eDITH: An R‐package to spatially project eDNA‐based biodiversity across river networks with minimal prior information

Methods in Ecology and Evolution, Journal Year: 2024, Volume and Issue: 15(5), P. 806 - 815

Published: March 27, 2024

Abstract Ecological and ecosystem monitoring is rapidly shifting towards using environmental DNA (eDNA) data, particularly in aquatic systems. This approach enables a combined coverage of biodiversity across all major organismal groups the assessment ecological indices. Yet, most current approaches are not exploiting full potential eDNA largely interpreting results localized perspective. In riverine networks, by explicitly modelling hydrological transport associated decay, hydrology‐based models enable upscaling eDNA‐based diversity information, providing spatially integrated inference. To capitalize on these unprecedented data translate it into space‐filling projections, streamlined implementation needed. Here, we introduce eDITH R‐package, implementing model to project networks with minimal prior information. couples species distribution relating local taxon's shedding rate streamwater covariates, mass balance expressing concentration at river's cross‐section as weighted sum upstream contributions, an observational accounting for uncertainties measurements. By leveraging replicated measurements hydro‐morphological disentangling various sources, produces maps spatial any chosen resolution. applicable both metabarcoding taxon whose can be retrieved streamwater. The package provides user‐friendly functions single‐run execution fitting Bayesian methods (via BayesianTools package) non‐linear optimization. An interface DHARMa allows validation via posterior predictive checks. Necessary preliminary steps such watershed delineation characterization implemented rivnet package. We illustrate 's workflow functionalities two case studies from published fish data. eDITH, specifically intended ecologists conservation biologists. It used without previous knowledge but also customization experienced users. Ultimately, river globally, transforming how state change systems tracked high resolution highly versatile manner.

Language: Английский

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Integrating direct observation and environmental DNA data to enhance species distribution models in riverine environments

Ecological Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 103056 - 103056

Published: Feb. 1, 2025

Language: Английский

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Combining eDNA Metabarcoding, Hydrology‐Based Modeling and Camera Trap Datasets to Assess the Potential of River eDNA in Monitoring Terrestrial Mammals

Environmental DNA, Journal Year: 2025, Volume and Issue: 7(2)

Published: March 1, 2025

ABSTRACT Global efforts aimed at safeguarding and restoring biodiversity require methods to monitor progress towards conservation objectives. Such should provide a systematic robust assessment of for the lowest cost. River environmental DNA (eDNA) metabarcoding has been successfully applied measure in dendritic riverine habitats is increasingly used describe communities terrestrial vertebrates ecosystems that are challenging survey using traditional methods. However, interpreting eDNA surveys requires an understanding influence transport, decay, production on distribution eDNA. To this end, hydrology‐based eDITH (eDNA Integrating Transport Hydrology) model incorporates such factors can recover reliable spatial patterns aquatic taxa, but its potential taxa so far unexplored. Here, we data mammals collected over two mountainous catchments (575 745 km 2 ) British Columbia, Canada. We assessed prediction transferability between neighboring compared predictions with observations from camera trapping. found 9 out 15 detected by both traps, predicted distributions predominantly matched trap surveys, illustrating uncover mammal catchments. While lacking knowledge actual taxon density prevents us determining whether discrepancies stem limitations or complex production‐density relationships, good suggests some semi‐aquatic partly determined habitat preference hydrology. Downstream sampling most across catchment, inclusion upstream samples aid detecting elusive species. This study underscores broader applications river beyond species illustrates use addressing monitoring objectives tailored approaches.

Language: Английский

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eDITH: an R-package to spatially project eDNA-based biodiversity across river networks with minimal prior information

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 17, 2024

Abstract Ecological and ecosystem monitoring is rapidly shifting towards using environmental DNA (eDNA) data, particularly in aquatic systems. This approach enables a combined coverage of biodiversity across all major organismal groups the assessment ecological indices. Yet, most current approaches are not exploiting full potential eDNA largely interpreting results localized perspective. In riverine networks, by explicitly modelling hydrological transport associated decay, hydrology-based models enable upscaling eDNA-based diversity information, providing spatially integrated inference. To capitalize from these unprecedented data translate into space-filling projections, streamlined implementation needed. Here, we introduce eDITH R-package, implementing model to project networks with minimal prior information. couples species distribution relating local taxon’s shedding rate streamwater covariates, mass balance expressing concentration at river’s cross-section as weighted sum upstream contributions, an observational accounting for uncertainties measurements. By leveraging on replicated measurements hydromorphological disentangling various sources, produces maps spatial any chosen resolution. applicable both metabarcoding taxon whose can be retrieved streamwater. The package provides user-friendly functions single-run execution fitting Bayesian methods (via BayesianTools package) non-linear optimization. An interface DHARMa allows validation via posterior predictive checks. Necessary preliminary steps such watershed delineation characterization implemented rivnet package. We illustrate ’s workflow functionalities two case studies published fish data. eDITH, specifically intended ecologists conservation biologists. It used without previous knowledge but also customization experienced users. Ultimately, river globally, transforming how state change systems tracked high resolution highly versatile manner.

Language: Английский

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rivnet: Extract and Analyze Rivers from Elevation Data

Published: March 1, 2023

Language: Английский

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