Using learning networks to understand complex systems: A case study of biological, geophysical and social research in the Amazon
Developing high-quality scientific research will be most effective if research communities with diverse skills and interests are able to share information and knowledge, are aware of the major challenges across disciplines, and can exploit economies of scale to provide robust answers and better inform policy. We evaluate opportunities and challenges facing the development of a more interactive research environment by developing an interdisciplinary synthesis of research on a single geographic region. We focus on the Amazon as it is of enormous regional and global environmental importance and faces a highly uncertain future. To take stock of existing knowledge and provide a framework for analysis we present a set of mini-reviews from fourteen different areas of research, encompassing taxonomy, biodiversity, biogeography, vegetation dynamics, landscape ecology, earth-atmosphere interactions, ecosystem processes, fire, deforestation dynamics, hydrology, hunting, conservation planning, livelihoods, and payments for ecosystem services. Each review highlights the current state of knowledge and identifies research priorities, including major challenges and opportunities. We show that while substantial progress is being made across many areas of scientific research, our understanding of specific issues is often dependent on knowledge from other disciplines. Accelerating the acquisition of reliable and contextualized knowledge about the fate of complex pristine and modified ecosystems is partly dependent on our ability to exploit economies of scale in shared resources and technical expertise, recognise and make explicit interconnections and feedbacks among sub-disciplines, increase the temporal and spatial scale of existing studies, and 458 Jos Barlow and others improve the dissemination of scientific findings to policy makers and society at large. Enhancing interaction among research efforts is vital if we are to make the most of limited funds and overcome the challenges posed by addressing large-scale interdisciplinary questions. Bringing together a diverse scientific community with a single geographic focus can help increase awareness of research questions both within and among disciplines, and reveal the opportunities that may exist for advancing acquisition of reliable knowledge. This approach could be useful for a variety of globally important scientific questions.
Biol. Rev. (2011), 86, pp. 457–474. 457
Using learning networks to understand
complex systems: a case study of biological,
geophysical and social research in the Amazon
, Liana Anderson
, Luiz E. O. C. Aragao
, Ted R. Feldpausch
, Emanuel Gloor
, Anthony Hall
, William Milliken
, Mark Mulligan
, Toby Pennington
, Rosa Maria Roman-Cuesta
, Joseph A. Tobias
Toby A. Gardner
Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, SL5 7PY, UK
Environmental Change Institute, School of Geography and the Environment, University of Oxford, South Parks Road, OX1 3QY, Oxford, UK
School of Geography, University of Exeter, Amory Building, Rennes Drive, Exeter, EX4 4RJ, UK
School of Geography, University of Leeds, Leeds, LS2 9JT, UK
School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK
Department of Social Policy, London School of Economics, Houghton Street, London, WC2A 2AE, UK
Royal Botanic Gardens, Kew, Richmond, Surrey, TW9 3AB, UK
Environmental Monitoring and Modelling Research Group, Department of Geography, King’s College London, Strand, London, WC2R 2LS, UK
Tropical Diversity Section, Royal Botanic Garden Edinburgh, 20a Inverleith Row, Edinburgh, EH3 5LR, UK
School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
Centre of Ecological Research and Forestry Applications (CREAF), Facultat de Ciencies, Universitat Autonoma de Barcelona, 08193,
Bellaterra (Barcelona), Spain
Edward Grey Institute, Department of Zoology, Oxford University, South Parks Road, OX1 3PS, UK
Department of Zoology, University of Cambridge, Downing Street, Cambridge, CB2 3EJ, UK
(Received 6 February 2010; revised 14 July 2010; accepted 5 August 2010)
Developing high-quality scientiﬁc research will be most effective if research communities with diverse skills and interests
are able to share information and knowledge, are aware of the major challenges across disciplines, and can exploit
economies of scale to provide robust answers and better inform policy. We evaluate opportunities and challenges facing
the development of a more interactive research environment by developing an interdisciplinary synthesis of research on
a single geographic region. We focus on the Amazon as it is of enormous regional and global environmental importance
and faces a highly uncertain future. To take stock of existing knowledge and provide a framework for analysis
we present a set of mini-reviews from fourteen different areas of research, encompassing taxonomy, biodiversity,
biogeography, vegetation dynamics, landscape ecology, earth-atmosphere interactions, ecosystem processes, ﬁre,
deforestation dynamics, hydrology, hunting, conservation planning, livelihoods, and payments for ecosystem services.
Each review highlights the current state of knowledge and identiﬁes research priorities, including major challenges
and opportunities. We show that while substantial progress is being made across many areas of scientiﬁc research, our
understanding of speciﬁc issues is often dependent on knowledge from other disciplines. Accelerating the acquisition of
reliable and contextualized knowledge about the fate of complex pristine and modiﬁed ecosystems is partly dependent
on our ability to exploit economies of scale in shared resources and technical expertise, recognise and make explicit
interconnections and feedbacks among sub-disciplines, increase the temporal and spatial scale of existing studies, and
* Address for correspondence: E-mail: email@example.com
Biological Reviews 86 (2011) 457–474 © 2010 The Authors. Biological Reviews © 2010 Cambridge Philosophical Society
458 Jos Barlow and others
improve the dissemination of scientiﬁc ﬁndings to policy makers and society at large. Enhancing interaction among
research efforts is vital if we are to make the most of limited funds and overcome the challenges posed by addressing
large-scale interdisciplinary questions. Bringing together a diverse scientiﬁc community with a single geographic focus
can help increase awareness of research questions both within and among disciplines, and reveal the opportunities
that may exist for advancing acquisition of reliable knowledge. This approach could be useful for a variety of globally
important scientiﬁc questions.
Key words: biodiversity, learning networks, interdisciplinary research, deforestation, REDD, degradation, hydrology,
ﬁre, conservation, livelihoods, taxonomy.
