Contribution of anthropogenic aerosols to persistent La Niña-like conditions in the early 21st century.

The discrepancy between the observed lack of surface warming in the eastern equatorial Pacific and climate model projections of an El Niño-like warming pattern confronts the climate research community. While anthropogenic aerosols have been suggested as a cause, the prolonged cooling trend over the equatorial Pacific appears in conflict with Northern Hemisphere aerosol emission reduction since the 1980s. Here, using CESM, we show that the superposition of fast and slow responses to aerosol emission change-an increase followed by a decrease-can sustain the La Niña-like condition for a longer time than expected. The rapid adjustment of Hadley Cell to aerosol reduction triggers joint feedback between low clouds, wind, evaporation, and sea surface temperature in the Southeast Pacific, leading to a wedge-shaped cooling that extends to the central equatorial Pacific. Meanwhile, the northern subtropical cell gradually intensifies, resulting in equatorial subsurface cooling that lasts for decades.

Pacific salmon in the Canadian Arctic highlight a range-expansion pathway for sub-Arctic fishes.

Rapid climate change is altering Arctic ecosystems at unprecedented rates. These changes in the physical environment may open new corridors for species range expansions, with substantial implications for subsistence-dependent communities and sensitive ecosystems. Over the past 20 years, rising incidental harvest of Pacific salmon by subsistence fishers has been monitored across a widening range spanning multiple land claim jurisdictions in Arctic Canada. In this study, we connect Indigenous and scientific knowledges to explore potential oceanographic mechanisms facilitating this ongoing northward expansion of Pacific salmon into the western Canadian Arctic. A regression analysis was used to reveal and characterize a two-part mechanism related to thermal and sea-ice conditions in the Chukchi and Beaufort seas that explains nearly all of the variation in the relative abundance of salmon observed within this region. The results indicate that warmer late-spring temperatures in a Chukchi Sea watch-zone and persistent, suitable summer thermal conditions in a Beaufort Sea watch-zone together create a range-expansion corridor and are associated with higher salmon occurrences in subsistence harvests. Furthermore, there is a body of knowledge to suggest that these conditions, and consequently the presence and abundance of Pacific salmon, will become more persistent in the coming decades. Our collaborative approach positions us to document, explore, and explain mechanisms driving changes in fish biodiversity that have the potential to, or are already affecting, Indigenous rights-holders in a rapidly warming Arctic.

Long-term effects of climate change on juvenile bull shark migratory patterns.

Seasonal variability in environmental conditions is a strong determinant of animal migrations, but warming temperatures associated with climate change are anticipated to alter this phenomenon with unknown consequences. We used a 40-year fishery-independent survey to assess how a changing climate has altered the migration timing, duration and first-year survival of juvenile bull sharks (Carcharhinus leucas). From 1982 to 2021, estuaries in the western Gulf of Mexico (Texas) experienced a mean increase of 1.55°C in autumn water temperatures, and delays in autumn cold fronts by ca. 0.5 days per year. Bull shark migrations in more northern estuaries concomitantly changed, with departures 25-36 days later in 2021 than in 1982. Later, migrations resulted in reduced overwintering durations by up to 81 days, and the relative abundance of post-overwintering age 0-1 sharks increased by >50% during the 40-year study period. Yet, reductions in prey availability were the most influential factor delaying migrations. Juvenile sharks remained in natal estuaries longer when prey were less abundant. Long-term declines in prey reportedly occurred due to reduced spawning success associated with climate change based on published reports. Consequently, warming waters likely enabled and indirectly caused the observed changes in shark migratory behaviour. As water temperatures continue to rise, bull sharks in the north-western Gulf of Mexico could forgo their winter migrations in the next 50-100 years based on current trends and physiological limits, thereby altering their ecological roles in estuarine ecosystems and recruitment into the adult population. It is unclear if estuarine food webs will be able to support changing residency patterns as climate change affects the spawning success of forage species. We expect these trends are not unique to the western Gulf of Mexico or bull sharks, and migratory patterns of predators in subtropical latitudes are similarly changing at a global scale.

