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Smartphone applications for anglers that function as citizen science platforms are an alternative to the traditional survey methods that are used to collect data from recreational fisheries. Comparisons between these two methods are needed to understand the impacts of the biases associated with data generated from smartphone applications. However, such comparisons are uncommon, especially for multiple fisheries over time and across space. In this study, we compared catch and effort data from an electronic citizen science platform for anglers with an offsite web-based recall survey for consecutive (i) 3-month periods in a spatially distinct (i.e., the Danish island of Funen) sea trout (Salmo trutta) fishery (2017–2020), (ii) 6-month periods in coastal sea trout and coastal/offshore cod (Gadus morhua) fisheries across eight ICES management areas (2016–2020), and (iii) 6-month periods in a freshwater pike (Esox lucius) fishery (2016–2020). Catch and effort data from the two surveys were, in most cases, consistently similar over time for the Funen sea trout and Danish freshwater pike fisheries. In contrast, we found that the recall survey estimates were consistently 100–200% larger than the citizen science platform for both sea trout and cod in ICES areas. Our findings suggest that the applicability of electronic citizen science platforms for anglers can be fishery-specific, and that systematic bias may occur.

Agri-ecological environment management is a valuable tool for reducing agricultural impacts on ecosystems. Socio-ecological simulations can support these tools to find better solutions for managing natural resources. Nonetheless, these models are still few and scattered, often stand-alone and usually applicable to a specific context. Here, we present a Formal Model for reproducing the farmer opinion dynamic in a multi-layer geospatial network, focusing on the influence farmers embedded in the same landscape have on each other. The study aims to provide a new tool to integrate complex socio-ecological system simulations incorporating human behaviour and decision-making components, specifically focused on the farmer’s social networks and opinion diffusion modelling. The farmers are modelled following the bounded rationality framework and applying the concept of ecological rationality and a bounded confidence opinion dynamic model governs the interaction between agents. The interaction between the agents is governed by an asymmetrical function and involves an explicit role of uncertainty. The model generates a connection between farmers using different criteria and developing a multilayer system where geographical, economic and social aspects are considered. The Geo-Social Network model (GeSoN) shows promising dynamics and types of behaviour, mainly attributable to the formation of consensus, polarisation and fragmentation amongst the agents’ opinions. Moreover, the GeSoN model presents flexibility and adaptability to be incorporated into more complex simulation systems.

Abstract. Carbon monoxide (CO) is a naturally occurring atmospheric trace gas, a regulated pollutant, and one of the main components determining the oxidative capacity of the atmosphere. Evaluating climate–chemistry models under different conditions than today and constraining past CO sources requires a reliable record of atmospheric CO mixing ratios ([CO]) that includes data since preindustrial times. Here, we report the first continuous record of atmospheric [CO] for Southern Hemisphere (SH) high latitudes over the past 3 millennia. Our continuous record is a composite of three high-resolution Antarctic ice core gas records and firn air measurements from seven Antarctic locations. The ice core gas [CO] records were measured by continuous flow analysis (CFA), using an optical feedback cavity-enhanced absorption spectrometer (OF-CEAS), achieving excellent external precision (2.8–8.8 ppb; 2σ) and consistently low blanks (ranging from 4.1±1.2 to 7.4±1.4 ppb), thus enabling paleo-atmospheric interpretations. Six new firn air [CO] Antarctic datasets collected between 1993 and 2016 CE at the DE08-2, DSSW19K, DSSW20K, South Pole, Aurora Basin North (ABN), and Lock-In sites (and one previously published firn CO dataset at Berkner) were used to reconstruct the atmospheric history of CO from ∼1897 CE, using inverse modeling that incorporates the influence of gas transport in firn. Excellent consistency was observed between the youngest ice core gas [CO] and the [CO] from the base of the firn and between the recent firn [CO] and atmospheric [CO] measurements at Mawson station (eastern Antarctica), yielding a consistent and contiguous record of CO across these different archives. Our Antarctic [CO] record is relatively stable from −835 to 1500 CE, with mixing ratios within a 30–45 ppb range (2σ). There is a ∼5 ppb decrease in [CO] to a minimum at around 1700 CE during the Little Ice Age. CO mixing ratios then increase over time to reach a maximum of ∼54 ppb by ∼1985 CE. Most of the industrial period [CO] growth occurred between about 1940 to 1985 CE, after which there was an overall [CO] decrease, as observed in Greenland firn air and later at atmospheric monitoring sites and attributed partly to reduced CO emissions from combustion sources. Our Antarctic ice core gas CO observations differ from previously published records in two key aspects. First, our mixing ratios are significantly lower than reported previously, suggesting that previous studies underestimated blank contributions. Second, our new CO record does not show a maximum in the late 1800s. The absence of a [CO] peak around the turn of the century argues against there being a peak in Southern Hemisphere biomass burning at this time, which is in agreement with (i) other paleofire proxies such as ethane or acetylene and (ii) conclusions reached by paleofire modeling. The combined ice core and firn air [CO] history, spanning −835 to 1992 CE, extended to the present by the Mawson atmospheric record, provides a useful benchmark for future atmospheric chemistry modeling studies. International audience