I. Introduction ................................................................................................ 458
II. State of existing knowledge and research challenges in amazonian research ............................... 459
(1) Climate and earth-atmosphere interactions ............................................................ 459
(2) Deforestation dynamics and land-use change .......................................................... 459
(3) Amazonian wildﬁres ................................................................................... 460
(4) Water resources and hydrology ........................................................................ 460
(5) Vegetation dynamics ................................................................................... 461
(6) Ecosystem processes ................................................................................... 461
(7) Landscape ecology ..................................................................................... 461
(8) Sampling biodiversity .................................................................................. 462
(9) Plant taxonomy and databases ......................................................................... 462
(10) Speciation and biogeography .......................................................................... 463
(11) Amazonian hunting research .......................................................................... 463
(12) Conservation planning ................................................................................. 463
(13) Livelihoods and governance ........................................................................... 464
(14) Market-based conservation strategies .................................................................. 464
III. Discussion .................................................................................................. 465
(1) Improving research performance by enhancing interaction within scientiﬁc disciplines ................ 465
(a) Problem formulation, research design and analysis ................................................. 465
(b) Sharing data, research protocols and research infrastructure ....................................... 465
(c) Achieving an understanding of scale ................................................................ 466
(d) Keeping up with the cutting edge ................................................................... 466
(e) Enhancing scientiﬁc impact and dissemination ..................................................... 466
(2) Improving research performance by increasing interaction across disciplines .......................... 467
(3) Effective communication provides the basis of an interactive research environment ................... 468
(4) Overcoming barriers to interactive and interdisciplinary research ..................................... 469
(a) Expanding the regional scope ....................................................................... 469
(b) Funding barriers .................................................................................... 469
(c) Researcher behaviour .............................................................................. 469
IV. Conclusions ................................................................................................ 470
V. Acknowledgments .......................................................................................... 470
VI. References .................................................................................................. 470
The global research community is extremely proliﬁc, but
the huge volume of information presents a major challenge
to scientists attempting to keep up with the latest develop-
ments, and to those responsible for developing science-based
policy recommendations. In many cases researchers are sim-
ply unaware of the research that is being conducted in
either their own or parallel disciplines, or are too focused or
busy to make the connections. Moreover, traditional reward
systems in academia can favour practices that result in a
narrow and more assured set of outcomes (e.g. low-risk,
single-discipline research products) that limit the range and
scale of scientiﬁc pursuits and the scope of interdisciplinary
collaboration (Uriarte et al., 2007). This isolation and frag-
mentation process can drive a positive feedback: the more
fragmented academic research becomes, the more challeng-
ing it is to synthesise for newcomers to a ﬁeld, and the greater
the risk that it becomes increasingly inaccessible or inap-
propriate for potential end-users. This can lead to parallel
research initiatives being conducted within the same geo-
graphic region, and a lack of clear incentives for researchers
to interact or learn from one another (Salafsky & Margoluis,
Biological Reviews 86 (2011) 457–474 © 2010 The Authors. Biological Reviews © 2010 Cambridge Philosophical Society
Using learning networks to understand complex systems 459
A more interactive research environment may be
stimulated through the development of learning or research
networks (Salafsky & Margoluis, 1999; Brown & Salafsky,
2004), which could prevent the fragmentation of science and
increase the effectiveness of research. A learning network
(also termed portfolio) is a varyingly formalized structure
for facilitating collaborative learning and action (Brown &
Salafsky, 2004), and ensures that the latest ideas, practical
and technical expertise and research ﬁndings can be readily
exchanged and beneﬁted from. Within a scientiﬁc context,
the delivery of robust and socially relevant knowledge would
be enhanced if research communities with diverse skills
and interests are: (1) able to share new information and
knowledge efﬁciently and rapidly; (2) aware of the major
scientiﬁc challenges that characterize both their own and
other disciplines; and (3) able to draw on this knowledge and
awareness to exploit economies of scale in resources and
expertise, as well as to contribute towards interdisciplinary
Here, we present ﬁndings from a symposium held in
London in 2008 which formed an initial stage in the
development of a learning network for a group of researchers
based within one nation (the United Kingdom) who have a
common interest in the Amazon. This region makes a suitable
case study because it: (1) is of enormous global importance;
(2) faces a highly uncertain future, threatened by both
development pressures and climate change (Lenton et al.,
2008; Malhi et al., 2008; Phillips et al., 2009); and (3) is large
and complex, so that effective and sustainable management
and development of the region depends upon the success
of effective and collaborative research efforts. Moreover,
by focusing on a relatively small research community such
as that based in the UK, it was comparatively easy to
bring together representatives from disparate disciplines. An
obvious next step would be to expand this by including the
many Amazon researchers based elsewhere. However, the
UK-based research community provides an excellent test-
case for this exercise as they target similar funding sources,
are likely to share similar challenges, and there are few
logistical barriers to prevent interaction and communication
The 14 mini-reviews presented herein cover a variety
of scientiﬁc disciplines and areas of research, ranging from
climatology and ecology to economics and social science.
Each review highlights the current state of our knowledge,
and then brieﬂy identiﬁes key gaps in understanding and
major research challenges. While our coverage of individual
disciplines is necessarily concise, the value of this exercise
lies in the juxtaposition of information from a diverse array
of scientiﬁc disciplines within a single forum, allowing an
up-to-date appraisal of current understanding and inter-
connections within and among disciplines. In the discussion
we draw on the groundwork provided by these syntheses
to examine potentially rewarding opportunities and mech-
anisms to facilitate collaborative investigation. This review
and analysis is a ﬁrst and important step in the development
of a more interactive research and learning environment.
II. STATE OF EXISTING KNOWLEDGE AND
RESEARCH CHALLENGES IN AMAZONIAN
(1) Climate and earth-atmosphere interactions
Temperature has increased by approximately 0.25
decade over the Amazon basin during the last 30 years,
levels have risen by approximately 35% compared to
pre-industrial times and surface solar radiation has varied
(Leuenberger, Siegenthaler & Langway, 1992; Wild et al.,
2005). While there has been no signiﬁcant trend in annual
precipitation (Malhi & Wright, 2004), there were widespread
droughts in 1998 and 2005 (Marengo et al., 2008; Phillips
et al., 2009) and dry season intensity may have increased in
southern Amazonia (Li, Fu & Dickinson, 2006).
Correlative evidence suggests soil water balance and its
seasonality to be a main control of vegetation type and
the extent of forests (Woodward, 1987; Malhi et al., 2009a).
Vegetation distribution and extent may also be affected by
temperature-induced changes in plant functioning as well as
by changes in atmospheric CO
level (Lloyd & Farquhar,
2008) and radiation.
There are important vegetation-climate feedbacks, with
early water isotope analyses estimating that approximately
50% of water is recirculated to the atmosphere through
Amazon forest canopies (Salati & Vose, 1984; Shukla,
Nobre & Sellers, 1990). Cox et al. (2000) published results
from the ﬁrst fully coupled climate land vegetation
model and suggested a high likelihood of Amazonian
rainforests converting to savanna under 21
warming. However climate models underlying these results
underestimate today’s Amazon precipitation. Malhi et al.
(2009a) used a heuristic approach to correct for the model
precipitation biases, and suggested that a tendency to
seasonal forest was more likely than a full transition to
savanna, although the latter remained a possibility.
The current main limitations on future Amazon vegetation
predictions include a simplistic representation of vegetation
dynamics, insufﬁcient model resolution (Malhi et al., 2009a),
poor cloud physics representation (D. Parker, personal
communication) and uncertainties in the prediction of large-
scale warming patterns of the tropical Paciﬁc and Atlantic
Oceans (Held et al., 2005).
(2) Deforestation dynamics and land-use change
The Amazon basin is the most active frontier of land cover
change in the world. Historically, government-sponsored
colonisation schemes initiated widespread deforestation in
the Amazon as nations rushed to secure ownership of their
territory and gain access to natural resources (Rudel, 2005).
Although there is signiﬁcant intra-regional variability in the
drivers of land-use change, the majority of deforestation is
currently explained by: (1) the expansion of extensive cattle
ranching and industrial-scale agriculture for an increasingly
global food market, and the associated development of
infrastructure (Pan et al., 2004; Armenteras et al., 2006;
Biological Reviews 86 (2011) 457–474 © 2010 The Authors. Biological Reviews © 2010 Cambridge Philosophical Society
460 Jos Barlow and others
Morton et al., 2006); (2) the small clearings of subsistence
farmers migrating to new forest frontiers (Etter et al., 2006;
Carr, 2009); and (3) logging which can act as a precursor to
outright deforestation (e.g. Asner et al., 2006). The location
of most deforestation is determined by the construction of
new and paving of existing roads, combined with a lack of
strong governance (Soares-Filho et al., 2004; Fearnside & de
Alencastro, 2006). Protected areas, sustainable use reserves
and indigenous lands set spatial limits to deforestation and
largely perform an effective job at slowing the spread of
deforestation across the basin (Nepstad et al., 2006; Oliveira
et al., 2007). In fact, deforestation rates in the Brazilian
Amazon have been decreasing since the last peak in 2004
(Nepstad et al., 2009) and the Brazilian government recently
set a target of 80% reduction in the deforestation rates by
2020 (COP-15 in December 2009, http://www.abin.gov.br).
Developing better predictive models of deforestation will
require: (1) understanding the drivers of deforestation and
subsequent land cover change at appropriate spatial scales;
and (2) predicting the patterns of future road networks
based on social, economic and political drivers. Detecting
deforestation and its drivers in such a diverse region
is challenging, although some methodologies have been
successfully tested for areas with large-scale deforestation
patterns (Anderson et al., 2005; Morton et al., 2006). Attempts
to predict road expansion have improved in recent years
(Arima et al., 2008) although these are yet to be validated and
have suffered from a lack of data on unofﬁcial road networks
ao Jr & Souza Jr, 2006).
