupled with this,
elevation gradients are good proxies for temperature and can be used as
space-for-time model systems for simulating climate change-induced
temperature increase, where low elevation systems to a certain extent
represent future scenarios for higher elevations in a warming climate
(Blois et al., 2013; Lembrechts et al., 2017). Given this, combining
elevation-based climate gradients with road effects allows researchers
to disentangle the interactive effects of climate and road construction
-- as an example of human land-use change -- on biodiversity, including
their relative importance as drivers of species redistributions. Indeed,
it is along clear linear dispersal pathways like roads that changes in
species distributions -- and especially those of non-native species --
become apparent (Lembrechts et al., 2017). This is particularly relevant
when considering the repeated survey approach of the MIREN design, which
makes it possible to study the temporal dynamics of plant species
distributions in response to natural (e.g. succession after natural
disturbances, such as fire), as well as anthropogenic disturbances (e.g.
land-use changes, such as increasing urbanization or domestic grazing,
or the introduction of non-native species).

A final advantage is that along each road, sites are selected at
predetermined elevations and capture all habitats found along an
elevation gradient, equally covering all elevational belts. The protocol
provides a methodological standardization that is straightforward to
replicate globally and yet still yields sufficient explanatory power for
regional case studies due to due to its relationship to the elevation
gradient and its within-region replication (i.e. sampling along three
mountain roads in each region; e.g. Ar\selectlanguage{ngerman}évalo et al., 2010; Pollnac et
al., 2012). In doing so, the protocol remains simple, for example with
plots close to roads remaining easy to reach, and thus applicable in
many mountain regions even when fieldwork sites need to be easily
accessible. This provides another strength of the protocol: it can be
repeated in many places, so that general patterns at the global scale
can be detected through multi-region replication (Alexander et al.,
2011; Seipel et al., 2012; Lembrechts et al., 2017). In summary, data
collected within the MIREN survey framework can be useful for regional
and global studies in a large variety of fields, ranging from classical
biogeography and community ecology to ecological modelling and global
change research.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

Figure 5: Summary of the strengths and opportunities of the MIREN road
survey protocol as well as limitations of the protocol itself and those
resulting from external circumstances.

\emph{Limitations of the protocol}

The focus of the protocol on mountain roads provides excellent
opportunities to disentangle the effects of climate and road
construction on plant species and community redistributions. However,
the protocol also has three important limitations (Figure 5).

First, the protocol excludes the most pristine environments that exist
far from roads and at elevations above where roads reach, so does not
monitor mountain biodiversity as a whole. As such, the protocol is a
complement to the GLORIA protocol, which focuses on long-term climate
change-related vegetation shifts on undisturbed mountain summits (Pauli
et al., 2015). Nevertheless, one regional study has shown that, at least
in northern Scandinavia, the effect of roads on mountain plant diversity
disappears beyond 25 m from the roadside (Lembrechts et al., 2014),
suggesting that the vegetation surveyed in the MIREN survey plot
furthest from the roadside (Figure 3b; 50-100 m distance) may indeed be
representative of regional biodiversity. Yet, using these data beyond
the 100 m reach of the sample site could bring issues for some
applications, such as spatial modelling, where extrapolations for
locations away from the road will suffer from increased uncertainty
(Kadmon et al., 2004). Coupled to this, the restriction of the protocol
to mountain roads means that, depending on the heterogeneity of the
landscape, not all habitat types are necessarily covered relative to
their distribution in the ecosystem. Plot locations may be biased
towards valleys and less steep terrain if road construction favours such
areas. Additionally, while roads represent the most prominent dispersal
pathway present in mountains, they are not the only one (e.g. rivers,
mountain trails, powerline cuttings, cable cars; Foxcroft et al., 2019).
However, the protocol could be easily adapted for other pathways (as
done for trails (Liedtke et al., 2020) and rivers (Vorstenbosch et al.,
2020)), and we suggest that this would be of particular interest in
regions with sparse roads and/or where most of the common non-native
species are wind or water dispersed.

Second, MIREN adopts a discrete temporal and spatial sampling approach.
Specifically, since the protocol focuses on community dynamics and
large-scale patterns it lacks the spatio-temporal resolution to monitor
individual species and populations over time. The relatively low spatial
sampling intensity (i.e. few plots for each elevational belt) and
sometimes large distances between elevational increments (e.g. on
average c. 75 m steps across current MIREN regions) can limit
understanding of local processes, while also biasing sampling against
rarer plant species or habitats. Furthermore, while repeated surveys
facilitate investigation of species range dynamics under global change,
the complete design does not explicitly consider dispersal dynamics
(e.g. through seed rain or seed bank sampling, or seed tracking),
instead assessing such dynamics indirectly through repeated snapshots of
plant community composition.

