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AbstractIn the 1960s, influential thinkers defined design as a rational problem-solving approach to deal with the challenges of sustainable human development. In 2009, a design consultant and a business academic selected some of these ideas and successfully branded them with the term “design thinking.” As a result, design thinking has developed into a stream of innovation management research discussing how to innovate faster and better in competitive markets. This article aims to foster a reconsideration of the purposes of design thinking moving forward, in view of the sustainable development challenges intertwined with accelerating innovation in a perpetual economic growth paradigm. To this end, we use a problematization method to challenge innovation management research on design thinking. As part of this method, we first systematically collect and critically analyze the articles in this research stream. We uncover a prominent focus on economic impact, while social and environmental impacts remain largely neglected. To overcome this critical limitation, we integrate design thinking with responsible innovation theorizing. We develop a framework for responsible design thinking, explaining how to apply this approach beyond a private interest and competitive advantage logic, to address sustainable development challenges, such as climate change, resource depletion, poverty, and injustice. The framework contributes to strengthening the practical relevance of design thinking and its theoretical foundations. To catalyze this effort, we propose an agenda for future research.

Background: Human exposure to pesticides is being associated with feminisation for which a decrease of the anogenital distance (AGD) is a sensitive endpoint. Dose addition for the cumulative risk assessment of pesticides in food is considered sufficiently conservative for combinations of compounds with both similar and dissimilar modes of action (MoA).Objective: The present study was designed to test the dose addition hypothesis in a binary mixture of endocrine active compounds with a dissimilar mode of action for the endpoint feminisation.Methods: Compounds were selected from a list of chemicals of which exposure is related to a decrease of the AGD in rats and completed with reference compounds. These chemicals were characterised using specific in vitro transcriptional activation (TA) assays for estrogenic and androgenic properties, leading to a final selection of dienestrol as an ER-agonist and flutamide, linuron, and deltamethrin as AR-antagonists. These compounds were then tested in an in vivo model, i.e. in zebrafish (Danio rerio), using sex ratio in the population as an endpoint in order to confirm their feminising effect and MoA. Ultimately, the fish model was used to test a binary mixture of flutamide and dienestrol.Results: Statistical analysis of the binary mixture of flutamide and dienestrol in the fish sexual development tests (FSDT) with zebrafish supported dose addition. International audience

Riparian forests remain largely understudied in the context of climate change in comparison to other forest ecosystems although they serve multiple socio-ecological functions. We evaluated local adaptation and adaptive potential in Populus nigra L., an emblematic tree species of European riparian forests. We set up a reciprocal transplant experiment and measured 17 structural and functional traits among 10 progenies of two genetically differentiated populations. The populations originated from two separate watersheds differing in climate conditions and a total of 1200 seedlings were grown in 1-m3 mesocosms at both sites for one growing season. Traits measured were related to growth, leaf physiology and xylem water transport. The populations showed similar biomass suggesting no local adaptation for overall performance but displayed distinct trait syndromes and plastic abilities. The southern population primarily adjusted through changes in allocation and leaf water-use efficiency while the northern population primarily adjusted through changes in specific leaf area. Genetic variation within populations was most of the times equal or larger than between populations. This combined with the generally moderate to high heritability values and the observed plasticity suggested significant adaptive potential. Altogether, our findings reveal that although evolution may not lead to obvious differentiation between populations in global performance, integrated multi-trait approaches are highly valuable to shed light on how evolution may shape distinct underlying functional strategies among populations resulting in a similar outcome. International audience

This study evaluates tropospheric columns of methane, carbon monoxide, and ozone in the Arctic simulated by 11 models. The Arctic is warming at nearly 4 times the global average rate, and with changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. Both measurements and modelling of air pollution in the Arctic are difficult, making model validation with local measurements valuable. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). The models were selected as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) report on short-lived climate forcers. This work augments the model–measurement comparisons presented in that report by including a new data source: column-integrated FTIR measurements, whose spatial and temporal footprint is more representative of the free troposphere than in situ and satellite measurements. Mixing ratios of trace gases are modelled at 3-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0–7 km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased low in the tropospheric column, on average by −9.7 % for CH4, −21 % for CO, and −18 % for O3. Results for CH4 are relatively consistent across the 4 years, whereas CO has a maximum negative bias in the spring and minimum in the summer and O3 has a maximum difference centered around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15 % of the model–location comparisons.

No abstracts are to be cited without prior reference to the author. Modelling of fish movement behaviour within a heterogeneous marine environment is a challenging but also key issue for understanding the effect of environmental factors and climatic change on fish processes (growth, distribution, mortality, reproduction). Fish movement models have the capability to encompass the combined effect of environment and empirical knowledge of fish individuals as energy requirements, known preys and predators, swimming capacities into a unified framework (Planque et al., 2011). Following an Individual Based Model (IBM) approach, a fish movement model has been developed to simulate the active movement of adult anchovy in the Bay of Biscay (BoB) in response to the spatio-temporal variations of both biotic and abiotic factors, as well as its internal conditions based on a bioenergetics model

No abstracts are to be cited without prior reference to the author.Deep-sea fisheries in the West of the British Isles have experienced in only two decades many changes regarding the size of the fleets, engine power and fishing gears, fishing grounds and depth while signs of depletion of deep-water stocks and damages to the seabed have led to an increasing number of management rules aiming at ecosystem conservation and at protecting stocks from unsustainable fishing pressure. As deep-water scientific surveys are scarce, abundance indices have been lately estimated using a database containing the catch composition of 29 000 hauls and provided by two organizations from the French fishing industry through a science–industry partnership. Catch composition reflects the combination of the influence of the above factors and the “true” species distribution, itself depending on environmental factors varying in space and time. It is therefore impossible to treat haul-by-haul datasets by standard analyses as they generally require independent observations and normal distributions of continuous variables. Various multivariate analyses and clustering methods were applied in an attempt to characterize the spatio-temporal variability in species abundance and to identify structuring factors and species associations in the catches. Two temporal scales were considered: seasonal and interannual. The relevance of the different methods employed and the information they provide were discussed and results were analysed with stock assessment and management options for those mixed fisheries in perspective.

