Skin marks in Capitoline dolphins shed light on threats to the population at the Tiber River Estuary (Mediterranean Sea)

Skin marks in Capitoline dolphins shed light on threats to the population at the Tiber River Estuary (Mediterranean Sea) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Skin marks in Capitoline dolphins shed light on threats to the population at the Tiber River Estuary (Mediterranean Sea) Alice Turchi, Giulia Pedrazzi, Alex Mattiussi, Maria Silvia Labriola, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4814406/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The analysis of skin marks and lesions is used for many cetacean species to assess the general health status of the populations, based on evidence of interaction between conspecifics and with human activities. This study applies mark analysis to characterise common bottlenose dolphin ( Tursiops truncatus ) skin marks and lesions, and their evolution in time, in the Tiber River Estuary area (Mediterranean Sea, Italy), to test their efficacy as proxies of individual or population health in a region under several anthropogenic pressures. Using high-quality photographic data collected between 2016 and 2023 during 205 sightings, marks were identified, classified, counted and measured on 39 individuals photographed on multiple occasions. Marks related to intraspecific interactions ( e.g. , tooth-rakes), anthropogenic activities ( e.g. , signs of interaction with fishery) and health conditions ( e.g. , skin diseases and emaciation) were selected as indicators, and five indices were applied to estimate their extension and progression through time. Prevalent marks in all individuals were of social origin and aggressive nature. Marks related to skin diseases and emaciation were present in 97% and 70% of individuals, respectively. Almost half of the individuals showed physical signs of interaction with fishing gears. No significant trends in the temporal evolution of marks were observed. These results highlight that the local population is under the pressure of multiple stressors mostly related to human activities, both directly (fishing) and indirectly (malnutrition, aggression). The consequences of stressor interactions may be complex to predict and raise challenges for the conservation of this protected species in a highly anthropized area. Bottlenose dolphin skin lesions mark analysis anthropogenic threats conservation interaction with fisheries Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Disentangling the complex network of relationships between a species and the ecosystem it belongs to is challenging (Heinen et al., 2020 ). Direct observations of individuals interacting with both their biotic and abiotic surroundings may be difficult to collect, especially at sea (Marley et al., 2013 ), thus making the use of alternative and indirect techniques highly advantageous. In this framework, mark analysis has emerged in the past 20 years as a non-invasive and reliable methodology to infer the level of exposure of a population to different environmental and ecological factors (Toms et al., 2020 ), and thus identify potential threats to its conservation. Indeed, social and environmental interactions by individuals can leave visible signs, or marks, on the body surface of the interactor (Herr et al., 2020 ; Leone et al., 2019 ; Serres et al., 2023 ). This is particularly relevant in hairless mammalian species, like cetaceans, as these marks may be clearly evident and easier to detect for observers. The use of mark analysis on high-quality pictures to study and characterise cutaneous lesions represents a wide-distributed and consolidated non-invasive technique and has been applied to several cetacean species, including common bottlenose dolphins ( Tursiops truncatus ) (Bertulli et al., 2016 ; Blasi et al., 2023 ; Feyrer et al., 2021 ; Grimes et al., 2022 ; James et al., 2022 ; Leone et al., 2019 ; Mariani et al., 2016 ; Serres et al., 2023 ; Stylos et al., 2022 ). Individuals may accumulate on their skin signs of interaction with the habitat and human activities ( e.g. , fishing gear-related injuries), which can indirectly provide different types of information (Blasi et al., 2023 ; Lee et al., 2019 ; Leone et al., 2019 ; Marley et al., 2013 ; Scott et al., 2005 ; Stylos et al., 2022 ; Taylor et al., 2021 ). Skin diseases and epidermal conditions ( e.g. , tattoo-like lesions), for instance, can be useful in evaluating habitat quality (Herr et al., 2020 ; Segura-Göthlin et al., 2023 ; Serres et al., 2023 ; Stylos et al., 2022 ; Taylor et al., 2021 ), reducing the necessity of invasive procedures, like biopsies, while speeding up the identification of possible pathogens. Emaciation is the most useful mark to study the nutritional status of a population, since it is directly linked to malnutrition (Dunkin et al., 2010 ; Herr et al., 2020 ). Indeed, malnutrition may be caused both by extreme competition and/or restricted access to food resources (even prey depletion), and thus be indicative of a potential suboptimal habitat for the population (Dunkin et al., 2010 ). In addition, many social exchanges and interaction behaviours ( e.g. , interaction with fishing gears) can leave recognisable marks on the body of the individuals (Scott et al., 2005 ; Würsig, 2019 ). Therefore, researchers are able to get a deeper understanding of a species sociality and behaviour, without the need for live observations, ultimately making ecological and ethological studies faster and more efficient (Blasi et al., 2023 ; Marley et al., 2013 ; Scott et al., 2005 ; Würsig, 2019 ). The common bottlenose dolphin is a global cetacean species mainly inhabiting coastal regions, for which some populations have been extensively monitored in long-term research programs. Being a long-lived species and feeding at the top of the food web, bottlenose dolphins are subjected to longstanding exposure to environmental and anthropogenic pressures (Wells et al., 2004 ). Because of this, they are considered a sentinel species, whose presence and health status can in turn be indicative of the ecosystem’s health (Wells et al., 2004 ), making their skin marks a valuable tool to gain insight on the pressures they face (Stylos et al., 2022 ). Furthermore, as small cetaceans and apex predators, they play important ecological roles, including predation, nutrient cycling, and foraging facilitation for other species (Kiszka et al., 2022 ), which is why their conservation can benefit the marine ecosystem at different levels. For these reasons, common bottlenose dolphins in the Mediterranean are protected under the EU Habitats Directive (92/43/CEE) Annex IV of the priority species, making their conservation a necessity (Pace et al., 2022 a). In the Mediterranean Sea, at the Tiber River Estuary (central Tyrrhenian Sea, Italy), the presence of a geographical unit of bottlenose dolphins, also known as “Capitoline dolphins”, is well-documented, with a population of 529 individuals as of 2020 estimates (Pace et al., 2021 ). Up to now, detailed analyses of skin marks and emaciation have not been conducted for this population. To fill this knowledge gap and address possible management actions, this study applies skin mark analysis to characterise common bottlenose dolphin lesions, and their evolution in time, with the aim of testing their efficacy as proxies to infer individual or population health in a region under severe threat from human activities. More specifically, the description, quantification and measurement of different marks and cutaneous injuries found on the entire body of individual dolphins, and the assessment of changes in marked surface over time ( i.e. , the rate of change; Bertulli et al., 2016 ; Feyrer et al., 2021 ; Luksenburg, 2014 ; Olaya-Ponzone et al., 2020 ; Serres et al., 2023 ; Stylos et al., 2022 ; Taylor et al., 2021 ) are used to estimate the severity of potential pressures in the area. Methods Study area The study area is located in the Western Mediterranean Sea (Central Tyrrhenian Sea), near the city of Rome (Italy), covering approximately 1300 \(\:{Km}^{2}\) between the coastline and the Italian territorial waters’ limit of 12 nm (Fig. 1 ). It is a highly productive area, characterised by a variety of environmental conditions and habitats including: (1) the Tiber River Estuary, which brings organic matter to the oligotrophic Mediterranean waters and transfers several pollutants collected during the transit in the city of Rome (Montuori et al., 2016 ); (2) two single-point moorings (SPMs) called R1 and R2, and located 3 nautical miles from the coast, where crude oil and petroleum products are received; and (3) the Marine Protected Area (MPA) called “Secche di Tor Paterno” (Tor Paterno Banks, Natura 2000 Code: IT6000010). The regular occurrence of bottlenose dolphins in the area has been documented since 2016, with the presence of at least 42 resident individuals, over a total of 362 photographically identified animals (Pace et al., 2021 ). Many feeding groups and females with calves have been repeatedly sighted each year, suggesting the area might be an important foraging and breeding site for the species (Pace et al., 2021 , 2022 a, 2022 b; Pedrazzi et al., 2022 ). The area is heavily exposed to human disturbance, mainly deriving from three sources (Pace et al., 2019 ): (1) artisanal and commercial fishing, largely ascribable to trawling fisheries (Pace et al., 2022 b); the local trawling fleet is composed of 25–30 vessels of 18–25 m in length, which operate from Monday to Friday on the continental shelf and slope (in compliance with the national regulations of a minimum of 50 m depth or 3 nautical miles from the coast); (2) maritime traffic, which refers to both commercial vessels and pleasure boats; (3) recreational activities, such as sportfishing, whale watching and diving. Data collection Data were collected through daily boat-based surveys using a Benteau Oceanis 41.1 sailing vessel equipped with a 55 hp Volvo diesel engine, in optimal weather conditions (sea state \(\:\le\:\) 3 Douglas, wind force \(\:\le\:\) 3 Beaufort, no rain, no fog) to reduce detection probability bias (Pace et al., 2021 ). Most of the surveys were conducted from late spring to early autumn, in a 4-to-6-months span over 8 consecutive years (2016–2023). Once at sea, an adaptive sampling method (Martino et al., 2021 ; Pace et al., 2021 ) was employed to maximize the encounter probability, following the track lines reported in Fig. 1 . Once a group of dolphins was sighted, the searching effort was suspended and the animals were approached to collect visual data (i.e., group size, presence of calves, predominant behaviour) and assess eventual interactions with anthropic activities. Photographic data were collected while proceeding parallel to the direction of the group at very low speed, using Canon digital 5D and 6D cameras and Canon 100–400 mm f/4.5–5.6 L lens. Once good quality pictures of both sides of the animals were obtained, or if the animals showed any sign of discomfort, the sighting and data collection ended. Data analysis Photo-identification, dataset selection and body scoring A standard photo-identification protocol was applied to identify and catalogue individuals in the population (Pace et al., 2021 ). A number of 39 individuals (out of a total of 362 photo-identified animals) was randomly selected for the mark analysis, based on the number of available high-quality images allowing detailed mark descriptions and accurate measurements. Most of the selected individuals (97%) were characterised by a high level of site fidelity, and by multiple years of encounters, making the analysed sample quite representative of the portion of the population that permanently inhabits the area. In order to analyse as much of the dolphins’ body surface as possible, photographs of different