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Phycosphere pH of single phytoplankton cellsThe pH in the phycosphere of a single cell Chlamydomonas concordia (~5 µm diameter) exposed to 140 μmol photons m−2 s−1 was 8.27 ± 0.01 (179 measurements), while the pH of bulk seawater was 8.01 ± 0.01 (160 measurements) (Fig. 1c). The observed pH variation near the cell surface was 150 µmol m−2 s−1 [33]. At light intensities More

Coupled model experiments for detecting vegetation-climate feedbackWe quantified changes of near-surface (2-m) air temperature (Ta) in response to the observed NH greening for all active growing seasons during 1982–2014 using IPSL-CM. We defined the three growing seasons (spring, summer, and autumn) across the entire NH domain as periods of March-April-May (MAM), June-July-August (JJA), and September-October-November (SON), respectively. For each season, a pair of transient numerical experiments was performed by modifying LAI: a dynamic vegetation experiment (SCE) forced by annually and seasonally varying LAI from satellite observations36, and three seasonal control experiments (({{{{{{rm{LAI}}}}}}}_{{{{{{rm{CTL}}}}}}}^{{{{{{rm{MAM}}}}}}}), ({{{{{{rm{LAI}}}}}}}_{{{{{{rm{CTL}}}}}}}^{{{{{{rm{JJA}}}}}}}), and ({{{{{{rm{LAI}}}}}}}_{{{{{{rm{CTL}}}}}}}^{{{{{{rm{SON}}}}}}}) for MAM, JJA, and SON, respectively) forced by annually varying LAI for all seasons, except in the season of interest when the LAI was fixed to the climatological conditions observed during 1982–2014 (Fig. S1). For all experiments, other boundary conditions, including sea surface temperature (SST), sea ice fraction (SIC), and atmospheric CO2 concentrations, were kept consistent (Methods). Therefore, differences between SCE and the control experiments characterized the effects of the observed LAI changes on Ta (hereafter denoted as ΔTa), both intra- and inter-seasonally. Multimember paired ensembles were generated for each coupled model experiment by performing 30 repeated runs but with different initial conditions (see Methods).The capacity of the IPSL-CM GCM for simulating the seasonal variations and spatial patterns of Ta was assessed by comparing the SCE simulation results with the observation-based Ta data (Methods). Throughout most of the growing season (May to October), the SCE simulation well reproduced the increasing trend and interannual variability of the NH land mean Ta observed during 1982–2014 (Fig. S2). Observational data showed that the strongest NH warming occurred in early spring (March and April) and late autumn (November). However, the SCE simulation failed to capture the exceptionally strong warming during the transitional seasons, leading to the underestimation of the annual mean warming trend (SCE: 0.237 ± 0.024 °C decade−1; observed: 0.362 ± 0.048 °C decade−1). This underestimation stemmed from a negative bias in the increase of downwelling shortwave radiation, possibly due to an absence of short-lived forcing and bias in the cloud systems37. Overall, the SCE reproduced the geographical patterns of seasonal warming reasonably well (Fig. S3), which strengthened our confidence in the model projections. Notably, it successfully captured the observed amplified warming over pan-arctic and semi-arid regions, as well as the few cases of regional cooling, such as that over northwestern North America during MAM (Fig. S3).Intra-seasonal temperature responses to NH LAI changesFor the period from 1982 to 2014, satellite-retrieved LAI showed statistically significant increasing trends (p  0.1), strong and significant JJA cooling (−0.044 ± 0.008 °C decade−1, p  0.1) (intra-seasonal feedbacks shown in Fig. 1b). The LAI-induced JJA Ta trend was equivalent to cooling of −0.15 ± 0.03 °C in JJA over the study period, offsetting the overall SCE-simulated near-surface air warming over this period by ~12.5%. This strong JJA cooling was further supported by a significant negative correlation (r = −0.64, p  0.1) or SON (r = 0.07, p  > 0.1) (Fig. S4a, c), during which the LAI-induced changes accounted for only 1.3% (MAM) and −3.2% (SON) of the concurrent greenhouse warming. We also verified the robustness of our results by performing equilibrium experiments with an independent model, the NCAR Community Atmosphere Model coupled with Community Land Model (CAM-CLM, Methods). Indeed, this model generated a similarly strong LAI-induced cooling in JJA (−0.18 °C, p  0.1) and SON (−0.05 °C, p  > 0.1) (Fig. S5).Fig. 1: Intra- and inter-seasonal temperature responses to leaf area index (LAI) changes.a Monthly trends (shadings) of Northern Hemisphere (NH) mean LAI during 1982–2014 used as input to the seasonal simulations. The dashed curve and transparent bars indicate trends of monthly LAI and seasonally aggregated LAI values, respectively. b Linear trends of Ta driven by LAI changes within the same season (intra-seasonal) and other growing seasons (inter-seasonal). Error bars in a, b indicate uncertainty ranges [1 – standard deviation (SD)]. c Monthly trends of LAI-induced air temperature changes (ΔTa), with red and blue shadings representing positive and negative trends, respectively. The bottom panel shows the overall ΔTa trends induced by LAI changes in all growing seasons, calculated as the sum of ΔTa trends from the three seasonal runs shown separately in the above panels. ***p  More

