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Tracking the long-term dynamics of plant diversity in Northeast Spain with a network of volunteers and rangers

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Scientific projects can greatly benefit from the participation of non-professionals in identifying environmental changes at a variety of spatial and temporal scales. In 2010, we launched a long-term project in Northeast Spain (MONITO) that has recruited more than 200 volunteers and rangers. Participants monitor regional-species distribution and local-population abundance for a wide variety of plant species: threatened, rare, and indicators of climatic change or habitats of interest. At the local abundance level (the novel “Adopt-a-plant” program), they carry out annual censuses of population abundance for 10 years at least, to eventually estimate standard trends and future vulnerability. In order to show the functional structure of the network and facilitate implementation elsewhere, we evaluate the key aspects of MONITO, which currently involves 183 single-species or multi-species monitoring sites. We use the participant database, an anonymous survey, and the analyses of time invested in fieldwork training, participant turnover, and scientific assessment of monitoring quality. No significant differences were found between volunteers and rangers regarding time invested per monitoring site, quality of data collected, or primary motivation (“participating in a real scientific experience”). Volunteers fit better the local abundance level and reach higher satisfaction and learning. Rangers contribute more to the distribution level and present a higher turnover throughout the monitoring period. MONITO represents a successful way of tracking real biodiversity changes and connecting scientific research to public outreach. Mentoring is a key element of this project, together with a socially integrative (participants with and without experience) and methodologically complementary approach.
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ORIGINAL ARTICLE
Tracking the long-term dynamics of plant diversity in Northeast Spain
with a network of volunteers and rangers
Maria Begoña García
1
&Jose Luis Silva
1
&Pablo Tejero
1
&Iker Pardo
1
&Daniel Gómez
1
Received: 12 October 2017 / Accepted: 18 April 2018
#Springer-Verlag GmbH Germany, part of Springer Nature 2018
Abstract
Scientific projects can greatly benefit from the participation of non-professionals in identifying environmental changes at a
variety of spatial and temporal scales. In 2010, we launched a long-term project in Northeast Spain (MONITO) that has recruited
more than 200 volunteers and rangers. Participants monitor regional-species distribution and local-population abundance for a
wide variety of plant species: threatened, rare, and indicators of climatic change or habitats of interest. At the local abundance
level (the novel BAdopt-a-plant^program), they carry out annual censuses of population abundance for 10 years at least, to
eventually estimate standard trends and future vulnerability. In order to show the functional structure of the network and facilitate
implementation elsewhere, we evaluate the key aspects of MONITO, which currently involves 183 single-species or multi-
species monitoring sites. We use the participant database, an anonymous survey, and the analyses of time invested in fieldwork
training, participant turnover, and scientific assessment of monitoring quality. No significant differences were found between
volunteers and rangers regarding time invested per monitoring site, quality of data collected, or primary motivation
(Bparticipating in a real scientific experience^). Volunteers fit better the local abundance level and reach higher satisfaction
and learning.Rangers contribute more to the distribution level and present a higher turnover throughout the monitoring period.
MONITO represents a successful way of tracking real biodiversity changes and connecting scientific research to public outreach.
Mentoring is a key element of this project, together with a socially integrative (participants with and without experience) and
methodologically complementary approach.
Keywords Citizenscience .Populationtrends .Dataquality .LTER .Vulnerable plant species .Speciesandhabitatsof community
interest
Introduction
Ecological systems naturally vary through time, but over-
whelming evidence demonstrates that the current rate of spe-
cies extinctions far exceeds anything in the fossil record
(Barnosky et al. 2011). Projections of future biodiversity
based on macroecological models indicate a further loss due
to the effects of climate and habitat change (Engler et al. 2011;
Newbold et al. 2015). This alarming situation has prompted
scientists, environmental agencies, and citizens to join forces
in order to track ongoing biodiversity changes and evaluate to
what extent environmental drivers are responsible for them,
before reaching a non-return point (Chapin et al. 2000).
The complexity and the magnitude of current biodiversity
changes make it difficult to use simple variables and indicators
to get a real overview of what is going on in ecological sys-
tems (but see Tittensor et al. 2014). Important biodiversity
changes can often be estimated by analyzing changes through
*Maria Begoña García
mariab@ipe.csic.es
Jose Luis Silva
jl.silva@csic.es
Pablo Tejero
ptibarra@ipe.csic.es
Iker Pardo
ik.pardo.g@gmail.com
Daniel Gómez
dgomez@ipe.csic.es
1
Pyrenean Institute of Ecology (CSIC), Apdo. 13034,
50080 Zaragoza, Spain
Regional Environmental Change
https://doi.org/10.1007/s10113-018-1350-6
time in habitat cover and structure with remote sensing. A
major challenge, however, is assessing the extent of local
short-term changes in the abundance of particular species in
communities characterized by high biodiversity. The rigorous
assessment of changes in species distributions and population
abundances was recently nominated as one of the essential
biodiversity variables (EBV; Pereira et al. 2013), but
collecting this kind of information in a standardized form at
different scales becomes a major challenge (Kissling et al.
2017). We urgently need to track biodiversity changes from
massive data collection in order to determine the current rate
of biodiversity loss and future vulnerability (Magurran et al.
2010). This is, however, very much dependent on long-term
programs (LTER, long-term ecological research) not easy to
be implemented and supported through time. The main reason
is that they depend on a stable crew of well-trained people able
to record and process data year after year (Schmeller et al.
2015), a nearly impossible task for professional scientists
and resource managers alone. Fortunately, the long-term mon-
itoring of some EBV can be covered by programs involving
volunteers (Chandler et al. 2017), demonstrating the high val-
ue of public participation in ecological monitoring.
Citizen science (CS) programs are increasingly helping
with environmental, evolutionary, biogeographic, and conser-
vation issues at broad scales and have yielded important sci-
entific results (Bonney et al. 2015; Devictor et al. 2010;
Dickinson et al. 2010; Silvertown et al. 2011). Volunteers
not only supply a large quantity of data at relatively low cost
(see for example Schmeller et al. 2009;Levreletal.2010;
Bonney et al. 2015), but they also experience a personal in-
crease of their understanding of science (Pocock et al. 2015).
Public data collection projects are, for such reasons, becoming
an essential part of environmental monitoring and adaptive
management (Aceves-Bueno et al. 2015). Nevertheless, these
projects may entail an important risk for subsequent data anal-
ysis if non-professional tasks go beyond using digital devices
recording environmental variables. Moreover, data collection
might be challenging when dealing with living organisms be-
cause some are difficult to be spotted or present difficulties for
taxonomical identification; as a result, variations in sampling
effort might end up in serious bias and compromise the scien-
tific use of the data. Therefore, volunteer mentoring and data
validation are key elements in programs involving the partic-
ipation of non-professionals (Crall et al. 2011; Isaac and
Pocock 2015).
Well-designed and supervised CS projects not only im-
prove cost-effectiveness compared to traditional monitoring
involving professional experts, but they also reduce the cost
of achieving community engagement in environmental issues.