Environmental drivers of global variation in home range size of terrestrial and marine mammals.

As animal home range size (HRS) provides valuable information for species conservation, it is important to understand the driving factors of HRS variation. It is widely known that differences in species traits (e.g. body mass) are major contributors to variation in mammal HRS. However, most studies examining how environmental variation explains mammal HRS variation have been limited to a few species, or only included a single (mean) HRS estimate for the majority of species, neglecting intraspecific HRS variation. Additionally, most studies examining environmental drivers of HRS variation included only terrestrial species, neglecting marine species. Using a novel dataset of 2800 HRS estimates from 586 terrestrial and 27 marine mammal species, we quantified the relationships between HRS and environmental variables, accounting for species traits. Our results indicate that terrestrial mammal HRS was on average 5.3 times larger in areas with low human disturbance (human footprint index [HFI] = 0), compared to areas with maximum human disturbance (HFI = 50). Similarly, HRS was on average 5.4 times larger in areas with low annual mean productivity (NDVI = 0), compared to areas with high productivity (NDVI = 1). In addition, HRS increased by a factor of 1.9 on average from low to high seasonality in productivity (standard deviation (SD) of monthly NDVI from 0 to 0.36). Of these environmental variables, human disturbance and annual mean productivity explained a larger proportion of HRS variance than seasonality in productivity. Marine mammal HRS decreased, on average, by a factor of 3.7 per 10°C decline in annual mean sea surface temperature (SST), and increased by a factor of 1.5 per 1°C increase in SST seasonality (SD of monthly values). Annual mean SST explained more variance in HRS than SST seasonality. Due to the small sample size, caution should be taken when interpreting the marine mammal results. Our results indicate that environmental variation is relevant for HRS and that future environmental changes might alter the HRS of individuals, with potential consequences for ecosystem functioning and the effectiveness of conservation actions.

Fresh and recirculated submarine groundwater discharge zones along the central west coast of India.

The study area receives an average of 2840.0 mm of rainfall within four months every year. A portion of the rainwater is flown to the sea as surface water, and the other part is percolated into the bottom as groundwater. In coastal aquifers, the groundwater is transported to the sea due to a hydraulic gradient, and it contains a significant quantity of dissolved materials and nutrients. SGD processes impact the ocean productivity, mangrove and coral growth, local acidification and many. To isolate the SGD on the central west coast of India, different data was referred. The GWL concerning MSL contributed significantly to demarcating the SGD zones by considering the positive (>0 m) and negative (<0 m) values of GWL concerning above MSL. Thermal images for SST of pre-monsoon and post-monsoon periods of 2020 exhibit cooler surrounded by warmer, which might be the SGD buffering zones in the off-central west coast of India. By considering the results from GWL and SST, 8 SGD beach sites were identified for the further particularized study. The water samples were collected in March 2022, and analyzed using standard procedures and instruments. Fresh and mixing (recirculated) zones have been isolated by piper, hydrochemical facies evolution, and Ca2++Mg2+/K++Na + Vs log Cl- ionic ratio plots. The aquifer water chemical elements are converting possibly due to ionic exchange processes. The decrease in salinity and conductivity observed in the pore water just below the seawater might be due to the influence of freshwater inputs, helping to isolate the fresh SGD and recirculated SGD zones in the study area. Among 8 sites, 3 were found to be fresh SGD sites and 5 were noticed to be mixing/recirculated SGD sites. Most of these Beaches are bounded by hills, which helps to lead the SGD along the central west coast of India.

Regional differences in the effects of various Stokes drifts on the cooling of the marine environment under different wave conditions.

