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The Nile tilapia (Oreochromis niloticus) is the second-most economically important fish species in East African countries (EAC), surpassed only by the Nile perch (Lates niloticus). It is the most-farmed freshwater fish species in EAC and the second-most-farmed worldwide. Currently, in EAC, through direct stocking activities and likely indirectly via aquaculture escapees, Nile tilapia are present in waterbodies where it is not native and where it is thought to have contributed to the fish biodiversity loss observed in recent decades. Introduced Nile tilapia may hybridise with native, congeneric species, promoting genetic introgression that can be detrimental to the sustainability of biodiversity. Moreover, the translocation dynamics and escapes from aquaculture can contribute to artificial geneflow between Nile tilapia stocks, compromising their gene pool and the sustainability of the species as a fishery resource. In the current work, we review some examples of these phenomena in EAC. Additionally, we explore the importance of collecting genetic data to define baseline knowledge for native and non-native Nile tilapia populations that can be used in monitoring programmes for development, management and conservation of tilapia genetic resources.

Summer pasture grazing is perceived as being under pressure from renewed wolf presence in the Italian Alpine province of South Tyrol. To investigate this, we combined a literature review with expert interviews to (1) get an overview of the situation of small ruminant farming and (2) identify drivers with an influence on summer pasture use, including wolf presence. Firstly, the results show an increase in small ruminant farms and stock numbers in the valley and on summer pastures during the last years. Secondly, subsidy programs, off-farm employment, lack of personnel and tourism are some of the main drivers for summer pasture development in the past and future. Thirdly, this analysis detects the potential pressure of wolf presence on small ruminant summer farming. Nevertheless, this impact should still be considered modest compared to other driving processes that have started before the return of the wolves. Based on this, the study finally discusses the importance of focusing on targeted funding, the revalorization of the shepherd profession and the balance between tourism and livestock farming to support summer pasture farming in the future.

Insect wing deformities can be caused by various factors, including the Deformed wing virus (DWV). Symptomatic and asymptomatic specimens of the introduced solitary wild bees Megachile sculpturalis and Megachile disjunctiformis collected at eleven Central European locations were screened for DWV infections. Even though virus spillover is common, and DWV was detected in other bee species collected in the same habitat as Megachile spp., neither DWV-A nor DWV-B were found in any of the samples (N = 54) including two symptomatic males with deformed wings. This indicates that other stressors were responsible for the observed clinical symptoms, thereby highlighting the necessity of differential diagnostics.

Background: Various anthropogenic activities continue to threaten the fish biodiversity of the East African water bodies such as the Victoria Nile. Although the Victoria Nile is a significant source of livelihood to human populations, the biology and ecology of Nile tilapia in this ecosystem remain understudied with little or no information on the morphology of the fish given varying and immense anthropogenic activities. Here, we use geometric morphometrics to examine the morphology/shape variations of Nile tilapia populations in Victoria Nile to gain insights into their current ecological state. Results: Our results indicate unexpected smaller body weights of Nile tilapia in Victoria Nile than in L. Victoria. Despite this, all the populations displayed condition factors of greater than 2 suggesting a healthy stock. We also report that the Upper and Lower Victoria Nile populations display morphological similarities. We note that Nile tilapia from Nalubale Dam Reservoir is morphologically distinct from the close neighboring Victoria Nile populations which are likely allied to the influence of the Nalubale Hydroelectric power dam as a barrier. Conclusion: Nile tilapia’s morphological variation appears to be influenced by various anthropogenic disturbances notably, overfishing, hydroelectric power dams, and fish translocational history in Uganda. Management should enforce regulatory frameworks to avert human-mediated activities as these are likely to compromise the sustainability of the fisheries. Further studies are required to follow these populations with molecular data to gain a deeper understanding of the fish species for sustainable management and conservation.

Despite their high abundance and species richness, tilapiines have been compromised by various factors especially overfishing, climate change, and un-controlled fish translocations. Fish translocations have negatively impacted native tilapiine populations through competition, predation, hybridization, and introgression compromising their genetic integrity. The hybridization levels of different tilapiines in the Lake Victoria basin remains an understudied aspect relatively. The study utilized nuclear microsatellite and mitochondrial DNA (mtDNA) genetic markers to investigate hybridization signals and compare the genetic diversity of different tilapiines in Lake Victoria, Kenya, using next-generation sequencing. Low levels of hybridization from Oreochromis niloticus into other Oreochromis species were detected by Bayesian clustering analysis and principal coordinate analysis (PCoA). The results contribute to the need for conservation measures of these fish species.

