Marta Coll’s research while affiliated with Institut Marqués, Spain, Barcelona and other places

Food webs depict the intricate connections between organisms in ecosystems, vital for grasping energy and material transfers. However, creating precise food webs is challenging due to the complexity of ecological systems and the need for extensive data. Recent advancements in artificial intelligence (AI), notably in Natural Language Processing (NLP), are revolutionizing data handling, particularly with the availability of large datasets containing nodes (i.e., species) within food webs. Here we present FoodwebAI, a user-friendly web application that fills gaps in species records with additional metadata and creates food webs using only taxa lists by combining limited ecological knowledge with AI capabilities. We utilized OpenAI's GPT-3.5-Turbo model via the rpgt3 package in R to augment (i.e. to complement the species within a list with additional properties) three existing species-based food webs of varying complexity (Arctic, Chesapeake Bay, and Amazon River basin) by classifying taxa by their "type" (e.g., fish, bird, invertebrate, mammal, primary producer and detritus) and International Union for Conservations of Nature (IUCN) conservation status. Additionally, we used FoodWebAI to recreate the three food webs using only the taxa list as input data from each ecosystem and verify its accuracy. FoodWebAI achieves the highest accuracy rates (assessed by comparing the result to a known or accepted value) for the Arctic, both for augmenting species; calculating properties in an existing food web (accuracy rates ranging from 95 to 100%) and creating new food webs (achieving 100% accuracy in determining trophic levels and 79% accuracy in predicting trophic links). However, in ecosystems characterized by a larger number of taxa, such as the Chesapeake Bay and the Amazon River basin, with less familiar species and ambiguous taxa names, FoodWebAI provides lower accuracy rates when augmenting existing food webs by conservation status. For these two ecosystems, despite yielding good results for predicting trophic levels, the accuracy is lower when predicting trophic links. FoodWebAI is still experimental, however it opens a powerful complementary methodology for food web ecology. By bringing together food web ecology and AI, we take an important stride towards complementing access to global data and attaining a better understanding of complex network systems. Such advancements are vital in times of rapid global change, where society needs to make swift decisions and act based on scientific knowledge. The application can be accessed online at https:// foodwebai.shinyapps.io/foodweb.

Fisheries have transformed significantly in recent decades, and further changes are anticipated to address pressing environmental and social challenges. In this context, there is an urgent need to implement science-based public policies that incorporate local knowledge. It is necessary to better assess fishers' perceptions, including both historical (e.g., perceived changes of abundance of species) and future (e.g., views on potential future changes) perspectives. In this paper, we focus on a case study of small-pelagic fisheries in the Spanish northwestern Mediterranean Sea, using semi-structured interviews, graphical analysis, and a Q-methodology. Based in the information obtained from all the active purse seiners vessels in Castelló de la Plana, the most important Spanish Mediterranean small pelagic purse seine harbour, we show how these methodologies are useful for gathering fisher's knowledge regarding historical biomass trends for small pelagic and accompanying species over the last six decades, contributing valuable information on periods where no scientific assessments were available. When looking towards the future, Q-methodology reveals three fisher discourses regarding how to ensure the future sustainability of fisheries: (i) "We don't need more subsidies we need more fish," (ii) "We need more public support for fishing," and (iii) "The future of the fishery it's not in our hands". These three perspectives highlight internal disagreements about what should be the priorities for implementing public policies. However, results also show consensus that the implementation of adaptive management measures can be of common interest, and that bottom trawling activities should avoid juveniles and spawning ground of small pelagic fish.

Marine heatwaves are events of extreme warming in the ocean and have devastating consequences for marine life. Here we used a K-mean clustering analysis to detect different types of marine heatwaves along the South American coast from 10°S to 45°S and identify their remote drivers. In the central part of the domain, marine heatwaves are associated with atmospheric blocking caused by wave trains triggered by the Madden-Julian Oscillation. On the other hand, marine heatwaves occurring along the northern and southern coast of South America are associated with El Niño and La Niña events, respectively. The intensity and duration of these marine heatwaves are modulated by the development phase and intensity of the Niño and Niña events. By identifying the climatic modes of variability leading to each type of marine heatwaves, our study can help develop adaptation strategies, such as early warning systems, to prevent the devastating effects of marine heatwaves.

The coastal fishing sector encompasses a great diversity of fishing activities, each exhibiting distinctive ecological, social, and economic characteristics. These activities are subject to a complex interplay of common and opposing interests, resulting in competitive and collaborative behaviours. This paper presents a case study of the Catalan Mediterranean Sea, examining the diversity of fishing fleets from the perspective of Sustainable Development Goals (SDGs) 2, 8, 12, 13 and 14. The results of this study demonstrate the trade-offs between fishing fleets' performances in relation to the explored SDG objectives, and the common but differentiated contributions of the fleets tracked. Secondly, the competition for shared stocks and the economic implications of fleets' competition in terms of catches are assessed. The bottom trawl fleet is found to interact the most with the rest of the fleets. Finally, we evaluate the collaborative relations between the fleets through the analysis of the collective success attracting public subsidies and achieving tax exemptions for the sector. While being a collective action, again, the bottom trawl fleet is the most benefited. These results contribute to the ongoing debate on the socio-ecological and economic transitions taking place worldwide. In our case, the asymmetry between fleets is especially relevant because of the dominant role of bottom trawls over other fishing fleets. The recognition of this asymmetry has significant implications for the management of coastal fisheries and the formulation of public policies, as these should be managed according to the social interests over which fisheries act. In conclusion, this study highlights why coastal fishing activities cannot be considered as a single unit, but as a diversity of fishing activities that interact, compete, and collaborate for ecological and economic resources in a shared socio-ecological system.

