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In this study, we present a spatially explicit bayesian model which is able to predict the distribution of potential fire ignition at a grid resolution of over the entire main island of New-Caledonia. This statistical model, when used in conjunction with a mechanistic fire model (FlamMap), is able to estimate the comparative and spatialized risk of fire impact on specific areas for specific issues such as biodiversity or erosion. The input data includes variables related to the physical environment such as the topography, climate, and some geographical indicators relating to human influences such as population density and type of land property. Flowchart computation for the specific cell i. The grey rectangles denote the input data, the trapezoids denote the intermediate indices and the rounded corners rectangles denote the integrated wildfire risk indices. The connection legends indicates the corresponding equations and below certain nodes a drawing describes an example related to the main variables and the associated area used. [ABSTRACT FROM AUTHOR]

Background: Dengue is a mosquito-borne virus that causes extensive morbidity and economic loss in many tropical and subtropical regions of the world. Often present in cities, dengue virus is rapidly spreading due to urbanization, climate change and increased human movements. Dengue cases are often heterogeneously distributed throughout cities, suggesting that small-scale determinants influence dengue urban transmission. A better understanding of these determinants is crucial to efficiently target prevention measures such as vector control and education. The aim of this study was to determine which socioeconomic and environmental determinants were associated with dengue incidence in an urban setting in the Pacific., Methodology: An ecological study was performed using data summarized by neighborhood (i.e. the neighborhood is the unit of analysis) from two dengue epidemics (2008-2009 and 2012-2013) in the city of Nouméa, the capital of New Caledonia. Spatial patterns and hotspots of dengue transmission were assessed using global and local Moran's I statistics. Multivariable negative binomial regression models were used to investigate the association between dengue incidence and various socioeconomic and environmental factors throughout the city., Principal Findings: The 2008-2009 epidemic was spatially structured, with clusters of high and low incidence neighborhoods. In 2012-2013, dengue incidence rates were more homogeneous throughout the city. In all models tested, higher dengue incidence rates were consistently associated with lower socioeconomic status (higher unemployment, lower revenue or higher percentage of population born in the Pacific, which are interrelated). A higher percentage of apartments was associated with lower dengue incidence rates during both epidemics in all models but one. A link between vegetation coverage and dengue incidence rates was also detected, but the link varied depending on the model used., Conclusions: This study demonstrates a robust spatial association between dengue incidence rates and socioeconomic status across the different neighborhoods of the city of Nouméa. Our findings provide useful information to guide policy and help target dengue prevention efforts where they are needed most.

The frequency of plant species introductions has increased in a highly connected world, modifying species distribution patterns to include areas outside their natural ranges. These introductions provide the opportunity to gain new insight into the importance of flowering phenology as a component of adaptation to a new environment. Three Coffea species, C. arabica, C. canephora (Robusta), and C. liberica, native to intertropical Africa have been introduced to New Caledonia. On this archipelago, a secondary contact zone has been characterized where these species coexist, persist, and hybridize spontaneously. We investigated the impact of environmental changes undergone by each species following its introduction in New Caledonia on flowering phenology and overcoming reproductive barriers between sister species. We developed species distribution models and compared both environmental envelopes and climatic niches between native and introduced hybrid zones. Flowering phenology was monitored in a population in the hybrid zone along with temperature and precipitation sequences recorded at a nearby weather station. The extent and nature of hybridization events were characterized using chloroplast and nuclear microsatellite markers. The three Coffea species encountered weak environmental suitability compared to their native ranges when introduced to New Caledonia, especially C. arabica and C. canephora. The niche of the New Caledonia hybrid zone was significantly different from all three species' native niches based on identity tests (I Similarity and D Schoener's Similarity Indexes). This area appeared to exhibit intermediate conditions between the native conditions of the three species for temperature-related variables and divergent conditions for precipitation-related ones. Flowering pattern in these Coffea species was shown to have a strong genetic component that determined the time between the triggering rain and anthesis (flower opening), specific to each species. However, a precipitation regime different from those in Africa was directly involved in generating partial flowering overlap between species and thus in allowing hybridization and interspecific gene flow. Interspecific hybrids accounted for 4% of the mature individuals in the sympatric population and occurred between each pair of species with various level of introgression. Adaptation to new environmental conditions following introduction of Coffea species to New Caledonia has resulted in a secondary contact between three related species, which would not have happened in their native ranges, leading to hybridization and gene flow.

Wildfire has been recognized as one of the most ubiquitous disturbance agents to impact on natural environments. In this study, our main objective was to propose a modeling approach to investigate the potential impact of wildfire on biodiversity. The method is illustrated with an application example in New Caledonia where conservation and sustainable biodiversity management represent an important challenge. Firstly, a biodiversity loss index, including the diversity and the vulnerability indexes, was calculated for every vegetation unit in New Caledonia and mapped according to its distribution over the New Caledonian mainland. Then, based on spatially explicit fire behavior simulations (using the FLAMMAP software) and fire ignition probabilities, two original fire risk assessment approaches were proposed: a one-off event model and a multi-event burn probability model. The spatial distribution of fire risk across New Caledonia was similar for both indices with very small localized spots having high risk. The patterns relating to highest risk are all located around the remaining sclerophyll forest fragments and are representing 0.012% of the mainland surface. A small part of maquis and areas adjacent to dense humid forest on ultramafic substrates should also be monitored. Vegetation interfaces between secondary and primary units displayed high risk and should represent priority zones for fire effects mitigation. Low fire ignition probability in anthropogenic-free areas decreases drastically the risk. A one-off event associated risk allowed localizing of the most likely ignition areas with potential for extensive damage. Emergency actions could aim limiting specific fire spread known to have high impact or consist of on targeting high risk areas to limit one-off fire ignitions. Spatially explicit information on burning probability is necessary for setting strategic fire and fuel management planning. Both risk indices provide clues to preserve New Caledonia hot spot of biodiversity facing wildfires.