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Pragmatic methods to assess the status of biodiversity at multiple scales are required to support conservation decision-making. At the intersection of several major biogeographic zones, Bolivia has extraordinary potential to develop a monitoring strategy aligned with the objectives of the Group on Earth Observations Biodiversity Observation Network (GEO BON). Bolivia, a GEO Observer since 2005, is already working on the adequacy of national earth observations towards the objectives of the Global Earth Observation System of Systems (GEOSS). However, biodiversity is still an underrepresented component in this initiative. The integration of biodiversity into Bolivia’s GEO framework would confirm the need for a country level biodiversity monitoring strategy, fundamental to assess the progress towards the 2020 Aichi targets. Here we analyse and discuss two aspects of the process of developing such a strategy: (1) identification of taxonomic, temporal and spatial coverage of biodiversity data to detect both availability and gaps; and (2) evaluation of issues related to the acquisition, integration and analyses of multi-scale and multi-temporal biodiversity datasets. Our efforts resulted in the most comprehensive biodiversity database for the country of Bolivia, containing 648,534 records for 27,534 species referenced in time and space that account for 92.5% of the species previously reported for the country. We capitalise this information into recommendations for the implementation of the Bolivian Biodiversity Observation Network that will help ensure that biodiversity is sustained as the country continues on its path of development.
Taxonomic representativity. Number of species from the integrated database (black) compared to number of species in previous studies (grey) from well-known taxonomic groups: fish (J. Sarmiento pers. com.), amphibians (De la Riva and Reichle 201410. De la Riva, I., and S. Reichle. 2014. “Diversity and Conservation of the Amphibians of Bolivia.” Herpetological Monographs 28 (1): 46–65.10.1655/HERPMONOGRAPHS-D-13-00009View all references), reptiles (Aguirre, Aguayo, and Balderrama 20091. Aguirre, L., R. Aguayo, and J. Balderrama. 2009. Libro rojo de la fauna silvestre de vertebrados de Bolivia [The Red Book of Vertebrates in Bolivia]. La Paz, Bolivia: Ministerio de Medio Ambiente y Agua.View all references), birds (S. Herzog pers. com.), mammals (Peñaranda and Simonetti 201534. Peñaranda, D., and J. Simonetti. 2015. “Predicting and Setting Conservation Priorities for Bolivian Mammals Based on Biological Correlates of the Risk of Decline.” Conservation Biology 29 (3): 834–843.View all references), bryophytes (Churchill, Sanjines-Asturizaga, and Aldana 20096. Churchill, S., N. Sanjines-Asturizaga, and C. Aldana. 2009. Catálogo de las briofitas de Bolivia: diversidad, distribución y ecología [Catalog of Bryophytes of Bolivia: Diversity, Distribution and Ecology]. Santa Cruz, Bolivia: La Rosa.View all references) and vascular plants (Jørgensen, Nee, and Beck 201523. Jørgensen, P., M. Nee, and S. Beck. 2015. Catálogo de las Plantas Vasculares de Bolivia [Catalog of the vascular plants of Bolivia]. vol. 127. St. Loius, Missouri: Missouri Botanical Garden Press, St. Louis.View all references).
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Challenges and opportunities for the Bolivian
Biodiversity Observation Network
Miguel Fernándezabc, Laetitia M. Navarroa, Amira Apaza-Quevedoad, Silvia C. Gallegosd,
Alexandra Marquesa, Carlos Zambrana-Torrelioe, Florian Wolfa, Healy Hamiltonf, Alvaro
J. Aguilar-Kiriging, Luis F. Aguirreh, Marcela Alveari, James Apariciog, Lilian Apaza-
Vargasj, Gabriel Arellanok, Eric Armijol, Nataly Ascarrunzm, Soraya Barrerag, Stephan G.
Beckd, Héctor Cabrera-Condarcon, Consuelo Campos-Villanuevad, Leslie Cayolad, N. Paola
Flores-Saldanao, Alfredo F. Fuentesd, M. Carolina García-Linop, M. Isabel Gómezg, Yara S.
Higuerasq, Michael Kesslerr, Juan Carlos Ledezmas, J. Miguel Limachig, Ramiro P. Lópezd,
M. Isabel Lozat, Manuel J. Macíak, Rosa I. Menesesu, Tatiana B. Mirandad, A. Bruno Miranda-
Calleg, R. Fernando Molina-Rodriguezv, Mónica Moraes R.d, M. Isabel Moya-Diazg, Mauricio
Ocampog, Humberto L. Perotto-Baldiviesow, Oscar Platad, Steffen Reichlex, Kathia Riveroaa,
Renate Seideld, Liliana Soriaaa, Marcos F. Terány, Marisol Toledom, F. Santiago Zenteno-Ruizd
& Henrique Miguel Pereiraaz
a German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig,
Germany
b Department of Integrative Biology, University of California, Berkeley, CA, USA
c Instituto de Ecología, Universidad Mayor de San Andrés, La Paz, Bolivia
d Herbario Nacional de Bolivia, Instituto de Ecología, Universidad Mayor de San Andrés, La
Paz, Bolivia
e EcoHealth Alliance, New York, NY, USA
f NatureServe, Arlington, VA, USA
g Colección Boliviana de Fauna, Museo Nacional de Historia Natural–Instituto de Ecología, La
Paz, Bolivia
h Centro de Biodiversidad y Genética, Facultad de Ciencias y Tecnología, Universidad Mayor
de San Simón, Cochambamba, Bolivia
i Institute for Biodiversity Science and Sustainability, California Academy of Sciences, San
Francisco, CA, USA
j Food and Agriculture Organization of the United Nations-Bolivia, La Paz, Bolivia
k Departamento de Biología, Universidad Autónoma de Madrid, Madrid, Spain
l Investigador Independiente, Santa Cruz, Bolivia
m Instituto Boliviano de Investigación Forestal, Universidad Autónoma Gabriel René Moreno,
Santa Cruz, Bolivia
n Servicio Nacional de Áreas Protegidas, Ministerio de Medio Ambiente y Agua, La Paz,
Bolivia
o Society for Conservation Biology – Bolivia Chapter, La Paz, Bolivia
p Departamento de Botánica, Facultad de Ciencias Naturales y Oceanográficas, Universidad
de Concepción, Concepción, Chile
q Instituto de Biodiversidad BIORENA, Universidad de San Francisco Xavier de Chuquisaca,
Sucre, Bolivia
r Institute of Systematic Botany, University of Zurich, Zurich, Switzerland
s Conservacion Internacional, La Paz, Bolivia
t Department of Biology, University of Missouri, St. Louis, MO, USA
u Herbario Nacional de Bolivia, Museo Nacional de Historia Natural, La Paz, Bolivia
v GEOBOLIVIA, Vicepresidencia del Estado Plurinacional de Bolivia, La Paz, Bolivia
w Caesar Kleberg Wildlife Research Institute, Texas A and M University--Kingsville,
Kingsville, TX, USA
x Investigador Indepediente, Santa Cruz, Bolivia
y Asociación Boliviana para la Investigación y Conservación de Ecosistemas Andino
Amazónicos, La Paz, Bolivia
z CIBIO/InBIO, Vairão, Portugal
aa Museo de Historia Natural Noel Kempff Mercado, Universidad Autónoma Gabriel Rene
Moreno, Santa Cruz, Bolivia
Published online: 17 Aug 2015.
