Merve Nur Tunc
email: merve-nur.tunc@inrae.fr

Rosa Del Campo

Steven Porter

Florence Dubois-Brissonnet

Romain Briandet

Rut Carballido-Lopez

Resistance to the Last-Resort Antibiotic Colistin in Pseudomonas aeruginosa

INTRODUCTION

Pseudomonas aeruginosa is among 'the 3 most critical antibiotic-resistant priority pathogens list' of the World Health Organisation (WHO) 1 . Besides being resistant , it causes several chronic infections including biofilm formation in cystic fibrosis patients.

Desease cause by Pseudomonas aeruginosa infection [START_REF] Proctor | Potential Therapeutic Targets for Combination Antibody Therapy against Pseudomonas aeruginosa Infections[END_REF] .

Colistin (polymyxin E) is an antibiotic used as a lastresort treatment for infections caused by multidrugresistant (MDR) Gram-negative bacteria, for example P. aeruginosa. As a last resort antibiotic, it is in the WHO list of 'the critically important antimicrobials for human medicine' 1 .

Illustration of Colistin mode of action, resistant/tolerance mechanisms of P. aeruginosa 3 and new combination therapies.

OBJECTIVE

Recent studies show an increase in the number of P. aeruginosa isolates less sensitive to colistin in chronic infection [START_REF] Mohapatra | Polymyxins, the last-resort antibiotics: Mode of action, resistance emergence, and potential solutions[END_REF] . Drug A is a new candidate to restore colistin sensitivity in P. aeruginosa. It is the mainstone of the project: it has no antimicrobial activity on its own in P. aeruginosa but has synergistic antibacterial activity with colistin. Preliminary results show that it restores sensibility to colistin in resistant strains. The main aim of the project is hence to decipher the molecular processes involved in the colistin-resensitivation mechanisms to better control it.

Why is the Colistin-Drug A synergy important? Hypothesis

RESULTS

I. Demonstration of the colistin -Drug A Synergy a. Minimum Inhibitory Concentration (MIC)

• For P. aeruginosa the breakpoint of colistin is 4 mg/L. • As a control, aztreonam is used and its breakpoint is 16 mg/L. Biofilm was grown for 24 hours and treated with only colistin, Drug A , and a combination of them for 24 hours. Green channel refers to sfGFP fluorescent protein expressed live cell population in the biofilm.

> Drug

> There is a decrease of live cell biofilm population in the end of 24 hour treatment when Drug A is combined with colistin, but quantitative analysis results are needed to make a conclusion <

CONCLUSION/ PERSPECTIVES

Even though the bactericidal mechanism of colistin is not fully known yet, several hypotheses could be involked to explain the synergistic interaction of colistin and Drug A . The first results suggest that the leading cause of this synergistic interaction is not related to membrane fatty acids modification or colistin resistance mechanism of P. aeruginosa.

The first steps were taken for the genetic construction of the strains required for the test of bacterial membrane structure and permeability. Developed fluorescent tools including Lattice-SIM, 4D-LSC Microscopy and cytometry will be put in used to decipher the molecular origin of the observed synergy.

•

  A decreasing MIC value of colistin and polymyxin B for both sensitive and resistant P. aeruginosa strains while it has no effects on aztreonam MIC value < b. Which resistance/tolerance mechanisms cause high MIC values? > All strains have same colistin resistantce/tolerant genes, but replication number of them are different from strain to strain < c. What we need for the next step? of Cell Ultrastructure When Combinatory Treatment is Applied > Presence of extracellular materials is observed in the presence of colistin, and their size is increasing when colistin is combined with Drug Effect on the growth rate • Membranes permeability • Cell death differences *Please scan the QR code to observe the preliminary results of Lattice-SIM time-lapse imaging of P. aeruginosa with colistin alone, Drug A alone, and their combination. III. Action in biofilms structures • Effect on biofilm formation • Biofilm structural dynamics • Local expression of resistance /tolerance genes with fluorescent reporters 3D z-stack visualisation of live cell biofilm population of PAO1-fix + pMCR-1 strain.

ACKNOWLEDGEMENTS

The project is conducted within the ProCeD and B3D Teams of The Micalis Institute, INRAe, and Merve Nur TUNC ( PhD student) is supported by Paris Region (Region Ile-de-France, DIM1HEALTH). This poster is granted by BioProbe interdisciplinary initiative of Université Paris-Saclay.


