Biology subjects

Noguerales, V.

Publications and source records attributed to Noguerales, V..

3 recordsLinked to original sources

bioRxiv2021

Genomic evidence of speciation by fusion linked to trophic niche expansion in a recent radiation of grasshoppers

Post-divergence gene flow can trigger a number of creative evolutionary outcomes, ranging from the transfer of beneficial alleles across species boundaries (i.e., adaptive introgression) to the formation of new species (i.e., hybrid speciation). While neutral and adaptive introgression has been broadly documented in nature, hybrid speciation is assumed to be rare and the evolutionary and ecological context facilitating this phenomenon still remains controversial. Through combining genomic and phenotypic data, we evaluate the hypothesis that the dual feeding regime (scrub legumes and gramineous herbs) of the taxonomically controversial grasshopper Chorthippus saulcyi algoaldensis resulted from hybridization between two sister taxa that exhibit contrasting host-plant specializations: C. binotatus (scrub legumes) and C. saulcyi (gramineous herbs). Genetic clustering analyses and inferences from coalescent-based demographic simulations confirmed that C. s. algoaldensis represents a uniquely evolving lineage and supported the ancient hybrid origin of this taxon (ca. 1.4 Ma), which provides a mechanistic explanation for its broader trophic niche and sheds light on its uncertain phylogenetic position. We propose a Pleistocene hybrid speciation model where range shifts resulting from climatic oscillations can promote the formation of hybrid swarms and facilitate its long-term persistence through geographic isolation from parental forms in topographically complex landscapes.

genetics↗

bioRxiv2021

Image-based taxonomic classification of bulk biodiversity samples using deep learning and domain adaptation

Complex bulk samples of invertebrates from biodiversity surveys present a great challenge for taxonomic identification, especially if obtained from unexplored ecosystems. High-throughput imaging combined with machine learning for rapid classification could overcome this bottleneck. Developing such procedures requires that taxonomic labels from an existing source data set are used for model training and prediction of an unknown target sample. Yet the feasibility of transfer learning for the classification of unknown samples remains to be tested. Here, we assess the efficiency of deep learning and domain transfer algorithms for family-level classification of below-ground bulk samples of Coleoptera from understudied forests of Cyprus. We trained neural network models with images from local surveys versus global databases of above-ground samples from tropical forests and evaluated how prediction accuracy was affected by: (a) the quality and resolution of images, (b) the size and complexity of the training set and (c) the transferability of identifications across very disparate source-target pairs that do not share any species or genera. Within-dataset classification accuracy reached 98% and depended on the number and quality of training images and on dataset complexity. The accuracy of between-datasets predictions was reduced to a maximum of 82% and depended greatly on the standardisation of the imaging procedure. When the source and target images were of similar quality and resolution, albeit from different faunas, the reduction of accuracy was minimal. Application of algorithms for domain adaptation significantly improved the prediction performance of models trained by non-standardised, low-quality images. Our findings demonstrate that existing databases can be used to train models and successfully classify images from unexplored biota, when the imaging conditions and classification algorithms are carefully considered. Also, our results provide guidelines for data acquisition and algorithmic development for high-throughput image-based biodiversity surveys.

zoology↗

bioRxiv2017

Ecological drivers of body size evolution and sexual size dimorphism in short-horned grasshoppers (Orthoptera: Acrididae)

Sexual size dimorphism (SSD) is widespread and variable in nature. Although female-biased SSD predominates among insects, the proximate ecological and evolutionary factors promoting this phenomenon remain largely unstudied. Here, we employ modern phylogenetic comparative methods on 8 subfamilies of Iberian grasshoppers (85 species) to examine the validity of different models of evolution of body size and SSD and explore how they are shaped by a suite of ecological variables (habitat specialization, substrate use, altitude) and/or constrained by different evolutionary pressures (female fecundity, strength of sexual selection, length of the breeding season). Body size disparity primarily accumulated late in the history of the group and did not follow a Brownian motion pattern, indicating the existence of directional evolution for this trait. We found support for the converse of Renschs rule across all taxa but not within the two most speciose subfamilies (Gomphocerinae and Oedipodinae), which showed an isometric pattern. Our results do not provide support for the fecundity or sexual selection hypotheses and we did not find evidence for significant effects of habitat use. Contrary to that expected, we found that species with narrower reproductive window are less dimorphic in size than those that exhibit a longer breeding cycle, suggesting that male protandry cannot solely account for the evolution of female-biased SSD in Orthoptera. Our study highlights the need to consider alternatives to the classical evolutionary hypotheses when trying to explain why in certain insect groups males remain small.

evolutionary biology↗