To cite this article: Miguel Fernández, Laetitia M. Navarro, Amira Apaza-Quevedo, Silvia C. Gallegos, Alexandra Marques,
Carlos Zambrana-Torrelio, Florian Wolf, Healy Hamilton, Alvaro J. Aguilar-Kirigin, Luis F. Aguirre, Marcela Alvear, James
Aparicio, Lilian Apaza-Vargas, Gabriel Arellano, Eric Armijo, Nataly Ascarrunz, Soraya Barrera, Stephan G. Beck, Héctor
Cabrera-Condarco, Consuelo Campos-Villanueva, Leslie Cayola, N. Paola Flores-Saldana, Alfredo F. Fuentes, M. Carolina
García-Lino, M. Isabel Gómez, Yara S. Higueras, Michael Kessler, Juan Carlos Ledezma, J. Miguel Limachi, Ramiro P.
López, M. Isabel Loza, Manuel J. Macía, Rosa I. Meneses, Tatiana B. Miranda, A. Bruno Miranda-Calle, R. Fernando Molina-
Rodriguez, Mónica Moraes R., M. Isabel Moya-Diaz, Mauricio Ocampo, Humberto L. Perotto-Baldivieso, Oscar Plata, Steffen
Reichle, Kathia Rivero, Renate Seidel, Liliana Soria, Marcos F. Terán, Marisol Toledo, F. Santiago Zenteno-Ruiz & Henrique
Miguel Pereira (2015): Challenges and opportunities for the Bolivian Biodiversity Observation Network, Biodiversity, DOI:
10.1080/14888386.2015.1068710
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Challenges and opportunities for the Bolivian Biodiversity Observation Network
Miguel Fernández
a,b,c
*, Laetitia M. Navarro
a
, Amira Apaza-Quevedo
a,d
, Silvia C. Gallegos
d
, Alexandra Marques
a
,
Carlos Zambrana-Torrelio
e
, Florian Wolf
a
, Healy Hamilton
f
, Alvaro J. Aguilar-Kirigin
g
, Luis F. Aguirre
h
, Marcela
Alvear
i
, James Aparicio
g
, Lilian Apaza-Vargas
j
, Gabriel Arellano
k
, Eric Armijo
l
, Nataly Ascarrunz
m
, Soraya Barrera
g
,
Stephan G. Beck
d
, Héctor Cabrera-Condarco
n
, Consuelo Campos-Villanueva
d
, Leslie Cayola
d
, N. Paola Flores-Saldana
o
,
Alfredo F. Fuentes
d
, M. Carolina García-Lino
p
, M. Isabel Gómez
g
, Yara S. Higueras
q
, Michael Kessler
r
, Juan Carlos
Ledezma
s
, J. Miguel Limachi
g
, Ramiro P. López
d
, M. Isabel Loza
t
, Manuel J. Macía
k
, Rosa I. Meneses
u
, Tatiana B.
Miranda
d
, A. Bruno Miranda-Calle
g
, R. Fernando Molina-Rodriguez
v
, Mónica Moraes R.
d
, M. Isabel Moya-Diaz
g
,
Mauricio Ocampo
g
, Humberto L. Perotto-Baldivieso
w
, Oscar Plata
d
, Steffen Reichle
x
, Kathia Rivero
aa
, Renate Seidel
d
,
Liliana Soria
aa
, Marcos F. Terán
y
, Marisol Toledo
m
, F. Santiago Zenteno-Ruiz
d
and Henrique Miguel Pereira
a,z
a
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany;
b
Department of Integrative Biology, University of California, Berkeley, CA, USA;
c
Instituto de Ecología, Universidad Mayor de San Andrés, La Paz, Bolivia;
d
Herbario Nacional de Bolivia, Instituto de Ecología, Universidad Mayor de San Andrés, La Paz, Bolivia;
e
EcoHealth Alliance, New York, NY, USA;
f
NatureServe, Arlington, VA, USA;
g
Colección Boliviana de Fauna, Museo Nacional de Historia NaturalInstituto de Ecología, La Paz, Bolivia;
h
Centro de Biodiversidad y Genética, Facultad de Ciencias y Tecnología, Universidad Mayor de San Simón, Cochambamba, Bolivia;
i
Institute for Biodiversity Science and Sustainability, California Academy of Sciences, San Francisco, CA, USA;
j
Food and Agriculture Organization of the United Nations-Bolivia, La Paz, Bolivia;
k
Departamento de Biología, Universidad Autónoma de Madrid, Madrid, Spain;
l
Investigador Independiente, Santa Cruz, Bolivia;
m
Instituto Boliviano de Investigación Forestal, Universidad Autónoma Gabriel René Moreno, Santa Cruz, Bolivia;
n
Servicio Nacional de Áreas Protegidas, Ministerio de Medio Ambiente y Agua, La Paz, Bolivia;
o
Society for Conservation Biology Bolivia Chapter, La Paz, Bolivia;
p
Departamento de Botánica, Facultad de Ciencias Naturales y Oceanográcas, Universidad de Concepción, Concepción, Chile;
q
Instituto de Biodiversidad BIORENA, Universidad de San Francisco Xavier de Chuquisaca, Sucre, Bolivia;
r
Institute of Systematic Botany, University of Zurich, Zurich, Switzerland;
s
Conservacion Internacional, La Paz, Bolivia;
t
Department of Biology, University of Missouri, St. Louis, MO, USA;
u
Herbario Nacional de Bolivia, Museo Nacional de Historia Natural, La Paz, Bolivia;
v
GEOBOLIVIA, Vicepresidencia del Estado Plurinacional de Bolivia, La Paz, Bolivia;
w
Caesar Kleberg Wildlife Research Institute, Texas A and M UniversityKingsville, Kingsville, TX, USA;
x
Investigador Indepediente, Santa Cruz, Bolivia;
y
Asociación Boliviana para la Investigación y Conservación de Ecosistemas Andino Amazónicos, La Paz, Bolivia;
z
CIBIO/InBIO, Vairão, Portugal;
aa
Museo de Historia Natural Noel Kempff Mercado, Universidad Autónoma Gabriel Rene Moreno, Santa Cruz, Bolivia
(Received 23 April 2015; nal version received 30 June 2015)
Pragmatic methods to assess the status of biodiversity at multiple scales are required to support conservation
decision-making. At the intersection of several major biogeographic zones, Bolivia has extraordinary potential to develop
a monitoring strategy aligned with the objectives of the Group on Earth Observations Biodiversity Observation Network
(GEO BON). Bolivia, a GEO Observer since 2005, is already working on the adequacy of national earth observations
towards the objectives of the Global Earth Observation System of Systems (GEOSS). However, biodiversity is still an
underrepresented component in this initiative. The integration of biodiversity into Bolivias GEO framework would con-
rm the need for a country level biodiversity monitoring strategy, fundamental to assess the progress towards the 2020
Aichi targets. Here we analyse and discuss two aspects of the process of developing such a strategy: (1) identication of
taxonomic, temporal and spatial coverage of biodiversity data to detect both availability and gaps; and (2) evaluation of
issues related to the acquisition, integration and analyses of multi-scale and multi-temporal biodiversity datasets. Our
efforts resulted in the most comprehensive biodiversity database for the country of Bolivia, containing 648,534 records
*Corresponding author. Email: miguel.fernandez.trigoso@gmail.com
© 2015 Biodiversity Conservancy International
BIODIVERSITY, 2015
http://dx.doi.org/10.1080/14888386.2015.1068710
Downloaded by [University of Leipzig] at 04:19 17 August 2015
for 27,534 species referenced in time and space that account for 92.5% of the species previously reported for the coun-
try. We capitalise this information into recommendations for the implementation of the Bolivian Biodiversity Observation
Network that will help ensure that biodiversity is sustained as the country continues on its path of development.
