DNA metabarcoding has been widely used to access and monitor species. However, several challenges remain open for its mainstream application in ecological studies, particularly when dealing with a quantitative approach. In a From the Cover article in this issue of Molecular Ecology, Mariac et al. (2021) report species-level ichthyoplankton dynamics for 97 fish species from two Amazon river basins using a clever quantitative metabarcoding approach employing a probe capture method. They clearly show that most species spawned during the floods, although ~20% also spawned mainly during the receding period and some other year-round, but interestingly, species from the same genus reproduced in distinct periods (i.e., inverse phenology). Opportunistically, Mariac et al. (2021) reported that during an intense hydrological anomaly, several species had a sharp reduction in spawning activity, demonstrating a quick response to environmental cues. This is an interesting result since the speed at which fish species can react to environmental changes, during the spawning period, is largely unknown. Thus, this study brings remarkable insights into basic life history information that is imperative for proposing strategies that could lead to a realistic framework for sustainable fisheries management practices and conservation, fundamental for an understudied and threatened realm, such as the Amazon River basin.
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http://dx.doi.org/10.1111/mec.16387 | DOI Listing |
Many sharks, rays and skates are highly threatened and vulnerable to overexploitation, as such reliable monitoring of elasmobranchs is key to effective management and conservation. The mobile and elusive nature of these species makes monitoring challenging, particularly in temperate waters with low visibility. Environmental DNA (eDNA) methods present an opportunity to study these species in the absence of visual identification or invasive techniques.
View Article and Find Full Text PDFData Brief
February 2025
Marine Research Institute, Klaipėda University, H. Manto 84, 92294 Klaipėda, Lithuania.
Over the last few decades, climate change in Svalbard (European Arctic) has led to the emergence and growth of periglacial coastal lagoons in the place of retreating glaciers. In these emerging water bodies, new ecosystems are formed, consisting of elements presumably entering the lagoon from the melting glacier, the surrounding tundra water bodies and the coastal ocean. The data presented here were collected from an emerging lagoon in the western region of Spitsbergen, Svalbard, situated between the retreating Eidembreen Glacier and Eidembukta Bay in 2022-2023.
View Article and Find Full Text PDFCurr Microbiol
January 2025
Department of Tropical Medicine, Institute of Tropical Medicine, Arthropods of Medical Importance Resource Bank, Yonsei University College of Medicine, Yonsei-Ro 50-1, Seodaemun-Gu, Seoul, 03722, Republic of Korea.
Interactions between microbial communities and the host can modulate mosquito biology, including vector competence. Therefore, future vector biocontrol measures will utilize these interactions and require extensive monitoring of the mosquito microbiome. Metabarcoding strategies will be useful for conducting vector monitoring on a large scale.
View Article and Find Full Text PDFPLoS One
January 2025
Bio Bureau Biotechnology, Rio de Janeiro, Rio de Janeiro, Brazil.
Monitoring biodiversity on a large scale, such as in hydropower reservoirs, poses scientific challenges. Conventional methods such as passive fishing gear are prone to various biases, while the utilization of environmental DNA (eDNA) metabarcoding has been restricted. Most eDNA studies have primarily focused on replicating results from traditional methods, which themselves have limitations regarding representativeness and bias.
View Article and Find Full Text PDFIn recent years, DNA metabarcoding has been used for a more efficient assessment of bulk samples. However, there remains a paucity of studies examining potential disparities in species identification methodologies. Here, we explore the outcomes of diverse clustering and filtering techniques on data from a non-destructive metabarcoding approach, compared to species-level morphological identification of Brachycera (Diptera) and Hymenoptera of two bulk samples collected with Malaise traps.
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