Small rodent monitoring at Birkebeiner Road, Norway

Abstract

Background
Northern small mammal populations are renowned for their multi-annual population cycles. Population cycles are multi-faceted and have extensive impacts on the rest of the ecosystem. In 2011, we started a student-based research activity to monitor the variation of small rodent density along an elevation gradient following the Birkebeiner Road, in southeast Norway. Fieldwork was conducted by staff and students at the University campus Evenstad, Inland Norway University of Applied Sciences, which has a long history of researching cyclic population dynamics. The faculty has a strong focus on engaging students in all parts of the research activities, including data collection. Small rodents were monitored using a set of snap trap stations. Trapped animals were measured (e.g. body mass, body length, sex) and dissected to assess their reproductive status. We also characterised the vegetation at trapping sites.

New information
We provide a dataset of small rodent observations that show fluctuating population dynamics across an elevation gradient (300 m to 1,100 m a.s.l) and in contrasting habitats. This dataset encompasses three peaks of the typical 3-4-year vole population cycles; the number of small rodents and shrews captured show synchrony and peaked in years 2014, 2017 and 2021. The bank vole Myodes glareolus was by far (87%) the most common species trapped, but also other species were observed (including shrews). We provide digital data collection forms and highlight the importance of long-term data collection.

Full text

Biodiversity Data Journal 11: e105914
doi: 10.3897/BDJ.11.e105914
Data Paper
Small rodent monitoring at Birkebeiner Road,
Norway
Magne Neby , Harry Andreassen , Cyril Pierre Milleret , Simen Pedersen , Ana-Maria Peris Tamayo
, David Carriondo Sánchez , Erik Versluijs , Barbara Zimmermann
‡ Faculty of Applied Ecology, Agricultural Sciences and Biotechnology, Campus Evenstad, Inland Norway University of Applied
Sciences, Koppang, Norway
§ Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, Ås, Norway
| Faculty of Biosciences and Aquaculture, Nord University, N-8049 Bodø, Norway
Corresponding author: Magne Neby (magne.neby@inn.no)
Academic editor: Krizler Tanalgo
Received: 04 May 2023 | Accepted: 12 Aug 2023 | Published: 11 Sep 2023
Citation: Neby M, Andreassen H, Milleret CP, Pedersen S, Peris Tamayo A-M, Carriondo Sánchez D, Versluijs E,
Zimmermann B (2023) Small rodent monitoring at Birkebeiner Road, Norway. Biodiversity Data Journal 11:
e105914. https://doi.org/10.3897/BDJ.11.e105914
Abstract
Background
Northern small mammal populations are renowned for their multi-annual population cycles.
Population cycles are multi-faceted and have extensive impacts on the rest of the
ecosystem. In 2011, we started a student-based research activity to monitor the variation of
small rodent density along an elevation gradient following the Birkebeiner Road, in
southeast Norway. Fieldwork was conducted by staff and students at the University
campus Evenstad, Inland Norway University of Applied Sciences, which has a long history
of researching cyclic population dynamics. The faculty has a strong focus on engaging
students in all parts of the research activities, including data collection. Small rodents were
monitored using a set of snap trap stations. Trapped animals were measured (e.g. body
mass, body length, sex) and dissected to assess their reproductive status. We also
characterised the vegetation at trapping sites.
‡ ‡ ‡,§ ‡
‡,| ‡ ‡ ‡
© Neby M et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY
4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are
credited.

