An acoustic view of ocean mixing

Knowledge of the parameter K (turbulent diffusivity/"mixing intensity") is a key to understand transport processes of matter and energy in the ocean. Especially the almost vertical component of K across the ocean stratification (diapycnal diffusivity) is vital for research on biogeochemical cycles or greenhouse gas budgets. Recent boost in precision of water velocity data that can be obtained from vessel-mounted acoustic instruments (vmADCP) allows identifying ocean regions of elevated diapycnal diffusivity during research cruises - in high horizontal resolution and without extra ship time needed. This contribution relates acoustic data from two cruises in the Tropical North East Atlantic Oxygen Minimum Zone to simultaneous field observations of diapycnal diffusivity: pointwise measurements by a microstructure profiler as well as one integrative value from a large scale Tracer Release Experiment

Long-Term Spatiotemporal Variability of Whitings in Lake Geneva from Multispectral Remote Sensing and Machine Learning

Whiting events are massive calcite precipitation events turning hardwater lake waters to a milky turquoise color. Herein, we use a multispectral remote sensing approach to describe the spatial and temporal occurrences of whitings in Lake Geneva from 2013 to 2021. Landsat-8, Sentinel-2, and Sentinel-3 sensors are combined to derive the AreaBGR index and identify whitings using appropriate filters. 95% of the detected whitings are located in the northeastern part of the lake and occur in a highly reproducible environmental setting. An extended time series of whitings in the last 60 years is reconstructed from a random forest algorithm and analyzed through a Bayesian decomposition for annual and seasonal trends. The annual number of whiting days between 1958 and 2021 does not follow any particular monotonic trend. The inter-annual changes of whiting occurrences significantly correlate to the Western Mediterranean Oscillation Index. Spring whitings have increased since 2000 and significantly follow the Atlantic Multidecadal Oscillation index. Future climate change in the Mediterranean Sea and the Atlantic Ocean could induce more variable and earlier whiting events in Lake Geneva

CHALLENGES AND OPPORTUNITIES PROVIDED BY SEASONAL CLIMATE FORECASTS: A LITERATURE REVIEW

Use of seasonal climate forecasts is a rapidly evolving area. Effective research and application of climate forecasts require close cooperation between scientists in diverse disciplines and decision makers. Successful collaboration requires all players to at least partially understand each other's perspectives. Issues associated with seasonal forecasts, through a selected review of both physical and social sciences literature, is presented. Our hope is that the review will improve research in this area by stimulating further collaborations.climate forecasts, review, value of information, Resource /Energy Economics and Policy, D80, D81, O30, Q00,

Environmental variables and machine learning models to predict cetacean abundance in the Central-eastern Mediterranean Sea

: Although the Mediterranean Sea is a crucial hotspot in marine biodiversity, it has been threatened by numerous anthropogenic pressures. As flagship species, Cetaceans are exposed to those anthropogenic impacts and global changes. Assessing their conservation status becomes strategic to set effective management plans. The aim of this paper is to understand the habitat requirements of cetaceans, exploiting the advantages of a machine-learning framework. To this end, 28 physical and biogeochemical variables were identified as environmental predictors related to the abundance of three odontocete species in the Northern Ionian Sea (Central-eastern Mediterranean Sea). In fact, habitat models were built using sighting data collected for striped dolphins Stenella coeruleoalba, common bottlenose dolphins Tursiops truncatus, and Risso's dolphins Grampus griseus between July 2009 and October 2021. Random Forest was a suitable machine learning algorithm for the cetacean abundance estimation. Nitrate, phytoplankton carbon biomass, temperature, and salinity were the most common influential predictors, followed by latitude, 3D-chlorophyll and density. The habitat models proposed here were validated using sighting data acquired during 2022 in the study area, confirming the good performance of the strategy. This study provides valuable information to support management decisions and conservation measures in the EU marine spatial planning context

The unique chemistry of Eastern Mediterranean water masses selects for distinct microbial communities by depth