Dr Dominique Lamonica
email: dominique.lamonica@ird.fr

Lison Charvy

Dr Dave Kuo

Dr Clémentine Fritsch

Michael Coeurdassier

Philippe Berny

Sandrine Charles

Mrs Lison Charvy

Dr Michaël Coeurdassier

Prof Charles Sandrine

A brief review on models for birds exposed to chemicals

Keywords: ecotoxicology, avian species, toxicokinetic-toxicodynamic models, drug, diet

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

Introduction

As early as 1962, Rachel Carson warned about the devastating effects of plant protection products (PPP) on terrestrial vertebrates in her pioneering book Silent Spring [START_REF] Carson | Silent Spring[END_REF]. Later in 1967, Ratcliffe reported that birds ingesting the synthetic pesticide DDT (dichloro-diphenyl-trichloroethane) had a tendency to lay eggs with thin shells that broke prematurely in the nest. This was confirmed by [START_REF] Cade | DDE residues and eggshell changes in Alaskan falcons and hawks[END_REF] as resulting in marked population declines, a problem that has driven bald eagles, the national symbol of the United States, along with peregrine falcons and other bird species, to the brink of extinction, with populations collapsing by up to 80%. Since then, all around the world, extensive studies have been carried out to understand the mechanisms underlying this phenomenon. The results of these studies are summarized in a recent collective expertise (ESCo, Pesce et al ( 2021)), especially chapter 9 (Mamy et al ( 2022), p623-720) focusing on terrestrial vertebrates to report on the state-of-the-art about: (i) active substances, types or families of PPP for which effects on wildlife are proven, probable, possible or null; (ii) the relationship between the exposure features in different groups of terrestrial vertebrates and the induced effects; (iii) the main mechanisms (in particular direct and indirect ones) inducing the main effects; (iv) the identification of the most influential environmental factors (agronomic, ecological. . .); (iv) the impact of PPP on functions and ecosystem services provided by terrestrial vertebrates.

Basically, Mamy et al (2022) identified as highly probable the causal link between the use of PPP and the decline in invertebrate and bird populations observed over several decades, particularly in agricultural areas, in interaction with landscape simplification. Depending on the bird species and their diet, PPP impacts are mainly the result of either a direct effect (e.g., ingestion of PPP-treated seeds by granivorous birds) or an indirect effect (e.g., reduction of food resources due to the decline of prey); see Chapter 9 in Mamy et al (2022) for more details. Environmental monitoring networks in various European countries, including France, have revealed a large number of cases of PPP poisoning of birds in the vicinity of agro-ecosystems. For granivorous birds, the recorded cases since the beginning of the 2000s are mostly caused by the ingestion of seeds treated with neonicotinoids [START_REF] Bishop | Hummingbirds and bumble bees exposed to neonicotinoid and organophosphate insecticides in the fraser valley, british columbia, canada[END_REF], more specifically imidacloprid (Rogers et al, 2019). For insectivorous birds, the impact of PPP is mainly expressed indirectly, through the decline in food resources. Several studies in Europe have demonstrated the existence of significant correlations between the use of PPP and the concomitant decline in insect communities and bird populations [START_REF] Hallmann | Declines in insectivorous birds are associated with high neonicotinoid concentrations[END_REF][START_REF] Bowler | Long-term declines of European insectivorous bird populations and potential causes[END_REF]Møller, 2019). In addition to these correlations, effects through the consumption of contaminated prey have recently been demonstrated by a multi-residue analysis of the diet of nestlings (Poisson et al, 2021); these effects, which lead to the decline of certain populations, are mainly due to the presence of neonicotinoids in the environment [START_REF] Humann-Guilleminot | Contamination by neonicotinoid insecticides in barn owls (Tyto alba) and alpine swifts (Tachymarptis melba)[END_REF]. Apart from the lethal effects of PPP, flight efficiency and orientation of birds may also be impaired in response to exposure. Such sublethal effects have been observed, for example, in migratory birds stopping over in agricultural areas, thus compromising the smooth running of the critical migration period (Eng et al, 2017(Eng et al, , 2019)).