New information
We provide a dataset of small rodent observations that show fluctuating population
dynamics across an elevation gradient (300 m to 1,100 m a.s.l) and in contrasting habitats.
This dataset encompasses three peaks of the typical 3-4-year vole population cycles; the
number of small rodents and shrews captured show synchrony and peaked in years 2014,
2017 and 2021. The bank vole Myodes glareolus was by far (87%) the most common
species trapped, but also other species were observed (including shrews). We provide
digital data collection forms and highlight the importance of long-term data collection.
Keywords
arvicolinae, vole, shrews, trapping, occurrence, database, dissection
Introduction
Voles and lemmings in boreal, alpine and arctic ecosystems are renowned for their multi-
annual population cycles (Elton 1924, Hansson and Henttonen 1985, Kendall et al. 1999).
The fluctuating population dynamics amplify the population’s integral roles in the
ecosystem food web (Boonstra et al. 2016) as vectors of diseases, prey and plant
consumers Nystuen et al. 2014, Magnusson et al. 2015, Kouba et al. 2021. Many decades
of studies on population cycles have brought insights into the complexity of mechanisms
involved in the dynamics and ecology of populations (Stenseth 1999, Myers 2018, Oli 2019
). However, many questions remain to understand the generality of small rodent population
dynamics (Andreassen et al. 2021).
The focus of this study is the understanding and exploration of the population dynamics of
arvicoline rodent species, particularly the field vole Microtus agrestis (Linnaeus, 1761) and
the bank vole Myodes glareolus (Schreber, 1780), which are amongst the most widespread
and abundant mammals in the European boreal biome. Moreover, the ongoing changes in
climate and biodiversity, particularly warmer winters, are expected to affect these
population dynamics and, consequently, the role these small rodents play in the ecosystem
(Cornulier et al. 2013). In general, long-term studies are much needed to understand such
effects; especially when controlling for phase dependence in multi-annual cycles. Here, we
contribute to the research on population dynamics and the intricate mechanisms involved,
by providing a dataset that encompasses three population cycle peaks. We include data on
small mammal occurrences, physiological measures on captures and habitat descriptions.
General description
Purpose: Assessing changes can only be observed by comparing the new state with a
previous one. Thus, systematic long-term data collection efforts are vital to reveal changes
in nature or the lack thereof. Nevertheless, due to long-term data’s innate high degree of
2Neby M et al

replication, the credibility and usefulness of such time series are high in research,
management and policy (Clutton-Brock and Sheldon 2010, Magurran et al. 2010).
Ironically, as the need for long-term time series increases, the persistence of established
long-term studies is weakened and the establishment of new ones is rare (Hughes et al.
2017).
Evenstad is located in the southeast of Norway and is a campus at Inland Norway
University of Applied Sciences. Evenstad has a long history in ecological investigations
(e.g. Mathisen et al. (2012), Neby et al. (2021)), including researching population dynamics
(e.g. Pedersen et al. (2011), Johnsen et al. (2017)). Furthermore, the faculty has a strong
focus on engaging students in all parts of the research activities, including research data
collection. In 2011, we started a student-based research activity to monitor small rodent
populations. After more than ten years, the time series is still young in terms of observing
cyclic phenomena. Nonetheless, the data include three high-density periods (i.e. peaks).
We hope this paper will motivate long-term maintenance of the time series and facilitate
data and knowledge sharing.
Project description
Title: Birkebeinervegen monitoring (alias Birkebeinervegen rodent trapping).
Personnel: Personnel: Over different years, the co-authors have led the sampling in the
field and/or lab, with a yearly turnover of student participation.
Study area description: The study area is located in the southeast of Norway, in Innlandet
Municipality (61°N, 11°E, Fig. 1). Here, arvicoline small rodents are known to exhibit cyclic
population dynamics (Andreassen et al. 2020, Sonerud 2022) and the area is
characterised by a semi-humid and continental climate. The study area is situated across
an elevation gradient following the east-west orientated Birkebeiner Road with gradients in
temperature, precipitation and vegetation (Table 1). The area is dominated by mixed
coniferous forests with Norway spruce Picea albies and Scots pine Pinus sylvestris at low
altitudes and more open areas with mountain birch Betula pubescens at higher elevations.
The understoreys are dominated by dwarf shrubs, such as the bilberry Vaccinium myrtillus
in the low elevations and lichens and grasses higher up.
Funding: This research was part of the BEcoDyn project supported by Hedmark University
of Applied Sciences and a grant from the Norwegian Research Council (NFR project
221056) to H.P.A. Remaining funding from INN—Inland Norway University of Applied
Sciences.
Sampling methods
Description: Study design: The Birkebeiner Road connects the two large valleys
Gudbrandsdalen and Østerdalen from east to west over approximately 60 km (40 km
straight line distance). The locations for the trapping stations were selected to obtain 100 m
Small rodent monitoring at Birkebeiner Road, Norway 3