(3) Amazonian wildﬁres
Forest degradation (logging, fragmentation) and severe
droughts combine to increase the frequency of ﬁre in
Amazonian forests, which acts as a powerful agent of
tropical forest degradation. Low-intensity ﬁres often lead
to very high levels of tree mortality (up to 50% of trees
≥10 cm diameter) and a signiﬁcant loss of faunal diversity
(including disturbance sensitive forest vertebrates) (Barlow
& Peres, 2004). Fires can also lead to ecosystem instability
and destabilising feedback cycles, as forests that have burned
once are more likely to burn again, with greater effects
on vegetation and biodiversity (Cochrane et al., 1999; but
see Balch et al., 2008 from experimental burns). Recent
research has demonstrated the critical role of rare drought
events led by El Nino Southern Oscillation (ENSO) and
Atlantic Multidecadal Oscilation (AMO) events with related
changes in the Paciﬁc and Atlantic Oceans sea surface
temperature (SST), which increase ﬁre occurrence when
combined with ﬁre-dependent human activities (Alencar,
Nepstad & Diaz, 2006; Arag
ao et al., 2007, 2008). Fire is
considered to be one of the key processes through which
a climate-mediated forest dieback could occur (Barlow
& Peres, 2008; Malhi et al., 2009a).
We still have a relatively poor understanding of the spatial
and temporal variation in the causes and consequences of ﬁre,
and how ﬁres interact with other forms of forest degradation
and across different spatial scales. This information is vital
to predict better the local and global implications of ﬁres,
identify vulnerability, and deﬁne and highlight potential
tipping points where humid tropical forests may no longer
recover. Although some attempts have been made to quantify
ﬁre-mediated changes in vegetation cover (e.g. Thonicke
et al., 2001; Bond, Woodward & Midgley, 2005) and carbon
emissions (DeFries et al., 2008), we are still unable to make
accurate predictions about long-term changes in vegetation
and carbon dynamics in ﬁre-disturbed forests. Key areas of
uncertainty include tree mortality, biodiversity loss, forest
regeneration, the above- and below-ground carbon budget,
feedback cycles, and the socio-economic context of ﬁre use
and management. Remote sensing plays a critical role in any
scaling-up exercises, and accuracy would be vastly improved
through a temporal analysis of ﬁre scars that takes into
account ﬁre intensity, land cover, and the type of ﬁre.
(4) Water resources and hydrology
Estimations of the discharge of the Amazon range from
200,000 to 220,000 m
(Korzun, 1978; Richey, Nobre
& Deser, 1989) up to 280,000 m
representing some 15–16% of all fresh water delivered to
the oceans globally. The river carries less sediment than other
comparable rivers, most of which (80–90%) derives from the
Andean parts of the basin (Goulding, Barthem & Ferreira,
2003). At least ﬁve large dams exist within the basin with a
further nine proposed.
Forest cover is widely assumed to facilitate the
maintenance of high rainfall, ﬂood control, dry season,
environmental ﬂows and water quality (Kaimowitz, 2004).
Loss of forest cover over large spatial scales is thought
to decrease rainfall, though studies have shown rainfall to
decrease in some areas and increase in others and the
impacts to be rather small (Kaimowitz, 2004; ESPA-AA,
2008). Forests are also expected to reduce ﬂooding frequency
but appear to have little impact on the largest and most
destructive events (Bradshaw et al., 2007). The picture is
less clear for the maintenance of dry season ﬂows, where
the outcome depends on the balance between evaporation-
induced ﬂow loss under forests and enhanced baseﬂows
through increased inﬁltration. There is also an important
distinction to be made between lowland and tropical
montane cloud forests in this regard (Bruijnzeel, 2004).
Though a wealth of hydrological and hydro-climatic
studies have been carried out at the plot scale in the Amazon
(e.g. the Large-Scale Biosphere Atmosphere programme
LBA), much less effort has been given to sub-basin and
basin-scale hydrological remote sensing and modelling (but
see Marengo et al., 2001). This is critical to understand
the basin-wide response to land use and climate change.
Early basin-wide studies indicate that the hydrological
impact of climate change may be much greater than that
of land-use change (ESPA-AA, 2008). Similarly there is
a dearth of long-term monitoring sufﬁcient to capture
important variability, including droughts and extreme
events, with the notable exception of initiatives from
ANA (http://www.ana.gov.br/ingles/indexingles.asp), the
Using learning networks to understand complex systems 461
GRDC (http://www.bafg.de/GRDC) and GEMS (http://
www.gemswater.org/). Studies so far have tended to focus
on how hydrological processes respond to large-scale clear-
cut whereas much land-use change is less dramatic and the
hydrological response is likely to be conditioned by the nature
and growth dynamics of the replacement cover.
(5) Vegetation dynamics
Recent comparative studies have revealed that patterns of
carbon storage and dynamics vary strongly among different
upland forests in Amazonia, overturning previous ideas that
different tropical forests function in broadly similar ways.
Western Amazon upland forests have greater above-ground
productivity (Malhi et al., 2004), and tree turnover (Phillips
et al., 2004) but lower above-ground biomass (Baker et al.,
2004b) than forests in central and eastern Amazonia (Arag
et al., 2009; Baker et al., 2009; Pati
no et al., 2009). Edaphic
factors, rather than mean climate, determine these patterns
within forests; both soil chemical properties, particularly
phosphorous concentrations, and physical properties, such
as soil depth, have important roles (Quesada et al., 2009).
In addition, variation in species composition modiﬁes how
soil conditions affect ecosystem properties such as stand-level
biomass estimates (Baker et al., 2004b; Honorio Coronado
et al., 2009) and mortality rates (Chao et al., 2008).
Rates of tree recruitment and mortality, and the stock
of biomass, have increased widely in Amazonian forests in
recent decades (Baker et al., 2004a;Lewiset al., 2004; Phillips
et al., 2004) probably as a result of global environmental
change (Phillips et al., 2008). Understanding the underlying
spatial variation in forest dynamics has been important for
interpreting these changes: increases in tree turnover and
biomass have been largest where tree turnover rates and
productivity were already high, in western Amazonia (Baker
et al., 2004a;Lewiset al., 2004).
Understanding the context of individual sites and regions
is crucial for a correct evaluation of the actual spatial
patterns (Anderson et al., 2009) and will remain important
for interpreting change in Amazonian forests. Such shifts
may be driven by the observed increase in tree turnover rates
or increased drought frequency, predicted by some models
of future climate. For example, a change to a system where
patterns of forest dynamics are more strongly constrained by
water availability would cause abrupt increases in drought-
related tree mortality (Nepstad et al., 2007; Phillips et al.,
2009), decreased tree growth (Baker, Burslem & Swaine,
2003) and could alter the distribution of different forest
typesoverlongertimescales(Malhiet al., 2009a). However,
the many drivers of change and signiﬁcant heterogeneity of
the Amazonian forest make the exact nature of ecological
responses difﬁcult to predict. Long-term monitoring in
multiple sites, studies of the short- and long-term impacts
of disturbance and drought, and close coupling of ﬁeld
data and modelling efforts are the key priorities for
understanding the future vegetation dynamics of Amazonian
(6) Ecosystem processes
While an extensive network of forest inventories had revealed
regional patterns and temporal trends in the functioning and
dynamics of old-growth tropical forests [e.g. the RAINFOR
network (Malhi et al., 2002)], other studies have intensiﬁed
research on the ecosystem ecology of particular sites. One
result has been improved understanding of how the more
obvious facets of a tropical forest stand (biomass, structure,
tree growth and death) relate to the overall carbon cycle of
One intensive approach has been micrometeorological,
through the use of eddy covariance measurements of
the turbulent transfer of carbon dioxide and water, and
detailed automatic weather station data. The pioneering
measurements in Amazonia were in the late 1980s and early
1990s, but the scale of such measurements greatly expanded
under the Brazil-led LBA experiment in Amazonia (Keller
et al., 2004) to around ten research sites in Brazil on forests,
cerrado savannas and agri-pastoral landscapes. These studies
have revealed new insights into how forests respond to daily
and seasonal variation in light and water, and enabled
quantiﬁcation of water ﬂuxes (J.B. Fisher et al., 2009) and
gross photosynthesis (Hutyra et al., 2008). However, they
have proved disappointing for addressing the key question
of the net carbon balance of old-growth forests because of
difﬁculties in accurately quantifying the night-time release
of carbon dioxide in the calm, turbulence-free sub-canopy
space that prevails in tropical forests.