Since volunteer characteristics such as education, motivation,
prior experience, or training, can affect the quality of data
(Ahrends et al. 2011; Crall et al. 2011;Jordanetal.,2011),
an important question in CS programs is to explore whether
their previous experience or academic background can influ-
ence their personal satisfaction, effort invested, or quality of
data gathered.
In this paper, we describe the structure, functionality, and
effectiveness of the network behinda participatory monitoring
project carried out in a very diverse region of the Northeast of
Spain: MONITO (see details at http://www.liferesecom.ipe.
csic.es/en.php, webpage of a LIFE project included). The
overall objective of MONITO is to arrange a long-term system
able to assess the conservation status of the most singular,
vulnerable, and/or interesting flora, as well as some key spe-
cies of habitats of interest to the European Union for which
remote sensing does not work. To accomplish this objective,
we promote and arrange widespread data collection at two
complementary levels entailing different degrees of commit-
ment and skill: regional-distribution species and local-
population abundance. The first level (distribution) is a clas-
sical approach based on species distribution with the aid of
photo vouchers, GPS records, or herbarium specimens, plus
additional information on the population size and actual
threats. In this case, participants need a minimum botanical
knowledge and they conduct the surveys on their own. The
second level (local abundance) focuses on demographic
changes at local scale through the collection of abundance
data over one decade, following a population-specific proto-
col. This is the BAdopt-a-plant^program, which has a strong
scientific component and will produce standard indexes like
the population growth rate (see for example García et al.
2010). This second level is expected to provide earlier warn-
ings of negative trends than the distribution one. To the best of
our knowledge, the Adopt-a-plant program is a unique case in
the world because, contrary to most traditional CS projects
where volunteers contribute to better map plant diversity
(see for example Pescott et al. 2015), it deals with long-term
trends of plant populations, and sampling designs are carefully
set for each monitored population (see below).
An important point of the philosophy of MONITO is that
anyone should be able to participate, either at the distribution
or local abundance level, or both. Although the overall project
has an important CS component, rangers working for the ad-
ministration also do participate. Rangers and volunteers get
the same kind of training and carry out similar tasks under the
supervision of a team of scientists. Neither rangers nor volun-
teers are Bprofessionals,^but the former participate as part of
their job and have easier movement within their working
range (four-wheel cars available and no permits needed to
drive through protected areas), and they have experience or
background on environmental issues (censuses of birds or
mammals are part of their job).
In order to examine the effectiveness of the fast-growing
MONITO network and find out key points for the implemen-
tation of the novel Adopt-a-plant program elsewhere, we an-
alyzed its current structure, some characteristics of people
M. B. García et al.
involved, the effort investment (days for training and hours of
fieldwork), and the data quality. We compared those variables
between volunteers and rangers to testif our methods are good
enough to make results independent on collective background
and professional situation. On the other hand, evaluating what
can encourage participation of citizen scientists is critical, and
which incentives keep their enthusiasm need to be an integral
part of a long-term project. Consequently, we also report the
learning growth and overall satisfaction of the participants, an
information not commonly reported in CS programs (Bela
et al. 2016). In particular, we aimed to answer the following
questions: (1) do volunteers and rangers perform similarly at
the distribution and population levels, and what are the main
differences between them?; (2) what is the main reward vol-
unteers get when they are involved in the Adopt-a-plant pro-
gram?; and (3) what is the cost and rate of success of the
Adopt-a-plant program in terms of time invested by trainers
and participants?. Identifying the strength and weaknesses
perceived by participants and scientists will help to increase
the success of similar projects in the future.
Material and methods
The MONITO project
MONITO was launched as a pilot project for the Natura 2000
network of NE of Spain in 2010 by the Pyrenean Institute of
Ecology (IPE-CSIC), under request of the Regional
Government of Aragón. Later, it was supported by national
research projects and mainly the European Union through a
LIFE project carried out by both institutions. The Natura 2000
network is the largest network of protected areas in the world
and consists of a set of selected European areas for the con-
servation of species and habitats. Many of the studied species
so far in MONITO are catalogued of community interest and
listed in Anexes II, IV, and Vof the Habitats Directive, where-
as others are catalogued as threatened at the regional or na-
tional level. Another important monitored group of plants is
narrow endemics, or classified as rare, alpine, or indicator of
climatic change (e.g., typical of wetlands). A last group of
plants is characteristic of habitats of community interest, and
their dynamics will be used to evaluate habitat changes. The
area where MONITO is carried out covers an extension of
50,000 km
2
across an altitudinal range of 403355 m a.s.l.
(the whole Aragón Autonomous Community) and includes
about 3500 vascular plants, which represents one fourth of
the European flora according to the collective work Flora
Europaea (Tutin et al. 19641980). Populations of monitored
species are located in contrasted environments, from semi-
deserts of the Ebro Valley to Pyrenean alpine summits.
The MONITO people network is made of two different
collectives: volunteers (VOL) and rangers working for the
Regional Government of Aragón (RAN). VOL pay their
own expenses and carry out censuses during free time (vaca-
tion or weekends). RAN are selected by their coordinators at
the Regional Government according to time availability, back-
ground knowledge on botany, and previous experience in oth-
er ecological monitorings. Participants are offered a choice of
species and populations among a list of plants of interest. They
can decide according to their physical condition and prefer-
ence to visit a site over the next decade. Often, volunteers just
want to be of any help to the project and let scientists to choose
the monitored plant or habitat for them. The number and kind
of plants or habitats adopted by rangers, on the contrary, is
usually limited to threatened plants and habitats of community
interest occurring in the area they conduct their work.
Monitored sites are annually visited by individuals or teams
of up to six people. When there is more than one person
involved in the same monitoring site, one is designated in
charge of communication (responsible) and the others as as-
sistants. The turnover of responsible participants was calculat-
ed for VOL and RAN since the beginning of the program.
Sampling design, fieldwork protocols and training, and
overall coordination of the network are carried out by the
research team. This team is also responsible for subsequent
data validation and analyses to produce conclusions on the
dynamics of biodiversity in the working area (Fig. 1).
Besides accurate geolocalization of the populations, field-
work protocols for the distribution level request information
on the total occupancy area and population size, as well as
current threats or disturbances. Protocols for the population
level request information on the abundance of the target plant
such as presence, plant cover, or number of individuals in
permanent, replicated areas across the population. Sampling
design is customized for each site (variable number and size of
permanent plots or transects) to fit the physical conditions of
the responsible person or team, and to reduce sampling error
by taking into account density, population size, and biological
features such as plant size. The ultimate goal is to produce
reliable population time series from single-species or multi-
species monitoring schemes. In the first monitoring year, the
scientists spend one day with each team in the field, explain
the reasons to set up the design in a particular way, and train
them to overcome difficulties by carrying out the census to-
gether. If necessary, scientists assist volunteers and rangers
over a second or third year to make sure that errors in species
detection and individual counting across multiple sampling
units are minimized, and the sampling method holds through
time. Personal communication with participants is frequent
later on, in order to assist or provide them with the necessary
information and materials, or to validate data. That interaction
usually takes place individually, although general meetings
also take place in towns or cities (Fig. 1).
Tracking the long-term dynamics of plant diversity in Northeast Spain with a network of volunteers and...
