Optimising species detection probability and sampling effort in lake fish eDNA surveys

Environmental DNA (eDNA) metabarcoding is transforming biodiversity monitoring in aquatic environments. Such an approach has been developed and deployed for monitoring lake fish communities in Great Britain, where the method has repeatedly shown a comparable or better performance than conventional approaches. Previous analyses indicated that 20 water samples per lake are sufficient to reliably estimate fish species richness, but it is unclear how reduced eDNA sampling effort affects richness, or other biodiversity estimates and metrics. As the number of samples strongly influences the cost of monitoring programmes, it is essential that sampling effort is optimised for a specific monitoring objective. The aim of this project was to explore the effect of reduced eDNA sampling effort on biodiversity metrics (namely species richness and community composition) using algorithmic and statistical resampling techniques of a data set from 101 lakes, covering a wide spectrum of lake types and ecological quality. The results showed that reliable estimation of lake fish species richness could, in fact, usually be achieved with a much lower number of samples. For example, in almost 90% of lakes, 95% of complete fish richness could be detected with only 10 water samples, regardless of lake area. Similarly, other measures of alpha and beta-diversity were not greatly affected by a reduction in sample size from 20 to 10 samples. We also found that there is no significant difference in detected species richness between shoreline and offshore sampling transects, allowing for simplified field logistics. This could potentially allow the effective sampling of a larger number of lakes within a given monitoring budget. However, rare species were more often missed with fewer samples, with potential implications for monitoring of invasive or endangered species. These results should inform the design of eDNA sampling strategies, so that these can be optimised to achieve specific monitoring goals

The importance of nitrogen limitation in the restoration of Llangorse Lake, Wales, UK

Llangorse Lake is the largest natural lake in South Wales, UK, and is of European conservation importance. The site has a long history of eutrophication problems and, in recent years, significant efforts have been made to meet water quality restoration targets at this site by reducing the input of phosphorus (P) from external sources. Although the lake has improved substantially in quality since the late 1970s, it is still not meeting its ecological targets. Phosphorus concentrations have remained high and there has been little reduction in algal biomass. Management decisions to reduce P input were originally based on the widely held assumption that shallow lakes are P limited in summer. However, this study clearly shows that this is not always the case; Llangorse Lake, at least, is strongly nitrogen (N) limited over the summer months. As a result, bio-available P released from the sediments cannot be used by the phytoplankton population. So, it accumulates in the water column, causing very high concentrations to occur in late summer. This puts the lake at very high risk of developing algal blooms when N availability increases, usually in early autumn. The study also found that the hydrology of the lake was strongly affected by sub-surface flow. This suggested that nutrients and water could be delivered to the lake from areas beyond the topographically defined surface water catchment. These findings have widespread implications for the successful management of external inputs to lakes, which currently tends to focus on management of the surface water catchment only. The results are discussed in relation to the restoration and management of nitrogen limited lakes, and of those that are significantly affected by sub-surface flow

Extinction risks and threats facing the freshwater fishes of Britain

1.Extinctions occur naturally in all environments, but rates have accelerated rapidly during the Anthropocene, especially in fresh water. Despite supporting many fish species of conservation importance, there has never been a formal assessment of their extinction risks in Britain, which has impeded their inclusion in relevant legislation and policy. This study therefore used the International Union for the Conservation of Nature (IUCN) Red List of Threatened SpeciesTM Categories and Criteria to conduct the first systematic assessment of the extinction risks and threats facing the native freshwater and diadromous fishes of Britain. Additionally, national assessments were produced for England, Scotland and Wales, reflecting the level at which environmental policy decisions are taken in Britain.2.Seven species were categorised as being threatened with extinction at regional level, with European eel Anguilla anguilla and allis shad Alosa alosa classified as Critically Endangered, Atlantic salmon Salmo salar, vendace Coregonus albula and European whitefish Coregonus lavaretus classified as Endangered, and Arctic charr Salvelinus alpinus and twaite shad Alosa fallax classified as Vulnerable. In addition, burbot Lota lota was classified as Regionally Extinct, ferox trout Salmo ferox was categorised as Data Deficient, and 25 species were categorised as Least Concern. European sturgeon Acipenser sturio and houting Coregonus oxyrinchus, although probably native, qualified as only “vagrants” in fresh water, so were categorised as Not Applicable.3.The assessments provide objective baselines against which future changes can be determined, and a key evidence base to support policy and management decisions for the conservation of freshwater and diadromous fish species and their habitats in Britain. It is recommended that the assessments are repeated every 10 years, which would enable changes in conservation status, the effectiveness of policies and where targeted interventions may be required to be examined using the Red List Index