a.s.l. intervals between each station ranging from 300 m to 1,100 m a.s.l. (Fig. 1). This
resulted in stations being between 0.5 and 4 km apart. This minimised the chances of
trapping stations overlapping home ranges of small rodents.
Western endpoint High elevation point Eastern endpoint
Elevation (m a.s.l.) 500 1100 300
Weather station name Lillehammer - Nordsetervegen Sjusjøen - Storåsen Evenstad
- Elevation (m a.s.l.) 562 930 255
- Temperature ( C) 4.2 2.1 4.0
- Mean daily precipitation (mm) 2.3 2.9 NA
In the initial setup for each trapping station, starting 10 m from the road, 10 metal snap
traps (numbered 1-10, with trap 1 being closest to the road) were placed systematically 10
m apart along a transect at a right angle from the road. These trap locations were
registered using handheld GPS devices (ca. 5 m accuracy), marked with coloured ribbons
that were left out all year and their coordinates were reused the following years. The traps
were placed in the understorey at the exact GPS location, however, slightly adjusted from
2022, when the traps were placed in the understorey in the most suitable location (i.e.
close to holes, rock boulders, tree roots etc.) within one metre from the GPS location in
order to maximise catches within the microsite.
0
Table 1.
Weather statistics in representative locations to the trapping transect area (MET Norway, 2022).
Figure 1.
Study area and the 23 trapping station locations (red circles) situated along the Birkebeiner
Road. Each station contains a transect of 10 traps with fixed locations. The vegetation
descriptions were taken close to the traps. The captures were further described and dissected
at the University campus Evenstad (marked with a black dot).
4Neby M et al

Small mammal data: The trapping sessions consisted of five days of fieldwork. The
trapping session was started by activating and baiting the traps with pieces of carrots
mixed with peanut butter during the first morning. The three following mornings, all traps
were checked and, if necessary, re-baited and/or re-activated. During these procedures,
the trap’s status was noted (e.g. animal captured, broken trap etc., see a complete set of
variables and definitions in the Data Resources section below in the DynamicProperties
description in the Event dataset) and trapped animals were collected. On the last day of
the session, traps were monitored as usual and retrieved from the field.
We carried out trapping sessions in autumn from years 2011 onwards and also in spring
during the years 2011–2015. This translates into a total effort of 690 trap-nights per
trapping session (see details in Table 2) with large inter-annual variation in the number of
caught animals (Fig. 2, Table 2) and with the bank vole (Myodes glareolus) as the most
common catch (87%).
Year Month Apodemus
flavicollis
Apodemus
sylvaticus
Lemmus
lemmus
Microtus
agrestis
Microtus
oeconomus
Microtus
sp.
Myodes
glareolus
Myodes
rufocanus
Myopus
schisticolor
Sorex
sp.
Unidentified Total
captures
Number
of trap
nights
2011 June 1 - 2 1 1 - 33 - 1 - - 39 690
2011 September - - - - - - 38 6 - 2 - 46 689
2012 June 1 - - - - - 11 1 - 2 - 15 690
2012 September 1 1 - - - - 42 2 - 9 - 55 690
2013 June - - - 4 - - 21 1 - 1 1 28 689
2013 September - 1 - 12 - - 166 - - 3 3 185 686
2014 June - - 2 20 1 - 92 - 1 - 4 120 688
2014 September - - 1 13 2 - 186 - - 8 - 210 682
2015 June - - - - - - 7 - - - - 7 690
2015 September - - - - - - 11 - - 1 - 12 685
2016 September - - - 1 - - 47 - - 4 - 52 688
2017 September - - 1 9 - - 184 - - 2 1 197 639
2018 September - - - 2 - - 137 - - 5 - 144 687
2019 September - - - - - - 22 - - - - 22 685
2020 September - 4 - 3 - - 72 - - 2 - 81 677
2021 September - 2 - 23 - - 92 - - 4 3 124 690
2022 October - - - - - 1 83 4 - 6 - 94 690
The collected animals were either brought into a laboratory immediately or frozen at -20 C
until dissection. Here, the animals were examined further including dissection for
reproductive trait measures (see a complete set of variables and their description in Table
3). By using the variables eventID, occurrenceID or locationID, the datasets can be joined.
o
Table 2.
Trapping history with number of total captures during trapping season. When we were unable to
find a trap or it was broken, these were subtracted from the default number of 690 trap nights (i.e.
default 230 traps over three nights).
Small rodent monitoring at Birkebeiner Road, Norway 5

