Biology subjects

Ramon-Laca, A.

Publications and source records attributed to Ramon-Laca, A..

6 recordsLinked to original sources

bioRxiv2025

Modeling cetacean eDNA distribution along the Washington coast using metabarcoding from opportunistic samples and generalized additive models

Effective cetacean conservation depends on robust monitoring, yet traditional visual and passive-acoustic surveys have constraints. We evaluated environmental DNA (eDNA) metabarcoding coupled with species distribution modeling (SDM) as a tool to study habitat use of cetaceans along the Washington State coast, USA. Seawater was collected at the surface and at a 50 m depth from 43 sites (86 samples) during the 2019 U.S.-Canada Integrated Ecosystem & Acoustic-Trawl Survey. A partial section of the mitochondrial control region was amplified with cetacean - specific primers, sequenced on an Illumina MiSeq, and taxonomically assigned with a curated reference database. Nine species were detected; we modelled the three most frequent: Pacific white-sided dolphin (Lagenorhynchus obliquidens) (10 detections), humpback whale (Megaptera novaeangliae) (8 detections), and Rissos dolphin (Grampus griseus) (6 detections). Binomial generalized additive models related presence-absence to bathymetry, distance to shore, longitude, slope, and sea-surface temperature; model performance was assessed with stratified five-fold cross-validation. SDMs explained 17-51% of null deviance and presented high specificity ([≥] 0.80). The Pacific white-sided dolphin showed the highest eDNA presence probabilities offshore, beyond the shelf break. Humpback whale eDNA presence probabilities showed hotspots along the shelf break with secondary high-probability patches in near-shore waters. Rissos dolphin eDNA presence probabilities were elevated in offshore zones characterized by steep bathymetric gradients, particularly northwest of the sampled transect. These spatial patterns are consistent with historical visual-acoustic records, suggesting that eDNA-informed SDMs can capture cetacean habitat use. This proof of concept indicates that combining eDNA detections with flexible SDMs could provide a cost-effective, non-invasive complement to conventional surveys and may offer a scalable pathway for marine-mammal monitoring and spatial planning.

genomics↗

bioRxiv2025

Quantitative, Multispecies Monitoring at a Continental Scale

Molecular data from environmental samples can reflect the abundance of species DNA, an index immediately relevant to natural-resources management at a broad geographic scale. These data commonly derive from assays designed and targeted for individual species (e.g., using qPCR or ddPCR), or from metabarcoding that use more general PCR primers to amplify many species simultaneously. Multispecies analyses make efficient use of field samples and laboratory time, and speak to inherently multispecies questions of management and ecological interest. However, unlike single-species techniques, metabarcoding alone generally reflects only the environmental DNA (eDNA) proportions of target-species DNA present, not their absolute quantities. Here, we combine qPCR and metabarcoding data derived from the same samples to estimate quantities of eDNA from many fish species along the US West Coast in three dimensions, demonstrating a technique of practical relevance for both management and ecology. We derive spatially explicit maps of eDNA abundances for 12 common species of ecological and management importance and point the way to quantitative surveys of wild species using molecules alone. We find that species distribution maps derived from eDNA largely mirror known species niches and known spatial distributions. Notably, our analyses indentify biodiversity hotspots that align with previously documented regions of ecological significance, such as the Columbia River plume and the Heceta Bank.

ecology↗

bioRxiv2024

Spatial and seasonal biodiversity variation in a large Mediterranean lagoon using environmental DNA metabarcoding through sponge tissue collection

Ecosystem monitoring is a fundamental tool to avert biodiversity loss, gathering valuable information that can be used to develop conservation policies, evaluating management outcomes, and guiding science-based decision-making. The Mar Menor costal lagoon (South-East of Spain) has experienced episodes of eutrophication due to intensive agriculture and other human activities, causing mass mortalities of marine fauna. In this scenario, biodiversity monitoring is crucial to evaluate the status of fauna and flora and take appropriate measures. Here, our main objective was to assess faunal composition and its spatial and temporal structure associated with the pillars used to support the built recreational well-being facilities along the Mar Menor. We capitalised on the many sea sponges that settle on these structures by collecting tissue samples for subsequent extraction of filtered environmental DNA (i.e. natural sampler DNA, nsDNA) in northern and southern areas of the lagoon, both in spring and summer. We metabarcoded all samples at the cytochrome oxidase subunit I gene (COI), and reliably identified 76 taxa belonging to nine different phyla, with annelids, poriferans, molluscs and cnidarians being the richest groups. We detected emblematic species of threatened status, such as pipefishes (genus Syngnathus) and the piddock clam, Pholas dactylus, and others known to become invasive, such as the ascidians Styela canopus and Botrylloides niger, the barnacle Amphibalanus amphitrite, and the polychaetes Branchiomma bairdi and Branchiomma boholense. The use of common and widely distributed sponges as natural eDNA samplers allowed us to characterise both spatial and temporal diversity, further emphasizing the importance of this low-cost approach to monitoring biological communities in shallow coastal ecosystems.

