Species distribution models (SDMs) represent a widely acknowledged tool to identify priority areas on the basis of occurrence data and environmental factors. However, high levels of topographical and climatic micro-variation are a hindrance to reliably modelling the distribution of narrow-endemic species when based on classic occurrence and climate datasets. Here, we used high-resolution environmental variables and occurrence data obtained from dedicated field studies to produce accurate SDMs at a local scale. We modelled the potential current distribution of 23 of the 25 rarest species from Mount Kaala, a hotspot of narrow-endemism in New Caledonia, using occurrence data from two recent sampling campaigns, and eight high-resolution (10 m and 30 m) environmental predictors in a Species Distribution Modelling framework. After a first sampling operation, we surveyed six additional areas containing, overall, 13 of the 20 species modelled at this stage, to validate our projections where the highest species richness levels were predicted. The ability of our method to define conservation areas was largely validated with an average 84% of predicted species found in the validation areas, and additional data collected enabling us to model three more species. We therefore identified the areas of highest conservation value for the whole of Mount Kaala. Our results support the ability of SDMs based on presence-only data such as MaxEnt to predict areas of high conservation value using fine-resolution environmental layers and field-collected occurrence data in the context of small and heterogeneous systems such as tropical islands.

Premise of the study:High-throughput sequencing of genomic DNA can recover complete chloroplast genome sequences, but the sequence data are usually dominated by sequences from nuclear/mitochondrial genomes. To overcome this deficiency, a simple enrichment method for chloroplast DNA from small amounts of plant tissue was tested for eight plant species including a gymnosperm and various angiosperms.Methods:Chloroplasts were enriched using a high-salt isolation buffer without any step gradient procedures, and enriched chloroplast DNA was sequenced by multiplexed high-throughput sequencing.Results:Using this simple method, significant enrichment of chloroplast DNA-derived reads was attained, allowing deep sequencing of chloroplast genomes. As an example, the chloroplast genome of the conifer Callitris sulcata was assembled, from which polymorphic microsatellite loci were isolated successfully.Discussion:This chloroplast enrichment method from small amounts of plant tissue will be particularly useful for studies that use sequencers with relatively small throughput and that cannot use large amounts of tissue (e.g., for endangered species).

HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

The genus Lagenophora Cass. is taxonomically revised for New Caledonia with two species recognised. Lagenophora sinuosa Lannuzel, Gâteblé & Jian Wang ter, sp. nov. is endemic to New Caledonia and the other, L. sublyrata (Cass.) A.R.Bean & Jian Wang ter occurs there and in many other countries from the region. Both are fully described and illustrated. An identification key is provided, as are notes on the distribution (including maps), habitat, phenology and conservation status. The generic placement of the new species is also discussed.

Conservation efforts in global biodiversity hotspots often face a common predicament: an urgent need for conservation action hampered by a significant lack of knowledge about that biodiversity. In recent decades, the computerisation of primary biodiversity data worldwide has provided the scientific community with raw material to increase our understanding of the shared natural heritage. These datasets, however, suffer from a lot of geographical and taxonomic inaccuracies. Automated tools developed to enhance their reliability have shown that detailed expert examination remains the best way to achieve robust and exhaustive datasets. In New Caledonia, one of the most important biodiversity hotspots worldwide, the plant diversity inventory is still underway, and most taxa awaiting formal description are narrow endemics, hence by definition hard to discern in the datasets. In the meantime, anthropogenic pressures, such as nickel-ore mining, are threatening the unique ultramafic ecosystems at an increasing rate. The conservation challenge is therefore a race against time, as the rarest species must be identified and protected before they vanish. In this study, based on all available datasets and resources, we applied a workflow capable of highlighting the lesser known taxa. The main challenges addressed were to aggregate all data available worldwide, and tackle the geographical and taxonomic biases, avoiding the data loss resulting from automated filtering. Every doubtful specimen went through a careful taxonomic analysis by a local and international taxonomist panel. Geolocation of the whole dataset was achieved through dataset cross-checking, local botanists’ field knowledge, and historical material examination. Field studies were also conducted to clarify the most unresolved taxa. With the help of this method and by analysing over 85,000 data, we were able to double the number of known narrow endemic taxa, elucidate 68 putative new species, and update our knowledge of the rarest species’ distributions so as to promote conservation measures.