The WAVEWATCHIII model is employed to simulate Stokes drift, utilizing four distinct schemes integrated into the SBPOM circulation model. Deviations between simulated values and observations from the Optimum Interpolation Sea Surface Temperature (OISST) dataset unveil significant variations, particularly in regions characterized by pronounced swell. The northern hemisphere exhibits the highest deviations, reaching up to 0.3 °C during the March-April-May (MAM) and December-January-February (DJF) periods, while the Antarctic Circumpolar Current (ACC) consistently displays smaller deviations of approximately 0.1 °C. Deviations from Argo buoy measurements hover around 0.1 °C, except in the northern hemisphere where they escalate to approximately 1.5 °C. A comparative analysis of simulation results and Argo buoy measurements reveals an increasing deviation trend with a higher proportion of swell in specific sea areas, particularly evident in simulations utilizing approximate parameterization schemes. Notably, the Phillips profile scheme exhibits optimal performance, while the monochromatic profile scheme peaks with a simulated deviation of 0.13 °C. In contrast, the wave spectrum profile scheme consistently demonstrates applicability across diverse wave conditions and accurately captures the mixed layer at various depths. This study highlights the importance of the coupled WAVEWATCHIII-SBPOM model in accurately modeling future ocean conditions, providing valuable insight into the field of environmental science.

Sea spray aerosol concentration modulated by sea surface temperature.

Natural aerosols in pristine regions form the baseline used to evaluate the impact of anthropogenic aerosols on climate. Sea spray aerosol (SSA) is a major component of natural aerosols. Despite its importance, the abundance of SSA is poorly constrained. It is generally accepted that wind-driven wave breaking is the principle governing SSA production. This mechanism alone, however, is insufficient to explain the variability of SSA concentration at given wind speed. The role of other parameters, such as sea surface temperature (SST), remains controversial. Here, we show that higher SST promotes SSA mass generation at a wide range of wind speed levels over the remote Pacific and Atlantic Oceans, in addition to demonstrating the wind-driven SSA production mechanism. The results are from a global scale dataset of airborne SSA measurements at 150 to 200 m above the ocean surface during the NASA Atmospheric Tomography Mission. Statistical analysis suggests that accounting for SST greatly enhances the predictability of the observed SSA concentration compared to using wind speed alone. Our results support implementing SST into SSA source functions in global models to better understand the atmospheric burdens of SSA.

Monitoring Off-Shore Fishing in the Northern Indian Ocean Based on Satellite Automatic Identification System and Remote Sensing Data.

Satellite-derived Sea Surface Temperature (SST) and sea-surface Chlorophyll a concentration (Chl-a), along with Automatic Identification System (AIS) data of fishing vessels, were used in the examination of the correlation between fishing operations and oceanographic factors within the northern Indian Ocean from March 2020 to February 2023. Frequency analysis and the empirical cumulative distribution function (ECDF) were used to calculate the optimum ranges of two oceanographic factors for fishing operations. The results revealed a substantial influence of the northeast and southwest monsoons significantly impacting fishing operations in the northern Indian Ocean, with extensive and active operations during the period from October to March and a notable reduction from April to September. Spatially, fishing vessels were mainly concentrated between 20° N and 6° S, extending from west of 90° E to the eastern coast of Africa. Observable seasonal variations in the distribution of fishing vessels were observed in the central and southeastern Arabian Sea, along with its adjacent high sea of the Indian Ocean. Concerning the marine environment, it was observed that during the northeast monsoon, the suitable SST contributed to high CPUEs in fishing operation areas. Fishing vessels were widely distributed in the areas with both mid-range and low-range Chl-a concentrations, with a small part distributed in high-concentration areas. Moreover, the monthly numbers of fishing vessels showed seasonal fluctuations between March 2020 and February 2023, displaying a periodic pattern with an overall increasing trend. The total number of fishing vessels decreased due to the impact of the COVID-19 pandemic in 2020, but this was followed by a gradual recovery in the subsequent two years. For fishing operations in the northern Indian Ocean, the optimum ranges for SST and Chl-a concentration were 27.96 to 29.47 °C and 0.03 to 1.81 mg/m3, respectively. The preliminary findings of this study revealed the spatial-temporal distribution characteristics of fishing vessels in the northern Indian Ocean and the suitable ranges of SST and Chl-a concentration for fishing operations. These results can serve as theoretical references for the production and resource management of off-shore fishing operations in the northern Indian Ocean.