Variable Variable description
MaturityOutside An age/maturity approximation of the animal, either adult, juvenile or unidentified based
on cues on the
outside of the animal (Variable type: text)
BodyMass The body mass of the animal is given in grams. (Variable type: numeric)
Tail The length of the tail in mm (Variable type: numeric)
HeadWidth The width of the head/skull in mm (Variable type: numeric)
BodyLength The length of the whole body including the tail in mm (Variable type: numeric)
MaturityInside Maturity approximation based on immature females having a transparent uterus and
mature females
having a milky-white uterus (Variable type: text)
LitterSize1 Placental scars were used to estimate litter size. First litter. Number of scars from the
freshest litter
(darkest scars) (Variable type: integer)
LitterSize2 Placental scars were used to estimate litter size. Second litter. Number of scars of the
next litter back in
time (Variable type: integer)
LitterSize3 Placental scars were used to estimate litter size. Third litter (Variable type: integer)
Figure 2.
The density index is estimated by the number of captured animals (grey) and captured bank
voles Myodes glareolus (black) per 100 trap nights for annual autumn trappings (filled circle).
The first years of trapping also included trapping during the spring season (+).
Table 3.
The animals that were trapped were further analysed in the laboratory and several variables were
measured. These measures are named with the prefix "anim" in Extendedmeasurementorfact
dataset.
6Neby M et al

Variable Variable description
LitterSizeSummed The total number of placental scars. Independent of litter (Variable type: integer)
EmbryoCount Count of embryos, total (Variable type: integer)
EmbryoLength Embryos were extracted from the body and measured in millimetres. Measured all and
calculated
average (Variable type: numeric)
EmbryoResorption The number of embryo resorption. Small and less developed embryos are subject to
resorption
(Variable type: numeric)
TestesVisibleOutside Visibly swollen testes on the outside prior to dissection (Present or absent) (Variable
type: text)
TestesLength Total length in mm of testes measured during dissection (Variable type: numeric)
Tubili_epididimysPresent Tubili present in the epididymis or absent. The body next to the testes containing whitish
coiled tube
signifies maturity in males (Variable type: text)
Tubili_epididimys Length of tubuli epididymis during dissection in mm (Variable type: numeric)
ObserverLab An anonymised identifier of the observer in the lab (Variable type: integer)
ObserverField An anonymised identifier of the observer during fieldwork (Variable type: integer)
Vegetation data: Within a five-metre radius of each trap, we monitored the vegetation by
describing the dominant habitat, tree layer, bush layer and field layer. We characterised
these variables according to the descriptors given in Table 4. In 2020, each station’s
habitat was described in further detail (Table 5), named with the prefix "ext" in the
Extendedmeasurementorfact dataset.
Dominant habitat Dominant tree layer Dominant shrub layer Dominant field layer
Open Picea sp. Picea sp. Bryophytes
Forest Pinus sp. Pinus sp. Dwarf shrubs
Shrubs Deciduous Deciduous Graminoids
-Juniperus sp. Juniperus sp. Lichens
- None None Herbs
- - - Bare ground
Data availability: The data are available on Dataverse (DOI: https://doi.org/10.18710/
OOJYQ0) and consist of three datasets that can be joined using the variables eventID,
occurrenceID or locationID. The data and R script to ease download and import (including
Table 4.
Vegetation measures performed during each trapping season. Here, the nearby surroundings of
each trap were described using the following fixed variables. These measures are named with the
prefix "min" in the Extendedmeasurementorfact dataset.
Small rodent monitoring at Birkebeiner Road, Norway 7

