Are all species necessary to reveal ecologically important patterns?

Pos, Edwin and Guevara Andino, Juan Ernesto and Sabatier, Daniel and Molino, Jean-François and Pitman, Nigel and Mogollón, Hugo and Neill, David and Cerón, Carlos and Rivas, Gonzalo and Di Fiore, Anthony and Thomas, Raquel and Tirado, Milton and Young, Kenneth R. and Wang, Ophelia and Sierra, Rodrigo and García-Villacorta, Roosevelt and Zagt, Roderick and Palacios, Walter and Aulestia, Milton and Ter Steege, Hans (2014) Are all species necessary to reveal ecologically important patterns? Ecology and Evolution, 4 (24). pp. 4626-4636. ISSN 2045-7758

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Abstract

While studying ecological patterns at large scales, ecologists are often unable to identify all collections, forcing them to either omit these unidentified records entirely, without knowing the effect of this, or pursue very costly and time-consuming efforts for identifying them. These "indets" may be of critical importance, but as yet, their impact on the reliability of ecological analyses is poorly known. We investigated the consequence of omitting the unidentified records and provide an explanation for the results. We used three large-scale independent datasets, (Guyana/ Suriname, French Guiana, Ecuador) each consisting of records having been identified to a valid species name (identified morpho-species - IMS) and a number of unidentified records (unidentified morpho-species - UMS). A subset was created for each dataset containing only the IMS, which was compared with the complete dataset containing all morpho-species (AMS: = IMS + UMS) for the following analyses: species diversity (Fisher's alpha), similarity of species composition, Mantel test and ordination (NMDS). In addition, we also simulated an even larger number of unidentified records for all three datasets and analyzed the agreement between similarities again with these simulated datasets. For all analyses, results were extremely similar when using the complete datasets or the truncated subsets. IMS predicted ≥91% of the variation in AMS in all tests/analyses. Even when simulating a larger fraction of UMS, IMS predicted the results for AMS rather well. Using only IMS also out-performed using higher taxon data (genus-level identification) for similarity analyses. Finding a high congruence for all analyses when using IMS rather than AMS suggests that patterns of similarity and composition are very robust. In other words, having a large number of unidentified species in a dataset may not affect our conclusions as much as is often thought.

Item Type:	Article
Publisher’s Statement:	© 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
ID number or DOI:	10.1002/ece3.1246
Subjects:	Q Science > QH Natural history Q Science > QL Zoology
NAU Depositing Author Academic Status:	Faculty/Staff
Department/Unit:	College of Engineering, Forestry, and Natural Science > School of Earth Sciences and Environmental Sustainability
Date Deposited:	14 Oct 2015 01:15
URI:	http://openknowledge.nau.edu/id/eprint/662

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