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International audienceAim Many attempts to predict the potential range of species rely on environmental niche (or 'bioclimate envelope') modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions, identify key reasons why model output may differ and discuss the implications that model uncertainty has for policy-guiding applications. Location The Western Cape of South Africa. Methods We applied nine of the most widely used modelling techniques to model potential distributions under current and predicted future climate for four species (including two subspecies) of Proteaceae. Each model was built using an identical set of five input variables and distribution data for 3996 sampled sites. We compare model predictions by testing agreement between observed and simulated distributions for the present day (using the area under the receiver operating characteristic curve (AUC) and kappa statistics) and by assessing consistency in predictions of range size changes under future climate (using cluster analysis). Results Our analyses show significant differences between predictions from different models, with predicted changes in range size by 2030 differing in both magnitude and direction (e.g. from 92% loss to 322% gain). We explain differences with reference to two characteristics of the modelling techniques: data input requirements (presence/absence vs. presence-only approaches) and assumptions made by each algorithm when extrapolating beyond the range of data used to build the model. The effects of these factors should be carefully considered when using this modelling approach to predict species ranges. Main Conclusions We highlight an important source of uncertainty in assessments of the impacts of climate change on biodiversity and emphasize that model predictions should be interpreted in policy-guiding applications along with a full appreciation of uncertainty

High-throughput DNA sequencing has the potential to accelerate species discovery if it is able to recognize evolutionary entities from sequence data that are comparable to species. The general mixed Yule-coalescent (GMYC) model estimates the species boundary from DNA surveys by identifying independently evolving lineages as a transition from coalescent to speciation branching patterns on a phylogenetic tree. Applied here to 12 families from 4 orders of insects in Madagascar, we used the model to delineate 370 putative species from mitochondrial DNA sequence variation among 1614 individuals. These were compared with data from the nuclear genome and morphological identification and found to be highly congruent (98% and 94%). We developed a modified GMYC that allows for a variable transition from coalescent to speciation among lineages. This revised model increased the congruence with morphology (97%), suggesting that a variable threshold better reflects the clustering of sequence data into biological species. Local endemism was pronounced in all 5 insect groups. Most species (60-91%) and haplotypes (88-99%) were found at only 1 of the 5 study sites (40-1000 km apart). This pronounced endemism resulted in a 37% increase in species numbers using diagnostic nucleotides in a population aggregation analysis. Sample sizes between 7 and 10 individuals represented a threshold above which there was minimal increase in genetic diversity, broadly agreeing with coalescent theory and other empirical studies. Our results from > 1.4 Mb of empirical data suggest that the GMYC model captures species boundaries comparable to those from traditional methods without the need for prior hypotheses of population coherence. This provides a method of species discovery and biodiversity assessment using single-locus data from mixed or environmental samples while building a globally available taxonomic database for future identifications.

The application of DNA barcoding to dietary studies allows prey taxa to be identified in the absence of morphological evidence and permits a greater resolution of prey identity than is possible through direct examination of faecal material. For insectivorous bats, which typically eat a great diversity of prey and which chew and digest their prey thoroughly, DNA-based approaches to diet analysis may provide the only means of assessing the range and diversity of prey within faeces. Here, we investigated the effectiveness of DNA barcoding in determining the diets of bat species that specialize in eating different taxa of arthropod prey. We designed and tested a novel taxon-specific primer set and examined the performance of short barcode sequences in resolving prey species. We recovered prey DNA from all faecal samples and subsequent cloning and sequencing of PCR products, followed by a comparison of sequences to a reference database, provided species-level identifications for 149/207 (72%) clones. We detected a phylogenetically broad range of prey while completely avoiding detection of nontarget groups. In total, 37 unique prey taxa were identified from 15 faecal samples. A comparison of DNA data with parallel morphological analyses revealed a close correlation between the two methods. However, the sensitivity and taxonomic resolution of the DNA method were far superior. The methodology developed here provides new opportunities for the study of bat diets and will be of great benefit to the conservation of these ecologically important predators.

BackgroundHigher-level relationships within the Lepidoptera, and particularly within the species-rich subclade Ditrysia, are generally not well understood, although recent studies have yielded progress. We present the most comprehensive molecular analysis of lepidopteran phylogeny to date, focusing on relationships among superfamilies.Methodology / Principal Findings483 taxa spanning 115 of 124 families were sampled for 19 protein-coding nuclear genes, from which maximum likelihood tree estimates and bootstrap percentages were obtained using GARLI. Assessment of heuristic search effectiveness showed that better trees and higher bootstrap percentages probably remain to be discovered even after 1000 or more search replicates, but further search proved impractical even with grid computing. Other analyses explored the effects of sampling nonsynonymous change only versus partitioned and unpartitioned total nucleotide change; deletion of rogue taxa; and compositional heterogeneity. Relationships among the non-ditrysian lineages previously inferred from morphology were largely confirmed, plus some new ones, with strong support. Robust support was also found for divergences among non-apoditrysian lineages of Ditrysia, but only rarely so within Apoditrysia. Paraphyly for Tineoidea is strongly supported by analysis of nonsynonymous-only signal; conflicting, strong support for tineoid monophyly when synonymous signal was added back is shown to result from compositional heterogeneity.Conclusions / SignificanceSupport for among-superfamily relationships outside the Apoditrysia is now generally strong. Comparable support is mostly lacking within Apoditrysia, but dramatically increased bootstrap percentages for some nodes after rogue taxon removal, and concordance with other evidence, strongly suggest that our picture of apoditrysian phylogeny is approximately correct. This study highlights the challenge of finding optimal topologies when analyzing hundreds of taxa. It also shows that some nodes get strong support only when analysis is restricted to nonsynonymous change, while total change is necessary for strong support of others. Thus, multiple types of analyses will be necessary to fully resolve lepidopteran phylogeny.

Globally, priority areas for biodiversity are relatively well known, yet few detailed plans exist to direct conservation action within them, despite urgent need. Madagascar, like other globally recognized biodiversity hot spots, has complex spatial patterns of endemism that differ among taxonomic groups, creating challenges for the selection of within-country priorities. We show, in an analysis of wide taxonomic and geographic breadth and high spatial resolution, that multitaxonomic rather than single-taxon approaches are critical for identifying areas likely to promote the persistence of most species. Our conservation prioritization, facilitated by newly available techniques, identifies optimal expansion sites for the Madagascar government's current goal of tripling the land area under protection. Our findings further suggest that high-resolution multitaxonomic approaches to prioritization may be necessary to ensure protection for biodiversity in other global hot spots.

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