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Abstract Detail


Kasperski, Anne [1], Hasenstab-Lehman, Kristen [2], Guilliams, C. Matt [2].

Biogeographic and Morphometric analyses of the California Channel Island endemic Cryptantha (Boraginaceae).

The islands off the Pacific Coast of Alta and Baja California represent a diverse range of ecosystems across a wide latitudinal gradient, and are well known for their endemic flora. Among these are a number of taxa in Cryptantha (Boraginaceae). The genus comprises 102 species and is restricted to western North and South America. The six minimum rank taxa that are endemic to the Channel Islands have never been the focus of phylogenetic study. We know little about the number and timing of colonization events in the genus, or morphological features associated with island endemism. For this study, we sequenced nrITS for two missing taxa, and combined it with existing data from previous studies in this clade to assess history of dispersal to and possible radiation across the islands. Additionally, the loss of features commonly associated with dispersal such as texture and size, a phenomenon noted in other island systems, was tested for Channel Island Cryptantha. To examine the relationship between presence on an island and loss of traits potentially associated with dispersal, we performed comparative phylogenetic analyses of fruit features using our best maximum likelihood tree. Images of nutlet features were obtained using light microscopy and measured with scikit-image library and ImageJ software. We then place the evolution of morphological features of Channel Island Cryptantha into context of the patterns noted in other groups endemic to the archipelago.

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1 - Santa Barbara Botanic Garden, Conservation and Research, 1212 Mission Canyon Rd, Santa Barbara, CA, 93105, United States
2 - Santa Barbara Botanic Garden, Conservation and Research , 1212 Mission Canyon Rd, Santa Barbara, CA, 93105, USA

island biology.

Presentation Type: Poster
Session: P3, Systematics Posters
Location: Virtual/Virtual
Date: Wednesday, July 21st, 2021
Time: 5:00 PM(EDT)
Number: P3SY010
Abstract ID:861
Candidate for Awards:None

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