Unravelling the signatures of submarine groundwater discharge and seawater intrusion along the coastal plains of Odisha, India: a multi-proxy approach.

Submarine Groundwater Discharge (SGD) and Seawater Intrusion (SWI) are two contrary hydrological processes that occur across the land-sea continuum and understanding their nature is essential for management and development of coastal groundwater resource. Present study has attempted to demarcate probable zones of SGD and SWI along highly populated Odisha coastal plains which is water stressed due to indiscriminate-exploitation of groundwater leading to salinization and fresh groundwater loss from the alluvial aquifers. A multi-proxy investigation approach including decadal groundwater level dynamics, LANDSAT derived sea surface temperature (SST) anomalies and in-situ physicochemical analysis (pH, EC, TDS, salinity and temperature) of porewater, groundwater and seawater were used to locate the SGD and SWI sites. A total of 340 samples for four seasons (85 samples i.e., 30 porewater, 30 seawater and 25 groundwater in each season) were collected and their in-situ parameters were measured at every 1-2 km gap along ~ 145 km coastline of central Odisha (excluding the estuarine region). Considering high groundwater EC values (> 3000 µS/cm), three probable SWI and low porewater salinities (< 32 ppt in pre- and < 25 ppt in post-monsoons), four probable SGD zones were identified. The identified zones were validated with observed high positive hydraulic gradient (> 10 m) at SGD and negative hydraulic gradient (< 0 m) at SWI sites along with anomalous SST (colder in pre- and warmer in post-monsoon) near probable SGD locations. This study is first of its kind along the Odisha coast and may act as initial basis for subsequent investigations on fresh-saline interaction along the coastal plains where environmental integrity supports the livelihood of coastal communities and the ecosystem.

The impact of rising temperatures on the prevalence of coral diseases and its predictability: A global meta-analysis.

Coral reefs are under threat from disease as climate change alters environmental conditions. Rising temperatures exacerbate coral disease, but this relationship is likely complex as other factors also influence coral disease prevalence. To better understand this relationship, we meta-analytically examined 108 studies for changes in global coral disease over time alongside temperature, expressed using average summer sea surface temperature (SST) and cumulative heat stress as weekly sea surface temperature anomalies (WSSTAs). We found that both rising average summer SST and WSSTA were associated with global increases in the mean and variability in coral disease prevalence. Global coral disease prevalence tripled, reaching 9.92% in the 25 years examined, and the effect of 'year' became more stable (i.e. prevalence has lower variance over time), contrasting the effects of the two temperature stressors. Regional patterns diverged over time and differed in response to average summer SST. Our model predicted that, under the same trajectory, 76.8% of corals would be diseased globally by 2100, even assuming moderate average summer SST and WSSTA. These results highlight the need for urgent action to mitigate coral disease. Mitigating the impact of rising ocean temperatures on coral disease is a complex challenge requiring global discussion and further study.

Improved the Impact of SST for HY-2A Scatterometer Measurements by Using Neural Network Model.

The variation of sea surface temperature (SST) can change the backscatter coefficient measured by a scatterometer, resulting in a decrease in the accuracy of the sea surface wind measurement. This study proposed a new approach to correct the effect of SST on the backscatter coefficient. The method focuses on the Ku-band scatterometer HY-2A SCAT, which is more sensitive to SST than C-band scatterometers, can improve the wind measurement accuracy of the scatterometer without relying on reconstructed geophysical model function (GMF), and is more suitable for operational scatterometers. Through comparisons to WindSat wind data, we found that the Ku-band scatterometer HY-2A SCAT wind speeds are systemically lower under low SST and higher under high SST conditions. We trained a neural network model called the temperature neural network (TNNW) using HY-2A data and WindSat data. TNNW-corrected backscatter coefficients retrieved wind speed with a small systematic deviation from WindSat wind speed. In addition, we also carried out a validation of HY-2A wind and TNNW wind using European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data as a reference, and the results showed that the retrieved TNNW-corrected backscatter coefficient wind speed is more consistent with ECMWF wind speed, indicating that the method is effective in correcting SST impact on HY-2A scatterometer measurements.

