Malaria: une espèce en voie de disparition [Malaria: an endangered species?].

The implementation at scale of preventive measures and the use of effective treatments in populations living in endemic areas has led to a drastic reduction of the burden of malaria in all continents. The considerable investment of international agencies to support local governments in the fight against malaria allows hoping to achieve the millennium goals for malaria and child mortality in several countries. Malaria elimination, and even eradication becomes a realistic objective, especially so because a vaccine may be soon available to complement the armamentarium. For travelers, the tendency will be to reduce the number of countries where chemoprophylaxis or stand-by treatment is recommended and to insist on the rigorous use of measures to prevent mosquito bites such as repellents and insecticide-impregnated bednets.

An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data

1. Few examples of habitat-modelling studies of rare and endangered species exist in the literature, although from a conservation perspective predicting their distribution would prove particularly useful. Paucity of data and lack of valid absences are the probable reasons for this shortcoming. Analytic solutions to accommodate the lack of absence include the ecological niche factor analysis (ENFA) and the use of generalized linear models (GLM) with simulated pseudo-absences. 2. In this study we tested a new approach to generating pseudo-absences, based on a preliminary ENFA habitat suitability (HS) map, for the endangered species Eryngium alpinum. This method of generating pseudo-absences was compared with two others: (i) use of a GLM with pseudo-absences generated totally at random, and (ii) use of an ENFA only. 3. The influence of two different spatial resolutions (i.e. grain) was also assessed for tackling the dilemma of quality (grain) vs. quantity (number of occurrences). Each combination of the three above-mentioned methods with the two grains generated a distinct HS map. 4. Four evaluation measures were used for comparing these HS maps: total deviance explained, best kappa, Gini coefficient and minimal predicted area (MPA). The last is a new evaluation criterion proposed in this study. 5. Results showed that (i) GLM models using ENFA-weighted pseudo-absence provide better results, except for the MPA value, and that (ii) quality (spatial resolution and locational accuracy) of the data appears to be more important than quantity (number of occurrences). Furthermore, the proposed MPA value is suggested as a useful measure of model evaluation when used to complement classical statistical measures. 6. Synthesis and applications. We suggest that the use of ENFA-weighted pseudo-absence is a possible way to enhance the quality of GLM-based potential distribution maps and that data quality (i.e. spatial resolution) prevails over quantity (i.e. number of data). Increased accuracy of potential distribution maps could help to define better suitable areas for species protection and reintroduction.

A multi-temporal approach to model endangered species distribution in Europe: the case of the Eurasian otter in Italy

We analysed the relationship between changes in land cover patterns and the Eurasian otter occurrence over the course of about 20 years (1985-2006) using multi-temporal Species Distribution Models (SDMs). The study area includes five river catchments covering most of the otter's Italian range. Land cover and topographic data were used as proxies of the ecological requirements of the otter within a 300-m buffer around river courses. We used species presence, pseudo-absence data, and environmental predictors to build past (1985) and current (2006) SDMs by applying an ensemble procedure through the BIOMOD modelling package. The performance of each model was evaluated by measuring the area under the curve (AUC) of the receiver-operating characteristic (ROC). Multi-temporal analyses of species distribution and land cover maps were performed by comparing the maps produced for 1985 and 2006. The ensemble procedure provided a good overall modelling accuracy, revealing that elevation and slope affected the otter's distribution in the past; in contrast, land cover predictors, such as cultivations and forests, were more important in the present period. During the transition period, 20.5% of the area became suitable, with 76% of the new otter presence data being located in these newly available areas. The multi-temporal analysis suggested that the quality of otter habitat improved in the last 20 years owing to the expansion of forests and to the reduction of cultivated fields in riparian belts. The evidence presented here stresses the great potential of riverine habitat restoration and environmental management for the future expansion of the otter in Italy

Predicting the impacts of climate change on genetic diversity in an endangered lizard species.