Peer reviewedPublisher PD

Machine Learning in Management of Precautionary Closures Caused by Lipophilic Biotoxins

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] Mussel farming is one of the most important aquaculture industries. The main risk to mussel farming is harmful algal blooms (HABs), which pose a risk to human consumption. In Galicia, the Spanish main producer of cultivated mussels, the opening and closing of the production areas is controlled by a monitoring program. In addition to the closures resulting from the presence of toxicity exceeding the legal threshold, in the absence of a confirmatory sampling and the existence of risk factors, precautionary closures may be applied. These decisions are made by experts without the support or formalisation of the experience on which they are based. Therefore, this work proposes a predictive model capable of supporting the application of precautionary closures. Achieving sensitivity, accuracy and kappa index values of 97.34%, 91.83% and 0.75 respectively, the kNN algorithm has provided the best results. This allows the creation of a system capable of helping in complex situations where forecast errors are more common.The authors want to acknowledge the support from INTECMAR, who have provide mostly data for this work and CESGA, who allows to conduct the tests on their installations. Funding for open access charge: Universidade da Coruña/CISUG. This work is supported by the “Collaborative Project in Genomic Data Integration (CICLOGEN) PI17/01826 funded by the Carlos III Health Institute in the context of the Spanish National Plan for Scientific and Technical Research and Innovation 2013–2016 and the European Regional Development Funds (FEDER)—”A way to build Europe.” This project was also supported by the General Directorate of Culture, Education and University Management of Xunta de Galicia (Ref. ED431G/01, ED431D 2017/16), the “Galician Network for Colorectal Cancer Research” (Ref. ED431D 2017/23), Competitive Reference Groups (Ref. ED431C 2018/49) and the Spanish Ministry of Economy and Competitiveness via funding of the unique installation BIOCAI (UNLC08-1E-002, UNLC13-13–3503) and the European Regional Development Funds (FEDER). Enrique Fernandez-Blanco would also like to thank NVidia corp., which granted a GPU used in this work for the preliminary testsXunta de Galicia; ED431G/01Xunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431D 2017/23Xunta de Galicia; ED431C 2018/4

Factors controlling common smelt abundance and rainbow trout growth in the Rotorua Lakes, New Zealand