BackgroundThe need for enhancing the productivity of fisheries in Africa triggered the introduction of non-native fish, causing dramatic changes to local species. In East Africa, the extensive translocation of Nile tilapia (Oreochromis niloticus) is one of the major factors in this respect. Using 40 microsatellite loci with SSR-GBS techniques, we amplified a total of 664 individuals to investigate the genetic structure ofO. niloticusfrom East Africa in comparison to Ethiopian and Burkina Faso populations.ResultsAll three African regions were characterized by independent gene-pools, however, the Ethiopian population from Lake Tana was genetically more divergent (Fst = 2.1) than expected suggesting that it might be a different sub-species. In East Africa, the genetic structure was congruent with both geographical location and anthropogenic activities (Isolation By Distance for East Africa, R2 = 0.67 and Uganda, R2 = 0.24).O. niloticusfrom Lake Turkana (Kenya) was isolated, while in Uganda, despite populations being rather similar to each other, two main natural catchments were able to be defined. We show that these two groups contributed to the gene-pool of different non-native populations. Moreover, admixture and possible hybridization with other tilapiine species may have contributed to the genetic divergence found in some populations such as Lake Victoria. We detected other factors that might be affecting Nile tilapia genetic variation. For example, most of the populations have gone through a reduction in genetic diversity, which can be a consequence of bottleneck (G-W, ConclusionsThe anthropogenic activities particularly in the East AfricanO. niloticustranslocations, promoted artificial admixture among Nile Tilapia populations. Translocations may also have triggered hybridization with the native congenerics, which needs to be further studied. These events may contribute to outbreeding depression and hence compromising the sustainability of the species in the region.

Urban areas consist of wide expanses of impervious surfaces which are known to negatively affect insect biodiversity in general, but green spaces within cities have the potential to provide necessary habitat and foraging resources. Although, communal gardens were primarily intended to provide fresh, regional food to denizens, these green islands also host a surprisingly high number of wild bee species. The gardens were characterized based on structural elements such as flower frequency, the relative percentage of lawn, trees, shrubs, planted crops and infrastructure (e.g. seating possibilities or garden houses). Further, the effects of different landscape structures surrounding the gardens and distance to the city center were analyzed on the total wild bee species richness and functional traits. Focusing on these putative influencing factors, statistical analyses calculating random decision forests along with generalized linear mixed models were applied. With 113 observed wild bee species, communal gardens provide habitat for a quarter of all known species in Vienna. In conclusion, results revealed that only elements within the gardens had an effect on species richness, with flower frequency as the major positive driver. The examined communal gardens promote and conserve wild bees independent from the location within the city or garden size. Furthermore, these green patches are important sanctuaries, hosting rare and threatened species as well as remarkably special wild bee communities.

Ailanthus altissima is a common tree species of the European non-native flora. In Eastern Austria, Ailanthus has both a long tradition, dating back to the late 18th century, and a high frequency of occurrence. Here, we apply molecular markers from the nuclear and chloroplast DNA in order to study the origin, as well as the clonal and genetic structure of the species in forest stands of this region. Our results indicate a single area of origin for all our study populations from the north-eastern part of the native range, in agreement with historical reports. Within populations, vegetative reproduction has resulted in extensive clonal structures at some sites. Long presence and repeated vegetative recruitment might have led to expansion of clones in areas of early introduction. In addition, limited mate availability may also have promoted vegetative reproduction. Tests for recent bottlenecks were significant in almost all stands, possibly reflecting founder effects since the introduction of Ailanthus in our study area. Among populations, we found a very pronounced and significant genetic structure, which did not follow a spatial pattern. We argue that founder effects due to population establishment with a low number of propagules – whether naturally or artificially – have caused genetic drift and a structured gene pool. The lack of spatial pattern or isolation-by-distance suggests that seed transfer by humans might have been a major factor shaping the genetic variation of Ailanthus in Eastern Austria.