The field of modeling has been particularly prolific in recent years, for example in the prediction of contaminant transfer based on the physico-chemical characteristics of the substances involved, combined with scenarios incorporating different types of crops, climate and soil (Servien et al, 2022). But numerous models have also been developed to better describe how organisms accumulate the chemicals and how the internal damages translate into effects on their life history traits (Larras et al, 2022b). Modeling is also repeatedly mentioned as a potential solution for integrating the processes involved at different spatial and temporal scales. For example, it is not uncommon in the literature to find work that combines ecotoxicological models, to describe the impacts of PPP, with ecological models, which describe the links between organisms and the functions they ensure within ecosystems. In particular, there are spatially explicit models that take into account not only the exposure of organisms, but also the toxic potential of PPP and the adverse effects they have on demography, while taking into account variability in both the landscape and exposure [START_REF] Topping | Risk assessment of UK skylark populations using life-history and individual-based landscape models[END_REF](Topping et al, , 2016;;Topping and Weyman, 2018;Topping et al, 2020). Nevertheless, as modeling strongly relies on the collection of experimental data and the metadata to which they are associated, data availability is the major constraint to which model building and the testing of their performances faces, especially at large spatial and temporal scales. All of this finally prevents a wider use of models in environmental risk assessment. Bird models in brief An interesting perspective of the use of population modeling is the possibility to extrapolate bio-monitoring data related to PPP bioaccumulation or specific effects in terms of population risk of extinction. Based on a matrix population model, [START_REF] Goutte | Demographic, endocrine and behavioral responses to mirex in the South polar skua[END_REF] provided a nice illustration with the South polar skua, a large seabird, for which long term demographic monitoring disclosed a possible effect of an organochlorine insecticide on the breeding success, thus compromising the population viability. One of the key points of population models is their ability to support extrapolation from one species to another, as illustrated for birds by Etterson et al 2017. Such a rapid cross-species transposition of population models (especially stage-structured ones) benefits from the recent construction of large ecological databases gathering together demographic traits particularly helpful in conservation science. For instance, De Zwaan et al. have recently compiled a huge data set of alpine breeding records for 1,310 bird species, representing 12.0% of extant species and covering all major mountain regions across the five continents, except Antarctica (de Zwaan et al, 2022). Benefiting of such data collections is the condition to support parameter inference for population models, especially when a large number of species is involved. Such data bases are also particularly helpful when ranking species vulnerabilities is required in relationship with the different uses of PPP [START_REF] Forbes | Assessing pesticide risks to threatened and endangered species using population models: Findings and recommendations from a CropLife America Science Forum[END_REF][START_REF] Etterson | Mechanistic modeling of insecticide risks to breeding birds in North American agroecosystems[END_REF].

The EU Regulation 1107/2009 defines all requirements before placing PPP on the market, in association with data requirements from regulations 283/2013 and 284/2011. In particular, an assessment is required regarding the risks for bird reproduction when they are exposed to PPP. In this perspective, the OECD guideline 206 provides the way data must be collected through standard toxicity test protocols whereby birds are exposed to the active substance of interest for a period of 20 weeks. However, the expected exposure period of active substances and their numerous degradation products in field (as determined by EFSA guidelines), can be much shorter thus creating disparities between both methodologies. For non-vertebrate species, such an issue can be overcome by additional testing. However, owing to the need to avoid vertebrate testing, this option is not valid for birds. Therefore, the use of in silico approaches predicting toxicity endpoints for birds can be helpful (European Food Safety Authority et al, 2023). In particular, toxicokinetic (TK) models, relating the exposure concentration to the fate of chemicals within an organism, coupled with toxicodynamic (TD) models, that make the link between cellular, biochemical and physiological damages and individual effects on life history traits, are potentially useful tools to refine risk assessment of PPP for birds, especially under a regulatory framework where such models remain still underused. [START_REF] Forbes | A Framework for Predicting Impacts on Ecosystem Services From (Sub)Organismal Responses to Chemicals[END_REF]. One inside the other, PBTKTD models are the key pillars of a comprehensive approach along the gradient of effects at all levels of biological organization (European Food Safety Authority et al, 2023). However, as already stated above, moving towards more complex models necessarily means benefiting of more data. In particular, no generic PBTKTD models are available for refined environmental risk assessment of birds and mammals, since data requirements are very high [START_REF] Astuto | In Silico Methods for Environmental Risk Assessment: Principles, Tiered Approaches, Applications, and Future Perspectives[END_REF]. Here lies the dilemma facing PPP risk assessors for birds, i.e. discourage the use of additional vertebrate testing, while acquiring sufficient and appropriate data to improve assessment models. Clearly, the way forward seems to be an intensive search of the literature for information already collected. In this context, this paper presents a state-of-the-art of the different kinds of models that have been developed in the last decades to sustain the deciphering of chemical effects on birds. Notice that we do not detail the different types of model (done by Larras et al (2022b); Astuto et al ( 2022)) to focus on where reusable data feeding these models can be caught up.

After giving full details on the bibliographical methodology we adopted, we present the general trends that emerge from our corpus of articles. We give a breakdown of models by type (e.g., TD, food web) and by level of organization (e.g., individual, community), before specifically examining bird models crossing model type with their inputs (e.g., exposure routes) and outputs (e.g., measured internal concentration). Then, we conclude in identifying the main gaps, as well as some ideas for overcoming them, and to go beyond.

Methods

Scientific articles were screened within several bibliographic databases including Clarivate Web of Science ©, PubMed (McEntyre and Ostell, 2002), Google Scholar (López-Cózar et al, 2019), Scopus [START_REF] Baas | Scopus as a curated, highquality bibliometric data source for academic research in quantitative science studies[END_REF], and the co-authors' personal databases (those provided by [START_REF] Kuo | A Critical Review of Bioaccumulation and Biotransformation of Organic Chemicals in Birds[END_REF], > 500 Bird models in brief entries, and Mamy et al ( 2022), > 2500 entries). The final paper collection was achieved in February 2023, covering a period from the end of the seventies until today.

