Species distribution models are powerful tools to infer ecology and support management of conservation and socio-economic valuable taxa, such as brown trout (Salmo trutta complex). Using a random forest approach, we modelled its distribution in central Italy watercourses, using recent presences/absences and eight environmental/bioclimatic predictors. The model shows (i) high predictive ability (K = 0.76), (ii) predicts suitable, naturally-infrequent lowland watercourses where brown trout occurs or may occur. Moreover, the prediction values (iii) expresses a remarkable positive monotone relationship with abundance classes of brown trout computed during field sampling, despite such information was not included in the model development. Predictors' importance pointed out to the crucial role of bioclimatic constraints (linked to thermal suitability and habitat availability) over anthropogenic disturbance and lithotypes. This modelling exercise reiterates the importance of modelling approaches based on spatially explicit proxies of species habitat requirements to assist taxa management by revealing suitable but infrequent and singular areas that could be considered worthy of protection.

Ecotoxicological bioassays are widely recognized as excellent tools for detecting the bioavailability and toxicity of many environmental pollutants. Specifically, embryo bioassays with invertebrates are among the most sensitive approaches used in the ecological quality assessment of the marine environment. However, these tests are time-consuming and expert judgment dependent, which potentially affects the results based on the ability of the operator and the number of counted embryos. These limitations can be overcome by developing a morphometric analysis based on image acquisition. Herein, a completely automated acquisition system of images for a fast and effective discriminant morphometric analysis is faced by using digital pictures of embryos of the Mediterranean Sea urchin Paracentrotus lividus. Linear Discriminant Analysis (LDA) was applied to find the best combination of automatically acquired morphometric parameters capable of discriminating among different morphological phenotypes by following the expert judgment. The automatized method shows a performance of 82% in detecting normal embryos vs a performance of manual observation of 79%. Our findings highlight the parameter area/perimeter ratio as the most critical descriptor to discriminate among different morphological phenotypes based on a predetermined classification covering six morphotypes. The method was validated on embryos exposed to elutriates from contaminated marine sediments. The high proficiency in classifying the embryos reveals the suitability of this method for the future assessment of marine pollution and complex scenario simulations.

Marine sediments host heterogeneous protist communities consisting of both living benthic microorganisms and planktonic resting stages. Despite their key functions in marine ecosystem processes and biogeochemical cycles, their structure and dynamics are largely unknown. In the present study, with a spatially intensive sampling design we investigated benthic protist diversity and function of surface sediment samples from three subregions of the Mediterranean Sea, through an environmental DNA metabarcoding approach targeting the 18S V4 region of rRNA gene. Protists were characterized at the taxonomic level and trophic function, both in terms of alpha diversity and community composition, testing for potential differences among marine subregions and bathymetric groups. Overall, Alveolata and Stramenopiles were the two divisions that dominated the communities. These dominant groups exhibited significant differences among the three Mediterranean subregions in the alpha diversity estimates based on the detected ASVs, for all computed indices (ASV richness, Shannon and Simpson indices). Protist communities were also found to be significantly different in terms of composition at the order rank in the three subregions p-value < 0.01). These differences were mainly driven by Anoecales, Peridiniales, Borokales, Paraliales and Gonyaulacales, which together contributed almost 80% of the average dissimilarity. Anoecales was the dominant order in the Ionian – Central Mediterranean and Adriatic Sea, but with considerably different relative abundances (52% and 36%, respectively), while Borokales was the dominant order in the Western Mediterranean Sea (33%). Similarly, significant differences among the three marine subregions were also highlighted when protist assemblages were examined in terms of trophic function, both in terms of alpha diversity (calculated on the ASVs for each trophic group) and community composition p-value < 0.01. In particular, the Adriatic Sea stood out for having the highest relative abundance of autotrophic/mixotrophic components in the surface sediments analyzed. Conversely, no significant differences in protist assemblages were found among depth groups. This study provided new insights into the taxonomic and trophic composition of benthic protist communities found in Mediterranean surface sediments, revealing geographical differences among regional seas. The results were discussed in relation to the Mediterranean environmental features that could generate the differences among benthic protist communities.

