Dataset Information

Using eDNA to biomonitor the fish community in a tropical oligotrophic lake.

ABSTRACT: Environmental DNA (eDNA) is an effective approach for detecting vertebrates and plants, especially in aquatic ecosystems, but prior studies have largely examined eDNA in cool temperate settings. By contrast, this study employs eDNA to survey the fish fauna in tropical Lake Bacalar (Mexico) with the additional goal of assessing the possible presence of invasive fishes, such as Amazon sailfin catfish and tilapia. Sediment and water samples were collected from eight stations in Lake Bacalar on three occasions over a 4-month interval. Each sample was stored in the presence or absence of lysis buffer to compare eDNA recovery. Short fragments (184-187 bp) of the cytochrome c oxidase I (COI) gene were amplified using fusion primers and then sequenced on Ion Torrent PGM or S5 before their source species were determined using a custom reference sequence database constructed on BOLD. In total, eDNA sequences were recovered from 75 species of vertebrates including 47 fishes, 15 birds, 7 mammals, 5 reptiles, and 1 amphibian. Although all species are known from this region, six fish species represent new records for the study area, while two require verification. Sequences for five species (2 birds, 2 mammals, 1 reptile) were only detected from sediments, while sequences from 52 species were only recovered from water. Because DNA from the Amazon sailfin catfish was not detected, we used a mock eDNA experiment to confirm our methods would enable its detection. In summary, we developed protocols that recovered eDNA from tropical oligotrophic aquatic ecosystems and confirmed their effectiveness in detecting fishes and diverse species of vertebrates.

SUBMITTER: Valdez-Moreno M

PROVIDER: S-EPMC6476559 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Using eDNA to biomonitor the fish community in a tropical oligotrophic lake.

Valdez-Moreno Martha M Ivanova Natalia V NV Elías-Gutiérrez Manuel M Pedersen Stephanie L SL Bessonov Kyrylo K Hebert Paul D N PDN

PloS one 20190422 4

Environmental DNA (eDNA) is an effective approach for detecting vertebrates and plants, especially in aquatic ecosystems, but prior studies have largely examined eDNA in cool temperate settings. By contrast, this study employs eDNA to survey the fish fauna in tropical Lake Bacalar (Mexico) with the additional goal of assessing the possible presence of invasive fishes, such as Amazon sailfin catfish and tilapia. Sediment and water samples were collected from eight stations in Lake Bacalar on thre ...[more]

PMID: 31009491

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Project description:BackgroundOver the past decade, environmental DNA (eDNA) has become a resourceful tool in conservation and biomonitoring. Environmental DNA has been applied in a variety of environments, but the application to studies of marine fish, particularly at tropical latitudes, are limited. Since many commercially important Caribbean fishes are overexploited, these species are optimal candidates to explore the use of this method as a biomonitoring tool. Specifically, for many of these species, the formation of fish spawning aggregations (FSAs) marks a critical life history event where fishes will gather in large numbers for reproduction. These FSAs are ephemeral in nature, lasting only a few days, but are predictable in time and space which makes them susceptible to overfishing.MethodsIn this study, we test the feasibility of using an eDNA sampling approach (water and sediment collection) to detect the presence of known FSAs off the west coast of Puerto Rico, with cytochrome c oxidase subunit 1 (CO1) and 12S rRNA (12S) primers designed to target specific species. A total of 290 eDNA samples were collected and, of those, 206 eDNA samples were processed. All eDNA samples varied in DNA concentration, both between replicates and collection methods. A total of 12 primer sets were developed and tested using traditional PCR and qPCR.ResultsDespite validation of primer accuracy and sample collection during known peak spawning times, the use of traditional PCR and qPCR with both molecular markers failed to produce species-specific amplification. Thus, a trial test was conducted using the CO1 primers in which target fish DNA was 'spiked' at various concentrations into the respective eDNA samples to determine the target species DNA concentration limit of detection. Upon successful amplification of the trial, results indicated that eDNA samples were below the detection threshold of our methods, suggesting that the number of fish present at the spawning aggregations was inadequate for single-species detection methods. In addition, elements such as the unavoidable presence of non-target DNA, oceanic environmental conditions, shedding rates of target fish, among other biotic and abiotic factors could have affected DNA persistence and degradation rates at the sites.ConclusionWe provide recommendations for species-specific fish detection in lower latitudes, and suggestions for studies aiming to monitor or detect fish spawning aggregations using eDNA sampling.