Assessment of MONITOs network: structure,
functionality, and effectiveness
We used four different sources of information to describe the
MONITO network and its functionality (see Table 1):
(1) The volunteers network database in December 2017,
containing information of variables such as age, academic
background, and current job.
(2) The total number of monitored sites and the onset year.
(3) An anonymous survey requesting information to VOL
and RAN such as degree of satisfaction with the program, and
evaluating the scientists mentoring them. The survey was an-
swered by 102 people (72 volunteers and 30 rangers),
representing about 70% of participants at the time it was con-
ducted (December 2016).
(4) The total number of training hours in the field, and a
scientific evaluation of the quality of the monitoring carried
out by the participants (Bquality assessment^). Both summa-
rize the effort made by the research teamand the data accuracy
in each monitored population.
Data analysis
Chi-square tests were used to compare differences between
VOL and RAN for variables listed in Table 1. In the anony-
mous survey, if one of the levels of the variable under analysis
got extremely low frequencies, B(very)low^and
Bintermediate^frequencies were added up to be compared
with Bhigh^(df = 1 instead of df = 2). Fishers exact tests were
used instead when cell proportions of the 2 × 2 contingence
table did not meet chi-square test requirements.
Results
MONITO consists of 205 active participants by December
2017, 65% volunteers (133) and 35% rangers (72). About
one fourth of VOL (35 persons) and half of RAN (35 persons)
have participated in the distribution level, providing informa-
tion on the presence and population extension or size of
catalogued or rare species across the region. The higher par-
ticipation of RAN in this level reflects their facility to move
around, higher time availability in the area where plants occur,
and experience with maps and GPS devices. This level seems
therefore more suitable for rangers than volunteers.
A much higher proportion of participants (93%) are en-
gaged in the Adopt-a-plant program (local abundance level),
i.e., monitoring one or several plant populations or habitats.
This program was launched in 2010, and it has grown at an
average of 31 new monitoring sites per year since 2014.
Before launching MONITO, only a handful of populations
of endangered plants had been monitored in the region, where-
as 183 population time series from single-species or multi-
species monitoring schemes are being produced now
(Fig. 2). RAN and VOL contribute similarly to this program
in terms of number of plants or habitats monitored, although
volunteer participation has been growing faster in the last
years (Fig. 2).
VOL ages range between 23 and 77 years old, although
more than half (57%) are between 46 and 65 years old (n=
122; Fig. 3a). Gender ratio is balanced (1.2:1 for
males:females respectively; χ
2
=0.538;df=1,p= 0.463), al-
though females outnumber males at younger stages (26
45 years old). Gender ratio for the RAN collective, in contrast,
is very much biased, with 65 males and only 6 females
Fig. 1 MONITO organizational
structure including stakeholders
and actions involved in each step
of the process, from sampling
design to final reports for
administration, agencies, and
general public
M. B. García et al.
involved (χ
2
= 29.629, df = 1, p< 0.001), which is in accor-
dance with a rather unbalanced gender ratio in this collective.
The typical profile of a volunteer is a college graduate
(64%), with no previous background in biology or expertise
Table 1 Variables obtained from three different information sources to describe and assess MONITO, and possible values or responses
Information source Variable Score or answer
Monitored sites Collective responsible VOL (volunteer) / RAN (ranger)
Starting year of the monitoring site 2010 / 2011 / 2012 / 2013 / 2014 / 2015 / 2016 / 2017
Volunteers network
database
Collective VOL (volunteer) / RAN (ranger)
Age (years) 25 / 2635 / 3645 / 4655 / 65
Academic background Primary education / high school graduate / college graduate
Current working situation Student / Pub_Co (employed in a public company) / Priv_
Co (employed in a private company) / employer / un-
employed / retired
Biological background or experience in monitoring Yes / no
Participation in distribution and/or local abundance level Distribution/local abundance/both
Anonymous survey (VOL +
RAN)
Collective VOL (volunteer) / RAN (ranger or equivalent)
Days per year invested in the BAdopt-a-plant^program 1 / 23/410 / more than 10
Hours invested in traveling to the monitoring place 1 / 13/>3
Time invested in fieldwork once in the monitoring place Half day / one day / more than one day
Perception of time invested in the project (very)Low / intermediate / (very)high
Perception of scientific learning or approach to science in
the project
(very)Low / intermediate / (very)high
Degree of overall satisfaction as participant in the project (very)Low / intermediate / (very)high
Evaluation of the responsible scientist (very)Low / intermediate / (very)high
Would you adopt another plant? Yes / maybe / no
How did you know about the network? By friends or colleagues / naturalist associations / media /
others
Have you recommended other people to participate? Yes / no
What do you like most of participating? Be part of a scientific project / learning botany / determine
the success of an endangered or rare plant / share
experiences with other people doing the same / going out
for fieldwork / attending training courses / others (free
description)
What would you like to get from the project and do you
miss?
(Free description)
Scientist assessment Total number of days of fieldwork assistance per MU to
train participants
1/2/3/4/5
Degree of accuracy after participants independency Low / intermediate / high
Fig. 2 Cumulative number of
monitored plant populations or
habitats started with volunteers
(VOL) and rangers (RAN) since
MONITO was launched as a pilot
study in 2010. The map shows the
European area where MONITO is
implemented (Northeast of Spain:
Aragón region)
Tracking the long-term dynamics of plant diversity in Northeast Spain with a network of volunteers and...
in monitoring (65%) and working as a state employee for the
public administration (45%; Fig. 3b). There are some expert
amateurs very skillful for plant identification, but many VOL
engaged in the Adopt-a-plant program carry out fieldwork in
small groups and do not know the scientific names of the
plants. After a short fieldwork training, however, they are able
to distinguish a juvenile and adult plant of the species they
have adopted. There is a high variability in their academic and
professional status, from elementary studies to university pro-
fessors, and from students to owners of small companies.
Their jobs represent a cross section of the Aragon community,
including nurses, teachers, salesmen, businessmen and wom-
en, massage therapists, policeman, or director of a public
research institute (Fig. 3c). Only 14% of VOL are retired,
and, consequently, most volunteers collaborate in the project
during weekends or vacations. Despite such variety of aca-
demic backgrounds, professions, and expertise, the quality
of data gathered by both collectives was similar, slightly but
not significantly higher for RAN than VOL (94% and 85% got
the category of Bhigh or very high^respectively; χ
2
=2.847,
df = 1, p=0.092).
Since the pilot project was launched, virtually all partici-
pants have monitored their population every year. Three vol-
unteers dropped the program due to jobrequirementsor health
problems. Meanwhile, some people from other Spanish re-
gions have requested to participate when they knew about
the Adopt-a-plant program, which means it is attractive
enough to people that has to travel hours and stay longer than
a single day in the region. The main difference between RAN
and VOL is the higher turnover for RAN (25%) than VOL
teams (6%; χ
2
=13.23,df=1,p< 0.001), caused by the high
job mobility of the formers. In these cases, we have to find
replacements and sometimes repeat the training to make sure
that the newcomers will follow exactly the same protocol.