A second intensive approach has examined the carbon
cycle in greater detail at a few key sites, explicitly quantifying
the components of net primary productivity (NPP) and
autotrophic and heterotrophic respiration. These studies
have been conducted by numerous investigators, in particular
through the LBA programme, and were recently compiled
into a single synthesis which showed they were consistent
with independent ﬂux tower and soil gas ﬂux data (Malhi
et al., 2009b). More recently, this approach has been applied
to lowland forest sites in Peru and Colombia, to a fertile terra
preta do indio site (Arag
ao et al., 2009), and to an elevational
transect in the Andes (Girardin et al., in press). These studies
have revealed that increases in above-ground productivity
are generally mirrored by increases in below-ground NPP,
and that both are positively related to the soil phosphorus
(7) Landscape ecology
Landscape ecology studies in the Amazon have been
dominated by the long-running Biological Dynamics of
Forest Fragmentation Project (BDFFP; Laurance et al., 2002).
The long-term study of a single site has allowed the
detection of many temporal effects of forest fragmentation
that have rarely been described, such as the progression from
crowding effects in birds immediately post-fragmentation
(Stouffer & Bierregaard, 1995) to local extinction events
in small remnants (Ferraz et al., 2003). Time-series data
from the BDFFP have also allowed the quantiﬁcation of
462 Jos Barlow and others
fragmentation-induced changes to ecological processes such
as tree mortality and recruitment rates (Laurance et al.,
2006), leading to a better understanding of the temporal
development of edge effects and the drivers of spatio-
temporal variability in fragmented landscapes (Laurance
et al., 2007).
The uneven spatial distribution of landscape ecology
research and the strong focus on the BDFFP landscape
necessarily means that our understanding of the context-
dependence of landscape patterns and species dynamics is
very limited (Gardner et al., 2009). Consequently, there is only
a limited understanding of the cumulative and synergistic
effects of multiple disturbances that are known to exacerbate
fragmentation impacts in heavily settled parts of the Amazon
(Peres, 2001; Peres & Michalski, 2006).
Landscape ecology in the Amazon suffers shortcomings
that are common to the whole discipline. Although the
biological integrity of forest fragments is heavily dependent
on the structural characteristics of the habitat matrix
surrounding those fragments (Nascimento et al., 2006;
Stouffer, Strong & Naka, 2009), there is a persistent
reluctance to collect biological data in that matrix despite the
overwhelming importance of understanding species’ abilities
to tolerate, disperse through, or survive in the modiﬁed
habitats that replace old-growth forest. Recent studies have
begun to address these questions by sampling multiple taxa in
multiple habitat types (e.g. Barlow et al., 2007). A second and
related issue is that carefully designed studies with multiple
landscapes are completely absent, yet the biophysical, socio-
economic and historical context of landscapes can exert
a strong inﬂuence on long-term biodiversity persistence
(Gardner et al., 2009).
(8) Sampling biodiversity
The Amazon basin is one of the world’s most species-rich
biomes and contains some of the highest known levels of
biological diversity including >50,000 terrestrial vascular
plant species (e.g. Hubbell et al., 2008) and with some single
localities of SW Amazonia sustaining the highest levels of
alpha-diversity ever documented on Earth, including woody
plants (Gentry, 1988), butterﬂies (Emmel & Austin, 1990),
lizards (Dixon & Soini, 1986) and non-volant mammals
(Peres, 1999). Yet the distribution of Amazonian forest
biodiversity is highly heterogeneous (ter Steege et al., 2006;
Pitman et al., 2008), particularly when comparing between
seasonally ﬂooded and unﬂooded forests [e.g. large forest
vertebrates (Haugaasen & Peres, 2005) and small mammals
(Malcolm, Patton & Da Silva, 2005)].
Because of the region’s vast size, poor infrastructure and
lack of research investment, our understanding of Amazonian
biodiversity remains very poor with most species lists
representing gross underestimates. For example, individual
ﬁsh-collecting expeditions in the last two decades have
consistently yielded 5% new species, while an average of 2.3
new bird species have been described each year since 1996
(Peres, 2005). Additionally, the distribution of biodiversity
sampling across Amazonia is highly patchy and often limited
to areas immediately around research stations (e.g. Schulman
et al., 2007).
Improvements in the cost-effectiveness of biodiversity
research in Amazonia are urgently needed to overcome these
challenges (Higgins & Ruokolainen, 2004; Gardner et al.,
2008; Magnusson et al., 2008), and could be achieved through
a number of complementary approaches, including: (1) better
use of existing, unpublished datasets; (2) use of eco-regional
analyses to help identify areas that are most likely to contain
new species; (3) development of standardised sampling
methods for species groups that rely on passive trapping
techniques (e.g. many invertebrates), or which require a
high level of ﬁeld expertise (e.g. birds); (4) exploitation of
economies of scale in ﬁeld and laboratory research when
conducting multi-taxa surveys; and (5) increased investment
in training and education—not only of expert taxonomists
and dissemination of guides and keys (including web-based
identiﬁcation tools), but also local ﬁeld teams and laboratory
technicians who are an essential part of any research
program. Recent large-scale sampling programs such as
the Brazilian PPBIO project (http://ppbio.inpa.gov.br/Eng)
have made some progress in these areas but it is vital that
the momentum is maintained.
(9) Plant taxonomy and databases
Taxonomic understanding of Amazonian plants is very
limited. For example, 20–40% of tree species described
in recent taxonomic monographs were new (e.g. Pen-
nington, 1997). Additionally, the distribution of plant
collections across Amazonia is highly patchy (Schul-
man, Toivonen & Ruokolainen, 2008). Integrating reli-
able species identiﬁcations into non-taxonomic studies can
make a major contribution towards improving data qual-
ity, but this is challenging in a diverse, poorly docu-
mented ﬂora. A number of botanical organisations are
helping by developing user-friendly identiﬁcation tools (e.g.
neotropikey.htm), databases integrating distribution data
(e.g. Global Biodiversity Information Facility, GBIF), and
checklists to unravel complex synonymy (e.g. Govaerts,
Frodin & Pennington, 2001).
Voucher specimens are needed to verify identiﬁcations
and as a taxonomic resource, but specimens from ecological
studies—particularly sterile ones in the case of plants—may
never be incorporated into collections and herbaria, and
their identiﬁcations remain unveriﬁable. To capitalise on
data from ecological studies, there is scope for a standard
mechanism for sharing and annotating location records and
specimen images online. The Atrium system used by many
may provide an appropriate model.
DNA sequences will have an important future role in
facilitating identiﬁcation and taxonomy. DNA ‘‘barcodes’’,
short sequences from a standardized genome position, are
promising for identiﬁcation, particularly of non-reproductive
specimens (e.g. juvenile insects and seedlings). If the same
barcodes were sequenced for sampling locations across the
Using learning networks to understand complex systems 463
Amazon, the data accumulated would be of enormous use
in taxonomy, biogeography and conservation. The DNA
sequences could be used: (1) as a new dataset alongside
morphology in species delimitation; (2) in beta diversity
studies using approaches of community phylogenetic
structure (e.g. Webb et al., 2002); (3) in analyses to identify
areas that contain most lineage diversity (e.g. Forest et al.,
2007). The cost of DNA sequencing is decreasing, and the
limiting factor to implementing such ‘‘biodiversity genomics’’
will be in collecting leaf samples for DNA extraction and
voucher specimens. We urge ﬁeld workers to make the
effort and resource allocation required to collect voucher
specimens and digital images. Such effort allied to emerging
tools promises to deliver a huge improvement of biodiversity
knowledge in the world’s most species-rich biome.
(10) Speciation and biogeography
Biodiversity can be viewed as existing patterns or underlying
processes, and both perspectives should play a role in
conservation strategies (Moritz, 2002). This is particularly
true in Amazonia, which is one of the most species-
rich regions of the world for many terrestrial taxa (Bush,
1994; Haffer, 1997; Colinvaux, De Oliveira & Bush,
2000). Most explanations for these exceptional levels of
biodiversity rely on populations being historically isolated
(Haffer, 1969; Lovejoy, Bermingham & Martin, 1998), yet
various hypotheses based on forest refugia, riverine barriers
and marine incursions receive mixed support at best (e.g.
