A near-infrared spectroscopy routine for unambiguous identification of cryptic ant species

作者：Martin‐Carl Kinzner, Herbert C. Wagner, Andrea Peskoller, Karl Moder, Floyd E. Dowell, Wolfgang Arthofer, Birgit C. Schlick‐Steiner, Florian M. Steiner · 发表于：PeerJ · 年份：2015 · DOI：10.7717/peerj.991 · 被引用次数：36 · 研究领域：Insect and Arachnid Ecology and Behavior、Plant and animal studies、Insect and Pesticide Research

Species identification-of importance for most biological disciplines-is not always straightforward as cryptic species hamper traditional identification. Fibre-optic near-infrared spectroscopy (NIRS) is a rapid and inexpensive method of use in various applications, including the identification of species. Despite its efficiency, NIRS has never been tested on a group of more than two cryptic species, and a working routine is still missing. Hence, we tested if the four morphologically highly similar, but genetically distinct ant species Tetramorium alpestre, T. caespitum, T. impurum, and T. sp. B, all four co-occurring above 1,300 m above sea level in the Alps, can be identified unambiguously using NIRS. Furthermore, we evaluated which of our implementations of the three analysis approaches, partial least squares regression (PLS), artificial neural networks (ANN), and random forests (RF), is most efficient in species identification with our data set. We opted for a 100% classification certainty, i.e., a residual risk of misidentification of zero within the available data, at the cost of excluding specimens from identification. Additionally, we examined which strategy among our implementations, one-vs-all, i.e., one species compared with the pooled set of the remaining species, or binary-decision strategies, worked best with our data to reduce a multi-class system to a two-class system, as is necessary for PLS. Our NIRS identification routine, based on a 100% identification certa...