Most VOL invest less than one hour traveling and hiking to
the population or habitat they monitor, and less than half a day
carrying out the annual census (Fig. 4). Between 11% and
14% (VOL and RAN respectively) invest more than three
hours before they start monitoring. A few (8% and 10%) de-
clared that it takes them more than a full day to finish the
census. Overall, both collectives show a similar pattern of time
invested per site monitored, slightlylower for RAN thanVOL
(Fig. 4). The total time invested by scientists training or
assisting them in the field was very similar for VOL and
RAN: 1.3 and 1.4 working days per monitored site respective-
ly. Actually, the range of such assistance goes from just using
the phone to instruct them how to proceed (in very simple
cases of populations consisting of a few individuals it was
not necessary to do training in the field) to up to five days in
five years (when there was a high turnover of people through
time, or it was necessary to change the method or to set up new
permanent areas due to disturbances or loss of signs).
According to responses of the survey (Fig. 5), both collec-
tives ranked similarly as Bloworverylow^the effort they
invested for fieldwork (χ
2
= 0.691, df = 1, p= 0.406), al-
though it seems to be less costly for RAN (60%) than VOL
(49%). The degree of learning or participating in science did
not differ between collectives either (χ
2
= 1.0512, df = 2, p=
0.591), but 43% of VOL considered it Bhigh or very high^
whereas the same percentage scored it as Bintermediate^
among RAN (Fig. 5). VOL declared a higher satisfaction of
being enrolled in MONITO than RAN (83% versus 67% re-
spectively; χ
2
=3.477, df=1, p= 0.0622), and scientists got
higher marks from VOL than RAN too (93 and 80% of VOL
and RAN scored the work of scientists with them as Bgood or
very good;^Fishersexacttestpvalue = 0.077).
Fig. 3 Demographic and social characteristics of MONITO volunteers:
gender and age structure (a), academic background (b), and current job
(c) (see Table 1for further details)
M. B. García et al.
Interestingly, RAN were more prone to Badopt a new plant^
(63%) than VOL (43%), suggesting that either rangers really
enjoy the program or prefer this activity to other regular tasks
included in their jobs.
Almost half of the people (47% of both collectives) have
suggested colleagues or friends to join the program, and 60%
of VOL knew the program through a colleague or friend. Only
12% was aware of the program through the media. Thus,
participant recruitment is not a problem, since newcomers
usually join the project through friends and relatives, not pub-
licity campaigns. VOL and RAN seem to get a similar enjoy-
ment from their involvement in the project, ranking first their
Bparticipation in a scientific project^(61%67% respective-
ly), and second, third, and fourth Bimproving their botanical
knowledge,^Blearning about the dynamics of a threatened
plant,^and Bbeing part of a network^(53%67%). Whereas
VOL rank fifth Bto go out to the field^(36%), RAN have no
interest on that, which makes sense because they spend most
of the time outdoors; they placed Btraining courses^in the
fifth position (10%).
Discussion
MONITO can be considered a Btargeted monitoring^(sensu
Nichols and Williams 2006)andBadaptative monitoring^pro-
ject (Lindenmayer and Likens 2009), conceived as a tool to
track the tendencies of many singular, vulnerable, or key plant
species of habitats through time. It involves two different col-
lectives of participants (volunteers and rangers) and two com-
plementary operational levels of data gathering (regional-spe-
cies distribution and local-population abundance). The com-
plexity and integrative nature of MONITO confers the project
with the capacity of addressing broad environmental questions
related to biodiversity changes.
The Group of Earth Observations Biodiversity Observation
Network (GEO BON) recently proposed monitoring species
distribution and population abundance and structure as one of
the essential biodiversity variables related to biodiversity
changes (Pereira et al. 2013), and citizen science as a feasible
method for that (Chandler et al. 2017). At the same time,
determining trends in abundance has become a standard
Fig. 5 Percentage of participants
according to their perception of
general effort, learning or
approaching to science through
the project, overall satisfaction,
and assessment of his/her scien-
tific mentor (results come from
the answers of n=102
participants)
Fig. 4 Percentage of participants
(VOL volunteers, RAN rangers)
of the program Adopt-a-plant,
according to the total time
invested for traveling (driving +
hiking) to get to the monitoring
site plus carrying out fieldwork
once arrived to the site (results
come from the answers of n=100
participants)
Tracking the long-term dynamics of plant diversity in Northeast Spain with a network of volunteers and...
indicator adopted by EU members to implement the
Convention on Biological Diversity (European
Environmental Agency 2009; Levrel et al. 2010), but only
for selected species of birds and butterflies. In this paper, we
have demonstrated that collaborative projects such as
MONITO, based on personalized research experiences of
non-scientists, can accurately contribute to track changes of
plant population abundance besides species distributions, and
produce reliable and standard indicators similar to the ones
used for animals.
As most CS programs, a scientific institution is behind
MONITO data collection on plant distribution, i.e., CREW
in South Africa (https://www.sanbi.org/biodiversity-science/
state-biodiversity/biodiversity-monitoring-assessment/
custodians-rare-and-endan), POC in Chicago (Havens et al.
2012), etc. The Pyrenean Institute of Ecology, home base for
the project, has welcomed public participation in its herbarium
for decades since its foundation in the 1960s. The citizen
involvement has increased after launching two digital plat-
forms that describe the flora or the NE of Spain and offer
extensive information about the distribution and biology of
plants in the region: FLORAGON (http://floragon.ipe.csic.
es/alfabetica.php) and FLORAPYR (http://
atlasflorapyrenaea.org/florapyrenaea/index.jsp). With these
tools, visual self-learning about plant identification has be-
come easier for amateur volunteers and rangers, and their con-
tribution to species distribution has increased in the last de-
cade (García et al. unpublished). It is crucial to keep their
enthusiasm through collaborative and coordinated projectsbe-
cause these expert amateurs, together with ecological consul-
tants, will have to sustain the inventory and surveillance of
biodiversity in the near future after the loss of professional
taxonomists in academic institutions (Drew 2011).
Therefore, the contribution of non-professionals to biodiver-
sity is not just an opportunistic option but a need if we want to
acquire reliable inventories of biodiversity to implement ef-
fective conservation management practices.
The main concern of CS programs is the quality of the data
from a scientific point of view, as low-quality data would lead
to inappropriate conclusions. Some studies have explored un-
avoidable shortcomings and statistical solutions for error and
bias (Bird et al. 2014; Isaac et al. 2014), but most analyses rule
out concerns about low quality of data gathered through CS
projects, as many examples show that volunteer-collected data
in well-designed studies are as good as those collected by
professional scientists (Comber et al. 2016; Lewandowski
and Specht, 2015). Prior knowledge has been suggested to
improve data quality, and professionals are also thought to
produce data of higher quality than volunteers because they
are likely to have more training and experience (e.g., Ahrends
et al. 2011). However, a recent review failed to conclude that
(Lewandowski and Specht 2015). Moreover, much assess-
ment on data quality has concentrated on surveillance
monitoring of species over broad geographic regions
(Dickinson et al. 2010), and CS methods are so diverse that
it is difficult to make generalizations. The potential effect of
prior experience or any other social variable or demographic
trait of participants on their skill for the collection of high-
quality data seems to be very much task-dependent (Crall
et al. 2011).
