Marina Fernandez-Declerck

Emilie Rojas

Loïc Prosnier

Loïc Teulier

François-Xavier Dechaume-Moncharmont

Vincent Médoc
email: vincentmédoc@univ-st-etienne.fr

François- Xavier Dechaume-Moncharmont

Adding insult to injury: anthropogenic noise intensifies predation risk by an invasive freshwater fish species

Keywords: functional response, trophic impact, biological invasion, noise pollution, round goby

scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Predation by invasive species is an important threat to biodiversity, estimated as causing a 21% decline in species richness in aquatic habitats [START_REF] Mollot | The Effects of Invasive Species on the Decline in Species Richness: A Global Meta-Analysis[END_REF][START_REF] Reid | Emerging threats and persistent conservation challenges for freshwater biodiversity[END_REF]. For certain invasive species, higher tolerance to environmental stressors such as hypoxia [START_REF] Lagos | Do low oxygen environments facilitate marine invasions? Relative tolerance of native and invasive species to low oxygen conditions[END_REF][START_REF] Dickey | Breathing space: deoxygenation of aquatic environments can drive differential ecological impacts across biological invasion stages[END_REF], increased temperature [START_REF] Christensen | Effects of temperature on physiological performance and behavioral thermoregulation in an invasive fish, the round goby[END_REF]) and salinity [START_REF] Karsiotis | Salinity tolerance of the invasive round goby: Experimental implications for seawater ballast exchange and spread to North American estuaries[END_REF][START_REF] Behrens | Evaluating dispersal potential of an invasive fish by the use of aerobic scope and osmoregulation capacity[END_REF]), might promote their ecological impact, allowing them to settle easily in new environments and to maintain strong topdown control on lower trophic levels.

The worldwide increase in boat traffic is a major driver of the spread of invasive species [START_REF] Hulme | Unwelcome exchange: International trade as a direct and indirect driver of biological invasions worldwide[END_REF], but it also contributes to the degradation of natural habitats on many levels. In particular, motorised boats significantly alter underwater soundscapes [START_REF] Reid | Emerging threats and persistent conservation challenges for freshwater biodiversity[END_REF]. Anthropogenic (i.e., man-made) noise is indeed one of the most pervasive symptoms of human activities [START_REF] Buxton | Noise pollution is pervasive in US protected areas[END_REF]. It can induce changes in animal behaviour, physiology and sometimes anatomy, and mask important acoustic cues involved in reproduction, social interactions, foraging or predator avoidance [START_REF] Kunc | The effects of anthropogenic noise on animals: A meta-analysis[END_REF]. Reduced foraging performance is a common response to anthropogenic noise [START_REF] Cox | Sound the alarm: A meta-analysis on the effect of aquatic noise on fish behavior and physiology[END_REF], with many examples both from the lab and field [START_REF] Sabet | The effect of temporal variation in sound exposure on swimming and foraging behaviour of captive zebrafish[END_REF][START_REF] Magnhagen | Effects of motorboat noise on foraging behaviour in Eurasian perch and roach: a field experiment[END_REF]. The consequences of reduced foraging can propagate through nested ecological interactions to ultimately alter community composition and dynamics [START_REF] Francis | Noise pollution changes avian communities and species interactions[END_REF].

While the number of invasive species is predicted to increase (Anton 2021) in an underwater world that becomes more and more noisy [START_REF] Duarte | The soundscape of the Anthropocene ocean[END_REF], surprisingly, their tolerance to anthropogenic noise has received scant attention. This is symptomatic of the general picture that there are fewer studies examining the effects of noise pollution on freshwater fishes and invertebrates than on marine organisms [START_REF] Mickle | Integrating techniques: a review of the effects of anthropogenic noise on freshwater fish[END_REF]. Tolerance to noise might help invasive species to spread in anthropized environments while maintaining strong trophic and competitive pressures on native species, especially if the performance of the latter are reduced by noise.

In the present study, we investigated whether predation rate by the round goby (Neogobius melanostomus) was influenced by anthropogenic noise and particularly motorboat sounds. Although this species uses acoustic cues as part of its reproductive repertoire (males defend a nest and emit calls to attract females, [START_REF] Rollo | Attraction and localization of round goby (Neogobius melanostomus) to conspecific FOrcalls[END_REF] it does not possess a swim bladder or obvious hearing specializations and therefore relies on particle motion and not pressure to detect sounds [START_REF] Belanger | Hearing and the round goby: Understanding the auditory system of the round goby (Neogobius melanostomus)[END_REF][START_REF] Belanger | The effect of stimulus type and background noise on hearing abilities of the round goby Neogobius melanostomus[END_REF]. It hears mainly below 800 Hz, a frequency range where motorboat noise typically has high energy. Regarded as one of the most impactful invasive species, the round goby has spread from the Pontocaspian region to the North American Great Lakes and throughout Western Europe where it outcompetes native fishes and impoverishes invertebrate communities [START_REF] Kornis | Twenty years of invasion: A review of round goby Neogobius melanostomus biology, spread and ecological implications[END_REF][START_REF] Henseler | Impact of round goby on native invertebrate communities -An experimental field study[END_REF][START_REF] Van Deurs | Impacts of the invasive round goby (Neogobius melanostomus) on benthic invertebrate fauna: a case study from the Baltic Sea[END_REF]. As opportunistic predators, round gobies prey on large epifaunal invertebrates that are available at high abundances, which causes a decrease in taxonomic diversity, trait-based diversity and average body size [START_REF] Henseler | Impact of round goby on native invertebrate communities -An experimental field study[END_REF], with potential consequences on ecosystem processes. Native fishes experience competition for food, spawning sites and are pushed to sub-optimal habitats. They can also experience increased apparent competition when fish-eating predators benefit from a dietary shift toward round gobies [START_REF] Reyjol | Do native predators feed on non-native prey? The case of round goby in a fluvial piscivorous fish assemblage[END_REF].

We derived the functional response of the round goby feeding on live dipteran prey with or without motorboat sounds. The functional response (FR) defines the relationship between resource availability (i.e. prey density) and per-capita predation rate [START_REF] Holling | The Components of Predation as Revealed by a Study of Small-Mammal Predation of the European Pine Sawfly[END_REF][START_REF] Delong | Predator ecology: Evolutionary ecology of the functional response[END_REF]. Because FR shape and magnitude are indicative of how the predator can control or destabilize its prey population [START_REF] Murdoch | Predation and Population Stability[END_REF][START_REF] Kalinkat | Body masses, functional responses and predator-prey stability[END_REF], it became a pivotal tool in ecology to quantify predation strength and parametrize dynamic models, and more recently in invasion biology to predict the trophic impact of invasive species [START_REF] Dick | Advancing impact prediction and hypothesis testing in invasion ecology using a comparative functional response approach[END_REF]. Predation tests were filmed to measure fish swimming distance and link alteration in FR with alteration in mobility. In separate tests, we measured the mobility of the dipteran larvae under the same acoustic regimes to be sure that alterations in FR were due to fish response to noise and not to prey behaviour. For instance, more active prey with noise could elicit higher predation by the fish. No change in functional response nor mobility between the two noise conditions would suggest tolerance to noise.

Materials and Methods

Fish collection

In April 2021, 60 round gobies (mean body mass ± sd = 1.7 ± 0.6 g) were captured by electrofishing in the Saône river at Cendrecourt (47°50'38''N, 05°55'34''E, Haute-Saône, France), an area of active range expansion in France. There is no motorboat activity on this upstream part of the river. This invasive goby population can thus be considered naive regarding motorboat noise. The fish were housed in the rearing facilities of the ENES lab (Equipe de Neuro-Ethologie Sensorielle) in a room thermoregulated at 18°C ± 1°C with 12:12 light:dark cycles. They were randomly allocated to two 110-L stock aquariums (30 fish per tank) filled with dechlorinated and salted (1.5 g. L -1 ) water and equipped with a 2-cm layer of natural sand (Aquasand Nature, Zolux), PVC tubes to provide shelters, air stones, and an external filter (Tetra EX 600). During a 3-week acclimatization period, they were fed three times a week with 0.11g of frozen chironomid larvae (Petra-Aqua, Praque-West, Czech Republic) per fish and starved for 24 hr prior to experimentation to standardize motivation. Water quality and oxygen content were checked daily.