The bibliographic queries were performed following several steps summarized in Figure 1. Google Scholar was first requested with an initial Scopus keyword equation (data not shown) providing a preliminary collection of few papers that were scrutinized through titles and abstracts to refine the final query equation.

Then, the above-mentioned bibliographic databases were all required with the final Scopus keyword equation (Figure 1). From there, we excluded references of books, book chapters, editorials and notes, to only keep peer-reviewed journal articles. Finally, we excluded all papers not referring to modeling issues. In particular, we excluded papers without any model, or containing pure descriptive models, such as those with only basic hypothesis testing methods. Purely general papers without case studies were also removed from our collection. Additionally to the terms we used in our query, our paper collection was only limited to research and review papers published in peer-reviewed journals and written in English. At the end of the process, we had a total of 130 papers (97 from the bibliographic databases and 33 from the coauthors' personal databases). All these papers have been gathered together within a metadata file (in comma separator value format) available at https://doi.org/10.5281/zenodo.7685817. In addition to the classical fields defining a bibliographic reference, this metadata file records information about the biological species (wild/domestic, feeding regime, common and Latin names), the chemical substances (group, name, CAS number) and/or the models (model type, level of biological organization that is concerned) that have been used by the authors. The metadata file also inventories the Bird models in brief exposure routes and the measured endpoints provided in the papers. In the end, the metadata file has 130 rows and 59 columns. A critical step in the assembly of this metadata was the identification of the model type used by the authors. To proceed, we first separated models processing at the individual level, that is the most employed. Among them, dose-response models were easy to classify. For the rest of the papers, a careful check within the different sections of the papers finally allowed us to clearly identified the type of model.

The paper collection, no reference being duplicated, was imported into the R software (R Core Team, 2022) and analyzed to quantify the scientific production per year, feeding groups (distinguishing between carnivores, frugivores, granivores, herbivores, insectivores, omnivores, and piscivores), chemical groups (according to their usage), level of biological organization (individual, population community)) and model types (see Table 1 hereafter). In the end, our paper collection led us to identify the main research tendencies related to the employment of models in support of a better deciphering of the impacts of chemical substances on birds. This also allowed us to highlight advantages and drawbacks of these models.

Additionally to the metadata file, the supplementary material provided at https://doi.org/10.5281/zenodo.7685817 contains all resources to identically reproduce the figures we are presenting below.

Results

Without claiming exhaustivity, our collection of papers (fully listed at the end of the manuscript) shows that studies involving models in bird ecotoxicology started to be published during the late seventies, with a slight increase from 2000, then only few papers each year (Figure 2). Half of the 130 papers focused on granivores (namely, seed-eating birds [START_REF] Anadón | Plasma disposition and tissue depletion of difloxacin and its metabolite sarafloxacin in the food producing animals, chickens for fattening[END_REF][START_REF] Fournier | Modeling PCB transfer into hen eggs: Influence of physiological characteristics of the animal[END_REF][START_REF] Pollet | The pharmacokinetics of chlortetracycline orally administered to turkeys: Influence of citric acid and Pasteurella multocida infection[END_REF]). Among wild species, groups of carnivores (i.e., predatory birds, such as raptors [START_REF] Azmanis | Disposition of posaconazole after single oral administration in large falcons (Falco spp): Effect of meal and dosage and a non-compartmental model to predict effective dosage[END_REF][START_REF] Engelman | Modelling effects of chemical exposure on birds wintering in agricultural landscapes: The western burrowing owl (Athene cunicularia hypugaea) as a case study[END_REF][START_REF] Rattner | Brodifacoum Toxicity in American Kestrels (Falco sparverius) with Evidence of Increased Hazard on Subsequent Anticoagulant Rodenticide Exposure[END_REF]) and piscivores (i.e., birds foraging for and eating fish or other sea life [START_REF] An | A method of assessing ecological risk to night heron, Nycticorax nycticorax, population persistence from dichlorodiphenyltrichloroethane exposure[END_REF][START_REF] Goutte | Demographic, endocrine and behavioral responses to mirex in the South polar skua[END_REF][START_REF] Sánchez | Population pharmacokinetics of itraconazole solution after a single oral administration in captive lesser Bird models in brief flamingos (Phoeniconaias minor )[END_REF] are similarly represented (between 9 and 14 %) (Figure 3, upper panel). A bit less than one third of the papers investigated drugs, while around 20% of them focused on PPP (Figure 3, lower panel). Regarding trace metallic elements, mercury and derivatives have been the most studied [START_REF] Smith | Do estuaries pose a toxic contamination risk for wading birds?[END_REF][START_REF] Nichols | A physiologically based toxicokinetic model for methylmercury in female American kestrels[END_REF][START_REF] Jackson | Mercury exposure affects the reproductive success of a free-living terrestrial songbird, the carolina wren (Thryothorus Ludovicianus)[END_REF]. Exposure routes, all chemical substances combined, covered the full range of bird feeding regimes via their food sources. Exposure via injection or oral administration were the most widely studied regarding toxicokinetic-toxicodynamic aspects. Last but not least, exposure models describing the contamination routes, dealt with environment (i.e., exposure via air, or not specified), food, or more rarely water via drinking [START_REF] Nelson | Model for trace metal exposure in filter-feeding flamingos at alkaline Rift Valley Lake, Kenya[END_REF][START_REF] Conder | Avian ecological risk potential in an urbanized estuary: Lower Hackensack River, New Jersey[END_REF][START_REF] Moore | A probabilistic risk assessment for the Kirtland's warbler potentially exposed to chlorpyrifos and malathion during the breeding season and migration[END_REF].

