Marine Ecosystem Dynamics Research Articles

A Beacon in the Dark: Grey Literature Data Mining and Machine Learning Enlightening Historical Plankton Seasonality Dynamics in the Ligurian Sea

The Mediterranean Sea, as one of the world’s most climate-sensitive regions, faces significant environmental changes due to rising temperatures. Zooplankton communities, particularly copepods, play a vital role in marine ecosystems, yet their distribution dynamics remain poorly understood, especially in the Ligurian Sea. Leveraging open-source software and environmental data, this study adapted a methodology to model copepod distributions from 1985 to 1986 in the Portofino Promontory ecosystem using the Random Forest machine learning algorithm to produce the first abundance and distribution maps of the area. Five copepod genera were studied across different trophic guilds, revealing habitat preferences and ecological fluctuations throughout the seasons. The assessment of model accuracy through symmetric mean absolute percentage error (sMAPE) highlighted the variability in copepod dynamics influenced by environmental factors. While certain genera exhibited higher predictive accuracy during specific seasons, others posed challenges due to ecological complexities. This study underscores the importance of species-specific responses and environmental variability in predictive modeling. Moreover, this study represents the first attempt to model copepod distribution in the Ligurian Sea, shedding light on their ecological niches and historical spatial dynamics. The study adhered to FAIR principles, repurposing historical data to generate three-dimensional predictive maps, enhancing our understanding of copepod biodiversity. Future studies will focus on developing abundance distribution models using machine learning and artificial intelligence to predict copepod standing crop in the Ligurian Sea with greater precision. This integrated approach advances knowledge of copepod ecology in the Mediterranean and sets a precedent for integrating historical data with contemporary methodologies to elucidate marine ecosystem dynamics.

A Historical Plankton Index: Zooplankton abundance in the North Sea since 800 CE

The North Sea region boasted one of the world’s most important fisheries for many centuries. Climate directly and indirectly influences the development and survival of many important pelagic fish in the North Sea ecosystem. One indirect influence is the food availability in the form of phyto- and zooplankton abundance, which is strongly controlled by environmental factors. One of these environmental factors is local sea surface temperatures. A negative correlation between zooplankton abundance and sea surface temperature is well established for the epeiric sea on the European continental shelf. Continuous temporal observations of North Sea zooplankton production only exist since 1958. Therefore we developed a Historical Plankton Index (HPI) from 800 CE onwards to extend our record of temperature-driven zooplankton abundance in the North Sea over a multi-centennial time scale. For this we used the North Atlantic temperature reconstructions and associations between zooplankton abundance and contemporary sea surface temperatures established applying a General Additive Modelling (GAM) approach. We then examined the association between the HPI and historical landings from the Dutch commercial herring fishery in the 17th century to test the utility of our HPI. We examine the potential influence of food availability (in terms of zooplankton abundance) on the fishery, the evolution of which is often only considered in terms of human influences such as conflict, fishing gear and demand for fish as a commodity. We find that under certain conditions the HPI can explain 20% of the variability in Dutch herring landings. This highlights the importance of developing long-term and large-scale indices of natural marine ecosystem dynamics to understand the historical fortunes of the commercial fishing industry. The results are directly relevant to the United Nations’ sustainable development goal 14 – life below water.

Navigating the waters of innovation: advancing in aquatic research and sustainability

Aquatic research and sustainability represent critical pillars in our collective efforts to safeguard the health and resilience of the planet’s aquatic ecosystems. Through rigorous scientific inquiry and innovative practices, researchers strive to unravel the complexities of aquatic environments, from the intricate dynamics of marine ecosystems to the delicate balance of freshwater habitats. Sustainable management approaches are essential to ensure the long-term viability of these invaluable resources, balancing human needs with the imperative to protect biodiversity and ecosystem services. From combating pollution and overfishing along with the impacts of climate change, aquatic research plays a pivotal role in informing evidence-based policies and practices aimed at preserving our oceans, rivers, and lakes for future generations. By fostering interdisciplinary collaboration, embracing emerging technologies, and promoting stakeholder engagement, we can collectively work towards a more sustainable future where the treasures of our aquatic world are cherished and protected.