In recent years, numerous efforts to transplant Posidonia oceanica have been carried out in the Mediterranean Basin for experimental and large-scale restoration purposes. However, data on the long-term outcomes of these initiatives remain scarce. This study aims to address this gap by investigating the long-term response of transplanted P. oceanica at both the population and plant level in comparison to adjacent natural meadows. We report on two large-scale transplantation sites in Italy: Santa Marinella in the Central Tyrrhenian Sea and Ischia Porto in the Southern Tyrrhenian Sea, assessing their progress 14 and 10 years after transplantation, respectively. Descriptors of the meadows and of individual plants were investigated through field and laboratory activities. Sampling was conducted in both transplanted and adjacent control areas within the natural P. oceanica meadow. After about a decade, shoot density in the transplanted areas equaled that of the natural ones. Nevertheless, phenological and lepidochronological descriptors in the transplanted areas still did not match those of the natural meadows. Our work provides crucial information into the restoration process of P. oceanica, with implications for managing this habitat in line with recent EU marine legislation.

Ecological systems can be regarded as natural capital that yields ecosystem services vital for human well-being. The provision of these services strictly depends on the protection of natural capital stocks generating them, highlighting the need for conservation and monitoring actions led by proper assessment methodologies. Among the available methods, the Environmental Accounting Model based on the emergy approach is rapidly gaining popularity in ecological applications. We used such method to assess the natural capital value of Posidonia oceanica meadows, widely recognized the most important ecosystems in the Mediterranean basin, at Italian national spatial scale. The natural capital value of P. oceanica was further weighed by the estimates provided by a Habitat Suitability Model. We observed that the estimated level of habitat suitability played an important role as modifier of the average biophysical value of P. oceanica. Our approach allowed to identify the meadows having the highest stability and over space and time, which we defined as the most valuable in biophysical terms, thus with highest natural capital value. The spatially explicit estimates we provided could support managers and policy-makers to ensure the long-term provision of ecosystem services generated by P. oceanica, enhancing ecosystem management and maritime spatial planning.

Different phytoplankton biomass estimations can provide information about abundance variation, but they are not able to describe the metabolic activity of species or groups within assemblages. Conversely, molecular traits are key for the metabolic dynamics in pelagic ecosystems. To investigate if the RNA/DNA and taxon-specific 18S ribosomal RNA (rRNA)/ribosomal DNA (rDNA) ratios could be used to assess and be indicators of metabolic activity in marine phytoplankton species, two Adriatic diatom species, Chaetoceros socialis and Skeletonema marinoi, were studied. Significant correlations between abundance, chlorophyll a, carbon content and proteins were found in individual and co-cultured growth experiments (from r(s) = 0.570 to r(s) = 0.986, P < 0.001). The biomass trend followed a logistic curve without providing additional information regarding diatom metabolic activity. In both experiments, the RNA/DNA and taxon-specific 18S rRNA/rDNA ratios of C. socialis and S. marinoi showed maximum values at the beginning of the growth phase, i.e as 23.2 +/- 1.5 and 15.3 +/- 0.8, and 16.2 +/- 1.6 and 30.1 +/- 5.4 after 2 and 6 days, respectively, in individual cultures, with a subsequent significant decrease in these values for both species in individual and co-culture experiments. Our results showed that these molecular rRNA/rDNA ratios expressed an activation of metabolism before the abundance increases, even in the presence of interspecific interaction between C. socialis and S. marinoi.