The salient point, which is not directly visible from Figure 3 but which follows directly from it, is the total absence of studies that address the effects of PPP on bird species of interest for the regulatory environmental risk assessment.

For example, European regulations 283/20134 and 284/20135 recommend determining the acute oral toxicity of an active substance to a quail species (Japanese quail, Coturnix coturnix japonica or bobwhite quail, Colinus virginianus), while data on additional species, such as Serinus canaria, may be requested by other legislative frameworks (European Food Safety Authority et al, 2023). These quail and canary species were totally absent from our set of studies. On the contrary, poultry species are studied a lot, and the most, with a majority of the related papers employing toxico-/phamarco-kinetic (TPK) models. Laying hens and broiler chicken species were both studied, the latter being much more used (47 out of 130 papers). Regarding chicken, exposures to drugs and PPP were the most investigated contaminants, while modeling speaking, TPK models are almost exclusively used among the 47 papers. About 80% of the studies were conducted at the individual level ( At the population level, several model frameworks have been employed such as individual-based models [START_REF] Hallam | Modeling effects of chemicals on a population: Application to a wading bird nesting colony[END_REF], matrix demographic models [START_REF] Goutte | Demographic, endocrine and behavioral responses to mirex in the South polar skua[END_REF], or Monte Carlo Markov Chain models [START_REF] Bennett | Incorporating Results of Avian Toxicity Tests into a Model of Annual Reproductive Success[END_REF]. Such models describe the effect of a chemical at the population level, either by incorporating critical effect concentrations on the chosen endpoints (e.g., survival, reproduction, behavior) together with an exposure scenario [START_REF] Etterson | Quantifying the effects of pesticide exposure on annual reproductive success of birds[END_REF], or by directly negatively impacting one or several vital rates, such as survival rate or reproductive success, compared to a scenario without contamination [START_REF] An | A method of assessing ecological risk to night heron, Nycticorax nycticorax, population persistence from dichlorodiphenyltrichloroethane exposure[END_REF].

At higher levels of biological organization and/or with spatially explicit models, studies are much rarer (less that 5%) (Table 1, right panel). Community level papers from our collection used food chain models to investigate bioaccumulation via two case studies (organochlorine accumulated in Arctic birds [START_REF] Borgå | Biological and chemical factors of importance in the bioaccumulation and trophic transfer of persistent organochlorine contaminants in arctic marine food webs[END_REF]) and polychlorinated biphenyls accumulated in eggs of San Francisco bay birds [START_REF] Gobas | Food web bioaccumulation model for polychlorinated biphenyls in san francisco bay, California, USA[END_REF]). In our database spatially explicit models were population models including a compartment describing environmental changes and/or where birds were located in space, allowing to investigate for example habitat modification impact [START_REF] Nacci | An approach to predict risks to wildlife populations from mercury and other stressors[END_REF], feeding habits [START_REF] Matsinos | An individual-oriented model for ecological risk assessment of wading birds[END_REF], or crop rotation [START_REF] Topping | Risk assessment of UK skylark populations using life-history and individual-based landscape models[END_REF]. 4, most of the studies employed TPK models to investigate drug effects on birds after injection or oral administration [START_REF] Kuo | A Critical Review of Bioaccumulation and Biotransformation of Organic Chemicals in Birds[END_REF], by measuring the time course of internal concentrations at the whole organism level [START_REF] Gögebakan | Single-dose toxicokinetics of permethrin in broiler chickens[END_REF], or distinguishing target organs [START_REF] Yang | Estimating marbofloxacin withdrawal time in broiler chickens using a population physiologically based pharmacokinetics model[END_REF].

Figure 4 (second column and blue lines) also clearly demonstrates that toxico/pharmaco-dynamics and dose-response analyses are under-represented (see also Table 1,left panel), which points to a crucial gap in observed data of chemical effects on bird life history traits. While the lack of toxico/pharmacodynamic models can be understood easily enough (due to their difficult handling and implementation), it is much more surprising to find so few studies involving dose-response models, while they are today the basis of the regulatory environmental risk assessment. Moreover, there are today no general accepted methods that are currently available for how to calibrate and from that, the quantity of pesticide ingested [START_REF] Moore | A probabilistic risk assessment for the Kirtland's warbler potentially exposed to chlorpyrifos and malathion during the breeding season and migration[END_REF].