Background Nile tilapia, Oreochromis niloticus (Linnaeus, 1758) is among the economically most important freshwater fish species in East Africa, and a major source of protein for local consumption. Human induced translocations of non-native stocks for aquaculture and fisheries have been found as a potential threat to the genetic diversity and integrity of local populations. In the present study, we investigate the genetic structure of O. niloticus from 16 waterbodies across Ethiopia using 37 microsatellite loci with SSR-GBAS techniques. Results The samples are structured into three main clusters shaped either by biogeographic factors or stocking activities. High FST values (Global FST = 0.438) between populations indicate a high level of genetic differentiation and may suggest long term isolation even within the same drainage systems. Natural populations of the Omo-Turkana system and the lakes in the Southern Main Ethiopian Rift showed the highest genetic variability while low variability was found in stocked populations of lakes Hora, Hashenge and Hayq. Conclusions The results presented herein, may provide an essential basis for the management and conservation of the unique genetic resources in northern East Africa, and advance our understanding of biodiversity, phylogeny, evolution and development towards phylogenetically more accurate taxonomic classifications.

Visuelle Merkmale gehören zu den wichtigsten biologischen Charakteristika um Organismen zu beschreiben. Farbe und Körperbau sind wichtige Merkmale zur Unterscheidung von Untergruppen, für die Beurteilung von Diversität und für Untersuchungen hinsichtlich Anpassung an lokale Gegebenheiten. In der klassischen Morphologie setzt man zur Charakterisierung auf vordefinierte Kartierungspunkte die für jede zu untersuchende Probe manuell in einer digitalen Abbildung markiert werden. Eine manuelle Zuordnung von Kartierungspunkten ist zeitaufwendig und fehleranfällig. Vordefinierte Kartierungspunkte haben darüber hinaus den Nachteil, dass Information, die für eine genaue Charakterisierung der betrachteten Organismen wichtig wäre gar nicht berücksichtigt wird. Dieses Problem tritt besonders dann auf, wenn Charakteristika komplexe Zusammenhänge aufweisen, die für menschliche Betrachter schwer zu erkennen sind. Im Bereich des maschinellen Lernens (ML) wurden in den vergangenen Jahren innovative Methoden zur Datenanalyse entwickelt, die insbesondere in der Bildanalyse maßgebliche Performanzsprünge erlauben. Um wissenschaftlich glaubwürdige Ergebnisse zu erhalten, ist es allerdings wichtig auf Interpretierbarkeit der Methoden zu achten und die black-box Charakteristik beim Einsatz von ML abzufedern. Um reproduzierbare visuelle Merkmale in Nile tilapia zu finden die auf eine Anpassung der Fischpopulationen an lokale Gegebenheiten hindeuten, setzt die vorliegende Arbeit auf komplementäre Analyseschritte und auf die Interpretation sogenannter "saliency maps". Als Datenbasis für die vorliegende Analyse dienen Nile tilapia Bilder, die von Fischen aufgenommen wurden, die aus sechs Äthiopischen Seen stammen. Ein Methodenvergleich, der zur Vorhersage des Ursprungs aus den Fischbildern auf deep learning bzw. auf eine klassische morphometrische Analyse setzt, deutet auf eine signifikante Verbesserung der Vorhersagegenauigkeit durch den Einsatz von deep learning hin. Eine kritische Analyse der saliency maps zeigt allerdings, dass die Vorhersagen mittels deep learning nicht nur auf authentischen biologischen Merkmalen, sondern auch auf technischen Fehlern basieren, die die Vorhersage des Ursprungs der Fische begünstigen. So werden zum Beispiel der unterschiedliche Bildhintergrund oder eine Nadel mit der Fische fixiert werden als Hinweis auf den Ursprung mancher Fische interpretiert. Vertrauenswürdigere Merkmale, die für den Ursprung der Nile tilapia Populationen charakteristisch sind, konnten mit einer Bayes'schen Methode automatisch aus den Fischbildern bestimmt werden. Die dabei entdeckten Merkmale überlappen teilweise mit den Kartierungspunkten der klassischen Morphologie, erweitern diese aber um Körperregionen, die bisher nicht berücksichtigt wurden. Aus methodischer Sicht kann aus der Analyse der Schluss gezogen werden, dass kritische hinterfragtes maschinelles Lernen geeignet ist, um morphologische Merkmale automatisch aus Bildern zu extrahieren, die es erlauben reproduzierbare biologische Erkenntnisse zu gewinnen. Hinsichtlich Fischbiologie kommt die vorliegende Analyse zum Schluss, dass Nile tilapia Populationen dazu tendieren, ortsspezifische Merkmale auszubilden. Visual characteristics are among the most important features for characterizing the phenotype of biological organisms. Color and geometric properties define population phenotype and allow assessing diversity and adaptation to environmental conditions. To analyze geometric properties classical morphometrics relies on biologically relevant landmarks which are manually assigned to digital images. Assigning landmarks is tedious and error prone. Predefined landmarks may in addition miss out on information which is not obvious to the human eye. The machine learning (ML) community has recently proposed new data analysis methods which by uncovering subtle features in images obtain excellent predictive accuracy. Scientific credibility demands however that results are interpretable and hence to mitigate the black-box nature of ML methods. To overcome the black-box nature of ML we apply complementary methods and investigate internal representations with saliency maps to reliably identify location specific characteristics in images of Nile tilapia populations. Analyzing fish images which were sampled from six Ethiopian lakes reveals that deep learning improves on a conventional morphometric analysis in predictive performance. A critical assessment of established saliency maps with a novel significance test reveals however that the improvement is aided by artifacts which have no biological interpretation. More interpretable results are obtained by a Bayesian approach which allows us to identify genuine Nile tilapia body features which differ in dependence of the animals habitat. We find that automatically inferred Nile tilapia body features corroborate and expand the results of a landmark based analysis that the anterior dorsum, the fish belly, the posterior dorsal region and the caudal fin show signs of adaptation to the fish habitat. We may thus conclude that Nile tilapia show habitat specific morphotypes and that a ML analysis allows inferring novel biological knowledge in a reproducible manner. (VLID)6040310