Accurate data on community structure is a priority issue in studying coastal habitats facing human pressures. The recent development of remote sensing tools has offered a ground-breaking way to collect ecological information at a very fine scale, especially using low-cost aerial photogrammetry. Although coastal mapping is carried out using Unmanned Aerial Vehicles (UAVs or drones), they can provide limited information regarding underwater benthic habitats. To achieve a precise characterisation of underwater habitat types and species assemblages, new imagery acquisition instruments become necessary to support accurate mapping programmes. Therefore, this study aims to evaluate an integrated approach based on Structure from Motion (SfM) photogrammetric acquisition using low-cost Unmanned Aerial (UAV) and Surface (USV) Vehicles to finely map shallow benthic communities, which determine the high complexity of coastal environments. The photogrammetric outputs, including both UAV-based high (sub-meter) and USV-based ultra-high (sub-centimetre) raster products such as orthophoto mosaics and Digital Surface Models (DSMs), were classified using Object-Based Image Analysis (OBIA) approach. The application of a supervised learning method based on Support Vector Machines (SVM) classification resulted in good overall classification accuracies > 70%, proving to be a practical and feasible tool for analysing both aerial and underwater ultra-high spatial resolution imagery. The detected seabed cover classes included above and below-water key coastal features of ecological interest such as seagrass beds, “banquettes” deposits and hard bottoms. Using USV-based imagery can considerably improve the identification of specific organisms with a critical role in benthic communities, such as photophilous macroalgal beds. We conclude that the integrated use of low-cost unmanned aerial and surface vehicles and GIS processing is an effective strategy for allowing fully remote detailed data on shallow water benthic communities.

Filter-feeding mussels blend suspended particles into faeces and pseudo-faeces enhancing organic matter flows between the water column and the bottom, and strengthening benthic-pelagic coupling. Inside operating farms, high bivalve densities in relatively confined areas result in an elevated rate of organic sinking to the seabed, which may cause a localized impact in the immediate surrounding. Deposit-feeding sea cucumbers are potentially optimal candidates to bioremediate mussel organic waste, due to their ability to process organic-enriched sediments impacted by aquaculture waste. However, although the feasibility of this polyculture has been investigated for a few Indo-Pacific species, little is known about Atlanto-Mediterranean species. Hence, for the first time, in the present study, we conducted a comparative investigation on the suitability of different Mediterranean sea cucumber species, to be reared in Integrated Multitrophic Aquaculture (IMTA) with mussels. A pilot-scale experiment was accomplished operating within a mussel farm where two sea cucumbers species, Holothuria tubulosa and Holothuria polii , were caged beneath the long-line mussel farm of Mytilus galloprovincialis . After four months, H. tubulosa showed high survivorship (94%) and positive somatic growth (6.07%); conversely H. polii showed negative growth (− 25.37%), although 92% of specimens survived. Furthermore, sea cucumber growth was size-dependent. In fact, smaller individuals, independently from the species, grew significantly faster than larger ones. These results evidenced a clear difference in the suitability of the two sea cucumber species for IMTA with M. galloprovincialis , probably due to their different trophic ecology (feeding specialization on different microhabitats, i.e. different sediment layers). Specifically, H. tubulosa seems to be an optimal candidate as extractive species both for polycultures production and waste bioremediation in M. galloprovincialis operating farms.

Investigations on trophic requirements of different life cycle stages of Paracentrotus lividus are crucial for the comprehension of species ecology and for its artificial rearing. The future success of echinoculture depends heavily on the development of suitable and cost-effective diets that are specifically designed to maximize somatic growth during the early life stages and gonadal production in the later stages. In this context, a considerable number of studies have recommended animal sources as supplements in sea urchin diets. However, with the exception of Fernandez and Boudouresque (2000), no studies have investigated the dietary requirements over the different life stages of the sea urchin. In the present study, the growth and nutrition of three life stages of P. lividus (juveniles: 15-25 mm; subadults: 25-35 mm; adults: 45-55 mm) were analyzed over a 4-month rearing experiment. Three experimental diets, with 0%, 20% and 40% of animal sourced enrichments, were tested in parallel in sea urchin three size classes. The food conversion ratio, somatic and gonadal growth were assessed in each condition in order to evaluate the optimal level of animal-sourced supplements for each life stage. A general growth model covering the full post-metamorphic P. lividus life cycle was defined for each condition. During the juvenile stage P. lividus requires higher animal supply (40%), while a feeding requirement shift takes place toward lower animal supply (20%) in sub-adult and adult stages. Our results evidenced that the progressive increase in size after the metamorphosis led to a consequent variation of trophic requirements and food energy allocation in the sea urchin P. lividus . Macronutrient requirements varied widely during the different life stages, in response to changes in the energy allocation from somatic growth to reproductive investment. This study sheds light on P. lividus trophic ecology, broadening our basic knowledge of the dietary requirements of juveniles, sub-adults and adults as a function of their behavior also in the natural environment.