Keywords: Bolivia; biodiversity; big data integration; monitoring; baseline; GEO BON
Introduction
In the last two decades, aided by increased connectivity
and easy access to data capturing devices and analytical
tools, societies are witnessing a change in the paradigm
on how to deal with information. We are rapidly moving
from data control schemes to more collaboration, integra-
tion and sharing (Wallis, Rolando, and Borgman 2013).
Within the biodiversity community, there is a plethora of
initiatives dedicated to collecting data on multiple dimen-
sions of biodiversity and at different spatial scales and
resolutions such as the Living Planet Index (Collen et al.
2009), the Map of Life (Jetz, McPherson, and Guralnick
2012) and the PREDICTS database (Hudson et al.
2014). More data could lead to improved knowledge on
how biodiversity is distributed in space and how it is
changing over time; both components are essential for
better informed policy-making and more accurate scenar-
ios for conservation and management (Pereira et al.
2010; Schmeller et al. 2015).
However, quantity does not mean quality (Maldonado
et al. 2015). One of the main problems is that not all
biodiversity data was collected using a sampling design
appropriate for monitoring in space and time. For
instance, in the last global biodiversity assessment
(Tittensor et al. 2014) only 55 out of 163 potential indica-
tors were selected to measure progress towards conserva-
tion targets. Spatial coverage and availability of temporal
series were amongst ve criteria used to determine the
indicators suitability to measure change and/or response
to change (Tittensor et al. 2014). Thus urgent harmonisa-
tion and standardisation of methods, protocols and quality
control measures are needed (Pereira et al. 2013).
However, while ontological alignment (i.e. correspon-
dence among concepts) is a priority in data rich regions,
this is not as important in data decient regions where a
baseline for monitoring change might not even exist.
Incidentally, data decient regions also happen to occur
not only in areas of high conservation value but also in
areas where the highest degrees of degradation occur
(Collen et al. 2008; Pereira, Navarro, and Martins 2012),
making the strategies to dene monitoring priorities even
more urgent (Hardisty and Roberts 2013).
The country of Bolivia, at the heart of South America,
is a perfect example where high levels of biodiversity,
decient information and high degrees of degradation
overlap. Baseline information even for the most well-
known and charismatic species data is lacking (Vié,
Hilton-Taylor, and Stuart 2009). For example, from the
389 mammalian species described for Bolivia, 106 species
have stable populations while 84 species are declining
(Tarifa and Aguirre 2009). Yet, for the remaining 199
mammalian species, the status of their populations is
unknown since there is simply not enough information to
estimate or infer a trend (Peñaranda and Simonetti 2015).
Similarly, for the 266 species of amphibians reported for
Bolivia, available data on possible threats or declines is
mostly anecdotal, and long-term well-funded programmes
that monitor populations and putative declines are
nonexistent (De la Riva and Reichle 2014).
One of the most pressing environmental concerns of
Bolivia is deforestation for large-scale mechanised
agriculture, small-scale agriculture and cattle ranching
(Killeen et al. 2007; Müller et al. 2012). Although defor-
estation rates were considered moderate for decades,
relative to other countries in the region, the situation has
changed dramatically in the rst decade of the twenty-
rst century. Independently of whether we look at the
lower estimates (0.49%; FAO 2010) or the higher esti-
mates of deforestation (0.66%; Cuéllar et al. 2012),
Bolivia is currently placed in the top 10 list of countries
with the highest annual rates of forest loss in the world
(FAO 2010), with potentially dramatic consequences for
biodiversity (Pinto-Ledezma and Rivero Mamani 2014).
Thus, establishing monitoring schemes in, for instance,
deforested and control areas would be an essential step
towards the assessment of consequences of human-
induced land-use change for biodiversity in the country.
To provide a baseline against which to measure biodi-
versity change in countries with similar co-occurring
conditions to Bolivia, centralisation, systematisation,
archiving and curation of biodiversity data is urgently
needed. The Essential Biodiversity Variables framework
concept proposed by Pereira et al. (2013) provides an
attractive framework for the development of national and
sub-national initiatives. These monitoring initiatives can
provide the knowledge base to assess the targets for 2020
set by the Convention on Biological Diversity (CBD).
As the rst step towards building a monitoring scheme
for biodiversity in Bolivia, we evaluate two key aspects in
establishing a baseline: rst, the identication of taxo-
nomic, temporal and spatial data availability to detect both
data gaps and opportunities for long-term monitoring; and
second, the evaluation of issues related to the acquisition,
integration and analyses of multi-scale biodiversity data-
sets. We capitalise this information into recommendations
for the implementation of the Bolivian Biodiversity
2 M. FERNÁNDEZ ET AL.
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Observation Network, consistent with the essential
biodiversity variables framework.
Methods
Biodiversity observation: data acquisition and
integration
We evaluated the taxonomic, spatial and temporal cover-
age of biodiversity observations in Bolivia from the year
1789 until 2015. We used, as the main sources of informa-
tion on species occurrence, data derived from specimens
hosted in natural history museums and herbaria located
inside and outside Bolivia (i.e. Herbario Nacional de Boli-
via (LPB) and Colección Boliviana de Fauna (CBF)
Universidad Mayor de San Andres, Museo de Historia
Natural Noel Kempff Mercado (MHNNKM) Universi-
dad Autónoma Gabriel Rene Moreno, Missouri Botanical
Garden (MOBOT), California Academy of Sciences
(CAS), Museum of Vertebrate Zoology at Berkeley
(MVZ), Smithsonian Institution National Museum of
Natural History (NMNH), Museum National dHistoire
Naturelle de Paris (MNHN), Global Biodiversity Informa-
tion Facility (GBIF)); we also included expert observa-
tions databases from other research institutions (e.g.