Project description:Active sulfate-reducing microorganisms (SRM) in freshwater sediments are under-examined, despite the well-documented cryptic sulfur cycle occurring in these low-sulfate habitats. In Lake Constance sediment, sulfate reduction rates of up to 1,800 nmol cm-3 day-1 were previously measured. To characterize its SRM community, we used a tripartite amplicon sequencing approach based on 16S rRNA genes, 16S rRNA, and dsrB transcripts (encoding the beta subunit of dissimilatory sulfite reductase). We followed the respective amplicon dynamics in four anoxic microcosm setups supplemented either with (i) chitin and sulfate, (ii) sulfate only, (iii) chitin only, or (iv) no amendment. Chitin was used as a general substrate for the whole carbon degradation chain. Sulfate turnover in sulfate-supplemented microcosms ranged from 38 to 955 nmol day-1 (g sediment f. wt.)-1 and was paralleled by a decrease of 90-100% in methanogenesis as compared to the respective methanogenic controls. In the initial sediment, relative abundances of recognized SRM lineages accounted for 3.1 and 4.4% of all bacterial 16S rRNA gene and 16S rRNA sequences, respectively. When normalized against the 1.4 × 108 total prokaryotic 16S rRNA gene copies as determined by qPCR and taking multiple rrn operons per genome into account, this resulted in approximately 105-106 SRM cells (g sediment f. wt.)-1. The three amplicon approaches jointly identified Desulfobacteraceae and Syntrophobacteraceae as the numerically dominant and transcriptionally most active SRM in the initial sediment. This was corroborated in the time course analyses of sulfate-consuming sediment microcosms irrespective of chitin amendment. Uncultured dsrAB family-level lineages constituted in sum only 1.9% of all dsrB transcripts, with uncultured lineage 5 and 6 being transcriptionally most active. Our study is the first holistic molecular approach to quantify and characterize active SRM including uncultured dsrAB lineages not only in Lake Constance but for lake sediments in general.

Project description:Near-term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water quality. Importantly, ecological forecasts can identify where there is uncertainty in the forecasting system, which is necessary to improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance introduced by different sources, including specification of the model structure, errors in driver data, and estimation of current states (initial conditions). Uncertainty partitioning could be particularly useful in improving forecasts of highly variable cyanobacterial densities, which are difficult to predict and present a persistent challenge for lake managers. As cyanobacteria can produce toxic and unsightly surface scums, advance warning when cyanobacterial densities are increasing could help managers mitigate water quality issues. Here, we fit 13 Bayesian state-space models to evaluate different hypotheses about cyanobacterial densities in a low nutrient lake that experiences sporadic surface scums of the toxin-producing cyanobacterium, Gloeotrichia echinulata. We used data from several summers of weekly cyanobacteria samples to identify dominant sources of uncertainty for near-term (1- to 4-week) forecasts of G. echinulata densities. Water temperature was an important predictor of cyanobacterial densities during model fitting and at the 4-week forecast horizon. However, no physical covariates improved model performance over a simple model including the previous week's densities in 1-week-ahead forecasts. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and did not capture rare peak occurrences, indicating that significant explanatory variables when fitting models to historical data are not always effective for forecasting. Uncertainty partitioning revealed that model process specification and initial conditions dominated forecast uncertainty. These findings indicate that long-term studies of different cyanobacterial life stages and movement in the water column as well as measurements of drivers relevant to different life stages could improve model process representation of cyanobacteria abundance. In addition, improved observation protocols could better define initial conditions and reduce spatial misalignment of environmental data and cyanobacteria observations. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems.

Dataset Information

Using eDNA to biomonitor the fish community in a tropical oligotrophic lake.

Publications

Using eDNA to biomonitor the fish community in a tropical oligotrophic lake.

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