Abstract The dramatic Mass Mortality Event, MME, of Pinna nobilis populations initially detected in 2016 in the western Mediterranean basin, has also spread rapidly to the central and eastern basin. Unfortunately, there is still a significant lack of information on the status and health of P. nobilis, since only a fragmentary picture of the mortality rate affecting these populations is available. Regarding the Italian coast, several surveys have given only localized or point-like views on the distribution of species and the effect of the MME. Therefore, for the first time, this study investigated P. nobilis densities, distribution and mortality in 164 surveys covering a total of 800 km along the southeast coast of Italy (Apulia region). The geographical scale of this investigation made it the largest ever conducted in Italy, and this was achieved through a rapid and standardized protocol. No live individuals were observed along the 92 km linear transects, allowing us to assess that the P. nobilis populations had totally collapsed, with a mortality rate of 100% in Apulia. The distributional pattern of the species showed a strong overlap with seagrass meadows on meso and macro geographical scale, however this was not the case on a micro scale. This result indicates that although there is a relationship between P. nobilis and seagrass meadows, it is not limited to the habitat patch but crosses the boundaries of seagrass. This observation led us to the conclusion that the distribution of P. nobilis shows a trophic link through the cross-boundary subsidy occurring from seagrass meadows to the nearby habitat, by means of the refractory detrital pathway.

Ecological analyses are aimed at characterizing the complexity of the structure of natural objects, yet their heterogeneity is hardly described by the Euclidean concepts. For such purpose, the fractal geometry can be best suited due to its ability in describing, with mathematical rigor, the inherent irregularity of nature. Fractal dimension provides indeed a measurement of the complexity of the analyzed object in terms of space occupation. In this study, we applied the fractal geometry to Posidonia oceanica in order to characterize the structural complexity of its meadows, which are widely recognized as one of the most important coastal ecosystems in the Mediterranean basin. For achieving our aim, we developed an ad hoc implementation of the Box-Counting algorithm based on the Moore neighborhood analysis. Our approach allowed to render the structural complexity of P. oceanica meadows spatially explicit, thus expressing an intrinsic ecological property. The fractal analysis suggested that the complexity of meadows structure is intimately connected with the ecological conditions of P. oceanica. In fact, meadows in living and mixed conditions showed a higher fractal dimension, suggesting a largely uniform and smooth structure. While the fractal dimension associated to the regressed ecological condition of P. oceanica meadows exhibited lower values, highlighting a more jagged and rough structure. Therefore, the fractal theory may prove useful to both fundamental and applied ecological research focusing on P. oceanica and its interactions with Mediterranean coastal ecosystems. In fact, the fractal analysis we performed could result in an effective and straightforward approach for assessing the condition of P. oceanica at large spatial scale, enhancing an integrated maritime spatial planning over the whole Mediterranean basin.

