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This data set describes the population dynamics of Wilson's Storm Petrels (Oceanites oceanicus) at King George Island (Isla 25 de Mayo, Antarctica) over a forty year period (1978 – 2020). It includes all available data on Wilson's Storm Petrels from two colonies: around the Argentinian Base Carlini (62°14′S, 58°40′W; CA, formerly called Base Jubany) and the Henryk Arctowski Polish Antarctic Station (62°09′S, 58°27′W; HA). Data on population productivity (number of nests, eggs, chicks and fledglings) was collected by regular visits to the colonies and searching for nest burrows, or monitoring of the egg or chick if found. Data on adult abundance and estimated age categories (i.e., presence of foot spots; Quillfeldt et al. (2000, doi:10.1007/s003000000167) were collected at CA by using the same size mistnet every study year in the same location within the breeding colony. Chicks were measured regularly (varying intervals depending on the study) at both CA and HA. Chick tarsus was measured using callipers (vernier or digital depending on the study year) to the nearest 0.1 mm, chick wing length was measured using wing rulers to the nearest 1 mm, and chick body mass was measured using mechanical or digital scales depending on the study year to the nearest 0.1 g. Chick growth rates were calculated based on the linear growth period following Ausems et al. (2020, doi:10.1016/j.scitotenv.2020.138768). Chick food loads (g) were recorded at CA and determined based on changes in chick body mass on consecutive days (Gladbach et al. (2009, doi:10.1007/s00300-009-0628-z); Kuepper et al. (2018, doi:10.1016/j.cbpa.2018.06.018). This study was further supported by the Erasmus+ programm and thee German Academic Exchange Service (DAAD)

Misurazioni orarie SMPS per Malin Head per l'anno 2019 Clima Chimica e Climate Change Network (AC3) Stazione: Testa di Malin (MLH) Le coordinate: 55º 22′ N, 7º 20′ O ALTITUDINE: 22 m s.l.m. Altezza di misura: 5 m Tipo di sito: fondo rurale Strumentazione: PALAS U200 SMPS Gamma di dati: 8-1200 nm (l'intestazione determina l'intervallo inferiore) Unità:[1/cm³] Tempo di consegna: TERMINI E CONDIZIONI Informazioni di base: Malin Head è l'attuale stazione meteorologica sinottica Met Eireann. Numero di serie dello strumento: Informazioni di calibrazione: Calibrato ogni 2 anni Погодинний вимірювання SMPS для Малін Голова на 2019 рік Хімія атмосфери та мережа змін клімату (AC3) Станція метро: Малін Голова (MLH) Географічні координати міста: 55° 22′ N, 7° 20′ ВТ ВИСОТА ПІДЙОМУ: 22 м с. Висота вимірювання: 5 м Тип сайту: сільський фон Вимірювальні прилади: ПАЛАС U200 SMPS Діапазон даних: 8-1200 нм (заголовок визначає нижній діапазон) Одиниці:[1/см³] Час роботи: СТВОРЕННЯ UTC Довідкова інформація: Малін Хед - існуюча синоптична метеорологічна станція Met Eireann. Серійний номер приладу: Інформація про калібрування: Калібрується кожні 2 роки Stundas SMPS mērījumi Malin Head 2019. gadam Atmosfēras ķīmijas un klimata pārmaiņu tīkls (AC3) Atrašanās vieta: Malin Head (MLH) Koordinātas: 55° 22′ ZIEMEĻU PLATUMA, 7° 20′ RIETUMU GARUMA, AUGSTUMS VIRS JŪRAS LĪMEŅA: 22 m asl Mērīšanas augstums: 5 m Vietnes tips: lauku vide Instrumenti: PALAS U200 SMPS Datu diapazons: 8–1200 nm (virsma nosaka zemāko diapazonu) Vienības:[1/cm³] Laiks: UTC UTC Vispārīga informācija: Malin Head ir esošā Met Eireann sinoptiskās meteoroloģijas stacija. Instrumenta sērijas numurs: Kalibrēšanas informācija: Kalibrēts ik pēc 2 gadiem Kejl fis-siegħa tal-SMPS għal Malin Head għas-sena 2019 Netwerk dwar il-Kimika u t-Tibdil fil-Klima (AC3) Stazzjon: Ras ta’ Malin (MLH) Koordinati: 55° 22′ N, 7° 20′ W ALTITUDNI: 22 m asl L-għoli tal-kejl: 5 m Tip ta’ sit: sfond rurali Strumentazzjoni: PALAS U200 SMPS Firxa ta’ dejta: 8–1200 nm (l-intestatura tiddetermina l-firxa aktar baxxa) Unitajiet:[1/cm³] Ħin: UTC Informazzjoni ta’ sfond: Malin Head huwa l-istazzjon eżistenti tal-meteoroloġija sinottika Met Eireann. Numru tas-serje tal-istrument: Informazzjoni ta’ kalibrazzjoni: Kalibrat kull sentejn Valandiniai SMPS matavimai Malin Head 2019 metams Atmosferos chemijos ir klimato kaitos tinklas (AC3) Stotelės: Malin Head (MLH) Koordinatės: 55° 22′ ŠIAURĖS PLATUMOS, 7° 20′ VAKARŲ ILGUMOS AUKŠTIS: 22 m asl Matavimo aukštis: 5 m Svetainės tipas: kaimo fonas Instrumentai: PALAS U200 SMPS Duomenų diapazonas: 8–1200 nm (antraštė nustato žemesnį diapazoną) Vienetų skaičius:[1/cm³] Laikas: UTC Pagrindinė informacija: Malin Head yra esama Met Eireann sinoptinės meteorologijos stotis. Priemonės serijos numeris: Kalibravimo informacija: Kalibruojama kas 2 metus Mediciones por hora de SMPS para Malin Head para el año 2019 Red de Química y Cambio Climático de la Atmósfera (AC3) De la estación: Malin Head (MLH) Coordenadas: 55.