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Abstract Tropical and extra-tropical storms generate extreme waves, impacting both nearby and remote regions through swell propagation. Despite their devastating effects in tropical areas, the contribution of tropical cyclones (TCs) to global wave-induced coastal risk remains unknown. Here, we enable a quantitative assessment of TC’s role in extreme waves approaching global coastlines, by designing twin oceanic wave simulations with and without realistic TC wind forcing. We find that TCs substantially contribute to extreme breaking heights in tropical regions (35-50% on average), reaching 100% in high-density TC areas like the North Pacific. TCs also impact remote TC-free regions, such as the equatorial Pacific experiencing in average 30% of its extreme wave events due to TCs. Interannual variability amplifies TC-induced wave hazards, notably during El Niño in the Central Pacific, and La Niña in the South China Sea, Caribbean Arc, and South Indian Ocean coastlines. This research offers critical insights for global risk management and preparedness.

Abstract Oceanic eddies are recognized as pivotal components in marine ecosystems, believed to concentrate a wide range of marine life spanning from phytoplankton to top predators. Previous studies have posited that marine predators are drawn to these eddies due to an aggregation of their forage fauna. In this study, we examine the response of forage fauna, detected by shipboard acoustics, across a broad sample of a thousand eddies across the world’s oceans. While our findings show an impact of eddies on surface temperatures and phytoplankton in most cases, they reveal that only a minority (13%) exhibit significant effects on forage fauna, with only 6% demonstrating an oasis effect. We also show that an oasis effect can occur both in anticyclonic and cyclonic eddies, and that the few high-impact eddies are marked by high eddy amplitude and strong water-mass-trapping. Our study underscores the nuanced and complex nature of the aggregating role of oceanic eddies, highlighting the need for further research to elucidate how these structures attract marine predators.

BackgroundLeptospirosis is a neglected zoonosis which remains poorly known despite its epidemic potential, especially in tropical islands where outdoor lifestyle, vulnerability to invasive reservoir species and hot and rainy climate constitute higher risks for infections. Burden remains poorly documented while outbreaks can easily overflow health systems of these isolated and poorly populated areas. Identification of generic patterns driving leptospirosis dynamics across tropical islands would help understand its epidemiology for better preparedness of communities. In this study, we aim to model leptospirosis seasonality and outbreaks in tropical islands based on precipitation and temperature indicators.Methodology/principal findingsWe adjusted machine learning models on leptospirosis surveillance data from seven tropical islands (Guadeloupe, Reunion Island, Fiji, Futuna, New Caledonia, and Tahiti) to investigate 1) the effect of climate on the disease's seasonal dynamic, i.e., the centered seasonal profile and 2) inter-annual anomalies, i.e., the incidence deviations from the seasonal profile. The model was then used to estimate seasonal dynamics of leptospirosis in Vanuatu and Puerto Rico where disease incidence data were not available. A robust model, validated across different islands with leave-island-out cross-validation and based on current and 2-month lagged precipitation and current and 1-month lagged temperature, can be constructed to estimate the seasonal dynamic of leptospirosis. In opposition, climate determinants and their importance in estimating inter-annual anomalies highly differed across islands.Conclusions/significanceClimate appears as a strong determinant of leptospirosis seasonality in tropical islands regardless of the diversity of the considered environments and the different lifestyles across the islands. However, predictive and expandable abilities from climate indicators weaken when estimating inter-annual outbreaks and emphasize the importance of these local characteristics in the occurrence of outbreaks.