Fish functional response and behaviour

Measures of functional response (FR) followed the procedure described by [START_REF] Rojas | From distraction to habituation: Ecological and behavioural responses of invasive fish to anthropogenic noise[END_REF]. Briefly, one single fish was introduced in a 50-L aquarium (length×width×height: 60×25×35 cm) containing a 2 cm layer of natural sand (Aquasand Nature, Zolux), 15-mm rubber panels covering both ends to control for acoustic reverberation, and a waterproof speaker (Electro-Voice UW30, 0.1-10 kHz) inserted in the middle of one of the two panels (side changed between tests). After a 30-min acclimatization period where the fish experienced the soundscape of their rearing aquarium (ambient noise condition, see 2.3), live chironomid larvae were introduced using a 250-ml glass beaker, and the fish was allowed to feed for 15 minutes under either ambient noise only (ambient noise condition hereafter) or ambient noise supplemented with motorboat sounds (boat noise condition hereafter). The fish was then removed with a hand net, weighted and the live prey remaining were counted. Each fish was only tested once and was randomly assigned to one trial defined by a noise condition (ambient noise or boat noise) and an initial prey density. The experimental plan was based on seven initial prey densities (N0 = 4, 8, 16, 32, 64, 128, 256) with four replicates each, corresponding to a total of 56 trials with 56 different fish. We finally did 54 predation trials instead of 56 (missing trials: N0 = 256 with ambient noise and N0 = 128 with boat noise) as six of the 60 sampled fish died during transport from the field or acclimatisation period in the laboratory prior to tests. For each noise condition, we added four replicates of the highest density without fish to confirm that prey removal was only due to fish predation and that no prey died in the experimental aquarium due to the noise conditions.

Fish behaviour was recorded using two cameras (HD-TVI ABUS TVVR33418), one facing the aquarium and one above. We used four experimental aquariums concurrently placed inside acoustic insulation boxes (81 x 67,5 x 73 cm) to reduce the duration of the whole experiment (4 days with the 54 trials distributed in a quasi-systematic way to balance the effect of time). Fish mobility was estimated as the total swimming distance (i.e., cumulative distance covered over the tested period) using the Mousotron software (12.1 version, Blacksun software).

Playback tracks

Using the Audacity software (Audacity Team 2021), we created two 45-min audio tracks starting with a 30-min acclimatisation period of ambient noise and continuing with a 15-min feeding period of either ambient noise alone for the control condition or ambient noise supplemented with eleven motorboat sounds distributed over three successive 3-min noise sequences (Table 1) for the boat noise condition.

Ambient noise corresponded to the soundscape of the 110 L rearing aquariums in which the fish spent three weeks before the FR experiments. Root-mean-square sound pressure level (RMS SPL) was approximately 110 dB re 1 mPa and included noise from the filtering system and general background noise of the breeding room. Such value is representative of the level of fast-flowing waters [START_REF] Wysocki | Diversity in ambient noise in European freshwater habitats: Noise levels, spectral profiles, and impact on fishes[END_REF]). We chose as control noise condition the soundscape that the fish experienced during the 3-week acclimatization period at the lab, and that we considered as the baseline level. An alternative control could be their natural soundscape. However, a playback of natural soundscape in the rearing aquariums would be superimposed to the noise emissions from the electric devices and the breeding room, resulting in higher levels and something that would not represent what the fish experience in the river. Motorboat sounds have been recorded in September 2018 by V. Médoc in the Grangent lake (45°45′07.54″N, 4°25′56.47″E, Loire, France) at one meter depth and corresponded to small recreational boats with outboard engines passing at various distances. Small tanks present three main acoustic biases that distort sound signals: low frequency attenuation, resonant frequencies and sound reverberation [START_REF] Akamatsu | Empirical refinements applicable to the recording of fish sounds in small tanks[END_REF]Novak et al. 2018). To make the playback as close as possible to the original signal, we used rubber panels as mentioned earlier and modulated some frequency contents of the input signal using the Audacity equalizer. We applied linear fading at both ends to make boat sounds emerge from ambient noise. We adjusted their intensity so as to obtain naturally-occurring signal-to-noise-ratio (SNR) values ranging from 12 to 22 dB (Fig. 1) with:

𝑆𝑁𝑅 = 20 𝑙𝑜𝑔 10 ( 𝑅𝑀𝑆 𝑏𝑜𝑎𝑡 𝑛𝑜𝑖𝑠𝑒 𝑅𝑀𝑆 𝐴𝑚𝑏𝑖𝑎𝑛𝑡 𝑛𝑜𝑖𝑠𝑒 )
The audio tracks were played back as WAV files using an audio player (VLC media player 1.1.8), an amplifier (Dynavox CS-PA 1MK) and the UW30 speaker. All recordings were made with an Aquarian Audio H2A-HLR hydrophone (frequency response from 10 to 100 kHz) connected to a Zoom H4next (Mogar Music, France) handy recorder. The spectral density was created with the R software using the seewave [START_REF] Sueur | Seewave, a free modular tool for sound analysis and synthesis[END_REF]) and tuneR [START_REF] Ligges | tuneR: Analysis of music and speech[END_REF] packages.

Prey behaviour

We used the same experimental aquarium and procedure as for the FR trials, except the cameras that have been replaced by an underwater GoPro (San Mateo, USA) Hero4 located 5 cm below the surface in the middle of the aquarium to increase resolution for the video analysis. A group of 16 live chironomid larvae was introduced into the aquarium and exposed to the 15-min playback tracks of either ambient noise or boat noise. We selected one of the seven densities used during the FR experiment and decided that 16 was a good trade-off, assuming that larval behaviour does not change with group size. For both noise conditions, we performed ten replicates and analysed the behaviour of two randomly chosen larvae among the group of 16, representing 40 individuals in total. Using the BORIS software [START_REF] Friard | BORIS: a free, versatile open-source event-logging software for video/audio coding and live observations[END_REF], we recorded the time spent moving during two periods: from 6'00 to 9'01 and from 12'00 to 15'04 (repeated measures), corresponding to the second and third sequences of motorboat sounds for the boat noise condition (see 2.3) and to ambient noise for the control. It was not possible to accurately monitor behaviour during the first noise sequence because some larvae were still sinking slowly after their release at the water surface.

Statistics

We used the R software (4.1.3 version, R Core Team 2022) with a significance level of 0.05 for all the statistics. FR analysis was done using the Frair package [START_REF] Pritchard | frair: an R package for fitting and comparing consumer functional responses[END_REF]. We used the frair_fit function to model by maximum likelihood estimation the three main prey-dependant FR models describing a linear (type I), saturating (Rogers's type II) or sigmoidal (Hassel's type III) relationship between prey density and predation rate. The best model was identified based on the second-order Akaike information criterion (AIC) and was always of type II where the per-capita predation rate (F) follows the equation:

𝐹 = 𝑎𝑅 1 + 𝑎𝑅ℎ (Eq. 1)
where a is the attack rate, R the prey density and h the handling time. This equation describes a diminishing return curve: predation rate increases monotonously with prey density and tapers off to an asymptote at high prey density. To account for the decline in prey density (consumed prey were not replaced to not disturb the fish), we used a modified version of Eq. 1 through the Random Predator Equation [START_REF] Bolker | Ecological models and data in R[END_REF][START_REF] Delong | Predator ecology: Evolutionary ecology of the functional response[END_REF] where the number of prey eaten (Ne) follows:

𝑁 𝑒 = 𝑁 0 (1 -𝑒 𝑎(𝑁 𝑒 ℎ-𝑇) )

where N0 is the initial prey density and T the total experimental time. As chironomid larvae are benthic, we standardized prey density to the number of prey per square metre as recommended by [START_REF] Uiterwaal | FoRAGE (Functional Responses from Around the Globe in all Ecosystems) database: a compilation of functional responses for consumers and parasitoids[END_REF]. Attack rate, which corresponds to the initial slope of the FR curve, was thus reported as m 2 per hour per predator. Handling time can be read as the inverse of the asymptotic predation rate [START_REF] Uiterwaal | FoRAGE (Functional Responses from Around the Globe in all Ecosystems) database: a compilation of functional responses for consumers and parasitoids[END_REF] and was reported as hour per prey. Bias corrected and accelerated 95% intervals (BCa) were generated and plotted on the FR curve using the frair-boot and drawpoly functions respectively. We used the delta method implemented by the frair-compare function to compare the estimates of a and h between the two noise conditions, with the null hypothesis that differences in attack rate (Da) and handling time (Dh) do not differ from zero [START_REF] Pritchard | frair: an R package for fitting and comparing consumer functional responses[END_REF]. A complementary approach based on non-parametric bootstraps gave us the same results (see supp. mat.).

Fish swimming distance was log-transformed [log(distance+0.5)] to normalize data for the analysis. Nontransformed data were used in the plot for readability. We used a generalized linear model with the glm() R function. The effects of noise condition, prey density, fish body mass and their interactions were assessed using AIC model selection [START_REF] Galipaud | Ecologists overestimate the importance of predictor variables in model averaging: a plea for cautious interpretations[END_REF] with the MuMIn package [START_REF] Bartoń | MuMIn: multi-model inference[END_REF].