producing Fig. 2) are available at https://gitlab.com/becodyn/birkebeiner. Updates from
future monitoring will be available on these services.
Dominant
habitat type
Forest
cutting class
Cutting class description Field layer cover
variables
Field layer cover
alternatives
Forest 0 0: impediment (non-productive
forest)
Bilberry absent
Bog 1 1: fresh clearcut, ready for planting
and regrowth
Cowberry seldom < 5%
Shrub 2 2: young forest before first
thinning, trees up to 10-12 m
Other heather frequent < 5%
Alpine tundra 3 3: young forest in thinning stage Grasses 5-25%
- 4 4: forest ready to be harvested Herbs 25-50%
- 5 5: old-growth forest Mosses 50-75%
- - - Lichens 75-100%
- - - Stones -
- - - Old wood -
- - - Bare ground -
Quality control: We used standardised field forms to note observations which were
followed by import to MS Excel (2011-2019 and 2021) and with predefined digital forms
using KoboCollect (https://www.kobotoolbox.org/) from 2020 and onwards (with the
exception of 2021) to reduce transcribing errors. The digital forms are available as .XML in
the repositories and can be imported to KoboToolbox, ODK or similar services. Permits for
trapping are given by The Norwegian Ministry of Climate and Environment.
Sources of error: Snap trapping provides only a relative density index. There are also
local sources of error that potentially affect within and between-year values, such as: 1)
trapping in various weather conditions affecting trapping success, 2) trap placement in
more/less risky/suitable microhabitats, 3) trap placement in general could be an issue in
spatio-temporal analysis, 4) molar teeth were not always checked on Microtus sp., thus
there may be species level uncertainty between species identified as M. oeconomus and
M. agrestis.
Geographic coverage
Description: Description: Birkebeiner Road, Innlandet County, Norway.
Table 5.
Extended vegetation measures were performed in 2020 and 2021. Here, the nearby surroundings
of each trap were described in more detail using the following fixed variables. These measures are
named with the prefix "ext" in the Extended measurement or fact dataset.
8Neby M et al

Coordinates: 61.460856 and 61.247073 Latitude; 11.023757 and 10.465131 Longitude.
Taxonomic coverage
Taxa included:
Rank Scientific Name Common Name
kingdom Animalia Animal
phylum Chordata
subphylum Vertebrata
class Mammalia
order Rodentia
order Eulipotyphla
family Cricetidae
family Soricidae
family Muridae
subfamily Arvicolinae
genus Apodemus
genus Lemmus
genus Microtus
genus Myodes
genus Myopus
genus Sorex
species Apodemus flavicollis Yellow-necked mouse
species Apodemus sylvaticus Wood mouse
species Lemmus lemmus Norway lemming
species Microtus agrestis Field vole
species Microtus oeconomus Tundra vole
species Myodes glareolus Bank vole
species Myodes rufocanus Grey red-backed vole
species Myopus schisticolor Wood lemming
Small rodent monitoring at Birkebeiner Road, Norway 9

Temporal coverage
Notes: We monitored all trapping plots in the fall during the period from 07-06-2011 to
20-10-2022. During the years 2011-2015, we also performed a trapping session during the
spring. The monitoring is planned to continue in the years ahead.
Usage licence
Usage licence: Creative Commons Public Domain Waiver (CC-Zero)
IP rights notes: The dataset in the current work is licensed under a Creative Commons
Attribution (CC-BY) 4.0 Licence.
Data resources
Data package title: Birkebeinervegen monitoring
Resource link: DOI: https://doi.org/10.18710/OOJYQ0
Alternative identifiers: https://gitlab.com/becodyn/birkebeiner
Number of data sets: 3
Data set name: Event
Character set: UTF-8
Download URL: https://doi.org/10.18710/OOJYQ0
Data format: Darwin Core Archive
Data format version: 1.2
Description: A Darwin Core formatted file that describes an occurrence of an event,
such as a trapping survey.
Column label Column description
eventID An identifier for the set of information associated with an Event. The values consist
of the trapping station and the trap number separated by a T (Trap) and the date of
the event. (Variable type: text)
eventDate The date which an Event occurred in the format 'YYYY-MM-DD'. (Variable type:
text).
locationID An identifier for the set of Location information consisting of the trap station (1-23)
and trap number (1-10) separated by T (Trap). (Variable type: text).
verbatimCoordinates The verbatim original spatial coordinates of the Location. (Variable type: text).
10 Neby M et al