body parts were selected for each individual and for each available year within the 2016–2023 study period. To account for the different proportions of visible body surface in different photographs, an operational protocol was developed (see Fig. 2 ). Each side of the animal’s body (right and left) was divided into five areas, namely anterior, dorsal fin, posterior, ventral, and flukes (Marley et al., 2013 ; Serres et al., 2023 ). The body partition was obtained without ambiguities by considering the length of the dorsal fin base (hereafter, FBL = Fin Base Length) as a standard measure to define the limits between an area and the other. Specifically, the dorsal fin area was separated from the anterior and posterior areas by two segments traced at a distance of ½ FBL from the dorsal fin itself, while the segment separating the dorsal fin area from the ventral area was traced at a distance equal to the FBL value from the fin. Lastly, the fluke area was simply defined as the region going from the base of the caudal fin to its extremes. Each of the ten body parts (i.e., the aforementioned five body areas defined on the left and right sides of the body) was scored from 0 to 3 based on their visibility (score 0: 70% of the section visible). Next, the scores assigned to each body part were summed up and divided by 30 (maximum score for an entirely visible dolphin, left and right sides), to calculate the pictures’ body scoring (BS). Then, BSs were summed for each individual separately every year, thus obtaining the proportion of visible dolphin body each year. The scoring was then integrated in yearly calculations of marked body surface to weigh the contributions of the different pictures. In total, 461 high-quality pictures were analysed and scored (number of pictures analysed per individual = 11–12). Mark analysis A catalogue consisting of 31 mark types and three mark categories [Skin Lesions (SI); Physical Impact (PI) and Emaciation (E)] was built and used for the mark analysis (Table 1 ), following the classification proposed by Correia et al. ( 2023 ). The full catalogue containing descriptions and photographs of the analysed marks is provided in the Online resource 1 of the Supplementary information (SI). Table 1 Mark categories and types identified in the Capitoline dolphin population (adapted from Correia et al., 2023 ) Mark category Mark type Skin lesions (SL) n = 16 Light Area (LA), Light Linear Lesion (LLL), Snake-Like Lesion (SLL), Light Mark (LM), Light Speckles (LSP), Light Fringed Spot (LFS), Dark Linear Lesion (DLL), Dark Mark (DM), Dark Area (DA), Dark Speckles (DS), Tattoo-Like Lesion (TTL), Starburst Lesion (SL), Nodules (ND), Vesicular Lesion (VL), Hyperplastic Lesion (HL), Hole (H) Physical impact (PI) n = 14 Wound (W), Cut (C), Fin Amputation (FA), Notch (N), Protruding Tissue (PT), Linear Scrape (LS), Linear Scrape-Tooth Rakes (LST), Linear Scrape-Anthropogenic (LSA), Scratch Patch (SP), Shark Bite Mark (SBM), Sea-Lamprey Mark (SLM), Scar (S), Bruising (B), Miscellaneous (M) Emaciation (E) n = 1 Emaciation (E) Eight attributes and features were assigned, measured and/or estimated for each mark type in every picture of selected individuals (Table 2 ), ultimately leading to cumulative yearly information for all individuals. For tooth rake marks only (included in the Physical Impact category), two additional features were recorded: 1) Age (New, Obvious, and Faint; Scott et al., 2005 ); 2) Number of rakes per tooth rake. In the case of heavily degraded fins, with multiple notches merged, the original fin was reconstructed in the most conservative way possible, excluding the protruding pieces, and the current profile of the fin was determined. This choice allowed for the measuring of missing fin surfaces due to notches and reduced the possibility of observer error bound to counting the wrong number of notches in the presence of multiple notches merged. All mark measurements were obtained using the software ImageJ 1.54d (Schneider et al., 2012 ). Table 2 Attributes and features used to describe each skin mark in each picture Attribute/Feature Description Mark code A unique code for each identified mark category or type Mark category Category to which the identified mark belongs to Mark type Type to which the identified mark belongs to Mark position Body section to which a mark belongs to Body visibility scoring The estimated proportion of the body visible in the picture Body area (pixels) The number of pixels belonging to the body of a dolphin in the picture Marked body area (pixels) The number of pixels belonging to the mark % of marked body area The percentage of body surface occupied by a mark (pixels) Statistical analysis To assess mark presence and distribution the number of marks on each of the available body areas (both left and right sides) was counted and the following five indices were computed: Total Number, Prevalence, Severity, % of body occupied, Richness (see Table 3 ) (Feyrer et al., 2021 ; Leone et al., 2019 ; Mariani et al., 2016 ; Serres et al., 2023 ; Stylos et al., 2022 ). Mark density on each body area was calculated as the number of marks per body area divided by the number of times the body area was present in the analysed pictures. Table 3 List of indices used to describe mark presence and distribution on Capitoline dolphins (adapted from Lee et al., 2019 ; Leone et al., 2019 ; Luksenburg, 2014 ; Marley et al., 2013 ; Serres et al., 2022 , 2023 ; Stylos et al., 2022 ; Taylor et al., 2021 ) Index Abbreviation Description Total number n i The number of marks of each category or type per photo per individual Prevalence p i The number of individuals with a certain mark category or type, divided by the total number of individuals in the population Severity l i The mean number of marks per mark categories or types on individuals with i mark category or type % of body occupied o i The mean percentage of body occupied by each mark of a certain category or type (except for “emaciation”) Richness r i The mean of the total number of mark categories or types present on an individual’s body To analyse how individuals changed over the study period, the Rate of Change metric (RoC) was adapted from James et al. ( 2022 ) and computed as: $$\:\text{R}\text{o}\text{C}=\:\frac{{\sum\:}_{{t}_{i}=1}^{{T}_{i}}({y}_{{t}_{i}+1}-{y}_{{t}_{i}})}{{T}_{i}}\:\forall\:\:i=1,\dots\:,N$$ where \(\:{y}_{{t}_{i}}\) is the percentage of marked body area for the \(\:i\:\) individual in the \(\:t\) year, and \(\:{T}_{i}\) is the number of follow-up years for the \(\:i\) individual. RoC calculation can yield positive or negative values, with positive ones indicating the accumulation of new marks throughout the study period and negative indicating a lower marked surface due to healing of marks. Since data were not available for all years for some individuals, the gap between non-consecutive years was filled considering the variation in markings as linear throughout the years. As at least two consecutive years are needed to calculate the RoC index, two individuals not meeting this criterion were excluded. To estimate the impact of fisheries operating in the area, a Probability of Fishing gear Injury (PFI) was calculated on mark types possibly related to fishing gear interactions (i.e., LSA and FA; see Table 1 ) as: $$\:PFI=\:\frac{\sum\:_{i=1}^{n}{N}_{i}}{\sum\:id}*100$$ where \(\:{N}_{i}\) is the number of individuals with at least one LSA or FA mark and \(\:id\) is the total number of photo identified individuals used in the analysis. R Studio software, version 2023.06.2 was used for all statistical analysis. A summary of data collection and analysis workflow is represented in Fig. 3 . Results Overall, 5055 marks were identified on 39 individuals using 461 high-quality pictures, which led to a BS (body scoring) of 0.12 per picture and 0.31 per year. As expected, the dorsal fin was the body area with the highest number of observations (n = 373; 45%), marks (n = 3234; 63%), and density (n = 9 marks per body section; 32%); relatively to the number of observations, the flukes were the area with the second highest number of marks and density (Fig. 4 ). A mean (± standard error) of 30.5 ± 1.1% of the body surface was occupied by skin marks. For all mark types, the following mean values of the different indices were estimated: Number \(\:{n}_{i}\) =163 ± 61; Prevalence \(\:{p}_{i}\) =37 ± 6; Severity \(\:{l}_{i}\) = 6 ± 2; % of body occupied \(\:{o}_{i}\) =0.97 ± 4.7 and Richness \(\:{r}_{i}\) =5±0.1. The mark category Physical Impact (PI) showed the highest values for all indices (Table 4 ) and was found on all body areas (Fig. 4 ). Linear Scrape-Tooth Rakes (LST), Linear Scrape (LS), Notch (N) and Scratch Patch (SP) were the most represented mark types within this category, being present on every analysed animal on all body parts. LST had the highest level of Severity (l = 30) and SP of % of body occupied (o = 25.8). Almost half LSTs (49%) were Faint, 38% Obvious and 13% New, with a mean of 5 rakes per tooth rake. Notches (N) were the most present marks on the dorsal fin and flukes. The mark category Skin Lesions (SL) was detected in all body areas except for flukes and signs of Emaciation (E) was only found in the anterior part. Table 4 Summary of the indices calculated for mark categories and types. Only the 13 marks with the highest or lowest value for each index are reported (see also full table in SI Online resource 3) Mark category Mark type \(\:{\varvec{n}}_{\varvec{i}}\) \(\:{\varvec{p}}_{\varvec{i}}\) \(\:{\varvec{l}}_{\varvec{i}}\) \(\:{\varvec{o}}_{\varvec{i}}\) Skin Lesions (SL) 474 97 12 0.4 ± 0.04 Light Area (LA) 78 77 3 0.21 ± 0.04 Dark Mark (DM) 17 31 1 0.006 ± 0.02 Dark Speckles (DS) 11 23 1 0.003 ± 0.001 Tattoo-like Lesion (TLL) 4 3 4 0.006 ± 0.003 Physical Impact (PI) 4557 100 117 28.7 ± 1.3 Linear Scrape-Tooth Rakes (LST) 1172 100 30 2.2 ± 0.2 Linear Scrape (LS) 1093 97 29 0.4 ± 0.02 Notch (N) 1069 100 27 0.2 ± 0.01 Scratch Patch (SP) 744 100 19 25.8 ± 1.3 Linear Scrape-Anthropogenic (LSA) 61 41 4 0.05 ± 0.1 Fin Amputation (FA) 47 18 7 0.06 ± 0.04 Bruising (B) 1 3 1 0.0002 ± 0.0002 Miscellaneous (M) 1 3 1 0.0004 ± 0.0004 Shark Bite (SBM) 1 3 1 0.002 ± 0.002 Emaciation (E) 43 72 2 - As for the temporal evolution of marks, the overall average RoC was 0.35 ± 0.59. The highest RoC (6.9) was found on a male individual (ID 040), indicating a predominance of scarring processes on healing, while the lowest one (-12.1) on the individual ID 139, implying opposite processes (Table 5 ). The Probability of Fishing gear Injuries (PFI) was 48%, meaning that almost half of the individuals presented physical signs of interaction with fishery. Table 5 RoC (Rate of Change), \(\:{y}_{{t}_{i}}\) (the percentage of marked body area for the \(\:i\:\) individual in the \(\:t\) year), and \(\:{T}_{i}\) (the number of follow-up years for the \(\:i\) individual) for individuals with more than one year of observation. The six most relevant individuals (highest and lowest RoC) over the total of 37 are reported (full table in SI Online resource 4) ID individual \(\:{\varvec{y}}_{2016}\) \(\:{\varvec{y}}_{2017}\) \(\:{\varvec{y}}_{2018}\) \(\:{\varvec{y}}_{2019}\) \(\:{\varvec{y}}_{2020}\) \(\:{\varvec{y}}_{2021}\) \(\:{\varvec{y}}_{2022}\) \(\:{\varvec{y}}_{2023}\) \(\:{\varvec{T}}_{\varvec{i}}\) RoC 003 55.6 36.2 36.2 36.2 36.2 36.2 36.2 36.2 2 -9.7 039 - 21.0 38.3 31.7 56.1 50.6 50.6 21.0 6 4.9 040 - - 23.2 30.4 52.4 47.2 57.7 - 5 6.9 139 - - 62.1 62.1 62.1 62.1 1.4 - 5 -12.1 221 - - 23.6 23.6 23.6 23.4 4.8 - 5 -3.8 366 - - - - 31.5 31.5 50.8 - 3 6.4 Discussion This study analysed for the first time the skin marks of the Capitoline bottlenose dolphin population through the application of mark analysis on the entire animals’ body. Not many studies have assessed mark presence on the whole body in cetacean species (Bertulli