Data collectionThe present dataset was collected within the framework of the Atlantic Lobster Moult and Quality (ALMQ) project originally managed and implemented by the Atlantic Veterinary College Lobster Science Centre at the University of Prince Edward Island in collaboration with the Fishermen and Scientists Research Society. The Atlantic Lobster Moult and Quality project was initially funded through the Atlantic Innovation Fund program from the Atlantic Canada Opportunities Agency (ACOA) and transferred to the Fishermen and Scientists Research Society (FSRS) in 2012.Sampling took place every 2–3 weeks in eight lobster fishing areas (LFA) in Atlantic Canada from 2004 to 2014 (see Fig. 1, Table 1). The sampling followed the FSRS Lobster Moult and Quality sampling protocol and was conducted by technicians from the Atlantic Veterinary College and the Fishermen and Scientists Research Society in fixed locations from traps set the day before2. Locations based on targeted sampling (LFA 33 and 34) were chosen according to the fishing efforts in the respective areas and selected by a lobster science committee consisting of members from industry, academia, research and federal and provincial representatives. Other locations (LFA 24, 25, 26A, 35) were chosen based on proximity to the Atlantic Veterinary College and other projects with commercial fishers which allowed sampling.Table 1 Overview of sampling locations, surface areas (km2) and number of lobsters (N) sampled for the Atlantic Lobster Moult and Quality Project by AVC Lobster Science Centre from 2004–2015 in Atlantic Canada. (PEI = Prince Edward Island, NS = Nova Scotia).Full size tableFig. 1(a) Map of the lobster fishing areas (LFAs) in the Maritime Provinces in eastern Canada with the sampling locations (red) recorded by the AVC Lobster Science Centre for the Atlantic Lobster Moult and Quality project. (b) Enlarged map of LFA 33. (c) Enlarged map of LFAs on Prince Edward Island. The maps were created using QGIS (v. 3.18; https://qgis.org). Contours depict water depths in meters.Full size imageFor each sampling event, 40 commercial lobster traps with escape vents for lobsters below the minimum legal size were used. Legal sizes depend on size-at-maturity (size at which 50% of the population reach maturity) which differs between LFAs due to regional differences in water temperature that influence lobster growth. There were some differences in sampling procedure between lobster fishing season and off-season. During lobster fishing season sampling took place within 48 h post landing and only legal-sized lobsters were assessed. During off season, lobsters were sampled directly on board chartered boats and were returned to sea immediately after sampling. During non-fishing season sampling, lobsters below minimum legal size were also sampled but no egg-bearing females were targeted to minimize negative handling effects. Targeted sample size was 200 lobsters per sampling event before 2009 and 125 lobsters after 2009 due to budget constraints.On average, 3–4 lobsters of each sex were sampled in every 2 mm lobster size grouping. Lobster size was recorded as the carapace length in mm and determined using calipers rounding down to the nearest mm. The size distribution of sampled lobsters is presented in Fig. 2. Lobsters were assessed for general health (lesions, shell damage, liveliness/vigour) and shell hardness. Shell hardness was recorded as soft, medium or hard. A carapace of a soft-shelled lobster would be compressible at the ventral and dorsal (anterior and posterior) carapace, a medium-shelled lobster would only be compressible at the ventral carapace and a hard-shelled lobster would not be compressible at any carapace location.Fig. 2Lobster size (as carapace length in mm) distribution for all lobsters sampled during the sampling period (15 missing values).Full size imageTo estimate hemolymph protein levels, the ventral abdomen between the first pair of walking legs was sprayed with 70% ethanol and 3 ml of hemolymph were extracted with a 22 gauge needle and a 3 ml syringe. A few drops of hemolymph were placed on a handheld refractometer and the refractive index (“°Brix” value) was recorded and used as a proxy for total hemolymph levels. The distribution of hemolymph protein level is shown in Fig. 3. The moult stages were determined by pleopod stages under a stereomicroscope and recorded in pleopod stages (see Table 2). The stage determinations are shown in Table 2 and Fig. 46.Fig. 3Distribution of hemolymph protein level (measured in °Brix) for all lobsters sampled in the dataset (892 missing values).Full size imageTable 2 Description of premoult stages and pleopod stages in adult American lobster based on Aiken6. C: Intermoult, D: Premoult.Full size tableFig. 4Pleopod stages of lobsters at different times in their moult cycle. Illustrations by Lavallée et al.2.Full size imageIn total, 141,659 lobsters were sampled from 2004–2015 over 1,195 sampling events. Data were recorded manually on data sheets and re-checked before being entered into an Excel data sheet (Excel, Microsoft). More

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