Among the 130 papers, some studies were generic in scope, but for different reasons. A total of 41 papers (31.5%) concerned several biological species that were simultaneously studied as exposed to a same chemical [START_REF] Newsted | Pharmacokinetics and acute lethality of perfluorooctanesulfonate (PFOS) to juvenile mallard and northern bobwhite[END_REF][START_REF] Samuels | Calculations of seabird population recovery from potential oilspills in the mid-atlantic region of the united states[END_REF]. A total of 45 papers (34.6%) reported effects of several chemicals on one bird species [START_REF] Topping | Risk assessment of UK skylark populations using life-history and individual-based landscape models[END_REF][START_REF] Wayland | Survival rates and blood metal concentrations in two species of free-ranging North American sea ducks[END_REF]. And only 8 papers out the 130 were general reviews covering a wide spectrum of species-compound combinations (see for example [START_REF] Kuo | A Critical Review of Bioaccumulation and Biotransformation of Organic Chemicals in Birds[END_REF]). It is worth to note that only two papers dealt with the impacts of multiple stressors: the first on white-tailed eagle populations [START_REF] Korsman | Modelling the impact of toxic and disturbance stress on white-tailed eagle (Haliaeetus albicilla) populations[END_REF]; the second on the common loon [START_REF] Nacci | An approach to predict risks to wildlife populations from mercury and other stressors[END_REF]. One of the most striking points of our review is that only 9 papers (∼7%) gave access to raw data, potentially reusable for further studies. Results displayed in Figure 4 also appeared in a limpid manner within the title-394 based word cloud provided as graphical abstract. This word cloud specifically emphasizes how frequent TPK studies applied to chickens were, as well as that toxico/pharmaco-kinetic models were equally frequently employed, while no chemical substances appeared more studied than another one.

Conclusion

Our bibliographic corpus showed a certain diversity in model types, chemicals, exposure routes and feeding groups. Nevertheless, we identified a huge gap in models dealing with chemical effects on birds at the individual level, even if we found a large collection of papers on toxico/pharmaco-kinetic aspects. This is far from being a negligible source of information. However, originally interested in toxicokinetic-toxicodynamic models on birds exposed to PPP, it was clear that we would have very few previous studies at our disposal on which to capitalize. Focusing on bird species targeted by the regulatory environmental risk assessment and their exposure to PPP in addition, we ended up with no dedicated resources to draw on. Both bad and good news in the end. Indeed, we had found a new niche in which to innovate and develop new modeling tools to support next generation risk assessment for birds. In such a perspective, the key point will undoubtedly be the availability of raw data to build clever and comprehensible mechanistic effects models, generic enough to be employed for a wide battery of bird species and chemical compound combinations. Under the umbrella of Open Science, achieving such dreamed tools, should mandatorily imply full compliance to the FAIR data principles. To do so, we could recommend adding non invasive endpoint measurements on birds together with the current practice of TPK studies, or in vitro studies that are considered as a good alternative to in vivo testing to better decipher TPK properties.

Such data could advantageously support further development of the TPK part of TPK-TPD models, tools that now make sense to our community, which more broadly advocates the need to modernize wildlife risk assessment through improved collaboration, data sharing, application of standardized exposure scenarios, better communication of assumptions and uncertainties of models, and post-regulatory monitoring [START_REF] Ml | Peer review of the pesticide risk assessment of the active substance Reynoutria sachalinensis extract[END_REF].

Supplementary Information

All supplementary information mentioned in this manuscript is available at https://doi.org/10.5281/zenodo.7685817.

Acknowledgment

  EFSA recently formulated recommendations to develop open source generic physiologically based TK (PBTK) models for a range of relevant species among which birds play an important role (European Food Safety Authority et al, 2023). Larras et al (2022a) also established how huge is the gap between Bird models in brief the set of models used in PPP regulatory reports and those existing in the literature, thus highlighting the need for the implementation of more sophisticated models into PPP regulation. With the idea of describing the whole cascade of impairments, from the exposure conditions to the apical effects, PBTKTD models clearly appear as the most appropriate tool to focus with effects at the individual level in the perspective of moving towards the next generation risk assessment practice. Nevertheless, accounting for molecular initiating events (usually based on omic-type data) and the subsequent series of intermediate steps and key events leading to an adverse outcome is also of great interest to provide a clear-cut mechanistic representation of critical toxicological effects; this is what are allowing Adverse Outcome Pathways (AOP) approaches (Vinken, 2013). Hence, combining AOP with PBTKTD models could help in finely refining risk assessment. Similarly, linking individual effect models such as PBTKTD models with population and community ones could complement protection schemes including both direct and indirect effects

1 Fig. 1

 11 Fig.1Diagram of the bibliographic method we used to built the final corpus of scientific papers analyzed in this review.