Concerning larvae behaviour, we used generalized linear mixed-effect (GLME) models to take into account the repeated measures on the same individuals and the nested design in which two individuals were observed per trial. Individual identity nested in replicate number was used as a random variable. Noise condition, sequence number (second or third noise sequence), and their interaction were used as fixed variables. The proportion of time moving 𝑃 was modelled using beta regression [START_REF] Smithson | A better lemon squeezer? Maximum-likelihood regression with beta-distributed dependent variables[END_REF] with the transformation 𝑃′ = ((𝑛 -1)𝑃 + 0.5)/𝑛 in order to comply with the beta regression assumption stating that the data are within the interval ]0; 1[ [START_REF] Laubu | Mate choice based on behavioural type: do convict cichlids prefer similar partners?[END_REF]). The analysis was done using the glmmTMB package [START_REF] Brooks | glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling[END_REF]. Model selection was based on a backward procedure using likelihood-ratio tests.

Results

For both noise conditions, we did not observe chironomid mortality in the fishless replicates suggesting that chironomid removal was due to fish predation during the FR tests. There was no difference in fish body mass between noise conditions (𝐹 1,52 = 0.78, 𝑝 = 0.38) and prey densities (𝐹 1,52 = 0.015, 𝑝 = 0.90), or the interaction between noise conditions and prey densities (𝐹 1,50 = 1.07, 𝑝 = 0.30). Attack rates were 𝑎 = 0.351 prey per square metre, 95% 𝐶𝐼 = [0.143; 1.08] for the ambient condition, and 𝑎 = 1.134 prey per square metre, 95%𝐶𝐼 = [0.566; 2.27] for the boat noise condition. These two rates were significantly different (delta method: 𝑝 = 3 × 10 -5 ). Handling times were ℎ = 0.020 hour per prey, 95% 𝐶𝐼 = [0.01; 0.04] for the ambient condition, and ℎ = 0.012 hour per prey, 95%𝐶𝐼 = [0.009; 0.015] for the boat condition. These two values were significantly different (delta method: 𝑝 = 0.0012). As a result, FR was higher under boat noise compared to ambient noise, with both a steeper initial slope and a higher asymptote (Fig. 2A).

Concerning fish swimming distance, the best model based on the AICc values was the one that only includes noise condition and there was no other best model as the △AICc value of the second model exceeded the threshold value of two (Table 2). Swimming distance was longer under boat noise (Cohen's 𝑑 = 0.71, 95%CI = [0.15; 1.28], 𝜒 1 2 = 6.69, 𝑝 = 0.0097, Fig. 2B). Taking into account fish body mass, prey density, or any interactions between explanatory variables did not significantly improve the goodness of fit of the model. Table 2. Results of the multimodel inference analysis performed on fish swimming distance and comparing all possible combinations of the three explanatory variables: noise condition (C), fish body mass (M), prey density (D), and their two-way (C:M, C:D, M:D) or three-way (C:M:D) interaction terms. Each line corresponds to a model.

For each model, we reported intercept of the regression, adjusted R² (adj.R²), degree of freedom (df), Log likelihood (LogLik) values, Akaike information criteria values with a correction for small sample sizes (AICc), change in AICc (△AICc) from the best model, and model weight. The regression parameter is only given for the corresponding continuous variable (M, D) when this variable is present in the model. The presence of the categorial variable (T being either "boat noise" or "ambient noise") in the model is indicated by a "+" symbol.

The proportion of time spent active by chironomid larvae was affected neither by the interaction between noise condition and sound sequence (𝜒 1 2 = 0.288, 𝑝 = 0.59) nor by the sound sequence (𝜒 1 2 = 3.11, 𝑝 = 0.077, Fig. 3). More importantly, noise condition (ambient or boat noise) had no effect on prey activity (𝜒 1 2 = 0.327, 𝑝 = 0.57).

Discussion

First exposure to anthropogenic noise typically decreases foraging behaviours [START_REF] Cox | Sound the alarm: A meta-analysis on the effect of aquatic noise on fish behavior and physiology[END_REF]) and for some species this response weakens with prolonged exposure suggesting habituation [START_REF] Pritchard | frair: an R package for fitting and comparing consumer functional responses[END_REF][START_REF] Rojas | From distraction to habituation: Ecological and behavioural responses of invasive fish to anthropogenic noise[END_REF], as animals learn it is not associated with direct threat. Through the use of functional response (FR), we found for the first time that motorboat noise suggestively increases predation by an invasive fish, irrespectively of prey density. Noise also made round gobies more mobile, but had no effect on prey behaviour, suggesting that increased predation was solely attributable to fish behaviour. We cannot rule out that noise-disturbed larvae send out some sort of chemical cues like kairomones that might trigger fish mobility. However, this is unlikely given that, in general, non-predatory invertebrates as well as zooplankton usually behave as receivers while fish and predatory invertebrates act as senders [START_REF] Burks | Cued in: advances and opportunities in freshwater chemical ecology[END_REF]. For instance, fish kairomones have been shown to increase digging in the chironomid larvae Chironomus riparius [START_REF] Hölker | Adaptive behaviour of chironomid larvae (Chironomus riparius) in response to chemical stimuli from predators and resource density[END_REF] but we did not observe such response in the face of noise.

Attack rate describes predator's efficiency at capturing prey, namely the space (here the surface) that a predator searches per unit of time [START_REF] Holling | The Components of Predation as Revealed by a Study of Small-Mammal Predation of the European Pine Sawfly[END_REF]. It fixes the initial slope of the FR curve: the higher the attack rate, the steeper the slope. Round gobies were more mobile with noise, which increased the searched area and provided opportunities to encounter and catch prey [START_REF] Gerritsen | Encounter probabilities and community structure in zooplankton: A mathematical model[END_REF], thus explaining the increase in attack rate. In the meta-analysis by [START_REF] Cox | Sound the alarm: A meta-analysis on the effect of aquatic noise on fish behavior and physiology[END_REF], anthropogenic noise was found to increase fish movements in general, which could be part of an escape response as found under predation risk. Fish could also move more to avoid the source of noise or to look for the presence of conspecifics. However, under the assumption of a stress response, we would expect reduced feeding motivation and not increased predation as we observed. Further investigation is needed to explain why round gobies are more mobile with noise, for instance allowing for conspecific interactions, providing shelters, or mixing behavioural metrics with physiological makers of stress like cortisol [START_REF] Wysocki | Ship noise and cortisol secretion in European freshwater fishes[END_REF].

Ideally, handling time is associated with prey processing and describes the average time spent on a caught prey item (Holling The reverse of handling time gives an estimation of maximum feeding rate, which fixes the asymptote of the curve. Handling time was significantly lower with noise, suggesting that fish did better in terms of prey processing than under control conditions. This result seems contradictory to the principle of optimal foraging. It might be that experimental duration was long enough so that handling time also included other activities than prey processing [START_REF] Li | Experimental duration and predator satiation levels systematically affect functional response parameters[END_REF]. Such activities, like resting, could be modulated and in our case decreased by noise.

Supporting our findings that round gobies were not disturbed by boat noise when feeding, Higgs & Humphrey, (2020) reported that noise from recreational boats does not impair the calling behaviour of round goby. Using the same approach, we recently found that the functional response of another invasive fish, the pumpkinseed sunfish Lepomis gibbosus, was not altered by chronic exposure to boat noise [START_REF] Rojas | From distraction to habituation: Ecological and behavioural responses of invasive fish to anthropogenic noise[END_REF]. As it has been documented with other environmental stressors like temperature, salinity, hypoxia or food (Elis and MacIsaac 2009;[START_REF] Zerebecki | Temperature tolerance and stress proteins as mechanisms of invasive species success[END_REF][START_REF] Lagos | Do low oxygen environments facilitate marine invasions? Relative tolerance of native and invasive species to low oxygen conditions[END_REF], tolerance to anthropogenic noise might be another feature of successful invaders. Our results also provide an alternative explanation to the decrease in presence but not in foraging events in response to boat noise reported by [START_REF] Pieniazek | Comparative analysis of noise effects on wild and captive freshwater fish behaviour[END_REF]. It might be that increased mobility makes some gobies leave the area while those remaining forage more.

Increase in both functional response parameters indicates stronger top-down control that might drive the prey to exclusion, especially because high attack rates (i.e. steep initial slopes) can generate unstable boom-burst population dynamics [START_REF] Murdoch | Predation and Population Stability[END_REF]. Our study provides additional evidence that anthropogenic noise can modulate the strength of predator -prey interactions, with potential to reinforce the trophic impact of an invasive species. However, before scaling up these results to communities and generalizations, some limitations have to be discussed.

We reported sound levels in units of sound pressure while round gobies rely on particle motion to detect sounds [START_REF] Belanger | Hearing and the round goby: Understanding the auditory system of the round goby (Neogobius melanostomus)[END_REF]. According to Nedelec et al. (1016), we are in the conditions where the kinetic energy (KE) of particle motion has to me measured with a dedicated sensor and cannot be calculated from the potential energy (PE) of sound pressure. We don't have such sensor but in the recent paper by [START_REF] Olivier | Assessing the impacts of anthropogenic sounds on early stages of benthic invertebrates: The "Larvosonic system[END_REF] where they described the sound field of a tank using a hydrophone and a particle motion sensor concurrently, they demonstrated that acoustic impedance (PE/KE in dB) for a given frequency was constant (i.e., independent from source level). In other words, when source level increases or decreases by N dB, both PE and KE will increase or decrease by N dB. They conclude that relying solely on pressure can be used to detect trends, suggesting that the noise-induced increase in FR we found is still relevant although we did not measure particle motion.