BackgroundInvasive species are increasingly driving biodiversity decline, and knowledge of colonization dynamics, including both drivers and dispersal modes, are important to prevent future invasions. The bee speciesMegachile sculpturalis(Hymenoptera: Megachilidae), native to East-Asia, was first recognized in Southeast-France in 2008, and has since spread throughout much of Europe. The spread is very fast, and colonization may result from multiple fronts.ResultTo track the history of this invasion, codominant markers were genotyped using Illumina sequencing and the invasion history and degree of connectivity between populations across the European invasion axis were investigated. Distinctive genetic clusters were detected with east–west differentiations in Middle-Europe.ConclusionWe hypothesize that the observed cluster formation resulted from multiple, independent introductions of the species to the European continent. This study draws a first picture of an early invasion stage of this wild bee and forms a foundation for further investigations, including studies of the species in their native Asian range and in the invaded range in North America.

The Nile tilapia (Oreochromis niloticus) gut harbors a diverse microbial community, however, their variation across gut regions, lumen and mucosa is not fully elucidated. In this study, gut microbiota of all samples across gut regions and sample types (luminal content and mucosa) were analyzed and compared from two Ethiopian lakes. Microbiota were characterized using 16S rRNA Illumina MiSeq platform sequencing. A total of 2061 operational taxonomic units (OTUs) were obtained and the results indicated that Nile tilapia from Lake Chamo harbored a much more diversified gut microbiota than Lake Awassa. In addition, the gut microbiota diversity varied significantly across the gut region based on the Chao1, Shannon and Simpson index. The microbiome analyses of all samples in the midgut region showed significantly higher values for alpha diversity (Chao 1, Shannon and Simpson). Beta diversity analysis revealed a clear separation of samples according to sampling areas and gut regions. The most abundant genera were Clostridium_sensu_stricto and Clostridium_XI genera across all samples. Between the two sampling lakes, two phyla, Phylum Fusobacteria and Cyanobacteria, were found to be significantly different. On the other hand, six phyla (Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Proteobacteria and Cyanobacteria) were significantly different across gut regions. In this study, we found that all samples shared a large core microbiota, comprising a relatively large number of OTUs, which was dominated by Proteobacteria, Firmicutes, Cyanobacteria, Fusobacteria and Actinobacteria. This study has established the bases for future large-scale investigations of gut microbiota of fishes in Ethiopian lakes.