Instituto Boliviano de Investigación Forestal (IBIF), Wild-
life Conservation Society (WCS) and NatureServe).
Biodiversity observations that fullled the following crite-
ria: (1) terrestrial macrobiotic organisms identied at the
species level, (2) with georeferenced occurrence informa-
tion precise to minutes in latitude and longitude and (3)
that contained information about the date of the collection
event, were integrated into a single database using Post-
greSQL, an open-source database software.
Once all the records were integrated into the data-
base, we applied a series of consistent quality control
routines on the data. These included a verication of the
types of input values and alignment of elds to con-
trolled vocabularies and standards (i.e. Darwin Core;
Wieczorek et al. 2012). We also checked the taxonomic
accuracy and redundancy of the database by aligning the
scientic identication of each record against a reference
taxonomic backbone. For plants we used the Taxonomic
Name Resolution Service v.3.2. (TNRS; Boyle et al.
2013) and for animals and fungi we used the Integrated
Taxonomic Information System database (ITIS 2010).
After applying this systematic quality checks, we
replaced synonymies by most current taxonomy and
removed the invalid records from the database. We then
transformed all the geographic coordinates to decimal
degrees and using PostGIS, a spatial database extender,
and we imported the database into a Geographic
Information System (ArcGIS v.10.2).
Then, we checked if the coordinates of each record
were aligned with the country (IDE-EPB 2015): we
applied a buffer to the country boundaries and removed
all records that fell at distances larger than 2.5 km of the
ofcial international boundary of the country.
Taxonomic data coverage
From the integrated database, we rst counted the num-
ber of species in taxonomic groups from which we were
able to nd previously published accounts (i.e. sh,
amphibians, reptiles, birds, mammals, bryophytes and
vascular plants) and then compared the results against
our numbers. Secondly, using a national ecoregional
classication based on Ibisch and Merida (2013), which
provides a more tailored and accurate representation for
Bolivia than the global classication from Olson and
Dinerstein (2002), we counted the number of records
and species that occur within each ecoregion. Based on
the results of these analyses we calculated the ratio of
the number of records to the number of species, and
reported averaged values per ecoregion for animals and
plants. A ratio close to one is an indicator that more
species in the group are known from one single record.
Spatial and temporal data coverage
We created a grid of 5 × 5 km
2
, and counted the number
of unique species that occur in each cell. We dened the
spatial resolution of the grid based on the average error
estimate of the retrospectively georeferenced observa-
tions (~2.5 km) using the point-radius method developed
by Wieczorek, Guo, and Hijmans (2004), a well know
and accepted method that has been incorporated in proto-
cols, geospatial guidelines and software (e.g. BioGeo-
mancer, SpeciesGeoCoder, ModEco). We also counted
the number of unique years represented in each 25 km
2
cell, to understand the temporal distribution of the data
across space. Finally, to evaluate the distribution of
records across time in our database, we plotted the num-
ber of records and the number of species collected for
each year. In order to compare national and regional pat-
terns, we repeated these exercises at the ecoregion level.
Results
From a total of 965,896 biodiversity observations, our
data integration efforts resulted in a database referenced
at the taxonomic, spatial and temporal level that contains
648,534 records from 27,534 species for the country of
Bolivia (Figure 1), From this database, 93.7% of the
records were obtained from vouchered specimens from
natural history museums and herbaria and the remaining
6.3% of the records were originated from direct expert
observations. Also, 55.4% of the records were obtained
from institutions hosted outside Bolivia and 44.6% from
institutions hosted inside the country.
Our database contains 92.5% of the total number of
species reported for Bolivia when compared with
BIODIVERSITY 3
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species accounts and checklists from previous studies
(Figure 2) and 95.8% of the species included in the
IUCN Red List of Threatened Species (Categories: CR,
EN and VU), providing a good coverage of the number
of species for the most well-known taxonomic groups
including amphibians, birds and mammals. Our results
also indicate that 34.5% of all the records fall within a
protected area with an IUCN protection status, which
indicates that biodiversity observations have been
sampled slightly more inside protected areas given
that 25% of the total area of the country is under
protection.
Using ratios, we found that in average plants have 10
times less records per species than animals (Table 1).
For animals, the ecoregion with the lowest number of
records relative to the number of species was the
Prepuna, with an average of two records per species; the
larger number of records relative to the number of spe-
cies were from Sudoeste de la Amazonia and Gran
Chaco with an average of 21.3 and 22.7 records per
species, respectively (Table 1). For plants, the ecoregions
with the lowest number of records relative to species
were Lago Titicaca,Prepuna and Puna Sureña, with
an average of 1.6, 2.2 and 2.7 records per species,
Figure 1. Georeferenced biodiversity observations for Bolivia, compiled from records in local and international natural history
museums, herbaria and direct observations reported by experts.
4 M. FERNÁNDEZ ET AL.
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respectively; and the largest number of records relative
to species were from Yungas and Sudoeste de la
Amazonia, with an average of 10 and 13 records per
species, respectively (Table 1).
From a species richness perspective, at the resolu-
tion of 25 km
2
, the number of species recorded per
pixel ranged from 1 to 1278 with a mean of 27 spe-
cies (Figure 3). The highest numbers of species were
recorded in Yungas (Figures 3and 4). From a spatial
perspective the ecoregions that were better sampled are:
Bosques Secos Interandinos (46.1% of the total area
sampled), Yungas (43.1%) and Bosque Tucumano
Boliviano (39.6%; Table 1and Figure 4). Conversely
the ecoregions that were least sampled were Puna
Sureña (8.5%), Prepuna (12.3%) and Gran Chaco
(15.3%; Table 1and Figure 4).
Figure 2. Taxonomic representativity. Number of species from the integrated database (black) compared to number of species in
previous studies (grey) from well-known taxonomic groups: sh (J. Sarmiento pers. com.), amphibians (De la Riva and Reichle
2014), reptiles (Aguirre, Aguayo, and Balderrama 2009), birds (S. Herzog pers. com.), mammals (Peñaranda and Simonetti 2015),
bryophytes (Churchill, Sanjines-Asturizaga, and Aldana 2009) and vascular plants (Jørgensen, Nee, and Beck 2015).
Table 1. Number of records vs. number of species.