The dramatic Mass Mortality Event, MME, of Pinna nobilis populations initially detected in the western Mediterranean basin, has also spread rapidly to the central and eastern basin. Unfortunately, there is still a significant lack of information on the status and health of P. nobilis , since only a fragmentary picture of the mortality rate affecting these populations is available. Regarding the Italian coast, several surveys have given only localized or point-like views on the distribution of species and the effect of the MME. Therefore, for the first time, this study investigated P. nobilis density of individuals, distribution and mortality throughout 161 surveys along 800 km of coastline in the Apulia region (South-east of Italy). The geographical scale of this investigation made it the largest ever conducted in Italy, and this was achieved through a rapid and standardized protocol. During this monitoring campaign, 90 km of linear underwater transects were surveyed, along which no live individuals were observed. This result allowed to estimate that the P. nobilis populations had totally collapsed, with a mortality rate of 100% in Apulia. The distributional pattern of the species showed a strong overlap with seagrass meadows on meso- and macro-geographical scale, however this was not the case on a micro-scale. This result evidenced that relationships between P. nobilis and seagrass meadows are not limited to the habitat patch, but cross the boundaries of seagrass leading us to suggest that the distribution of P. nobilis hold a trophic link through the cross-boundary subsidy occurring from seagrass meadows to the nearby habitat, by means of the refractory detrital pathway.

Phytoplankton assemblage structure was analyzed based on time series data (2008-2019) together with envi-ronmental variables in two coastal sites in the Northwestern Adriatic Sea. The main component of phytoplankton assemblage was the diatom group. Distinct seasonal and inter annual variations in the presence of taxa were observed within the phytoplankton assemblage over the study period. Mainly four taxa showed a non-random pattern in the binary time series, such as three diatoms Skeletonema marinoi, Thalassionema nitzschioides and Dactyliosolen fragilissimus, and undetermined Dinophyceae. S. marinoi was more frequent in winter and early spring, whereas T. nitzschioides showed an opposite pattern, being more frequent in late spring and summer. In both cases, deviation from randomness was caused by a clear and almost stationary annual cycle. On the con-trary, deviation from randomness depended on the long-term trend of D. fragilissimus time series, as this diatom showed an increasing frequency of occurrence since 2016. A clear phytoplankton assemblage structure affected by seasonal and environmental factors was observed. This was very evident for representative specie (i.e., S. marinoi associated with colder and rich nutrient waters or Heterocapsa niei and T. nitzschioides associated with high temperature and low nutrient conditions) and other species associated with various environmental pa-rameters. Furthermore, the analysis of the association among phytoplankton taxa showed a partial and varied pattern. Our results highlight that phytoplankton time series showed changes in assemblage structure exhibiting a regular 12-month period affected by environmental factors. The long time series observations are important to understand the phytoplankton assemblage structure in relation to environmental changes and human pressures, crucial to achieving the Good Environmental Status in compliance to environmental directives.

Understanding the evolution of natural systems spatio-temporal dynamics is paramount in modern ecology. We focused on highlighting and analysing temporal and spatial dynamics of remotely-sensed chlorophyll a concentration. This pigment is linked with phytoplankton production, which in turn play a pivotal role in marine environment. Satellite platforms offer a synoptic view of surface chlorophyll a concentration for the last two decades. Coupling this source of information with statistical and Machine Learning techniques could help highlighting eventual patterns. We merged the Mediterranean chlorophyll a satellite data for the last two decades into a single dataset. We tested several techniques for reconstructing missing data and performed a general analysis. Finally, we implemented a Dynamic Time Warping Self-Organizing Map algorithm to cluster our series showing that an elastic distance measure outperforms a non-elastic one. The proposed satellite data management and analysis provided insights on spatio-temporal chlorophyll a dynamics in the Mediterranean Basin.

