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ARBOLES: a trait-based understanding of LATAM forest biodiversity and resilience

Abstract

Latin American (LATAM) forests from Brazil, Peru, Argentina and Chile are global epicentres of biological and environmental diversity. LATAM forests are home of Earth's poorest and most vulnerable people and are highly threatened by local anthropogenic disturbance and global environmental change. ARBOLES aims to improve our understanding of LATAM forest response to anthropogenic disturbance and environmental change, by integrating established forest inventory surveys with cutting-edge functional trait, genomics, experimental, computational and remote sensing approaches. Anthropogenic disturbances include deforestation, within-forest disturbance such as logging or wildfires, and defaunation. There are considerable opportunities for active restoration and enrichment of degraded land, evidenced by the Brazilian government's pledge to re-forest 12 million hectares by 2030, with a substantial reforestation commitment also made by Chile. LATAM forests are also affected by rapid global environmental change, including temperature rise (0.5 °C/decade) in some regions and droughts, causing widespread increases in forest fires. Therefore, ARBOLES will test the overarching hypothesis that plant traits determine (i) biodiversity patterns, (ii) temporal responses to global environmental change, (iii) regeneration success along gradients of anthropogenic influence, and (iv) performance of species in restoration projects. These hypotheses will be tested following five objectives. Objective 1 (O1) quantifies functional trait patterns across LATAM forests. Objective 2 (O2) assesses the trait basis of temporal changes in old-growth LATAM forests, linking these to global environmental change. Objective 3 (O3) examines whether there are predictable changes in the mean trait values of regenerating trees along gradients of forest loss, edge effects, and defaunation. Objective 4 (O4) evaluates the capacity of functional traits to inform management decisions in an applied context (forest restoration practice and planting/harvesting of commercially important taxa). Objective 5 (O5) provides scaled-up knowledge of trait variation in space and time by combining high and moderate spatial resolution remote sensing (RS) derived information with emergent computational processing methods and field-based trait data (O1-3). The outputs of this project will provide insights into the four main themes of the call, helping LATAM countries to manage natural capital in terms of biodiversity, carbon and other ecosystems services as well as to achieve critical Sustainable Development Goals. (AU)

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VEICULO: TITULO (DATA)
VEICULO: TITULO (DATA)

Scientific publications (8)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
BERENGUER, ERIKA; LENNOX, GARETH D.; FERREIRA, JOICE; MALHI, YADVINDER; ARAGAO, LUIZ E. O. C.; BARRETO, JULIA RODRIGUES; ESPIRITO-SANTO, FERNANDO DEL BON; FIGUEIREDO, AXA EMANUELLE S.; FRANCA, FILIPE; GARDNER, TOBY ALAN; JOLY, CARLOS A.; PALMEIRA, ALESSANDRO F.; QUESADA, CARLOS ALBERTO; ROSSI, LIANA CHESINI; MORAES DE SEIXAS, MARINA MARIA; SMITH, CHARLOTTE C.; WITHEY, KIERAN; BARLOW, JOS. Tracking the impacts of El Nino drought and fire in human-modified Amazonian forests. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, v. 118, n. 30 JUL 27 2021. Web of Science Citations: 1.
GUIMARAES ZICCARDI, LEONARDO; DOS REIS, MATEUS; LIMA DE ALENCASTRO GRACA, PAULO MAURICIO; BORGES GONCALVES, NATHAN; PONTES-LOPES, ALINE; ARAGAO, LUIZ E. O. C.; DE OLIVEIRA, REYJANE PATRICIA; CLARK, LYNN; FEARNSIDE, PHILIP MARTIN. Forest fires facilitate growth of herbaceous bamboos in central Amazonia. Biotropica, v. 53, n. 4, p. 1021-1030, JUL 2021. Web of Science Citations: 2.
HEINRICH, VIOLA H. A.; DALAGNOL, RICARDO; CASSOL, HENRIQUE L. G.; ROSAN, THAIS M.; DE ALMEIDA, CATHERINE TORRES; SILVA JUNIOR, CELSO H. L.; CAMPANHARO, WESLEY A.; HOUSE, JOANNA I.; SITCH, STEPHEN; HALES, TRISTRAM C.; ADAMI, MARCOS; ANDERSON, LIANA O.; ARAGAO, LUIZ E. O. C. Large carbon sink potential of secondary forests in the Brazilian Amazon to mitigate climate change. NATURE COMMUNICATIONS, v. 12, n. 1 MAR 19 2021. Web of Science Citations: 5.
MAEDA, EDUARDO EIJI; ABERA, TEMESGEN ALEMAYEHU; SILJANDER, MIKA; ARAGAO, LUIZ E. O. C.; DE MOURA, YHASMIN MENDES; HEISKANEN, JANNE. Large-scale commodity agriculture exacerbates the climatic impacts of Amazonian deforestation. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, v. 118, n. 7 FEB 16 2021. Web of Science Citations: 1.
GUIMARAES ZICCARDI, LEONARDO; DOS REIS, MATEUS; LIMA DE ALENCASTRO GRACA, PAULO MAURICIO; BORGES GONCALVES, NATHAN; PONTES-LOPES, ALINE; ARAGAO, LUIZ E. O. C.; DE OLIVEIRA, REYJANE PATRICIA; CLARK, LYNN; FEARNSIDE, PHILIP MARTIN. Forest fires facilitate growth of herbaceous bamboos in central Amazonia. Biotropica, v. 53, n. 4 FEB 2021. Web of Science Citations: 2.
SILVA, CAMILA V. J.; ARAGAO, LUIZ E. O. C.; YOUNG, PAUL J.; ESPIRITO-SANTO, FERNANDO; BERENGUER, ERIKA; ANDERSON, LIANA O.; BRASIL, IZAIAS; PONTES-LOPES, ALINE; FERREIRA, JOICE; WITHEY, KIERAN; FRANCA, FILIPE; GRACA, PAULO M. L. A.; KIRSTEN, LETICIA; XAUD, HARON; SALIMON, CLEBER; SCARANELLO, MARCOS A.; CASTRO, BRUNO; SEIXAS, MARINA; FARIAS, RENATO; BARLOW, JOS. Estimating the multi-decadal carbon deficit of burned Amazonian forests. ENVIRONMENTAL RESEARCH LETTERS, v. 15, n. 11 NOV 2020. Web of Science Citations: 0.
SILVA JUNIOR, CELSO H. L.; HEINRICH, VIOLA H. A.; FREIRE, ANA T. G.; BROGGIO, IGOR S.; ROSAN, THAIS M.; DOBLAS, JUAN; ANDERSON, LIANA O.; ROUSSEAU, GUILLAUME X.; SHIMABUKURO, YOSIO E.; SILVA, CARLOS A.; HOUSE, JOANNA I.; ARAGAO, LUIZ E. O. C. Benchmark maps of 33 years of secondary forest age for Brazil. SCIENTIFIC DATA, v. 7, n. 1 AUG 14 2020. Web of Science Citations: 1.
BRAGA, JOSE R. G.; PERIPATO, VINICIUS; DALAGNOL, RICARDO; FERREIRA, MATHEUS P.; TARABALKA, YULIYA; ARAGAO, LUIZ E. O. C.; DE CAMPOS VELHO, HAROLDO E.; SHIGUEMORI, ELCIO H.; WAGNER, FABIEN H. Tree Crown Delineation Algorithm Based on a Convolutional Neural Network. REMOTE SENSING, v. 12, n. 8 APR 2 2020. Web of Science Citations: 14.

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