Unusual Hemiaulus bloom influences ocean productivity in Northeastern US Shelf waters

Abstract. Because of its temperate location, high dynamic range of environmental conditions, and extensive human activity, the long-term ecological research site in the coastal Northeastern US Shelf (NES) of the northwestern Atlantic Ocean offers an ideal opportunity to understand how productivity shifts in response to changes in planktonic community composition. Ocean production and trophic transfer rates, including net community production (NCP), net primary production (NPP), gross oxygen production (GOP), and microzooplankton grazing rates, are key metrics for understanding marine ecosystem dynamics and associated impacts on biogeochemical cycles. Although small phytoplankton usually dominate phytoplankton community composition and Chl a concentration in the NES waters during the summer, in August 2019, a bloom of the large diatom genus Hemiaulus, with N2-fixing symbionts, was observed in the mid-shelf region. NCP was 2.5 to 9 times higher when Hemiaulus dominated phytoplankton carbon compared to NCP throughout the same geographic area during the summers of 2020–2022. The Hemiaulus bloom in summer 2019 also coincided with higher trophic transfer efficiency from phytoplankton to microzooplankton and higher GOP and NPP than in the summers 2020–2022. This study suggests that the dominance of an atypical phytoplankton community that alters the typical size distribution of primary producers can significantly influence productivity and trophic transfer, highlighting the dynamic nature of the coastal ocean. Notably, summer 2018 NCP levels were also high, although the size distribution of Chl a was typical and an atypical phytoplankton community was not observed. A better understanding of the dynamics of the NES in terms of biological productivity is of primary importance, especially in the context of changing environmental conditions due to climate processes.

Making Ecosystem Modeling Operational–A Novel Distributed Execution Framework to Systematically Explore Ecological Responses to Divergent Climate Trajectories

AbstractMarine Ecosystem Models (MEMs) are increasingly driven by Earth System Models (ESMs) to better understand marine ecosystem dynamics, and to analyze the effects of alternative management efforts for marine ecosystems under potential scenarios of climate change. However, policy and commercial activities typically occur on seasonal‐to‐decadal time scales, a time span widely used in the global climate modeling community but where the skill level assessments of MEMs are in their infancy. This is mostly due to technical hurdles that prevent the global MEM community from performing large ensemble simulations with which to undergo systematic skill assessments. Here, we developed a novel distributed execution framework constructed of low‐tech and freely available technologies to enable the systematic execution and analysis of linked ESM/MEM prediction ensembles. We apply this framework on the seasonal‐to‐decadal time scale, and assess how retrospective forecast uncertainty in an ensemble of initialized decadal ESM predictions affects a mechanistic and spatiotemporal explicit global trophodynamic MEM. Our results indicate that ESM internal variability has a relatively low impact on the MEM variability in comparison to the broad assumptions related to reconstructed fisheries. We also observe that the results are also sensitive to the ESM specificities. Our case study warrants further systematic explorations to disentangle the impacts of climate change, fisheries scenarios, MEM internal ecological hypotheses, and ESM variability. Most importantly, our case study demonstrates that a simple and free distributed execution framework has the potential to empower any modeling group with the fundamental capabilities to operationalize marine ecosystem modeling.

Assessing the Plastisphere from Floating Plastics in the Northwestern Mediterranean Sea, with Emphasis on Viruses.