Simple Summary Hedgehogs are regularly brought to wildlife shelters. Depending on the area from where animals are accepted, translocation can occur between different regions or populations. In this study, the genetic diversity of wild hedgehog populations was compared with “shelter populations” within central Europe focusing on the western contact zone between both European hedgehog species. Some shelters were hosting both species at the same time, in one this could be shown genetically. Generally, no difference in genetic diversity between shelter individuals and wild populations was found. Two shelters from Innsbruck hosted individuals that probably belong to two subpopulations. This indicates that shelter management-related translocations could facilitate gene flow across a dispersal barrier. Abstract Hedgehogs are among the most abundant species to be found within wildlife shelters and after successful rehabilitation they are frequently translocated. The effects and potential impact of these translocations on gene flow within wild populations are largely unknown. In this study, different wild hedgehog populations were compared with artificially created “shelter populations”, with regard to their genetic diversity, in order to establish basic data for future inferences on the genetic impact of hedgehog translocations. Observed populations are located within central Europe, including the species Erinaceus europaeus and E. roumanicus. Shelters were mainly hosting one species; in one case, both species were present syntopically. Apart from one exception, the results did not show a higher genetic diversity within shelter populations, indicating that individuals did not originate from a wider geographical area than individuals grouped into one of the wild populations. Two shelters from Innsbruck hosted individuals that belonged to two potential clusters, as indicated in a distance analysis. When such a structure stems from the effects of landscape elements like large rivers, the shelter management-related translocations might lead to homogenization across the dispersal barrier.

By applying second‐generation sequencing technologies to microsatellite genotyping, sequence information is produced which can result in high‐resolution population genetics analysis populations and increased replicability between runs and laboratories. In the present study, we establish an approach to study the genetic structure patterns of two European hedgehog species Erinaceaus europaeus and E. roumanicus. These species are usually associated with human settlements and are good models to study anthropogenic impacts on the genetic diversity of wild populations. The short sequence repeats genotyping by sequence (SSR‐GBS) method presented uses amplicon sequences to determine genotypes for which allelic variants can be defined according to both length and single nucleotide polymorphisms (SNPs). To evaluate whether complete sequence information improved genetic structure definition, we compared this information with datasets based solely on length information. We identified a total of 42 markers which were successfully amplified in both species. Overall, genotyping based on complete sequence information resulted in a higher number of alleles, as well as greater genetic diversity and differentiation between species. Additionally, the structure patterns were slightly clearer with a division between both species and some potential hybrids. There was some degree of genetic structure within species, although only in E. roumanicus was this related to geographical distance. The statistically significant results obtained by SSR‐GBS demonstrate that it is superior to electrophoresis‐based methods for SSR genotyping. Moreover, the greater reproducibility and throughput with lower effort which can be obtained with SSR‐GBS and the possibility to include degraded DNA into the analysis, allow for continued relevance of SSR markers during the genomic era.

PREMISE OF THE STUDY Qat (Catha edulis, Celastraceae) is a woody plant species cultivated for its stimulant alkaloids. Qat is important to the economy and culture in large regions of Ethiopia, Kenya, and Yemen. Despite the importance of this species, the wild origins and dispersal of cultivars have only been described in often contradictory historical documents. We examined the wild origins, human-mediated dispersal, and genetic divergence of cultivated qat compared to wild qat. METHODS We sampled 17 SSR markers and 1561 wild and cultivated individuals across the historical areas of qat cultivation. KEY RESULTS On the basis of genetic structure inferred using Bayesian and nonparametric methods, two centers of origin in Kenya and one in Ethiopia were found for cultivated qat. The centers of origin in Ethiopia and northeast of Mt. Kenya are the primary sources of cultivated qat genotypes. Qat cultivated in Yemen is derived from Ethiopian genotypes rather than Yemeni wild populations. Cultivated qat with a wild Kenyan origin has not spread to Ethiopia or Yemen, whereas a small minority of qat cultivated in Kenya originated in Ethiopia. Hybrid genotypes with both Ethiopian and Kenyan parentage are present in northern Kenya. CONCLUSIONS Ethiopian cultivars have diverged from their wild relatives, whereas Kenyan qat has diverged less. This pattern of divergence could be caused by the extinction of the wild-source qat populations in Ethiopia due to deforestation, undersampling, and/or artificial selection for agronomically important traits.

