Abstract: This Paper Reports On Consolidated Ground-based Validation Results Of The Atmospheric No2 Data Produced Operationally Since April 2018 By The Tropospheric Monitoring Instrument (Tropomi) On Board Of The Esa/eu Copernicus Sentinel-5 Precursor (S5p) Satellite. Tropospheric, Stratospheric, And Total No2 Column Data From S5p Are Compared To Correlative Measurements Collected From, Respectively, 19 Multi-axis Differential Optical Absorption Spectroscopy (Max-doas), 26 Network For The Detection Of Atmospheric Composition Change (Ndacc) Zenith-scattered-light Doas (Zsl-doas), And 25 Pandonia Global Network (Pgn)/pandora Instruments Distributed Globally. The Validation Methodology Gives Special Care To Minimizing Mismatch Errors Due To Imperfect Spatio-temporal Co-location Of The Satellite And Correlative Data, E.g. By Using Tailored Observation Operators To Account For Differences In Smoothing And In Sampling Of Atmospheric Structures And Variability And Photochemical Modelling To Reduce Diurnal Cycle Effects. Compared To The Ground-based Measurements, S5p Data Show, On Average, (I) A Negative Bias For The Tropospheric Column Data, Of Typically −23 % To −37 % In Clean To Slightly Polluted Conditions But Reaching Values As High As −51 % Over Highly Polluted Areas; (Ii) A Slight Negative Median Difference For The Stratospheric Column Data, Of About −0.2 Pmolec Cm−2, I.e. Approx. −2 % In Summer To −15 % In Winter; And (Iii) A Bias Ranging From Zero To −50 % For The Total Column Data, Found To Depend On The Amplitude Of The Total No2 Column, With Small To Slightly Positive Bias Values For Columns Below 6 Pmolec Cm−2 And Negative Values Above. The Dispersion Between S5p And Correlative Measurements Contains Mostly Random Components, Which Remain Within Mission Requirements For The Stratospheric Column Data (0.5 Pmolec Cm−2) But Exceed Those For The Tropospheric Column Data (0.7 Pmolec Cm−2). While A Part Of The Biases And Dispersion May Be Due To Representativeness Differences Such As Different Area Averaging And Measurement Times, It Is Known That Errors In The S5p Tropospheric Columns Exist Due To Shortcomings In The (Horizontally Coarse) A Priori Profile Representation In The Tm5-mp Chemical Transport Model Used In The S5p Retrieval And, To A Lesser Extent, To The Treatment Of Cloud Effects And Aerosols. Although Considerable Differences (Up To 2 Pmolec Cm−2 And More) Are Observed At Single Ground-pixel Level, The Near-real-time (Nrti) And Offline (Offl) Versions Of The S5p No2 Operational Data Processor Provide Similar No2 Column Values And Validation Results When Globally Averaged, With The Nrti Values Being On Average 0.79 % Larger Than The Offl Values.

Abstract: The conservation of migratory marine species, including pelagic seabirds, is challenging because their movements span vast distances frequently beyond national jurisdictions. Here, we aim to identify important aggregations of seabirds in the North Atlantic to inform ongoing regional conservation efforts. Using tracking, phenology, and population data, we mapped the abundance and diversity of 21 seabird species. This revealed a major hotspot associated with a discrete area of the subpolar frontal zone, used annually by 2.9–5 million seabirds from ≥56 colonies in the Atlantic: the first time this magnitude of seabird concentrations has been documented in the high seas. The hotspot is temporally stable and amenable to site-based conservation and is under consideration as a marine protected area by the OSPAR Commission. Protection could help mitigate current and future threats facing species in the area. Overall, our approach provides an exemplar data-driven pathway for future conservation efforts on the high seas.

Abstract: Within ecophysiological and genetic studies on insects, morphological and physiological traits are commonly assessed and phenotypes are typically obtained from manual measurements on numerous individuals. Manual observations are, however, time consuming, can introduce observer bias and are prone to human error. Here, we contrast results obtained from manual assessment of larval size and thermal tolerance traits in black soldier flies (Hermetia illucens) and houseflies (Musca domestica) that have been acclimated under three different temperature regimes with those obtained automatically using an image analysis software (Noldus EthoVision XT). We found that (i) larval size estimates of both species, obtained by manual weighing or by using the software, were highly correlated, (ii) measures of heat and cold tolerance using manual and automated approaches provided qualitatively similar results, and (iii) by using the software we obtained quantifiable information on stress responses and acclimation effects of potentially higher ecological relevance than the endpoint traits that are typically assessed when manual assessments are used. Based on these findings, we argue that automated assessment of insect stress responses and largescale phenotyping of morphological traits such as size will provide new opportunities within many disciplines where accurate and largescale phenotyping of insects is required.