Plastics in the ocean create the "plastisphere", a diverse habitat hosting various life forms. Other than the pollution induced by plastics, the co-occurrence of primary producers, symbiotic organisms, decomposers, and pathogens within the plastisphere raises questions about how they influence the dynamics of marine ecosystems. Here, we used a shotgun DNA-sequencing approach to describe the species thriving on floating plastics collected in two Mediterranean sites. Our findings revealed many species of bacteria, eukaryotes, viruses, and archaea on each plastic. Proteobacteria was dominant (70% of reads in the entire dataset), with other groups such as Ascomycota fungi (11%) and Bacteroidetes (9%) also being represented. The community structure was not affected by the polymeric composition or the plastic shape. Notably, pathogenic Vibrio species, including V. campbelli, V. alginolyticus, and V. coralliilyticus, were among the most abundant species. Viruses, despite showing lower relative abundances, occurred in all samples, especially Herpesvirales, Caudovirales, and Poxviridae groups. A significant finding was the presence of the White Spot Syndrome virus (WSSV). This pathogen, responsible for devastating outbreaks in aquaculture systems, had not been previously reported in the marine plastisphere. Our study emphasizes the need for further investigation into the ecological and economic impacts of plastisphere organisms in the ocean.

Shortcomings of the dissipation rate for understanding the turbulent environment of plankton—And a potential solution

AbstractFundamental marine ecosystem dynamics such as mating, predation, and infection require individual plankton to move relative to one another. Ambient turbulence is often invoked as a mechanism to facilitate such interactions. The local intensity of turbulence is quantified as the dissipation rate of turbulent kinetic energy. While the dissipation rate is central to understanding large‐scale fluxes of heat, salt, and nutrients in the ocean, we show that it can be a poor descriptor of the turbulent environment experienced by individual plankton. A dissipation rate is a single integrated quantity representing all the complex motions in a turbulent region; the instantaneous turbulent environment of plankton may bear little resemblance to that predicted by the dissipation rate or quantities derived from it. Most importantly, the statistics (probabilities) of the relative motions of plankton in turbulence cannot be recovered from the dissipation rate or its spectrum: the probabilities of the plankton experiencing any given turbulent relative velocity are lost in the calculation. This presents a fundamental barrier to our understanding of the effects of ambient turbulence on planktonic ecosystem dynamics in the ocean. Rather than relying on dissipation rates, we show that quantifying the probability distributions of the microscale turbulent motions can provide much richer insights into the turbulent environment of individual plankton. Expanding such statistical analyses, and improving our understanding of the Lagrangian properties of ocean turbulence as experienced by plankton in the ocean will lead to significant increases in our ability to understand and quantify the effects of turbulence on plankton.

Oceanographic characteristics of Lampung Bay and its relationship to the Indian Ocean Dipole (IOD) period 2013-2021

The Indian Ocean Dipole (IOD) may affect the distribution pattern of the sea surface temperature (SST) in the Indonesian seas. Understanding this impact is crucial for comprehending the dynamics of marine ecosystems, particularly in Lampung Bay. This study evaluates IOD effects on SST and associated upwelling/downwelling in Lampung Bay. 2014 fish catch data analysis reveals during negative IOD phases, SST increases (0.2°C to 2°C) with subsequent downwelling, coinciding with reduced catches (609.18 tons vs. 3,079 tons normal). Conversely, positive IOD phases show SST anomalies (-1°C to -2.5°C) with upwelling, correlating with increased catches to 3,349 tons in 2018. IOD-SST relationship primarily observed in Lampung Bay’s open connection to Sunda Strait (r=0.64 to 0.69), while weak correlations in coastal waters (r < 0.2) suggesting the influence of other factors on SST in Lampung Bay.

Investigation and Analysis of Fish Assemblages within The Berau Bay Ecosystem, West Papua, and Their Utilization Potential

Fisheries resource assessment is pivotal for grasping marine ecosystem dynamics and guiding sustainable management practices. This study focuses on exploring the fisheries resources within Berau Bay, situated in the biodiverse-rich West Papua Province, known for its significant marine biodiversity and importance to local livelihoods. Despite its importance, there is a notable absence of comprehensive assessments concerning the bay’s fisheries resources and their utilization potential. This research endeavors to fill this gap by providing a detailed analysis to inform sustainable management strategies. Our findings reveal a diverse range of fish families dominating Berau Bay, with significant contributions from Carangidae and Scombridae. Moreover, acoustic surveys uncover substantial Fisheries Resource Potential (FRP) across three zones: Zone 1 at 501.555 tons, Zone 2 at 854.634 tons, and Zone 3, primarily designated as a conservation area, at 678.188 tons. The cumulative FRP potential amounts to 2.034.377 tons, encompassing various species categories, with an estimated annual utilization rate of around 1.627.502 tons. These results challenge previous assumptions regarding the bay’s fisheries composition and potential, emphasizing the necessity of updated assessments. Additionally, they enhance our understanding of the region’s marine biodiversity, underscoring the urgency of targeted conservation efforts for sustainable resource management. This study emphasizes the significance of holistic approaches to fisheries management, integrating ecological, socioeconomic, and conservation considerations. Such interdisciplinary efforts are paramount for safeguarding marine ecosystems and supporting the livelihoods of coastal communities worldwide.

