Low dispersing species : population genetic processes in space and time : the genus "Trochulus" (Gastropoda: Hygromiidae) as a case study

RÉSUMÉ Une espèce est rarement composée d'une population unique. Parce que les individus ont des capacités de dispersion limitées et que les paysages sont des mosaïques d'habitats, la plupart des espèces sont plutôt composées de sous-populations connectées par la migration. Cette variation spatiale influence directement la distribution de la variabilité génétique dans et entre les populations. Durant ce travail, nous avons abordé certains des processus populationnels qui ont joué un rôle supposé dans l'apparition de nouvelles espèces au sein du genre Trochulus. Plus précisément, nous avons tenté d'évaluer les impacts respectifs de l'isolement passé (facteurs historiques) et présent (facteurs locaux). Nous avons d'abord pu montrer que les faibles capacités de dispersion des escargots terrestres ont directement influencé leur histoire évolutive à toutes les échelles spatiales et temporelles. En réduisant l'effet homogénéisant de la migration, une faible dispersion maintient dans les populations les traces génétiques d'évènements passés. A l'échelle de la distribution globale de Trochulus villosus, ces traces ont permis de reconstruire une histoire faite d'isolements et d'expansions de populations. En combinant des données génétiques avec une modélisation de la niche climatique passée, il a été possible de proposer un scénario significativement meilleur que toutes les hypothèses alternatives que nous avons testées. A l'échelle locale par contre, l'héritage historique est difficile à distinguer de la dynamique actuelle. Ce fut le cas des lignées mitochondriales du complexe sericeus-hispidus : les deux principales lignées étaient phylogénétiquement éloignées, avaient eu des démographies passées différentes et corrélaient avec des différences morphologiques. D'un autre côté, le flux de gène nucléaire était fort, contredisant l'idée de deux espèces cryptiques isolées reproductivement. Pour pouvoir conclure à la présence ou non de deux espèces, il nous a manqué des informations locales sur la dynamique des populations et les conditions écologiques que l'on trouve dans la région d'étude. Enfin, nous avons pu souligner que la connectivité entre populations d'escargots est soumise à la qualité des habitats et à leur organisation spatiale. Les escargots sont dépendants d'un habitat et s'y adaptent, comme l'indiquent la présence de «poils » uniquement sur la coquille d'espèces vivant dans des habitats humides ou la corrélation entre morphologie et habitat au sein du complexe sericeus-hispidus. Logiquement donc, les escargots migrent préférentiellement au travers d'habitats favorables comme l'a montré la réduction de flux de gènes au travers des prairies chez T. villosus (une espèce forestière). De ces données, nous pouvons supposer que les populations d'escargots en particulier, et des espèces à faible dispersion en général, ont de fortes chances d'être affectées par les changements climatiques, avec de probables implications pour leurs histoires évolutives. SUMMARY : Species rarely consists in a single population. Because individuals have limited dispersal abilities, because landscapes are habitat patchworks, most species are made of several subpopulations connected by migration. This spatial variation has consequences on the distribution of genetic diversity within and between populations, creating a structure among the populations. During the present work, we investigated some of the population processes assumed to have played an important role on the speciation within the genus Trochulus. More specifically, we questioned the respective impacts of past (historical factors) or present (local factors) population isolations. We first could show that the poor dispersal abilities of land snails have had profound impacts on their evolutionary histories at all spatial and temporal scales. Low dispersal maintains a strong signature of past events in the populations by minimising the homogenising effects of geneflow. At the scale of Trochulus villosus global distribution, they allowed to retrieve the detailed history of this species population isolations and expansions. Combining a large genetic dataset with paleo-climatic niche modelling ended up with a historical scenario significantly better than all traditional alternatives we tested. At local scale on the contrary, past events become difficult to tease apart from ongoing processes. This was the case for the divergent mitochondria) lineages within the sericeus-hispidus complex: the two principal lineages appeared to be phylogenetically distant, to have experienced different demographic histories and to correlate with morphological differences. On the other hand, nuclear (present day) geneflow was high, contradicting the idea of two reproductively isolated cryptic species. Information on the local population dynamics and environmental conditions are lacking to be able to decide whether past isolation has indeed resulted here in new species. Finally, we emphasised the importance of the habitat types present in a landscape as well as their spatial organisation for the population connectivity of land snails. These species are tightly dependent on a habitat and adapt to it as shown by thé occurrence of hair-like structures only in species living in humid environments or by the correlation between shell morphology and habitat in the sericeus-hispidus complex. As a result, land snails preferentially migrate through favourable habitats: Trochulus villosus, a forest species, had its geneflow significantly reduced across meadows. From these data, we can hypothesise that the populations of land snails in particular and of low dispersing species in general are likely to be strongly affected by the ongoing climate changes, with potential major consequences on their evolutionary histories.

