Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula.

The major intention of the present study was to investigate whether an approach combining the use of niche-based palaeodistribution modeling and phylo-geography would support or modify hypotheses about the Quaternary distributional history derived from phylogeographic methods alone. Our study system comprised two closely related species of Alpine Primula. We used species distribution models based on the extant distribution of the species and last glacial maximum (LGM) climate models to predict the distribution of the two species during the LGM. Phylogeographic data were generated using amplified fragment length polymorphisms (AFLPs). In Primula hirsuta, models of past distribution and phylogeographic data are partly congruent and support the hypothesis of widespread nunatak survival in the Central Alps. Species distribution models (SDMs) allowed us to differentiate between alpine regions that harbor potential nunatak areas and regions that have been colonized from other areas. SDMs revealed that diversity is a good indicator for nunataks, while rarity is a good indicator for peripheral relict populations that were not source for the recolonization of the inner Alps. In P. daonensis, palaeo-distribution models and phylogeographic data are incongruent. Besides the uncertainty inherent to this type of modeling approach (e.g., relatively coarse 1-km grain size), disagreement of models and data may partly be caused by shifts of ecological niche in both species. Nevertheless, we demonstrate that the combination of palaeo-distribution modeling with phylogeographical approaches provides a more differentiated picture of the distributional history of species and partly supports (P. hirsuta) and partly modifies (P. daonensis and P. hirsuta) hypotheses of Quaternary distributional history. Some of the refugial area indicated by palaeodistribution models could not have been identified with phylogeographic data.

Impact of model complexity on cross-temporal transferability in Maxent species distribution models: An assessment using paleobotanical data

Maximum entropy modeling (Maxent) is a widely used algorithm for predicting species distributions across space and time. Properly assessing the uncertainty in such predictions is non-trivial and requires validation with independent datasets. Notably, model complexity (number of model parameters) remains a major concern in relation to overfitting and, hence, transferability of Maxent models. An emerging approach is to validate the cross-temporal transferability of model predictions using paleoecological data. In this study, we assess the effect of model complexity on the performance of Maxent projections across time using two European plant species (Alnus giutinosa (L.) Gaertn. and Corylus avellana L) with an extensive late Quaternary fossil record in Spain as a study case. We fit 110 models with different levels of complexity under present time and tested model performance using AUC (area under the receiver operating characteristic curve) and AlCc (corrected Akaike Information Criterion) through the standard procedure of randomly partitioning current occurrence data. We then compared these results to an independent validation by projecting the models to mid-Holocene (6000 years before present) climatic conditions in Spain to assess their ability to predict fossil pollen presence-absence and abundance. We find that calibrating Maxent models with default settings result in the generation of overly complex models. While model performance increased with model complexity when predicting current distributions, it was higher with intermediate complexity when predicting mid-Holocene distributions. Hence, models of intermediate complexity resulted in the best trade-off to predict species distributions across time. Reliable temporal model transferability is especially relevant for forecasting species distributions under future climate change. Consequently, species-specific model tuning should be used to find the best modeling settings to control for complexity, notably with paleoecological data to independently validate model projections. For cross-temporal projections of species distributions for which paleoecological data is not available, models of intermediate complexity should be selected.

Prevalence of ragweed allergy in rural Geneva - a pilot study.

OBJECTIVE: The prevalence of ragweed allergy is increasing worldwide. Ragweed distribution and abundance is spreading in Europe in a wide area ranging from the Rhone valley in France to Hungary and Ukraine, where the rate of the prevalence can peak at as high as 12%. Low-grade ragweed colonisation was seen in Geneva and Ticino, less than two decades ago. There were fears that allergies to ragweed would increase Switzerland. The intent of this study was to assess the rate of prevalence of sensitisation and allergy to ragweed in the population living in the first rural Swiss setting where ragweed had been identified in 1996, and to evaluate indirectly the efficacy of elimination and containment strategies. MATERIAL AND METHODS: In 2009, 35 adults in a rural village in the Canton of Geneva were recruited. Data were collected by means of questionnaires and skin-prick tests were done on each participant. The study was approved by the local Ethics Committee. RESULTS: Based on questionnaires, 48.6% had rhinitis (95% confidence interval [CI] 32.9-64.4; n = 17/35) and 17.1% asthma (95% CI 8.1-32.6; n = 6/35). Atopy was diagnosed in 26.4% (95% CI 12.9-44.4) of the sample (n = 9/34). Ragweed sensitisation was found in 2.9% (95% CI 0.7-19.7; n = 1/34), mugwort sensitisation in 2.9% (95% CI 0.1-14.9; n = 1/35), alder sensitisation in 17.1% (95% CI 6.6-33.6; n = 6/35), ash sensitisation in 12.5% (95% CI 3.5-29.0; n = 4/32) and grass sensitisation in 22.9% (95% CI 10.4-40.1; n = 8/35). Ragweed (95% CI 0.1-14.9; n = 1/34) and mugwort allergies (95% CI 0.1-14.9; n = 1/35) were both found in 2.9% of the population. CONCLUSION: This study showed a surprisingly low incidence of ragweed sensitisation and allergy, of 2.9% and 2.9%, respectively, 20 years after the first ragweed detection in Geneva. The feared rise in ragweed allergy seems not to have happened in Switzerland, compared with other ragweed colonised countries. These results strongly support early field strategies against ragweed.