Grape phylloxera is one of the most dangerous insect pests for worldwide viticulture. The leaf- and root-galling phylloxerid has been managed by grafting European grapevines onto American rootstock hybrids. Recent reports pinpoint the appearance of host-adapted biotypes, but information about the biomolecular characteristics underlying grape phylloxera biotypisation and its role in host performance is scarce. Using RNA-sequencing, we sequenced the transcriptome of two larval stages: L1 (probing) and L2-3 (feeding) larvae of two root-feeding grape phylloxera lineages feeding on the rootstock Teleki 5C (biotype C) and V. vinifera Riesling (biotype A). In total, 7501 differentially expressed genes (DEGs) were commonly modulated by the two biotypes. For the probing larvae, we found an increased number of DEGs functionally associated with insect chemoreception traits, such as odorant-binding proteins, chemosensory proteins, ionotropic, odorant, and gustatory receptors. The transcriptomic profile of feeding larvae was enriched with DEGs associated with the primary metabolism. Larvae feeding on the tolerant rootstock Teleki 5C exhibited higher numbers of plant defense suppression-associated DEGs than larvae feeding on the susceptible host. Based on the identified DEGs, we discuss their potential role for the compatible grape phylloxera&ndash, Vitis interaction belowground. This study was the first to compare the transcriptomes of two grape phylloxera lineages feeding on a tolerant and susceptible host, respectively, and to identify DEGs involved in the molecular interaction with these hosts. Our data provide a source for future studies on host adaptation mechanisms of grape phylloxera and help to elucidate grape phylloxera resistance further.

Biodiversity monitoring programs are the baseline of species abundancy studies, which in case of introduced species are especially critical. Megachile sculpturalis Smith, 1853 native to Eastern-Asia, constitutes the first ever recorded wild bee species accidently introduced in Europe. Since its first discovery in 2008, M. sculpturalis has been spreading across the continent. By initiating a citizen science monitoring program, we aimed to investigate the occurrence pattern of M. sculpturalis. Within only two years after starting the project, 111 new reports from Switzerland, Liechtenstein and Austria were recorded. Comparably to other European countries, the population progressed remarkably fast from year to year expanding its area geographically but also ecologically by increasing its altitudinal range. The distribution pattern indicates human assisted jump-dispersal travelling on the major traffic routes of central Europe.

Cinchona officinalisL., a tree species endemic to the cloud forests of the northern Tropical Andes, has suffered from historical bark harvesting for extraction of antimalarial compounds and has also experienced recent demographic losses from high rates of deforestation. Most remnant populations are found in severely degraded habitat on the edges of pastures while a minority are protected in private reserves. The goals of our research were to assess the genetic diversities of fragmented populations ofC. officinalisin the Loja province of southern Ecuador, characterize their phylogeographic distribution with respect to the region’s complex topography, and identify priority populations for conservation. Five nuclear microsatellite loci and the chloroplastrps16intron were used to analyze six populations. Moderate levels of genetic diversity were found in all populations although the more remote southern population (Angashcola) had slightly higher heterozygosity and allelic richness. There were no indications of recent genetic bottlenecks although anrps16intron haplotype was fixed in four populations. Genetic distance analysis based on microsatellite data placed the four easternmost populations in the same clade while the Angashcola population was the most divergent. Also, the most frequentrps16intron haplotype in Angashcola was not found in any other population. Although each of the studied populations should be protected from further deforestation and agricultural expansion, the Angashcola population deserves highest conservation priority.

Das UBRM erfordert Wissen uber Funktionen, Leistungen und Wechselwirkungen von Okosystemen und deren Veranderungen in Raum und Zeit, die etwa durch Anderungen klimatischer, politischer oder gesellschaftlicher Rahmenbedingungen angestosen werden. Die Kenntnis der Wirkungen unterschiedlicher Instrumente im Natur-, Gewasser- und Landschaftsschutz ermoglicht es, die Erhaltung lebensnotwendiger naturlicher Ressourcen und den Schutz der Biodiversitat effizient zu gestalten. Nur bei einer integrierenden Herangehensweise konnen nachhaltige Landnutzung und Landbewirtschaftung unter den Bedingungen des globalen Wandels gelingen. Damit soll die Ernahrung der Weltbevolkerung mit hochwertigen Lebensmitteln sichergestellt werden. Gleichzeitig sollen aber die Auswirkungen auf Natur und Umwelt auf ein tragfahiges Ausmas reduziert werden. Die Raum- und Umweltplanung ist gefordert, menschliche Lebensraume unter Berucksichtigung okologischer, sozialer, kultureller und okonomischer Interessen zu gestalten sowie Instrumente fur die multifunktionale Nutzung von Raumen zu erarbeiten.