Climate change impacts on seabirds and marine mammals: The importance of study duration, thermal tolerance and generation time.

Understanding climate change impacts on top predators is fundamental to marine biodiversity conservation, due to their increasingly threatened populations and their importance in marine ecosystems. We conducted a systematic review of the effects of climate change (prolonged, directional change) and climate variability on seabirds and marine mammals. We extracted data from 484 studies (4808 published studies were reviewed), comprising 2215 observations on demography, phenology, distribution, diet, behaviour, body condition and physiology. The likelihood of concluding that climate change had an impact increased with study duration. However, the temporal thresholds for the effects of climate change to be discernibly varied from 10 to 29 years depending on the species, the biological response and the oceanic study region. Species with narrow thermal ranges and relatively long generation times were more often reported to be affected by climate change. This provides an important framework for future assessments, with guidance on response- and region-specific temporal dimensions that need to be considered when reporting effects of climate change. Finally, we found that tropical regions and non-breeding life stages were poorly covered in the literature, a concern that should be addressed to enable a better understanding of the vulnerability of marine predators to climate change.

Geographic range size, water temperature, and extrinsic threats predict the extinction risk in global cetaceans.

Despite the fact that cetaceans provide significant ecological contributions to the health and stability of aquatic ecosystems, many are highly endangered with nearly one-third of species assessed as threatened with extinction. Nevertheless, to date, few studies have explicitly examined the patterns and processes of extinction risk and threats for this taxon, and even less between the two subclades (Mysticeti and Odontoceti). To fill this gap, we compiled a dataset of six intrinsic traits (active region, geographic range size, body weight, diving depth, school size, and reproductive cycle), six environmental factors relating to sea surface temperature and chlorophyll concentration, and two human-related threat indices that are commonly recognized for cetaceans. We then employed phylogenetic generalized least squares models and model selection to identify the key predictors of extinction risk in all cetaceans, as well as in the two subclades. We found that geographic range size, sea surface temperature, and human threat index were the most important predictors of extinction risk in all cetaceans and in odontocetes. Interestingly, maximum body weight was positively associated with the extinction risk in mysticetes, but negatively related to that for odontocetes. By linking seven major threat types to extinction risk, we further revealed that fisheries bycatch was the most common threat, yet the impacts of certain threats could be overestimated when considering all species rather than just threatened ones. Overall, we suggest that conservation efforts should focus on small-ranged cetaceans and species living in warmer waters or under strong anthropogenic pressures. Moreover, further studies should consider the threatened status of species when superimposing risk maps and quantifying risk severity. Finally, we emphasize that mysticetes and odontocetes should be conserved with different strategies, because their extinction risk patterns and major threat types are considerably different. For instance, large-bodied mysticetes and small-ranged odontocetes require special conservation priority.

Sea ice variability and trends in the Indian Ocean sector of Antarctica: Interaction with ENSO and SAM.

Antarctic sea ice variability is primarily associated with ocean-atmospheric forcing driven by anomalous conditions over the tropical regions of the Pacific and Indian Oceans. The ice-ocean-atmosphere dynamics in the Indian Ocean Sector (IOS) of Antarctica have been studied using monthly satellite and reanalysis observations over four decades (1979-2019). In this study, we revealed that the annual sea ice extent (SIE) in the IOS increases at a rate of 0.7 ± 0.9% decade-1, with a maximum increase in austral summer (5.9 ± 3.7% decade-1). The wavelet approach was used to determine the variability in IOS sea ice caused by the El Niño/Southern Oscillation (ENSO) and southern annular mode (SAM). The SIE has a significant association with both indices during the summer and autumn. In comparison to ENSO, the sea ice variability associated with SAM is typically seasonal in nature and lacks distinct patterns. The wavelet coherence analysis revealed a relatively weak relationship between ENSO and SAM but a highly significant coherence between climatic indices and SIE. We observed that sea ice in the IOS is influenced significantly by climatic oscillations during their negative SAM/El Niño or positive SAM/La Niña phases. Furthermore, the study demonstrated a substantial impact of climatic disturbances in determining the sea ice variability in the IOS.