Plants Animals
Code Ecoregion Records Species Ratio Records Species Ratio
Area sampled
(%)
PUSU Puna Sur 3092 1128 2.74 4645 312 14.89 8.54
PREP Prepuna 660 289 2.28 108 53 2.04 12.3
GRCH Gran Chaco 9682 3169 3.06 31,523 1388 22.71 15.37
SAIN Sabanas Inundables 11,073 3335 3.32 34,110 2251 15.15 15.59
BSCH Bosque Seco Chiquitano 11,630 3139 3.71 17,213 1306 13.18 15.61
CERR Cerrado 14,310 4212 3.40 14,189 1352 10.49 15.68
SAMZ Sudoeste de la Amazonia 126,373 9387 13.46 85,877 4026 21.33 22.24
PUNO Puna Norte 21,088 4104 5.14 11,366 701 16.21 24.83
LGTK Lago Titicaca 527 323 1.63 1650 168 9.82 27.89
CHSE Chaco Serrano 7151 2222 3.22 9984 908 11.00 32.04
BTBO Bosque Tucumano
Boliviano
17,435 3821 4.56 9112 1077 8.46 39.65
YUNG Yungas 112,198 10,466 10.69 33,915 2203 15.39 43.16
BSIN Bosques Secos Interandinos 36,574 6639 5.51 23,049 1476 15.62 46.15
Notes: Number of records, species and the ratio between them, calculated per ecoregion for animals and plants. Ratio values larger
than one indicate multiple records for a particular species.
BIODIVERSITY 5
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The number of non-consecutive years recorded in
each pixel range from 1 to 90 with a mean value of
3 years (Figure 5). The ecoregions with more years
recorded are: Bosques Secos Interandinos and Sudoeste
de la Amazonia (Figure 5). The oldest record in our
database was collected in the Gran Chaco ecoregion in
the year 1789 (Figure 6). Ecoregions where collection
efforts started early in time are Gran Chaco,Bosque
Seco Interandino and Sudoeste de la Amazonia; whereas
more recent collection efforts are from the Prepuna and
Chaco Serrano. In general, for all ecoregions, the sam-
pling effort increased in the late 1970s with a marked
peak in the number of records and species between 1995
and 2005 (Figure 6).
Discussion
When investigating biodiversity response to global
change and human pressure, it is important to make a
distinction between biodiversity lossand biodiversity
alterations(Pereira, Navarro, and Martins 2012). Deter-
mining a baseline and monitoring changes are essential
to distinguish the spatial scale of extinction (i.e. from
local to global), to identify potential range shifts, and to
Figure 3. Number of unique species calculated based on a grid of 5 × 5 km
2
.
6 M. FERNÁNDEZ ET AL.
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measure changes in communities. In this paper, we pro-
vide a state of the art regarding Bolivias knowledge on
biodiversity data and show how collaborative initiatives
can help to overcome major resource limitations, and
move forward with the creation of a baseline that can
serve as the foundation for a biodiversity monitoring
strategy in Bolivia.
Our results, by no means are complete. Specic taxo-
nomic groups where our database falls short when com-
pared with previous species accounts are sh, reptiles and
bryophytes (Figure 2). As a consequence, this database
will require to be constantly and dynamically updated as
new information becomes available if the goal is that it
serves as a reference against which biodiversity loss and
alterations could be monitored. Along these lines, taxo-
nomically accurate and spatially well-distributed data col-
lected at short time intervals are essential to produce
reliable scenarios of biodiversity change (Fernandez
2013) that can be used to inform issues such as climate
change, food security and public health.
Several limitations preclude biodiversity data integra-
tion in Bolivia. They can be grouped under four main
non-exclusive categories: dispersion, availability, com-
pleteness and alignment. Data dispersion means that
Figure 4. Spatial coverage of biodiversity observations per ecoregion based on a grid of 5 × 5 km
2
.
BIODIVERSITY 7
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information is dispersed across multiple researchers and
research institutions, each with different data standards
and data sharing policies. Data availability is related to
how much of the biodiversity information is actually
readily available for smooth integration into a database
system. In most of the cases this is proportional to the
amount of information that has been digitised in a
museum or herbarium. However, not all the information
available in digital form is complete. Old specimens
without GPS coordinates are a good example of this,
requiring additional work to retrospectively georeference
the textual descriptions of the places where they were
collected. Finally, if the data is in one place, available
and complete, it might still require considerable amount
of ontological alignment due to issues that have to do
with changes in the taxonomy, differences in database
standards and different reference vocabularies.
Despite the limitations mentioned above, the present
effort represents the most comprehensive biodiversity
database for the country of Bolivia built with one
specic goal in mind: the creation of a baseline that can
provide an objective basis for directing future collection
efforts that can serve to monitor change. With more than
half million records, the present database represents a
Figure 5. Temporal data coverage of biodiversity observations, calculated based on the number of non-contiguous years represented
in each 5 × 5 km
2
cell.
8 M. FERNÁNDEZ ET AL.
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Number of records per ecoregion
Number of records
0
10000
20000
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20000
0
10000
20000
0
10000
20000
0
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0
10000
20000
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10000
20000
BSCH BSIN BTBO CERR CHSE GRCH LGTK PREP PUNO PUSU SAIN SAMZ YUNG
ECOREGION
1800
1825
1850
1875
1900
1925
1950
1975
2000
Year
Number of species per ecoregion
Number of species
0
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BSCH BSIN BTBO CERR CHSE GRCH LGTK PREP PUNO PUSU SAIN SAMZ YUNG
ECOREGION
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1825
1850
1875
1900
1925
1950
1975
2000
Year
Bolivian biodiversity observations over time
Number of
recordsspecies
0
10000
20000
30000
40000
50000
0
10000
20000
30000
40000
50000
1800
1810
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1830
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1930
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1970
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1990
2000
2010
Year
Figure 6. Bolivian biodiversity observations over time. Top panel: total number of records and species over time. Bottom-left and
-right panel: number of records and species, respectively, per ecoregion over time.
BIODIVERSITY 9
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good approximation of the state of knowledge of
biodiversity in Bolivia, corresponding to 92.5% of the
species reported in the literature. In this sense, the high
representativity of our results provides a good foundation
to integrate, analyze and interpret the information in
taxonomic, spatial and temporal dimensions.
Taxonomic dimension
Biodiversity research in Bolivia is unevenly distributed
across the tree of life. Traditionally, the focus of biodiver-
sity research has been on highly emblematic and charis-
matic groups such as mammals and birds (e.g. Butchart
et al. 2005; Collen et al. 2009). Much less effort has been
placed in other groups such as reptiles, amphibians, plants
and insects; and the present database for Bolivia is not the
exception. The main reason behind this is the lack of
nancial, technical and human resources enhanced by a
worldwide downward trend in available funding for natu-
ral history assessments. Biodiversity institutions in Boli-
via, despite some isolated efforts, do not have yet a
working coordinated strategy and a stable source of fund-
ing that allows the long-term storage, maintenance, cura-
tion and expansion of biodiversity data holdings and
inventories. Infrastructure and technology devoted to the
collection and identication of specimens in general is
either insufcient or extremely limited and with serious
problems in maintenance in the best of the cases. More-
over there are almost no incentives for training local tax-
onomists in these underrepresented groups, which is
worsen by the lack of employment opportunities for
young biodiversity researchers inside the country. Finally
the lack of a clear national strategy reverberates in the
absence of an evaluation mechanism towards a national
monitoring strategy that includes these taxonomically
underrepresented groups (MMAyA 2014).