Recreational fisheries are of considerable ecological, economic and cultural importance worldwide, and understanding the factors that influence them is an important goal of fishery managers. The two most important factors influencing the growth of fish are habitat quality and food supply. This study was undertaken to gain a better understanding of how these two factors influence rainbow trout growth in the Rotorua Lakes, central North Island, New Zealand, by surveying prey dynamics, quantifying rainbow trout diet, and assessing the effects of environmental factors and population density on trout growth. Rainbow trout populations in lakes of New Zealand’s central North Island mainly prey upon common smelt (Retropinna retropinna), a small, widespread, pelagic species. Routine monitoring of smelt populations would assist in trout fishery management decisions, especially for optimisation of stocking rates and timing. To recommend an effective capture technique for smelt, we tested purse seining, beach seining, drop netting, and boat electrofishing in Lake Rotoiti. Boat electrofishing in the littoral zone at night allowed us to collect more adult smelt than all other methods, and long boat electrofishing transects across the lake were the most effective method for capturing a wide size range of smelt specimens, including larvae. Most methods also caught other species as bycatch. In terms of the number of smelt caught, the most effective method was (1) boat electrofishing at night, followed by (2) scoop nets at night (i.e. boat electrofishing with the current turned off), then (3) beach seining during the day. The first two sampling methods are suggested as the best methods for collecting data on seasonal dynamics, growth, and reproduction of smelt. For enumeration of the total smelt population, these methods should be carried out in the littoral and pelagic zones and combined with a method such as hydroacoustics that can enumerate smelt in the deeper waters of the pelagic zone. Population dynamics of common smelt in lakes are not well understood. To determine the factors influencing smelt populations in Lake Rotoiti, we examined seasonal changes in habitat and resource use by measuring spatial and seasonal changes in smelt abundance, body condition, and diet. We also characterised seasonal and spatial changes in smelt reproductive state and benthic egg abundance. Smelt abundance in the littoral zone and surface waters of the pelagic zone was highest in autumn, coinciding with peaks in smelt body condition, gonadosomatic index, and benthic egg abundance. Smelt larvae were only found in the pelagic zone, and were more abundant in spring than in summer and autumn. Body condition of smelt varied throughout the year, and was lowest in winter, a period of low abundance of littoral invertebrates and zooplankton. Smelt caught in the littoral zone during the day consumed a range of benthic and pelagic invertebrates and smelt eggs, while at night, smelt caught in the littoral and pelagic zones consumed zooplankton, smelt eggs and larval common bully (Gobiomorphus cotidianus). The amount of food in the stomach relative to smelt mass was higher in the littoral zone than in the pelagic zone, suggesting that food resources in the littoral zone exceed those in the pelagic zone. Predation on zooplankton was highest in winter and spring, and smelt eggs formed a large proportion of smelt diet in autumn and winter. Stomach contents and stable isotope analyses showed that smelt undergo an ontogenetic change in diet, from mainly zooplankton as juveniles to mainly benthic invertebrates as adults. The information obtained in this study is necessary for managing smelt and their predator—rainbow trout—in lakes. To better understand the prey requirements of trout in central North Island lakes, we characterised seasonal and ontogenetic changes in diet and prey energy density of rainbow trout in Lake Rotoiti. Common smelt was the dominant prey item of rainbow trout larger than 200 mm (77.8% of diet by mass), followed by koura (freshwater crayfish Paranephrops planifrons; 6.3%), common bully (5.5%), and koaro (Galaxias brevipinnis; 3.4%). Juvenile rainbow trout (<200 mm) consumed amphipods, aquatic and terrestrial insects, oligochaetes, tanaid shrimps, and smelt. Trout consumed koaro only in autumn and winter; consumption of other species did not vary seasonally. The maximum size of smelt consumed increased with increasing trout size, but trout continued to consume small smelt even as large adults. Consumption of larger prey items (koaro and koura) also increased with increasing trout size. This study indicates the importance of smelt for sustaining rainbow trout populations, as predation on other species was relatively low. These findings provide a basis for bioenergetics modelling of rainbow trout populations in lakes of the central North Island of New Zealand. Though the factors influencing the growth of salmonids in cool-temperate and boreal climates are well understood, we lack an understanding of the influences on salmonid growth in warm-temperate areas, especially in lakes. To determine the combined effects of environmental factors, including habitat, on rainbow trout growth, we investigated the growth patterns of rainbow trout (Oncorhynchus mykiss) in nine warm-temperate New Zealand lakes of contrasting morphometry, mixing regime, and trophic state. Mark-recapture data (some collected by anglers) from hatchery trout releases during eight consecutive years were used to calculate growth parameters and body condition factor. Fish growth rates and condition factors were highest in deep (≥20 m mean depth) lakes of moderate trophic state. Overall, growth rate increased with increasing lake size and volume of favourable habitat (i.e. dissolved oxygen >6.0 mg L-1 and temperature <21°C), but decreased with increasing turbidity, chlorophyll a, and nitrogen concentrations. A classification and regression tree (CART) analysis found that variables describing habitat volume were the most important determinants of trout growth rate, and correlates of trophic state (chl a, conductivity) were important secondary determinants of trout growth rate. These results suggest that lake morphometry and trophic state are important attributes structuring overall habitat quality and thus influencing growth of rainbow trout in lakes in warm-temperate climates. The effects of future ecosystem degradation and climate warming on trout growth are likely to be most severe in shallow, eutrophic lakes. To investigate the carrying capacity and factors affecting growth of rainbow trout in Lake Rotoiti, we employed a bioenergetics model to assess the influence of past stocking rates, timing of releases, and prey abundance on growth and prey consumption. We hypothesised that stocking rates and prey abundance would affect growth and prey consumption by influencing per-capita prey availability, and that the environmental conditions encountered by fish at the time of stocking would affect growth and consumption. Prey consumption of stocked rainbow trout was calculated with the Wisconsin bioenergetics model. We calculated growth trajectories based on data from trout that were stocked into the lake in spring and autumn from 1995 to 2009 and then re-captured by anglers. Diet, prey energy density, body mass lost due to spawning, and lake temperature were measured locally. There was no difference in tag return rate between fish released in spring and autumn. Though trout released in autumn were smaller initially, they grew at a faster rate than trout released in spring. The ratio of observed to predicted change in biomass at the maximum consumption rate by individual trout in the first year of lake residence was negatively correlated with the number of yearlings released in a cohort, suggesting that stocking rates (347–809 fish ha-1 year-1) caused density-dependent effects on growth. Common smelt accounted for 85% of total prey consumption. However, no significant relationship was found between prey consumption by individual trout and adult smelt abundance, suggesting that more detailed investigations of smelt abundance are required to predict trout growth rates. Because there is little risk of non-human predation of stocked fish in Lake Rotoiti, and winter temperatures are mild (11–14°C), stocking smaller trout (~160 mm fork length) in autumn is likely to produce larger fish than stocking larger fish (~200 mm fork length) in spring. Possible reasons for this difference include higher prey abundance in the littoral zone in autumn and more suitable temperature and dissolved oxygen habitat in autumn-winter. These results suggest that optimal stocking strategies in warm-temperate systems may differ to those in cooler temperate regions