Validation and Improvement of COCTS/HY-1C Sea Surface Temperature Products.

In oceanographic study, satellite-based sea surface temperature (SST) retrieval has always been the focus of researchers. This paper investigates several multi-channel SST retrieval algorithms for the thermal infrared band, and evaluates the accuracy of the COCTS/HY-1C SST products. NEAR-GOOS in situ SST data are utilized for validation and improvement, and a three-step matching procedure including geographic location screening, cloud masking, and homogeneity check is conducted to match in situ SST data with satellite SST data. Two improvement schemes, including nonlinear regression and regularization iteration, are proposed to improve the accuracy of the COCTS/HY-1C SST products and the typical application scenarios and the algorithm characteristics of these two schemes are discussed. The standard deviation of residual between retrieved SST and measured SST for these two data improvement algorithms, which are considered as the main indexes for assessment, result in an improvement of 13.245% and 14.096%, respectively. In addition, the generalization ability of the SST models under two data improvement methods is quantitatively compared, and the factors affecting the model accuracy are also carefully evaluated, including the in situ data acquisition method and measurement time (day/night). Finally, future works about SST retrieval with COCTS/HY-1C satellite data are summarized.

High-Precision Measurement of Sea Surface Temperature with Integrated Infrared Thermometer.

The sea surface temperature (SST) is a crucial parameter system in climate monitoring. Satellite remote sensing is currently the most common approach for measuring long-term and large-area sea surface temperatures. The SST data measured by the satellite radiometer include the sea surface skin temperature (SSTskin) at a depth of approximately 10 µm. Satellite remote sensing measurement data must be compared and validated with on-site measured data. There are various solutions for on-site measuring instruments; the essential components are usually infrared radiation sensors with radiation output. This paper uses an ordinary integrated infrared thermometer without a radiation output function to remotely measure the sea surface temperature to achieve a high-precision measurement. The scheme of integrating infrared thermometers to measure the sea surface temperature is investigated in this paper. Based on Planck's formula, the bidirectional conversion relationship between temperature and radiation in a certain band is established. The experimental system introduced in this paper uses an integrated infrared thermometer to measure the small blackbody and the target in a cyclic measurement system. We combine it with the sea surface emissivity characteristics and eliminate the influence of sky background radiation on the sea surface to obtain the actual amount of radiation on the sea surface, from which we obtain the actual radiation amount on the sea surface. Accurate SST can be calculated from the actual amount of radiation at the sea surface. The temperature measurement accuracy can reach 0.1 K, allowing it to meet on-site temperature measurement requirements, as well as the comparison measurement requirements confirmed by satellite remote sensing on-site data. There are relatively few products available for sensors with a temperature measurement accuracy of 0.1 K on the market, and temperature measurement equipment with a temperature measurement accuracy of 0.1 K is relatively expensive. Cost is one of the important factors to consider when using in bulk, especially as global warming increases the need for ocean monitoring. The scheme proposed in this paper is beneficial to reduce the volume and weight of measuring instruments, reduce the cost, and promote the large-scale combined application of sea surface temperature change monitoring.

High Precision Sea Surface Temperature Prediction of Long Period and Large Area in the Indian Ocean Based on the Temporal Convolutional Network and Internet of Things.