Abstract Background Dengue dynamics result from the complex interactions between the virus, the host and the vector, all being under the influence of the environment. Several studies explored the link between weather and dengue dynamics and some investigated the impact of climate change on these dynamics. Most attempted to predict incidence rate at a country scale or assess the environmental suitability at a global or regional scale. Here, we propose a new approach which consists in modeling the risk of dengue outbreak at a local scale according to climate conditions and study the evolution of this risk taking climate change into account. We apply this approach in New Caledonia, where high quality data are available. Methods We used a statistical estimation of the effective reproduction number (R t ) based on case counts to create a categorical target variable : epidemic week/non-epidemic week. A machine learning classifier has been trained using relevant climate indicators in order to estimate the probability for a week to be epidemic under current climate data and this probability was then estimated under climate change scenarios. Results Weekly probability of dengue outbreak was best predicted with the number of days when maximal temperature exceeded 30.8°C and the mean of daily precipitation over 80 and 60 days prior to the predicted week respectively. According to scenario RCP8.5, climate will allow dengue outbreak every year in New Caledonia if the epidemiological and entomological contexts remain the same. Conclusion We identified locally relevant climatic factor driving dengue outbreaks in New Caledonia and assessed the inter-annual and seasonal risk of dengue outbreak under different climate change scenarios up to the year 2100. We introduced a new modeling approach to estimate the risk of dengue outbreak depending on climate conditions. This approach is easily reproducible in other countries provided that reliable epidemiological and climate data are available.

Mosquito-borne viruses are leading causes of morbidity and mortality in many parts of the world. In recent years, modelling studies have shown that climate change strongly influences vector-borne disease transmission, particularly rising temperatures. As a result, the risk of epidemics has increased, posing a significant public health risk. This review aims to summarize all published laboratory experimental studies carried out over the years to determine the impact of temperature on the transmission of arboviruses by the mosquito vector. Given their high public health importance, we focus on dengue, chikungunya, and Zika viruses, which are transmitted by the mosquitoes Aedes aegypti and Aedes albopictus. Following PRISMA guidelines, 34 papers were included in this systematic review. Most studies found that increasing temperatures result in higher rates of infection, dissemination, and transmission of these viruses in mosquitoes, although several studies had differing findings. Overall, the studies reviewed here suggest that rising temperatures due to climate change would alter the vector competence of mosquitoes to increase epidemic risk, but that some critical research gaps remain.

Study region: Six watersheds of the main island of New Caledonia. Study focus: In the context of a projected reduction of extreme precipitation events by ~ 20% by 2100 combined to large land cover variability, a distributed hydrological approach was adopted over New Caledonia. The WRF-Hydro model was implemented using a one-way WRF meteorological forcing, with rainfall being spatially interpolated from rain gauge observations using the Thiessen polygon and IDEW methods. The Dynamically Dimensioned Search algorithm was applied for calibration on three contrasted flash-floods. Two-year validation allowed the dynamics of the watersheds to be studied and compared. New hydrological insights for the region: Good results in terms of Nash-Sutcliffe efficiency were reached on all watersheds (NSE ≥ 0.6). WRF-Hydro showed consistent water budget components for two flash-floods with 90% correlation between simulated and observed runoff coefficients of all basins. Adjusted physical parameters matched known watershed morphological and hydrological features. Both methods of rainfall interpolation produced similar NSE but strongly different water distributions, with simulated soil moisture changes varying by up to 60% during flash-floods. Spatial patterns of soil moisture and flood decomposition led to improved understanding of watershed behavior and to a revision of infiltration properties for one of them. Overall, WRF-Hydro proved to be a suitable framework to better understand hydrological processes and efficiently handle prospective modifications of New Caledonia’s land cover and climate regimes.