Concerning MONITO, we found that the regional-species
distribution level seems to be more suitable for rangers be-
cause of their stronger background or experience in environ-
mental monitoring, besides easier movement in areas of high
diversity. Only a few expert volunteers can make a valuable
contribution in an independent way, as most of them restricted
their contribution to filling up the protocol of their monitored
plant population. Giving the high turnover of rangers, this
Bopportunistic monitoring^(sensu Lewandowski and
Specht, 2015) seems more suitable for them because it is not
as dependent on repeated visits or censuses as the local abun-
dance level. They spend much time in the field, know well
remote places, and have higher chances to find out rare local
plants compared to volunteers. Data gathered through this
level serve to qualitatively assess the overall conservation sta-
tus of target plant species (i.e., number of populations, overall
population sizes, threat and pressures), but they might be less
useful to produce indexes describing the current performance
of populations.
Participants of the Adopt-a-plant program, on the other
hand, follow a strict protocol set up by scientists in the field
at each monitored site. Since this program fits a systematic
monitoring scheme based on repeated annual censuses over a
decade, special care is taken to guarantee that neither the par-
ticipant nor the method for data collection change through
time. To ensure data accuracy, data are validated by the scien-
tific team after collection: if suspicious data come up, partic-
ipants are contacted to avoid mistakes (Fig. 1). Maintaining
the same methods for both volunteers and rangers allowed us
to test the general validity of the protocols and procedures,
and, as we discussed in previous sections, we could not find
significant differences in the quality of their contribution.
Actually, we think that the difficulties for carrying out an
accurate census have little to do with the collective and come
up from the local conditions of the monitored plant or popu-
lation. For example, to estimate abundance data for a small
plant with clonal reproduction, occurring at high density, or
under high interspecific competition usually entails a higher
sampling error than counting large individuals clearly
separated.
Personal interaction is a crucial variable in MONITO, and
that needs a strong implication and commitment of the scien-
tists. Our approach greatly differs from most successful web-
based portals where volunteers collect and send information
on their own. In our case, the success of the project among
volunteers with high academic level might have to do with
M. B. García et al.
their enjoyment of the rigorous scientific methodologies, and
among volunteers with no botanical experience with the secu-
rity provided by scientists. Real-time communications and
face-to-face interactions make rangers and citizen scientists
feel that their participation is a personal and unique research
experience, and they become more confident and motivated
about the utility of their contribution to science.
Rangers often work in protected areas of high biodiversity
value, sometimes located in remote or more isolated mountain
places difficult to reach, and monitor threatened plants. They
play an important role for policy makers, responsible for the
assessment of the conservation status of listed plants or habi-
tats in official catalogues. However, rangers have many other
tasks, and their contribution to the future growth of the net-
work will be probably limited by the size of the collective and
high turnover. Volunteers, on the other hand, need to be often
mentored and helped during weekends and they need special
permits to monitor protected species or move across protected
areas, but we notice how quickly they learn plant names and
natural history, and try to enroll friends and relatives in
MONITO. Since their recruitment is faster and less than 3%
of them abandoned the program, they will probably make a
larger contribution to the expansion of the network in the
future.
It is well known that volunteers are more likely to stay with
projects in which scientists regularly offer feedback, provide
progress reports, thank them for participation, and arrange
field trips and local meetings to increase the likelihood of
easier communication (Bell et al. 2008;Havensetal.2012;
Kühn et al. 2013). This is also what we found in our program,
and that is why we pay attention to social aspects of the project
beyond data quality. MONITO volunteers constitute a com-
munity of participants sharing common features (they do not
enjoy any economic incentive, hardly use technological tools,
the majority have no previous botanical knowledge) and in-
terests (enrollment in a scientific program and potential for
increasing knowledge are common motivations). That is
why besides personal communication about annual data col-
lection, every year we arrange an BAdopt-a-plant celebration
day^in a protected area. We show the results collected over
the year, introduce new volunteers, hike to enjoy the area and
learn local plants, promote exchange of information among
people, and give them the annual certificate of engagement
with a particular plant or group of them in a habitat. Such
event is our way of saying thank you and paying backfor their
work. As demonstrated in other projects, including human and
social components since the beginning is a guarantee of suc-
cess in volunteer-based long-term monitoring schemes
(Dickinson et al. 2012).
Citizen science projects are often focused on environmen-
tal data collection across an array of locations, sometimes at
continental scale. MONITO is geographically more restricted.
It was born to expand the reduced capacity of scientists and
managers in a region of high biodiversity with very few pro-
fessionals, and solve the dependence of data collection from
annual budgets approved by politicians. The project, there-
fore, aims at resolving some of the shortcomings of environ-
mental monitoring and public engagement, by providing a
way of involving amateur botanists and plant ecologists in a
scientific project. CS programs have a great potential for in
situ long-term monitoring given their relative independence of
external funding. Actually, well-organized CS projects are
several years longer than the mean length of US National
Science Foundation grants (Theobald et al. 2015). Recent
studies demonstrated that some CS projects monitoring for-
ests, birds, and butterflies resulted in large net savings as com-
pared to the expected costs of monitoring by government em-
ployees (see review in Aceves-Bueno et al. 2015). The impact
of biodiversity-based CS projects is enormous all over the
world: more than two millions of volunteers collect data,
which translates into billions of US$ or and hundreds of
scientific publications (see reviews in Bonney et al. 2015
and Theobald et al. 2015). But developing and implementing
public data collection projects that yield both scientific and
educational outcomes requires significant effort (Bonney
et al. 2009). CS programs cannot be regarded neither a pana-
cea nor a cheap way of collecting biodiversity information
(Levrel et al. 2010). They require coordination and assistance
and have very important educational and social emergent
properties that go beyond pure academic or management sub-
jects. In the case of MONITO, it has been necessary to set up
easy and robust designs in the first fieldwork visit, train par-
ticipants in a very effective way, simplify protocols to become
straightforward and easy to be filled, and launch new social
activities every year to keep the motivation of veteran partic-
ipants. This also means to maintain the availability of the
facilities (the herbarium and biodiversity database) and the
salaries of the trainers. The scientific team has to find and
check the suitability of new populations to monitor in the
field, assure data quality control through interactive commu-
nication with participants, and assist with general meetings
and activities. But obviously the cost-benefit of a CS coordi-
nated system is very efficient.
Conclusions
MONITO represents a clear improvement in the first step of
plant conservation management: the integrative and extensive
collection of rigorous data on distribution, occupancy, threats,
and trends of plant species over a diverse territory. Besides,
the project constitutes an example of partnership between par-
ticipants with and without experience, managers, and scien-
tists, and also serves to connecting scientific research to public
outreach and education. Volunteers are always there, but their
enthusiasm and energy need to be coordinated and hold
Tracking the long-term dynamics of plant diversity in Northeast Spain with a network of volunteers and...
through time. Managers need information from monitoring
programs for resource management and have employees en-
rolled in them. Scientists should be either responsible or in-
volved in Badaptive monitoring^(sensu Lindenmayer and
Likens 2009) for designing adequate and efficient monitoring
systems, to establish quality controls and apply rigorous sta-
tistical analysis. The success of a project with more than 180
monitoring sites and the regional recruitment of 200 rangers
and volunteers in less than a decade in a small European
region is an evidence of its potential, and make us confident
that it can be replicated in other regions.
