Biology subjects

Cuevas, J.

Publications and source records attributed to Cuevas, J..

3 recordsLinked to original sources

bioRxiv2025

Hidden Diversity of Threatened Sharks and Rays in the Global Meat Trade

International wildlife trade is a major source of biodiversity loss, yet many species lie hidden within aggregated data that conceals trade impacts. We overcome this problem for the largest vertebrate wildlife trade globally - shark and ray meat - comprising 438 538 mt yr-1 across more than 150 species, 76% of which are Threatened. Revealed trade contains greater quantities of skates (+10%), hammerheads (+8%), and smoothhounds, dogfishes & tope (+5%), and fewer pelagic sharks (-38%) than previously known. Shorttail yellownose skate, smoothound, silky, mako, and blue sharks are the most underreported meat species, due to aggregated landings from China, Argentina, Japan, and Indonesia, demonstrating international trade in shark and ray meat as a diverse, pervasive, and previously hidden source of fishing mortality for many threatened species.

ecology↗

bioRxiv2024

Complete genomes of DNA viruses in faecal samples from small terrestrial mammals in Spain

Viromics studies are allowing us to understand not only the enormous diversity of the virosphere, but also the potential threat posed by emerging viruses. Regarding the latter, the main concern lies in monitoring the presence of RNA viruses, but the zoonotic potential of some DNA viruses, on which we have focused in the present study, should also be highlighted. For this purpose, we analysed 160 faecal samples from 14 species belonging to three orders of small terrestrial mammals (i.e. Rodentia, Lagomorpha and Eulypotyphla). This allowed us to identify a total of 25 complete or near-complete genomes belonging to the families Papillomaviridae, Polyomaviridae, Adenoviridae, Circoviridae and Genomoviridae, 18 of which could be considered new species or types. Our results provide a significant increase in the number of complete genomes of DNA viruses of European origin with zoonotic potential in databases, which are at present clearly under-represented compared to RNA viruses.

microbiology↗

bioRxiv2022

Modeling genotype environment interaction for single- and multi-trait genomic prediction in potato (Solanum tuberosum L.)

In this study we extend research on genomic prediction (GP) to polysomic polyploid plant species with the main objective to investigate single trait (ST) versus multi-trait (MT) for multi-environment (ME) models for the combination of three locations in Sweden (Helgeg[a]rden [HEL], Mosslunda [MOS], Ume[a] [UM]) over two year-trials (2020, 2021) of 253 potato cultivars and breeding clones for five tuber weight traits and two tuber flesh quality characteristics. This research investigated the GP of four genome-based prediction models with genotype xenvironment interactions (GE): (1) single trait reaction norm model (M1), (2) single trait model considering covariances between environments (M2), (3) single trait M2 extended to include a random vector that utilizes the environmental covariances (M3) and (4) multi-trait model with GE (M4). Several prediction problems were analyzed for each of the GP accuracy of the four models. Results of the prediction of traits in HEL, the high yield potential testing site in 2021, show that the best predicted traits were tuber flesh starch (%), weight of tuber above 60 or below 40 mm in size, and total tuber weight. In terms of GP, accuracy model M4 gave the best prediction accuracy in three traits, namely tuber weight of 40-50 or above 60 mm in size, and total tuber weight and very similar in the starch trait. For MOS in 2021, the best predictive traits were starch, weight of tuber above 60, 50-60, or below 40 mm in size, and total tuber weight. MT model M4 was the best GP model based on its accuracy when some cultivars are observed in some traits. For GP accuracy of traits in UM in 2021, the best predictive traits were weight of tuber above 60, 50-60, or below 40 mm in size and the best model was MT M4 followed by models ST M3 and M2.

plant biology↗