et al., 2016 ; Herr et al., 2020 ; J. Kiszka et al., 2008 ; Leone et al., 2019 ; Luksenburg, 2014 ; Marley et al., 2013 ; Scott et al., 2005 ), often analysing dorsal fins only, and most of them lack a discrete measurement of the size of skin marks, with a possible information loss. Studying barely the dorsal fin can limit the efficiency of the methodology (Toms et al., 2020 ), reducing, if not eliminating, the possibility of noticing relevant mark categories, such as emaciation. Assessing the marked surface without its measurement can lead to an over- or under-estimation of the marked body area, possibly impacting not only the study per se , but also any comparison between populations, making them less reliable. Here, in the selected sample of 39 dolphins, 3 out of 6 mark categories, and 29 mark types out of 60 listed by Correia et al. ( 2023 ) were found. No signs of anatomical malformations, anomalous pigmentation, or epibionts were detected in the analysed individuals. Although we here reported only a portion of the bottlenose dolphin population at the Tiber River estuary, most of the selected individuals (97%) presented a high level of site fidelity and multiple years of encounters, thus making the analysed sample sufficiently representative of the population inhabiting the area and thus persistently exposed to local pressures (Hanninger et al., 2023 ). On average, almost 1/3 of the visible body of the analysed animals was found to be covered by marks. This result doesn’t seem to have a precedent in the current literature on common bottlenose dolphin mark analysis, since to our knowledge measurements of marked body surface on the whole animal’s body have never been investigated before in this species. The dorsal fin was the body area with the highest density of marks, followed by the flukes. Their high values highlight the important role that these protruding appendices assume in the interactions with the environment and conspecifics (Würsig, 2019 ). Scott et al. ( 2005 ) in their analysis of tooth rake prevalence found the highest presence of aggression-related marks on the dorsal fin area. Marley et al ( 2013 ) suggested that, at least for aggressive interactions, dolphins might accumulate more tooth rakes on this area by exposing their less-vulnerable dorsal side to the attacks. As for interactions with their environment, especially fisheries, physically speaking protruding appendices such as the dorsal fin and the flukes may accumulate marks easier because of their vertical extension from the body of the animal, thus explaining the higher mark presence in these areas. The prevalence of externally visible marks was of 100%, similarly to what was found in other mark analysis studies (Stylos et al., 2022 ). In particular, Skin Lesions (SL) showed a prevlalence of 97%, higher than what previously observed in other bottlenose dolphin populations (Stylos et al., 2022 ; Taylor et al., 2021 ). Their widespread presence in a highly polluted environment like the Tiber River Estuary is not surprising and might indicate a worse water quality in the study area, compared to other locations (Herr et al., 2020 ; Serres et al., 2023 ; Stylos et al., 2022 ; Taylor et al., 2021 ). However, since biological samples were not collected in our study, the specific origin of most skin lesions cannot be attributed with certainty and further investigations are needed to validate any link with chemical pollution in the area. The only mark type of recognized infectious origin was the tattoo-like lesion (TLL), caused by the cetacean poxvirus (CePV) (Powell et al., 2018 ; Segura-Göthlin et al., 2023 ). TLL overall indices were similar to the ones found by Stylos et al. ( 2022 ), with a prevalence of 3% in our population, and 2.8% in the Welsh ones. These values are lower than the ones commonly found in other common bottlenose dolphin populations. For example, the most recent study reports a TLL prevalence of 19.4% in the Shark Bay (Australia) bottlenose dolphins (Powell et al., 2018 ). Considering tattoo-like lesions are usually detected in cetaceans inhabiting polluted nearshore waters and can be exacerbated by high concentrations of halogenated organochlorines (Serres et al., 2023 ), this relatively low presence in individuals at the Tiber River Estuary is surprising and could indicate lower CePV incidence in the study area. On the other hand, it is possible that a higher number of individuals from the studied population might be infected by CePV, even if not presenting physical signs of infection, as the CePV responsible for TLL has also been found on apparently healthy skin with low viral loads (Segura-Göthlin et al., 2023 ). Our study found more than 2/3 of the individuals to be emaciated, with the presence of visible ribs on over 70% of the population. Emaciation has direct consequences on the energetic necessities of bottlenose dolphins, as it reduces the thickness of the blubber, causing the animals to be 12 times more negatively buoyant than non-emaciated individuals (Dunkin et al., 2010 ). Thus, emaciated individuals might experience higher locomotion costs, increasing the nutritional stress to which they are already subjected, with potential higher mortality rates (Dunkin et al., 2010 ). Malnutrition is usually caused by prey scarcity and/or low prey availability due to competition (Dunkin et al., 2010 ). While direct evidence of reduced prey availability cannot be inferred by photographic data alone, the high prevalence of emaciation suggests a reduced access to prey. Professional and recreational fishing are highly present pressures in the area (Pace et al., 2022 a). The exacerbated fishing effort could be a factor contributing to reducing prey access for this population. Prey depletion may also be linked to other human-induced causes, such as disturbance generated by maritime traffic or pollution (Leone et al., 2019 ). To reduce the energetic costs associated with finding scarcely abundant prey, dolphins might turn to commercial fishing to gain easy access to fish. In this study, fishing-related marks were frequently observed (PFI = 48%), reflecting the already reported common interaction with fishery by Capitoline bottlenose dolphins (Pace et al., 2022 b). Almost half of the population showed signs of interaction with commercial fishing, particularly trawling. However, bycatch seems to be limited (Carpentieri et al., 2021 ; Pace et al., 2022 b), suggesting that individuals in the study area might have learned to reduce the hazards associated with trawling interactions. The high levels of interaction with fishery here observed may therefore be a symptom of a broader problem, possibly related to the reduction of prey abundance in the area. The high prevalence intra-specific aggression-related marks (tooth-rakes) seem to support this hypothesis as well (aggression can derive from competition for food; Scott et al., 2005 ; Marley et al., 2013 ). Prey scarcity could induce variations in the abundance of the population, as the relationship between overfishing, prey depletion and decreased abundance has been already reported in other cetacean species (Bearzi et al., 2006 ; Moore, 2013 ). Monitoring the interaction of bottlenose dolphins with trawlers and the abundance of their potential prey over time can be highly significant towards the conservation of this species. As for the mark changes over time, RoC values showed high inter-individual variability in the cumulative marked area, with a common tendency of accumulating new marks, rather than healing capacities. It is known that the healing process in common bottlenose dolphins may be sped up by higher water salinity levels (Hurst & Orbach, 2022 ). This condition is not found in the study area, bound to its estuarine nature, thus not positively affecting healing times. In addition, a predominance of scarring processes was found in a male individual with a high degree of site-fidelity, opening further investigations on both sex-specific and residency-related differences in markings (Leone et al., 2019 ; Marley et al., 2013 ; Scott et al., 2005 ). In conclusion, by using a non-invasive, low-cost, and time-efficient technique, this study provided – for the first time – strong evidence that common bottlenose dolphins residing in the Tiber River Estuary are under the pressure of multiple stressors. This information is critical, especially in an area where there are no conservation efforts or management actions in place for this sentinel species. At the same time, the methods presented in the study could represent a useful baseline to make initial assessments of the health of common bottlenose dolphins populations in highly impacted coastal regions, as previously done with other coastal cetacean populations (e.g., Guiana dolphins, Sotalia guaianensis ) (Soares et al., 2022 ). Declarations Competing interests The authors declare the absence of conflicts of interest. Compliance with ethical standards No ethical review nor approval was necessary for this study because of its non-invasive nature. Funding This work was supported by Sapienza University of Rome under the Ateneo Grant Program [number RM1221816AE34004]. Author Contribution Conceptualization and methodology: A.T. and D.S.P.; field work: A.T., G.P., A.M., M.S.L., G.G., D.S.P.; photo-identification analysis: A.T. and A.M.; mark analysis: A.T.; statistical analysis: A.T., G.P., D.P., and D.S.P.; writing: A.T. and D.S.P.; revision and approval: all authors. All authors read and approved the final manuscript. Acknowledgement We thank all the master’s degree students who helped with data collection and photo-identification during the years. We also thank Daniela Taliana, Eleonora De Sabata, Cristiana Roppo and Carlotta Vivaldi for providing us with additional photographic materials. A special thanks to Giovanna Jona-Lasinio for statistical suggestions. Data Availability The data used for this article can be made available by the authors upon reasonable request. References Bearzi, G., Politi, E., Agazzi, S., & Azzellino, A. (2006). 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Science of The Total Environment, 630, 774–780. https://doi.org/10.1016/J.SCITOTENV.2018.02.202 Schneider, C. A., Rasband, W. S., & Eliceiri, K. W. (2012). NIH Image to ImageJ: 25 years of image analysis. In Nature Methods (Vol. 9, Issue 7, pp. 671–675). https://doi.org/10.1038/nmeth.2089 Scott, E. M., Mann, J., Watson-Capps, J. J., Sargeant, B. L., & Connor, R. C. (2005). Aggression in bottlenose dolphins: Evidence for sexual coercion, male-male competition, and female tolerance through analysis of tooth-rake marks and behaviour. Behaviour, 142(1), 21–44. https://doi.org/10.1163/1568539053627712 Segura-Göthlin, S., Fernández, A., Arbelo, M., Almunia, J., von Fersen, L., Baumgartner, K., Garcés, J. G., Llanos, A. G., Felipe-Jiménez, I., Colom-Rivero, A., & Sierra, E. (2023). Towards understanding host–pathogen dynamics of cetacean poxvirus: attainable approach through the application of a repetitive non-invasive skin sampling in bottlenose dolphins (Tursiops truncatus) under human care. Frontiers in Marine Science, 10. https://doi.org/10.3389/fmars.2023.1125629 Serres, A., Lin, W., Liu, B., Lin, M., Liu, M., Chen, S., & Li, S. (2022). Season, age, sex, and location impact the density of tooth rake mark and dorsal fin notch of Indo‐Pacific humpback dolphins ( Sousa chinensis ) in the northern South China Sea . Marine Mammal Science. https://doi.org/10.1111/mms.12986 Serres, A., Lin, W., Liu, B., Lin, M., Liu, M., & Li, S. (2023). Injuries and skin condition of Indo‐Pacific humpback dolphins ( Sousa chinensis ) in the northern South China Sea. Marine Mammal Science. https://doi.org/10.1111/mms.13043 Soares, E.D., Cantor, M., Bracarense, A.P.F.R.L. et al. Health conditions of Guiana dolphins facing cumulative anthropogenic impacts. Mamm Biol 102 , 1589–1604 (2022). https://doi.org/10.1007/s42991-022-00299-3 Stylos, A., Akritopoulou, E., Bertulli, C. G., Lohrengel, K., McGinty, N., Moutopoulos, D. K., & Evans, P. G. H. (2022). Prevalence and spatio-temporal variation of epidermal conditions, deformities and injuries in common bottlenose dolphins (Tursiops truncatus) in Welsh waters. Mammalian Biology. https://doi.org/10.1007/s42991-022-00300-z Taylor, J. S., Hart, L. B., & Adams, J. (2021). Skin lesion prevalence of estuarine common bottlenose dolphins (Tursiops truncatus) in North Carolina, with comparisons to other east coast study sites. Marine Mammal Science, 37(1), 127–141. https://doi.org/10.1111/mms.12731 Toms, C. N., Stone, T., & Och-Adams, T. (2020). Visual-only assessments of skin lesions on free-ranging common bottlenose dolphins (Tursiops truncatus): Reliability and utility of quantitative tools. Marine Mammal Science, 36(3), 744–773. https://doi.org/10.1111/mms.12670 Wells, RandallS., Rhinehart, HowardL., Hansen, LarryJ., Sweeney, JayC., Townsend, ForrestI., Stone, R., Casper, D. R., Scott, MichaelD., Hohn, AletaA., & Rowles, TeriK. (2004). Bottlenose Dolphins as Marine Ecosystem Sentinels: Developing a Health Monitoring System. EcoHealth, 1(3). https://doi.org/10.1007/s10393-004-0094-6 Würsig, B. (2019). Ethology and Behavioral Ecology of Marine Mammals Series Editor: Bernd. http://www.springer.com/series/15983 Additional Declarations No competing interests reported. Supplementary Files Onlineresource1.pdf Onlineresource2.pdf Onlineresource3.pdf Onlineresource4.