In the near future, standardized population trends will be
associated to global change drivers such as extreme climatic
events or habitat modification, because other data are being
gathered in parallel with plant abundance: temperatures are
recorded by miniaturized instrumentation, and land use
changes by remote sensing. This design turns our cluster of
monitoring sites into a Blong-term monitoring mini-sites
network^(Haase et al. 2018), where both biotic and abiotic
variables are integrated to provide more powerful conclusions.
Well-organized networks involving volunteers, even operat-
ing at regional scales such as MONITO, constitute promising
and feasible observatories of biodiversity changes: they in-
crease our scientific knowledge, facilitate public awareness
of environmental problems, and provide information to policy
makers in order to implement adaptive managements.
Acknowledgements We are very grateful to all participants for believing
in this LTER project and Badopting^plants. Their enthusiasm in this
adventure is our inspiration to keep going. We thank P. Errea for assis-
tance with herbarium databases, P. Bravo and P. Sánchez for field assis-
tance, M. Pizarro for making our life easier with the network database,
and B. Valero and L. Hoppe for linguistic corrections. We are very grate-
ful to the staff of the Regional Government of Aragón (M. Alcántara, J.
Fauré, D. Guzmán, M. Montes, V. Sanz, E Villagrasa), numerous range
coordinators for facilitating the participation of rangers, as well as C.
Fabregat, D. Goñi, J. Guerrero, S. López, J. Puente, and G. Sanz, for
helping with the location of some populations. Two anonymous re-
viewers, T. Dirnböck and C. Reyer provided many suggestions to im-
prove the manuscript.
Funding information The study was funded by RESECOM (European
project LIFE12 NAT/ES/000180) and also DYNBIO (OAPN Project,
Ref. 1656) and PERDIVER (BBVA Foundation).
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... 12% "( . . . enrollment in a scientific program and potential for increasing knowledge are common motivations)" [73] ...
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... • Esta participación mediante programas de voluntariado requiere procesos de aprendizaje, la supervisión de expertos y la dinamización activa de grupos de trabajo (García et al. 2019). Hay una persona dinamizadora (nido de nuevos puestos de trabajo y dinamización sostenible de personal cualificado en territorios alejados de los núcleos científicos) / No es necesario. ...
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Aquest llibre conté els articles i resums derivats de les comunicacions i pòsters presentats al XII Col·loqui Internacional de Botànica Pirenaica‐Cantàbrica celebrat a Girona del 3 al 5 de juliol de 2019. L’ordre seguit en els articles, és el de presentació durant el congres. També s’han afegit la conferencia inaugural del Dr. Pèlachs, titulada “El papel de la geografía histórica ambiental en la conservación del paisaje de alta montaña” i el guió de la sortida que es va realitzar als Pirineus orientals. https://www.udg.edu/ca/viu/Serveis-Universitaris/Llibres-i-revistes-UdG/cataleg/detall?ID=2227
... Pipan et al. (2018) present an overview of LTER in cave ecosystems, conceptualizing and prioritizing LTER for these rarely studied habitats. García et al. (2018) report on the emerging field of citizen science and show how it can help in detecting mountain biodiversity trends in Spain. Last but not least, Swemmer et al. (2018) elucidate socio-ecological drivers and responses in relation to the sustainability of fuelwood harvesting to meet the energy needs of a resource-poor community in an African semi-arid savanna ecosystem. ...
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Long-term ecological research (LTER) has a strong foundation in the fields of biogeosciences and ecosystem research with infrastructures established in the nineteenth (e.g., 1891—Plön, Germany; 1840—Rothamsted, England) and twentieth centuries (e.g., 1906—Lunz, Austria; 1925—Trout Lake Station, WI, USA; 1955—Hubbard Brook, NH, USA; 1960—Solling, Germany). Over time, it has been repeatedly shown that the long-term study of processes has the potential to significantly improve ecological understanding at the ecosystem or larger scales. The international network of LTER sites (ILTER) was established in 1993 and included 28 countries by the turn of the millennium. The geographical spread of LTER sites across the globe has significantly increased since then, and by 2016, 44 countries have established formal LTER programs with approximately 800 LTER sites and 70 Long-term Socio-ecological Research (LTSER) platforms as part of the international network. Stimulated by the World Summit on Sustainable Development and the UN Convention on Biodiversity, research topics at ILTER sites have diversified considerably. Scientists started to address societal processes driving environmental change, as well as feedbacks of environmental changes on society. Furthermore, biodiversity research became an intrinsic part of LTER in many countries initializing the establishment of research infrastructures in ecosystems not yet included (e.g., caves, marine habitats). In October 2016, the ILTER Open Science Meeting in the Kruger National Park, South Africa, gave an impressive overview of the diversity of LTER across the globe today. With this special issue, we aim to present the broad range of research currently conducted across the ILTER network with a collection of papers from different continents and with research topics both classical to LTER and emerging fields of contemporary LTER.
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Globally, hundreds of thousands of rangers patrol protected areas every day. The data they collect have immense potential for monitoring biodiversity and threats to it. Technologies like SMART (Spatial Monitoring and Reporting Tool), which facilitate the management of ranger‐collected data, have enhanced this potential. However, based on our experience across diverse use cases and geographies, we have found that ranger‐based monitoring is often implemented without a clear plan for how the data will inform management and without critical evaluation of whether the data are reliable enough to meet specific monitoring goals. Here we distill six key lessons and present a decision framework to guide funders, governments, protected area managers, and NGOs toward more effective use of ranger‐based monitoring for protected area management and suggest when alternative monitoring approaches may add value. Essential considerations include the welfare and motivation of rangers, biases in patrol coverage and detectability, the capacity to analyze data, and the buy‐in of those tasked with using the data to inform management decisions. When implemented well, ranger‐based monitoring can help improve conservation outcomes through evaluating management interventions, more efficient deployment of limited law enforcement budgets to optimize the deterrence of illegal activities, and basic ecological monitoring.
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It is commonly argued that, despite the tremendous resonance Citizen Science (CS) has shown in recent years, there is still lack of understanding of important aspects defining citizens’ participation and engagement in CS initiatives. While CS initiatives could provide a vehicle to foster forms of participation contributing to the democratization of science, there is still limited attention paid to the “Citizen” component of the Citizen Science term. For the purpose of this work, we systematically reviewed the available literature for empirical studies in respect to citizens’ participation in environmental and nature-based CS initiatives established during the last two decades, using the PRISMA methodology. The participatory facet of the retrieved 119 CS initiatives was analysed on the basis of: (a) exclusion and inclusion demographic factors, (b) CS models and practices, (c) facilitators and constraints of citizen’s participation, and (d) environmental citizenship. Our findings show that the majority of the CS initiatives did not place restrictions on gender participation; however, we have identified that mostly highly educated adults participated in the reviewed initiatives. In addition, most of the CS initiatives reported in the literature were situated in the EU and USA, were mostly limited to the local scale, and primarily followed the contributory model. Academic institutions were found to coordinate the majority of the CS initiatives examined. By using digital technologies, academic scientists were able to control and increase data quality, as well as to engage a broader audience, even though they were mostly treating volunteers as “data collectors”, desiring their long-term engagement. Therefore, it will be of CS benefit to be better aligned with the mentality and needs of citizens. In this direction CS initiatives should trigger citizens’ learning gains and interpersonal/social benefits and personal, environmental, and social motivations, but also to shift their goals towards contributing to science and citizens’ connection with nature. On the other hand, there is a need to overcome any design and implementation barriers, and to enhance democratization through a more participative engagement of active and aware citizens, thus promoting environmental citizenship.