Mesopelagic resources are central to the ecosystem but remain poorly studied mainly due to the lack of observations. This paper investigates the assemblages of micronekton organisms and their habitat in the Natural Park of the Coral Sea around New Caledonia (southwest Pacific) using data from 141 pelagic trawls. A total of 67,130 micronekton individuals (fish, crustaceans, and mollusks) were collected with 252 species identified among 152 genus and 76 families. In the analyses, we focused on 22 species; each were present in more than 33 trawls (i.e., in more than 25% of the total number of trawls) and studied their spatial distribution and vertical dynamic behavior. Community structure was investigated through region of common profile (RCP), an innovative statistical multivariate method allowing the study of both species assemblages and environmental conditions’ influence on species occurrence probability. Nine major assemblages were identified, mainly driven by time of the day and sampling depth. Environmental variables, such as mean oxygen concentration, mean temperature, and bathymetry, also influenced micronekton assemblages, inducing a north/south distribution pattern. Three major day-assemblages were identified, distributed over the whole EEZ but segregated by depth: one assemblage in waters shallower than 200 m and the other two in deeper waters, respectively, in the north and the south. The night-assemblages were mostly segregated by depth with two community changes at approximately 80 and 200 m and spatially with a north–south gradient. The predominant northern night assemblages were dominated by crustacean, whereas the southern assemblage mostly by cephalopods and fish species. Generally, the southwest part of the EEZ was the most diverse part. Statistical analyses allowed the prediction of the spatial distribution of each species, and its vertical migration behavior was determined. Based on results, three important areas were identified to be considered for special management measures as part of the Natural Park of the Coral Sea.

Monitoring the spatio-temporal variations of surface chlorophyll-a concentration (Chl, a proxy of phytoplankton biomass) greatly benefited from the availability of continuous and global ocean color satellite measurements from 1997 onward. These two decades of satellite observations are however still too short to provide a comprehensive description of Chl variations at decadal to multi-decadal timescales. This paper investigates the ability of a machine learning approach (a non-linear statistical approach based on Support Vector Regression, hereafter SVR) to reconstruct global spatio-temporal Chl variations from selected surface oceanic and atmospheric physical parameters. With a limited training period (13 years), we first demonstrate that Chl variability from a 32-years global physical-biogeochemical simulation can generally be skillfully reproduced with a SVR using the model surface variables as input parameters. We then apply the SVR to reconstruct satellite Chl observations using the physical predictors from the above numerical model and show that the Chl reconstructed by this SVR more accurately reproduces some aspects of observed Chl variability and trends compared to the model simulation. This SVR is able to reproduce the main modes of interannual Chl variations depicted by satellite observations in most regions, including El Niño signature in the tropical Pacific and Indian Oceans. In stark contrast with the trends simulated by the biogeochemical model, it also accurately captures spatial patterns of Chl trends estimated by satellite data, with a Chl increase in most extratropical regions and a Chl decrease in the center of the subtropical gyres, although the amplitude of these trends are underestimated by half. Results from our SVR reconstruction over the entire period (1979–2010) also suggest that the Interdecadal Pacific Oscillation drives a significant part of decadal Chl variations in both the tropical Pacific and Indian Oceans. Overall, this study demonstrates that non-linear statistical reconstructions can be complementary tools to in situ and satellite observations as well as conventional physical-biogeochemical numerical simulations to reconstruct and investigate Chl decadal variability.

Tropical cyclones (TCs) can have profound effects on the dynamics of forest vegetation that need to be better understood. Here, we analysed changes in forest vegetation induced by TCs using the normalized difference vegetation index (NDVI). We used an accurate historical database of TC tracks and intensities, together with the Willoughby cyclone model to reconstruct the 2D surface wind speed structure of TCs and analyse how TCs affect forest vegetation. We used segmented linear models to identify significant breakpoints in the relationship between the reconstructed maximum sustained wind speed (Wmax) and the observed changes in NDVI. We tested the hypothesis that the rate of change in damage caused by TCs to forest and recovery time would increase according to Wmax thresholds as defined in the widely used Saffir–Simpson hurricane wind scale (SSHWS). We showed that the most significant breakpoint was located at 50 m/s. This breakpoint corresponds to the transition between categories 2 and 3 TCs in the SSHWS. Below this breakpoint, damages caused to forest vegetation and the time needed to recover from these damages were negligable. We found a second breakpoint, with a sharp increase in damages for winds >75 m/s. This suggested that extremely intense tropical cyclones, which might be more frequent in the future, can cause extreme damages to forest vegetation. Nevertheless, we found high variation in the observed damages and time needed to recover for a given Wmax. Further studies are needed to integrate other factors that might affect the exposure and resistance to TCs as well as forests’ capacity to recover from these disturbances.