Spatial and temporal trends of phytoplankton and physiochemical variables in a hypertrophic, monomictic lake

Spatial and temporal variations in the physical, chemical and biological composition of Lake Ōkaro were measured over 16 months. Lake Ōkaro is a small (0.32 km2) hypertrophic, monomictic lake located in the Central Volcanic Zone of the North Island, New Zealand. Vertical profiles of temperature, chlorophyll fluorescence, dissolved oxygen concentration (DO), pH, specific conductance, photosynthetically active radiation (PAR) and nutrient species, including ammonium-nitrogen (NH4-N), nitrite-nitrogen (NO2-N), nitrate-nitrogen (NO3-N) and phosphate-phosphorus (PO4-P), were collected at up to nine stations at weekly to monthly frequencies. High-frequency variability was assessed during two separate 24-hour monitoring periods, coinciding with an Anabaena spiroides-dominated surface bloom, and a Ceratium hirundinella-dominated deep chlorophyll maximum. Additional data for wind direction and velocity, incident solar irradiance and rainfall was sourced from a meteorological weather station and a lake monitoring buoy at Rotorua, 20 km north of the lake. Spatial variability was more pronounced during summer. Observed vertical gradients in chlorophyll fluorescence, DO, specific conductance and nutrient species were closely linked to thermal stability of the water column. There were large variations in chlorophyll fluorescence amongst stations in summer, which related to displacement of the metalimnion and associated changes in chlorophyll fluorescence. Winter mixing was characterised by relative homogeneity of the water column. Nutrient concentrations were elevated at all depths whereas high concentrations had previously been confined to lower depth strata (the hypolimnion). Temperature profiles in summer displayed clear vertical gradients with a well-defined metalimnion that increased in depth until winter mixing generated isothermal conditions. Chlorophyll fluorescence profiles were characterised by the formation of a DCM that was recurrent over both summer periods, and was strongly statistically related to the depth of the thermocline for the duration of stratification. Dissolved oxygen, specific conductance and pH were relatively uniform horizontally, though pH was consistently lower at a well-sheltered near-shore station. All variables showed strong variations with depth during the stratified period. Dissolved oxygen was negligible or zero below the thermocline for much of the stratified period while specific conductance was lowest above or at the thermocline. There were also strong vertical gradients in nutrient concentrations in summer, with concentrations below the thermocline often an order of magnitude higher than those above. The representativeness of fluorescence at a central station to a whole-lake scale was assessed using a vertical integrated value and the standard error derived from up to eight other stations. Values at the single station frequently deviated from the mean fluorescence of the wider lake, particularly at the DCM which suggests that extrapolating single-station measurements to a whole lake could provide highly exaggerated values of lake fluorescence. High-frequency sampling during the A. spiroides-dominated surface bloom showed diel temperature variations attributed mostly to solar irradiance. There was high light attenuation from the high phytoplankton biomass and consistently elevated pH and DO. Fluorescence profiles suggested that the phytoplankton population was strongly buoyant and did not undergo diel vertical migration. High-frequency sampling during a period when there was a dinoflagellate-dominated DCM showed two coinciding fluorescence peaks had formed at 6-7 and 7-8 m depth and contained morphologically and physiologically distinct taxa. The 6-7 m DCM was predominantly Ceratium hirundinella, while the 7-8 m DCM was composed of C. hirundinella and unidentified colonial picoplankton. Fluorescence profiles suggested diel vertical migration was not taking place, and strong gradients in light, nutrient availability and the relative biomass of the dominants suggested that the 6-7 and 7-8 m DCM populations potentially differed in their modes of nutrition, light history and susceptibility to grazing. This research illustrates the degree of spatial variability that can exist in a small, monomictic hypertrophic lake at a given time, and highlights some of the potential limitations of using single-site monitoring stations to represent the physical, chemical and biological conditions of a whole lake. This information may be used to critically evaluate the reliability of phytoplankton biomass estimates that have been derived from spatially-limited sampling methods. This study further illustrates the role that thermal stratification plays in creating vertical gradients in a number of biological and chemical variables, and demonstrates that parallels exist with regard to DCM formation in oligotrophic and hypertrophic lakes, relating to the interplay between light, chlorophyll fluorescence and thermal stratification. Evidence is also provided showing that diel-scale variations in phytoplankton biomass can differ markedly between a cyanobacteria-dominated surface bloom and a dinoflagellate-dominated DCM, which further highlights the value of high-frequency sampling when seeking to estimate phytoplankton biomass using in situ methods

