Mass mortality events in atoll lagoons: environmental control and increased future vulnerability.

Coral reefs and lagoons worldwide are vulnerable environments. However, specific geomorphological reef types (fringing, barrier, atoll, bank for the main ones) can be vulnerable to specific disturbances that will not affect most other reefs. This has implications for local management and science priorities. Several geomorphologically closed atolls of the Pacific Ocean have experienced in recent decades mass benthic and pelagic lagoonal life mortalities, likely triggered by unusually calm weather conditions lasting for several weeks. These events, although poorly known, reported, and characterized, pose a major threat for resource sustainability. Based on a sample of eleven events on eight atolls from the central South Pacific occurring between 1993 and 2012, the conservative environmental thresholds required to trigger such events are identified using sea surface temperature, significant wave height and wind stress satellite data. Using these thresholds, spatial maps of potential risk are produced for the central South Pacific region, with the highest risk zone lying north of Tuamotu Archipelago. A regional climate model, which risk map compares well with observations over the recent period (r=0.97), is then used to downscale the projected future climate. This allows us to estimate the potential change in risk by the end of the 21st century and highlights a relative risk increase of up to 60% for the eastern Tuamotu atolls. However, the small sample size used to train the analysis led to the identification of conservative thresholds that overestimated the observed risk. The results of this study suggest that long-term monitoring of the biophysical conditions of the lagoons at risk would enable more precise identification of the physical thresholds and better understanding of the biological processes involved in these rare, but consequential, mass mortality events.

Climate-driven models of leptospirosis dynamics in tropical islands from three oceanic basins.

BACKGROUND: Leptospirosis 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 FINDINGS: We 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/SIGNIFICANCE: Climate 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.

Global hotspots for the occurrence of compound events.

Compound events (CEs) are weather and climate events that result from multiple hazards or drivers with the potential to cause severe socio-economic impacts. Compared with isolated hazards, the multiple hazards/drivers associated with CEs can lead to higher economic losses and death tolls. Here, we provide the first analysis of multiple multivariate CEs potentially causing high-impact floods, droughts, and fires. Using observations and reanalysis data during 1980-2014, we analyse 27 hazard pairs and provide the first spatial estimates of their occurrences on the global scale. We identify hotspots of multivariate CEs including many socio-economically important regions such as North America, Russia and western Europe. We analyse the relative importance of different multivariate CEs in six continental regions to highlight CEs posing the highest risk. Our results provide initial guidance to assess the regional risk of CE events and an observationally-based dataset to aid evaluation of climate models for simulating multivariate CEs.