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Excluding spatial sampling bias does not eliminate oversplitting in DNA-based species delimitation analyses.

ABSTRACT: DNA barcoding and DNA-based species delimitation are major tools in DNA taxonomy. Sampling has been a central debate in this context, because the geographical composition of samples affects the accuracy and performance of DNA barcoding. Performance of complex DNA-based species delimitation is to be tested under simpler conditions in absence of geographic sampling bias. Here, we present an empirical dataset sampled from a single locality in a Southeast-Asian biodiversity hotspot (Laos: Phou Pan mountain). We investigate the performance of various species delimitation approaches on a megadiverse assemblage of herbivorous chafer beetles (Coleoptera: Scarabaeidae) to infer whether species delimitation suffers in the same way from exaggerate infraspecific variation despite the lack of geographic genetic variation that led to inconsistencies between entities from DNA-based and morphology-based species inference in previous studies. For this purpose, a 658 bp fragment of the mitochondrial cytochrome c oxidase subunit 1 (cox1) was analyzed for a total of 186 individuals of 56 morphospecies. Tree-based and distance-based species delimitation methods were used. All approaches showed a rather limited match ratio (max. 77%) with morphospecies. Poisson tree process (PTP) and statistical parsimony network analysis (TCS) prevailingly over-splitted morphospecies, while 3% clustering and Automatic Barcode Gap Discovery (ABGD) also lumped several species into one entity. ABGD revealed the highest congruence between molecular operational taxonomic units (MOTUs) and morphospecies. Disagreements between morphospecies and MOTUs have to be explained by historically acquired geographic genetic differentiation, incomplete lineage sorting, and hybridization. The study once again highlights how important morphology still is in order to correctly interpret the results of molecular species delimitation.

SUBMITTER: Lukic D

PROVIDER: S-EPMC8328443 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:AimPresence records from surveys with spatially heterogeneous sampling intensity are a key challenge for species distribution models (SDMs). When sex groups differ in their habitat association, the correction of the spatial bias becomes important for preventing model predictions that are biased toward one sex. The objectives of this study were to investigate the effectiveness of existing correction methods for spatial sampling bias for SDMs when male and female have different habitat preferences.LocationJura massif, France.MethodsWe used a spatially sex-segregated virtual species to understand the effect of three sampling designs (spatially biased, uniform random, and systematic), and two correction methods (targeted background points, and distance to trajectories) on estimated habitat preferences, sex ratios, and prediction accuracy. We then evaluated these effects for two empirical Capercaillie (Tetrao urogallus) presence-only datasets from a systematic and a spatially biased sampling design.ResultsSampling design strongly affected parameter estimation accuracy for the virtual species: noncorrected spatially biased sampling resulted in biased estimates of habitat association and sex ratios. Both established methods of bias correction were successful in the case of virtual species, with the targeted correction methods showing stronger correction, as it more closely followed the simulated decay of detectability with distance from sampling locations. On the Capercaillie dataset, only the targeted background points method resulted in the same sex ratio estimate for the spatially biased sampling design as for the spatially unbiased sampling.Main conclusionsWe suggest that information on subgroups with distinct habitat associations should be included in SDMs analyses when possible. We conclude that current methods for correcting spatially biased sampling can improve estimates of both habitat association and subgroup ratios (e.g., sex and age), but that their efficiency depends on their ability to well represent the spatial observation bias.

Project description:Delimiting species boundaries among closely related lineages often requires a range of independent data sets and analytical approaches. Similar to other organismal groups, robust species circumscriptions in fungi are increasingly investigated within an empirical framework. Here we attempt to delimit species boundaries in a closely related clade of lichen-forming fungi endemic to Asia, the Hypogymnia hypotrypa group (Parmeliaceae). In the current classification, the Hypogymnia hypotrypa group includes two species: H. hypotrypa and H. flavida, which are separated based on distinctive reproductive modes, the former producing soredia but absent in the latter. We reexamined the relationship between these two species using phenotypic characters and molecular sequence data (ITS, GPD, and MCM7 sequences) to address species boundaries in this group. In addition to morphological investigations, we used Bayesian clustering to identify potential genetic groups in the H. hypotrypa/H. flavida clade. We also used a variety of empirical, sequence-based species delimitation approaches, including: the "Automatic Barcode Gap Discovery" (ABGD), the Poisson tree process model (PTP), the General Mixed Yule Coalescent (GMYC), and the multispecies coalescent approach BPP. Different species delimitation scenarios were compared using Bayes factors delimitation analysis, in addition to comparisons of pairwise genetic distances, pairwise fixation indices (FST). The majority of the species delimitation analyses implemented in this study failed to support H. hypotrypa and H. flavida as distinct lineages, as did the Bayesian clustering analysis. However, strong support for the evolutionary independence of H. hypotrypa and H. flavida was inferred using BPP and further supported by Bayes factor delimitation. In spite of rigorous morphological comparisons and a wide range of sequence-based approaches to delimit species, species boundaries in the H. hypotrypa group remain uncertain. This study reveals the potential limitations of relying on distinct reproductive strategies as diagnostic taxonomic characters for Hypogymnia and also the challenges of using popular sequence-based species delimitation methods in groups with recent diversification histories.

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Excluding spatial sampling bias does not eliminate oversplitting in DNA-based species delimitation analyses.

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