Using learning networks to understand complex systems: a case study of biological, geophysical and social research in the Amazon

Lancaster Environment Centre, Lancaster University, LA1 4YQ, Lancaster, UK; Department of Life Sciences, Imperial College London, SL5 7PY, Ascot, UK; School of Geography and the Environment, Environmental Change Institute, University of Oxford, OX1 3QY, Oxford, UK; School of Geography, University of Exeter, Amory Building, EX4 4RJ, Exeter, UK; School of Geography, University of Leeds, LS2 9JT, Leeds, UK; School of Earth and Environment, University of Leeds, LS2 9JT, Leeds, UK; Department of Social Policy, London School of Economics, WC2A 2AE, London, UK; Royal Botanic Gardens, TW9 3AB, Kew, Richmond, Surrey, UK; Environmental Monitoring and Modelling Research Group, Department of Geography, King's College London, WC2R 2LS, Strand, London, UK; Tropical Diversity Section, Royal Botanic Garden Edinburgh, EH3 5LR, Edinburgh, UK; School of Environmental Sciences, University of East Anglia, NR4 7TJ, Norwich, UK; Centre of Ecological Research and Forestry Applications (CREAF), Facultat de Ciencies, Universitat Autonoma de Barcelona, 08193, Bellaterra (Barcelona), Spain; Department of Zoology, Edward Grey Institute, Oxford University, OX1 3PS, UK; Department of Zoology, University of Cambridge, CB2 3EJ, Cambridge, UK
Biological Reviews (Impact Factor: 10.26). 01/2011; 86(86):457-474. DOI: 10.1111/j.1469-185X.2010.00155.x
Source: PubMed

ABSTRACT 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.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The Amazon Basin harbors one of the richest biotas on Earth, such that a number of diversification hypotheses have been formulated to explain patterns of Amazonian biodiversity and biogeography. For nearly two decades, phylogeographic approaches have been applied to better understand the underlying causes of genetic differentiation and geographic structure among Amazonian organisms. Although this research program has made progress in elucidating several aspects of species diversification in the region, recent methodological and theoretical developments in the discipline of phylogeography will provide new perspectives through more robust hypothesis testing. Herein, we outline central aspects of Amazonian geology and landscape evolution as well as climate and vegetation dynamics through the Neogene and Quaternary to contextualize the historical settings considered by major hypotheses of diversification. We address each of these hypotheses by reviewing key phylogeographic papers and by expanding their respective predictions. We also propose future directions for devising and testing hypotheses. Specifically, combining the exploratory power of phylogeography with the statistical rigor of coalescent methods will greatly expand analytical inferences on the evolutionary history of Amazonian biota. Incorporation of non-genetic data from Earth science disciplines into the phylogeographic approach is key to a better understanding of the influence of climatic and geophysical events on patterns of Amazonian biodiversity and biogeography. In addition, achieving such an integrative enterprise must involve overcoming issues such as limited geographic and taxonomic sampling. These future challenges likely will be accomplished by a combination of extensive collaborative research and incentives for conducting basic inventories.
    Organisms Diversity & Evolution 12/2013; · 3.37 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Land use and land cover (LULC) change is one of the largest drivers of biodiversity loss and carbon emissions globally. We use the tropical rainforests of the Amazon, the Congo basin and South-East Asia as a case study to investigate spatial predictive models of LULC change. Current predictions differ in their modelling approaches, are highly variable and often poorly validated. We carried out a quantitative review of 48 modelling methodologies, considering model spatio-temporal scales, inputs, calibration and validation methods. In addition, we requested model outputs from each of the models reviewed and carried out a quantitative assessment of model performance for tropical LULC predictions in the Brazilian Amazon. We highlight existing shortfalls in the discipline and uncover three key points that need addressing to improve the transparency, reliability and utility of tropical LULC change models: 1) a lack of openness with regard to describing and making available the model inputs and model code, 2) the difficulties of conducting appropriate model validations and 3) the difficulty that users of tropical LULC models face in obtaining the model predictions to help inform their own analyses and policy decisions. We further draw comparisons between tropical LULC change models in the tropics and the modelling approaches and paradigms in other disciplines, and suggest that recent changes in the climate change and species distribution modelling communities may provide a pathway that tropical LULC change modellers may emulate to further improve the discipline. Climate change models have exerted considerable influence over public perceptions of climate change and now impact policy decisions at all political levels. We suggest that tropical LULC change models have an equally high potential to influence public opinion and impact the development of land use policies based on plausible future scenarios, but to do that reliably may require further improvements in the discipline. This article is protected by copyright. All rights reserved.
    Global Change Biology 01/2014; · 8.22 Impact Factor
  • Ecological Indicators 01/2014; 36:572-581. · 2.89 Impact Factor

Full-text (5 Sources)

Available from
May 29, 2014