Interploidy gene flow involving the sexual-asexual cycle facilitates the diversification of gynogenetic triploid Carassius fish

Asexual vertebrates are rare and at risk of extinction due to their restricted adaptability through the loss of genetic recombination. We explore the mechanisms behind the generation and maintenance of genetic diversity in triploid asexual (gynogenetic) Carassius auratus fish, which is widespread in East Asian fresh waters and exhibits one of the most extensive distribution among asexual vertebrates despite its dependence on host sperm. Our analyses of genetic composition using dozens of genetic markers and genome-wide transcriptome sequencing uncover admixed genetic composition of Japanese asexual triploid Carassius consisting of both the diverged Japanese and Eurasian alleles, suggesting the involvement of Eurasian lineages in its origin. However, coexisting sexual diploid relatives and asexual triploids in Japan show regional genetic similarity in both mitochondrial and nuclear markers. These results are attributed to a unique unidirectional gene flow from diploids to sympatric triploids, with the involvement of occasional sexual reproduction. Additionally, the asexual triploid shows a weaker population structure than the sexual diploid, and multiple triploid lineages coexist in most Japanese rivers. The generated diversity via repeated interploidy gene flow as well as an increased establishment of immigrants is assumed to offset the cost of asexual reproduction and might contribute to the successful broad distribution of this asexual vertebrate.

Spatiotemporal Changes of the Environmental DNA Concentrations of Amphidromous Fish Plecoglossus altivelis altivelis in the Spawning Grounds in the Takatsu River, Western Japan

The Ayu Plecoglossus altivelis altivelis is an amphidromous fish that is not only the most important commercial fishery species in Japanese rivers but also has a high economic value in recreational fishing. However, the degradation of its spawning grounds has caused a decrease in its abundance. In this study, we used environmental DNA (eDNA) to monitor the Ayu in the Takatsu River in Japan to (1) identify the spawning season in three known spawning grounds, (2) clarify changes in the main spawning grounds during the spawning season, and (3) discover unknown spawning grounds. We collected 1 L of the surface river water at three known spawning grounds nine times in 2018 and seven times in 2019 in the lower reaches of the Takatsu River. We also collected samples from seven unknown sites in 2018. The water samples were filtered through glass fiber filters. Total eDNA was extracted from each filtered sample and a Real-time quantitative PCR was performed with the specific primers and probe for Ayu. The results of the eDNA analyses showed that (1) the spawning season was in November in 2018 and in September in 2019. (2) One site was used as a spawning ground in both the early and the late spawning season, depending on the year. At the second site, the frequency of use changed year by year. The third site was the main spawning ground in the middle to late spawning season every year. From these results, we elucidated that some spawning grounds are used regularly every year, while the use of others varies year by year. (3) In five of the seven unknown sites, the nighttime eDNA concentrations were high at least once during the four surveys, suggesting that these sites may have functioned as spawning grounds. In particular, one site could be an important new spawning ground.

Colorisation of archival aerial imagery using deep learning

<p>Archival imagery dating back to the mid-twentieth century holds information that pre-dates urban expansion and the worst impacts of climate change.  In this research, we examine deep learning colorisation methods applied to historical aerial images in Japan.  Specifically, we attempt to colorize monochrome images of river basins by applying the method of Neural Style Transfer (NST).    First, we created RGB orthomosaics (1m) for reaches of 3 Japanese rivers, the Kurobe, Ishikari, and Kinu rivers.  From the orthomosaics, we extract 60 thousand image tiles of `100 x100` pixels in order to train the CNN used in NST.  The Image tiles were classified into 6 classes: urban, river, forest, tree, grass, and paddy field.  Second, we use the VGG16 model pre-trained on ImageNet data in a transfer learning approach where we freeze a variable number of layers.  We fine-tuned the training epochs, learning rate, and frozen layers in VGG16 in order to derive the optimal CNN used in NST.  The fine tuning resulted in the F-measure accuracy of 0.961, 0.947, and 0.917 for the freeze layer in 7,11,15, respectively.  Third, we colorize monochrome aerial images by the NST with the retrained model weights.  Here used RGB images for 7 Japanese rivers and the corresponding grayscale versions to evaluate the present NST colorization performance.  The RMSE between the RGB and resultant colorized images showed the best performance with the model parameters of lower content layer (6), shallower freeze layer (7), and larger style/content weighting ratio (1.0 x10⁵).  The NST hyperparameter analysis indicated that the colorized images became rougher when the content layer selected deeper in the VGG model.  This is because the deeper the layer, the more features were extracted from the original image.  It was also confirmed that the Kurobe and Ishikari rivers indicated higher accuracy in colorisation.  It might come from the fact that the training dataset of the fine tuning was extracted from these river images.  Finally, we colorized historical monochrome images of Kurobe river with the best NST parameters, resulting in quality high enough compared with the RGB images.  The result indicated that the fine tuning of the NST model could achieve high performance to proceed further land cover classification in future research work.</p>

Tissue Hydrogen Peroxide Concentration Can Explain the Invasiveness of Aquatic Macrophytes: A Modeling Perspective

In recent years, an invasive macrophyte, Egeria densa, has overwhelmingly colonized some midstream reaches of Japanese rivers. This study was designed to determine how E. densa has been able to colonize these areas and to assess the environmental conditions that limit or even prevent colonization. Invasive species (E. densa and Elodea nuttallii), and Japanese native species (Myriophyllum spicatum, Ceratophyllum demersum, and Potamogeton crispuss) were kept in experimental tanks and a flume with different environmental conditions. Tissue hydrogen peroxide (H2O2) concentrations were measured responding to either individual or multiple environmental factors of light intensity, water temperature, and water flow velocity. In addition, plants were sampled in rivers across Japan, and environmental conditions were measured. The H2O2 concentration increased in parallel to the increment of unpreferable levels of each abiotic factor, and the trend was independent of other factors. The total H2O2 concentration is provided by the sum of contribution of each factor. Under increased total H2O2 concentration, plants first started to decrease in chlorophyll concentration, then reduce their growth rate, and subsequently reduce their biomass. The H2O2 concentration threshold, beyond which degradation is initiated, was between 15 and 20 µmol/gFW regardless of the environmental factors. These results highlight the potential efficacy of total H2O2 concentration as a proxy for the overall environmental condition. In Japanese rivers, major environmental factors limiting macrophyte colonization were identified as water temperature, high solar radiation, and flow velocity. The relationship between the unpreferable levels of these factors and H2O2 concentration was empirically obtained for these species. Then a mathematical model was developed to predict the colonization area of these species with environmental conditions. The tissue H2O2 concentration decreases with increasing temperature for E. densa and increases for other species, including native species. Therefore, native species grow intensively in spring; however, they often deteriorate in summer. For E. densa, on the other hand, H2O2 concentration decreases with high water temperature in summer, allowing intensive growth. High solar radiation increases the H2O2 concentration, deteriorating the plant. Although the H2O2 concentration of E. densa increases with low water temperature in winter, it can survive in deep water with low H2O2 concentration due to diffused solar radiation. Currently, river rehabilitation has created a deep zone in the channel, which supports the growth and spreading of E. densa.