Third, the standard protocol emphasises simplicity to be as inclusive as
possible and to keep resource use to a minimum. The approach thus
focuses chiefly on plant community composition and coarse estimates of
species abundance (see Supporting Information S1). Other important
variables such as biomass, functional traits, community 3D-structure,
species interactions and other abiotic and biotic variables thus require
additional sampling effort. For the same reason, the protocol is limited
to vascular plants, excluding bryophytes and other taxonomic groups of
potential interest.

Finally, the assumption that elevation can serve as a proxy for climate
is of particular relevance here. Testing how the elevation gradient
correlates with fine-grained climatic gradients requires validation
using high-resolution climate data produced either using
\emph{in-situ}measurements or downscaling of climate models (Lembrechts
et al., 2019). We therefore recommend participants to include at least
one add-on study that deploys temperature data loggers to allow linking
of vegetation patterns with microclimatic gradients (Lembrechts et al.,
2019) -- although this would already add cost.

\emph{External limitations}

Application of the MIREN road survey protocol might be hindered in some
regions, most obviously due to the lack of roads spanning sufficiently
large elevation gradients. Additionally, local land ownership, safety
issues or administrative complexities may complicate 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 insecurities, as
the timeframe of 5-year intervals is beyond what is covered by most
grants. Even though maintaining the observational sites themselves comes
at virtually no financial cost, the monitoring involves considerable
input of field labour, for which costs will vary between regions (Figure
5).

\emph{Opportunities}

Many drivers of global change act rapidly and interactively, and
intensify over time, so assessing their impact on global biodiversity
urgently requires comparable data collected on a truly global scale. The
MIREN road survey protocol has already demonstrated its potential to
explain crucial patterns in native and non-native species
redistributions along mountain roads, but there are a range of further
applications that can be explored. For example, due to its simplicity
the protocol can readily be implemented in many more mountain ranges and
regions. Increasing the number of participating regions, all with their
unique combination of climatic conditions and anthropogenic pressures,
would further increase the potential to draw general conclusions about
the interacting effects of climate change and roads as anthropogenic
disturbance on mountain plant communities (Guo et al., 2018). This is
particularly important for regions currently under-represented by the
existing MIREN survey sites (Figure 4), such as Africa, Eastern Asia and
central America, regions for which long-term biodiversity data are often
lacking (Maestre \& Eisenhauer, 2019). Despite these spatial gaps, MIREN
has already more than doubled in size on its road to becoming a
global-scale network since it was first established in eight regions.
New participants would thus be able to place their region into a much
larger spatio-temporal picture and, as time passes, get an increasingly
strong grasp of how species distributions are changing dynamically,
regionally and across the world.

With its potential to answer important local questions, and feed into
the growing multi-region database, we hope that the MIREN road survey
protocol will become the protocol of choice for those interested in
native and non-native plant biodiversity dynamics in mountain regions.
At the local scale, it can provide good baseline data on biodiversity
changes along elevation gradients in disturbed regions, with
opportunities to inform management decisions (McDougall et al., 2011a).
For example, it can inform policy makers on some of the impacts of urban
expansion and new infrastructure projects in mountains, as well as
identify new non-native species before they become problematic. The
protocol can also provide essential biodiversity variables for global
monitoring efforts (Jetz et al., 2019), since it provides insight into
species abundance change over space and time and can further enrich the
mountain biodiversity data provided on the online data portal of the
Global Mountain Biodiversity Assessment (GMBA). In doing so, it has the
capacity to inform global biodiversity policy initiatives, such as the
Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem
Services (IPBES).

Further opportunities include add-ons and expansions to the protocol
design, for example to measure microclimate (Lembrechts et al., 2019),
dispersal dynamics (e.g. with seed traps), soil biodiversity (e.g.
analyses of the soil microbiome or mycorrhizal colonization of roots) or
plant-animal interactions (e.g. pollinator records, herbivore
abundance). Collecting such data would be important not only in
isolation, but also for helping to create explicit links between
descriptive and predictive species distribution models, both at local
and global scales. Such efforts could even facilitate modelling of
(changes in) the distributions and habitat occupation of mountain plant
species, for instance by coupling georeferenced long-term survey plots
with high-resolution remotely sensed and modelled environmental data
(Randin et al., 2020). The survey approach can similarly be expanded by
adapting it for use along other linear introduction pathways for
non-native species, such as rivers or hiking trails, or by connecting it
with other standardized global biodiversity surveys and assessments,
such as GLORIA (Pauli et al., 2015), sPlot (Bruelheide et al., 2019),
the Global Inventory of Floras and Traits (GIFT; Weigelt et al., 2020),
the Global Naturalized Alien Flora (GloNAF) database (van Kleunen et
al., 2015) and the BioTIME database (Dornelas et al., 2018). Finally,
the protocol has already shown to have great potential for teaching, for
instance by training undergraduate and graduate students in vegetation
sampling, while also having relevance for local policy and management,
for example as demonstration sites (Figure 5).