Enhanced Condition Assessment for Maine Lakes

The Influence of anthropogenic activities on lake water quality is well documented, but how those influences interact with the effects of natural features, such as watershed geology or lake morphometry, has been less explored. Further, some aspects of lake condition are influenced by factors that are not lake or watershed specific, but occur across large regions, such as weather patterns. All these factors may be interrelated in some instances, which can complicate lake condition assessments which have the purpose of determining how lakes are being affected by human activities. This dissertation investigates how lake assessments can integrate the interactions among natural features of lakes, their watersheds, and anthropogenic influences. Chapter 1 discusses the variety of factors that may affect lake condition and how those influences may confound lake condition assessments. Chapter 2 details the creation of a hydrogeomorphic lake classification, based on ecoregions and lake depth, that partitioned lakes into groups that share similarities in background water quality condition. In chapter 3, a logistic regression model is described that uses maximum depth and relative lake area beneath the epilimnion to predict which low-nutrient lakes (total phosphorus \u3c 15 μg/L) may exhibit naturally-occurring anoxia. In chapter 4, water clarity patterns from different types of reference lakes (detailed in chapter 2) were modeled to allow for comparisons between yearly water clarity values in non-reference lakes and a reference baseline that shifts over time. Cumulative precipitation during the lake stratification season was the primary driver of yearly differences in background lake water clarity. In chapter 5, methods were developed to measure the effect of anthropogenic shoreland disturbance on the condition of littoral habitat. Multi-metric indices based on various habitat measures were established that determine if the littoral habitat is different from a natural reference condition. Chapter 6 summarizes the research in this dissertation and offers potential foci of future lake research in Maine. The overall goal of this dissertation was to advance our collective understanding of how lakes may be variably affected by natural and anthropogenic factors, thereby allowing for better-informed lake assessments and the development of more comprehensive, achievable lake management goals. The research presented herein underscores the importance of considering the interactions of multiple cross-scale factors when evaluating lake condition, especially those related to landscape traits that influence runoff water chemistry, natural lake-specific features such as basin morphometry, large-scale weather patterns, and localized shoreland development