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Under pressure: deep-sea elasmobranchs experience high mortality and stress in a crustacean trawling fishery
Publication . Graça Aranha Carvalho Ramos, Sofia; Teodosio, Maria; Marsili, Tiago; Pires da Rocha, Pedro; Modesto, Teresa; Guerreiro, Pedro Miguel; Tambutte, Aurélien; Carvalho Alves, Alexandra; Relvas, Paulo; Dias, Ester
Crustacean bottom trawling in southern Portugal is an economic and culturally important fishing activity but may result in considerable bycatch of deep-sea elasmobranchs (DSE). Due to DSE life-history strategies, at-vessel mortality (AVM) rates in crustacean bottom trawl fisheries are expectedly high but require further investigations. This study assessed the at-vessel condition of 18 species of DSE, and AVM rates and stress of four deep-sea shark species (Etmopterus pusillus, E. spinax, Galeus melastomus, and Scymnodon ringens), to understand the impact of bottom trawling on these animals. Opportunistic sampling on a crustacean trawler in the southern Portuguese coast, revealed that 95% of specimens were either dead (n = 1,258) or in poor condition (n = 224) upon collection, underscoring their minimal chance of post-release survival. General linear model analyses showed that AVM was species-specific and highest in smaller sharks, as well as in those from hauls that exhibited larger temperature dierences between bottom and surface waters, and those caught in hauls with heavier codend weight using a 55 mm codend mesh (targeting shrimp and prawns) instead of those caught in hauls using a 70 mm codend mesh (targeting Norway lobster). Stress, evaluated through metabolites and electrolytes levels in sharks’ plasma, indicated significant dierences in potassium, urea, and magnesium levels between live and deceased specimens of E. pusillus and G. melastomus, suggesting these as reliable mortality markers. Elevated lactate levels in G. melastomus further pointed to high post-release mortality risk. These findings highlight an urgent need to find solutions to mitigate the impacts of bottom trawling on those DSE, which are thoroughly discussed. A coordinated, multi-stakeholder approach involving researchers, the fishing industry, and regulatory bodies is crucial for developing and implementing eective, and more sustainable fisheries management and protection of DSE populations.
Machine learning applications in use-wear analysis: a critical review
Publication . Eleftheriadou, Anastasia; McPherron, Shannon P.; Marreiros, João
Use-wear analysis examines the macroscopic and microscopic patterns of traces left on tool surfaces as a result of use. Recently, machine learning (ML) has been employed as a promising method for automating and standardizing the identification of these traces. While the number of use-wear analysts using ML continues to grow, discussions regarding the effectiveness and appropriate implementation of these methods are ongoing. The main aim of this literature review is to provide recommendations for the more effective application of ML in use-wear analysis and archaeological research, by identifying trends, research gaps, and evaluating the quality of the models developed.
There are three key challenges identified. Firstly, the limited adoption of open science practices restricts the creation of large datasets and hinders reproducibility and transparency. Secondly, research efforts are concentrated within limited institutions, focusing on certain research questions, algorithms, raw materials, and use-wear traces. Thirdly, the inadequate quality, quantity, and diversity of data affect the performance of the models being developed.
To address these challenges, this paper advocates for the promotion of open science and the systematic gathering of experimental and analytical data. Involving a broader range of institutions can improve research quality and promote greater diversity of perspectives. Collaboration with computer scientists and computational archaeologists is essential to integrate the expertise necessary for designing and implementing effective ML methods. By addressing these factors, this paper facilitates the effective use of machine learning, enabling use-wear analysts and archaeologists to develop robust models that automate, accelerate, and improve their research.
Relationship between skin and body condition in three species of baleen whales
Publication . Neves, Joyce; Methion, Séverine; Díaz López, Bruno
The assessment of free-ranging cetacean health through the study of skin conditions using photographs has gained prominence in recent years. However, little attention has been given to the relationships between cetacean skin conditions, species, and body condition. To explore this relationship among baleen whale species along the northwestern coast of Spain, we employed a non-invasive method involving photograph analysis. In this study, we examined skin conditions (including injuries, epizoites and ectoparasites, pigmentation disorders, skin lesions, and anatomical malformations) and body condition (overall physical contours and form, as an indicator of nutritional status and health) in 3 species of whales (blue, fin, and minke whales). This methodology facilitated the identification of 29 subcategories of distinct skin conditions and an assessment of body condition over a 5 yr period (2017 to 2021). In our study, we present evidence linking hypopigmentation, protruding pieces of tissue, and tattoo-like lesions to ‘Poor’ body condition in the 3 baleen whale species. Fin whales exhibited a higher susceptibility to mottling (prevalence = 17.7%), while blue whales were more prone to starbursts (prevalence = 90.5%). Additionally, we found a significant relationship between skin condition diversity and individual body condition. Our findings contribute valuable information to the broader understanding of the health status of baleen whales. Further investigations are necessary to delve into the etiology of the documented skin conditions and their potential implications for individual survival. This study serves as a foundation for ongoing research aimed at advancing our comprehension of these findings.
Lexicalized meaning representation (LMR)
Publication . Baptista, Jorge; Reis, Sónia; Dias, João; Santos, Pedro A.
This paper presents an adaptation of the Abstract Meaning Representation (AMR) framework for European Portuguese. This adaptation, referred to as Lexicalized Meaning Representation (LMR), was deemed necessary to address specific challenges posed by the grammar of the language, as well as various linguistic issues raised by the current version of AMR annotation guidelines. Some of these aspects stemmed from the use of a notation similar to AMR to represent real texts from the legal domain, enabling its use in Natural Language Processing (NLP) applications. In this context, several aspects of AMR were significantly simplified (e.g., the representation of multi-word expressions, named entities, and temporal expressions), while others were introduced, with efforts made to maintain the representation scheme as compatible as possible with standard AMR notation.
Charting the linguistic landscape of developing writers: an annotation scheme for enhancing native language proficiency
Publication . Da Corte, Miguel; Baptista, Jorge
This study describes a pilot annotation task designed to capture orthographic, grammatical, lexical, semantic, and discursive patterns exhibited by college native English speakers participating in developmental education (DevEd) courses. The paper introduces an annotation scheme developed by two linguists aiming at pinpointing linguistic challenges that hinder effective written communication. The scheme builds upon patterns supported by the literature, which are known as predictors of student placement in DevEd courses and English proficiency levels. Other novel, multilayered, linguistic aspects that the literature has not yet explored are also presented. The scheme and its primary categories are succinctly presented and justified. Two trained annotators used this scheme to annotate a sample of 103 text units (3 during the training phase and 100 during the annotation task proper). Texts were randomly selected from a population of 290 community college intending students. An in-depth quality assurance inspection was conducted to assess tagging consistency between annotators and to discern (and address) annotation inaccuracies. Krippendorff’s Alpha (K-alpha) interrater reliability coefficients were calculated, revealing a K-alpha score of k=0.40, which corresponds to a moderate level of agreement, deemed adequate for the complexity and length of the annotation task.