Oryzias latipes is increasingly used as a model in biomedical skeletal research. The standard approach is to generate genetic variants with particular skeletal phenotypes which resemble skeletal diseases in humans. The proper diagnosis of skeletal variation is key for this type of research. However, even laboratory rearing conditions can alter skeletal phenotypes. The subject of this study is the link between skeletal phenotypes and rearing conditions. Thus, wildtype medaka were reared from hatching to an early juvenile stage at low (LD: 5 individuals/L), medium (MD: 15 individuals/L), and high (HD: 45 individuals/L) densities. The objectives of the study are: (I) provide a comprehensive overview of the postcranial skeletal elements in medaka; (II) evaluate the effects of rearing density on specific meristic counts and on the variability in type and incidence of skeletal anomalies; (III) define the best laboratory settings to obtain a skeletal reference for a sound evaluation of future experimental conditions; (IV) contribute to elucidating the structural and cellular changes related to the onset of skeletal anomalies. The results from this study reveal that rearing densities greater than 5 medaka/L reduce the animals’ growth. This reduction is related to decreased mineralization of dermal (fin rays) and perichondral (fin supporting elements) bone. Furthermore, high density increases anomalies affecting the caudal fin endoskeleton and dermal rays, and the preural vertebral centra. A series of static observations on Alizarin red S whole mount-stained preural fusions provide insights into the etiology of centra fusion. The fusion of preural centra involves the ectopic formation of bony bridges over the intact intervertebral ligament. An apparent consequence is the degradation of the intervertebral ligaments and the remodeling and reshaping of the fused vertebral centra into a biconoid-shaped centrum. From this study it can be concluded that it is paramount to take into account the rearing conditions, natural variability, skeletal phenotypic plasticity, and the genetic background along with species-specific peculiarities when screening for skeletal phenotypes of mutant or wildtype medaka.

Understanding the dynamics of natural system is a crucial task in ecology especially when climate change is taken into account. In this context, assessing the evolution of marine ecosystems is pivotal since they cover a large portion of the biosphere.For these reasons, we decided to develop an approach aimed at evaluating temporal and spatial dynamics of remotely-sensed chlorophyll a concentration. The concentrations of this pigment are linked with phytoplankton biomass and production, which in turn play a central role in marine environment.Machine learning techniques proved to be valuable tools in dealing with satellite data since they need neither assumptions on data distribution nor explicit mathematical formulations. Accordingly, we exploited the Self Organizing Map (SOM) algorithm firstly to reconstruct missing data from satellite time series of chlorophyll a and secondly to classify them. The missing data reconstruction task was performed using a large SOM and allowed to enhance the available information filling the gaps caused by cloud coverage. The second part of the procedure involved a much smaller SOM used as a classification tool. This dimensionality reduction enabled the analysis and visualization of over 37 000 chlorophyll a time series. The proposed approach provided insights into both temporal and spatial chlorophyll a dynamics in the Mediterranean Basin.

Phytoplankton primary production is a key oceanographic process. It has relationships with marine-food-web dynamics, the global carbon cycle and Earth's climate. The study of phytoplankton production on a global scale relies on indirect approaches due to the difficulties of field campaigns. Modeling approaches require in situ data for calibration and validation. In fact, the need for more phytoplankton primary-production data was highlighted several times during the last decades. Most of the available primary-production datasets are scattered in various repositories, reporting heterogeneous information and missing records. We decided to retrieve field measurements of marine phytoplankton production from several sources and create a homogeneous and ready-to-use dataset. We handled missing data and added variables related to primary production which were not present in the original datasets. Subsequently, we performed a general analysis highlighting the relationships between the variables from a numerical and an ecological perspective. Data paucity is one of the main issues hindering the comprehension of complex natural processes. We believe that an updated and improved global dataset, complemented by an analysis of its characteristics, can be of interest to anyone studying marine phytoplankton production and the processes related to it. The dataset described in this work is published in the PANGAEA repository (https://doi.org/10.1594/PANGAEA.932417) (Mattei and Scardi, 2021).