Many endangered species persist as a series of isolated populations, with some populations more genetically diverse than others. If climate change disproportionately threatens the most diverse populations, the species' ability to adapt (and hence its long-term viability) may be affected more severely than would be apparent by its numerical reduction. In the present study, we combine genetic data with modelling of species distributions under climate change to document this situation in an endangered lizard (Eulamprus leuraensis) from montane southeastern Australia. The species is known from only about 40 isolated swamps. Genetic diversity of lizard populations is greater in some sites than others, presumably reflecting consistently high habitat suitability over evolutionary time. Species distribution modelling suggests that the most genetically diverse populations are the ones most at risk from climate change, so that global warming will erode the species' genetic variability faster than it curtails the species' geographic distribution.

Genetic identity of the critically endangered Wimmer's shrew Crocidura wimmeri

Coastal primary rainforests have suffered damage in Côte d'Ivoire as a result of a lack of protection and urban pressures. Consequently, the highly endemic and critically endangered Wimmer's shrew, Crocidura wimmeri, known only from its type locality, Adiopodoumé, near Abidjan, was considered to have been extinct since 1976. Shrew species assignment is often problematic because of strong phenotypic similarities among many species. The phylogenetic position of C. wimmeri within the African Crocidura species should thus be clarified. In light of its recent rediscovery in the nearby small Banco National Park (34 km2), we investigated the genetic identity of seven specimens of C. wimmeri, based on 1020 bp of the mitochondrial DNA cytochrome b gene compared to other species sampled in the same region and published sequences from GenBank. Crocidura wimmeri formed a well-defined clade, the closest-related species being Crocidura sp., with a distance of 9.3%, a yet unknown species from Taï and Ziama forests. These results thus confirmed the validity of this species. This genetic characterization not only contributes to our knowledge of the evolution of West African shrews, but also may help in the discovery of additional populations of this critically endangered species.

Modelling habitat-suitability using museum collections: an example with three sympatric Apodemus species from the Alps

Aim, Location Although the alpine mouse Apodemus alpicola has been given species status since 1989, no distribution map has ever been constructed for this endemic alpine rodent in Switzerland. Based on redetermined museum material and using the Ecological-Niche Factor Analysis (ENFA), habitat-suitability maps were computed for A. alpicola, and also for the co-occurring A. flavicollis and A. sylvaticus. Methods In the particular case of habitat suitability models, classical approaches (GLMs, GAMs, discriminant analysis, etc.) generally require presence and absence data. The presence records provided by museums can clearly give useful information about species distribution and ecology and have already been used for knowledge-based mapping. In this paper, we apply the ENFA which requires only presence data, to build a habitat-suitability map of three species of Apodemus on the basis of museum skull collections. Results Interspecific niche comparisons showed that A. alpicola is very specialized concerning habitat selection, meaning that its habitat differs unequivocally from the average conditions in Switzerland, while both A. flavicollis and A. sylvaticus could be considered as 'generalists' in the study area. Main conclusions Although an adequate sampling design is the best way to collect ecological data for predictive modelling, this is a time and money consuming process and there are cases where time is simply not available, as for instance with endangered species conservation. On the other hand, museums, herbariums and other similar institutions are treasuring huge presence data sets. By applying the ENFA to such data it is possible to rapidly construct a habitat suitability model. The ENFA method not only provides two key measurements regarding the niche of a species (i.e. marginality and specialization), but also has ecological meaning, and allows the scientist to compare directly the niches of different species.

Adapting global conservation strategies to climate change at the European scale: the otter as a flagship species

Climate change has created the need for new strategies in conservation planning that account for the dynamics of factors threatening endangered species. Here we assessed climate change threat to the European otter, a flagship species for freshwater ecosystems, considering how current conservation areas will perform in preserving the species in a climatically changed future. We used an ensemble forecasting approach considering six modelling techniques applied to eleven subsets of otter occurrences across Europe. We performed a pseudo-independent and an internal evaluation of predictions. Future projections of species distribution were made considering the A2 and B2 scenarios for 2080 across three climate models: CCCMA-CGCM2, CSIRO-MK2 and HCCPR HAD-CM3. The current and the predicted otter distributions were used to identify priority areas for the conservation of the species, and overlapped to existing network of protected areas. Our projections show that climate change may profoundly reshuffle the otter's potential distribution in Europe, with important differences between the two scenarios we considered. Overall, the priority areas for conservation of the otter in Europe appear to be unevenly covered by the existing network of protected areas, with the current conservation efforts being insufficient in most cases. For a better conservation, the existing protected areas should be integrated within a more general conservation and management strategy incorporating climate change projections. Due to the important role that the otter plays for freshwater habitats, our study further highlights the potential sensitivity of freshwater habitats in Europe to climate change.