Abstract In the Western Tropical South Pacific, patches of high chlorophyll concentrations linked to the occurrence of N2-fixing organisms are found in the vicinity of volcanic islands. The survival of these organisms relies on a high bioavailable iron supply whose origin and fluxes remain unknown. Here, we measured high dissolved iron (DFe) concentrations (up to 66 nM) in the euphotic layer, extending zonally over 10 degrees longitude (174 E−175 W) at ∼20°S latitude. DFe atmospheric fluxes were at the lower end of reported values of the remote ocean and could not explain the high DFe concentrations measured in the water column in the vicinity of Tonga. We argue that the high DFe concentrations may be sustained by a submarine source, also characterized by freshwater input and recorded as salinity anomalies by Argo float in situ measurements and atlas data. The observed negative salinity anomalies are reproduced by simulations from a general ocean circulation model. Submarine iron sources reaching the euphotic layer may impact nitrogen fixation across the whole region.

Abstract Seabirds concentrate nutrients from large marine areas on their nesting islands playing an important ecological role in nutrient transfer between marine and terrestrial ecosystems. Here we investigate the role of guano on corals reefs across scales by analyzing the stable nitrogen isotopic (δ15N) values of the scleractinian coral Pocillopora damicornis on fringing reefs around two Pacific remote islets with large seabird colonies. Marine stations closest to the seabird colonies had higher nitrate + nitrite concentrations compared to more distant stations. Coral and zooxanthellae δ15N values were also higher at these sites, suggesting that guano-derived nitrogen is assimilated into corals and contributes to their nitrogen requirements. The spatial extent of guano influence was however restricted to a local scale. Our results demonstrate that seabird-derived nutrients not only spread across the terrestrial ecosystem, but also affect components of the adjacent marine ecosystem. Further studies are now needed to assess if this nutrient input has a positive or negative effect for corals. Such studies on remote islets also open fresh perspectives to understand how nutrients affect coral reefs isolated from other anthropogenic stressors.

An underwater volcanic eruption off the Vava’u island group in Tonga on 7 August 2019 resulted in the creation of floating pumice on the ocean’s surface extending over an area of 150 km2. The pumice’s far-reaching effects from its origin in the Tonga region to Fiji and the methods of automatic detection using satellite imagery are described, making it possible to track the westward drift of the pumice raft over 43 days. Level 2 Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), Sentinel-3 Ocean and Land Color Instrument (OLCI), and Sentinel-3 Sea and Land Surface Temperature Radiometer (SLSTR) imagery of sea surface temperature, chlorophyll-a concentration, quasi-surface (i.e., Rayleigh-corrected) reflectance, and remote sensing reflectance were used to distinguish consolidated and fragmented rafts as well as discolored and mesotrophic waters. The rafts were detected by a 1 to 3.5 °C enhancement in the MODIS-derived “sea surface temperature” due to the emissivity difference of the raft material. Large plumes of discolored waters, characterized by higher satellite reflectance/backscattering of particles in the blue than surrounding waters (and corresponding to either submersed pumice or associated white minerals), were associated with the rafts. The discolored waters had relatively lower chlorophyll-a concentration, but this was artificial, resulting from the higher blue/red reflectance ratio caused by the reflective pumice particles. Mesotrophic waters were scarce in the region of the pumice rafts, presumably due to the absence of phytoplanktonic response to a silicium-rich pumice environment in these tropical oligotrophic environments. As beach accumulations around Pacific islands surrounded by coral shoals are a recurrent phenomenon that finds its origin far east in the ocean along the Tongan trench, monitoring the events from space, as demonstrated for the 7 August 2019 eruption, might help mitigate their potential economic impacts.

Arboviruses are viruses transmitted to humans by the bite of infected mosquito vectors. Over the last decade, arbovirus circulation has increasingly been detected in New Caledonia (NC), a French island territory located in the subtropical Pacific region. Reliable epidemiological, entomological, virological and climate data have been collected in NC over the last decade. Here, we describe these data and how they inform arboviruses’ epidemiological profile. We pinpoint areas which remain to be investigated to fully understand the peculiar epidemiological profile of arbovirus circulation in NC. Further, we discuss the advantages of conducting studies on arboviruses dynamics in NC. Overall, we show that conclusions drawn from observations conducted in NC may inform epidemiological risk assessments elsewhere and may be vital to guide surveillance and response, both in New Caledonia and beyond.