Disjunct habitat of cryptic Terebellides (Annelida, Trichobranchidae) species shows a phylogenetic link between polychaetes from the White and the North Seas

Understanding the distribution and biodiversity of marine species is crucial for developing effective conservation strategies and maintaining the health of global ecosystems. Advancements in molecular data utilization have significantly improved our understanding of biodiversity within the genus Terebellides. In this study, we conducted a phylogenetic analysis on polychaete samples from the Kandalaksha Bay, White Sea, revealing their affiliation with a putative undescribed species of the genus Terebellides found in two locations of the North Sea. Interestingly, this species was not detected in the Norwegian and Barents Seas, leading us to propose a disjunct distribution scenario for this Terebellides species. This unique distribution pattern might be attributed to the succession of polychaetes by new species, facilitated by the Gulf Stream and a climate change role in driving shifts in species' ranges and altering marine ecosystem dynamics.

Effects of seasonal variations and environmental factors on phytoplankton community structure and abundance in Beibu Gulf, China

The seasonal variation in phyla within the phytoplankton community is evident in the Beibu Gulf region, with Bacillariophyta being the most diverse group, accounting for 55% of genera in spring and slightly increasing to 57.9% in autumn. In contrast, Pyrrophyta exhibits a higher number of genera and taxa in spring at 43.3%, but this percentage declines to 40% in autumn. During both seasons, the phylum Cyanophyta had a limited occurrence, making up only 1.7% and 2.1% of the total species counts, but in the spring season, it emerged as the dominant phylum with a high cell density of 95.4%, surpassing other phyla such as Aphanocapsa elachista, Guinardia flaccida, Chaetoceros laciniosus, Trichodesmium thiebautii, and Thalassiosira subtilis. Conversely, in the autumn season, cyanophyta constituted merely 4% of the overall cell density. The relative abundance of Bacillariophyta species (Bacteriastrum sp. >Chaetoceros affinis > Chaetoceros lorenzianus > Thalassionema nitzschioides > Chaetoceros curvisetus) displayed a distinct trend, reaching its peak cell density of 94% during autumn. The significance of this study lies in its findings that different types of phytoplankton, such as dinoflagellates and diatoms, have distinct growth patterns in the northern Beibu Gulf. It also highlights the importance of nutrient levels, particularly nitrate, nitrite, silicate, and soluble reactive phosphorus, in influencing the composition of phytoplankton communities during the spring season. Additionally, the study reveals a negative relationship between ammonium concentration and water temperature during both spring and autumn. These findings suggest that changes in nutrient availability during seasonal shifts play a critical role in shaping phytoplankton dynamics in marine ecosystems. The observed negative relationship between ammonium concentration and water temperature raises questions about the potential impacts of climate change on phytoplankton dynamics in the Beibu Gulf. As temperatures continue to rise, it is possible that the nutrient-rich conditions in the spring season may be altered, leading to changes in the composition and abundance of phytoplankton populations. This could potentially have cascading effects on the overall ecosystem. Therefore, studying the interplay between temperature and nutrient availability is essential for accurately assessing the future health and productivity of the Beibu Gulf's phytoplankton communities.