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4814406","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":337760439,"identity":"d6d86662-19c7-4621-bad8-8720739eba89","order_by":0,"name":"Alice Turchi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYDACdsYGCEOCseHAhwogg5m5Ab8WZpCWBLCWxoMzzsBE8GoBEWAtDMyHedtAPAJa+JuZGz98/HE4n392c8MB3nm10fztQC0/Krbh1CJxmLFZckbCYcsZdw42HJDcdjx3xmHGBsaeM7dxW3OYsY2ZJ+GwgYFEYsMBw23HchuAWpgZ23BrkQdp+QPTkjjnWO58QloMQFoYYFoONtTkbiCkxRDkl560dAOJG4kNBxuOHcjdCNRyEJ9f5I63P/zww8bagH9G+uPPf2rqcuedP3zwwY8KPN5HA4fB5AGi1QNBHSmKR8EoGAWjYIQAAAB0YgbXZvkGAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Environmental Biology, Sapienza University of Rome","correspondingAuthor":true,"prefix":"","firstName":"Alice","middleName":"","lastName":"Turchi","suffix":""},{"id":337760440,"identity":"5ca38d80-a279-42de-a7d7-b887a416056a","order_by":1,"name":"Giulia Pedrazzi","email":"","orcid":"","institution":"Department of Environmental Biology, Sapienza University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Giulia","middleName":"","lastName":"Pedrazzi","suffix":""},{"id":337760441,"identity":"704e8415-95a2-48e9-a4d4-4b3c91926c26","order_by":2,"name":"Alex Mattiussi","email":"","orcid":"","institution":"Department of Environmental Biology, Sapienza University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Alex","middleName":"","lastName":"Mattiussi","suffix":""},{"id":337760442,"identity":"86d38d2e-cd88-4ebd-9721-385d6bcfbcc9","order_by":3,"name":"Maria Silvia Labriola","email":"","orcid":"","institution":"Department of Environmental Biology, Sapienza University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Silvia","lastName":"Labriola","suffix":""},{"id":337760443,"identity":"dd3bd9d7-4813-4d6e-a504-f7cfdc2a037b","order_by":4,"name":"Daniele Petrone","email":"","orcid":"","institution":"Department of Statistics, Sapienza University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Daniele","middleName":"","lastName":"Petrone","suffix":""},{"id":337760444,"identity":"be24c515-349b-441b-9a35-465d8113bcf2","order_by":5,"name":"Giancarlo Giacomini","email":"","orcid":"","institution":"Department of Environmental Biology, Sapienza University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Giancarlo","middleName":"","lastName":"Giacomini","suffix":""},{"id":337760445,"identity":"cff2275b-4a69-4045-8250-0ed0ba83b95d","order_by":6,"name":"Daniela Silvia Pace","email":"","orcid":"","institution":"Department of Environmental Biology, Sapienza University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Daniela","middleName":"Silvia","lastName":"Pace","suffix":""}],"badges":[],"createdAt":"2024-07-27 20:23:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4814406/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4814406/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":63398287,"identity":"38761e72-0fd8-4f77-befe-b58a0a5423f1","added_by":"auto","created_at":"2024-08-27 17:55:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":220088,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the study area with track lines of sightings 2018-2023. 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The FBL used to define the different body areas is here represented in red\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4814406/v1/1be0ccad82908d2dc44835d4.png"},{"id":63398284,"identity":"cc76113c-98f4-49de-a443-ba145a5a6c7e","added_by":"auto","created_at":"2024-08-27 17:55:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":101797,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical workflow: starting from top left, the data collection, selection, elaboration, analysis, and objectives\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4814406/v1/9ce7e3369ca3b95216990e95.png"},{"id":63398288,"identity":"9002f09f-ee34-4fc3-93a2-21cc1388f89c","added_by":"auto","created_at":"2024-08-27 17:55:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":175822,"visible":true,"origin":"","legend":"\u003cp\u003ePlots representing mark distribution. The top graphs show mark types (see Tab. 1 for mark type acronyms) and categories found on the different body sections. Only the marks with the highest percentages based on quartile distribution (Q2-Q3-Q4) are reported. The bottom plots show the number of marks, observations and mark density for each body section\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4814406/v1/ccbab6af332acc7d8cb9d6a4.png"},{"id":64124745,"identity":"d957d899-f225-4b98-851a-8276c6e91ca1","added_by":"auto","created_at":"2024-09-07 23:31:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1090740,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4814406/v1/51502807-7b93-4737-91f5-8b8f3b80dfad.pdf"},{"id":63398289,"identity":"089588ee-8d57-4896-b65c-00694a915c7a","added_by":"auto","created_at":"2024-08-27 17:55:35","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":661906,"visible":true,"origin":"","legend":"","description":"","filename":"Onlineresource1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4814406/v1/14ab4ddc44282653a83195b5.pdf"},{"id":63398291,"identity":"a81de7da-95bf-4d0e-aba2-7c5ce0a20a1d","added_by":"auto","created_at":"2024-08-27 17:55:35","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":209823,"visible":true,"origin":"","legend":"","description":"","filename":"Onlineresource2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4814406/v1/c277c3bbb9bd9924c2e8836f.pdf"},{"id":63398605,"identity":"ea6615bd-fcea-41c8-a3f1-6a7c0fb0b803","added_by":"auto","created_at":"2024-08-27 18:03:35","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":65050,"visible":true,"origin":"","legend":"","description":"","filename":"Onlineresource3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4814406/v1/4c05afb780b7a2dcdfecb7af.pdf"},{"id":63398290,"identity":"8723c963-d615-462b-b096-f104e4a237bb","added_by":"auto","created_at":"2024-08-27 17:55:35","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":690047,"visible":true,"origin":"","legend":"","description":"","filename":"Onlineresource4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4814406/v1/7a46b951db7a6bb8c0408144.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Skin marks in Capitoline dolphins shed light on threats to the population at the Tiber River Estuary (Mediterranean Sea)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDisentangling the complex network of relationships between a species and the ecosystem it belongs to is challenging (Heinen et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Direct observations of individuals interacting with both their biotic and abiotic surroundings may be difficult to collect, especially at sea (Marley et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), thus making the use of alternative and indirect techniques highly advantageous. In this framework, mark analysis has emerged in the past 20 years as a non-invasive and reliable methodology to infer the level of exposure of a population to different environmental and ecological factors (Toms et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and thus identify potential threats to its conservation. Indeed, social and environmental interactions by individuals can leave visible signs, or marks, on the body surface of the interactor (Herr et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Leone et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Serres et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This is particularly relevant in hairless mammalian species, like cetaceans, as these marks may be clearly evident and easier to detect for observers.\u003c/p\u003e \u003cp\u003eThe use of mark analysis on high-quality pictures to study and characterise cutaneous lesions represents a wide-distributed and consolidated non-invasive technique and has been applied to several cetacean species, including common bottlenose dolphins (\u003cem\u003eTursiops truncatus\u003c/em\u003e) (Bertulli et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Blasi et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Feyrer et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Grimes et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; James et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Leone et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Mariani et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Serres et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Stylos et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Individuals may accumulate on their skin signs of interaction with the habitat and human activities (\u003cem\u003ee.g.\u003c/em\u003e, fishing gear-related injuries), which can indirectly provide different types of information (Blasi et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lee et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Leone et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Marley et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Scott et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Stylos et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Taylor et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Skin diseases and epidermal conditions (\u003cem\u003ee.g.\u003c/em\u003e, tattoo-like lesions), for instance, can be useful in evaluating habitat quality (Herr et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Segura-G\u0026ouml;thlin et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Serres et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Stylos et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Taylor et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), reducing the necessity of invasive procedures, like biopsies, while speeding up the identification of possible pathogens. Emaciation is the most useful mark to study the nutritional status of a population, since it is directly linked to malnutrition (Dunkin et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Herr et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Indeed, malnutrition may be caused both by extreme competition and/or restricted access to food resources (even prey depletion), and thus be indicative of a potential suboptimal habitat for the population (Dunkin et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In addition, many social exchanges and interaction behaviours (\u003cem\u003ee.g.