Food web de-synchronization in England's largest lake: an assessment based on multiple phenological metrics

Phenological changes have been observed globally for marine, freshwater and terrestrial species, and are an important element of the global biological ‘fingerprint’ of climate change. Differences in rates of change could desynchronize seasonal species interactions within a food web, threatening ecosystem functioning. Quantification of this risk is hampered by the rarity of long-term data for multiple interacting species from the same ecosystem and by the diversity of possible phenological metrics, which vary in their ecological relevance to food web interactions. We compare phenological change for phytoplankton (chlorophyll a), zooplankton (Daphnia) and fish (perch, Perca fluviatilis) in two basins of Windermere over 40 years and determine whether change has differed among trophic levels, while explicitly accounting for among-metric differences in rates of change. Though rates of change differed markedly among the nine metrics used, seasonal events shifted earlier for all metrics and trophic levels: zooplankton advanced most, and fish least, rapidly. Evidence of altered synchrony was found in both lake basins, when combining information from all phenological metrics. However, comparisons based on single metrics did not consistently detect this signal. A multimetric approach showed that across trophic levels, earlier phenological events have been associated with increasing water temperature. However, for phytoplankton and zooplankton, phenological change was also associated with changes in resource availability. Lower silicate, and higher phosphorus, concentrations were associated with earlier phytoplankton growth, and earlier phytoplankton growth was associated with earlier zooplankton growth. The developing trophic mismatch detected between the dominant fish species in Windermere and important zooplankton food resources may ultimately affect fish survival and portend significant impacts upon ecosystem functioning.We advocate that future studies on phenological synchrony combine data from multiple phenological metrics, to increase confidence in assessments of change and likely ecological consequences

Advancing fishery-independent stock assessments for the Norway lobster (Nephrops norvegicus) with new monitoring technologies

The Norway lobster, Nephrops norvegicus, supports a key European fishery. Stock assessments for this species are mostly based on trawling and UnderWater TeleVision (UWTV) surveys. However, N. norvegicus are burrowing organisms and these survey methods are unable to sample or observe individuals in their burrows. To account for this, UWTV surveys generally assume that "1 burrow system = 1 animal", due to the territorial behavior of N. norvegicus. Nevertheless, this assumption still requires in-situ validation. Here, we outline how to improve the accuracy of current stock assessments for N. norvegicus with novel ecological monitoring technologies, including: robotic fixed and mobile camera-platforms, telemetry, environmental DNA (eDNA), and Artificial Intelligence (AI). First, we outline the present status and threat for overexploitation in N. norvegicus stocks. Then, we discuss how the burrowing behavior of N. norvegicus biases current stock assessment methods. We propose that state-of-the-art stationary and mobile robotic platforms endowed with innovative sensors and complemented with AI tools could be used to count both animals and burrows systems in-situ, as well as to provide key insights into burrowing behavior. Next, we illustrate how multiparametric monitoring can be incorporated into assessments of physiology and burrowing behavior. Finally, we develop a flowchart for the appropriate treatment of multiparametric biological and environmental data required to improve current stock assessment methods

Working Group on Nephrops Surveys (WGNEPS outputs from 2021)

183 pages, figures, 6 annexesThe Working Group on Nephrops Surveys (WGNEPS) is the international coordination group for Nephrops underwater television and trawl surveys within ICES. This report summarizes the national contributions on the results of the surveys conducted in 2021 together with time series covering all survey years, problems encountered, data quality checks and technological improvements as well as the planning for survey activities for 2022. In total, 19 surveys covering 25 functional units (FU’s) in the ICES area and 1 geographical sub- area (GSA) in the Adriatic Sea were discussed and further improvements in respect to survey design and data analysis standardization and the use of recent technologies were reviewed. Due to the COVID-19 pandemic there were minimal disruptions to survey operations where one survey was not completed (GSA 17). A trial trawl Nephrops survey offshore Portugal was carried out on the new research vessel. Preliminary work on how to measure burrow system size was presented using high definition (HD) and standard definition (SD) image data. Further work on comparison of SD and HD indi- cates the change to HD system mounted with a different camera angle was not significantly different for two survey areas (FU 16 and FU 20-21). Automatic burrow detection based on deep learning methods continues to show promising re- sults where datasets from multiple institutes were used. The working group members have agreed to draft a roadmap for automatic system technology requirements with links to the Work- ing Group on Machine Learning in Marine Science (WGMLEARN) and current researchers. The working group is progressing plans for an international Nephrops Underwater television (UWTW) database to be established at the ICES Data Centre. End-users of UWTV datasets for epifauna reporting presented their work and showed the potential for adding value to the survey data, where many of the institutes are involved in providing data for similar research purposesPeer reviewe