Disaster Risk, Livelihoods and Natural Barriers, Strengthening Decision-Making Tools for Disaster Risk Reduction: A case study from northern Pakistan

The goal of this interdisciplinary study is to better understand the land use factors that increase vulnerability of mountain areas in northern Pakistan. The study will identify and analyse the damages and losses caused by the October 2005 earthquake in two areas of the same valley: one "low-risk" watershed with sound natural resources management, the other, "high-risk" in an ecologically degraded watershed. Secondly, the study will examine natural and man-made causes of secondary hazards in the study area, especially landslides; and third it will evaluate the cost of the earthquake damage in the study areas on the livelihoods of local communities and the sub-regional economy. There are few interdisciplinary studies to have correlated community land use practices, resources management, and disaster risk reduction in high-risk mountain areas. By better understanding these linkages, development- humanitarian- and donor agencies focused on disaster reduction can improve their risk reduction programs for mountainous regions.

An evaluation of new parsimony-based versus parametric inference methods in biogeography: a case study using the globally distributed plant family Sapindaceae

Aim  Recently developed parametric methods in historical biogeography allow researchers to integrate temporal and palaeogeographical information into the reconstruction of biogeographical scenarios, thus overcoming a known bias of parsimony-based approaches. Here, we compare a parametric method, dispersal-extinction-cladogenesis (DEC), against a parsimony-based method, dispersal-vicariance analysis (DIVA), which does not incorporate branch lengths but accounts for phylogenetic uncertainty through a Bayesian empirical approach (Bayes-DIVA). We analyse the benefits and limitations of each method using the cosmopolitan plant family Sapindaceae as a case study.Location  World-wide.Methods  Phylogenetic relationships were estimated by Bayesian inference on a large dataset representing generic diversity within Sapindaceae. Lineage divergence times were estimated by penalized likelihood over a sample of trees from the posterior distribution of the phylogeny to account for dating uncertainty in biogeographical reconstructions. We compared biogeographical scenarios between Bayes-DIVA and two different DEC models: one with no geological constraints and another that employed a stratified palaeogeographical model in which dispersal rates were scaled according to area connectivity across four time slices, reflecting the changing continental configuration over the last 110 million years.Results  Despite differences in the underlying biogeographical model, Bayes-DIVA and DEC inferred similar biogeographical scenarios. The main differences were: (1) in the timing of dispersal events - which in Bayes-DIVA sometimes conflicts with palaeogeographical information, and (2) in the lower frequency of terminal dispersal events inferred by DEC. Uncertainty in divergence time estimations influenced both the inference of ancestral ranges and the decisiveness with which an area can be assigned to a node.Main conclusions  By considering lineage divergence times, the DEC method gives more accurate reconstructions that are in agreement with palaeogeographical evidence. In contrast, Bayes-DIVA showed the highest decisiveness in unequivocally reconstructing ancestral ranges, probably reflecting its ability to integrate phylogenetic uncertainty. Care should be taken in defining the palaeogeographical model in DEC because of the possibility of overestimating the frequency of extinction events, or of inferring ancestral ranges that are outside the extant species ranges, owing to dispersal constraints enforced by the model. The wide-spanning spatial and temporal model proposed here could prove useful for testing large-scale biogeographical patterns in plants.

Early detection of microcirculatory perfusion changes with a high resolution, real time laser Doppler imaging camera--frostbite case study.

A 41-year-old male presented with severe frostbite that was monitored clinically and with a new laser Doppler imaging (LDI) camera that records arbitrary microcirculatory perfusion units (1-256 arbitrary perfusion units (APU's)). LDI monitoring detected perfusion differences in hand and foot not seen visually. On day 4-5 after injury, LDI showed that while fingers did not experience any significant perfusion change (average of 31±25 APUs on day 5), the patient's left big toe did (from 17±29 APUs day 4 to 103±55 APUs day 5). These changes in regional perfusion were not detectable by visual examination. On day 53 postinjury, all fingers with reduced perfusion by LDI were amputated, while the toe could be salvaged. This case clearly demonstrates that insufficient microcirculatory perfusion can be identified using LDI in ways which visual examination alone does not permit, allowing prognosis of clinical outcomes. Such information may also be used to develop improved treatment approaches.

Emotional processing in a ten-session general psychiatric treatment for borderline personality disorder: a case study.

This study examines the effects of a borderline-specific treatment, called general psychiatric management, on emotional change, outcome and therapeutic alliance of an outpatient presenting with borderline personality disorder. Based on the sequential model of emotional processing, emotional states were assessed in a 10-session setting. The case showed an increase in expressions of distress and no change in therapeutic alliance and tended towards general deterioration. Results suggest emotional processing may play a lesser role in general psychiatric management in early phase treatment than previously hypothezised. Copyright © 2015 John Wiley & Sons, Ltd.

Statistical learning theory for geospatial data. Case study: Aral sea

In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).