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accession
locus
voucher
source
intro
The following text may make multiple use of each data field.
The field may contain magenta text presenting data from a type study
and/or revision of other original material cited in the protolog of the present taxon.
Macroscopic descriptions in magenta are a combination of data from the protolog and
additional observations made on the exiccata during revision of the cited original
material.
The same field may also contain black text, which is data from a revision of the present
taxon (including non-type material and/or material not cited in the protolog).
Paragraphs of black text will be labeled if further subdivision of
this text is appropriate.
Olive text indicates a specimen that has not been
thoroughly examined (for example, for microscopic details) and marks other places in the text
where data is missing or uncertain.
The following material is from the protolog of the present taxon.
ecology
protolog Solitary.
At ca. 1700 m elev. On clay soil of cloud forest.
Ectomycorrhizal trees reported from this forest include
Guapira obtusata and Cocoloba
brasiliensis.
material examined
protolog: BRAZIL:
BAHIA—Chapada da Diamantina, Abaíra,
Catolés de Cima, Serra do Barbado, Mata do Tijuquinho,
[13°16′74″ S/ 41°54′29″ W, 1757 m], 9.i.2015, F. Wartchow
et al. [Wartchow 01/2015] (holotype, JPB 60532).
citations
—R. E. Tulloss
editors
RET
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name
Amanita viridissima
name status
nomen acceptum
author
Wartchow
english name
"Brazilian Blue-Green Lepidella"
images
photo
Dr. F. Wartchow - (1-2) Chapada da Diamantina, Abaíra, Catolés de Cima,
Serra do Barbado, Mata do Tijuquinho, Bahia, Brazil.
(holotype)
name
Amanita viridissima
name
Amanita viridissima
Spore data for collections provisionally identified as: Amanita viridissima Wartchow
Each spore data set is intended to comprise a set of measurements from a single specimen made by a single observer;
and explanations prepared for this site talk about specimen-observer pairs associated with each data set.
Combining more data into a single data set is non-optimal because it obscures observer differences
(which may be valuable for instructional purposes, for example) and may obscure instances in which
a single collection inadvertently contains a mixture of taxa.