º 22′ N, 7.º 20′ O ALTURA: 22 m asl Altura de medición: 5 m Tipo de sitio: fondo rural Instrumentación: PALAS U200 SMPS Rango de datos: 8-1200 nm (la cabecera determina el rango inferior) Unidades:[1/cm³] Hora: UTC Información de antecedentes: Malin Head es la estación de meteorología sinóptica Met Eireann existente. Número de serie del instrumento: Información de calibración: Calibrado cada 2 años Medições horárias SMPS para Malin Head para o ano 2019 Rede de Química da Atmosfera e Alterações Climáticas (AC3) Estação: Cabeça de Malin (MLH) Coordenadas: 55.º 22′ N, 7.º 20′ W ALTITUDE: 22 m/sl Altura da medição: 5 m Tipo do site: contexto rural Instrumentação: PALAS U200 SMPS Gama de dados: 8-1200 nm (o cabeçalho determina o intervalo mais baixo) Unidades:[1/cm³] Hora: UTC Informações gerais: Malin Head é a estação de meteorologia sinóptica Met Eireann existente. Número de série do instrumento: Informações de calibração: Calibrado a cada 2 anos SMPS-metingen per uur voor Malin Head voor het jaar 2019 Netwerk van atmosfeerchemie en klimaatverandering (AC3) Locatie: Malin Hoofd (MLH) Coördinaten: 55° 22′ NOORDERBREEDTE, 7° 20′ WL HOOGTE: 22 m asl De hoogte van de meting: 5 m Soort site: landelijke achtergrond Instrumentatie: PALAS U200 SMPS Gegevensbereik: 8-1200 nm (header bepaalt een lager bereik) Eenheden:[1/cm³] Tijd: UTC Achtergrondinformatie: Malin Head is het bestaande synoptische meteorologisch station Met Eireann. Instrument serienummer: Kalibratie info: Om de 2 jaar gekalibreerd Почасови SMPS измервания за Malin Head за 2019 г. Мрежа за химия на атмосферата и изменение на климата (AC3) Станция: Malin Head (MLH) Координати: 55° 22′ С.Ш., 7° 20′ З.Д. ВИСОЧИНА:22 m asl Височина на измерване:5 м Тип на сайта:произход на селските райони Инструментална апаратура:PALAS U200 SMPS Обхват на данните:8—1200 nm (главата определя долен обхват) Единици:[1/cm³] Време:UTC Основна информация: Malin Head е съществуващата метеорологична станция Met Eireann. Сериен номер на инструмента: Информация за калибриране: Калибрирани на всеки 2 години Mesures horaires SMPS pour Malin Head pour l’année 2019 Réseau de chimie de l’atmosphère et du changement climatique (AC3) Station: Tête de Malin (MLH) Coordonnées: 55° 22′ N, 7° 20′ O ALTITUDE:22 m asl Hauteur de mesure:5 m Type de site:milieu rural Instrumentation:PALAS U200 SMPS Plage de données:8-1200 nm (l’en-tête détermine la plage inférieure) Unités:[1/cm³] Temps:UTC Informations générales: Malin Head est la station météorologique synoptique de Met Eireann. Numéro de série de l’instrument: Informations d’étalonnage: Calibré tous les 2 ans

The main objective of this Sternfahrt-8, from 10th to 16th September 2021, was to assess the temporal variance of oceanographic real time data in the Elbe influence area of the German Bight (North Sea). Therefore, the participating Ships should repeat the same tracks for four days (see map). One ship (RV Uthörn) covered the western part between Cuxhaven and Heligoland, the second ship (RV Littorina) went to the northern part between Heligoland and Büsum and the third vessel (RV Ludwig Prandtl) should have covered the middle part of the study area, but due to vandalism damage it could not participate on the cruise. During the whole cruise chemical and physical data were recorded continuously along the tracks. Additionally, discrete water samples were taken on six stations along the way for further analysis in the laboratory. The latter data is not included in the present dataset, and can be accessed via https://doi.pangaea.de/10.1594/PANGAEA.963455. For more information about the MOSES campaign and the "Sternfahrten" cruises see article cited in references.