No abstracts are to be cited without prior reference to the author.A database of tallybooks, from skippers' own logbooks, provided by the French industry involved in deep-water fishing to the west of the British Isles was used to standardise blue ling Landings per Unit of Effort (LPUEs). The data covered the years 1992-2008 with more extensive data for the period 2000-2007. For each haul, landings by species, tow duration, depth and location were reported. Compared to EU logbooks, this database is on a haul by haul basis instead of being aggregated by fishing sub-trips combining hauls from the same day, ICES rectangle and gear. Moreover, it includes depth, which is a major factor for catch rates in deepwater fisheries. LPUEs were estimated from Generalised Additive Models (GAMs) with depth, vessel, statistical rectangle and zone by year as explanatory variables. Owing to the statistical distribution of landings rates, landings were modelled by a Tweedie distribution, which is a compound Poisson distribution and allows to handle data with many zeros, as it is typical for catch data. In order to investigate how to reliably track stock trends, LPUEs were estimated in five regions for different subsets including or not the spawning season, when blue ling aggregates, or considering tows where blue ling was only a bycatch. The results based on the tallybook data indicated that blue ling LPUEs have been mainly stable over the past decade. This is consistent with stable mean length in the landings. Haul by haul data are suitable to derive abundance indices for deep-water fisheries assessment.

Under the EU Air Quality Directive (AQD) 2008/50/EC member states are required to undertake routine monitoring of PM2.5 composition at background stations. The AQD states for PM2.5 speciation this should include at least: nitrate (NO3−), sulfate (SO42−), chloride (Cl−), ammonium (NH4+), sodium (Na+), potassium (K+), magnesium (Mg2+), calcium (Ca2+), elemental carbon (EC) and organic carbon (OC). Until 2017, it was the responsibility of each country to determine the methodology used to report the composition for the inorganic components of PM2.5. In August 2017 a European standard method of measurement of PM2.5 inorganic chemical components (NO3−, SO42−, Cl−, NH4+, Na+, K+, Mg2+, Ca2+) as deposited on filters (EN16913:2017) was published. From August 2019 this then became the European standard method. This filter method is labour-intensive and provides limited time resolution and is prone to losses of volatile compounds. There is therefore increasing interest in the use of alternative automated methods. For example, the UK reports hourly PM2.5 chemical composition using the Monitor for AeRosols and Gases in Ambient air (MARGA, Metrohm, NL). This study is a pre-assessment review of available data to demonstrate if or to what extent equivalence is possible using either the MARGA or other available automatic methods, including the Aerosol Chemical Speciation Monitor (ACSM, Aerodyne Research Inc. US) and the Ambient Ion Monitor (AIM, URG, US). To demonstrate equivalence three objectives were to be met. The first two objectives focused on data capture and were met by all three instruments. The third objective was to have less than a 50% expanded uncertainty compared to the reference method for each species. Analysis of this objective was carried out using existing paired datasets available from different regions around the world. It was found that the MARGA (2006–2019 model) had the potential to demonstrate equivalence for all species in the standard, though it was only through a combination of case studies that it passed uncertainty criteria. The ACSM has the potential to demonstrate equivalence for NH4+, SO42−, and in some conditions NO3−, but did not for Cl− due to its inability to quantify refractory aerosol such as sea salt. The AIM has the potential for NH4+, NO3−, SO42−, Cl− and Mg2+. Future investigations are required to determine if the AIM could be optimised to meet the expanded uncertainty criterion for Na+, K+ and Ca2+. The recommendation is that a second stage to demonstrate equivalence is required which would include both laboratory and field studies of the three candidate methods and any other technologies identified with the potential to report the required species. The authors would like to thank the UK Environment Agency who funded this study. The measurements in this study were funded by the following bodies: - All the UK datasets were funded by UK Environment Agency under the UK Eutrophying and Acidifying Pollutant Network and the UKs Particle Numbers and Concentrations Network. The Auchencorth Moss measurements are supported by NERC UK Status, change and Projections of the Environment UK-SCaPE (NE/R016429/1). - The Revin fieldsite is coordinated by IMT Nord Europe in collaboration with the regional monitoring network (Atmo Grand-Est) and the National Reference Laboratory for Air Quality Monitoring (LCSQA) and funded by the French Ministry of Environment. ACSM measurements were supported by the Labex CaPPA project, which is funded by the French National Research Agency (ANR) through the PIA (Programme d’Investissement d’Avenir) under contract ANR-11-LABX-0005-01, and were part of the COST COLOSSAL Action CA16109. - Measurements in Barcelona Palau Reial were funded by the Spanish Ministry of Science and Innovation through CAIAC project (PID2019-108990RB-I00) and FEDER funds, through EQC2018-004598-P. - Measurements at the Mace Head Atmospheric Research Station are supported by the EPA-Ireland and the Department of Environment, Climate and Communications. - The Germany Federal Environment Agency (UBA) provided the financial support of this study and the deployment of the MARGA at the research station Melpitz under contracts No: 351 01 093 and 351 01 070. - The data from Kumpula was supported by the Academy of Finland as part of the Centre of Excellence program (project no 1118615). - US EPA gratefully acknowledges the contributions of Battelle and Wood (formerly Amec, Foster Wheeler) to the Research Triangle Park study. - The data from the San Pietro Capofiume was funded by the PEGASOS EU FP7 project. Peer reviewed