Spatial dimension
Current knowledge on biodiversity in Bolivia is spatially
biased. With still vast unexplored regions, the scarcity in
number of records for the: Gran Chaco,Bosque Seco
Chiquitano and Sabanas Inundables del Norte ecore-
gions (Figure 4) might be attributed to the low accessi-
bility and low human population density of these areas
(Ibisch, Chive, et al. 2003; Larrea-Alcázar et al. 2011);
for the Puna Sureña this might also be explained by the
intrinsic low diversity of this ecoregion (Table 1). The
relatively high number of records in time and space in
the Yungas and Bosques Secos Interandinos ecoregions
might be the result of the research focus that these two
regions have received over the years (Ibisch, Gerkmann,
et al. 2003). Particularly, the highly diverse Yungas
ecoregion is also one of the most threatened areas in
Bolivia (Kessler 2001), highlighting the importance and
opportunity to focus conservation as well as monitoring
efforts in the area. Our results also indicate that the Su-
doeste de la Amazonia and the Yungas ecoregions
include high levels of biodiversity, which is in line with
previous estimates where the two ecoregions and the
transition between them are listed as high priority
ecosystems due to the high species diversity and high
number of endemics, respectively (Araujo et al. 2010;
Moraes R. et al. 2014; Müller et al. 2003; Young 2007).
Temporal dimension
Data collection efforts in Bolivia have not been continu-
ous and data shows that there has been a steady decline
in the last decade. Our analysis revealed two periods of
time where there was a considerable increase in the num-
ber of biodiversity observations collected per year. The
rst one corresponds to the establishment of the Instituto
de Ecología in the late 1970s, a pioneer institution in the
eld of ecology and systematics in Bolivia (Baudoin and
España 1997; Ibisch 2003a), followed closely by other
research oriented universities and institutions. The sec-
ond increase (between 1995 and 2005) coincides with
the adoption of the CBD by Bolivia in 1994, and the
endorsement of the National Strategy for the Conserva-
tion of Biodiversity in 2002 (MMAyA 2014). Also as a
result of the international funding community focus on
biodiversity and biodiversity research, this decade was
characterised by high nancial support from national and
international institutions (FAN 2009). The observed
decrease in collection efforts in the last decade might be
attributed to two interlinked elements: rst, the change
of direction and focus in governmental policies from
biodiversity to management; and second, the decrease in
previously available funding opportunities for biodiver-
sity research in the country.
Biodiversity as a key for development
Bolivia acknowledges the importance of biodiversity for
its development. For example, in Bolivias Poverty
Reduction Strategy (IMF 2001), it is stated that biodi-
versity could come to represent an increase of about
10% in the Gross Domestic Product (GDP), if activities
are developed in ethnic and ecotourism, mitigation of cli-
mate change and biodiversity services relating to biotech-
nology, ecological products, and others(IMF 2001).
More recently, the country has dened ve major axis of
action regarding biodiversity, including linking conserva-
tion with both human development and economic poten-
tial, while highlighting the need to establish, inter alia,
legal, institutional, and political conditions to implement
a sustainable model of biodiversity development
(MMAyA 2014). However, realising the full potential of
biodiversity for development requires knowledge on the
status and trends.
10 M. FERNÁNDEZ ET AL.
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Bolivia identied several limitations to the conserva-
tion of biodiversity in its National Biodiversity Strategy
and Action Plan (MDSP 2001), being the most impor-
tant the lack of scientic knowledge on natural
regeneration, growth rates, population viabilities, the
absence of a denition of priorities for scientic
investigation resulting from a lack of coordination
between academics for in situ and ex situ conservation
and an insufcient and decient transfer of technology
(MDSP 2001). Since then, and as shown in the results,
the sampling and monitoring effort, and thus knowl-
edge, have stalled with some exceptions: (1) the Madidi
Project, which is a collaboration among the Missouri
Botanical Garden (MBG) and the Herbario Nacional de
Bolivia (LPB), since 2002 it has been monitoring 50
permanent plots of 1 ha in the Yungas ecoregion over
an elevation gradient of ~3000 m; (2) the Instituto Boli-
viano de Investigación Forestal (IBIF), a network of
permanent plots distributed across the Sudoeste de la
Amazonia and Bosque Seco Chiquitano ecoregions also
generating biodiversity information since 2002; and (3)
the Global Observation Research Initiative in Alpine
Environments (GLORIA) monitoring the Puna with
permanent plots since 2006, along an elevational gradi-
ent of 1000 m.
To date, no harmonised observation system that
delivers regular and timely data on biodiversity change
exists in Bolivia that supports all levels of governance,
management and decision-making. Despite the progress
in biodiversity data integration and mobilisation ((e.g.
Centro Geoespacial para la Biodiversidad de Bolivia
(CGB; Perotto-Baldivieso et al. 2012)), Centro Digital
de Recursos Naturales de Bolivia (CDRNB), it is still
difcult for research institutions or even country level
research infrastructures to develop, implement and
maintain the platforms required to retrieve, share and
leverage data investments through collaboration, integra-
tion and harmonisation. Only with the establishment of
a well-funded national biodiversity monitoring strategy
that can leverage individual efforts into a true collab-
oration and data sharing infrastructure, Bolivia will be
able to take full advantage of the new data-intensive
science that results from information integration needed
to inform urgent pressing issues such as global change.
Acknowledgements
We are extremely grateful to all the Bolivian and foreign
researchers funding agencies that contributed to the knowledge
of biodiversity in Bolivia over the past fty years; without their
efforts this type of work would not have been possible.
Disclosure statement
All authors declare no conict of interests.
Funding
MF, AAQ, LN, AM, FW and HMP were supported by the
German Centre for Integrative Biodiversity Research (iDiv)
Halle-Jena-Leipzig funded by the German Research Foundation
(FZT 118). The rest of the co-authors were supported by their
own institutions.
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BIODIVERSITY 13
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... Además, responden al fuerte aumento en la presión sobre el uso de los recursos naturales en los últimos diez años. En conjunto, los incendios constituyen una de las amenazas directas más importantes sobre la biodiversidad (Lidema 2010;Ribera 2011;Rodríguez-Montellano 2014;Fernández et al. 2015). ...
... In addition, they respond to the sharp increase in natural resource extraction over the last ten years. Altogether, fires constitute one of the most important direct threats to biodiversity, especially in dry forests (Lidema 2010;Ribera 2011;Rodríguez-Montellano 2014;Fernández et al. 2015). ...