As alien invasive species are a key driver of biodiversity loss, understanding patterns of rapidly changing global species compositions depends upon knowledge of invasive species population dynamics and trends at large scales. Within this context, the Ponto-Caspian region is among the most notable donor regions for aquatic invasive species in Europe. Using macroinvertebrate time series collected over 52 years (1968–2020) at 265 sites across 11 central and western European countries, we examined the occurrences, invasion rates, and abundances of freshwater Ponto-Caspian fauna. We examined whether: (i) successive Ponto-Caspian invasions follow a consistent pattern of composition pioneered by the same species, and (ii) Ponto-Caspian invasion accelerates subsequent invasion rates. In our dataset, Ponto-Caspian macroinvertebrates increased from two species in 1972 to 29 species in 2012. This trend was parallelled by a non-significant increasing trend in the abundances of Ponto-Caspian taxa. Trends in Ponto-Caspian invader richness increased significantly over time. We found a relatively uniform distribution of Ponto-Caspian macroinvertebrates across Europe without any relation to the distance to their native region. The Ponto-Caspian species that arrived first were often bivalves (46.5% of cases), particularly Dreissena polymorpha, followed secondarily by amphipods (83.8%; primarily Chelicorophium curvispinum and Dikerogammarus villosus). The time between consecutive invasions decreased significantly at our coarse regional scale, suggesting that previous alien establishments may facilitate invasions of subsequent taxa. Should alien species continue to translocate from the Ponto-Caspian region, our results suggest a high potential for their future invasion success highly connected central and western European waters. However, each species’ population may decline after an initial ‘boom’ phase or after the arrival of new invasive species, resulting in different alien species dominating over time. This study was supported by the Grant Agency of the University of South Bohemia, project number 065/2022/Z. R.N.C. acknowledges funding from the Leverhulme Trust Early Career Fellowship (ECF-2021-001). We also acknowledge Flanders Environment Agency for providing the publicy available data. P.H. and P.J.H. received funding from the EU Horizon 2020 project eLTER PLUS (Grant Agreement No. 871128). NB and MC were supported by the Serra-Hunter programme (Generalitat de Catalunya). MC was also supported by a Ramón y Cajal contract funded by the Spanish Ministry of Science and Innovation (RYC2020-029829-I). NB was also supported by the H2020 European Research and Innovation action Grant Agreement no. 869226 (DRYvER). The FEHM (Freshwater Ecology, Hydrology and Management) research group (to which NB and MC belong) was funded by the “Agència de Gestió d’Ajuts Universitaris i de Recerca” (AGAUR) at the "Generalitat de Catalunya” (2017SGR1643). BG was funded through the 2017–2018 Belmont Forum and BIODIVERSA joint call for research proposals, under the BiodivScen ERANet COFUND programme, funded through the Spanish State Research Agency (MCI/AEI/FEDER, UE, PCI2018-092986). Peer reviewed