Predicting species distributions for conservation decisions.

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of 'translators' between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.

Viability and Management of an Endangered Capercaillie (Tetrao urogallus) Metapopulation in the Jura Mountains, Western Switzerland

The populations of Capercaillie (Tetrao urogallus), the largest European grouse, have seriously declined during the last century over most of their distribution in western and central Europe. In the Jura mountains, the relict population is now isolated and critically endangered (about 500 breeding adults). We developed a simulation software (TetrasPool) that accounts for age and spatial structure as well as stochastic processes, to perform a viability analysis and explore management scenarios for this population, capitalizing on a 24 years-long series of field data. Simulations predict a marked decline and a significant extinction risk over the next century, largely due to environmental and demographic stochasticity (average values of life-history parameters would otherwise allow stability). Variances among scenarios mainly stem from uncertainties about the shape and intensity of density dependence. Uncertainty analyses suggest to focus conservation efforts on enhancing, not only adult survival (as often advocated for long-lived species), but also recruitment. The juvenile stage matters when local populations undergo extinctions, because it ensures connectivity and recolonization. Besides limiting human perturbations, a silvicultural strategy aimed at opening forest structure should improve the quality and surface of available patches, independent of their size and localization. Such measures are to be taken urgently, if the population is to be saved.

Rarity types among plant species with high conservation priority in Switzerland

We investigated the ecogeographic characteristics of 118 Swiss plant species listed as those deserving highest conservation priority in a national conservation guide and classified them into the seven Rabinowitz' rarity types, taking geographic distribution, habitat rarity and local population size into account. Our analysis revealed that species with high conservation priority in Switzerland mostly have a very restricted geographic distribution in Switzerland and generally occur in rare habitats, but do not necessarily constitute small populations and are generally not endemics on a global scale. Moreover, species that are geographically very restricted on a regional scale are not generally restricted on a global scale. By analysing relationships between rarity and IUCN extinction risks for Switzerland, we demonstrated that species with the highest risk of extinction are those with the most restricted geographic distribution; whereas species with lower risk of extinction (but still high conservation priority) include many regional endemics. Habitat rarity and local population size appeared to be of minor importance for the assessment of extinction risk in Switzerland, but the total number of fulfilled rarity criteria still correlated positively with the severity of extinction risk. Our classification is the first preliminary assessment of the relative importance of each rarity type among endangered plant species of the Swiss flora and our results underline the need to distinguish between a regional and a global responsibility for the conservation of rare and endangered species.

Modelling the influence of change in fire regime on the local distribution of a Mediterranean pyrophytic plant species (Cistus salviifolius) at its northern range limit

Aims: To assess the potential distribution of an obligate seeder and active pyrophyte, Cistus salviifolius, a vulnerable species in the Swiss Red List; to derive scenarios by changing the fire return interval; and to discuss the results from a conservation perspective. A more general aim is to assess the impact of fire as a natural factor influencing the vegetation of the southern slopes of the Alps. Locations: Alps, southern Switzerland. Methods: Presence-absence data to fit the model were obtained from the most recent field mapping of C. salviifolius. The quantitative environmental predictors used in this study include topographic, climatic and disturbance (fire) predictors. Models were fitted by logistic regression and evaluated by jackknife and bootstrap approaches. Changes in fire regime were simulated by increasing the time-return interval of fire (simulating longer periods without fire). Two scenarios were considered: no fire in the past 15 years; or in the past 35 years. Results: Rock cover, slope, topographic position, potential evapotranspiration and time elapsed since the last fire were selected in the final model. The Nagelkerke R-2 of the model for C. salviifolius was 0.57 and the Jackknife area under the curve evaluation was 0.89. The bootstrap evaluation revealed model robustness. By increasing the return interval of fire by either up to 15 years, or 35 years, the modelled C. salviifolius population declined by 30-40%, respectively. Main conclusions: Although fire plays a significant role, topography and rock cover appear to be the most important predictors, suggesting that the distribution of C. salviifolius in the southern Swiss Alps is closely related to the availability of supposedly competition-free sites, such as emerging bedrock, ridge locations or steep slopes. Fire is more likely to play a secondary role in allowing C. salviifolius to extend its occurrence temporarily, by increasing germination rates and reducing the competition from surrounding vegetation. To maintain a viable dormant seed bank for C. salviifolius, conservation managers should consider carrying out vegetation clearing and managing wild fire propagation to reduce competition and ensure sufficient recruitment for this species.