International audience; Gene Drives are regarded as future tools with a high potential for population control. Due to their inherent ability to overcome the rules of Mendelian inheritance, gene drives (GD) may spread genes rapidly through populations of sexually reproducing organisms. A release of organisms carrying a GD would constitute a paradigm shift in the handling of genetically modified organisms because gene drive organisms (GDO) are designed to drive their transgenes into wild populations and thereby increase the number of GDOs. The rapid development in this field and its focus on wild populations demand a prospective risk assessment with a focus on exposure related aspects. Presently, it is unclear how adequate risk management could be guaranteed to limit the spread of GDs in time and space, in order to avoid potential adverse effects in socio-ecological systems. The recent workshop on the “Evaluation of Spatial and Temporal Control of Gene Drives” hosted by the Institute of Safety/Security and Risk Sciences (ISR) in Vienna aimed at gaining some insight into the potential population dynamic behavior of GDs and appropriate measures of control. Scientists from France, Germany, England, and the USA discussed both topics in this meeting on April 4–5, 2019. This article summarizes results of the workshop.

For computer vision based appraoches such as image classification (Krizhevsky et al. 2012), object detection (Ren et al. 2015) or pixel-wise weed classification (Milioto et al. 2017) machine learning is used for both feature extraction and processing (e.g. classification or regression). Historically, feature extraction (e.g. PCA; Ch. 12.1. in Bishop 2006) and processing were sequential and independent tasks (Wöber et al. 2013). Since the rise of convolutional neuronal networks (LeCun et al. 1989), a deep machine learning approach optimized for images, in 2012 (Krizhevsky et al. 2012), feature extraction for image analysis became an automated procedure. A convolutional neuronal net uses a deep architecture of artificial neurons (Goodfellow 2016) for both feature extraction and processing. Based on prior information such as image classes and supervised learning procedures, parameters of the neuronal nets are adjusted. This is known as the learning process. Simultaneously, geometric morphometrics (Tibihika et al. 2018, Cadrin and Friedland 1999) are used in biodiversity research for association analysis. Those approaches use deterministic two-dimensional locations on digital images (landmarks; Mitteroecker et al. 2013), where each position corresponds to biologically relevant regions of interest. Since this methodology is based on scientific results and compresses image content into deterministic landmarks, no uncertainty regarding those landmark positions is taken into account, which leads to information loss (Pearl 1988). Both, the reduction of this loss and novel knowledge detection, can be done using machine learning. Supervised learning methods (e.g., neuronal nets or support vector machines (Ch. 5 and 6. in Bishop 2006)) map data on prior information (e.g. labels). This increases the performance of classification or regression but affects the latent representation of the data itself. Unsupervised learning (e.g. latent variable models) uses assumptions concerning data structures to extract latent representations without prior information. Those representations does not have to be useful for data processing such as classification and due to that, the use of supervised and unsupervised machine learning and combinations of both, needs to be chosen carefully, according to the application and data. In this work, we discuss unsupervised learning algorithms in terms of explainability, performance and theoretical restrictions in context of known deep learning restrictions (Marcus 2018, Szegedy et al. 2014, Su et al. 2017). We analyse extracted features based on multiple image datasets and discuss shortcomings and performance for processing (e.g. reconstruction error or complexity measurement (Pincus 1997)) using the principal component analysis (Wöber et al. 2013), independent component analysis (Stone 2004), deep neuronal nets (auto encoders; Ch. 14 in Goodfellow 2016) and Gaussian process latent variable models (Titsias and Lawrence 2010, Lawrence 2005).

The introduction of new genetic lineages into a population promotes interbreeding or hybridization and can be associated with the loss of genetic adaptation. This may contribute to financial losses for fish farmers following investments into fish strains that do not perform to their expectations. Oreochromis niloticus is one of the tilapiine species that has been widely distributed in areas far from its native range mainly for aquaculture purposes. This is principally due to its fast growth rates, adaptability to new habitats in addition to attractive market prices. Oreochromis niloticus has also been previously associated with the loss of native tilapiine species such as O. variabilis and O. esculentus in Lake Victoria and other lakes in Africa. To understand the impacts of O. niloticus translocation on native fish stocks, its species borders need to be delimited. Here we use microsatellite genotyping by amplicon sequencing (SSR-GBAS) for species delimitation of O. niloticus and seven related species from different regions in East and West Africa obtained from natural and farm environments. In total, 47 markers previously developed for O. niloticus were tested for cross-species amplification resulting in thirty-eight working markers. Most species were represented by different genetic units with little admixture between them even if ocuring in the same waterbodies. Exceptions involved the farmed populations from O. niloticus and O. mossambicus, which may be indicative of hybrid introgression. Our approach did also detect lower genetic diversity on the critically endangered species O. variabilis and O. esculentus. The possibility of introgressive hybridisation between O. niloticus and some of its congenerics may affect the sustainability of its exploitation. Moreover, long-term projects to monitor the response of genetic diversity and species boundaries to anthropogenic activities are required. In this context, SSR-GBAS can be a powerful tool given its high sample throughput and higher reproducibility compared to other methods.