Quantifying the diet composition of apex marine predators such as killer whales (Orcinus orca) is critical to assessing their food web impacts. Yet, with few exceptions, the feeding ecology of these apex predators remains poorly understood. Here, we use our newly validated quantitative fatty acid signature analysis (QFASA) approach on nearly 200 killer whales and over 900 potential prey to model their diets across the 5000 km span of the North Atlantic. Diet estimates show that killer whales mainly consume other whales in the western North Atlantic (Canadian Arctic, Eastern Canada), seals in the mid-North Atlantic (Greenland), and fish in the eastern North Atlantic (Iceland, Faroe Islands, Norway). Nonetheless, diet estimates also varied widely among individuals within most regions. This level of inter-individual feeding variation should be considered for future ecological studies focusing on killer whales in the North Atlantic and other oceans. These estimates reveal remarkable population- and individual-level variation in the trophic ecology of these killer whales, which can help to assess how their predation impacts community and ecosystem dynamics in changing North Atlantic marine ecosystems. This new approach provides researchers with an invaluable tool to study the feeding ecology of oceanic top predators.Connaître en détails la composition du régime alimentaire des grands prédateurs marins tels que les orques (Orcinus orca) est primordial afin d'évaluer leurs impacts sur les écosystèmes. Pourtant, à quelques exceptions près, l'écologie alimentaire de ces super-prédateurs reste mal comprise. Ici, nous utilisons notre nouvelle approche d'analyse quantitative des signatures d'acides gras (QFASA) sur près de 200 orques et plus de 900 proies potentielles pour modéliser leur régime alimentaire à travers l'Atlantique Nord. Les estimations de leurs régimes alimentaires montrent que les orques consomment principalement d'autres baleines dans l'ouest de l'Atlantique Nord (Arctique canadien, Est du Canada), des phoques dans le milieu de l'Atlantique Nord (Groenland) et des poissons dans l'est de l'Atlantique Nord (Islande, îles Féroé, Norvège). Néanmoins, ces estimations varient considérablement d'un individu à l'autre dans la plupart des régions. Cette variation alimentaire importante entre les individus doit être prise en compte dans les futures études écologiques qui s'intéressent aux orques de l'Atlantique Nord et d'ailleurs. Ces estimations révèlent des variations remarquables dans l'écologie trophique des orques tant au niveau des population que de l'individu, ce qui peut aider à évaluer l'impact de leur prédation sur la dynamique des communautés et des écosystèmes dans un contexte de changements climatiques en l'Atlantique Nord. Cette nouvelle approche fournit aux chercheurs un outil inestimable pour étudier l'écologie alimentaire des super-prédateurs océaniques.

In the last three decades, quantitative approaches that rely on organism traits instead of taxonomy have advanced different fields of ecological research through establishing the mechanistic links between environmental drivers, functional traits, and ecosystem functions. A research subfield where trait-based approaches have been frequently used but poorly synthesized is the ecology of seagrasses; marine angiosperms that colonized the ocean 100M YA and today make up productive yet threatened coastal ecosystems globally. Here, we compiled a comprehensive trait-based response-effect framework (TBF) which builds on previous concepts and ideas, including the use of traits for the study of community assembly processes, from dispersal and response to abiotic and biotic factors, to ecosystem function and service provision. We then apply this framework to the global seagrass literature, using a systematic review to identify the strengths, gaps, and opportunities of the field. Seagrass trait research has mostly focused on the effect of environmental drivers on traits, i.e., "environmental filtering" (72%), whereas links between traits and functions are less common (26.9%). Despite the richness of trait-based data available, concepts related to TBFs are rare in the seagrass literature (15% of studies), including the relative importance of neutral and niche assembly processes, or the influence of trait dominance or complementarity in ecosystem function provision. These knowledge gaps indicate ample potential for further research, highlighting the need to understand the links between the unique traits of seagrasses and the ecosystem services they provide. The Euromarine Network funded the initial workshop that led to the development of this manuscript. AM-S was funded by the Leibniz Association as part of the project SEATRAIT and MT was supported by the German Research Foundation (DFG) within the individual Grants Program, project SEAMAC (TE 1046/3-1). AIS was funded by Portuguese national funds through the FCT - Foundation for Science and Technology, I.P., under the project CEECIND/00962/2017 and by FCT/MCTES through the financial support to CESAM (UIDB/50017/2020+UIDP/50017/2020 +LA/P/0094/2020). This study received Portuguese national funds from FCT - Foundation for Science and Technology through projects UIDB/04326/2020, UIDP/04326/2020 and LA/P/0101/2020 of CCMAR. IO was funded by the EU-H2020-MSCA grant n° 752250 (SEAMET). CB was funded by the Åbo Akademi University Foundation Sr and LM was funded by the doctoral network Functional Marine Biodiversity (FunMarBio) at Åbo Akademi University. RS acknowledges the support of the European Union’s Horizon 2020 Research and Innovation Program under the Grant Agreement Number 857251. GP, ED and MR were partially supported by the project Marine Hazard, PON03PE_00203_1 (MUR, Italy); MR was partially supported by a SZN PhD fellowship via the Open University. Peer reviewed