There have been increasing calls to get away from tank-based acoustic studies that oversimplify reality and present acoustic biases as discussed above [START_REF] Popper | An overview of fish bioacoustics and the impacts of anthropogenic sounds on fishes[END_REF]. However, there are also studies demonstrating that field and lab results can be consistent (see [START_REF] Pieniazek | Comparative analysis of noise effects on wild and captive freshwater fish behaviour[END_REF]). In our opinion, tankbased studies are relevant to raise new predictions for further in-situ validation and identify potential causalities like the relationship between mobility and FR parameters of the present study.

Additional investigations exploring context dependencies in the response to noise are also needed. Functional response is known to be influenced by habitat complexity [START_REF] Alexander | Functional responses of the intertidal amphipod Echinogammarus marinus: effects of prey supply, model selection and habitat complexity[END_REF], conspecific presence [START_REF] Médoc | Functional response comparisons among freshwater amphipods: ratio-dependence and higher predation for Gammarus pulex compared to the non-natives Dikerogammarus villosus and Echinogammarus berilloni[END_REF], or natural enemies [START_REF] Iltis | Parasitism may alter functional response comparisons: a case study on the killer shrimp Dikerogammarus villosus and two non-invasive gammarids[END_REF]. Individual response to noise might also weaken with repeated exposure in case of habituation [START_REF] Rojas | From distraction to habituation: Ecological and behavioural responses of invasive fish to anthropogenic noise[END_REF]) and round gobies could resume normal behaviour on the long term. Comparing gobies from noiseless areas with areas where they experienced generations of boat noise would help address this question. As explained in the playback tracks section, we chose as control noise condition for the FR experiment the background noise that the fish experienced during the 3-week acclimatization period in the rearing aquariums, and that we considered as the baseline level. It would be interesting to also derive the FR under a river soundscape. For some reason that escape us, most of the round gobies we collected were small sized and it would be interesting to repeat the same experiment with large-sized individuals.

Our sampling location was in an area of active range expansion and it has been shown that round gobies from invasion fronts are bolder, disperse more and have higher metabolic rate compared to individuals from longer established populations [START_REF] Myles-Gonzalez | To boldly go where no goby has gone before: Boldness, dispersal tendency, and metabolism at the invasion front[END_REF][START_REF] Behrens | Physiology & Behavior Personality-and size-related metabolic performance in invasive round goby (Neogobius melanostomus)[END_REF]). An interesting perspective would be to investigate the response to anthropogenic noise between personality types and along the invasion gradient.

Figure 1 .

 1 Figure 1. Spectral density of the playback tracks measured in the experimental tank used for the functional response trials. The three red lines correspond to the three sequences of boat sounds from the boat noise condition and the blue line to the ambient noise condition.

Figure 2 . A :

 2A Figure 2. A: Functional response of round goby feeding on live chironomid larvae under boat noise (orange, top curve) or ambient noise (blue, bottom curve) condition. Each dot represents the number of prey consumed by a single fish for a given prey density. Curves show the predicted responses with their 95% confidence interval as shaded areas. B: Total swimming distance of the fish under ambient noise (blue) or boat noise (orange). The thick horizontal line depicts the median, and the solid dot the mean. The box depicts the interquartile range, and the whiskers are bound to the most extreme data point within 1.5 times the interquartile range. Data points outside this range are outliers. "**" means p < 0.01. On both plots, raw data points have been slightly horizontally jittered to avoid overlapping and increase readability.

Figure 3 .

 3 Figure 3. Reaction norm of 40 chironomid larvae (10 replicates per noise condition and two larvae per replicate) recorded under either ambient noise (blue lines) or boat noise (orange lines) condition during two three-minute noise sequences. Points are raw data and have been slightly horizontally and vertically jittered to avoid overlapping and increase readability.

Table 1 .

 1 Composition of the 15-min playback track broadcasting ambient noise supplemented with motorboat sounds during the functional response tests.

	Noise sequence	Boat ID	Sound duration (sec)	Start position	SNR (dB)
	1	1	70	00'00	14
	1	2	36	01'10	23
	1	3	47	01'46	20
	1	4	28	02'33	19
	2	5	38	06'00	22
	2	6	110	06'38	20
	2	7	33	08'28	12
	3	8	67	12'00	16
	3	9	20	12'20	21
	3	10	60	13'27	21
	3	11	34	14'01	22

10.1007/s10530-023-03072-w Marina Fernandez-Declerck et al. (2023)

10.1007/s10530-023-03072-w Marina Fernandez-Declerck et al. (2023)

Acknowledgements

We thank Jérôme Moreau, Sébastien Motreuil, Maria Texeira, Ludovic Guillard, Julien Bouchard, and Sylvain Besson for field sampling. We also thank Nicolas Boyer and Aurélie Pradeau for fish rearing. We are grateful to the referees who spent time on the manuscript and raised valuable comments.

Statements & Declarations

This research was supported by grant "AMI espèces prioritaires" (grant #20 014093 01) from Region Auvergne-Rhône-Alpes and PNA Apron.

We declare we have no competing interests. MFD, LT, FXDM and VM designed the study. MFD and ER performed the experiments and collected the data. MFD, LP, FXDM and VM analysed the data. MFD and VM drafted the manuscript, and all authors provided critical revisions. All authors approved the final version of the manuscript.

Data accessibility

All datasets and source code are available as electronic supplementary materials on public repository: Fernandez Declerck, Rojas, Prosnier, Teulier, Dechaume-Moncharmont, Médoc (2022) Datasets and R source code of manuscript "Adding insult to injury: anthropogenic noise intensifies predation risk by an invasive freshwater fish species" by Fernandez Declerck et al. Zenodo https://zenodo.org/record/6563528. DOI: 10.5281/zenodo.6563528

Ethics

Round goby and transport were approved by the Direction Départementale des Territoires de la Loire (DDT 42). All the procedures were conducted in accordance with appropriate European (Directive 2010/63/EU) and French national guidelines, permits, and regulations regarding animal care and experimental use (Approval no C42-218-0901, Direction Départementale de la Protection des Populations de la Loire, Préfecture du Rhône).


Thibault Clérice

Ariane Pinche

Malamatenia Vlachou-Efstathiou

Alix Chagué

Jean-Baptiste Camps

Matthias Gille-Levenson

Olivier Brisville-Fertin

Franz Fischer

Michaels Gervers

Agnès Boutreux

Matthias Gille Levenson

Federico Boschetti

Avery Manton

Simon Gabay

Patricia O'connor

Caroline Vandyck

Benjamin Kiessling

CATMuS Medieval: A multilingual large-scale cross-century dataset in Latin script for handwritten text recognition and beyond

Keywords: Historical sources, medieval manuscripts, Latin scripts, benchmarking dataset, multilingual, handwritten text recognition

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Cultural heritage institutions, propelled by the digitization wave of the last two decades, have made tens of thousands of manuscripts accessible online. However, these invaluable historical documents predominantly exist in image form, lacking machine-readable text. The surge in interest in automatic handwriting recognition for historical documents, as noted by Fischer et al. in 2011 [START_REF] Fischer | Transcription alignment of latin manuscripts using hidden markov models[END_REF], has only intensified, particularly with the emergence of all-in-one platforms such as Transkribus [START_REF] Kahle | Transkribus -A Service Platform for Transcription, Recognition and Retrieval of Historical Documents[END_REF] and eScriptorium [START_REF] Kiessling | escriptorium: an open source platform for historical document analysis[END_REF]. Offline Handwritten Text Recognition (hereafter HTR) has become an indispensable tool for philologists, historians, linguists, librarians, and archivists, providing large-scale transcriptions of documents that would otherwise remain largely untouched for research purposes [START_REF] Camps | Make love or war? monitoring the thematic evolution of medieval french narratives[END_REF].

While the advancements in HTR technology are commendable, producing a meaningful and diverse benchmark dataset remains a significant challenge. This challenge is particularly pronounced for manuscripts in the Latin script dating from the medieval millennium (500-1500 CE), where a substantial volume of documents awaits transcription. The precise number of such manuscripts is unknown, primarily due to the incomplete nature or overall absence of catalogues for every public or private collection. However, Buringh [7, p.,99] estimates that approximately 1,300,000 manuscripts from the Latin West, spanning the 1 st to the 19 th century CE, currently survive.

