Extracting Quantitative Information from Images Taken in the Wild: A Case Study of Two Vicariants of the Ophrys aveyronensis Species Complex

Characterising phenotypic differentiation is crucial to understand which traits are involved in population divergence and establish the evolutionary scenario underlying the speciation process. Species harbouring a disjunct spatial distribution or cryptic taxa suggest that scientists often fail to detect subtle phenotypic differentiation at first sight. We used image-based analyses coupled with a simple machine learning algorithm to test whether we could distinguish two vicariant population groups of an orchid species complex known to be difficult to tease apart based on morphological criteria. To assess whether these groups can be distinguished on the basis of their phenotypes, and to highlight the traits likely to be the most informative in supporting a putative differentiation, we (i) photographed and measured a set of 109 individuals in the field, (ii) extracted morphometric, colour, and colour pattern information from pictures, and (iii) used random forest algorithms for classification. When combined, field- and image-based information provided identification accuracy of 95%. Interestingly, the variables used by random forests to discriminate the groups were different from those suggested in the literature. Our results demonstrate the interest of field-captured pictures coupled with machine learning classification approaches to improve taxon identification and highlight candidate traits for further eco-evolutionary studies

Extracting Quantitative Information from Images Taken in the Wild: A Case Study of Two Vicariants of the Ophrys aveyronensis Species Complex

International audienceCharacterising phenotypic differentiation is crucial to understand which traits are involved in population divergence and establish the evolutionary scenario underlying the speciation process. Species harbouring a disjunct spatial distribution or cryptic taxa suggest that scientists often fail to detect subtle phenotypic differentiation at first sight. We used image-based analyses coupled with a simple machine learning algorithm to test whether we could distinguish two vicariant population groups of an orchid species complex known to be difficult to tease apart based on morphological criteria. To assess whether these groups can be distinguished on the basis of their phenotypes, and to highlight the traits likely to be the most informative in supporting a putative differentiation, we (i) photographed and measured a set of 109 individuals in the field, (ii) extracted morphometric, colour, and colour pattern information from pictures, and (iii) used random forest algorithms for classification. When combined, field- and image-based information provided identification accuracy of 95%. Interestingly, the variables used by random forests to discriminate the groups were different from those suggested in the literature. Our results demonstrate the interest of field-captured pictures coupled with machine learning classification approaches to improve taxon identification and highlight candidate traits for further eco-evolutionary studies

Epichloe fungal endophytes for grassland ecosystems

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Wild snapdragon plant pedigree sheds light on limited connectivity enhanced by higher migrant reproductive success in a fragmented landscape

Background: In contrast with historical knowledge, a recent view posits that a non-negligible proportion of populations thrive in a fragmented landscape. One underlying mechanism is the maintenance of functional connectivity, i.e., the net flow of individuals or their genes moving among suitable habitat patches. Alternatively, functional connectivity might be typically limited but enhanced by a higher reproductive success of migrants. Methods: We tested for this hypothesis in wild snapdragon plants inhabiting six patches separated by seawater in a fragmented Mediterranean scrubland landscape. We reconstructed their pedigree by using a parentage assignment method based on microsatellite genetic markers. We then estimated functional connectivity and the reproductive success of plants resulting from between-patch dispersal events. Results: We found that wild snapdragon plants thrived in this fragmented landscape, although functional connectivity between habitat patches was low (i.e. 2.9%). The progeny resulting from between-patch dispersal events had a higher reproductive success than residents. Conclusion: Our findings imply that low functional connectivity in a fragmented landscapes may have been enhanced by higher reproductive success after migration. This original mechanisms might be partly compensating the negative impact of fragmentation

Wild snapdragon plant pedigree sheds light on limited connectivity enhanced by higher migrant reproductive success in a fragmented landscape

Background: In contrast with historical knowledge, a recent view posits that a non-negligible proportion of populations might respond positively to habitat fragmentation. Populations might thrive in a fragmented landscape if functional connectivity, i.e., the net flow of individuals or their genes moving among suitable habitat patches, is not restricted. Alternatively, functional connectivity might be typically limited but enhanced by a higher reproductive success of migrants. Methods: We tested for this hypothesis in wild snapdragon plants inhabiting six patches separated by seawater in a fragmented Mediterranean scrubland landscape. We reconstructed their pedigree by using a parentage assignment method based on microsatellite genetic markers. We then estimated functional connectivity and the reproductive success of plants resulting from between-patch dispersal events. Results: We found that wild snapdragon plants thrived in this fragmented landscape, although functional connectivity between habitat patches was weak (i.e. 2.9%). The progeny resulting from between-patch dispersal events had a higher reproductive success than residents. Conclusion: Our findings expose a remarkable aspect of fragmented landscapes, where weak functional connectivity was enhanced by higher reproductive success after migration. This process might have the potential to compensate at least partly the negative impact of fragmentation

Subsurface Confinement: Evidence from Submariners of the Benefits of Mindfulness

International audienceObjectivesThe subsurface ballistic missile nuclear submarine (SSBN) is an extreme professional environment in which personnel are both isolated and confined during patrols, which can last longer than 2 months. This environment is known to degrade submariners’ mood and cognition.MethodsThis exploratory, empirical study followed a cohort of 24 volunteer submariners. Dispositional mindfulness was assessed with the Freiburg Mindfulness Inventory, in order to identify two groups (mindful and non-mindful) and compare change in emotional state, interoception, and health behaviors during the patrol.ResultsOverall, psychological health deteriorated during the patrol. However, mindful submariners demonstrated better psychological adaptation and interoception than the non-mindful group. This was associated with better subjective health behaviors (sleeping and eating).ConclusionsDispositional mindfulness appears to protect against the negative effects of long-term containment in a professional environment, such as a submarine patrol. Our work highlights that mindfulness may help individuals to cope with stress in such situations. Developing mindfulness could also be an important preventive healthcare measure during quarantine imposed by the outbreak of a serious infectious disease