ecology↗

bioRxiv2022

Distinguishing Signal from Noise: Understanding Patterns of Non-Detections to Inform Accurate Quantitative Metabarcoding

Correcting for amplification biases in genetic metabarcoding data can yield quantitative estimates of template DNA concentrations. However, a major source of uncertainty in metabarcoding data is the presence of non-detections, where a technical PCR replicate fails to detect a species observed in other replicates. Such non-detections are an important special case of variability among technical replicates in metabarcoding data, particularly in environmental samples. While many sampling and amplification processes underlie observed variation in metabarcoding data, understanding the causes of non-detections is an important step in distinguishing signal from noise in metabarcoding studies. Here, we use both simulated and empirical data to 1) develop a qualitative understanding of how non-detections arise in metabarcoding data, 2) outline steps to recognize uninformative data in practice, and 3) identify the conditions under which amplicon sequence data can reliably detect underlying biological signals. We show in both simulations and empirical data that, for a given species, the rate of non-detections among technical replicates is a function of both the template DNA concentration and species-specific amplification efficiency. Consequently, we conclude metabarcoding datasets are strongly affected by (1) deterministic amplification biases during PCR and (2) stochastic sampling of amplicons during sequencing -- both of which we can model -- but also by (3) stochastic sampling of rare molecules prior to PCR, which remains a frontier for quantitative metabarcoding. Our results highlight the importance of estimating species-specific amplification efficiencies and critically evaluating patterns of non-detection in metabarcoding datasets to better distinguish environmental signal from the noise inherent in molecular detections of rare targets.

molecular biology↗

bioRxiv2022

Toward Quantitative Metabarcoding

Amplicon-sequence data from environmental DNA (eDNA) and microbiome studies provides important information for ecology, conservation, management, and health. At present, amplicon-sequencing studies - known also as metabarcoding studies, in which the primary data consist of targeted, amplified fragments of DNA sequenced from many taxa in a mixture - struggle to link genetic observations to underlying biology in a quantitative way, but many applications require quantitative information about the taxa or systems under scrutiny. As metabarcoding studies proliferate in ecology following decades of microbial and microbiome work using similar techniques, it becomes more important to develop ways ot make them quantitative to ensure that their conclusions are adequately supported. Here we link previously disparate sets of techniques for making such data quantitative, showing that the underlying PCR mechanism explains observed patterns of amplicon data in a general way. By modeling the process through which amplicon-sequence data arises, rather than transforming the data post-hoc, we show how to estimate the starting DNA proportions from a mixture of many taxa. We illustrate how to calibrate the model using mock communities and apply the approach to simulated data and a series of empirical examples. Our approach opens the door to improve the use of metabarcoding data in a wide range of applications in ecology, public health, and related fields.

ecology↗

bioRxiv2019

Seagrass mediates microalgal community structure at a distance

Seagrass beds provide a variety of ecosystem services, both within and outside the bounds of the habitat itself. Here we use environmental DNA (eDNA) amplicons to analyze a broad cross-section of taxa from ecological communities in and immediately surrounding eelgrass (Zostera marina). Sampling seawater along transects extending alongshore outward from eelgrass beds, we demonstrate that eDNA provides meter-scale resolution of communities in the field. We evaluate eDNA abundance indices for thirteen major phylogenetic groups of marine and estuarine taxa along these transects, finding highly local changes linked with proximity to Z. marina for a diverse group of dinoflagellates, and for no other group of taxa. Eelgrass habitat is consistently associated with dramatic reductions in dinoflagellate abundance both within the contiguous beds and for at least fifteen meters outside, relative to nearby sites without eelgrass. These results are consistent with the hypothesis that eelgrass-associated communities have allelopathic effects on dinoflagellates, and that these effects can extend in a halo beyond the bounds of the contiguous beds. Because many dinoflagellates are capable of forming Harmful Algal Blooms (HABs) toxic to humans and other animal species, the apparent salutary effect of eelgrass habitat on neighboring waters has important implications for public health as well as shellfish aquaculture and harvesting.

ecology↗