Fig. 2 Fig. 3

 23 Fig. 2 Number of papers published per year among our collection of 130 scientific articles.

  validate toxicokinetic-toxicodynamics (TKTD) models without animal testing (European Food Safety Authority et al, 2023). As a consequence, due to the 3R requirements (European Parliament and European Council, 2010), such a lack in effect quantifier models prevents to attempt interconnecting individual and population levels in the perspective of gaining in ecological relevance, while still including information for which it is easier to obtain experimental observations. Contamination via food represented the main exposure route (∼ 45 %) within studies covered by our 130 papers (Figure 4, fourth orange line). For example, Meda et al. developed a physiologically based pharmacokinetic model to investigate the main factors involved in the transfer of α-hexabromocyclododecane to broiler meat (Méda et al, 2020); Fournier et al (2015) assessed the impact of physiological characteristics of laying hen on the transfer of ingested PCBs to their eggs. Regarding exposure models, they have been developed to address levels of chemical contamination in the field, Bird models in brief mainly for PPP. For example, Moore et al. developed probabilistic models to estimate, during the breeding season and the spring and fall migrations, how many chlorpyrifos and malathion granules Kirtland's warblers ingest and,

Fig. 4

 4 Fig. 4 Cross-view of the 130 papers analyzed in this review, categorized by model type (columns) and model outputs (measured internal concentration, pink lines, measured endpoints, blue lines) or model inputs (exposure routes, orange lines). At column-line intercepts, histograms show the number of papers as a function of the studied chemical(s).

Table 1

 1

	, left

[START_REF] Zhao | Integration of pharmacokinetic and pharmacodynamic indices of valnemulin in broiler chickens after a single intravenous and intramuscular administration[END_REF]

. However, Toxicodynamic and dose-response studies were rarer, probably because they would imply experiments with vertebrates that are subject to restrictions. Another plausible explanation could be a lack of interest in toxic effects on laboratory species themselves, contrary to the indirect effects that its diet may have on human health

(Rani et al, 2021)

. In this perspective, TPK models are the appropriate tools.

Table 1

 1 Number (#) of papers per model type (left) and per level of organization (right), among our collection of 130 scientific articles.

	Model type	Meaning or Based on	#	Biological level #
	TPK	Toxico-/Pharmaco-Kinetic	89	Individual	104
	TD	Toxico-Dynamic	12	Population	22
	DR	Dose response	4	Community	2
	Energy-based Dynamic Energy Budget theory 5	Landscape	3
	ODE based	Ordinary Differential Equations	11
	IBM	Individuals or Agents	3
	Food web	Multiple trophic interactions	2
	Spatial	Spatially explicit	3
	Exposure	Exposure profile feature	13
	Other	Any other type	6
	By crossing views on our paper collection, classified by both model types
	(columns) and either model outputs (measured internal concentration, pink
	lines / measured endpoints, blue lines) or model inputs (exposure routes,
	orange lines), we finely deciphered what were the main objectives of most
	of the studies on birds exposed to chemicals. As shown in Figure