\u003c/em\u003e, interaction with fishing gears) can leave recognisable marks on the body of the individuals (Scott et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; W\u0026uuml;rsig, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Therefore, researchers are able to get a deeper understanding of a species sociality and behaviour, without the need for live observations, ultimately making ecological and ethological studies faster and more efficient (Blasi et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Marley et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Scott et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; W\u0026uuml;rsig, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe common bottlenose dolphin is a global cetacean species mainly inhabiting coastal regions, for which some populations have been extensively monitored in long-term research programs. Being a long-lived species and feeding at the top of the food web, bottlenose dolphins are subjected to longstanding exposure to environmental and anthropogenic pressures (Wells et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Because of this, they are considered a sentinel species, whose presence and health status can in turn be indicative of the ecosystem\u0026rsquo;s health (Wells et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), making their skin marks a valuable tool to gain insight on the pressures they face (Stylos et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Furthermore, as small cetaceans and apex predators, they play important ecological roles, including predation, nutrient cycling, and foraging facilitation for other species (Kiszka et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), which is why their conservation can benefit the marine ecosystem at different levels. For these reasons, common bottlenose dolphins in the Mediterranean are protected under the EU Habitats Directive (92/43/CEE) Annex IV of the priority species, making their conservation a necessity (Pace et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003eIn the Mediterranean Sea, at the Tiber River Estuary (central Tyrrhenian Sea, Italy), the presence of a geographical unit of bottlenose dolphins, also known as \u0026ldquo;Capitoline dolphins\u0026rdquo;, is well-documented, with a population of 529 individuals as of 2020 estimates (Pace et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Up to now, detailed analyses of skin marks and emaciation have not been conducted for this population. To fill this knowledge gap and address possible management actions, this study applies skin mark analysis to characterise common bottlenose dolphin lesions, and their evolution in time, with the aim of testing their efficacy as proxies to infer individual or population health in a region under severe threat from human activities. More specifically, the description, quantification and measurement of different marks and cutaneous injuries found on the entire body of individual dolphins, and the assessment of changes in marked surface over time (\u003cem\u003ei.e.\u003c/em\u003e, the rate of change; Bertulli et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Feyrer et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Luksenburg, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Olaya-Ponzone et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Serres et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Stylos et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Taylor et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) are used to estimate the severity of potential pressures in the area.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy area\u003c/h2\u003e \u003cp\u003eThe study area is located in the Western Mediterranean Sea (Central Tyrrhenian Sea), near the city of Rome (Italy), covering approximately 1300 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Km}^{2}\\)\u003c/span\u003e\u003c/span\u003e between the coastline and the Italian territorial waters\u0026rsquo; limit of 12 nm (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). It is a highly productive area, characterised by a variety of environmental conditions and habitats including: (1) the Tiber River Estuary, which brings organic matter to the oligotrophic Mediterranean waters and transfers several pollutants collected during the transit in the city of Rome (Montuori et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e); (2) two single-point moorings (SPMs) called R1 and R2, and located 3 nautical miles from the coast, where crude oil and petroleum products are received; and (3) the Marine Protected Area (MPA) called \u0026ldquo;Secche di Tor Paterno\u0026rdquo; (Tor Paterno Banks, Natura 2000 Code: IT6000010).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe regular occurrence of bottlenose dolphins in the area has been documented since 2016, with the presence of at least 42 resident individuals, over a total of 362 photographically identified animals (Pace et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Many feeding groups and females with calves have been repeatedly sighted each year, suggesting the area might be an important foraging and breeding site for the species (Pace et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003ea, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003eb; Pedrazzi et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The area is heavily exposed to human disturbance, mainly deriving from three sources (Pace et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e): (1) artisanal and commercial fishing, largely ascribable to trawling fisheries (Pace et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003eb); the local trawling fleet is composed of 25\u0026ndash;30 vessels of 18\u0026ndash;25 m in length, which operate from Monday to Friday on the continental shelf and slope (in compliance with the national regulations of a minimum of 50 m depth or 3 nautical miles from the coast); (2) maritime traffic, which refers to both commercial vessels and pleasure boats; (3) recreational activities, such as sportfishing, whale watching and diving.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eData were collected through daily boat-based surveys using a Benteau Oceanis 41.1 sailing vessel equipped with a 55 hp Volvo diesel engine, in optimal weather conditions (sea state \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\le\\:\\)\u003c/span\u003e\u003c/span\u003e 3 Douglas, wind force \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\le\\:\\)\u003c/span\u003e\u003c/span\u003e 3 Beaufort, no rain, no fog) to reduce detection probability bias (Pace et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Most of the surveys were conducted from late spring to early autumn, in a 4-to-6-months span over 8 consecutive years (2016\u0026ndash;2023). Once at sea, an adaptive sampling method (Martino et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Pace et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) was employed to maximize the encounter probability, following the track lines reported in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Once a group of dolphins was sighted, the searching effort was suspended and the animals were approached to collect visual data (i.e., group size, presence of calves, predominant behaviour) and assess eventual interactions with anthropic activities. Photographic data were collected while proceeding parallel to the direction of the group at very low speed, using Canon digital 5D and 6D cameras and Canon 100\u0026ndash;400 mm f/4.5\u0026ndash;5.6 L lens. Once good quality pictures of both sides of the animals were obtained, or if the animals showed any sign of discomfort, the sighting and data collection ended.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003ePhoto-identification, dataset selection and body scoring\u003c/h2\u003e \u003cp\u003eA standard photo-identification protocol was applied to identify and catalogue individuals in the population (Pace et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). A number of 39 individuals (out of a total of 362 photo-identified animals) was randomly selected for the mark analysis, based on the number of available high-quality images allowing detailed mark descriptions and accurate measurements. Most of the selected individuals (97%) were characterised by a high level of site fidelity, and by multiple years of encounters, making the analysed sample quite representative of the portion of the population that permanently inhabits the area.\u003c/p\u003e \u003cp\u003eIn order to analyse as much of the dolphins\u0026rsquo; body surface as possible, photographs of different body parts were selected for each individual and for each available year within the 2016\u0026ndash;2023 study period. To account for the different proportions of visible body surface in different photographs, an operational protocol was developed (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Each side of the animal\u0026rsquo;s body (right and left) was divided into five areas, namely anterior, dorsal fin, posterior, ventral, and flukes (Marley et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Serres et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The body partition was obtained without ambiguities by considering the length of the dorsal fin base (hereafter, FBL\u0026thinsp;=\u0026thinsp;Fin Base Length) as a standard measure to define the limits between an area and the other. Specifically, the dorsal fin area was separated from the anterior and posterior areas by two segments traced at a distance of \u0026frac12; FBL from the dorsal fin itself, while the segment separating the dorsal fin area from the ventral area was traced at a distance equal to the FBL value from the fin. Lastly, the fluke area was simply defined as the region going from the base of the caudal fin to its extremes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eEach of the ten body parts (i.e., the aforementioned five body areas defined on the left and right sides of the body) was scored from 0 to 3 based on their visibility (score 0: \u0026lt;10% of the section visible; score 1: 10\u0026ndash;40% of the section visible; score 2: 40\u0026ndash;70% of the section visible; score 3: \u0026gt;70% of the section visible). Next, the scores assigned to each body part were summed up and divided by 30 (maximum score for an entirely visible dolphin, left and right sides), to calculate the pictures\u0026rsquo; body scoring (BS). Then, BSs were summed for each individual separately every year, thus obtaining the proportion of visible dolphin body each year. The scoring was then integrated in yearly calculations of marked body surface to weigh the contributions of the different pictures. In total, 461 high-quality pictures were analysed and scored (number of pictures analysed per individual\u0026thinsp;=\u0026thinsp;11\u0026ndash;12).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMark analysis\u003c/h2\u003e \u003cp\u003eA catalogue consisting of 31 mark types and three mark categories [Skin Lesions (SI); Physical Impact (PI) and Emaciation (E)] was built and used for the mark analysis (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), following the classification proposed by Correia et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The full catalogue containing descriptions and photographs of the analysed marks is provided in the Online resource 1 of the Supplementary information (SI).