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accession
locus
voucher
source
intro
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 derived from molecular
studies of Dr. L. V. Kudzma and other original
research of R. E. Tulloss.
Maine: Small group. In deep loose sand, with
Pinus and Quercus.
New Hampshire: In forest with Pinus
and Quercus.
New Jersey: In sandy soil of P.
rigida-Quercus barrens.
material examined
CANADA:
QUEBEC—Terrebonne - Terrebonne,
21.viii.1985 Carlo Famesi s.n. (CMMF 1767, nrITS seq'd.;
RET 085-5).
U.S.A.:
CONNECTICUT—Tolland Co. - Natchaug
St. For., 21.ix.1996 Susan Hopkins s.n.
[Tulloss 9-21-96-H] (RET 251-6).
MAINE—York Co. - Kennebunk, Kennebunk
Plains Wildlife Management Area [43.4102° N/
70.6156° W, 55 m], 26.vii.2015 L. V. Kudzma
LVK15156 (in herb. L. V. Kudzma,
nrITS seq'd.).
MASSACHUSETTS—Essex Co. - Lynn,
Lynn Woods, 7.ix.1990 Jura Strimaitis & R. E.
Tulloss [Tulloss 9-7-90-C] (RET 026-7).
NEW HAMPSHIRE—Rockingham Co. - 4 km
E of Pelham, Little Island Pond, Camp Runels,
19.ix.1993 COMA Babs Eldering s.n. (RET
106-6).
NEW JERSEY—Middlesex Co. - Jamesburg
Twp., Jamesburg Muni. Pk., ca. Helmetta
[40°23’07” N/ 74°25’48” W], 21.viii.1993
R. E. Tulloss 8-21-93-F (RET 096-9),
24.vii.1996 Britt
Carlson & R. E. Tulloss [Tulloss 7-24-96-J]
(RET 200-8), 21.ix.1986
R. E. Tulloss 9-21-86-A (L; RET 468-4).
discussion
The distinction between A. canadensis and
A. peckiana is not yet clear.
This species was called "species 39" in old
lists, keys, and correspondence of RET.
citations
—R. E. Tulloss
editors
RET
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name
Amanita canadensis
name status
nomen provisorum
author
Tulloss
name
Amanita canadensis
name
Amanita canadensis
Spore data for collections provisionally identified as: Amanita canadensis Tulloss
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.