The RNA/DNA ratio is used as indicator of growth in various marine organisms and to assess physiological status at species or community level. To evaluate the utility of the RNA/DNA ratio as a proxy of phytoplankton primary production, the relationships between phytoplankton RNA/DNA, taxon-specific diatom and dinoflagellate 18S rRNA/rDNA ratios and autotrophic phytoplankton biomass were investigated as a first step. Significant correlations between all phytoplankton ratios and total phytoplankton, diatom and dinoflagellate biomass as chlorophyll a (chl a) and carbon content were found. Diatoms showed higher correlation than dinoflagellates (18S rRNA/rDNA vs. chl a, r(s) = 0.74 and 0.64, P < 0.001; 18S rRNA/rDNA vs. carbon, r(s) = 0.66 and 0.53, P < 0.001, respectively), because they represented the most abundant and frequent group within sampled assemblages. Further, phytoplankton biomass production is known to be linked to protein biosynthesis and significant relationships between RNA/DNA ratios and protein content of phytoplankton assemblage were found (r(s) = 0.62 and 0.52, P < 0.001 for diatom and dinoflagellates, respectively). As taxon-specific RNA/DNA ratios were correlated with biomass and protein content, our results can be regarded as the first step toward further studies on the applicability of RNA/DNA ratios as indicators of growth rate and primary production in phytoplankton assemblages.

Sea cucumbers and sea urchins are promising candidates for aquaculture since they are high market value and low-trophic organisms. However, although they often co-exist in many marine habitats showing feeding interactions, there is currently a lack of investigations available regarding the co-culture of these organisms in Integrated Multi-Trophic Aquaculture (IMTA). The present study investigated, for the first time, the laboratory-scale feasibility of an integrated aquaculture between P. lividus and H. tubulosa, two of the most valuable Mediterranean echinoderms, through a four-month experiment. More specifically, three food sources with different fish meal concentrations were tested separately to sustain the integrated production in a land-based RAS (Recycling aquaculture system) of both co-cultured species: 1) completely vegetable diet (D-0), 2) vegetable diet with 20% of fish meal (D-20) and 3) vegetable diet with 40% of fish meal (D-40). Among these experimental diets D-20 (with 20% of fish meal supplement) was consumed more efficiently and sustained high growth rates for both co-cultured species. However, significant growth was detected with all experimental diets, indicating successful integrated aquaculture between sea urchins and sea cucumbers. The present study, therefore, suggested the existence of substantial benefits of an integrated aqua culture between these echinoderm species, that could promote the environmental and economic sustainability of their production on a large-scale. Our results showed, in fact, that less than 24% of the organic matter administered with the food remained as waste in our IMTA system after being ingested by the two trophic levels. The sea urchins ingested 87% of the food administered, absorbing 64% of the organic matter, whilst in the second step, the sea cucumbers consumed 54% of organic matter present in the sea urchin feces. Hence the aquaculture model investigated here was highly effective in reducing the total waste, at the same time providing added value in the form of sea cucumber biomass.

The emergy accounting method has been widely applied to terrestrial and marine ecosystems although there is a lack of emergy studies focusing on phytoplankton primary production. Phytoplankton production is a pivotal process since it is intimately coupled with oceanic food webs, energy fluxes, carbon cycle, and Earth's climate. In this study, we proposed a new methodology to perform a biophysical assessment of the global phytoplankton primary production combining Machine Learning (ML) techniques and an emergy-based accounting model. Firstly, we produced global phytoplankton production estimates using an Artificial Neural Network (ANN) model. Secondly, we assessed the main energy inputs supporting the global phytoplankton production. Finally, we converted these inputs into emergy units and analysed the results from an ecological perspective. Among the energy flows, tides showed the highest maximum emergy contribution to global phytoplankton production highlighting the importance of thise flow in the complex dynamics of marine ecosystems. In addition, an emergy/production ratio was calculated showing different global patterns in terms of emergy convergence into the primary production process. We believe that the proposed emergy-based assessment of phytoplankton production could be extremely valuable to improve our understanding of this key biological process at global scale adopting a systems perspective. This model can also provide a useful benchmark for future assessments of marine ecosystem services at global scale.