  The authors would like to thank Dr. Raphaël Pelissier & Dr. Philippe Verley from IRD (UMR AMAP, Montpellier, France) who supported the participation of Dr. Dominique Lamonica once she started in her new position as IT engineer in ecology. Competing interests The authors declare no competing interests. Bird models in brief Larras F, Beaudouin R, Berny P, et al (2022a) A meta-analysis of ecotoxicological models used for plant protection product risk assessment before their placing on the market. Science of the Total Environment p 157003. Mamy L, Achard Al, et al (2021) Collective scientific assessment as a relevant tool to inform public debate and policy-making : an illustration about the effects of plant protection products on biodiversity and ecosystem services. Environmental Science and Pollution Research 28:38,448-38,454. https://doi.org/10.1007/s11356-021-14863-w Poisson MC, Garrett DR, Sigouin A, et al (2021) Assessing pesticides exposure effects on the reproductive performance of a declining aerial insectivore. Ecological Applications 31(7):e02,415. https://doi.org/https://doi.org/10.1002/ eap.2415 R Core Team (2022) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, URL https://www.R-project.org/ Bird models in brief Rani L, Thapa K, Kanojia N, et al (2021) An extensive review on the consequences of chemical pesticides on human health and environment. Journal of Cleaner Production 283:124,657. https://doi.org/10.1016/j.jclepro.2020. 124657 Ratcliffe D (1967) Decrease in Eggshell Weight in Certain Birds of Prey. Nature 215(8):208-210 Rogers KH, McMillin S, Olstad KJ, et al (2019) Imidacloprid Poisoning of Songbirds Following a Drench Application of Trees in a Residential Neighborhood in California, USA. Environmental Toxicology and Chemistry 38:1724-1727. https://doi.org/10.1002/etc.4473 Servien R, Latrille E, Patureau D, et al (2022) Machine learning models based on molecular descriptors to predict human and environmental toxicological factors in continental freshwater. Peer Community In Ecotoxicology and Environmental Chemistry 2:e15 Tang FH, Lenzen M, McBratney A, et al (2021) Risk of pesticide pollution at the global scale. Nature Geoscience 14(4):206-210. https://doi.org/10.1038/ s41561-021-00712-5 Topping CJ, Weyman GS (2018) Rabbit population landscape-scale simulation to investigate the relevance of using rabbits in regulatory environmental risk assessment. Environmental Modeling and Assessment 23:415-457 Topping CJ, Dalby L, Skov F (2016) Landscape structure and management alter the outcome of a pesticide ERA: Evaluating impacts of endocrine disruption using the ALMaSS European Brown Hare model. Science of the Total Environment 541:1477-1488. https://doi.org/10.1016/j.scitotenv. 2015.10.042 Topping CJ, Aldrich A, Berny P (2020) Overhaul environmental risk assessment for pesticides. Science 367(6476):360-363. https://doi.org/10.1126/ science.aay1144 Vinken M (2013) The adverse outcome pathway concept: A pragmatic tool in toxicology. https://doi.org/10.1016/j.tox.2013.08.011 de Zwaan DR, Scridel D, Altamirano TA, et al (2022) GABB: A global dataset of alpine breeding birds and their ecological traits. Scientific Data 9:627.

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	This work was : (i) part of a tender project financially supported by EFSA (OC/EFSA/SCER/2021/07); (ii) based on a preliminary work performed by experts among co-authors within the framework of the collective scientific assessment commissioned by the French Ministries for Ecology, for Research, and for Agriculture on the effects of plant protection products on biodiversity and ecosystem services and published in May 2022; (iii) performed under the umbrella of the French GDR "Aquatic Ecotoxicology" framework which aims at fostering stimulating scientific discussions and collaborations for more Consent to participate Not applicable. Consent for publication All authors contributed to and agreed on the final version of the manuscript. Authors contributions Dominique Lamonica and Lison Charvy: Paper collection, Metadata collection and curation. Dominique Lamonica: Metadata investigation, Methodology, Visualization, Analysis. Dominique Lamonica and Sandrine Charles: Writing -Original draft preparation. Sandrine Charles: Investigation, Supervision, Validation, Writing -Reviewing and Editing. Dave Kuo, Clementine Fritsch, Michaël Coeurdassier and Philippe Berny: Investi-gation, Reviewing and Editing. Funding EFSA (OC/EFSA/SCER/2021/07). Larras F, Charles S, Chaumot A, et al (2022b) A critical review of modelling approaches for environmental risk assessment due to pesticides. Environ-ment Science and Pollution Research 29:43,448-43,500. https://doi.org/10. 1007/s11356-022-19111-3 Li L, Li D (2021) Inter-Individual Variability and Non-linear Dose-Response Relationship in Assessing Human Health Impact From Chemicals in LCA: Addressing Uncertainties in Exposure and Toxicological Susceptibility. Fron-tiers in Sustainability 2:1-12. https://doi.org/10.3389/frsus.2021.648138 López-Cózar ED, Orduña-Malea E, Martín-Martín A (2019) Google scholar as a data source for research assessment. In: Springer handbook of science and technology indicators. Springer, p 95-127 Mamy L, Pesce S, Sanchez W, et al (2022) Impacts des produits phytophar-maceutiques sur la biodiversité et les services écosystémiques. Rapport de l'expertise scientifique collective. https://doi.org/10.17180/0gp2-cd65 McEntyre J, Ostell J (2002) The NCBI handbook. Bethesda (MD): National Center for Biotechnology Information (US) birds in denmark over 22 years. Ecology and Evolution 9(11):6581-6587. https://doi.org/https://doi.org/10.1002/ece3.5236 Naidu R, Biswas B, Willett IR, et al (2021) Chemical pollution: A growing peril and potential catastrophic risk to humanity. Environment International 156:106,616. https://doi.org/10.1016/j.envint.2021.106616 Pesce S, https://doi.org/10.1038/s41597-022-01723-6 Bibliographic corpus of the review Abou-Donia MB (1979) Pharmacokinetics and metabolism of a topically applied dose of O-4-bromo-2,5-dichlorophenyl O-methyl phenylphospho-nothioate in hens. Toxicology and Applied Pharmacology 51(2):311-328. integrative approaches in ecotoxicology. Ethics approval Not applicable. https://doi.org/10.1016/0041-008X(79)90474-5

Data, Material and/or Code availability Data and code are available at https://doi.org/10.5281/zenodo.7685817.