Improvement in Spatiotemporal Chl-a Data in the South China Sea Using the Random-Forest-Based Geo-Imputation Method and Ocean Dynamics Data

The accurate estimation of the spatial and temporal distribution of chlorophyll-a (Chl-a) concentrations in the South China Sea (SCS) is crucial for understanding marine ecosystem dynamics and water quality assessment. However, the challenge of missing values in satellite-derived Chl-a data has hindered obtaining complete spatiotemporal information. Traditional methods for deriving Chl-a are based on the modeling of measured sensor data and in situ measurements. Spatiotemporal imputation of Chl-a is difficult due to the inaccessibility of the measured Chl-a. In this study, we introduce an innovative approach that incorporates an ocean dynamics dataset and utilizes the random forest algorithm for predicting the Chl-a concentration in the SCS. The method combines the spatiotemporal feature pattern of Chl-a and the main influencing factors, and it introduces ocean dynamics data, which has a high correlation with the spatiotemporal distribution of Chl-a, as the input data through feature engineering. Also, we compared Random Forest (RF) with other Machine Learning (ML) methods. The results show that (1) ocean dynamics datasets can provide important data support for Chl-a imputation by capturing the impact of dynamical processes on ecological roles in the South China Sea. (2) The RF method is the superior imputation method for the reconstruction of Chl-a in the South China Sea, with better model performance and smaller errors. This study provides valuable insight for researchers and practitioners in choosing suitable machine learning methods for the imputation of the Chl-a concentration in the SCS, facilitating a better understanding of the region’s marine ecosystems and supporting effective environmental management.

Soil nutrient conditions alter viral lifestyle strategy and potential function in phosphorous and nitrogen metabolisms

As one of the most abundant members of microbial communities, viruses are considered to influence prokaryotic mortality and biogeochemical cycles. While extensive research has been conducted to explore viral diversity and community dynamics in marine ecosystems, our understanding of soil viruses, particularly within agroecosystems, remains limited. Here, we conducted metagenomics and viromics analyses in a paddy ecosystem subjected to four different levels of soil nutrient modification by pig manure applications (PM0: 0 kg ha−1, PM1: 1930 kg ha−1, PM2: 3860 kg ha−1 and PM3: 5790 kg ha−1) over a period of 9 years. We aimed to investigate viral community adaptation and virus-host interactions in response to varying soil nutrient conditions. Our findings revealed that the viral communities are more adaptable to changes in soil nutrient contents compared to prokaryotic communities. Specifically, the relative abundance of Caudoviricetes decreased significantly with increasing levels of soil available phosphorus and total nitrogen. The ratio of lytic-lysogenic cycles increased with higher manure application rates, accompanied by an elevated prevalence of functional genes related to cell processes and viral protein structure. Moreover, we identified several putative auxiliary metabolic genes (AMGs) associated with phosphorus and nitrogen cycles, including phoA, phoH, phoB, and gdh, with the first discovery of phoB and gdh as soil viral-encoded AMG. Notably, the association between viruses and phoB-encoding bacteria displayed greater similarity within nutrient-deficient environments compared to nutrient-enriched environments, while the converse interaction pattern emerged between viruses and gdh-encoding bacteria. Collectively, our study highlights the importance of soil nutrient conditions in driving the transition between lytic-lysogenic cycles, as well as the interaction patterns between viruses and key bacteria. The insights gleaned from our findings significantly enrich our understanding of viral ecology within agricultural ecosystems.

Hybrid quantum-classical convolutional neural network for phytoplankton classification

The taxonomic composition and abundance of phytoplankton have a direct impact on marine ecosystem dynamics and global environment change. Phytoplankton classification is crucial for phytoplankton analysis, but it is challenging due to their large quantity and small size. Machine learning is the primary method for automatically performing phytoplankton image classification. As large-scale research on marine phytoplankton generates overwhelming amounts of data, more powerful computational resources are required for the success of machine learning methods. Recently, quantum machine learning has emerged as a potential solution for large-scale data processing by harnessing the exponentially computational power of quantum computers. Here, for the first time, we demonstrate the feasibility of using quantum deep neural networks for phytoplankton classification. Hybrid quantum-classical convolutional and residual neural networks are developed based on the classical architectures. These models strike a balance between the limited function of current quantum devices and the large size of phytoplankton images, making it possible to perform phytoplankton classification on near-term quantum computers. Our quantum models demonstrate superior performance compared to their classical counterparts, exhibiting faster convergence, higher classification accuracy and lower accuracy fluctuation. The present quantum models are versatile and can be applied to various tasks of image classification in the field of marine science.