... Este conjunto de esfuerzos, constituyen la más comprensible base de datos sobre biodiversidad nunca antes compilada para Bolivia (Fernández et al. 2015). Sirviendo como base para una estrategia nacional de monitoreo de la biodiversidad, la base de datos contiene hoy más de 1.5 millones de registros que están aumentando aún y que contienen más de 27 000 especies referidas espacial y temporalmente, proveyendo una base fundamental para la evaluación del conocimiento actual sobre la biodiversidad. ...
... Además, responden al fuerte aumento en la presión sobre el uso de los recursos naturales en los últimos diez años. En conjunto, los incendios constituyen una de las amenazas directas más importantes sobre la biodiversidad (Lidema 2010;Ribera 2011;Rodríguez-Montellano 2014;Fernández et al. 2015). ...
... In addition, they respond to the sharp increase in natural resource extraction over the last ten years. Altogether, fires constitute one of the most important direct threats to biodiversity, especially in dry forests (Lidema 2010;Ribera 2011;Rodríguez-Montellano 2014;Fernández et al. 2015). ...
... Este conjunto de esfuerzos, constituyen la más comprensible base de datos sobre biodiversidad nunca antes compilada para Bolivia (Fernández et al. 2015). Sirviendo como base para una estrategia nacional de monitoreo de la biodiversidad, la base de datos contiene hoy más de 1.5 millones de registros que están aumentando aún y que contienen más de 27 000 especies referidas espacial y temporalmente, proveyendo una base fundamental para la evaluación del conocimiento actual sobre la biodiversidad. ...
... La pesca, mediante estrategias apropiadas, podría ayudar a aliviar la pobreza y contribuir al desarrollo sostenible cumpliendo un papel económico importante a nivel familiar (Wiefels 2006, Alho et al. 2012. Sin embargo, los cambios ambientales ejercidos por el ser humano casi siempre afectan negativamente a la biodiversidad, porque, en general, traen como consecuencia el declive de riqueza y diversidad de especies , Pereira et al. 2012, Fernández et al. 2015 En los ríos amazónicos, parte importante de estos impactos se ha debido principalmente a modificaciones provocadas por las represas implementadas con el fin de generar electricidad (Fearnside 2014). ...
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El proyecto Gobernanza e Infraestructura en la Amazonía (GIA) liderado por el Programa de Conservación y Desarrollo Tropical de la Universidad de Florida se estableció en el otoño de 2018 para crear, fortalecer e implementar una Comunidad de Práctica y Aprendizaje (CoP-L) panamazónica. La CoP-L de GIA ha proporcionado un foro para el aprendizaje social y el análisis sobre los desafíos y las estrategias para reducir las amenazas a las áreas protegidas y otras tierras de los proyectos de infraestructura mal planificados. GIA es una red policéntrica de actores clave de organizaciones de base, academia, ONG y el gobierno en Bolivia, Brasil, Colombia y Perú. La red se desarrolló y adaptó a lo largo de los tres años del proyecto. La serie especial presentada aquí, se enfoca en las actividades planificadas y ejecutadas dentro de la CoP-L denominada Mosaico del Alto Madera, que comprende un área binacional entre Bolivia y Brasil que forma parte de la cuenca del Río Madera, que es uno de los afluentes más importantes de la cuenca Amazónica. Después de casi tres años de investigación y ejecución del proyecto GIA, nos sentimos honrados de poder presentar esta serie especial enfocada en la coproducción de conocimientos a través de la investigaciónacción transdisciplinar en la Amazonía, que lleva como título “Investigación Transdisciplinaria Participativa sobre Gobernanza e Infraestructura en la Cuenca Alta del Río Madera (Bolivia – Brasil)”. Esta serie especial comienza con una introducción general sobre el proyecto GIA, además hace una descripción precisa sobre todos los aliados y socios que forman parte del Mosaico del Alto Madera. De la misma forma, logra describir el proceso de planeación, y ejecución de la Investigación Transdisciplinaria. Detallas la conformación de los equipos de investigación, la selección de los estudiantes, el ajuste de las investigaciones, el trabajo de campo, hasta llegar a la conclusión de las investigaciones con una presentación formal en formato de Simposio, donde los estudiantes logran mostrar los resultados de sus investigaciones. Finalmente, logra describir los productos elaborados de las tesis de investigación, productos que han sido socializados y entregados a las comunidades que participaron de la investigación, y también a los aliados y socios. Ya que uno de los objetivos principales, es el de poder democratizar la información, y que los resultados llegan a las comunidades de forma clara, precisa, fácil de entender, sin que pierda el rigor científico-técnico. Posteriormente entramos a la descripción de cada investigación, la cual describimos brevemente a continuación: · Cambio del modo de vida de las familias de la comunidad Cachuela Mamoré (Bolivia) después de la construcción de las hidroeléctricas Jirau y Santo Antonio en el Estado de Rondonia (Brasil), donde el objetivo principal fue el de Describir los cambios del modo de vida de las familias de las comunidades campesinas de Cachuela Mamoré (Beni-Bolivia) y Puerto Consuelo Área II (Pando-Bolivia), posterior a la construcción de las hidroeléctricas de Jirau y Santo Antonio. · Caracterización de la pesca en la comunidad de Cachuela Esperanza (Beni, Bolivia), donde el objetivo principal fue el de caracterizar la actividad pesquera en la cuenca baja del rio Beni y explorar los posibles efectos de las represas hidroeléctricas, construidas en la cuenca media del rio Madeira, sobre peces migratorios, la pesca comercial y la pesca de subsistencia. · Ictiofauna de la Comunidad Puerto Consuelo II (Pando, Bolivia) y características de la pesca, donde se estudió la ictiofauna en la comunidad Puerto Consuelo II, ubicada a orillas del rio Beni (Pando, Bolivia), con el objetivo de conocer las especies de peces y las características de la pesca de la región. · El impacto socioeconómico de las hidroeléctricas sobre la pesca en tres comunidades ribereñas (región Alto Madera, Bolivia), en estudio tomó como muestra tres comunidades ribereñas de la región del Alto Madera en Bolivia (Cachuela Esperanza, Villa Bella y Puerto Consuelo I). El análisis económico fue enfocado directamente, basado en encuestas a pescadores, en el costo de producción, el margen de utilidad promedio y los gastos directos e indirectos que surgen por la actividad pesquera. · Percepción de las poblaciones locales sobre la degradación del bosque, previa a la posible construcción de una hidroeléctrica en el rio Beni, Bolivia, este trabajo documenta la percepción de las poblaciones locales de la región amazónica de Bolivia, sobre la posible degradación del bosque que conllevaría la construcción de la represa hidroeléctrica Cachuela Esperanza en el Río Beni, en Bolivia. Después de describir los casos de investigación, entramos a una parte muy importante dentro del proceso de investigación, que es el análisis de alianza entre actores e impulso a la investigación para la coconstrucción de conocimiento y las lecciones aprendidas en torno a las universidades Amazónicas. Este análisis incluye los procesos de impulso, capacitación, y apoyo a estudiantes de las universidades Amazónicas enfocado en la realización de investigaciones transdisciplinarias y participativas como parte de su formación académica. Finalmente, se dan lineamientos enfocados en la construcción de una agenda de conocimiento conjunta priorizando futuras investigaciones para la región. Se recomienda continuar con el esquema de investigación transdisciplinaria participativa, ya que los diferentes actores que participan de las investigaciones salen fortalecidos y son capaces de ver y sentir otras realidades, expanden su visión sobre el contexto local, y fortalecen sus capacidades. Estamos seguros de que esta serie especial enfocada en la coproducción de conocimientos a través de la investigación-acción transdisciplinar en la Amazonía aporta insumos fundamentales para el análisis de trabajos transdisciplinarios, y aboga por el fortalecimiento de una red transdisciplinaria sólida que permita que los aliados contiendan y logren avanzar en un objetivo común. Asimismo, tenemos la seguridad de que la generación de conocimiento participativo permite tener resultados reales y ajustados al contexto de cada área estudiada, el Alto Madera en particular, y de la Amazonía en general.