Vegetation surveys were carried out in four different study areas in the Sakha Republic, Russia: in the mountainous region of the Verkhoyansk Range within the Oymyakonsky and Tomponsky District (Event EN21-201 - EN21-219), and in three lowland regions of Central Yakutia within the Churapchinsky, Tattinsky and the Megino-Kangalassky District (Event EN21220 - EN21264). The study area is located within the boreal forest biome that is underlain by permafrost soils. The aim was to record the projective ground vegetation in different boreal forest types studied during the RU-Land_2021_Yakutia summer field campaign in August and September 2021.Ground vegetation was surveyed for different vegetation types within a circular forest plot of 15m radius. Depending on the heterogeneity of the forest plot, multiple vegetation types (VA, VB, or VC) were chosen for the survey. The assignment of a vegetation type is always unique to a site. Their cover on the circular forest plot was recorded in percent.In total, 84 vegetation types at 58 forest plots were assessed. All data were collected by scientists form the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) Germany, the University of Potsdam Germany, and the North-Easter Federal University of Yakutsk (NEFU) Russia.

Species distribution models (SDMs) are becoming an important tool for marine conservation and management. Yet while there is an increasing diversity and volume of marine biodiversity data for training SDMs, little practical guidance is available on how to leverage distinct data types to build robust models. We explored the effect of different data types on the fit, performance and predictive ability of SDMs by comparing models trained with four data types for a heavily exploited pelagic fish, the blue shark (Prionace glauca), in the Northwest Atlantic: two fishery-dependent (conventional mark-recapture tags, fisheries observer records) and two fishery-independent (satellite-linked electronic tags, pop-up archival tags). We found that all four data types can result in robust models, but differences among spatial predictions highlighted the need to consider ecological realism in model selection and interpretation regardless of data type. Differences among models were primarily attributed to biases in how each data type, and the associated representation of absences, sampled the environment and summarized the resulting species distributions. Outputs from model ensembles and a model trained on all pooled data both proved effective for combining inferences across data types and provided more ecologically realistic predictions than individual models. Our results provide valuable guidance for practitioners developing SDMs. With increasing access to diverse data sources, future work should further develop truly integrative modeling approaches that can explicitly leverage strengths of individual data types while statistically accounting for limitations, such as sampling biases.  Please see the README document ("README.md") and the accompanying published article: Braun, C. D., M. C. Arostegui, N. Farchadi, M. Alexander, P. Afonso, A. Allyn, S. J. Bograd, S. Brodie, D. P. Crear, E. F. Culhane, T. H. Curtis, E. L. Hazen, A. Kerney, N. Lezama-Ochoa, K. E. Mills, D. Pugh, N. Queiroz, J. D. Scott, G. B. Skomal, D. W. Sims, S. R. Thorrold, H. Welch, R. Young-Morse, R. Lewison. In press. Building use-inspired species distribution models: using multiple data types to examine and improve model performance. Ecological Applications. Accepted. DOI: < article DOI will be added when it is assigned >

This data was collected as a part of a mesocosm study to investigate the ecosystem impacts of ocean alkalinity enhancement, within the EU H2020 OceanNETs project. Nine mesocosms were deployed in Taliarte Harbour (Gran Canaria, Spain) and were regularly sampled using integrated water samplers between 10th September-25th October 2021. A gradient design was used in this experiment with a total of nine different alkalinity concentrations. Seawater alkalinity ranged between ambient (0 µeq kg-1 added alkalinity, OAE0) and 2400 µeq kg-1 additional alkalinity (OAE2400). The alkalinity levels increased in equal intervals of 300 µeq kg-1 across nine mesocosms (OAE0, OAE300, OAE600, OAE900, OAE1200, OAE1500, OAE1800, OAE2100, OAE2400). This data set contains metazoan zooplankton biomass (µgC per L) from these nine mesocosms. Biomass was calculated based on zooplankton abundances transformed using carbon mass conversion factors. Metazoan zooplankton were sampled with apstein net (ø17cm, mesh size 55µm, 64.06285L) hauls taken every two days (except for days 5 and 9). Zooplankton were size fractioned and assessed in the correspondent size class (small: 55-200µm; medium: 200-500µm; large: 500µm-3mm). Within each size class, all organisms were counted and identified to the lowest possible taxonomic level, and developmental stages were differentiated where possible. Zooplankton abundances (individuals per L) converted to carbon biomass (µgC per L) using biomass conversion factors. Conversion factors are obtained from different sources (Sanchez et al. (in prep)). Briefly: i) metazoan zooplankton functional groups were sampled and measured for carbon biomass using an elemental analyser at specific points throughout the experiment, ii) individual zooplankton were photographed, measured, and their biovolumes and carbon masses derived using standard conversions cited in the literature, iii) zooplankton conversion factors from KOSMOS Gran Canaria 2019 (https://doi.pangaea.de/10.1594/PANGAEA.971765). The experiment, which lasted 33 days, was divided into four response phases (see Sánchez et al. (in prep)): i) pretreatment (days 1 to 4, treatment was implemented on day 4), ii) immediate (days 5-10), iii) shorter term (days 11-22), iv) longer term (days 23 to 33). This data set is associated to the submission by Paul et al. (in review) (https://doi.pangaea.de/10.1594/PANGAEA.966941), so we refer to this data set for basic parameters like water temperature, salinity, pH and carbonate chemistry, to avoid repetition.

