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Abstract Detail


Hearn, David [1], Sanderson, Michael [2], McMahon, Michelle [3].

Range modeling of entire floras to estimate fine-scale patterns of alpha diversity across the landscape.

Understanding landscape-scale patterns of biological diversity has been a focus of ecological research since its inception. Recently, the prediction of fine-scale patterns of biological diversity and community composition has been made possible through the combined availability of massive biological specimen collections databases, range model inference improvements, and highly -resolved interpolated climate data. Our goal was to estimate angiosperm species diversity and plant community species composition for any arbitrary region in Arizona. We focused our efforts on Arizona due to a large plant specimen database that we compiled (over 1.2 million specimens). Using a computer cluster, we inferred range models of species in the flora of Arizona which have at least 10 georeferenced specimens in the database (4,013 species) using the criterion of maximum entropy. We developed and compared 11 approaches to assess regional angiosperm alpha diversity. Threshold methods tended to overestimate diversity, whereas probabilistic methods that estimated expected regional diversity tended to underestimate diversity. Our approach can identify biodiversity hot spots, potentially in regions with poor previous sampling effort.

Broader Impacts:

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Related Links:
Biodiversity Informatics Portal: Diversity Mapper

1 - Towson University, Department of Biological Sciences, 8000 York Rd, Baltimore, MD, 21252, USA
2 - University of Arizona, Ecology and Evolutionary Biology, Tucson, AZ, 85721, USA
3 - University of Arizona, Department of Plant Sciences and UA Herbarium, 1140 E. South Campus Dr., Tucson, Arizona, 85721, USA

range model
species diversity
Hot spot
Flora of Arizona
maximum entropy
species-time curve
specimen database.

Presentation Type: Oral Paper:Papers for Topics
Session: 28
Location: 552B/Convention Center
Date: Tuesday, August 3rd, 2010
Time: 8:15 AM
Number: 28002
Abstract ID:577

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