Abstract

ALLGAYER, Heloisa; HILLER, Rafael Francisco  and  VALIATI, Victor Hugo. An epistemic analysis to elucidate the cryptic species complex. Conjectura: filos. e Educ. [online]. 2021, vol.26, e021005.  Epub Jan 10, 2024. ISSN 2178-4612.  https://doi.org/10.18226/21784612.v26.e021005.

Historically, taxonomy, which is the area responsible for describing new species, used a priori only morphological characteristics. Darwin (1872) already pointed out that there was a great divergence among taxonomists when they classified some organism as a species. When a new species is described, due to its historical weight, the morphological characters are considered as the first species demarcation criterion, however, with the advance of genetics and molecular biology, new methods are added. The use of multiple methods seems to be necessary for us to develop a contemporary taxonomy, so, a little more than a decade ago, the “integrative taxonomy” emerged, which refers to a taxonomy that aims to integrate all available data sources to frame the data. species limits. Data integration is not possible, as we do not have the technological capacity to do so. In view of this, we can interact the data through interactive taxonomy, which suggests, a way of treating the data under the assumption of different lines of evidence, through which the explanations have logical consequences that can be tested, mitigating the subjectivity of the subject in the process. Data interactions can overlap taxonomic descriptions, as they could encompass different phenomena and problem solving, thereby mitigating subjectivism. Therefore, in different fields, at least two indications would be necessary, which could be contained in two different approaches, one hypothetical and one by estimation. Such interpellations would contain evidence with different assumptions and dissimilar data characteristics, thus increasing the number of evidence, as well as improving the reliability of the argument. In this way, we can bring new species to light with a more objective bias and with less likelihood of error.

Keywords : Taxonomy; Cryptic species; Estimation; Hypothetical.

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