Advancing fishery-independent stock assessments for the Norway lobster (Nephrops norvegicus) with new monitoring technologies

The Norway lobster, Nephrops norvegicus, supports a key European fishery. Stock assessments for this species are mostly based on trawling and UnderWater TeleVision (UWTV) surveys. However, N. norvegicus are burrowing organisms and these survey methods are unable to sample or observe individuals in their burrows. To account for this, UWTV surveys generally assume that “1 burrow system = 1 animal”, due to the territorial behavior of N. norvegicus. Nevertheless, this assumption still requires in-situ validation. Here, we outline how to improve the accuracy of current stock assessments for N. norvegicus with novel ecological monitoring technologies, including: robotic fixed and mobile camera-platforms, telemetry, environmental DNA (eDNA), and Artificial Intelligence (AI). First, we outline the present status and threat for overexploitation in N. norvegicus stocks. Then, we discuss how the burrowing behavior of N. norvegicus biases current stock assessment methods. We propose that state-of-the-art stationary and mobile robotic platforms endowed with innovative sensors and complemented with AI tools could be used to count both animals and burrows systems in-situ, as well as to provide key insights into burrowing behavior. Next, we illustrate how multiparametric monitoring can be incorporated into assessments of physiology and burrowing behavior. Finally, we develop a flowchart for the appropriate treatment of multiparametric biological and environmental data required to improve current stock assessment methods

Climate change and freshwater zooplankton: what does it boil down to?

Recently, major advances in the climate–zooplankton interface have been made some of which appeared to receive much attention in a broader audience of ecologists as well. In contrast to the marine realm, however, we still lack a more holistic summary of recent knowledge in freshwater. We discuss climate change-related variation in physical and biological attributes of lakes and running waters, high-order ecological functions, and subsequent alteration in zooplankton abundance, phenology, distribution, body size, community structure, life history parameters, and behavior by focusing on community level responses. The adequacy of large-scale climatic indices in ecology has received considerable support and provided a framework for the interpretation of community and species level responses in freshwater zooplankton. Modeling perspectives deserve particular consideration, since this promising stream of ecology is of particular applicability in climate change research owing to the inherently predictive nature of this field. In the future, ecologists should expand their research on species beyond daphnids, should address questions as to how different intrinsic and extrinsic drivers interact, should move beyond correlative approaches toward more mechanistic explanations, and last but not least, should facilitate transfer of biological data both across space and time

Spatial transferability of habitat suitability models of nephrops norvegicus among fished areas in the northeast atlantic: sufficiently stable for marine resource conservation?

Knowledge of the spatial distribution and habitat associations of species in relation to the environment is essential for their management and conservation. Habitat suitability models are useful in quantifying species- environment relationships and predicting species distribution patterns. Little is known, however, about the stability and performance of habitat suitability models when projected into new areas (spatial transferability) and how this can inform resource management. The aims of this study were to model habitat suitability of Norway lobster (Nephrops norvegicus) in five fished areas of the Northeast Atlantic (Aran ground, Irish Sea, Celtic Sea, Scotland Inshore and Fladen ground), and to test for spatial transferability of habitat models among multiple regions. Nephrops burrow density was modelled using generalised additive models (GAMs) with predictors selected from four environmental variables (depth, slope, sediment and rugosity). Models were evaluated and tested for spatial transferability among areas. The optimum models (lowest AICc) for different areas always included depth and sediment as predictors. Burrow densities were generally greater at depth and in finer sediments, but relationships for individual areas were sometimes more complex. Aside from an inclusion of depth and sediment, the optimum models differed between fished areas. When it came to tests of spatial transferability, however, most of the models were able to predict Nephrops density in other areas. Furthermore, transferability was not dependent on use of the optimum models since competing models were also able to achieve a similar level of transferability to new areas. A degree of decoupling between model \u27fitting\u27 performance and spatial transferability supports the use of simpler models when extrapolating habitat suitability maps to different areas. Differences in the form and performance of models from different areas may supply further information on the processes shaping species\u27 distributions. Spatial transferability of habitat models can be used to support fishery management when the information is scarce but caution needs to be applied when making inference and a multi-area transferability analysis is preferable to bilateral comparisons between areas