Tinamous (Tinamidae) represent one of the most ancient living avian lineages but their life history traits are relatively unstudied. Here we identified microsatellite loci for two sympatric tinamou species, the Ornate Tinamou ( Nothoprocta ornata) and the Darwin's Nothura ( Nothura darwinii) from low coverage Illumina sequencing of genomic DNA. The experiment yielded a large number of candidate loci. We designed primers and tested them for successful amplification in 1 to 2 populations of the target species, tested for deviation from the Hardy–Weinberg equilibrium and the presence of null alleles, the levels of polymorphism and potential cross-amplification. All 30 and 24 loci amplified consistently, in the Ornate Tinamou and in Darwin's Nothura, respectively. In the Ornate Tinamou, 25 loci were polymorphic and in the Darwin's Nothura 12, with 2 to 14 alleles per locus in both species. The expected heterozygosity ranged from 0.054 to 0.917 in the Ornate Tinamou and from 0.044 to 0.908 in the Darwin's Nothura. 23 (40%) of 54 loci were successfully cross-amplified. These newly discovered, polymorphic microsatellite loci represent a valuable tool for future studies on social behaviour, parentage and genetic population structure in tinamous.

Geological history of oceanic islands can have a profound effect on the evolutionary history of insular flora, especially in complex islands such as Tenerife in the Canary Islands. Tenerife results from the secondary connection of three paleo-islands by a central volcano, and other geological events that further shaped it. This geological history has been shown to influence the phylogenetic history of several taxa, including genus Micromeria (Lamiaceae). Screening 15 microsatellite markers in 289 individuals representing the eight species of Micromeria present in Tenerife, this study aims to assess the genetic diversity and structure of these species and its relation with the geological events on the island. In addition, we evaluate the extent of hybridization among species and discuss its influence on the speciation process. We found that the species restricted to the paleo-islands present lower levels of genetic diversity but the highest levels of genetic differentiation suggesting that their ranges might have contracted over time. The two most widespread species in the island, M. hyssopifolia and M. varia, present the highest genetic diversity levels and a genetic structure that seems correlated with the geological composition of the island. Samples from M. hyssopifolia from the oldest paleo-island, Adeje, appear as distinct while samples from M. varia segregate into two main clusters corresponding to the paleo-islands of Anaga and Teno. Evidence of hybridization and intraspecific migration between species was found. We argue that species boundaries would be retained despite hybridization in response to the habitat's specific conditions causing postzygotic isolation and preserving morphological differentiation.

Invasive species are increasingly driving biodiversity decline, and knowledge of colonization dynamics, including both drivers and dispersal modes, are important to prevent future invasions. The bee species Megachile sculpturalis (Hymenoptera: Megachilidae), native to East-Asia, was first recognized in Southeast-France in 2008, and has since spread throughout much of Europe. The spread is very fast, and colonization may result from multiple fronts.To track the history of this invasion, codominant markers were genotyped using Illumina sequencing and the invasion history and degree of connectivity between populations across the European invasion axis were investigated. Distinctive genetic clusters were detected with east-west differentiations in Middle-Europe.We hypothesize that the observed cluster formation resulted from multiple, independent introductions of the species to the European continent. This study draws a first picture of an early invasion stage of this wild bee and forms a foundation for further investigations, including studies of the species in their native Asian range and in the invaded range in North America.

DNA barcoding constitutes a supplemental genetically based characterization tool for the identification of species. Traditionally, the barcodes are generated with a length of 650 bp using standardized Sanger sequencing, but with the introduction of high-throughput sequencing (HTS) methods new opportunities for sequencing are available. To use HTS for barcode collection and identification, the amplification of shorter fragments is preferred. Reference DNA midi-barcodes of wild bees were produced using the Illumina MiSeq as well as the Sanger method. Although DNA midi-barcodes derived from Illumina were comparatively shorter (418 bp), their sequences were coherent to the morphological assignment of species. The Illumina barcodes proved to be effective and dealt better with some general limitations of DNA barcoding.