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMark categories and types identified in the Capitoline dolphin population\u003c/p\u003e \u003cdiv class=\"Credit\"\u003e\u003cp\u003e(adapted from Correia et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMark category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMark type\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSkin lesions (SL)\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLight Area (LA), Light Linear Lesion (LLL), Snake-Like Lesion (SLL), Light Mark (LM), Light Speckles (LSP), Light Fringed Spot (LFS), Dark Linear Lesion (DLL), Dark Mark (DM), Dark Area (DA), Dark Speckles (DS), Tattoo-Like Lesion (TTL), Starburst Lesion (SL), Nodules (ND), Vesicular Lesion (VL), Hyperplastic Lesion (HL), Hole (H)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical impact (PI)\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWound (W), Cut (C), Fin Amputation (FA), Notch (N), Protruding Tissue (PT), Linear Scrape (LS), Linear Scrape-Tooth Rakes (LST), Linear Scrape-Anthropogenic (LSA), Scratch Patch (SP), Shark Bite Mark (SBM), Sea-Lamprey Mark (SLM), Scar (S), Bruising (B), Miscellaneous (M)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmaciation (E)\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmaciation (E)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEight attributes and features were assigned, measured and/or estimated for each mark type in every picture of selected individuals (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), ultimately leading to cumulative yearly information for all individuals. For tooth rake marks only (included in the Physical Impact category), two additional features were recorded: 1) Age (New, Obvious, and Faint; Scott et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2005\u003c/span\u003e); 2) Number of rakes per tooth rake. In the case of heavily degraded fins, with multiple notches merged, the original fin was reconstructed in the most conservative way possible, excluding the protruding pieces, and the current profile of the fin was determined. This choice allowed for the measuring of missing fin surfaces due to notches and reduced the possibility of observer error bound to counting the wrong number of notches in the presence of multiple notches merged. All mark measurements were obtained using the software ImageJ 1.54d (Schneider et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAttributes and features used to describe each skin mark in each picture\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttribute/Feature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMark code\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA unique code for each identified mark category or type\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMark category\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory to which the identified mark belongs to\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMark type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType to which the identified mark belongs to\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMark position\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBody section to which a mark belongs to\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody visibility scoring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe estimated proportion of the body visible in the picture\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody area (pixels)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe number of pixels belonging to the body of a dolphin in the picture\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarked body area (pixels)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe number of pixels belonging to the mark\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e% of marked body area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe percentage of body surface occupied by a mark (pixels)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eTo assess mark presence and distribution the number of marks on each of the available body areas (both left and right sides) was counted and the following five indices were computed: Total Number, Prevalence, Severity, % of body occupied, Richness (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) (Feyrer et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Leone et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Mariani et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Serres et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Stylos et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Mark density on each body area was calculated as the number of marks per body area divided by the number of times the body area was present in the analysed pictures.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of indices used to describe mark presence and distribution on Capitoline dolphins\u003c/p\u003e \u003cdiv class=\"Credit\"\u003e\u003cp\u003e(adapted from Lee et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Leone et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Luksenburg, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Marley et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Serres et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Stylos et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Taylor et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbbreviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal number\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003csub\u003e\u003cb\u003ei\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe number of marks of each category or type per photo per individual\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevalence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003csub\u003e\u003cb\u003ei\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe number of individuals with a certain mark category or type, divided by the total number of individuals in the population\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeverity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003el\u003c/b\u003e\u003csub\u003e\u003cb\u003ei\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe mean number of marks per mark categories or types on individuals with \u003cem\u003ei\u003c/em\u003e mark category or type\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e% of body occupied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eo\u003c/b\u003e\u003csub\u003e\u003cb\u003ei\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe mean percentage of body occupied by each mark of a certain category or type (except for \u0026ldquo;emaciation\u0026rdquo;)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003er\u003c/b\u003e\u003csub\u003e\u003cb\u003ei\u003c/b\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe mean of the total number of mark categories or types present on an individual\u0026rsquo;s body\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo analyse how individuals changed over the study period, the Rate of Change metric (RoC) was adapted from James et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and computed as:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{R}\\text{o}\\text{C}=\\:\\frac{{\\sum\\:}_{{t}_{i}=1}^{{T}_{i}}({y}_{{t}_{i}+1}-{y}_{{t}_{i}})}{{T}_{i}}\\:\\forall\\:\\:i=1,\\dots\\:,N$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{y}_{{t}_{i}}\\)\u003c/span\u003e\u003c/span\u003e is the percentage of marked body area for the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:i\\:\\)\u003c/span\u003e\u003c/span\u003eindividual in the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:t\\)\u003c/span\u003e\u003c/span\u003e year, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{T}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the number of follow-up years for the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:i\\)\u003c/span\u003e\u003c/span\u003e individual. RoC calculation can yield positive or negative values, with positive ones indicating the accumulation of new marks throughout the study period and negative indicating a lower marked surface due to healing of marks. Since data were not available for all years for some individuals, the gap between non-consecutive years was filled considering the variation in markings as linear throughout the years. As at least two consecutive years are needed to calculate the RoC index, two individuals not meeting this criterion were excluded.\u003c/p\u003e \u003cp\u003eTo estimate the impact of fisheries operating in the area, a Probability of Fishing gear Injury (PFI) was calculated on mark types possibly related to fishing gear interactions (i.e., LSA and FA; see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) as:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:PFI=\\:\\frac{\\sum\\:_{i=1}^{n}{N}_{i}}{\\sum\\:id}*100$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{N}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the number of individuals with at least one LSA or FA mark and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:id\\)\u003c/span\u003e\u003c/span\u003e is the total number of photo identified individuals used in the analysis.\u003c/p\u003e \u003cp\u003eR Studio software, version 2023.06.2 was used for all statistical analysis.\u003c/p\u003e \u003cp\u003eA summary of data collection and analysis workflow is represented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOverall, 5055 marks were identified on 39 individuals using 461 high-quality pictures, which led to a BS (body scoring) of 0.12 per picture and 0.31 per year. As expected, the dorsal fin was the body area with the highest number of observations (n\u0026thinsp;=\u0026thinsp;373; 45%), marks (n\u0026thinsp;=\u0026thinsp;3234; 63%), and density (n\u0026thinsp;=\u0026thinsp;9 marks per body section; 32%); relatively to the number of observations, the flukes were the area with the second highest number of marks and density (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA mean (\u0026plusmn;\u0026thinsp;standard error) of 30.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1% of the body surface was occupied by skin marks.\u003c/p\u003e \u003cp\u003eFor all mark types, the following mean values of the different indices were estimated: Number \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{n}_{i}\\)\u003c/span\u003e\u003c/span\u003e=163\u0026thinsp;\u0026plusmn;\u0026thinsp;61; Prevalence \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{p}_{i}\\)\u003c/span\u003e\u003c/span\u003e=37\u0026thinsp;\u0026plusmn;\u0026thinsp;6; Severity \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{l}_{i}\\)\u003c/span\u003e\u003c/span\u003e= 6\u0026thinsp;\u0026plusmn;\u0026thinsp;2; % of body occupied \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{o}_{i}\\)\u003c/span\u003e\u003c/span\u003e=0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7 and Richness \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{r}_{i}\\)\u003c/span\u003e\u003c/span\u003e=5\u0026plusmn;0.1. The mark category Physical Impact (PI) showed the highest values for all indices (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) and was found on all body areas (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Linear Scrape-Tooth Rakes (LST), Linear Scrape (LS), Notch (N) and Scratch Patch (SP) were the most represented mark types within this category, being present on every analysed animal on all body parts. LST had the highest level of Severity (l\u0026thinsp;=\u0026thinsp;30) and SP of % of body occupied (o\u0026thinsp;=\u0026thinsp;25.8). Almost half LSTs (49%) were Faint, 38% Obvious and 13% New, with a mean of 5 rakes per tooth rake. Notches (N) were the most present marks on the dorsal fin and flukes. The mark category Skin Lesions (SL) was detected in all body areas except for flukes and signs of Emaciation (E) was only found in the anterior part.