# Can niche plasticity mediate species persistence under ocean acidification? [https://doi.org/10.5061/dryad.x0k6djhtq](https://doi.org/10.5061/dryad.x0k6djhtq) This dataset originates from a study investigating the impact of ocean acidification on a temperate rocky reef fish assemblage using natural CO2 vents as analogues. The dataset covers various niche dimensions, including trophic, habitat, and behavioural niches. The study focused on how fish niches are modified in response to ocean acidification, assessing changes in breadth, shift, and overlap with other species between the acidified site and the control site. ## Description of the data and file structure #### Raw\_single\_niche\_data The “*Raw_single_niche_data*” dataset consists of seven spreadsheets, each sharing two essential columns: 'group' and 'community'. These columns are crucial for subsequent analysis using the SIBER framework. **group** = species * Common = common triplefin, *Forsterygion lapillum* * Yaldwyn = Yaldwyn’s triplefin, *Notoclinops yaldwyni* * Blue_eyed = blue-eyed triplefin, *Notoclinops segmentatus* * Blenny = crested blenny, *Parablennius laticlavius* **community** = treatment * C = control * V = CO2 vents **Description of the seven spreadsheets:** 1. **Isotopes -** the dataset includes ratios of 13C/12C and 15N/14N expressed in the conventional δ notation as parts per thousand deviation from international standards. Stable isotopes were derived from a total of 251 fishes collected across three years of sampling. iso1= δ13C iso2= δ15N 2. **Stomach volumetric** - The dataset includes estimated volumetric measures of stomach contents, where the volume contribution of each prey category relative to the total stomach content (100%) was visually estimated. Data were collected between 2018 and 2019. The stomach content was analysed with this method for common triplefin, Yaldwyn's triplefin, blue eyed triplefin and crested blenny. There are 19 prey categories. 3. **Stomach count** - All prey items were counted in 10 prey categories: copepods, ostracods, polychaetes, amphipods, gastropods, bivalves, tanaids, mites, isopods , and others. Digested items that were not identifiable were excluded from the analysis. The stomach content was analysed with this method for common triplefin, Yaldwyn's triplefin and blue eyed triplefin. 4. **Stomach biomass -** The dataset includes calculated biomass derived from the mass of prey subsamples within each category, multiplied by their count. 5. **Habitat** - The microhabitat occupied and habitat orientation (horizontal, angled and vertical) was recorded using free roaming visual surveys on SCUBA (February 2018). *Microhabitat types:* t. = turf algae <10 cm in height ca. = erect calcareous algae cca. = crustose coralline algae b. = bare rocky substratum sp. = encrusting fleshy green algae cobble. = cobbles (~0.5–2 cm in diameter) *Type of surface orientation:* hor = horizontal angle = angled vert = vertical 6. **Behaviour** - Behavioural variables quantified from underwater footage and expressed as rates per minute. The behaviours are: swimming, jumping, feeding, attacking and fleeing from an attack. 7. **Aquarium**: Data from an aquarium experiment involving *Forsterygion lapillum and Notoclinops yaldwyni*, showing the proportion of time spent in available habitat types to assess habitat preference in controlled conditions. Time in each habitat type and spent in activity was derived from video recordings of 10 minutes and expressed as a proportion of total observation time. Common = common triplefin, *Forsterygion lapillum* Yaldwyn = Yaldwyn’s triplefin, *Notoclinops yaldwyni* Common.c = common triplefin in presence of Yaldwyn’s triplefin Yaldwyn.c = Yaldwyn’s triplefin in presence of common triplefin turf.horizontal = time spent on horizontal turf substratum bare.horizontal = time spent on horizontal bare substratum turf.vertical = time spent on vertical turf substratum bottom = time spent on the bottom of the tank swimming = time spent swimming aquarium.wall = time spent on the walls of the tank switches = numbers of changes between habitats #### Unified\_overlap\_dataset The *“Unified_overlap_dataset”* consists of ten spreadsheets, each sharing “id”, “year”, “location” and “species “column (with few exceptions detailed). These first columns need to be factors for analysis using the Unified overlap framework. We used the R scripts provided in the original study ([Geange et al, 2011](https://doi.org/10.1111/j.2041-210X.2010.00070.x)), as detailed in the manuscript. Data for control and vents are in separate data sheets, with C = control and V = vent. **Id**: sample number **Year:** year the data were collected **Location:** North (n) or South (s), site location **Species**: fish species * Common = common triplefin, *Forsterygion lapillum* * Yaldwyn = Yaldwyn’s triplefin, *Notoclinops yaldwyni* * Blue_eyed = blue-eyed triplefin, *Notoclinops segmentatus* * Blenny = crested blenny, *Parablennius laticlavius* We used the same data as per previous section. **Isotopes C and Isotopes V:** * iso1= δ13C * iso2= δ15N **Diet V and Diet C:** For **stomach content**: we used only volumetric stomach content data as inclusive of all species of interest. It is not raw data, but we used the reduced dimension obtained from nonmetric multidimensional scaling (nMDS), thus the 2 columns resulting from this analysis are vol1 and vol2. Raw data are in the datasheet **Stomach volumetric** in the “*Raw_single_niche_data*” dataset. **Habitat association C and Habitat association V** / **Habitat - C and Habitat - V** For **Habitat association**, the columns are id, species, habitat and position. The habitat association for each species is categorical based on habitat occupied and position (e.g., turf - vertical). Information for Crested blenny were extracted from the behavioural video recordings (with each video being a