Optimising species detection probability and sampling effort in lake fish eDNA surveys

Environmental DNA (eDNA) metabarcoding is transforming biodiversity monitoring in aquatic environments where the method has repeatedly shown comparable or better performance than conventional approaches to fish monitoring. This method has been developed and deployed, primarily using shoreline sampling during the winter months, across 101 lakes in Great Britain alone, covering a wide spectrum of lake types and ecological quality. Previous analyses on a subset of these lakes indicated that 20 water samples per lake are sufficient to reliably estimate fish species richness, but it is unclear how reduced eDNA sampling effort affects richness, or other biodiversity estimates and metrics. As the number of samples strongly influences the cost of monitoring programmes, it is essential that sampling effort is optimised for a specific monitoring objective. The aim of this project was to explore the effect of reduced eDNA sampling effort on biodiversity metrics (namely species richness and community composition) using algorithmic and statistical resampling techniques. The results showed that reliable estimation of lake fish species richness could in fact usually be achieved with a much lower number of samples. For example, in almost 90% of lakes, 95% of complete fish richness could be detected with only 10 water samples, regardless of lake area. Similarly other measures of alpha and beta-diversity were not greatly affected by a reduction in sample size from 20 to 10 samples. We also found that there is no significant difference in detected species richness between shoreline and offshore sampling transects, allowing for simplified field logistics. This could potentially allow the effective sampling of a larger number of lakes within a given monitoring budget. However, rare species were more often missed with fewer samples, with potential implications for monitoring of invasive or endangered species. These results should inform the design of eDNA sampling strategies, so that these can be optimised to achieve specific monitoring goals

Optimising species detection probability and sampling effort in lake fish eDNA surveys

Environmental DNA (eDNA) metabarcoding is transforming biodiversity monitoring in aquatic environments where the method has repeatedly shown comparable or better performance than conventional approaches to fish monitoring. This method has been developed and deployed, primarily using shoreline sampling during the winter months, across 101 lakes in Great Britain alone, covering a wide spectrum of lake types and ecological quality. Previous analyses on a subset of these lakes indicated that 20 water samples per lake are sufficient to reliably estimate fish species richness, but it is unclear how reduced eDNA sampling effort affects richness, or other biodiversity estimates and metrics. As the number of samples strongly influences the cost of monitoring programmes, it is essential that sampling effort is optimised for a specific monitoring objective. The aim of this project was to explore the effect of reduced eDNA sampling effort on biodiversity metrics (namely species richness and community composition) using algorithmic and statistical resampling techniques. The results showed that reliable estimation of lake fish species richness could in fact usually be achieved with a much lower number of samples. For example, in almost 90% of lakes, 95% of complete fish richness could be detected with only 10 water samples, regardless of lake area. Similarly other measures of alpha and beta-diversity were not greatly affected by a reduction in sample size from 20 to 10 samples. We also found that there is no significant difference in detected species richness between shoreline and offshore sampling transects, allowing for simplified field logistics. This could potentially allow the effective sampling of a larger number of lakes within a given monitoring budget. However, rare species were more often missed with fewer samples, with potential implications for monitoring of invasive or endangered species. These results should inform the design of eDNA sampling strategies, so that these can be optimised to achieve specific monitoring goals