PlasPi TDM: Augmentation of a low-cost camera platform for advanced underwater physical-ecological observations

Marine ecosystem dynamics in the context of climate change is a growing scientific, political and social concern requiring regular monitoring through appropriate observational technologies and studies. Thus, a wide range of tools comprising chemical, biogeochemical, physical, and biological sensors, as well as other platforms exists for marine monitoring. However, their high acquisition and maintenance costs are often a major obstacle, especially in low-income developing countries. We designed an advanced low-cost synoptic marine ecosystem observation system that operates at relatively high temporal frequencies, named PlasPi TDM. This instrument is an improved version of the camera system (PlasPI marine cameras) developed in 2020 by Autun Purser from the Alfred Wegener Institute Helmholtz Center for Polar and Marine Research (Germany), and collaborators. It incorporates several innovative developments such as multispectral (records the spectrum of any object photographed), temperature and pressure sensors. The PlasPi TDM operates to a depth of 200 m. The various field deployments demonstrate the operational capability of the PlasPi TDM for different applications and illustrate its considerable potential for in-situ observations and marine surveillance in Africa. This device is intended as an open-source project and its continued development is encouraged for a more integrated, sustainable and low-cost ocean observing system.

Species-specific metabolites mediate host selection and larval recruitment of the symbiotic seastar shrimp

In marine environments, host selection, defining how symbiotic organisms recognize and interact with their hosts, is often mediated by olfactory communication. Although adult symbionts may select their hosts detecting chemosensory cues, no information is available concerning the recruitment of symbiotic larvae which is a crucial step to sustain symbioses over generations. This study investigates the olfactory recognition of seastar hosts by adult Zenopontoniasoror shrimps and the recruitment of their larvae. We examine the semiochemicals that influence host selection using chemical extractions, behavioural experiments in olfactometers, and mass spectrometry analyses. After describing the symbiotic population and the embryonic development of shrimps, our results demonstrate that asterosaponins, which are traditionally considered as chemical defences in seastars, are species-specific and play a role in attracting the symbiotic shrimps. Adult shrimps were found to be attracted only by their original host species Culcitanovaeguineae, while larvae were attracted by different species of seastars. This study provides the first chemical identification of an olfactory cue used by larvae of symbiotic organisms to locate their host for recruitment. These findings highlight the importance of chemical communication in the mediation of symbiotic associations, which has broader significant implications for understanding the ecological dynamics of marine ecosystems.

Temperature sensitivity of the interspecific interaction strength of coastal marine fish communities

The effects of temperature on interaction strengths are important for understanding and forecasting how global climate change impacts marine ecosystems; however, tracking and quantifying interactions of marine fish species are practically difficult especially under field conditions, and thus, how temperature influences their interaction strengths under field conditions remains poorly understood. We herein performed quantitative fish environmental DNA (eDNA) metabarcoding on 550 seawater samples that were collected twice a month from 11 coastal sites for 2 years in the Boso Peninsula, Japan, and analyzed eDNA monitoring data using nonlinear time series analytical tools. We detected fish–fish interactions as information flow between eDNA time series, reconstructed interaction networks for the top 50 frequently detected species, and quantified pairwise, fluctuating interaction strengths. Although there was a large variation, water temperature influenced fish–fish interaction strengths. The impact of water temperature on interspecific interaction strengths varied among fish species, suggesting that fish species identity influences the temperature effects on interactions. For example, interaction strengths that Halichoeres tenuispinis and Microcanthus strigatus received strongly increased with water temperature, while those of Engraulis japonicus and Girella punctata decreased with water temperature. An increase in water temperature induced by global climate change may change fish interactions in a complex way, which consequently influences marine community dynamics and stability. Our research demonstrates a practical research framework to study the effects of environmental variables on interaction strengths of marine communities in nature, which would contribute to understanding and predicting natural marine ecosystem dynamics.