Simultaneously, medieval manuscript sources provide a distinctive playground for computer vision, particularly in the field of HTR, as the nature of the data presents a unique set of challenges and opportunities. Specifically, the dynamic evolution of language during the medieval millennium, manifested in linguistic variations across geographic regions and the absence of strict orthographic rules, along with variations in scribal practices at both collective and individual levels compared to their modern counterparts, establishes a rich and demanding Fig. 1: 96 random sample lines from the approximately 160,000 lines found in the dataset, written in different languages and scripts. Fig. 2: Several transcriptions are possible for these two images. On the left, ‹de la uirtut› and ‹dela ỽıꝛtut› are both acceptable transcriptions, depending on the annotation guidelines. Likewise, on the right, ‹uirũ principatu› could be normalized as ‹virum principatu›.

testing ground for exploring HTR capabilities. In this context, systems can be pushed to their limits (see Figure 1).

Due to conflicting or established traditions, transcription standards for medieval manuscripts exhibit significant diversity, thereby posing a considerable hurdle in creating a uniform framework for evaluating HTR models. Existing datasets adhere to a variety of project-specific practices, leading to compatibility issues in terms of data aggregation 15 . While some datasets include transcriptions according to printed edition standards, with resolved abbreviations [START_REF] Torres Aguilar | Handwritten text recognition for documentary medieval manuscripts[END_REF], others choose to maintain all parallel graphic variants for specific "characters", such as ‹s›/‹ſ› [START_REF] Gueville | Transcribing Medieval Manuscripts for Machine Learning[END_REF]. In contrast, our approach shifts the focus to the semantic weight of written signs, "merging" variant representations of the same "character" (cf. Figure 2), including diacritics such as macrons and tildes into one representative sign.

To address this visual diversity while maintaining common guidelines, we introduce the Consistent Approaches to Transcribing Manuscripts (CATMuS) and its medieval dataset, specifically tailored for evaluating HTR architectures. Collaboration among a dozen projects has resulted in a large-scale cohesive dataset comprising nearly 200 manuscripts or early printed documents in 10 different languages, containing over 160,000 lines. Presented in Parquet format, the dataset includes rich and historically relevant metadata such as century, language, script class, and genre.

While HTR and other discriminative methods, such as writer identification, script, and date classification, are the most prominent applications of our dataset, it could also cater to emerging techniques like Condition-Adaptive HTR [START_REF] Bhunia | Metahtr: Towards writer-adaptive handwritten text recognition[END_REF], computer-assisted palaeographical analysis [START_REF] Siglidis | The learnable typewriter: A generative approach to text line analysis[END_REF], as well as Handwriting Text Generation (HTG). For instance, through the utilization of Generative Adver-sarial Networks (GANs) for the creation of synthetic data [START_REF] Vidal-Gorène | Synthetic lines from historical manuscripts: an experiment using gan and style transfer[END_REF][START_REF] Karras | A style-based generator architecture for generative adversarial networks[END_REF][START_REF] Fogel | Scrabblegan: Semisupervised varying length handwritten text generation[END_REF][START_REF] Kang | Ganwriting: content-conditioned generation of styled handwritten word images[END_REF], we can leverage our extensive labeled dataset to generate under-represented features such as specific characters, script types, or period-related styles.

Before the detailed presentation of the related work, our contributions can be summarized as follows:

-Release of a large consistently annotated dataset in Latin script spanning over 9 centuries as text-image pairs in Parquet formats, enabling both imageto-text and text-to-image approaches given the scale of the data. -Metadata that enable experimentation for the previously mentioned tasks as well as different classification tasks, including script and century classification. -A thorough description of our transcription practice and an analysis of the datasets. -Benchmarking results for HTR.

Hereafter, this paper is organized into four distinct sections as follows: First, Section 2 provides an overview of parallel datasets, highlighting their annotation practices, metadata, and task specificities. Section 3 presents the CATMuS dataset, detailing general and specific characteristics as well as our transcription guidelines rationale, along with statistics. Finally, Section 4 presents standard benchmarking splits and results for two baseline models, followed by a brief discussion of the results.

Related Works

In terms of available data, numerous medium and large-size datasets have been released for HTR or specific tasks related to historical document analysis [START_REF] Nikolaidou | A survey of historical document image datasets[END_REF]. Some of these datasets have been utilized in HTR competitions organized within the framework of the ICDAR and ICFHR conferences. Only the most relevant datasets to ours, in terms of format (text-line annotation pairs), time-span, metadata, and tasks, are presented below to facilitate comparison.

Benchmarking Datasets for Historical Handwritten Text Recognition

In the domain of Historical HTR, various benchmarking datasets have gained attention, notably those focused on restricted periods such as the Middle Ages. Three main datasets serve as widely used benchmarks in HTR competitions, providing a foundational basis for evaluating model performance and advancements: the Perzival Database [START_REF] Fischer | Automatic transcription of handwritten medieval documents[END_REF] and the Saint Gall Database [START_REF] Fischer | Transcription alignment of latin manuscripts using hidden markov models[END_REF] from IAM-HistDB, and the ICFHR-2016 READ Dataset [START_REF] Toselli | Htr dataset icfhr[END_REF][START_REF] Sanchez | Icfhr2016 competition on handwritten text recognition on the read dataset[END_REF]. The first two address each a single document written by a single hand: Perzival comes from a manuscript from the 13 th century in Middle High German, and the second one Latin manuscripts from the 9 th century in Carolingian script. Despite being issued from the same "Historical Database," PerzivalDB and Saint Gall DB are incompatible when it comes to their transcription practices: the first one preserves parallel variants of letters -such as ‹s› and ‹ſ› -while the second one normalizes forms (such as ‹virum›), drops abbreviating diacritics such as macrons, and finally resolves specific signs such as ‹&› into "et." The ICFHR-2016 READ (Recognition and Enrichment of Archival Documents) dataset consists of a subset of documents from the "Ratsprotokolle collection" in Early Modern German, composed of approximately 30,000 pages of council meeting minutes from 1470 to 1805 written by several hands, which includes the very late Middle Ages with a much larger coverage of modern times.

Related Datasets for Historical Handwritten Text Recognition

Expanding beyond conventional benchmarks, there are several language-specific and period-specific datasets available in Latin characters, the details of which we elaborate on below. Despite their richness, these datasets may exhibit limitations for generalist approaches, including language specificity, temporal constraints, and project-specific variations in annotation practices.

Starting from French and Latin, the ORIFLAMMS Consortium macrodataset, composed of several different projects over a substantial interval of time, includes ECMEN[53], a subset of the dated and datable manuscripts from the Bibliothèque Nationale de France, PsautierIMS [START_REF] Stutzmann | Words as graphic and linguistic structures. Word spacing in Psalm 101 Domine exaudi orationem meam (eleventh-fifteenth centuries)[END_REF], transcriptions of the text of the biblical Psalm 101, and Fontenay [START_REF] Stutzmann | Fontenay dataset. original charters from fontenay before 1213[END_REF], containing charters from the Cistercian abbey Fontenay in Burgundy, providing a unique set of data. These datasets offer a diverse array of regional scripts from 779 manuscripts, ranging from the 12 th to the 14 th century, and offer meticulous metadata regarding provenance and date of production. They provide a mix of aligned preexisting normalized editions (without abbreviations) and graphemic transcriptions (including abbreviations and their expansion, but not regarding capital letters, punctuation, and spacing 16 ).

The most extensive source for documentary scripts 17 is HIMANIS(Historical MAnuscript Indexing for user-controlled Search) [START_REF] Stutzmann | la recherche en plein texte dans les sources manuscrites médiévales: enjeux et perspectives du projet himanis pour l'édition électronique[END_REF], which contains registers produced by the French Royal Chancery between 1302 and 1483. Ground truth was established by aligning digitized images line by line with the partial semidiplomatic edition of the text by Paul Guérin. In the same vein, but going a bit further, the e-NDP (e-Notre Dame de Paris) [START_REF] Claustre | The e-NDP project : collaborative digital edition of the Chapter registers of Notre-Dame of Paris (1326-1504). Ground-truth for handwriting text recognition (HTR) on late medieval manuscripts[END_REF], following an "edition-based" transcription, includes a total of 500 pages from 26 registers dating from 1326 to 1504, and the HOME-Alcar project [START_REF] Stutzmann | Home-alcar: Aligned and annotated cartularies[END_REF] includes 3090 acts from 17 French cartularies dating from the 12 th to the 14 th centuries respectively. The former is transcribed with edition norms, while the latter is aligned with scholarly editions, and both datasets include entities for important places and names.