verbatimCoordinateSystem The spatial coordinate system for the verbatimCoordinates of the Location.
(Variable type: text).
verbatimSRS The spatial reference system (SRS) upon which coordinates given in
verbatimCoordinates are based. (Variable type: text).
decimalLongitude The geographic longitude (in decimal degrees). (Variable type: numeric).
decimalLatitude The geographic latitude (in decimal degrees). (Variable type: numeric).
coordinateUncertaintyInMeters The horizontal distance (in metres) from the given decimalLatitude and
decimalLongitude describing the smallest circle containing the whole of the
Location. (Variable type: numeric).
geodeticDatum The ellipsoid, geodetic datum or spatial reference system (SRS) upon which the
geographic coordinates given in decimalLatitude and decimalLongitude are based.
(Variable type: text).
dynamicProperties A list of additional measurements, facts, characteristics or assertions about the
record. The keys (i.e. TrapReleased, BaitPresent, Capture, TrapRetrieved,
TrapMoved, TrapConditionOK) and values (i.e. Yes or No) are separated by colons
and properties separated by commas for a data interchange format, such as
JSON. (Variable type: text).
minimumElevationInMeters The lower limit of the range of elevation (altitude, usually above sea level), in
metres. (Variable type: text).
maximumElevationInMeters The upper limit of the range of elevation (altitude, usually above sea level), in
metres. (Variable type: text).
Data set name: Occurrence
Character set: UTF-8
Download URL: https://doi.org/10.18710/OOJYQ0
Data format: Darwin Core Archive
Data format version: 1.2
Description: A Darwin Core formatted file that describes the recorded instance of an
organism at a particular time and place given in event.txt file. It includes information
about the taxonomy and other relevant details. Further details on the trapped animals
are given in the dataset Extendedmeasurementorfact and further described in Table 3.
Column label Column description
eventID An identifier for the set of information associated with an Event. (Variable type: numeric).
occurrenceID An identifier for the Occurrence, here numbers in an ascending sequence from 1. (Variable type:
text).
Small rodent monitoring at Birkebeiner Road, Norway 11

scientificName The full scientific name, with authorship and date information, if known. Includes the name in
lowest level taxonomic rank that can be determined. (Variable type: text).
taxonRank The taxonomic rank of the most specific name in the scientificName. (Variable type: text).
sex The sex of the biological individual(s) represented in the Occurrence. (Variable type: text).
Data set name: Extendedmeasurementorfact
Character set: UTF-8
Download URL: https://doi.org/10.18710/OOJYQ0
Data format: Darwin Core Archive
Data format version: 1.2
Description: A Darwin Core formatted file that contains additional measurements or
facts about the occurrences that are not included in the core occurrence.txt file, e.g.
vegetation measurements included. The variable measurementType is further
described in Tables 3, 4, 5.
Column label Column description
measurementID An unique identifier for the MeasurementOrFact here numbers in an ascending
sequence from 1. (Variable type: text).
eventID If relevant, an identifier for the set of information associated with an Event. Join with
event.txt to include additional details, such as coordinates. (Variable type: text).
occurrenceID If relevant, an identifier for the Occurrence. Join with occurrence.txt to include
additional details, such as body mass of a trapped animal. (Variable type: text).
locationID If relevant, an identifier for the location that can be joined with event.txt. (Variable
type: text).
measurementDeterminedDate The date on which the MeasurementOrFact was made. (Variable type: text).
measurementType The nature of the measurement, fact, characteristic or assertion. The vocabulary
uses three types of prefixes: 'anim' for animal measures; and 'min' for minimum and
'ext' for extended habitat measures, the latter two separating the two methods used
for describing the habitat associated with locationID. These are further described in
Tables 3, 4 and 5, respectively. (Variable type: text).
measurementValue The value of the measurement, fact, characteristic or assertion. Values include text
and numeric values depending on the MeasurementType, see Tables 4, 5.
(Variable type: text).
measurementUnit The units associated with the measurementValue, for example, body mass is given
in grams (g). (Variable type: text).
12 Neby M et al

Acknowledgements
We are grateful to all students for their help and commitment to field and lab work
throughout the years and to Professor Morten Odden for his part in organising fieldwork in
2022. Thanks to Robert Mesibov for helpful comments on data formatting and Vidar Selås
and Krizler Tanalgo for improvements on the manuscript. Most of all, we are grateful to
Professor Harry P. Andreassen (1962-2019) for his kindness, mentorship and for spreading
joy for science.
Author contributions
BZ, HPA and SP conceived the study and designed the scientific protocol; all authors led
the student-orientated fieldwork, lab work and were involved in data management
processes (each in different years); MN wrote the original manuscript, prepared figures and
performed data curation; all authors contributed to the final manuscript.
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