Gascon et al., 2000; Hall & Harvey, 2002; Aleixo, 2004;
Funk et al., 2007). On one hand, recent genetic studies reveal
that Amazonian taxa tend to be derived from older lineages
in neighbouring upland regions, which may have acted
as ‘species pumps’ (Aleixo & Rossetti, 2007; Santos et al.,
2009). On the other hand, they show that dispersal from
Amazonia may also generate species through divergence in
peripheral populations (Brumﬁeld & Edwards, 2007; Seddon
& Tobias, 2007).
Modern molecular techniques are opening up new
challenges and opportunities. Recent research shows that
Amazonian species have complex evolutionary history, and
that current species limits often conceal highly divergent
intraspeciﬁc lineages (Marks, Hackett & Capparella, 2002;
Whinnett et al., 2005). In many cases, these lineages appear
to represent young or cryptic species, suggesting that we
may have underestimated the region’s biodiversity and its
propensity to generate new species. More molecular and
taxonomic studies are needed to explore this issue, and to
provide a phylogeographic dataset with which to investigate
the roles of geography, ecology and evolutionary history
in structuring biological communities across the basin. The
answers will not only help us to understand Amazonian
biodiversity, but to predict its response to environmental
change, and to pinpoint the best strategies for its protection.
One of the key points emerging is that Amazonia is a
dynamic ecosystem sustained by ongoing broad-scale eco-
evolutionary processes which can best be preserved by
maximizing connectivity between protected areas.
(11) Amazonian hunting research
Hunting of forest mammals and birds for food is widespread
across Amazonia (Peres & Lake, 2003) and the larger species
preferred by hunters are often over-exploited (Peres, 2000).
This is exacerbated by habitat loss in deforested areas (Peres,
2001) and possibly exacerbated when colonisation and forest
clearance centre on roads instead of productive rivers. Away
from the deforestation frontier, the decline of extractive
industries and process of rapid urbanization in recent decades
(Browder & Godfrey, 1997) may have alleviated hunting
pressure on some animal populations. However, in some
cases abandoned areas are already heavily degraded, and
although secondary regrowth on cleared lands can support
some large vertebrates and provide food to rural people
(Smith, 2005), it is unlikely that such areas can provide a
sustainable supply of game meat (Parry, Barlow & Peres,
Hunting research needs to address two major areas of
uncertainty. First, the scale of urban consumption of hunted
wildlife is poorly understood yet is likely to be increasing
due to urbanization and increases in urban wealth. There
has been only limited use of economics and social science
in Amazonian hunting research, unlike in Africa where
interdisciplinary approaches to understanding demand are
well advanced (e.g. Wilkie et al., 2005). Second, although the
extent of sustainable-use reserves has increased exponentially
in recent years it is unclear how hunting in inhabited reserves
will affect exploited populations and ecosystem functioning
through cascading effects. Encouraging the extraction of non-
timber forest products may exacerbate hunting by increasing
human activity in the forest (Parry, Barlow & Peres, 2009a).
The widespread adoption of community management of
hunting through no-take areas and catch-per-unit-effort
monitoring (Puertas & Bodmer, 2004) remains a distant
promise. We also need to understand better the interactions
between hunting and other forms of forest disturbance (Peres,
2001), ﬁshing, and the importance of keystone resources for
some game species (Fragoso, 1998).
(12) Conservation planning
Despite signiﬁcant recent progress in augmenting the
Amazonian network of protected areas (e.g. 148 reserves
with a total area of 640,000 km
were created between 2003
and 2007 in Brazil alone), there are ample opportunities
for further expansion of the number and total acreage of
forest reserves in lowland Amazonia. However, capitalizing
on this opportunity has so far been a largely ad hoc process.
A practical approach to designing and siting reserves cannot
rely on detailed biodiversity distribution data, which are
unavailable for all Amazonian countries (Peres, 2005).
Instead, reserve design criteria including the size, habitat
composition, denomination and level of protection have been
decided haphazardly depending on the local expediency of
sociopolitical circumstances, with little attention heeded to
lessons learned from policy debates on these topics (Peres &
Zimmerman, 2001; Nepstad et al., 2006) or the science of
464 Jos Barlow and others
reserve allocation and implementation (Fearnside & Ferraz,
1995; Peres & Terborgh, 1995; Ferreira et al., 2001).
Given our current disconcerting level of ignorance of
the patterns of biodiversity distribution across Amazonia,
vegetation types probably offer the best available coarse-
ﬁlter surrogate of species turnover for plant and animal
assemblages (Scott et al., 1993). Natural vegetation types
in tropical forest regions reﬂect baseline environmental
gradients that affect species distributions. In lowland
Amazonia, large rivers also form important geographic
barriers (e.g. Ayres & Clutton-Brock, 1992). A set of
biogeographic units deﬁned by the overlay of major river
barriers and vegetation types could therefore be used as a
basis for evaluating the representation of both existing and
future conservation areas (Peres, 2002).
The untested assumption is that a relatively simple gap
analysis would capture most of the region’s biodiversity with-
out the need to carry out detailed basin-wide species invento-
ries. In the short term, this coarse-grained approach probably
offers the best hope of achieving a geographically balanced
and robust pan-Amazonian nature reserve network irrespec-
tive of ecoregional differences in species richness, occurrence
of rare and endemic species, ecosystem vulnerability, and
urgency to counteract threats (e.g. Peres et al., in press).
A limitation of this approach, however, is that it provides lit-
tle guidance on the speciﬁcs of reserve design, including the
size, shape, connectivity, geographic position within water-
sheds, level of protection of conservation units, land use in
the intervening habitat matrix, or how individual reserves
will respond to a changing climate (Malhi et al., 2008).
(13) Livelihoods and governance
Amazonia smallholder livelihoods are diverse and in ﬂux,
inﬂuenced by a range of factors (Steward, 2007; de Sherbinin
et al., 2008; Pacheco, 2009). Traditional livelihoods can be
threatened when forest areas become more accessible to
markets and cattle ranching becomes preferable to the
extensive harvest of non-timber forest products. For example,
rubber tappers in Acre are increasingly expanding their
livelihood strategies into small-scale cattle operations, which
often function as effective insurance and savings strategies
(Salisbury & Schmink, 2007).
Livelihood diversiﬁcation is an important coping strategy
for communities (Pacheco, 2009) and steady access to cap-
ital of some form is needed to ensure household resilience
(Salisbury & Schmink, 2007). The potential impacts of con-
ditional cash-transfer mechanisms on livelihoods (e.g. recent
Brazilian government direct-grant programs such as Bolsa
Familia, Bolsa Floresta) have increased dramatically (see
Section II.14), as well as increased interactions with urban
centres where payments are normally collected and spent.
Expanding urban markets and urban opportunities may
increase rural-urban linkages. Migrants to urban centres in
Amazonia often form part of ‘multi-sited households’ par-
taking in networks across rural-urban areas and in rural
land-use decisions and helping determine urban markets for
food and construction materials (Padoch et al., 2008).
Migration across Amazonia is an increasingly important
demographic factor (Barbieri, Carr & Bilsborrow, 2009).
In older frontiers the declining capacity of farms to
maintain families, coupled with soil degradation and reduced
agricultural yields, can stimulate the next generation to move
to new settlements, with potentially signiﬁcant consequences
for forest conservation (Barbieri et al., 2009). In more
remote areas, a rural exodus may be being driven by the
lack of opportunities for education (Parry et al., in press).
The inﬂuence of demographics is particularly important
in indigenous communities, where patterns of settlement
expansion are cyclical according to household age (de
Sherbinin et al., 2008).
The effects of future social, economic and environmental
change are likely to vary along gradients of physical
accessibility and increasing remoteness from urban centres
and ‘‘the frontier’’ (Parry et al., 2010). Questions about how
climate change impacts local decision-making processes and
risk management strategies in land-use change are beginning
to gain attention (e.g. Brondizio & Moran, 2008), but little is
known about the way these interplay with wider governance
strategies that are emerging in Amazonia (e.g. Boyd, 2008).
(14) Market-based conservation strategies
It is now well established that the success of conservation
policies for inhabited tropical forests depends on the
inclusion of local populations and recognition of their needs.