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Long‐term monitoring of biodiversity is a fundamental part of environmental management, and Citizen Science (CS) approaches are increasing their contribution to such endeavour. CS plant monitoring programmes, however, almost exclusively report on the species presence, which can be used to detect changes in distribution or occupancy areas, but not to assess their local extinction risk. To anticipate the collapse of local populations, we need information on population sizes, trends, temporal fluctuations and threats. This is particularly important in the case of priority species (threatened, endangered and those that need special protection). Here we describe the working protocol of the ‘Adopt a plant’ programme, a collaborative network that is currently monitoring 332 populations of 204 plant taxa (threatened, of community interest, common, rare and habitat indicators) across a heterogeneous landscape in NE Spain. Coordinated by scientists, participants estimate population sizes, record disturbances and follow scientifically rigorous sampling methods to track plant abundances year after year in fixed representative areas within populations. Two simple indices are estimated from that information: the overall trend (mean population abundance change, as percentage; PAch) and temporal fluctuations (standard deviation of annual changes; PAchsd). The potential of this ongoing high‐quality dataset is demonstrated through the analysis of 242 populations monitored over 3–10 years. Stability is the dominant trend (mean PAch: +0.14%), with priority species having similar PAch and lower PAchsd than non‐priority ones. Regardless of the priority status, small populations performed worse than large ones. Only 8% of studied populations faced direct human threats. Synthesis and applications. The ‘Adopt a plant’ collaborative monitoring programme was launched in NE of Spain to produce standardized indices of abundance change and other early‐warning signals of concern or risk of population collapse. Such information is crucial to report the conservation status of threatened plants, and plants of Community interest (Habitats Directive). By analysing hundreds of populations, we found that priority plants experienced few threats and did not perform worse than non‐priority ones. This unexpected finding evidences the importance of gathering massive demographic information to refine conservation priorities and to achieve a more comprehensive assessment of flora's vulnerability.
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This chapter discusses the design and deployment of a citizen science application to inventory iconic medicinal non-timber forest products in the wild, such as black cohosh, ramps, and Bloodroot. The application is called PlantShoe (a pun on ‘Gumshoe’) and is used on mobile devices to collect data in the field about forest medicinal plants and their growing conditions. The users’ data is fed into a database, which they can manage, study, and share. Plantshoe data is a part of a larger regional community and consortium which is collecting information about the ecology and distribution of medicinal forest plants. Such analyses can help forest farmers and wild stewards in their processes of site selection and management of these valuable botanicals. We describe our usability engineering in the development of the PlantShoe application and enumerate key design tradeoffs we encountered. Thus, the design decisions and results of PlantShoe provide rich material for the design of future technology on the trail.
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Este manual sintetiza y describe métodos científicos para realizar seguimientos de diferentes especies de plantas, con el fin de estimar tendencias temporales en la abundancia.
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Traditional land-use decline in Mediterranean mountains is translating into extensive forest recovery and the loose of “cultural landscapes”. In this context, the management of semi-natural ecosystems plays a fundamental role for the future preservation of species and processes, particularly in protected areas, and managers need rigorous information for an integrative interpretation of the long-term and complex effects of land cover replacement. Here we analyze changes in the land cover structure of the Ordesa and Monte Perdido National Park and its peripheral protection zone, by comparing 7 types of patches from aerial photographs taken in 1956 and 2015. Then, we discuss how this affected landscape diversity and two kinds of potential vulnerable plants. We found higher changes in the unprotected than protected areas, concentrated below the treeline in both cases, as a result of forest densification and strong reduction of anthropic and unvegetated areas. Total edge of patches decreased, as well as the number of patches, whereas mean patch size increased, indicating that patches merged and ecotones reduced. Shannon diversity index of the landscape decreased too, confirming a simplification of the system. Most Pyrenean endemic plants and threatened ones occur either on stable grasslands over the treeline, “winner” forests, or as rocky specialist irrespective of the land cover class. Therefore, past landscape changes do not seem to have affected them negatively, and forest expansion could also benefit several plants and tree-dominated communities at the south limit of distribution (Abies alba, Fagus sylvatica, Pinus uncinata). Landscape simplification, however, translates into plant diversity reduction too, which could be slowed down by creating or keeping small open patches inside matrices of forest. Maximization of plant diversity would require in this case some human perturbation, but at lower intensity than in the far past, in order to preserve large stands of old forests too.
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Global change effects on biodiversity and human wellbeing call for improved long-termenvironmental data as a basis for science, policy and decision making, including increased interoperability, multifunctionality, and harmonization. Based on the example of two global initiatives, the International Long-Term Ecological Research (ILTER) network and theGroup on Earth Observations Biodiversity ObservationNetwork (GEO BON),we propose merging the frameworks behind these initiatives, namely ecosystem integrity and essential biodiversity variables, to serve as an improved guideline for future site-based long-term research and monitoring in terrestrial, freshwater and coastal ecosystems. We derive a list of specific recommendations of what and how to measure at a monitoring site and call for an integration of sites into co-located site networks across individual monitoring initiatives, and centered on ecosystems. This facilitates the generation of linked comprehensive ecosystem monitoring data, supports synergies in the use of costly infrastructures, fosters cross-initiative research and provides a template for collaboration beyond the ILTER and GEO BON communities.
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Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a ‘Big Data’ approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence-only or presence–absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi-source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter- or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi-source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA-based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals.
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To meet collective obligations towards biodiversity conservation and monitoring, it is essential that the world's governments and non-governmental organisations as well as the research community tap all possible sources of data and information, including new, fast-growing sources such as citizen science (CS), in which volunteers participate in some or all aspects of environmental assessments. Through compilation of a database on CS and community-based monitoring (CBM, a subset of CS) programs, we assess where contributions from CS and CBM are significant and where opportunities for growth exist. We use the Essential Biodiversity Variable framework to describe the range of biodiversity data needed to track progress towards global biodiversity targets, and we assess strengths and gaps in geographical and taxonomic coverage. Our results show that existing CS and CBM data particularly provide large-scale data on species distribution and population abundance, species traits such as phenology, and ecosystem function variables such as primary and secondary productivity. Only birds, Lepidoptera and plants are monitored at scale. Most CS schemes are found in Europe, North America, South Africa, India, and Australia. We then explore what can be learned from successful CS/CBM programs that would facilitate the scaling up of current efforts, how existing strengths in data coverage can be better exploited, and the strategies that could maximise the synergies between CS/CBM and other approaches for monitoring biodiversity, in particular from remote sensing. More and better targeted funding will be needed, if CS/CBM programs are to contribute further to international biodiversity monitoring.