\textbf{Conclusions}

The MIREN road survey protocol started in 2007 with a specific purpose
-- to monitor non-native plant species invasions along mountain roads --
but has since then proven to be well-suited for an increasing number of
questions related to species redistributions in the fields of
biogeography, ecology and conservation biology. The protocol is
low-tech, straightforward and standardized, and can therefore be
implemented immediately to fill global gaps in biodiversity data,
especially in areas that are traditionally underrepresented in global
biodiversity studies (Nu\selectlanguage{ngerman}ñez et al., 2019) or in regions with scarce or
fluctuating government support for scientific research. In short, this
on-the-ground, multi-regional, simple yet effective monitoring scheme is
a perfect example of `Think globally, measure locally', and has clear
capacity to bring together ecologists from around the world to generate
an even more complete picture of ongoing species redistributions in
mountains. We invite you all to join us!

\textbf{Acknowledgements}

We gratefully acknowledge the immense effort and time that numerous
professionals, field assistants, and students have contributed to the
collection of these data. SH and ARB gratefully acknowledge the support
of iDiv funded by the German Research Foundation (DFG--FZT 118,
202548816). JJL received a postdoctoral fellowship from the Research
Foundation Flanders (FWO, grant nr. 12P1819N), and OG received a
postdoctoral research fellowship through the Afromontane Research Unit,
University of the Free State. The work from JJL, JC and IN is supported
by a research grant from the FWO (grant nr. G018919N). KLS thanks
funding received from PICT 2015-2072 and PIP 2014-0758. LAC and AP
acknowledge support from FONDECYT 1171005, 1180205 and CONICYT PIA CCTE
AFB170008. VS was supported by SENESCYT\selectlanguage{english}-Ecuador, Instituto de Ecologia y
Biodiversidad (IEB) and Laboratorio de Ecologia, Biogeografia y
Sistematica (ECOBIOSIS) de la Universidad de Concepcion, Laboratorio de
Invasiones Biologicas (LIB) de la Universidad de Concepcion, Herbario
QCA and QCNE-Ecuador, Missouri Botanical Garden, and CONICYT (PFB\selectlanguage{english}-023).
MV was supported by a research grant from the BiodivClim Call 2019
(grant nr. TACR SS70010001) and together with JM by long-term research
development project RVO 67985939 from the Czech Academy of Sciences. FE,
BL and TV acknowledge funding by the Austrian Science Foundation FWF
(grant I 3757-B29). PK acknowledges support from the Swedish Research
Council (Vetenskapsradet) (project grant 2015-04214). BN was supported
by the US Forest Service and direct mentorship from C. Parks. Fieldwork
in the Northern Scandes is achieved using INTERACT Transnational Access
funding. AM and VA were supported by the Universidad Nacional de Cuyo
(SIIP 2019 UNCUYO) and the Rufford Foundation. JMA received funding from
the European Commission Horizon 2020 research and innovation programme
under grant agreement 678841. We also thank the Fondation Herbette,
University of Lausanne, for financial support to JMA for the workshop
``Distributed ecological observatories and long-term monitoring of
mountain biodiversity'' held in September 2019 that lead up to this
paper.

\textbf{Authors' contribution}

This paper builds on the protocol as designed originally by the Mountain
Invasion Research Network (MIREN) by SH, KM, AP, JMA, LJR, JRA, CD, HD,
PE, GJ, CK and BN. The idea for the paper and further fine-tuning of the
protocol stems from a MIREN workshop in 2019, attended by SH, KM, AP,
JMA, AB, IR, LJR, AnB, ARB, CC, BE, AG, AH, TTH, PK, CK, DP, EFL, JL,
RVC, SR, VV, TW, REMW, SZ, and TS. SH, JJL and TS led the writing of the
manuscript, with contributions by the MIREN steering committee (KM, AP,
JMA, AB, LAC, IR, LJR). All authors contributed critically to the drafts
-- based on their experience in applying the protocol in their regions
-- and gave final approval for publication.

\textbf{Data availability}

Data collected according to the MIREN road survey protocol will be
published in the context of paper publications or five years after data
collection. Details are governed in the current version of the MIREN
data-sharing agreement which is available on the network's website
(www.mountaininvasions.org) and provided as supplementary material to
this manuscript.

\textbf{Supporting Information}

Supporting Information S1: MIREN road survey protocol

Supporting Information S2: MIREN Data-sharing agreement

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