Population demography of an endangered lizard, the Blue Mountains Water Skink.

BACKGROUND: Information on the age structure within populations of an endangered species can facilitate effective management. The Blue Mountains Water Skink (Eulamprus leuraensis) is a viviparous scincid lizard that is restricted to < 40 isolated montane swamps in south-eastern Australia. We used skeletochronology of phalanges (corroborated by mark-recapture data) to estimate ages of 222 individuals from 13 populations. RESULTS: These lizards grow rapidly, from neonatal size (30 mm snout-vent length) to adult size (about 70 mm SVL) within two to three years. Fecundity is low (mean 2.9 offspring per litter) and is affected by maternal body length and age. Offspring quality may decline with maternal age, based upon captive-born neonates (older females gave birth to slower offspring). In contrast to its broadly sympatric (and abundant) congener E. tympanum, E. leuraensis is short-lived (maximum 6 years, vs 15 years for E. tympanum). Litter size and offspring size are similar in the two species, but female E. leuraensis reproduce annually whereas many E. tympanum produce litters biennially. Thus, a low survival rate (rather than delayed maturation or low annual fecundity) is the key reason why E. leuraensis is endangered. Our 13 populations exhibited similar growth rates and population age structures despite substantial variation in elevation, geographic location and swamp size. However, larger populations (based on a genetic estimate of effective population size) contained older lizards, and thus a wider variance in ages. CONCLUSION: Our study suggests that low adult survival rates, as well as specialisation on a rare and fragmented habitat type (montane swamps) contribute to the endangered status of the Blue Mountains Water Skink.

Overcoming limitations of modelling rare species by using ensembles of small models

1. Species distribution models (SDMs) have become a standard tool in ecology and applied conservation biology. Modelling rare and threatened species is particularly important for conservation purposes. However, modelling rare species is difficult because the combination of few occurrences and many predictor variables easily leads to model overfitting. A new strategy using ensembles of small models was recently developed in an attempt to overcome this limitation of rare species modelling and has been tested successfully for only a single species so far. Here, we aim to test the approach more comprehensively on a large number of species including a transferability assessment. 2. For each species numerous small (here bivariate) models were calibrated, evaluated and averaged to an ensemble weighted by AUC scores. These 'ensembles of small models' (ESMs) were compared to standard Species Distribution Models (SDMs) using three commonly used modelling techniques (GLM, GBM, Maxent) and their ensemble prediction. We tested 107 rare and under-sampled plant species of conservation concern in Switzerland. 3. We show that ESMs performed significantly better than standard SDMs. The rarer the species, the more pronounced the effects were. ESMs were also superior to standard SDMs and their ensemble when they were independently evaluated using a transferability assessment. 4. By averaging simple small models to an ensemble, ESMs avoid overfitting without losing explanatory power through reducing the number of predictor variables. They further improve the reliability of species distribution models, especially for rare species, and thus help to overcome limitations of modelling rare species.

Analyse des risques d'extinction des populations naturelles

A review of extinction risk analysis and viability methods is presented. The importance of environmental, demographic and genetic uncertainties, as well as the role of catastrophes are successively considered, and different approaches aiming at the integration of these risk factors in predictive population dynamic models are discussed.