Our results indicate that significant deviations from equal morph ratios not only affect plant reproductive success but also population genetic diversity of heterostylous plant species. Hence, when defining conservation measures for populations of heterostylous plant species, morph ratios should be considered as an important trait affecting their long-term population viability.

An idiogram construction following chromosome measurements is a versatile tool for cytological, cytogenetic and phylogenetic studies. The information on chromosome length, centromere index and position of cytogenetic landmarks along with modern techniques (e.g. genomic and fluorescence in situ hybridization, banding, chromosome painting) can help to shed light on genome constitution, chromosome rearrangements and evolution. While idiogram construction is a routine task there are only few freely available programs that can perform chromosome measurements and no software for simultaneous measuring of chromosome parameters, chromosomal landmark and FISH signal positions and idiogram construction. To fill this gap, we developed DRAWID (DRAWing IDiogram), java-based cross-platforming program for chromosome analysis and idiogram construction. DRAWID has number of advantages including a user-friendly interactive interface, possibility for simultaneous chromosome and FISH/GISH/banding signal measurement and idiogram drawing as well as number of useful functions facilitating the procedure of chromosome analysis. The output of the program is Microsoft XL table and publish-ready idiogram picture. DRAWID and the manual for its use are freely available on the website at: http://www.drawid.xyz

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The results are best interpreted from a "dynamic range" point of view in which the observed low levels of genetic diversity and high genetic differentiation in disjunct populations are best explained through historical processes, most likely the introduction of the species in medieval times. Lower levels of gene flow caused by the pronounced fragmentation of forests in Belgium may further have contributed to the genetic structure of P. officinalis in these disjunct populations.

Forests exhibit leaf-and ecosystem-level responses to environmental changes. Specifically, rising carbon dioxide (CO 2 ) levels over the past century are expected to have increased the intrinsic water-use efficiency (iWUE) of tropical trees while the ecosystem is gradually pushed into progressive nutrient limitation. Due to the longterm character of these changes, however, observational datasets to validate both paradigms are limited in space and time. In this study, we used a unique herbarium record to go back nearly a century and show that despite the rise in CO 2 concentrations, iWUE has decreased in central African tropical trees in the Congo Basin.Although we find evidence that points to leaf-level adaptation to increasing CO 2that is, increasing photosynthesis-related nutrients and decreasing maximum stomatal conductance, a decrease in leaf δ 13 C clearly indicates a decreasing iWUE over time. Additionally, the stoichiometric carbon to nitrogen and nitrogen to phosphorus ratios in the leaves show no sign of progressive nutrient limitation as they have remained constant since 1938, which suggests that nutrients have not increasingly limited productivity in this biome. Altogether, the data suggest that other environmental factors, such as increasing temperature, might have negatively affected net photosynthesis and consequently downregulated the iWUE. Results from this study reveal that the second largest tropical forest on Earth has responded differently to

This article documents the addition of 238 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Alytes dickhilleni, Arapaima gigas, Austropotamobius italicus, Blumeria graminis f. sp. tritici, Cobitis lutheri, Dendroctonus ponderosae, Glossina morsitans morsitans, Haplophilus subterraneus, Kirengeshoma palmata, Lysimachia japonica, Macrolophus pygmaeus, Microtus cabrerae, Mytilus galloprovincialis, Pallisentis (Neosentis) celatus, Pulmonaria officinalis, Salminus franciscanus, Thais chocolata and Zootoca vivipara. These loci were cross-tested on the following species: Acanthina monodon, Alytes cisternasii, Alytes maurus, Alytes muletensis, Alytes obstetricans almogavarii, Alytes obstetricans boscai, Alytes obstetricans obstetricans, Alytes obstetricans pertinax, Cambarellus montezumae, Cambarellus zempoalensis, Chorus giganteus, Cobitis tetralineata, Glossina fuscipes fuscipes, Glossina pallidipes, Lysimachia japonica var. japonica, Lysimachia japonica var. minutissima, Orconectes virilis, Pacifastacus leniusculus, Procambarus clarkii, Salminus brasiliensis and Salminus hilarii.

Hybridization is a creative evolutionary force, increasing genomic diversity and facilitating adaptation and even speciation. Hybrids often face significant challenges to establishment, including reduced fertility that arises from genomic incompatibilities between their parents. Whole-genome duplication in hybrids (allopolyploidy) can restore fertility, cause immediate phenotypic changes, and generate reproductive isolation. Yet the survival of polyploid lineages is uncertain, and few studies have compared the performance of recently formed allopolyploids and their parents under field conditions. Here, we use natural and synthetically produced hybrid and polyploid monkeyflowers ( Mimulus spp.) to study how polyploidy contributes to the fertility, reproductive isolation, phenotype, and performance of hybrids in the field. We find that polyploidization restores fertility and that allopolyploids are reproductively isolated from their parents. The phenotype of allopolyploids displays the classic gigas effect of whole-genome duplication, in which plants have larger organs and are slower to flower. Field experiments indicate that survival of synthetic hybrids before and after polyploidization is intermediate between that of the parents, whereas natural hybrids have higher survival than all other taxa. We conclude that hybridization and polyploidy can act as sources of genomic novelty, but adaptive evolution is key in mediating the establishment of young allopolyploid lineages.

Plant leaf stomata are the gatekeepers of the atmosphere–plant interface and are essential building blocks of land surface models as they control transpiration and photosynthesis. Although more stomatal trait data are needed to significantly reduce the error in these model predictions, recording these traits is time‐consuming, and no standardized protocol is currently available. Some attempts were made to automate stomatal detection from photomicrographs; however, these approaches have the disadvantage of using classic image processing or targeting a narrow taxonomic entity which makes these technologies less robust and generalizable to other plant species. We propose an easy‐to‐use and adaptable workflow from leaf to label. A methodology for automatic stomata detection was developed using deep neural networks according to the state of the art and its applicability demonstrated across the phylogeny of the angiosperms. We used a patch‐based approach for training/tuning three different deep learning architectures. For training, we used 431 micrographs taken from leaf prints made according to the nail polish method from herbarium specimens of 19 species. The best‐performing architecture was tested on 595 images of 16 additional species spread across the angiosperm phylogeny. The nail polish method was successfully applied in 78% of the species sampled here. The VGG19 architecture slightly outperformed the basic shallow and deep architectures, with a confidence threshold equal to 0.7 resulting in an optimal trade‐off between precision and recall. Applying this threshold, the VGG19 architecture obtained an average F‐score of 0.87, 0.89, and 0.67 on the training, validation, and unseen test set, respectively. The average accuracy was very high (94%) for computed stomatal counts on unseen images of species used for training. The leaf‐to‐label pipeline is an easy‐to‐use workflow for researchers of different areas of expertise interested in detecting stomata more efficiently. The described methodology was based on multiple species and well‐established methods so that it can serve as a reference for future work.