OBJECTIVE: To estimate the basic reproduction number (R0) of dengue fever including both imported and autochthonous cases. METHODS: The study was conducted based on epidemiological data of the 2003 dengue epidemic in Brasília, Brazil. The basic reproduction number is estimated from the epidemic curve, fitting linearly the increase of initial cases. Aiming at simulating an epidemic with both autochthonous and imported cases, a "susceptible-infectious-resistant" compartmental model was designed, in which the imported cases were considered as an external forcing. The ratio between R0 of imported versus autochthonous cases was used as an estimator of real R0. RESULTS: The comparison of both reproduction numbers (only autochthonous versus all cases) showed that considering all cases as autochthonous yielded a R0 above one, although the real R0 was below one. The same results were seen when the method was applied on simulated epidemics with fixed R0. This method was also compared to some previous proposed methods by other authors and showed that the latter underestimated R0 values. CONCLUSIONS: It was shown that the inclusion of both imported and autochthonous cases is crucial for the modeling of the epidemic dynamics, and thus provides critical information for decision makers in charge of prevention and control of this disease.OBJETIVO: Estimar el número de reproducción básica (R0) de la fiebre del dengue incluyendo casos importados y autóctonos. MÉTODOS: El estudio fue realizado basándose en datos epidemiológicos de la epidemia del dengue ocurrida en Brasilia, Districto Federal de Brasil, en el 2003. El número de reproducción básica es estimado de la curva epidémica, fijando el incremento lineal de los casos iniciales. Señalando casos importados y autóctonos en una simulación epidémica, fue diseñado un compartimiento "infeccioso-susceptible-resistente", en el cual los casos importados fueron considerados una fuerza externa. La tasa entre R0 de casos importados versus casos autóctonos fue usado como una estimación real de R0. RESULTADOS: La comparación de ambos números de reproducción (sólo autóctonos versus todos los casos) mostró que considerando todos los casos como autóctonos produjo un R0 por encima de uno, a pesar de que el valor real de R0 era menor que uno. Los mismos resultados fueron obtenidos cuando se aplicó el método a epidemias simuladas con valor fijo de R0. Este método fue también comparado con métodos propuestos anteriormente por otros autores y mostró los mismos valores subestimados de R0. CONCLUSIONES: Fue demostrado que la inclusión de casos importados y autóctonos es crucial para el modelaje de dinámicas epidémicas, y que provee información crítica para aquellos que participan en la toma de decisiones en la prevención y control de esta enfermedad.OBJETIVO: Estimar o número básico de reprodução da dengue (R0), com base nos casos importados, além dos casos autóctones. MÉTODOS: O estudo foi feito sobre dados epidemiológicos da epidemia de dengue em Brasília, 2003. O número básico de reprodução é determinado a partir da curva epidêmica, ajustando uma reta ao crescimento inicial do número de casos. Para simular uma epidemia com casos autóctones e importados, foi criado um modelo compartimentado do tipo "suscetíveis-infectados-resistentes". O R0 real foi estimado pela fração entre R0 dos casos autóctones e dos importados. RESULTADOS: A comparação de ambos valores de reprodução (apenas autóctones versus todos os casos) mostrou que considerando todos casos como autóctones, o valor de R0 foi superior a um, enquanto o R0 real era inferior a um. O mesmo resultado foi obtido com o conjunto de dados simulando uma epidemia com R0 fixo. O método foi também comparado a outros, observando-se que estes últimos subestimaram os valores do R0. CONCLUSÕES: A inclusão de tanto casos autóctones como os importados é essencial para modelar a dinâmica da epidemia, possibilitando informação crítica aos tomadores de decisão, responsáveis pelo controle da doença.