2007
DOI: 10.1057/9780230626416
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Bram Stoker

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Cited by 16 publications
(3 citation statements)
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“…Current limitations of this spectral technique for ample use in forest inventories are mostly related to lack of a robust reference model that can be used to predict species identities from a bark or a leaf spectrum. This requires obtaining spectra from bark tissues in the field for well-identified trees, preferably with a voucher specimen in a herbarium, since taxonomic definitions are largely unstable in the Amazon (Hopkins, 2007, Steege et al, 2016. Nonetheless, this technique may be used already at local/regional contexts, and may help at such contexts to better define local species even if their taxonomic names remain uncertain.…”
Section: Discussionmentioning
confidence: 99%
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“…Current limitations of this spectral technique for ample use in forest inventories are mostly related to lack of a robust reference model that can be used to predict species identities from a bark or a leaf spectrum. This requires obtaining spectra from bark tissues in the field for well-identified trees, preferably with a voucher specimen in a herbarium, since taxonomic definitions are largely unstable in the Amazon (Hopkins, 2007, Steege et al, 2016. Nonetheless, this technique may be used already at local/regional contexts, and may help at such contexts to better define local species even if their taxonomic names remain uncertain.…”
Section: Discussionmentioning
confidence: 99%
“…In the field, trees are frequently identified to species by para-botanists ('mateiros') and voucher specimens are only rarely collected for comparison with herbaria or consultation with plant specialists. In the Amazon region, high tree species diversity (Steege et al, 2016, Cardoso et al, 2017 and poor sampling make it difficult to recognize species with confidence , Hopkins, 2007, Gomes et al, 2013. Problems relate to both finding scientific names for species, and also to the grouping of trees into the same species at local scales (Gomes et al, 2013).…”
Section: Introductionmentioning
confidence: 99%
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