Temperature sensitivity of the interspecific interaction strength of coastal marine fish communities.

The effects of temperature on interaction strengths are important for understanding and forecasting how global climate change impacts marine ecosystems; however, tracking and quantifying interactions of marine fish species are practically difficult especially under field conditions, and thus, how temperature influences their interaction strengths under field conditions remains poorly understood. We herein performed quantitative fish environmental DNA (eDNA) metabarcoding on 550 seawater samples that were collected twice a month from 11 coastal sites for 2 years in the Boso Peninsula, Japan, and analyzed eDNA monitoring data using nonlinear time series analytical tools. We detected fish-fish interactions as information flow between eDNA time series, reconstructed interaction networks for the top 50 frequently detected species, and quantified pairwise, fluctuating interaction strengths. Although there was a large variation, water temperature influenced fish-fish interaction strengths. The impact of water temperature on interspecific interaction strengths varied among fish species, suggesting that fish species identity influences the temperature effects on interactions. For example, interaction strengths that Halichoeres tenuispinis and Microcanthus strigatus received strongly increased with water temperature, while those of Engraulis japonicus and Girella punctata decreased with water temperature. An increase in water temperature induced by global climate change may change fish interactions in a complex way, which consequently influences marine community dynamics and stability. Our research demonstrates a practical research framework to study the effects of environmental variables on interaction strengths of marine communities in nature, which would contribute to understanding and predicting natural marine ecosystem dynamics.

Species Distribution Models as Tools for Community Empowerment and Informed Decision Making in Colombia’s Chocó Pacific Coast Fisheries

Changes in marine ecosystem dynamics have led to alterations in the availability of fish in established fishing grounds. Predictive models suggest their utility in understanding and predicting species distribution at varying depths and times of the year, significantly influencing regional fisheries management. Thus, access to information on oceanographic conditions, serving as a science-based decision-making support tool for artisanal fishers, has been identified as an adaptation strategy fostering social empowerment in the Colombian Pacific region. To address this need, an open-source WebGIS (geographic information system) was co-created to provide users with the results of species distribution models of marine fish species, aiming to expand knowledge of the ever-changing environment dynamics. The Chocó Artisanal Fishing Geovisor offers options for planning fishing operations and provides tools for understanding the results of species distribution models and resource management. By promoting informed decision making and community empowerment, it serves as a strategic response to marine environmental fluctuations, establishing itself as an essential tool for adapting to shifting marine conditions and ensuring food security.

Diel vertical migration in Pacific sand lance (Ammodytes personatus)—a pelagic forage fish associated with benthic substrates

AbstractDiel vertical migration (DVM) in marine organisms is an evolved response to maximize foraging opportunities and minimize predation risk. This pattern in vertical distribution is a widely observed phenomenon and common in pelagic forage fish species. Modelling these dynamics has important relevance to understanding marine ecosystem dynamics, predator–prey interactions, and marine food webs. We examine DVM in sand lance—an ecologically important taxa of forage fishes throughout northern hemisphere marine systems and target of commercial fisheries. Much remains unknown about their diurnal emergence from sediments. We apply data from autonomous stereo-camera deployments and tank observations to provide new insight to DVM patterns in Pacific sand lance (Ammodytes personatus). We model emergence curves using beta regression models with random effects, depicting important differences in the shape of ascent and descent. Our observations and analyses document crepuscular movement patterns, suggesting pelagic foraging occurs primarily at dawn and dusk. Results suggest critical light thresholds are necessary to initiate and maintain pelagic foraging. Results also suggest the importance of seasonality and life stage, such that adult fish exhibit reduced pelagic foraging in the fall relative to juvenile fish. These results constitute a comprehensive evaluation of DVM in this species, better define the physical drivers, and mathematically depict the pattern and shape of emergence timing.