Still within the Latin alphabet inventory but for manuscripts in modern scripts 18 , for Castilian, the most extensive parallel dataset, RODRIGO [START_REF] Serrano | The rodrigo database[END_REF], concerns one 1545 manuscript in old Castilian by one writer. A smaller set of initial name indexes, the Esposalles/INDEX [START_REF] Romero | The esposalles database: An ancient marriage license corpus for off-line handwriting recognition[END_REF] subset, includes 29 pages in Catalan by a single writer between 1491 and 1495. The transcription guidelines are unique for these two projects, as its base is imitative in terms of punctuation, capitals, and special signs, but with the addition of the symbol $ after every word cut in a page break, characters for missing natural blank spaces between successive words that are indicated by the symbol ‹ ›, and super/subscript elements that follow LaTeX-like notation as _{sub} and ˆ{super}, respectively (e.g., qˆ{i}er for superscript "i" in the word "quier"). For Italian, the LAM (Ludovico Antonio Muratori) dataset [START_REF] Cascianelli | The lam dataset: A novel benchmark for line-level handwritten text recognition[END_REF] stands out as the most extensive for the 17 th century concerned with 72 manuscript samples from one hand over 60 years, with their diplomatic annotations.

All solely edition-based datasets present normalized punctuation, spacing, and capitals, as well as resolved abbreviation (see Table 1). The issue of transcribing texts with resolved abbreviation (following the edition-based paradigm) has been explored in several recent articles [START_REF] Camps | Handling Heavily Abbreviated Manuscripts: HTR Engines vs Text Normalisation Approaches[END_REF][START_REF] Romero | Modern vs Diplomatic Transcripts for Historical Handwritten Text Recognition[END_REF]. Torres et al. [START_REF] Torres Aguilar | Handwritten Text Recognition for Documentary Medieval Manuscripts[END_REF] acknowledges that abbreviations 19 are part of the most common errors of their models, which could only be resolved when fine-tuning on a specific collection. Moreover, each of these papers, including the latter, fails to evaluate the generalizability of the models in cross-genre, diachronic, and multilingual settings, as they at most offer a bilingual setting but in very repetitive genres in only a few manuscripts.

Latin Palaeography Task-Related Datasets

Further delving into specific tasks related to Latin Palaeography, datasets such as CLaMM (Classification of Latin Medieval Manuscripts) [START_REF] Cloppet | Icfhr2016 competition on the classification of medieval handwritings in latin script[END_REF], and MPS (Medieval Paleographical Scale) focus on Latin script classification and dating, two tasks closely intertwined for historical analysis. CLaMM, designed for the classification of 12 book script types, encompasses Latin medieval manuscripts from the 5 th to the 16 th century. Originally employed in the ICFHR 2016 Competition for Script Classification, CLaMM comprises 10,800 images.

Similarly, the MPS dataset [START_REF] He | Towards style-based dating of historical documents[END_REF], utilized in ICFHR 2014 for manuscript dating, focuses on handwriting-based dating within a corpus of 1,706 charters originating from the Middle Dutch language area, spanning from 1300 to 1550. For incunabula and early print 20 , the "Dataset of pages from early printed books with multiple font groups" [START_REF] Seuret | Dataset of pages from early printed books with multiple font groups[END_REF], includes 35,623 images of pages written in 12 3 The CATMuS-Medieval Dataset

Extraction and Annotation Workflow Data Collection and Preparation

The CATMuS Medieval dataset is a macro-dataset, derived from various sources (cf. Table 2): (1) datasets originally produced following guideline norms, (2) datasets easily converted due to shared or compatible transcription practices, and (3) manually corrected datasets. Its creation unfolded through three distinct project phases; in the initial phase, the CREMMA and HTRomance projects were instrumental, with their members leading the formulation of primary transcription guidelines. These guidelines primarily focused on literary manuscripts written in book scripts, spanning Old French, Latin, Castilian, and Italian. The second phase witnessed the involvement of the DEEDS project, focusing on Latin cartularies. Finally, the third phase saw the adoption of our guidelines by the team working on the Monastery of Herne and research on Middle English.

Segmentation and Transcription

In our dataset, eScriptorium [START_REF] Kiessling | escriptorium: an open source platform for historical document analysis[END_REF] serves as the primary software used for annotation across projects, except for Mid- dle Dutch data transcribed using Transkribus [START_REF] Kahle | Transkribus -A Service Platform for Transcription, Recognition and Retrieval of Historical Documents[END_REF]. The common transcription practice involves employing a line and region segmentation model such as BLLA on eScriptorium [START_REF] Kiessling | A modular region and text line layout analysis system[END_REF], with corrections typically including cutting non-continuous lines or expanding them to ensure correct coverage of the text. Following Pinche's experiment regarding the compatibility of Transkribus and eScriptorium data [START_REF] Pinche | HTR Models and genericity for Medieval Manuscripts[END_REF], we repolygonized the data from Transkribus and post-corrected the inconsistencies. After segmentation, in the majority of our projects, the ground-truth results in the post-correction of an automatic transcription (see Section 3.2).

Extraction and Post-Processing All lines are extracted from images with XML files containing segmentation coordinates (baselines and masks) and their corresponding text label. The extraction process is twofold: first, the minimal bounding box around the bounding polygonal mask is used to crop the masks, followed by filling the area outside the mask with a proxy value approximating the color of the writing surface. For colored images, we use the the median value of pixels inside the mask, while for gray-level images are filled with white.

As handwritten lines of text are frequently curved and rotated, causing, in extreme cases, a complete breakdown of recognition, line images are rectified by projecting every line segment of the text line image onto the horizontal axis. To achieve this, a piecewise affine transformation is estimated from points sampled at regular intervals along the baseline and mask boundary, along with their respective target coordinates after rotation. This transformation is subsequently applied to the cropped line image to produce an approximately straight and upright line, independent of curvature, rotation, and other distortions in the source image.

After every line is extracted from a given page, they are sorted according to the hash of their text 23 . Each image-label pair is further annotated with six types of metadata associated with the manuscript, namely manuscript id or "shelfmark", century of production, language, script type 24 , textual genre, verse, two types derived from the page layout with the region's and line's classes (e.g., Main text, Interlinear Line), and finally, metadata indicating which split the line belongs to (see Section 4.1).

Transcription Guidelines

Rationale Extrinsic variability, linked to the rendering of historical sources, and intrinsic variability, linked to the nature of the data, pose a twofold issue for automated transcription.

Firstly, in the landscape of philological studies, the focus on scholarly editions that represent the culmination of scholarly editing norms and practices has often overshadowed the importance of the transcription process, leading to intermediate imitative transcriptions relegated to drafts or even lost altogether. This prevailing notion of the edition as the ultimate goal has significantly influenced researchers' perspectives on transcription, blurring the line between the two, whether within or outside HTR settings. Ultimately, methods for transcribing or editing texts are shaped by local traditions and field-specific expectations, sometimes leading to isolated practices with contradictory outcomes, influenced by factors such as country, language, and project goal. Drawing upon the linguistic field of Old French for illustration, philologists within the Anglo-Saxon tradition, influenced by entrenched practices, may edit texts that are missing accents or apostrophes [6, Introduction, p. 5], particularly in Anglo-Norman contexts, resulting in forms such as Dangleterre and labbe, whereas literary edited texts from different traditions would typically yield d'Angleterre and l'abbé.

At the same time, the necessity to accommodate a wide array of writing styles, all while preserving a consistent approach (cf. Section 2) stands out as the most significant challenge. Several factors contribute to this such as: (i) the extensive temporal span, covering the 8 th to 16 th centuries, (ii) the diverse linguistic landscape characterized by dialectal variations and graphical systems with distinct special characters within each emerging or dominant language, and (iii) the multitude of document types, each adhering to its unique conventions.

To address these challenges, we present guidelines designed to produce straightforward yet precise transcriptions of historical sources in a computer-readable format. CATMuS adopts a strategic approach aimed at balancing information loss (in our case morphological variation of graphemes) with standardization in text reproduction. These guidelines, initially formulated for medieval French documents spanning from the 10 th to the 15 th centuries [START_REF] Pinche | Guide de transcription pour les manuscrits du Xe au XVe siècle[END_REF], and gradually incorporating more diverse documents, recognize that in practice, minor deviations from traditional transcription practices may be necessary to ensure and promote dataset coherence in a digital setting.

Character Representation and Word Segmentation Rather than opting for a wholly imitative transcription 25 , we adopted a transcription approach that groups the forms of letters within the system of the Latin alphabet at the time. This approach, known as a graphemic approach [START_REF] Stutzmann | Paléographie statistique pour décrire, identifier, dater... normaliser pour coopérer et aller plus loin ?[END_REF], ensures a many-to-one mapping where allographs (or "character variants") are normalized, resulting in a distinctive representation for each letter:

-Graphic distinctions for the same character like ‹s› ("round ‹s›") and ‹ſ› ("long" ‹s›), or ‹ꝛ› ("round" ‹r›) and ‹r› ("short" ‹r›), are disregarded to mitigate potential cascading effects on other letters like a, d, e, etc. -Ligatures between letters, such as ‹st› or ‹ct›, are treated as variations in form, leading to the independent transcription of their constituent characters. -Any emphasis on the letter, regardless of its form, is transcribed as capital letters, including if the emphasis is only conveyed by size of the letter (and does not result in a different shape).