Government regulation and the imposition of environmental
laws (‘fences-and-ﬁnes’) must be combined with positive
incentives which encourage users to protect terrestrial
and aquatic resources while strengthening their livelihoods
(Fisher et al., 2008). The use of market-based strategies as
part of a more rounded sustainable development approach
has thus become increasingly attractive. This could ﬁnd
expression through individual private and commercial
initiatives or as part of wider integrated conservation and
development projects (ICDPs) using a community-based
For example, although uncontrolled logging continues
to be a major source of environmental destruction in
Amazonia, sustainable timber harvesting has expanded
slowly but steadily to supply niche markets (Ozinga, 2004).
Non-timber forest products (NTFPs) such as latex, nuts,
fruits, oils, resins and medicinal plants have for centuries
been exploited by indigenous and traditional populations to
meet their own needs. Nowadays, domestic and international
markets for such products have grown considerably in various
sectors including food, cosmetics, medicines, clothing and
construction and ecotourism (Plotkin & Famolare, 2004).
Under the United Nations Framework Convention on
Climate Change (UNFCCC) and its proposed Reducing
Emissions from Deforestation and forest Degradation
(REDD+) or ‘avoided deforestation and forest protection
mechanism,’ carbon trading has the potential to generate
signiﬁcant income for forest peoples (Hall, 2008).
Although such solutions are often portrayed as ‘win-
win’, NTFP and other market-based initiatives face many
Using learning networks to understand complex systems 465
‘Amazon factor’). These include: (1) large distances from
urban markets; (2) low levels of management, organisational
and commercial expertise; (3) inadequate local production,
transport, ﬁnancial and communications infrastructure;
(4) vulnerability to ﬂuctuations in market prices and
consumer demand; (5) growing competition from alternative
land uses as well as other regions and countries; and
(6) assymetrical power relations which may marginalise
local groups (Ros-Tonen, van den Hombergh & Zoomers,
2007). Furthermore, REDD+ policies will face problems
of monitoring additionality in carbon sequestration and
ecosystem service provision, of leakage of carbon emissions
within and across national borders, of balancing social justice
with efﬁciency in the distribution of ﬁnancial rewards, and
of potential threats to the rights of forest dwellers, amongst
others (Grifﬁths, 2007; FOE, 2008).
These 14 mini-reviews demonstrate the strength and depth
of ongoing research efforts in the Amazon, but also highlight
factors currently limiting a more complete understanding
of the complex web of environmental, economic and social
patterns and processes. Many of the barriers to improved
research performance (i.e. the efﬁcient production and dis-
semination of reliable knowledge concerning key research
priorities) are common across disciplines, and stem partly
from a lack of interaction within and between natural and
social sciences. Here, we examine how efforts to develop
a more interactive research environment could help over-
come these barriers and drive research progress, linking
these observations to some of the key research challenges
identiﬁed by this learning network exercise. We ﬁrst consider
how improved interaction amongst scientists can enhance
research within traditional disciplines, and then examine
how interdisciplinary research programs can help scientists
engage with the full complexity of the problems facing
the Amazon. Finally, we draw upon the experience of our
research network exercise to propose ways to build a more
interactive research environment.
(1) Improving research performance by enhancing
interaction within scientiﬁc disciplines
Developing interactive research and learning networks
provides substantial beneﬁts for the progress of individual
scientiﬁc disciplines. We draw upon our review to illustrate
how interaction amongst researchers and the development
of learning networks can be valuable, if not essential, for
confronting ﬁve key challenges facing science in Amazonia
(a) Problem formulation, research design and analysis
There is an almost unlimited number of research questions
that could be asked regarding the environmental and
social patterns and processes occurring within the Amazon.
Many research design choices reﬂect short-term funding
opportunities, and time constraints experienced by relatively
isolated individual researchers or research groups. However,
the immediacy of most social and environmental problems
means scientists need to adopt a more strategic approach to
formulating research priorities and attempt to maximise the
return on investment from limited resources (Bottrill et al.,
2008; Gardner, 2010). More careful aprioriconsultation
within a wider research network would help establish
priorities for new research, including: the questions and
geographic regions that are likely to return the most novel
and complementary ﬁndings; the extent and quality of prior
research (published and unpublished); and the practical
feasibility (logistics, availability of appropriate methods, etc.)
of implementing new ﬁeldwork.
(b) Sharing data, research protocols and research infrastructure
Enhanced knowledge exchange could improve use of
existing data, which are often only known to a few
individuals but which could help re-direct priorities and the
demand for new information following summary assessments
and meta-analyses. The development and use of shared
research protocols and standardised sampling techniques
can signiﬁcantly increase the efﬁciency and integrity of
research projects working in new areas—as demonstrated
in Amazonia by the RAINFOR network (see Section
II.5). The widespread adoption of standardised methods
is also essential in allowing such approaches to be validated
constantly and improved for different contexts. Recent
developments in this area show promise, and include
the online PRODES database of deforestation maps and
statistics provided by the Brazilian National Institute for
Space Research (INPE; www.obt.inpe.br/prodes/), the
HidroWeb database of hydrological records hosted by the
Agencia Nacional de Aguas (http://hidroweb.ana.gov.br),
the Amazon spatial mapping tool provided by IMAZON
(www.imazongeo.org.br) and the Forest Plots Database,
designed to provide a permanent repository for forest
inventory data (http://www.forestplots.net/). Furthermore,
there is great potential in online biodiversity information
systems to help bridge the gap between the ecological and
taxonomic sciences (see Sections II.8–10 and below).
Sharing research infrastructure among scientists will also
facilitate more cost-efﬁcient research and therefore generate
greater scientiﬁc returns from limited funds. For example, it
takes considerable time and money to train ﬁeld staff to do
speciﬁc tasks, so making those staff trained in one project
available to groups running new projects will go a long way
towards increasing the efﬁciency of data collection. Similarly,
a simple yet centralised database of ﬁeld sites would allow
research teams to identify locations that have prior knowledge
of particular aspects of the wider social-ecological system,
thereby encouraging work in new sites and enhancing the
overall cost-effectiveness of research efforts across the basin.
The marginal cost of collecting new information as part of
an ongoing project is negligible compared to the cost of
466 Jos Barlow and others
establishing a new project from scratch, but this requires
a much wider sharing of research infrastructure than is
currently the case.
(c) Achieving an understanding of scale
Perhaps the greatest challenge facing researchers working
in the Amazon is its sheer size. Almost all the mini-reviews
highlight how our understanding of patterns and processes
across the Amazon basin is limited by insufﬁcient spatial and
temporal scale and resolution in sampling. Most research is
strongly aggregated spatially, and in some disciplines such
as landscape ecology the majority of existing information is
derived from an extremely small number of well-studied sites
(Gardner et al., 2009, and Section II.7). This constrained
sampling would matter less if Amazonian forests, rivers
and peoples were homogeneous, but evidence demonstrates
otherwise. Many research questions in Amazonia can only
be addressed by integrating datasets from across multiple
locations and contexts as it is becoming increasingly clear that
different forest types function in very different ways (Section
II.5), while human-environment interactions vary greatly
depending on historical and regional context (Fearnside,
2008, and Section II.13).
Temporal data are also critical for unravelling many
complex problems. For example, we currently have a poor
understanding of the longer term ecological consequences
of land-use change, as few research projects last more
than a few years. However, the few ecological studies that
explicitly considered disturbance history as an explanatory
variable have shown it to have a dominant effect on
extant biodiversity patterns (e.g. changes in biodiversity
following forest disturbance or fragmentation; Sections II.3
and II.7). Many human-environment interactions are also
highly dynamic over time, confounding attempts by short-
term studies to be reliable in identifying drivers of change
(e.g. Ewers, Laurance & Souza Jr, 2008).
Improved communication and collaboration among
research groups is likely to be the most effective way to
achieve improved spatial and temporal sample replication.