Impacted by global warming, the global sea surface temperature (SST) has increased, exerting profound effects on local climate and marine ecosystems. So far, investigators have focused on the short-term forecast of a small or medium-sized area of the ocean. It is still an important challenge to obtain accurate large-scale and long-term SST predictions. In this study, we used the reanalysis data sets provided by the National Centers for Environmental Prediction based on the Internet of Things technology and temporal convolutional network (TCN) to predict the monthly SSTs of the Indian Ocean from 2014 to 2018. The results yielded two points: Firstly, the TCN model can accurately predict long-term SSTs. In this paper, we used the Pearson correlation coefficient (hereafter this will be abbreviated as "correlation") to measure TCN model performance. The correlation coefficient between the predicted and true values was 88.23%. Secondly, compared with the CFSv2 model of the American National Oceanic and Atmospheric Administration (NOAA), the TCN model had a longer prediction time and produced better results. In short, TCN can accurately predict the long-term SST and provide a basis for studying large oceanic physical phenomena.

Experiment Degree Heating Week (eDHW) as a novel metric to reconcile and validate past and future global coral bleaching studies.

Coral bleaching has increasingly impacted reefs worldwide over the past four decades. Despite almost 40 years of research into the mechanistic, physiological, ecological, biophysical and climatic drivers of coral bleaching, metrics to allow comparison between ecological observations and experimental simulations still do not exist. Here we describe a novel metric - experimental Degree Heating Week (eDHW) - with which to standardise the persistently variable thermal conditions employed across experimental studies of coral bleaching by modify the widely used Degree Heating Week (DHW) metric used in ecological studies to standardise cumulative heat loading.

Climate causes shifts in grey seal phenology by modifying age structure.

There are numerous examples of phenological shifts that are recognized both as indicators of climate change and drivers of ecosystem change. A pressing challenge is to understand the causal mechanisms by which climate affects phenology. We combined annual population census data and individual longitudinal data (1992-2018) on grey seals, Halicheorus grypus, to quantify the relationship between pupping season phenology and sea surface temperature. A temperature increase of 2°C was associated with a pupping season advance of approximately seven days at the population level. However, we found that maternal age, rather than sea temperature, accounted for changes in pupping date by individuals. Warmer years were associated with an older average age of mothers, allowing us to explain phenological observations in terms of a changing population age structure. Finally, we developed a matrix population model to test whether our observations were consistent with changes to the stable age distribution. This could not fully account for observed phenological shift, strongly suggesting transient modification of population age structure, for example owing to immigration. We demonstrate a novel mechanism for phenological shifts under climate change in long-lived, age- or stage-structured species with broad implications for dynamics and resilience, as well as population management.

Cloudiness reduces the bleaching response of coral reefs exposed to heat stress.

Climate change and warming ocean temperatures are a threat to coral reef ecosystems. Since the 1980s, there has been an increase in mass coral bleaching and associated coral mortality due to more frequent and severe thermal stress. Although most research has focused on the role of temperature, coral bleaching is a product of the interacting effects of temperature and other environmental variables such as solar radiation. High light exacerbates the effects of thermal stress on corals, whereas reductions in light can reduce sensitivity to thermal stress. Here, we use an updated global dataset of coral bleaching observations (n = 35,769) from 1985 to 2017 and satellite-derived datasets of SST and clouds to examine for the first time at a global scale the influence of cloudiness on the likelihood of bleaching from thermal stress. We find that among coral reefs exposed to severe bleaching-level heat stress (Degree Heating Weeks >8°Cˑweek), bleaching severity is inversely correlated with the interaction of heat stress and cloud fraction anomalies (p < 0.05), such that higher cloudiness implies reduced bleaching response. A Random Forest model analysis employing different set of environmental variables shows that a model employing Degree Heating Weeks and the 30-day cloud fraction anomaly most accurately predicts bleaching severity (Accuracy = 0.834; Cohen's Kappa = 0.769). Based on these results and global warm-season cloudiness patterns, we develop a 'cloudy refugia' index which identifies the central equatorial Pacific and French Polynesia as regions where cloudiness is most likely to protect corals from bleaching. Our findings suggest that incorporating cloudiness into prediction models can help delineate bleaching responses and identify reefs which may be more resilient to climate change.