Literature DB >> 20849493

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

Jos Barlow1, Robert M Ewers, Liana Anderson, Luiz E O C Aragao, Tim R Baker, Emily Boyd, Ted R Feldpausch, Emanuel Gloor, Anthony Hall, Yadvinder Malhi, William Milliken, Mark Mulligan, Luke Parry, Toby Pennington, Carlos A Peres, Oliver L Phillips, Rosa Maria Roman-Cuesta, Joseph A Tobias, Toby A Gardner.   

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 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.
© 2010 The Authors. Biological Reviews © 2010 Cambridge Philosophical Society.

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Year:  2010        PMID: 20849493     DOI: 10.1111/j.1469-185X.2010.00155.x

Source DB:  PubMed          Journal:  Biol Rev Camb Philos Soc        ISSN: 0006-3231


  9 in total

1.  A social and ecological assessment of tropical land uses at multiple scales: the Sustainable Amazon Network.

Authors:  Toby A Gardner; Joice Ferreira; Jos Barlow; Alexander C Lees; Luke Parry; Ima Célia Guimarães Vieira; Erika Berenguer; Ricardo Abramovay; Alexandre Aleixo; Christian Andretti; Luiz E O C Aragão; Ivanei Araújo; Williams Souza de Ávila; Richard D Bardgett; Mateus Batistella; Rodrigo Anzolin Begotti; Troy Beldini; Driss Ezzine de Blas; Rodrigo Fagundes Braga; Danielle de Lima Braga; Janaína Gomes de Brito; Plínio Barbosa de Camargo; Fabiane Campos dos Santos; Vívian Campos de Oliveira; Amanda Cardoso Nunes Cordeiro; Thiago Moreira Cardoso; Déborah Reis de Carvalho; Sergio André Castelani; Júlio Cézar Mário Chaul; Carlos Eduardo Cerri; Francisco de Assis Costa; Carla Daniele Furtado da Costa; Emilie Coudel; Alexandre Camargo Coutinho; Dênis Cunha; Álvaro D'Antona; Joelma Dezincourt; Karina Dias-Silva; Mariana Durigan; Júlio César Dalla Mora Esquerdo; José Feres; Silvio Frosini de Barros Ferraz; Amanda Estefânia de Melo Ferreira; Ana Carolina Fiorini; Lenise Vargas Flores da Silva; Fábio Soares Frazão; Rachel Garrett; Alessandra dos Santos Gomes; Karoline da Silva Gonçalves; José Benito Guerrero; Neusa Hamada; Robert M Hughes; Danilo Carmago Igliori; Ederson da Conceição Jesus; Leandro Juen; Miércio Junior; José Max Barbosa de Oliveira Junior; Raimundo Cosme de Oliveira Junior; Carlos Souza Junior; Phil Kaufmann; Vanesca Korasaki; Cecília Gontijo Leal; Rafael Leitão; Natália Lima; Maria de Fátima Lopes Almeida; Reinaldo Lourival; Júlio Louzada; Ralph Mac Nally; Sébastien Marchand; Márcia Motta Maués; Fátima M S Moreira; Carla Morsello; Nárgila Moura; Jorge Nessimian; Sâmia Nunes; Victor Hugo Fonseca Oliveira; Renata Pardini; Heloisa Correia Pereira; Paulo Santos Pompeu; Carla Rodrigues Ribas; Felipe Rossetti; Fernando Augusto Schmidt; Rodrigo da Silva; Regina Célia Viana Martins da Silva; Thiago Fonseca Morello Ramalho da Silva; Juliana Silveira; João Victor Siqueira; Teotônio Soares de Carvalho; Ricardo R C Solar; Nicola Savério Holanda Tancredi; James R Thomson; Patrícia Carignano Torres; Fernando Zagury Vaz-de-Mello; Ruan Carlo Stulpen Veiga; Adriano Venturieri; Cecília Viana; Diana Weinhold; Ronald Zanetti; Jansen Zuanon
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2013-04-22       Impact factor: 6.237

2.  Barriers and Solutions to Conducting Large International, Interdisciplinary Research Projects.

Authors:  Erin C Pischke; Jessie L Knowlton; Colin C Phifer; Jose Gutierrez Lopez; Tamara S Propato; Amarella Eastmond; Tatiana Martins de Souza; Mark Kuhlberg; Valentin Picasso Risso; Santiago R Veron; Carlos Garcia; Marta Chiappe; Kathleen E Halvorsen
Journal:  Environ Manage       Date:  2017-09-18       Impact factor: 3.266

3.  Quantifying the impact and relevance of scientific research.

Authors:  William J Sutherland; David Goulson; Simon G Potts; Lynn V Dicks
Journal:  PLoS One       Date:  2011-11-16       Impact factor: 3.240

4.  Predictive modelling of contagious deforestation in the Brazilian Amazon.

Authors:  Isabel M D Rosa; Drew Purves; Carlos Souza; Robert M Ewers
Journal:  PLoS One       Date:  2013-10-18       Impact factor: 3.240

5.  Anticipatory governance for social-ecological resilience.

Authors:  Emily Boyd; Björn Nykvist; Sara Borgström; Izabela A Stacewicz
Journal:  Ambio       Date:  2015-01       Impact factor: 5.129

6.  Dataset of long-term monitoring of ground-dwelling ants (Hymenoptera: Formicidae) in the influence areas of a hydroelectric power plant on the Madeira River in the Amazon Basin.

Authors:  Itanna O Fernandes; Jorge L P de Souza
Journal:  Biodivers Data J       Date:  2018-04-02

7.  Evidence-Based Causal Chains for Linking Health, Development, and Conservation Actions.

Authors:  Jiangxiao Qiu; Edward T Game; Heather Tallis; Lydia P Olander; Louise Glew; James S Kagan; Elizabeth L Kalies; Drew Michanowicz; Jennifer Phelan; Stephen Polasky; James Reed; Erin O Sills; Dean Urban; Sarah Kate Weaver
Journal:  Bioscience       Date:  2018-02-21       Impact factor: 8.589

Review 8.  The future of hyperdiverse tropical ecosystems.

Authors:  Jos Barlow; Filipe França; Toby A Gardner; Christina C Hicks; Gareth D Lennox; Erika Berenguer; Leandro Castello; Evan P Economo; Joice Ferreira; Benoit Guénard; Cecília Gontijo Leal; Victoria Isaac; Alexander C Lees; Catherine L Parr; Shaun K Wilson; Paul J Young; Nicholas A J Graham
Journal:  Nature       Date:  2018-07-25       Impact factor: 49.962

9.  A social-ecological database to advance research on infrastructure development impacts in the Brazilian Amazon.

Authors:  Joanna M Tucker Lima; Denis Valle; Evandro Mateus Moretto; Sergio Mantovani Paiva Pulice; Nadia Lucia Zuca; Daniel Rondinelli Roquetti; Liviam Elizabeth Cordeiro Beduschi; Amanda Salles Praia; Claudia Parucce Franco Okamoto; Vinicius Leite da Silva Carvalhaes; Evandro Albiach Branco; Bruna Barbezani; Emily Labandera; Kelsie Timpe; David Kaplan
Journal:  Sci Data       Date:  2016-08-30       Impact factor: 6.444

  9 in total

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