... Although thinning supports the recovery of radial growth after drought events, it hardly affects the resistance to drought and can lead to higher evaporation in the short term due to higher wind exposure (Sohn, Hartig, et al., 2016). In addition, the magnitude of short-and medium-term resistance, recovery and resilience of radial growth was affected by (Sohn, Saha, et al., 2016), whereas thinning did not improve leaf-level efficiency and intrinsic water use efficiency (Fernández et al., 2015;Sohn, Saha, et al., 2016). Under certain conditions, the competition for water and water stress levels in forest stands can be reduced by thinning (Giuggiola et al., 2013;Sohn, Saha, et al., 2016). ...
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1. Forest management influences a variety of ecosystem structures and processes relevant to meso-and microclimatic regulation, but little research has been done on how forest management can mitigate the negative effects of climate change on forest ecosystems. 2. We studied the temperature regulation capacity during the two Central European extreme summers in 2018 and 2019 in Scots pine plantations and European beech forests with different management-related structural characteristics. 3. We found that the maximum temperature was higher when more trees were cut and canopy was more open. Logging 100 trees per hectare increased maximum temperature by 0.21-0.34 K at ground level and by 0.09-0.17 K in 1.3 m above ground. Opening the forest canopy by 10% significantly increased T max, measured 1.3 m above ground by 0.46 K (including pine and beech stands) and 0.35 K (only pine stands). At ground level, T max increased by 0.53 K for the model including pine and beech stands and by 0.41 K in pure pine stands. Relative temperature cooling capacity decreased with increasing wood harvest activities, with below average values in 2018 (and 2019) when more than 656 (and 867) trees per hectare were felled. In the pine forests studied, the relative temperature buffering capacity 1.3 m above ground was lower than average values for all sample plots when canopy cover was below 82%. In both study years, mean maximum temperature measured at ground level and in 1.3 m was highest in a pine-dominated sample plots with relatively low stand volume (177 m 3 ha −1) and 9 K lower in a sample plot with relatively high stock volumes of Fagus sylvatica (>565 m 3 ha −1). During the hottest day in 2019, the difference in temperature peaks was more than 13 K for pine-dominated sample plots with relatively dense (72%) and low (46%) canopy cover. 4. Structural forest characteristics influenced by forest management significantly affect microclimatic conditions and therefore ecosystem vulnerability to climate change. We advocate keeping the canopy as dense as possible (at least 80%) by maintaining sufficient overgrowth and by supporting deciduous trees that provide effective shade.
... According to [26,30], the highest concentration of plant endemism is registered in the Andean mountains, where both the Yungas (humid forests) and inter-Andean dry forests are found. Moreover, the major record of scientific collections and knowledge comes from the eastern slopes of the Andes from the NW toward the center of the country, where Bolivia's greatest biodiversity is higher [31]. Also the distribution of endemic palms (Arecaceae) is associated with the eastern Andes [32]. ...
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The inventory of Bolivia's vascular plants lists 2402 endemic species (ca. 20% of 12,339 of native flora). Among angiosperms, there are 2263 species from 124 families and 641 genera, whereas among pteridophytes, there are 139 species from 16 families and 29 genera. Seven families with the greatest number of endemic species are Orchidaceae (418), Asteraceae (246), Bromeliaceae (147), Cactaceae (127), Poaceae (92), and Piperaceae (81). Cleistocactus and Puya have 14 and 55 endemic species, respectively, so representing 82.3 and 84.6% of the species in these genera. Bolivia's endemic species show distribution patterns associated with past geological events, orographic dynamics (of the Andes and in the Cerrado), as well as areas of diversification. Dry xeric and humid regions host local and regional endemics in specific families and biogeographic regions of high conservation importance. Humid montane forests in the Yungas and dry inter-Andean valleys are rich in endemic species with 51 and 22% of the total recorded in the respective regions. Nevertheless, there are still many lesser known geographical areas that may generate new information in the short and medium term. Only 165 endemic species (6.9%) have been evaluated for their conservation status following IUCN categories with 49% assessed as endangered (EN).
... Novel biodiversity monitoring systems are being developed to systematically assess change for multiple taxa over large extents (Scholes et al. 2008(Scholes et al. , 2012Fern andez et al. 2015). To support these systems, several groups have developed novel approaches to monitor species, communities and ecosystems over time using globally consistent metrics of change (Butchart et al. 2010;Jetz et al. 2012;Metzger et al. 2013;Pereira et al. 2013). ...
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Human activity and land‐use change are dramatically altering the sizes, geographical distributions and functioning of biological populations worldwide, with tremendous consequences for human well‐being. Yet our ability to measure, monitor and forecast biodiversity change – crucial to addressing it – remains limited. Biodiversity monitoring systems are being developed to improve this capacity by deriving metrics of change from an array of in situ data (e.g. field plots or species occurrence records) and Earth observations (EO; e.g. satellite or airborne imagery). However, there are few ecologically based frameworks for integrating these data into meaningful metrics of biodiversity change. Here, I describe how concepts of pattern and scale in ecology could be used to design such a framework. I review three core topics: the role of scale in measuring and modelling biodiversity patterns with EO, scale‐dependent challenges linking in situ and EO data and opportunities to apply concepts of pattern and scale to EO to improve biodiversity mapping. From this analysis emerges an actionable approach for measuring, monitoring and forecasting biodiversity change, highlighting key opportunities to establish EO as the backbone of global‐scale, science‐driven conservation.
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We present an analysis of the biodiversity knowledge–implementation continuum in one of the most biologically and culturally diverse regions on the planet, South America. This chapter focuses on interactions between data producers and users, synergies and gaps in information flow between data production and decision-making processes, drawing on a survey of stakeholders from the Andean-Amazon countries.
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