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of the indices calculated for mark categories and types. Only the 13 marks with the highest or lowest value for each index are reported (see also full table in SI Online resource 3)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMark category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMark type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{n}}_{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{p}}_{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{l}}_{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{o}}_{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSkin Lesions (SL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e474\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e97\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLight Area (LA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDark Mark (DM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.006\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDark Speckles (DS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTattoo-like Lesion (TLL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.006\u0026thinsp;\u0026plusmn;\u0026thinsp;0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical Impact (PI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4557\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e117\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e28.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLinear Scrape-Tooth Rakes (LST)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLinear Scrape (LS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNotch (N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScratch Patch (SP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLinear Scrape-Anthropogenic (LSA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFin Amputation (FA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBruising (B)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0002\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiscellaneous (M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0004\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShark Bite (SBM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.002\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmaciation (E)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e43\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e72\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs for the temporal evolution of marks, the overall average RoC was 0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59. The highest RoC (6.9) was found on a male individual (ID 040), indicating a predominance of scarring processes on healing, while the lowest one (-12.1) on the individual ID 139, implying opposite processes (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The Probability of Fishing gear Injuries (PFI) was 48%, meaning that almost half of the individuals presented physical signs of interaction with fishery.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRoC (Rate of Change), \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{y}_{{t}_{i}}\\)\u003c/span\u003e\u003c/span\u003e(the percentage of marked body area for the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:i\\:\\)\u003c/span\u003e\u003c/span\u003eindividual in the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:t\\)\u003c/span\u003e\u003c/span\u003e year), and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{T}_{i}\\)\u003c/span\u003e\u003c/span\u003e (the number of follow-up years for the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:i\\)\u003c/span\u003e\u003c/span\u003e individual) for individuals with more than one year of observation. The six most relevant individuals (highest and lowest RoC) over the total of 37 are reported (full table in SI Online resource 4)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID individual\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{y}}_{2016}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{y}}_{2017}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{y}}_{2018}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{y}}_{2019}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{y}}_{2020}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{y}}_{2021}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{y}}_{2022}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{y}}_{2023}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{T}}_{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRoC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-9.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e56.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e50.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e50.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e52.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e47.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e57.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e62.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e62.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-12.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e23.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-3.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e31.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e31.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e50.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study analysed for the first time the skin marks of the Capitoline bottlenose dolphin population through the application of mark analysis on the entire animals\u0026rsquo; body. Not many studies have assessed mark presence on the whole body in cetacean species (Bertulli et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Herr et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; J. Kiszka et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Leone et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Luksenburg, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Marley et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Scott et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), often analysing dorsal fins only, and most of them lack a discrete measurement of the size of skin marks, with a possible information loss. Studying barely the dorsal fin can limit the efficiency of the methodology (Toms et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), reducing, if not eliminating, the possibility of noticing relevant mark categories, such as emaciation. Assessing the marked surface without its measurement can lead to an over- or under-estimation of the marked body area, possibly impacting not only the study \u003cem\u003eper se\u003c/em\u003e, but also any comparison between populations, making them less reliable. Here, in the selected sample of 39 dolphins, 3 out of 6 mark categories, and 29 mark types out of 60 listed by Correia et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) were found. No signs of anatomical malformations, anomalous pigmentation, or epibionts were detected in the analysed individuals. Although we here reported only a portion of the bottlenose dolphin population at the Tiber River estuary, most of the selected individuals (97%) presented a high level of site fidelity and multiple years of encounters, thus making the analysed sample sufficiently representative of the population inhabiting the area and thus persistently exposed to local pressures (Hanninger et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). On average, almost 1/3 of the visible body of the analysed animals was found to be covered by marks. This result doesn\u0026rsquo;t seem to have a precedent in the current literature on common bottlenose dolphin mark analysis, since to our knowledge measurements of marked body surface on the whole animal\u0026rsquo;s body have never been investigated before in this species. The dorsal fin was the body area with the highest density of marks, followed by the flukes. Their high values highlight the important role that these protruding appendices assume in the interactions with the environment and conspecifics (W\u0026uuml;rsig, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Scott et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) in their analysis of tooth rake prevalence found the highest presence of aggression-related marks on the dorsal fin area. Marley et al (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) suggested that, at least for aggressive interactions, dolphins might accumulate more tooth rakes on this area by exposing their less-vulnerable dorsal side to the attacks. As for interactions with their environment, especially fisheries, physically speaking protruding appendices such as the dorsal fin and the flukes may accumulate marks easier because of their vertical extension from the body of the animal, thus explaining the higher mark presence in these areas.\u003c/p\u003e \u003cp\u003eThe prevalence of externally visible marks was of 100%, similarly to what was found in other mark analysis studies (Stylos et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In particular, Skin Lesions (SL) showed a prevlalence of 97%, higher than what previously observed in other bottlenose dolphin populations (Stylos et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Taylor et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Their widespread presence in a highly polluted environment like the Tiber River Estuary is not surprising and might indicate a worse water quality in the study area, compared to other locations (Herr et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Serres et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Stylos et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Taylor et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, since biological samples were not collected in our study, the specific origin of most skin lesions cannot be attributed with certainty and further investigations are needed to validate any link with chemical pollution in the area. The only mark type of recognized infectious origin was the tattoo-like lesion (TLL), caused by the cetacean poxvirus (CePV) (Powell et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Segura-G\u0026ouml;thlin et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). TLL overall indices were similar to the ones found by Stylos et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), with a prevalence of 3% in our population, and 2.8% in the Welsh ones. These values are lower than the ones commonly found in other common bottlenose dolphin populations. For example, the most recent study reports a TLL prevalence of 19.4% in the Shark Bay (Australia) bottlenose dolphins (Powell et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Considering tattoo-like lesions are usually detected in cetaceans inhabiting polluted nearshore waters and can be exacerbated by high concentrations of halogenated organochlorines (Serres et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), this relatively low presence in individuals at the Tiber River Estuary is surprising and could indicate lower CePV incidence in the study area. On the other hand, it is possible that a higher number of individuals from the studied population might be infected by CePV, even if not presenting physical signs of infection, as the CePV responsible for TLL has also been found on apparently healthy skin with low viral loads (Segura-G\u0026ouml;thlin et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study found more than 2/3 of the individuals to be emaciated, with the presence of visible ribs on over 70% of the population. Emaciation has direct consequences on the energetic necessities of bottlenose dolphins, as it reduces the thickness of the blubber, causing the animals to be 12 times more negatively buoyant than non-emaciated individuals (Dunkin et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Thus, emaciated individuals might experience higher