One of our most significant choices lies in what is called the "ramist" distinction between the pairs ‹u›/‹v›, and ‹i›/‹j›. We disregard this distinction, as these signs generally denoted variations in form (often tied to the character's placement in the word) rather than distinct phonetic realizations in most medieval sources. An illustrative example is the Roman numeral ".iij." (iii), where ‹j› is a prolonged ‹i› rather than the modern ‹j›. As a result, each ‹v› is transcribed as a ‹u›, and each ‹j› as an ‹i›.

Lastly, given that canonical word separation for all Latin and vernacular texts in Western Europe became standardized only by the end of the Middle Ages, when the word emerged as the primary unit of meaning, the representation of spaces between words in our dataset varies. It spans from scriptio continua (without spaces) to aerated text and deliberate use of lexical spaces. To alleviate potential discrepancies in imitative practices among transcribers, we opt for the semantic segmentation of words (lexical spaces). This decision, serving as the sole language-dependent choice in the project, has proven to yield beneficial results in sharing the guidelines among transcribers.

Abbreviations Adding to generalization issues as seen by Torres et al. [START_REF] Torres Aguilar | Handwritten text recognition for documentary medieval manuscripts[END_REF], abbreviation resolution is often tied to local specificities and extra-textual information, which led us to identify abbreviation resolution as a natural language processing (NLP) task rather than an HTR one. For instance, the decision to develop the Tironian sign ‹⁊› into ‹et› or ‹e› depends on chronological and geographical factors and is considered an interpretation, as e is the Anglo-Norman variation of the Old French et. Additionally, abbreviation systems provide valuable insights into the text, handwriting, production, or reception area, and text status (formal or working text). Preserving this information for resolution in a later stage of the textual acquisition pipeline can be highly beneficial.

The various signs fall into two main categories:

1. A large number are additions to base letters with diacritical marks, such as macrons (e.g. ‹ē› for est, -em, etc.), and superscript letters (‹q i › for qui), and their meaning is often context-dependent. Diacritics are thus treated as separate characters using Unicode decomposed form (NFD). 2. Few are separate semantically distinct signs, such as ‹&› for et/e), or letters with strike-through marks, such as ‹ꝑ›. For these, we resorted to the Medieval Unicode Font Initiative (MUFI) [START_REF] Haugen | MUFI Character Recommendation: Characters in the Official Unicode Standard and in the Private Use Area for Medieval Texts Written in the Latin Alphabet[END_REF].

Diacritics and special characters are treated similarly to letter allographs: for example, the macron and the horizontal tilde are both represented as a horizontal tilde, with the latter being chosen for ease of typing on most Western keyboards.

Punctuation, functional Signs, and Corrections Medieval documents feature intricate and varied punctuation systems, differing across periods, genres, and individual practices. Representing punctuation accurately requires an in-depth understanding of the manuscript. However, achieving a comprehensive representation of punctuation across multiple projects and transcribers is not feasible. To ensure consistency, four standardized signs26 synthesize the complexity of punctuation systems:

-Single full stops are transcribed as ‹.›; -Double signs are represented by ‹;›; -Commas are transcribed as ‹,›, -Question marks are transcribed as ‹?›, as soon as they appear in the Latin inventory in late middle ages.

Functional signs, when present in the source, serve to denote hierarchical segmentation of content (‹ ¶›), hyphenation (‹-›) for an end-of-line break of words, referral outside of the main text (‹⁜› -"dotted cross"), or insertion (‹‸›).

Finally, we have adopted a standardized approach to transcribe corrections noted in the sources, marked with expunction, strikethrough, or similar annotations. Adhering to the Leiden transcription conventions, the text identified by the scribal correction is enclosed within double brackets, namely ‹⟦›(U+27E6) and ‹⟧›(U+27E7).

Dataset Statistics

First of all, depending on the time of the digitization and the type of document scanned, often microfilms of the original documents (30 documents out of 203 The different metadata classes accompanying the dataset were chosen on the basis of historical relevance, accommodating historical analysis as well as facilitating testing of various architectural and model designs in one or combined research questions. On one hand, document information (script, shelfmark, century) provides graphical variation information. On the other hand, language-specific characteristics significantly influence the frequencies of certain characters 27 . Moreover, the literary genre and form, whether verse or prose, can influence various features such as line length, number of characters, punctuation usage, or script execution to some degree. Certain script types were also often favored depending on the genre of the text being copied (e.g., the Textualis script was typically used for copying the Bible). Lastly, the century of production serves as a generic proxy for language evolution, with potential impacts on lexical usage, conservation state, visual characteristics, and more.

In the following paragraphs, we provide comprehensive details about the dataset, including metrics concerning the number of lines, and character frequencies, potential biases inherent in the dataset, and the benchmarking possibilities it offers.

Word-and Character-level Analysis

The distribution of the number of words and character per line, on average 7 words and 37 characters per line, seems to align with benchmarking datasets such as IAM and LAM, as well as exhibiting regularity as the length is bimodal-distributed (Figure 4). The full dataset comprises 220 classes of characters, including 25 combining superscript characters, 16 stricken-through characters, and 22 combining diacritics.

Script and Language Distribution

Five projects [START_REF] Pinche | Edition nativement numérique du recueil hagiographique[END_REF][START_REF] Gille Levenson | Towards a general open dataset and model for late medieval Castilian text recognition (HTR/OCR)[END_REF][START_REF] Vlachou-Efstathiou | Eutyches "de uerbo[END_REF][START_REF] Haverals | The middle dutch manuscripts surviving from the carthusian monastery of herne (14th century): Constructing an open dataset of digital transcriptions[END_REF] collectively contribute to around 64% of the dataset or �112,00 lines, resulting in an inherent , the prolonged focus on Old French within these projects has led to its overrepresentation. Notably, the Herne project dataset alone accounts for 27% of the dataset, predominantly comprising Dutch from the 14 th century in Textualis. Consequently, Old French, Latin, and Castilian together account for more than 50% of the dataset in Textualis. We integrated print into the dataset (approximately 12% of the dataset or �11,000 lines) because incunabula demonstrate an affiliation with manuscripts primarily, in terms of scripts, as existing handwriting shapes inspired the initial typographic characters and subsequently in terms of abbreviating and spacing practices.

Cross-features Benchmarking Capacities

In terms of balanced representation across scripts, the Latin language stands out as the most suitable for benchmarking cross-script evaluation. Nearly all scripts are represented in Latin, except for Semitextualis. Castilian offers a strong representation, featuring six scripts out of ten possible for this language 28 .

On the other hand, for cross-language benchmarking, Textualis emerges as the prime candidate, with all languages represented except for Old English. The same possibility is offered by the Hybrida and Cursiva scripts, though less prevalent 29 , as they are shared among Castilian, Catalan, French, Italian, and Latin.

Lastly, since textual genres influence abbreviation practices and lexical choices, cross-genre evaluations could be conducted, particularly focusing on the Treatise Fig. 5: Distribution of the dataset across languages, centuries, and scripts, in % of the total character count. and Narratives genres. These genres encompass technical texts such as commentaries or medical treatises on one hand and historical or hagiographic on the other.

CATMuS Medieval for Benchmarking

Benchmark Splits

General Split The first split is designed so that every manuscript is present, with their lines divided on a 90% / 5% / 5% ratio. This allows for building models that have seen the full range of the data diversity, which is particularly important for languages less represented in the training data, such as Venitian (2 documents), Navarese (1), or Old English (1). This split is provided in the gen_split column of the parquet file.

Feature-based Split

The second split is organized such that each manuscript is allocated to a single split, simplifying the assessment of model generalization. However, the data distribution across splits is uneven due to variations in the number of lines per manuscript. Data distribution was managed as follows:

1. Rare languages were distributed manually: English, having specific letters, was put in the train set only; Venitian has one manuscript in each of the train and test split; Navaresse, as a language of Spain, was put in the test set only, as it provides an interesting linguistic case (it is close to Castilian and Catalan); 2. Italian and Catalan (9 and 5 documents each) were split with one document in test, one in dev, and the rest in train. The choice of the document to put in dev and test was made based on the frequency of the script both in the larger corpus and the language class; 3. Each script was then picked from the dataset, to be present in train, dev, and test if possible. 4. Other documents were dispatched by language, using the number of characters to match roughly a 90% / 5% / 5% split, resulting in a 85% / 7% / 7% splits (see Table 3).