replicate). The dataset is then linked to **Habitat cover** in both control (C) and vent (V) sites to determine the choice of the habitat based on habitat availability. Therefore, the habitat cover only presents the percentage cover of each habitat type at control and vent. *Habitat:* turf = turf algae <10 cm in height ca = erect calcareous algae cca = crustose coralline algae barren = bare rocky substratum sp = encrusting fleshy green algae cobble = cobbles (~0.5–2 cm in diameter) sand = sand *Position:* hor = horizontal angle = angled vert = vertical **Behaviour C and Behaviour V**: Behavioural variables quantified from underwater footage and expressed as rates per minute. The behaviours are: swimming, jumping, feeding, attacking and fleeing from an attack. Reference: Geange, S. W., Pledger, S., Burns, K. C., & Shima, J. S. (2011). A unified analysis of niche overlap incorporating data of different types. *Methods in Ecology and Evolution*, 2(2), 175-184. [https://doi.org/10.1111/j.2041-210X.2010.00070.x](https://doi.org/10.1111/j.2041-210X.2010.00070.x) We used a small hand net and a mixture of ethanol and clove oil to collect the four species of interest (Forsterygion lapillum, Notoclinops yaldwyni, Notoclinops segmentatus and Parablennius laticlavius) at both control and vent sites over four years. For stable isotope analysis, white muscle tissue was extracted from each fish and oven-dried at 60 °C. The dried tissue was subsequently ground using a ball mill. Powdered muscle tissue from each fish was individually weighed into tin capsules and analysed for stable δ 15N and δ13C isotopes. Samples were combusted in an elemental analyser (EuroVector, EuroEA) coupled to a mass spectrometer (Nu Instruments Horizon) at the University of Adelaide. We then analysed the isotopic niche in SIBER. For stomach content analysis the entire gut was extracted from each fish. Using a stereomicroscope, for count and biomass, all prey items in the stomach were counted first. For each prey category, well-preserved individuals were photographed and their mass was calculated based on length and width. The average mass per individual for each category was then multiplied by the count to determine total prey biomass. For the volumetric method, the volume contribution of each prey category relative to the total stomach content was visually estimated (algae were accounted for). Digested items that were not identifiable were excluded from the analysis. Each stomach content dataset was reduced to two dimensions with non-metric multidimensional scaling (nMDS) to be then analysed in SIBER. To assess habitat choice, visual surveys were conducted on SCUBA, to record the microhabitat type and orientation occupied by Forsterygion lapillum, Notoclinops yaldwyni and Notoclinops segmentatus. The resulting dataset comprised a total of 17 distinct combinations of habitat types and surface orientations. The dataset was simplified to two dimensions using correspondence analysis (CA) for subsequent SIBER analysis. Fish behaviour was assessed using GoPro cameras both in situ and during controlled aquarium experiments. In the field, recordings lasted 30 minutes across 4 days, with analysis conducted using VLC. Initial acclimation and periodic intervals (10 minutes every 5 minutes) were excluded from analysis. In controlled aquarium settings, individuals of Forsterygion lapillum and Notoclinops yaldwyni were observed both in isolation and paired. Their habitat preference, surface orientation, and activity levels were recorded for 10 minutes to assess behaviour independent of external influences. Both datasets were dimensionally reduced for analysis in SIBER: non-metric multidimensional scaling (nMDS) was applied to the in situ behavioral data, while principal component analysis (PCA) was used for the aquarium experiments. Unified analysis of niche overlap We quantified the local realised niche space for each fish species at control and vent along the four niche classes, adapting the data as follows: isotopes (continuous data): raw data. stomach content (continuous data): reduced dimension from the volumetric measure of the previous step. habitat association (elective score): habitat and orientation preference linked to Manly’s Alpha association matrix. behaviour (continuous data): raw data. Global change stressors can modify ecological niches of species, and hence alter ecological interactions within communities and food webs. Yet, some species might take advantage of a fast-changing environment, and allow species with high niche plasticity to thrive under climate change. We used natural CO2 vents to test the effects of ocean acidification on niche modifications of a temperate rocky reef fish assemblage. We quantified three ecological niche traits (overlap, shift, and breadth) across three key niche dimensions (trophic, habitat, and behavioural). Only one species increased its niche width along multiple niche dimensions (trophic and behavioural), shifted its niche in the remaining (habitat), and was the only species to experience a highly increased density (i.e. doubling) at vents. The other three species that showed slightly increased or declining densities at vents only displayed a niche width increase in one (habitat niche) out of seven niche metrics considered. This niche modification was likely in response to habitat simplification (transition to a system dominated by turf algae) under ocean acidification. We further show that at the vents, the less abundant fishes have a negligible competitive impact on the most abundant and common species. Hence, this species appears to expand its niche space overlapping with other species, consequently leading to lower abundances of the latter under elevated CO2. We conclude that niche plasticity across multiple dimensions could be a potential adaptation in fishes to benefit from a changing environment in a high-CO2 world. 