Spatial transferability of habitat suitability models of Nephrops norvegicus among fished areas in the Northeast Atlantic: sufficiently stable for marine resource conservation?

Knowledge of the spatial distribution and habitat associations of species in relation to the environment is essential for their management and conservation. Habitat suitability models are useful in quantifying species-environment relationships and predicting species distribution patterns. Little is known, however, about the stability and performance of habitat suitability models when projected into new areas (spatial transferability) and how this can inform resource management. The aims of this study were to model habitat suitability of Norway lobster (Nephrops norvegicus) in five fished areas of the Northeast Atlantic (Aran ground, Irish Sea, Celtic Sea, Scotland Inshore and Fladen ground), and to test for spatial transferability of habitat models among multiple regions. Nephrops burrow density was modelled using generalised additive models (GAMs) with predictors selected from four environmental variables (depth, slope, sediment and rugosity). Models were evaluated and tested for spatial transferability among areas. The optimum models (lowest AICc) for different areas always included depth and sediment as predictors. Burrow densities were generally greater at depth and in finer sediments, but relationships for individual areas were sometimes more complex. Aside from an inclusion of depth and sediment, the optimum models differed between fished areas. When it came to tests of spatial transferability, however, most of the models were able to predict Nephrops density in other areas. Furthermore, transferability was not dependent on use of the optimum models since competing models were also able to achieve a similar level of transferability to new areas. A degree of decoupling between model 'fitting' performance and spatial transferability supports the use of simpler models when extrapolating habitat suitability maps to different areas. Differences in the form and performance of models from different areas may supply further information on the processes shaping species' distributions. Spatial transferability of habitat models can be used to support fishery management when the information is scarce but caution needs to be applied when making inference and a multi-area transferability analysis is preferable to bilateral comparisons between areas

Spatial transferability of habitat suitability models of nephrops norvegicus among fished areas in the northeast atlantic: sufficiently stable for marine resource conservation?

Knowledge of the spatial distribution and habitat associations of species in relation to the environment is essential for their management and conservation. Habitat suitability models are useful in quantifying species- environment relationships and predicting species distribution patterns. Little is known, however, about the stability and performance of habitat suitability models when projected into new areas (spatial transferability) and how this can inform resource management. The aims of this study were to model habitat suitability of Norway lobster (Nephrops norvegicus) in five fished areas of the Northeast Atlantic (Aran ground, Irish Sea, Celtic Sea, Scotland Inshore and Fladen ground), and to test for spatial transferability of habitat models among multiple regions. Nephrops burrow density was modelled using generalised additive models (GAMs) with predictors selected from four environmental variables (depth, slope, sediment and rugosity). Models were evaluated and tested for spatial transferability among areas. The optimum models (lowest AICc) for different areas always included depth and sediment as predictors. Burrow densities were generally greater at depth and in finer sediments, but relationships for individual areas were sometimes more complex. Aside from an inclusion of depth and sediment, the optimum models differed between fished areas. When it came to tests of spatial transferability, however, most of the models were able to predict Nephrops density in other areas. Furthermore, transferability was not dependent on use of the optimum models since competing models were also able to achieve a similar level of transferability to new areas. A degree of decoupling between model 'fitting' performance and spatial transferability supports the use of simpler models when extrapolating habitat suitability maps to different areas. Differences in the form and performance of models from different areas may supply further information on the processes shaping species' distributions. Spatial transferability of habitat models can be used to support fishery management when the information is scarce but caution needs to be applied when making inference and a multi-area transferability analysis is preferable to bilateral comparisons between areas