Baseline Scores for Handwritten Text Recognition

Setup In this section, we report an experimental analysis of the performance of two software behind the most common platform for HTR used in the humanities and in the GLAMs, Kraken (version 4.3.10) [START_REF] Kiessling | Kraken-an universal text recognizer for the humanities[END_REF] and Pylaia (version 1.1.0) [START_REF] Puigcerver | Are multidimensional recurrent layers really necessary for handwritten text recognition?[END_REF], on both splits. The performances are reported in terms of Character Error Rate (CER). This is the number of substitutions, deletions, and insertions that have to be applied to the predicted sentence to obtain the ground truth. In addition, we calculate the error rate associated with the space character, incorporating the count of inserted single dots, as they are frequently indicative of space-related errors based on our experience. We trained Kraken and Pylaia with the default specifications or for the first and the recommended specifications for the later [START_REF] Maarand | A comprehensive comparison of open-source libraries for handwritten text recognition in norwegian[END_REF], in deterministic mode, with a batch size of 64, with three different seeds [START_REF] Gauthier | The Death of the Historical Corpus[END_REF][START_REF] Pinche | Données HTR incunables du 15e siècle [dataset[END_REF]84), and 5-epoch patience. Learning rate was set to 1e -4 for Kraken and 5e -4 for Pylaia. We trained on RTX8000, with 12 CPU cores for each training.

Results

The results presented in Table 4 offer valuable baseline metrics for each split, shedding light on the trade-offs inherent in different model architectures and hyperparameters utilized by each toolkit. As anticipated, the "General" split exhibits lower CER, given the absence of out-of-domain documents, whereas the "Feature"-based split surpasses 10%. This higher score presents an intriguing challenge for developing more domain-specific models that consider factors such as script type and language.

In an effort to interpret the results, the most common sources of mistakes, independently from the split, are typically related to space and punctuation Table 4: Baseline scores (average CER and standard deviation) with default configurations of Kraken and Pylaia. Each tool was used to train 3 models on each split. Validation CER is provided by each software, and Test CER was provided by Kraken's codebase. Time is based on the real of the unix time command. Space-related CER is computed on the test set with errors regarding space deletion, insertion, and single mark insertion. and are directly related to the inconsistency of this practice in the documents (with ever-evolving languages). Another set of common errors is linked to the insertion and deletion of combining signs -this is an interesting mistake as it suggests that contextual noise can skew predictions for combining characters, usually those occupying the upper writing band of the line (cf. Figure 3).

Conclusion

In this paper, we introduced the CATMuS dataset tailored for line-level HTR of historical manuscripts in Latin scripts, comprising over 160,000 lines, which we are releasing on HuggingFace 30 . Alongside image-text pairs, it includes historical metadata, making it suitable not only for HTR research but also for tasks like script classification, century dating, and palaeographical analysis. Comprehensive analysis of the dataset, including quantitative and qualitative assessments of its characteristics and performance using two widely used architectures for HTR namely Kraken and PyLaia, underscore the challenges posed by the dataset's inherent variation. We believe these challenges contribute to making the dataset a valuable resource for advancing effective solutions in HTR for historical documents. As a future extension of this endeavor, enhancing the dataset mainly with more fine-grained labels on scribes and provenance could elevate its level of supervision and task-specific splits, broadening its suitability for additional tasks related to historical manuscript analysis. As a result of this joint collaboration, we are looking forward to improvements in the space of graphemic multilingual diachronic handwritten text recognition.

Fig. 3 :

 3 Fig. 3: Representative examples of the main script types lines, with CATMuS annotations.

Fig. 4 :

 4 Fig. 4: Statistics on the frequency of character types (left), number of words (middle), and characters (right) per line.

  Similarly

Table 1 :

 1 Overview of parallel datasets. Abbr. Res. identifies datasets with resolved abbreviations. Char. Var. identifies the presence of multiple classes for single letters (e.g. ‹s›/‹ſ›). Modern. stands for edition-like modernization (e.g. spelling). Mss stands for Manuscripts, EP for Early Prints, SC/FC/DC for Script, Font, and Date Classification, l. for lines, d. for documents, i. for images.

	Dataset	Type Century Language	Script type	Task	Abbr. Char. Modern. Quantity
							Res. Var.
	IAMHistDB/St. Gall Mss	9	Latin	Bookscript	HTR	1,410 l.
	IAMHistDB/Perzival Mss	13 German	Bookscript	HTR	4,477 l.
	ICFHR 2016-READ	Mss	15-19	Ger.	Modern	HTR	10,550 l.
	ORIFLAMMS	Mss	12-14 French, Lat. Book., Docum.	HTR	120,111 l.
	HIMANIS	Mss	14-15 Fr., Lat.	Documentary	HTR	23,112 l.
	HOME -Alcar	Mss	12-14 Fr., Lat.	Bookscripts	HTR, NER	74806 l.
	e-NDP	Mss	14-16 Fr., Lat.	Documentary	HTR	33,735 l.
	RODRIGO	Mss	16 Spanish	Bookscript	HTR	20,357 l.
	Esposalles/INDEX	Mss	15 Catalan	Modern	HTR	1,563 l.
	LAM	Mss	17-18	Italian	Modern	HTR, DC	25,823 l.
	MPS	Mss	13-16	Dutch	Documentary	DC	1,706 d.
	CLAMM	Mss	5-15	Lat.	Bookscripts	SC, DC	10,800 i.
	MFG 22	EP	15-17	Multi.	Fonts	FC	35,623 i.
	CATMuS (Ours) Mss, EP	8-16	Multi.	Bookscripts HTR, SC, DC	165,347 l.
					Documentary
					Fonts

fonts, including Greek and Hebrew, occasionally multilabel lines, for font and multilabel classification methods.

21

Table 2 :

 2 Reviewers are included in annotators. "Many" represents situations where the number of annotators is superior to three or unknown.

	Repository	Type	Annotators Documents Lines Characters
	Carthusian Monastery Of Herne	Manuscripts	Many	18 47,322 1,560,687
	Gallicorpora [43,20,42]	Manuscripts, Early prints, Incunabula	5	28 16,515	605,938
	CREMMA[41,14]	Manuscripts	4	35 29,722 1,048,144
	HTRomance[35,1,23,5]	Manuscripts	8	52 16,574	611,244
	PSL-Chartes-HTR-Students/HN2021-Boccace[63] Incunabula	Many	2	3647	126,677
	PSL-Chartes-HTR-Students/decameron-fr[4]	Manuscripts	Many	1	751	23,278
	Towards General Castilian HTR[22]	Manuscripts	1	29 29,043 1,003,888
	adhoc/matthias	Manuscripts	1	3	253	10,728
	adhoc/patricia	Manuscripts	1	1	586	18,396
	ciham/fabliaux[44]	Manuscripts	1	5	2070	54,245
	ciham/liber[2]	Manuscripts	Many	4	3788	159,799
	DEEDS Project	Manuscripts	1	9	2327	153,067
	malamatenia/Eutyches[62]	Manuscripts	1	4 12,309	372,528
	rescribe/carolineminuscule-groundtruth[27]	Manuscripts	Many	17	440	19,890
	Total			208 165,347 5,768,509

Table 3 :

 3 Statistics on the two different benchmarking splits.

	Split	Set	Lines Characters Languages Documents Scripts
	General	Train	146,885	5,178,330	9	203	10
		Validation	8,317	293,888	9	203	10
		Test	8,317	294,435	9	203	10
	Feature-based Train	138,900	4,892,639	8	176	10
		Validation	11,376	446,148	5	11	9
		Test	13,243	427,866	8	17	9

A similar tendency has been observed in the treatment of digital historical corpora[START_REF] Gauthier | The Death of the Historical Corpus[END_REF].

Note that all of the ORIFLAMMS datasets underwent minimal normalization when combined with other datasets by another research team[START_REF] Camps | Data diversity in handwritten text recognition. challenge or opportunity?[END_REF].

Documentary scripts in the Middle Ages are developed alongside Bookscripts, the latter used for literary manuscripts, and they are Cursiva-adjacent scripts.

We consider modern scripts the scripts developed after the Humanistic script, namely personal hands, like "Secretary" and Italic hands that resemble modern handwriting.

They provide the example of short expansions ("no[-bis]"), heavy contractions ("m[a]g[is]t[er]"); declension and syntax-dependent expansion ("Par." which can be "Par[is]", "Par[isiensis]" or "Par[isiense]"), among others.

The term incunabula refers to the books printed before the year 1501 using movable type.

This dataset was used alongside CLaMM and extra provenance annotations for script classification, document dating, and localization in ICDAR2021.

Due to limitations imposed by certain libraries, the line order of the page has not been preserved for certain manuscripts. This serves as a proxy for random shuffling while enabling a form of versioning.

Alongside CLaMM, we adhere to Derolez's typology[START_REF] Derolez | The palaeography of Gothic manuscript books: From the twelfth to the early sixteenth century[END_REF], which is based on morphological aspects. However, it is worth noting that this typology is based on consensus, especially considering the substantial increase in script families and sub-families by the late 14 th century, as well as cursivity techniques and level of execution which also affect their visual characteristics.

A choice that, given the collaborative nature of our initiative, might have led to divergent interpretations of letterforms.

All punctuation marks are transcribed directly after the preceding sign without spaces.

For instance "k" and "w", 90-95% of which is present only in text written in Middle Dutch and English.

Excluding the Caroline script, which historically ceased to be used as Gothic scripts came to the foreground in the 13 th century.

Especially for Hybrida, which offers a distinct Spanish variation.