The RAINFOR network provides an effective template for
how integrated research networks can work, and what they
can achieve. By linking more than 90 researchers from
multiple South American and international institutions,
RAINFOR has harmonized the data-collection methods
of scientists working in 140 permanent plots located at
42 geographically distinct sites across Amazonia (Malhi
et al., 2002), producing important insights into how
forests change over time and space, and how they
may respond to future environmental change (Sections
II.5 and II.6). It would be impossible for a single
research group to develop a project with such a wide
geographical and temporal base. The RAINFOR network
is made up of a consortium of research groups who
maintain independent lines of investigation, yet share
an interest in a common set of large-scale processes
inﬂuencing vegetation dynamics in Amazonia. This
shared interest justiﬁes the marginal cost of adjusting
or complementing existing sampling methodologies and
alleviates the need for top-down labour- and cost-intensive
(d) Keeping up with the cutting edge
Progress in science is not linear. New insights, theory
and technological developments can emerge very rapidly,
making it difﬁcult for individual researchers—especially
those working in isolated and poorly funded institutions—to
keep their science up-to-date and cost-effective. New
developments frequently spawn sub-disciplines and/or
centres of excellence associated with particular research
groups, further sub-dividing the learning process. Examples
of this are easy to ﬁnd in high-technology ﬁelds such as
remote-sensing, where new indices of land-cover change and
degradation from increasingly high-resolution imagery are
constantly out-dating previous techniques (e.g. Chambers
et al., 2007, and see Sections II.2 and II.7). In a similar
way, the use of DNA technology and emerging techniques
such as bar-coding has led to the ﬁeld of systematics
being divided amongst those who have access to genetic
laboratories and those that do not, generating considerable
controversy and confusion regarding the validity and
utility of new developments (e.g. Kress & Erickson,
Promoting an effective dialogue within a research
community can provide a means to allow busy or under-
resourced scientists access to state of the art science, as
well as to help prevent the excessive fragmentation of
scientiﬁc disciplines. This is critically important in the
applied sciences, as many new policy- and market-based
conservation initiatives are developing so fast that there is
a serious risk that science will lag behind, and will fail to
inform the development of these initiatives. A clear example
of this is provided by the disparate mix of REDD+ projects,
a process advanced during the UNFCCC conference in
Copenhagen in December 2009, which would beneﬁt from a
more coordinated approach underpinned by robust science
(see Fig. 1).
(e) Enhancing scientiﬁc impact and dissemination
Most researchers disseminate their science in peer-reviewed
journals, and there is often a lag period of years before even
the most important results are incorporated into the design
and interpretation of subsequent work. These delays can
be greatly reduced through research networks, which can
exploit multi-media communication channels (e.g. e-mail
list-servers, online discussion forums, web-based scientiﬁc
meetings, etc.) to disseminate key ﬁndings, helping the
research community to avoid past mistakes and maximising
the return on investment from new research initiatives.
Moreover, a more interactive scientiﬁc community can
increase the policy impact and societal awareness of research
by working to achieve consensus ﬁndings, making joint
press releases, and pooling resources to develop novel
Using learning networks to understand complex systems 467
Fig. 1. A summary of interdisciplinary research needs for understanding the supply and demand of carbon sequestration services
within an avoided deforestation (REDD) project, as well as long-term ecological, economic and social viability issues.
(2) Improving research performance by increasing
interaction across disciplines
Calls for interdisciplinary research in environmental
conservation are not new (Kinzig, 2001) but have
been increasing, reﬂected by the rapid development
of conservation science sensu lato as an inherently
interdisciplinary ﬁeld concerned with understanding
complex human-environment relationships in the search
for sustainability (Robinson, 2008; Cooke et al., 2009;
Lowe, Whitman & Phillipson, 2009). Interdisciplinarity is
particularly relevant for understanding processes in human-
modiﬁed tropical forests, which are both ecologically and
socially complex, as well as highly dynamic. Successful
interdisciplinary research will beneﬁt from research networks
in the same way as intra-disciplinary research (Section
III.1), although there are obvious and substantial additional
beneﬁts that can be gained from the establishment of a more
interactive research environment.
At the simplest level our research network exercise
highlighted several pairwise interactions between disciplines
that could generate signiﬁcant reciprocal beneﬁts. For
example, the link between the taxonomic and ecological
sciences could be greatly strengthened. At present many
of the biodiversity specimens collected during ecological
research fail to make it into museum collections or
herbariums (Section II.9), while ecologists frequently rely
upon outdated ﬁeld guides when making identiﬁcations.
Given that taxonomists (and biogeographers) require
specimens from as wide a range of localities as possible
and ecologists and conservation biologists require accurate
species data, there is a clear beneﬁt for these two groups
to work more closely together. Once again, the increasing
number of online resources could play an important role in
facilitating this interaction.
Another mutually beneﬁcial pairwise interaction exists
between ﬁeld ecologists and the remote sensing community.
Remote sensing scientists approximate real patterns of
ecological change, while ﬁeldworkers are often interested in
extrapolating direct measurements of ecological phenomena
from small sampling localities to landscapes and regions.
Given this apparent inter-dependence it is unclear why
only a very small number of studies has attempted to
link newly developed indices of canopy degradation [e.g.
Normalised Vegetation Fraction Index (Souza, Roberts
& Monteiro, 2005)] with ﬁeld biodiversity data (Aguilar-
Amuchastegui & Henebry, 2007), despite the fact that severe
forest degradation currently threatens a much larger area of
forest in the Amazon than deforestation (Asner et al., 2005;
Peres, Barlow & Laurance, 2006).
Interdisciplinary approaches are also critical when
confronting environmental problems whose characteristics
do not allow a clean separation of social, ecological and
biogeophysical phenomena (Kinzig, 2001; Liu et al., 2007).
One of the strongest conclusions to emerge from our learning
network exercise was the high level of interdependency that
underpins many observed phenomena, both within and
between the social and ecological sciences. A good example
of this is the process of road building. Despite being a
critical factor in the development of deforestation models (e.g.
Soares-Filho et al., 2006) there have been very few successful
468 Jos Barlow and others
validations of road-building models against actual ﬁeld data
(see Section II.2). Moreover, roads are only proximate drivers
of deforestation and their construction is underpinned by a
complex array of biophysical and socioeconomic drivers
(Perz et al., 2007). It is likely that deforestation models could
be greatly improved by more effectively harnessing this
socioeconomic information, allowing the evaluation of the
impact of more nuanced development scenarios on patterns
of deforestation and changing land use (Section II.2).
Interdisciplinary studies are also essential to understand
the potential for cascades and feedback effects in human-
modiﬁed forest ecosystems (Gardner et al., 2009). For
example it is well known that the perturbation of ecological
systems can precipitate cascading effects, such as those caused
by over-hunting of large vertebrates on the composition
of plant communities (e.g. Terborgh et al., 2008), though
changes to the ecological system can also have important
feedbacks on the coupled social system. In another example
increased ﬁres can reduce the value of the forest for NTFPs
(Sinha & Brault, 2005), encouraging a shift in livelihoods
towards farming and increasing the risk of ﬁres occurring
in neighbouring areas of forest in the future. The possibility
of severe climate change in the Amazon could lead to
an increasing number of feedbacks between climate, and
ecological and social systems (Malhi et al., 2008).
Like many areas of the world, the Amazon is expe-
riencing rapid change in its underlying governance
structure, with shifts from centralised command-control
systems to de-centralised governance and the emergence
of public-private, voluntary and market-based conserva-
tion strategies (Boyd, 2008). A major driver of these
changes is the promise offered by novel forest conser-
vation ﬁnance through ecosystem services markets, and
in particular REDD+; http://www.undp.org/mdtf/un-
redd/overview.shtml. Understanding the opportunities and
challenges posed by REDD+ is a quintessentially interdisci-
plinary problem that demands a variety of methodological
approaches as well as disciplinary expertise from nearly
all the areas of research analysed herein, including ques-
tions of ecological and social viability, forest management
and monitoring, livelihoods and market dynamics (Fig. 1).
Researchers should embrace this interdisciplinary approach
from the outset if science is to make a genuine contribution
to a more sustainable future for Amazonia: integration is
essential to ensuring that the right variables are collected at
appropriate spatial and temporal scales, and that researchers
from individual disciplines are aware from an early stage of
the assumptions and pervasive uncertainty confronting any
interdisciplinary analysis (Kinzig, 2001; Cooke et al., 2009).
Research and learning networks provide a vital ﬁrst step in
this process of integration.