Kejl ta’ CO2 fis-siegħa għal Mace Head għas-sena 2019, SN41 Netwerk dwar il-Kimika u t-Tibdil fil-Klima (AC3) KODIĊI TAL-ISTAZZJON: MHD ISEM L-ISTAZZJON: Ras Mace KATEGORIJA TA’ OSSERVAZZJONI: Osservazzjoni tat-teħid ta’ kampjuni tal-arja fi pjattaforma Stazzjonarja PAJJIŻ/TERRITORJU: L-Irlanda L-għoli tal-kejl: 24.0 m AGL ALTITUDNI: 5 m asl LATITUDNI: 53.3261 N LONĠITUDNI: —9.9036 E TIP TA’ SIT: sfond rurali STRUMENTAZZJONI: PICARRO G1301 FIRXA TA’ DEJTA: CO2 SKALA TA’ KEJL: GĦAD IRID JIĠI KKONFERMAT PERJODU TA’ KOPERTURA: 2019–01–01 00:00 2019–09–03 00:00 INTERVALL TA’ ĦIN: kull siegħa UNITÀ TA’ KEJL: nmol.mol-√ METODU TA’ KEJL: Spettrometru ta’ ringdown tal-kavità (ICOS strument Id 41) TIP TA’ PRODOTT TA’ DEJTA: L1 TIP TA’ TEĦID TA’ KAMPJUNI: kontinwu POLITIKA DWAR ID-DEJTA: Id-DATA tal-ICOs hija liċenzjata taħt liċenzja internazzjonali ta’ Creative Commons Attribution 4.0 (http://creativecommons.org/licenses/by/4.0/.The: Il-liċenzja tad-data ICOS hija deskritta fuq https://data.icos-cp.eu/licence) Почасови измервания на CO2 за Mace Head за 2019 г., SN41 Мрежа за химия на атмосферата и изменение на климата (AC3) КОД НА СТАНЦИЯТА: MHD ИМЕ НА СТАНЦИЯТА: Мейс Хед КАТЕГОРИЯ НА НАБЛЮДЕНИЕ: Наблюдение на вземането на проби от въздуха на стационарна платформа ДЪРЖАВА/ТЕРИТОРИЯ: Ирландия Височина на измерване: 24,0 м AGL ВИСОЧИНА: 5 m asl ГЕОГРАФСКА ШИРИНА: 53.3261 N ДЪЛЖИНА: —9.9036 Д ТИП НА САЙТА: произход на селските райони ИНСТРУМЕНТАЛНА АПАРАТУРА: PICARRO G1301 ОБХВАТ НА ДАННИТЕ: CO2 ИЗМЕРВАТЕЛНА СКАЛА: ОЧАКВА СЕ ПОТВЪРЖДЕНИЕ ОБХВАЩАЩ ПЕРИОД: 2019—01—01 00:00 2019—09—03 00:00 ВРЕМЕВИ ИНТЕРВАЛ: почасово МЕРНА ЕДИНИЦА: nmol.mol-Ω МЕТОД НА ИЗМЕРВАНЕ: Спектрометър за пръстен на кухината (ICOS инструмент Id 41) ТИП НА ПРОДУКТА: L1 ТИП НА ВЗЕМАНЕ НА ПРОБИ: непрекъснато ПОЛИТИКА ЗА ДАННИТЕ: ICOs DATA е лицензирана под международен лиценз Creative Commons Attribution 4.0 (http://creativecommons.org/licenses/by/4.0/.The лицензът за данни на ICOS е описан на https://data.icos-cp.eu/licence) Mediciones horarias de CO2 para Mace Head para el año 2019, SN41 Red de Química y Cambio Climático de la Atmósfera (AC3) CÓDIGO DE ESTACIÓN: MHD NOMBRE DE LA ESTACIÓN: Cabeza de Mace CATEGORÍA DE OBSERVACIÓN: Observación de muestreo de aire en una plataforma estacionaria PAÍS/TERRITORIO: Irlanda Altura de medición: 24,0 m AGL ALTURA: 5 m asl LA LATITUD: 53.3261 N LONGITUD: —9.9036 E TIPO DE SITIO: fondo rural INSTRUMENTACIÓN: PICARRO G1301 RANGO DE DATOS: CO2 ESCALA DE MEDICIÓN: PENDIENTE DE CONFIRMACIÓN PERÍODO DE COBERTURA: 2019-01-01 00:00 2019-09-03 00:00 INTERVALO DE TIEMPO: por hora UNIDAD DE MEDIDA: nmol.mol... MÉTODO DE MEDICIÓN: Espectrómetro de anillo de cavidad (instrumentoICOS Id 41) TIPO DE PRODUCTO DE DATOS: L1 TIPO DE MUESTREO: continuo POLÍTICA DE DATOS: ICOs DATA está licenciado bajo una licencia internacional Creative Commons Attribution 4.0 (http://creativecommons.org/licenses/by/4.0/.The la licencia de datos ICOS se describe en https://data.icos-cp.eu/licence) Mesures horaires de CO2 pour Mace Head pour l’année 2019, SN41 Réseau de chimie de l’atmosphère et du changement climatique (AC3) CODE DE LA STATION: MHD NOM DE LA STATION: Tête de Mace CATÉGORIE D’OBSERVATION: Observation d’échantillonnage d’air sur une plate-forme stationnaire PAYS/TERRITOIRE: Irlande Hauteur de mesure: 24,0 m AGL ALTITUDE: 5 m asl LATITUDE: 53.3261 N LONGITUDE: —9.9036 E TYPE DE SITE: milieu rural INSTRUMENTATION: PICARRO G1301 PLAGE DE DONNÉES: CO2 ÉCHELLE DE MESURE: À