locomotion costs, increasing the nutritional stress to which they are already subjected, with potential higher mortality rates (Dunkin et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Malnutrition is usually caused by prey scarcity and/or low prey availability due to competition (Dunkin et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). While direct evidence of reduced prey availability cannot be inferred by photographic data alone, the high prevalence of emaciation suggests a reduced access to prey. Professional and recreational fishing are highly present pressures in the area (Pace et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003ea). The exacerbated fishing effort could be a factor contributing to reducing prey access for this population. Prey depletion may also be linked to other human-induced causes, such as disturbance generated by maritime traffic or pollution (Leone et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). To reduce the energetic costs associated with finding scarcely abundant prey, dolphins might turn to commercial fishing to gain easy access to fish. In this study, fishing-related marks were frequently observed (PFI\u0026thinsp;=\u0026thinsp;48%), reflecting the already reported common interaction with fishery by Capitoline bottlenose dolphins (Pace et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003eb). Almost half of the population showed signs of interaction with commercial fishing, particularly trawling. However, bycatch seems to be limited (Carpentieri et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Pace et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003eb), suggesting that individuals in the study area might have learned to reduce the hazards associated with trawling interactions. The high levels of interaction with fishery here observed may therefore be a symptom of a broader problem, possibly related to the reduction of prey abundance in the area. The high prevalence intra-specific aggression-related marks (tooth-rakes) seem to support this hypothesis as well (aggression can derive from competition for food; Scott et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Marley et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Prey scarcity could induce variations in the abundance of the population, as the relationship between overfishing, prey depletion and decreased abundance has been already reported in other cetacean species (Bearzi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Moore, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Monitoring the interaction of bottlenose dolphins with trawlers and the abundance of their potential prey over time can be highly significant towards the conservation of this species.\u003c/p\u003e \u003cp\u003eAs for the mark changes over time, RoC values showed high inter-individual variability in the cumulative marked area, with a common tendency of accumulating new marks, rather than healing capacities. It is known that the healing process in common bottlenose dolphins may be sped up by higher water salinity levels (Hurst \u0026amp; Orbach, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This condition is not found in the study area, bound to its estuarine nature, thus not positively affecting healing times. In addition, a predominance of scarring processes was found in a male individual with a high degree of site-fidelity, opening further investigations on both sex-specific and residency-related differences in markings (Leone et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Marley et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Scott et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn conclusion, by using a non-invasive, low-cost, and time-efficient technique, this study provided \u0026ndash; for the first time \u0026ndash; strong evidence that common bottlenose dolphins residing in the Tiber River Estuary are under the pressure of multiple stressors. This information is critical, especially in an area where there are no conservation efforts or management actions in place for this sentinel species. At the same time, the methods presented in the study could represent a useful baseline to make initial assessments of the health of common bottlenose dolphins populations in highly impacted coastal regions, as previously done with other coastal cetacean populations (e.g., Guiana dolphins, \u003cem\u003eSotalia guaianensis\u003c/em\u003e) (Soares et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare the absence of conflicts of interest.\u003c/p\u003e\u003ch2\u003eCompliance with ethical standards\u003c/h2\u003e \u003cp\u003eNo ethical review nor approval was necessary for this study because of its non-invasive nature.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by Sapienza University of Rome under the Ateneo Grant Program [number RM1221816AE34004].\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization and methodology: A.T. and D.S.P.; field work: A.T., G.P., A.M., M.S.L., G.G., D.S.P.; photo-identification analysis: A.T. and A.M.; mark analysis: A.T.; statistical analysis: A.T., G.P., D.P., and D.S.P.; writing: A.T. and D.S.P.; revision and approval: all authors. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank all the master\u0026rsquo;s degree students who helped with data collection and photo-identification during the years. We also thank Daniela Taliana, Eleonora De Sabata, Cristiana Roppo and Carlotta Vivaldi for providing us with additional photographic materials. A special thanks to Giovanna Jona-Lasinio for statistical suggestions.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data used for this article can be made available by the authors upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBearzi, G., Politi, E., Agazzi, S., \u0026amp; Azzellino, A. (2006). Prey depletion caused by overfishing and the decline of marine megafauna in eastern Ionian Sea coastal waters (central Mediterranean). Biological Conservation, 127(4), 373\u0026ndash;382. https://doi.org/10.1016/J.BIOCON.2005.08.017\u003c/li\u003e\n\u003cli\u003eBertulli, C. G., Rasmussen, M. H., \u0026amp; Rosso, M. (2016). An assessment of the natural marking patterns used for photo-identification of common minke whales and white-beaked dolphins in Icelandic waters. Journal of the Marine Biological Association of the United Kingdom, 96(4), 807\u0026ndash;819. https://doi.org/10.1017/S0025315415000284\u003c/li\u003e\n\u003cli\u003eBlasi, M. F., Alessi, J., Melodia, C., Azzolin, M., Giacoma, C., Buscaino, G., Buffa, G., Ceraulo, M., Monaco, C., Bruccoleri, F., Cafaro, V., Raffa, A., \u0026amp; Papale, E. (2023). Bottlenose dolphins\u0026rsquo; fin marks comparison highlights limited movements and anthropogenic threats in the waters around Sicily (Italy, Central Mediterranean Sea). Hydrobiologia, 850(3), 627\u0026ndash;643. https://doi.org/10.1007/s10750-022-05108-z\u003c/li\u003e\n\u003cli\u003eCarpentieri, P., Nastasi, A., Sessa, M., Srour, A., (2021). Incidental catch of vulnerable species in Mediterranean and Black Sea fisheries - A review. (2021). FAO. https://doi.org/10.4060/cb5405en\u003c/li\u003e\n\u003cli\u003eCorreia, A. M., Dietterle, E., Dinis, A., \u0026amp; Alves, F. (2023). Defining a common language to assess external deformities in free-ranging cetaceans. In Mammal Review. John Wiley and Sons Inc. https://doi.org/10.1111/mam.12318\u003c/li\u003e\n\u003cli\u003eDunkin, R. C., McLellan, W. A., Blum, J. E., \u0026amp; Pabst, D. A. (2010). The buoyancy of the integument of Atlantic bottlenose dolphins (Tursiops truncatus): Effects of growth, reproduction, and nutritional state. Marine Mammal Science, 26(3), 573\u0026ndash;587. https://doi.org/10.1111/j.1748-7692.2009.00353.x\u003c/li\u003e\n\u003cli\u003eFeyrer, L. 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Seasonal distribution of an opportunistic apex predator (Tursiops truncatus) in marine coastal habitats of the Western Mediterranean Sea. \u003cem\u003eFrontiers in Marine Science\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e. https://doi.org/10.3389/fmars.2022.939692\u003c/li\u003e\n\u003cli\u003ePedrazzi, G., Giacomini, G., \u0026amp; Pace, D. S. (2022). First Report of Epimeletic and Acoustic Behavior in Mediterranean Common Bottlenose Dolphins (Tursiops truncatus) Carrying Dead Calves. \u003cem\u003eBiology\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(2). https://doi.org/10.3390/biology11020337\u003c/li\u003e\n\u003cli\u003ePowell, S. N., Wallen, M. M., Bansal, S., \u0026amp; Mann, J. (2018). Epidemiological investigation of tattoo-like skin lesions among bottlenose dolphins in Shark Bay, Australia. Science of The Total Environment, 630, 774\u0026ndash;780. https://doi.org/10.1016/J.SCITOTENV.2018.02.202\u003c/li\u003e\n\u003cli\u003eSchneider, C. A., Rasband, W. 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Ethology and Behavioral Ecology of Marine Mammals Series Editor: Bernd. http://www.springer.com/series/15983\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bottlenose dolphin, skin lesions, mark analysis, anthropogenic threats, conservation, interaction with fisheries","lastPublishedDoi":"10.21203/rs.3.rs-4814406/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4814406/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe analysis of skin marks and lesions is used for many cetacean species to assess the general health status of the populations, based on evidence of interaction between conspecifics and with human activities. This study applies mark analysis to characterise common bottlenose dolphin (\u003cem\u003eTursiops truncatus\u003c/em\u003e) skin marks and lesions, and their evolution in time, in the Tiber River Estuary area (Mediterranean Sea, Italy), to test their efficacy as proxies of individual or population health in a region under several anthropogenic pressures. Using high-quality photographic data collected between 2016 and 2023 during 205 sightings, marks were identified, classified, counted and measured on 39 individuals photographed on multiple occasions. Marks related to intraspecific interactions (\u003cem\u003ee.g.\u003c/em\u003e, tooth-rakes), anthropogenic activities (\u003cem\u003ee.g.\u003c/em\u003e, signs of interaction with fishery) and health conditions (\u003cem\u003ee.g.\u003c/em\u003e, skin diseases and emaciation) were selected as indicators, and five indices were applied to estimate their extension and progression through time. Prevalent marks in all individuals were of social origin and aggressive nature. Marks related to skin diseases and emaciation were present in 97% and 70% of individuals, respectively. Almost half of the individuals showed physical signs of interaction with fishing gears. No significant trends in the temporal evolution of marks were observed. These results highlight that the local population is under the pressure of multiple stressors mostly related to human activities, both directly (fishing) and indirectly (malnutrition, aggression). The consequences of stressor interactions may be complex to predict and raise challenges for the conservation of this protected species in a highly anthropized area.\u003c/p\u003e","manuscriptTitle":"Skin marks in Capitoline dolphins shed light on threats to the population at the Tiber River Estuary (Mediterranean Sea)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-27 17:55:30","doi":"10.21203/rs.3.rs-4814406/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fabec437-a371-4980-8d84-13fd76322d36","owner":[],"postedDate":"August 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-09-07T23:23:31+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-27 17:55:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4814406","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4814406","identity":"rs-4814406","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}