(3) Effective communication provides the basis
of an interactive research environment
While successful collaborations among scientists from the
same or different disciplines can bring many advantages,
they can be deceptively difﬁcult to establish. They are
Fig. 2. A conceptual model of the three main dimensions
of interaction within a research environment. Effective
communication provides a basis for more formal researcher
interactions including the coordination of data using
comparable sampling methods and the development of active
collaborations. All three forms of interaction can make valuable
contributions to improving research performance. While many
questions, including all interdisciplinary problems, require the
establishment of collaborations with researchers working in
other departments, institutions and countries, considerable
progress can often ﬁrst be made simply through efforts to
improve communication and transparency regarding new
ideas, unpublished ﬁndings and newly developed tools and
often driven as much by chance encounters, differences
in personal interest and trust as they are by scientiﬁc
priorities. Fortunately, one basic yet important lesson from
our learning and research network exercise is that there are
many ways of beneﬁting from increased interaction without
entering into full collaboration, and research performance
can also be improved through enhancing communication
and coordination among scientists engaged in independent
yet related research activities (Fig. 2).
Despite being the least ambitious form of interaction,
effective communication both within and among disciplines
provides an essential basis for identifying high-priority
research questions and helps ensure the best use of limited
resources by avoiding repetitive or unfeasible work (Fig. 2).
Communication of published work is often hindered by
an excess of subject-speciﬁc jargon (Ewers & Rodrigues,
2006) as well as by linguistic and ﬁnancial constraints
which means that scientists working in developing and
developed countries use very different sources of information
(Pitman et al., 2007). Research development could be
strengthened and accelerated through the development
of multi-disciplinary reviews, such as that presented here,
which encourage simpler terminology, as well as the
communication of a wide range of other types of information,
including unpublished ﬁndings, proven ﬁeld methods
and analytical approaches, untested research hypotheses
Using learning networks to understand complex systems 469
and ideas, published and unpublished literature, ongoing
independent research projects, funding opportunities and
recommendations on ﬁeld logistics. Unfortunately the
exchange of many of these forms of information is frequently
limited by a lack of time as well as concern that sharing
privileged information will compromise individual research
performance and intellectual property.
(4) Overcoming barriers to interactive
and interdisciplinary research
Establishing lasting networks is of course a very difﬁcult
task, and there are many potential barriers that could
prevent more interactive and interdisciplinary research
environments from developing. Many of these are structural,
relating to the regional scope of the network, scarcity (or
inequality) of funding, disciplinary institutional traditions
and organisational structures, inadequate interdisciplinary
training and insufﬁcient rewards for integrative research
(Kinzig, 2001; B. Fisher et al., 2009). We examine some of
the steps that are being taken to overcome these barriers in
(a) Expanding the regional scope
The narrow UK regional focus of the present learning
network helped bring together representatives from disparate
disciplines. However, this synthesis is obviously only a ﬁrst
step towards a more inclusive network, or set of networks,
which should involve researchers from many countries,
and most importantly those based within the Amazonian
basin itself. Amazonian universities, research institutions
and regulatory agencies are at the front line of Amazonian
research, and obviously represent the most important
component of effective collaborative research projects. They
are also best placed to coordinate and disseminate the results
of research to the most relevant decision makers, land-use
planners and land managers.
Signiﬁcant progress can be made through the develop-
ment of additional regional networks - bringing together
researchers who work in relative proximity to each other and
interact through applications to common funding sources
(e.g. as would be the case for networks based in each
of the nine countries that comprise the Amazon). Within
Brazil, initiatives such as the Center for Integrated Stud-
ies of Biodiversity in the Amazon (CENBAM) provide a
good example of this, and are helping support and train
ﬁeld assistants, parataxonomists and scientists beyond the
major regional centres of scientiﬁc research in Bel
Manaus. Similar initiatives in the other Amazonian coun-
tries would be beneﬁcial. Ultimately a more ambitious task
is to ﬁnd ways to connect members of the global research
community who work on tropical forests, irrespective of
where they are based. While this may seem impractical,
a superb precedent has been set by coral reef researchers
bringing together more than 6000 researchers from across
the world, effectively sharing ideas, data and opportunities
for research and education.
(b) Funding barriers
There are reassuring signs that structural barriers
to interdisciplinary research are being weakened by
novel funding programs, and a focus towards assess-
ing the actual impact of research programs (see the
proposed arrangements for the assessment and fund-
ing of research in UK higher education institutions;
ever, networks also depend on targeted resources that can
provide the physical, technological and human resources
necessary to maintain a coherent, responsive and up-to-date
network support structure, as well as to help overcome the
enormous barriers associated with data access and shar-
ing. Although much work remains to be done, there is
promising evidence for moves in this direction within the
Amazon region, such as through the Brazilian National
Institutes of Science and Technology in 2008 which received
R$600 million in federal government support to create
regional centres of excellence and better integrate existing
institutions and research groups. Decentralization of funds
towards institutions and individuals who are responsible for
developing research networks in distinct regions (while also
maintaining the integrity of shared goals and national or
global levels through coordinated selection, monitoring and
evaluation procedures) is essential for capacity building and
providing a dependable basis for future work. The regional
Executive Hubs created to support the Brazilian national
PPBio program (http://ppbio.inpa.gov.br/Eng) provides a
good example of this.
(c) Researcher behaviour
Perhaps a more serious barrier to interdisciplinary research
is behavioural, and relates to the values and attitudes held
by researchers working in different disciplines (Kinzig, 2001;
Lele & Norgaard, 2005). Whether intended or not, the
values held by individual scientists manifest themselves
during collaborative research exercises in the form of implicit
assumptions regarding the relative utility of other disciplines,
and different methodological approaches in tackling a given
problem. The personal experience of a number of authors
of this paper indicates that achieving an atmosphere of
mutual respect within an interdisciplinary project can be
extremely challenging and requires considerable patience,
acceptance of uncertainty as part of the research process,
and a willingness to be constructive and withhold subjective
judgement when confronted with alternative world-views.
Participants in interdisciplinary projects need to be self-
reﬂective about their own value judgements and should work
to achieve a common language for discussing fundamental
issues while also seeking to identify a core set of shared
values as a motivation for integration (Lele & Norgaard,
2005). We believe that the collaborative development of
470 Jos Barlow and others
multidisciplinary research syntheses such as that presented
herein is an important ﬁrst step towards achieving these aims.
(1) Proactive efforts to build a more interactive
research environment are necessary to improve the
performance and efﬁciency of scientiﬁc research and
help answer globally important scientiﬁc questions.
Our experience of writing this review indicates there
is an impressive willingness from researchers across
different disciplines to work together to achieve this.
(2) The production of portfolios of short and critical
syntheses on the status and direction of individual
disciplines, such as that presented here, can provide
a very useful and accessible brieﬁng on potential
interdisciplinary research opportunities, as well as an
entry point for dialogue among scientists who may
otherwise have little understanding of each others’
work. To encourage this, journals should provide
space for and actively encourage such syntheses, which
are complementary to the more traditional single-
discipline reviews and more subjective interdisciplinary
perspective-type pieces that are often led by a small
and potentially biased group of researchers.
(3) Emerging learning networks can form the basis for
developing a more collaborative research environment
that reaches beyond more traditional means of
knowledge exchange, and provides a basis for
improved research performance within and among
(4) Within the Amazonian context, the obvious next stage
in the development of a truly effective learning network
is to include researchers that are based outside the
UK, and in particular those based within Amazonian
(5) Nurturing the growth of a working and viable multi-
disciplinary research network will ultimately require
leadership and dedication from a critical mass of
participants in different disciplines, as well as a
signiﬁcant shift in attitudes towards research funding.
(6) Despite its experiential nature, we hope that this review
provides some inspiration for developing this and other
We would like to thank the Natural History Museum
in London for hosting the symposium that facilitated the
development of this manuscript. T.A.G. thanks the Natural
Environmental Research Council (NE/F01614X/1) and
J.B. and T.A.G. thank the Instituto Nacional de Ci
e Tecnologia - Biodiversidade e Uso da Terra na Amaz
(CNPq 574008/2008–0) for funding while this paper was
written. We also thank William Foster, William Magnusson
and one anonymous reviewer for comments that helped
improve the manuscript.
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