Understanding societal interest in invasive species is crucial as greater public attention can support the success of conservation efforts. One of the main challenges in monitoring societal interest to support conservation is the absence of near-real-time indicators to track large-scale spatiotemporal dynamics of public attention. However, the digital revolution has opened up new opportunities to develop such indicators in support of invasive species research and management. Here, we aim to evaluate public awareness and interest in the invasive lionfish (Pterois miles) in the Mediterranean Sea and investigate spatiotemporal patterns of public interest in the species along its invasion front by using Google search volumes as a proxy for public attention. We implemented topic searches for the lionfish to download Google search volumes from 2013 to 2022 and used these data to test two hypotheses: (1) countries experiencing lionfish invasion exhibit higher public attention than those without lionfish, and (2) in invaded countries, public attention peaks around the arrival year, followed by a decline to baseline levels. Our study confirmed the first hypothesis, showing higher public attention in invaded countries. However, temporal patterns of attention did not fully align with the year of lionfish arrival, suggesting that the socio-political complexity of the region (e.g., cultural trends or internet accessibility), may be a key aspect to consider in future studies. Overall our study shows that digital data sources provide a unique opportunity to monitor social aspects of biological invasions with low associated costs and quick access to a great amount of data generated by internet users.

In this study, we aimed to quantify the presence of microplastics (MPs) in the stomachs of large pelagic fish (swordfish, Xiphias gladius, Linnaeus, 1758) sampled in the western Mediterranean Sea, and assess temporal trends (2011–2012 vs. 2017–2019) in MP ingestion. MPs were extracted from stomachs and characterized by μ-Fourier transform infrared spectroscopy. Results highlighted the ingestion of MP in 39 out of 49 stomachs analysed. Ingested MPs consisted mostly of small (<1 mm) fibers (88.6 %, mean ± standard deviation = 2.5 ± 6.1 particles per stomach), with a greater frequency of occurrence (FO) in the second period (FO = 90 %, 3.3 ± 8.0 particles per stomach). The predominant colours were purple, black and blue, and polyethylene terephthalate was the most frequently detected polymer. These results are crucial for the development of management actions aimed at the conservation of swordfish in the Mediterranean Sea and the prevention of health risks to humans.

In various parts of the world, the fisheries sector is undergoing a rapid transition due to a combination of ecological and economic stressors. In this context, there is a growing interest in employing integrated ecological-economic tools that facilitate the adoption of ecosystem-based fisheries practices within a value chain perspective. These tools aim to contribute to find management options that decrease ecological impacts while increasing socioeconomic benefits. Our study integrates a food-web model with a value-chain model for an area of the Mediterranean Sea. This case study may provide valuable insights for decision-makers: 1) it allows the calculation of indicators that go beyond species evaluation and fisheries incomes, which are relevant for assessing fisheries management; 2) it offers a more comprehensive perspective on what should be considered priority fisheries species and their key characteristics; and 3) it supports the identification of key actors of the fisheries value chain and generates pertinent information to use in vertically integrated decision-making initiatives.

Species Distribution Models (SDMs) have been widely applied in ecology to analyze the historical and future patterns of marine species' distributions. With the increasing impact of climate change in recent decades, understanding potential shifts in species distributions has become a crucial challenge. Research on alterations in spatial and temporal distributions has revealed an increasing focus on developing different statistical approaches for global-scale and long-term forecasts. One promising approach is Bayesian Additive Regression Trees (BART), a non-parametric machine learning tool based on a sum-of-trees model that could be useful for addressing ecological problems. The goal of this study is to apply BART on a global scale and use it to estimate and predict possible present and future habitats of marine species under different climate change scenarios. Here we show an application of BART focused on the functional group of marine turtles, analyzing their historical and future distributions both individually and as a taxonomic group, their relationship with environmental variables, and BART's capacity to predict long-term distributions at global scales. Furthermore, to assess the capabilities of BART, we conduct a simulation study under two distinct scenarios: 1) simulating a hypothetical cosmopolitan species distribution and 2) simulating a hypothetical persistent species distribution. Our results show that BART is a promising approach to predict the potential distribution of our target species, as well as their relationship with key environmental variables, on a global scale.

Marine heatwaves (MHWs) are episodes of anomalous warming in the ocean that can last from a few days to years. MHWs have different characteristics in terms of intensity, duration and frequency and generate thermal stress in marine ecosystems. In reef ecosystems, they are one of the main causes of the decreased presence and abundance of corals, invertebrates and fish. The deleterious capacity of thermal stress often depends on biotic factors, such as the trophic control of predators on prey. Despite the evidence of thermal stress and biotic factors affecting individual species, the combined effects of both stressors on entire reef ecosystems are much less studied. Here, using a food web modelling approach, we estimated the rate of change in species' biomass due to different MHW characteristics. Specifically, we modelled the mechanistic link between species' consumption rate and seawater temperature (thermal stressor), simulating species' biomass dynamics for different MHW characteristics under different trophic control assumptions (top‐down, mixed trophic control and bottom‐up). We find that total reef ecosystem biomass declined by 10% ± 5% under MHWs with severe intensity and a top‐down control assumption. The bottom‐up control assumption moderates the total ecosystem biomass reduction by 5% ± 5%. Irrespective of the MHW characteristics and the trophic control assumption, the most substantial biomass changes occur among top, mesopredators and corals (5% to 20% ± 10%). We show that reef ecosystems where predators exert top‐down control on prey are prone to suffer species abundance declines under strong MHW events. We identify food web trophic control as a crucial driver that modulates the impacts of MHWs. Overall, our results provide a unified understanding of the interplay between abiotic stressors and biotic factors in reef ecosystems under extreme thermal events, offering insights into present baselines and future ecological states for reef ecosystems.