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Volunteered geographical information (VGI) and citizen science have become important sources data for much scientific research. In the domain of land cover, crowdsourcing can provide a high temporal resolution data to support different analyses of landscape processes. However, the scientists may have little control over what gets recorded by the crowd, providing a potential source of error and uncertainty. This study compared analyses of crowdsourced land cover data that were contributed by different groups, based on nationality (labelled Gondor and Non-Gondor) and on domain experience (labelled Expert and Non-Expert). The analyses used a geographically weighted model to generate maps of land cover and compared the maps generated by the different groups. The results highlight the differences between the maps how specific land cover classes were under- and over-estimated. As crowdsourced data and citizen science are increasingly used to replace data collected under the designed experiment, this paper highlights the importance of considering between group variations and their impacts on the results of analyses. Critically, differences in the way that landscape features are conceptualised by different groups of contributors need to be considered when using crowdsourced data in formal scientific analyses. The discussion considers the potential for variation in crowdsourced data, the relativist nature of land cover and suggests a number of areas for future research. The key finding is that the veracity of citizen science data is not the critical issue per se. Rather, it is important to consider the impacts of differences in the semantics, affordances and functions associated with landscape features held by different groups of crowdsourced data contributors.
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The number of collaborative initiatives between scientists and volunteers (i.e., citizen science) is increasing across many research fields. The promise of societal transformation together with scientific breakthroughs contributes to the current popularity of citizen science (CS) in the policy domain. We examined the transformative capacity of citizen science in particular learning through environmental CS as conservation tool. We reviewed the CS and social-learning literature and examined 14 conservation projects across Europe that involved collaborative CS. We also developed a template that can be used to explore learning arrangements (i.e., learning events and materials) in CS projects and to explain how the desired outcomes can be achieved through CS learning. We found that recent studies aiming to define CS for analytical purposes often fail to improve the conceptual clarity of CS; CS programs may have transformative potential, especially for the development of individual skills, but such transformation is not necessarily occurring at the organizational and institutional levels; empirical evidence on simple learning outcomes, but the assertion of transformative effects of CS learning is often based on assumptions rather than empirical observation; and it is unanimous that learning in CS is considered important, but in practice it often goes unreported or unevaluated. In conclusion, we point to the need for reliable and transparent measurement of transformative effects for democratization of knowledge production. This article is protected by copyright. All rights reserved.
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Interest in citizen science has been increasing rapidly, although the reviews available to date have not clearly outlined the links between the long-established practice of recording plant species' distributions for local and national atlases, or other recording projects, and the gradual development of more structured monitoring schemes that also rely on volunteer effort. We provide a review of volunteer-based plant monitoring in Britain and Ireland, with a particular focus on the contributions of expert volunteers working with biological recording schemes and natural history societies; in particular, we highlight projects and practices that have improved the quality of data collected. Although the monitoring of plant distributions at larger scales has led to numerous insights into floristic change and its causes, these activities have also led to the recognition that knowledge of species' abundances at finer-scales often provides a more powerful means of detecting and interpreting change. In the UK, this has led to the development of a new, abundance-based 'National Plant Monitoring Scheme'. We outline this new structured scheme, and review some of the design considerations that have been made during its development. New monitoring projects require a clear justification, and the launch of a new scheme is also an opportune moment to review whether some basic assumptions about the collection of monitoring data can withstand scrutiny. A distinction is often made between monitoring that is focused on answering particular, focused questions, and that which is more generally seeking to detect changes; for example, in species' distributions or abundances. Therefore, we also review the justification for such general 'surveillance' approaches to the monitoring of biodiversity, and place this in the context of volunteer-based initiatives. We conclude that data collected by biological recorders working within atlas or monitoring scheme frameworks will continue to produce datasets that are highly valued by governments, scientists, and the volunteers themselves.
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Over the past 20 years, thousands of citizen science projects engaging millions of participants in collecting and/or processing data have sprung up around the world. Here we review documented outcomes from four categories of citizen science projects which are defined by the nature of the activities in which their participants engage - Data Collection, Data Processing, Curriculum-based, and Community Science. We find strong evidence that scientific outcomes of citizen science are well documented, particularly for Data Collection and Data Processing projects. We find limited but growing evidence that citizen science projects achieve participant gains in knowledge about science knowledge and process, increase public awareness of the diversity of scientific research, and provide deeper meaning to participants' hobbies. We also find some evidence that citizen science can contribute positively to social well-being by influencing the questions that are being addressed and by giving people a voice in local environmental decision making. While not all citizen science projects are intended to achieve a greater degree of public understanding of science, social change, or improved science -society relationships, those projects that do require effort and resources in four main categories: (1) project design, (2) outcomes measurement, (3) engagement of new audiences, and (4) new directions for research.
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People have been recording wildlife for centuries and the resulting datasets lead to important scientific research. The Biological Records Centre (BRC), established in 1964, is a national focus for terrestrial and freshwater species recording in the United Kingdom (UK). BRC works with the voluntary recording community (i.e. a mutualistic symbiosis) through support of national recording schemes (i.e. ‘citizen science’, but unlike most citizen science it is volunteer led) and adds value to the data through analysis and reporting. Biological recording represents a diverse range of activities, involving an estimated 70 000 people annually in the UK, from expert volunteers undertaking systematic monitoring to mass participation recording. It is an invaluable monitoring tool because the datasets are long term, have large geographic extent and are taxonomically diverse (85 taxonomic groups). It supports a diverse range of outputs, e.g. atlases showing national distributions (12 127 species from over 40 taxonomic groups) and quantified trends (1636 species). BRC pioneers the use of technology for data capture (online portals and smartphone apps) and verification (including automated verification) through customisable, inter-operable database systems to facilitate efficient data flow. We are confident that biological recording has a bright future with benefits for people, science, and nature.
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Biological recording is in essence a very simple concept in which a record is the report of a species at a physical location at a certain time. The collation of these records into a dataset is a powerful approach to addressing large-scale questions about biodiversity change. Records are collected by volunteers at times and places that suit them, leading to a variety of biases: uneven sampling over space and time, uneven sampling effort per visit and uneven detectability. These need to be controlled for in statistical analyses that use biological records. In particular, the data are ‘presence-only’, and lack information on the sampling protocol or intensity. Submitting ‘complete lists’ of all the species seen is one potential solution because the data can be treated as ‘presence–absence’ and detectability of each species can be statistically modelled. The corollary of bias is that records vary in their ‘information content’. The information content is a measure of how much an individual record, or collection of records, contributes to reducing uncertainty in a parameter of interest. The information content of biological records varies, depending on the question to which the data are being applied. We consider a set of hypothetical ‘syndromes’ of recording behaviour, each of which is characterized by different information content. We demonstrate how these concepts can be used to support the growth of a particular type of recording behaviour. Approaches to recording are rapidly changing, especially with the growth of mass participation citizen science. We discuss how these developments present a range of challenges and opportunities for biological recording in the future. © 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, ●●, ●●–●●.