CONFIRMER PÉRIODE DE COUVERTURE: 2019-01-01 00:00 2019-09-03 00:00 INTERVALLE DE TEMPS: heure par heure UNITÉ DE MESURE: nmol.mol-’ MÉTHODE DE MESURE: Spectromètre d’anneau de cavité (instrument ICOS Id 41) TYPE DE PRODUIT DE DONNÉES: L1 TYPE D’ÉCHANTILLONNAGE: continu POLITIQUE DES DONNÉES: ICOs DATA est sous licence Creative Commons Attribution 4.0 (http://creativecommons.org/licenses/by/4.0/.The la licence de données ICOS est décrite sur https://data.icos-cp.eu/licence) Medições horárias de CO2 para Mace Head para o ano 2019, SN41 Rede de Química da Atmosfera e Alterações Climáticas (AC3) CÓDIGO DA ESTAÇÃO: MHD NOME DA ESTAÇÃO: Cabeça de mace CATEGORIA DE OBSERVAÇÃO: Observação da amostragem do ar numa plataforma estacionária PAÍS/TERRITÓRIO: Irlanda Altura da medição: 24,0 milhões de AGL ALTITUDE: 5 m de argila LATITUDE: 53.3261 N LONGITUDE: —9.9036 E TIPO DE SÍTIO: contexto rural INSTRUMENTAÇÃO: PICARRO G1301 GAMA DE DADOS: CO2 ESCALA DE MEDIÇÃO: A CONFIRMAR PERÍODO DE COBERTURA: 2019-01-01 00:00 2019-09-03 00:00 INTERVALO DE TEMPO: horário UNIDADE DE MEDIDA: nmol.mol— MÉTODO DE MEDIÇÃO: Cavidade ringdown Spectrometer (ICOS instrumento Id 41) TIPO DE PRODUTO DE DADOS: L1 TIPO DE AMOSTRAGEM: contínuo POLÍTICA DE DADOS: ICOs DATA é licenciado sob uma licença Creative Commons Atribuição 4.0 internacional (http://creativecommons.org/licenses/by/4.0/.The licença de dados ICOS é descrita em https://data.icos-cp.eu/licence) Погодинний вимірювання CO2 для Mace Head за 2019 рік, SN41 Хімія атмосфери та мережа змін клімату (AC3) КОД СТАНЦІЇ: МХД МХД НАЗВА СТАНЦІЇ: Голова Мейса КАТЕГОРІЯ СПОСТЕРЕЖЕННЯ: Спостереження за відбором повітря на стаціонарній платформі КРАЇНА/ТЕРИТОРІЯ: Україна - Україна Висота вимірювання: 24,0 м AGL ВИСОТА ПІДЙОМУ: 5 м ас ШИРОТА ШИРОТИ: 53.3261 N ДОВГОТА: 9.9036 E ТИП САЙТУ: сільський фон ВИМІРЮВАЛЬНІ ПРИЛАДИ: ПІКАРРО G1301 ДІАПАЗОН ДАНИХ: СО2 СО2 ШКАЛА ВИМІРЮВАННЯ: TBC / TBC ПЕРІОД ПОКРИТТЯ: 2019-01-01 00:00 2019-09-03 00:00 ІНТЕРВАЛ ЧАСУ: час від часу ОДИНИЦЯ ВИМІРЮВАННЯ: nmol.mol-. СПОСІБ ВИМІРЮВАННЯ: Порожнинний кільцевий спектрометр (ІКОС прилад Id 41) ТИП ПРОДУКТУ ДАНИХ: L1 (АНГЛ.) ТИП ВІДБОРУ ПРОБ: безперервний безперервний ПОЛІТИКА ЩОДО ДАНИХ: ICOs DATA ліцензовано за міжнародною ліцензією Creative Commons Attribution 4.0 (http://creativecommons.org/licenses/by/4.0/.The ліцензія на дані ICOS описана в https://data.icos-cp.eu/licence) Misurazioni orarie di CO2 per Mace Head per l'anno 2019, SN41 Clima Chimica e Climate Change Network (AC3) CODICE STAZIONE: MHD NOME DELLA STAZIONE: Testa di Mace CATEGORIA DI OSSERVAZIONE: Osservazione del campionamento dell'aria su una piattaforma stazionaria PAESE/TERRITORIO: Irlanda Altezza di misura: 24,0 m AGL ALTITUDINE: 5 m slm LATITUDINE: 53.3261 N LONGITUDINE: —9.9036 E TIPO DI SITO: fondo rurale STRUMENTAZIONE: PICARRO G1301 GAMMA DI DATI: CO2 SCALA DI MISURA: TBC PERIODO DI COPERTURA: 2019-01-01 00:00 2019-09-03 00:00 INTERVALLO DI TEMPO: ogni ora UNITÀ DI MISURA: nmol.mol— METODO DI MISURAZIONE: Spettrometro dell'anello della cavità (ICOS strumento Id 41) TIPO DI PRODOTTO: L1 TIPO DI CAMPIONAMENTO: continuo POLITICA DEI DATI: ICOs DATA è concesso sotto licenza Creative Commons Attribuzione 4.0 internazionale (http://creativecommons.org/licenses/by/4.0/.The ICOS licenza dati è descritto all'indirizzo https://data.icos-cp.eu/licence) Mjerenja CO2 po satu za Mace Head za 2019. godinu, SN41 Mreža za kemiju atmosfere i klimatske promjene (AC3) BROJ STANICE: MHD NAZIV STANICE: Mace glava KATEGORIJA PROMATRANJA: Promatranje uzorkovanja zraka na stacionarnoj platformi ZEMLJA/PODRUČJE: Irska Visina mjerenja: 24,0 m AGL VISINA: 5 m asl ZEMLJOPISNA ŠIRINA: 53.3261 N DUŽINA: —9.9036 E VRSTA STRANICE: ruralna pozadina INSTRUMENTACIJA: PICARRO G1301 RASPON PODATAKA: CO2 MJERNA LJESTVICA: JOŠ NIJE POTVRĐENO RAZDOBLJE POKRIVANJA: 2019 – 01 – 01 00:00 2019 – 09 – 03 00:00 VREMENSKI INTERVAL: satno MJERNA JEDINICA: nmol.mol-т METODA MJERENJA: Spektrometri prstenastih šupljina (ICOS instrument Id 41) VRSTA PODATKOVNOG PROIZVODA: L1 VRSTA UZORKOVANJA: kontinuirano PODATKOVNA POLITIKA: ICOs DATA je licencirana na temelju međunarodne licence Creative Commons Imenovanje 4.0 (http://creativecommons.org/licenses/by/4.0/.The ICOS dozvola za podatke opisana je na https://data.icos-cp.eu/licence) CO2-metingen per uur voor Mace Head voor het jaar 2019, SN41 Netwerk van atmosfeerchemie en klimaatverandering (AC3) DE CODE VAN HET STATION: MHD NAAM VAN HET STATION: Mace Hoofd OBSERVATIE CATEGORIE: Observatie van luchtbemonstering op een stationair platform LAND/GRONDGEBIED: Ierland De hoogte van de meting: 24,0 m AGL HOOGTE: 5 m asl BREEDTEGRAAD: 53.3261 N LENGTEGRAAD: —9.9036 E SOORT SITE: landelijke achtergrond INSTRUMENTATIE: PICARRO G1301 GEGEVENSBEREIK: CO2 MEETSCHAAL: TBC DEKKINGSPERIODE: 2019-01-01 00:00 2019-09-03 00:00 TIJDSINTERVAL: per uur MEETEENHEID: nmol.mol— MEETMETHODE: De Spectrometer van de holtering (ICOS-instrument Id 41) HET PRODUCTTYPE VAN DE GEGEVENS: L1 STEEKPROEFTYPE: continu GEGEVENSBELEID: ICO’s DATA is gelicentieerd onder een Creative Commons Naamsvermelding 4.0 internationale licentie (http://creativecommons.org/licenses/by/4.0/.The ICOS-gegevenslicentie wordt beschreven op https://data.icos-cp.eu/licence) Măsurarea CO2 pe oră pentru Mace Head pentru anul 2019, SN41 Rețeaua de Chimie și Schimbări Climatice (AC3) CODUL STAȚIEI: ROMÂNĂ NUMELE STAȚIEI: Capul lui Mace CATEGORIE DE OBSERVARE: Observarea eșantionării aerului pe o platformă staționară ȚARĂ/TERITORIU: Irlanda Înălțime de măsurare: 24,0 m AGL ALTITUDINE: 5 m asl LATITUDINE: 53.3261 N LONGITUDINE: —9.9036 E TIPUL SITE-ULUI: mediul rural INSTRUMENTAȚIE: PICARRO G1301 INTERVALUL DE DATE: CO2 SCALA DE MĂSURARE: DE CONFIRMAT PERIOADA DE ACOPERIRE: 2019-01-01 00:00 2019-09-03 00:00 INTERVAL DE TIMP: pe oră UNITATE DE MĂSURĂ: nmol.mol METODA DE MĂSURARE: Cavitatea inelului Spectrometru (ICOS instrument Id 41) TIPUL DE PRODUS DE DATE: L1 TIPUL DE EȘANTIONARE: continuă POLITICA DATELOR: ICOs DATA este licențiată sub licență internațională Creative Commons Attribution 4.0 (http://creativecommons.org/licenses/by/4.0/.The Licența de date ICOS este descrisă la https://data.icos-cp.eu/licence)

Bio-degradation assays were performed for bio-based polymers under environmental conditions with controlled temperature and pH using pH Stat titration. Suspensions of PLA and PBS microparticles, produced by e.g. cryo-milling, were incubated with proteolytic and lipolytic enzymes. Rates of hydrolysis, as determined by counter-titration with a diluted base (NaOH), was recorded for two hours. The thermal profile of PLA hydrolysis by protease was investigated. All measurements were conducted under controlled laboratory conditions. The columns headings are abbreviated and mean the following. Min: Duration of the titration in minutes; ml: Volume of added NaOH. Unless otherwise specified, c (NaOH) = 10 mM; pH: pH value of the suspension, set to 8.2; °C: Temperature of the suspension.