87 research outputs found
Pollinator diversity and specialization in relation to flower diversity
No full textIn the face of global decline in biodiversity, the relationship between diversity and species interactions deserves particular attention. If pollinators are strongly dependent on floral diversity due to mutual specialization, declines in plant diversity, e.g. caused by land use intensification, may be associated with linked extinctions of pollinators. However, the general extent of pollinator specialization is still poorly known. To explore the dependence of local bee and hoverfly communities on flower diversity, we recorded flower supply and flower-visiting insects on 27 meadows with varying flower diversity in southern Germany and analyzed (a) whether the diversity of flower visitors is correlated with flower diversity, (b) whether the degree of dietary specialization of flower visitors changes with flower diversity and (c) whether flower preferences of individual flower visitor species are constant or variable between different communities. Flower-visitor interaction webs were compiled during a single day on each meadow. This approach prevents relating pollinator species to flowers they never encounter because of non-overlapping phenology or spatial segregation. (a) Flower diversity and flower visitor diversity were positively correlated. (b) Flower visitor assemblies were significantly specialized at a relatively high level, contrasting to the opinion that plant-pollinator webs are highly generalized, and providing a possible explanation for the positive diversity correlation. However, the level of specialization did not change significantly across the gradient of flower diversity, suggesting that pollinators are partitioned to a similar extent in each meadow. (c) In the analysis of ten common flower visitor species previously categorized as generalists, strong evidence was found for both, consistent preferences and preferences that differ between sites. These results indicate a flexibility in flower preferences and a dynamic resource partitioning among pollinators. Generally, our findings highlight the complexity of plant-pollinator interactions and confirm the importance of flower diversity for bee and hoverfly communities.German Federal Foundation for Environment (DBU
Functional complementarity and specialisation: The role of biodiversity in plant–pollinator interactions
No full textEcological niche breadth (specialisation) and niche differentiation (complementarity) play a key role for species coexistence and hence biodiversity. Some niche dimensions of a species represent ecosystem functions or services such as pollination (functional niche). When species differ in their contribution to some collective function (functional complementarity), this implies that functions from several species are required for a high overall functional performance level. Applied to plant pollinator interactions, functional complementary suggests that a higher diversity of pollinators contributes to an increased pollination success of the plants or, in turn, that a higher diversity of flowers may better sustain the consumers' requirements. Complementarity can affect functioning at different scales: the collective functioning of the target community, a single species, an individual or even a part of the individual, e.g. a single flower. Recent network analyses revealed that plant pollinator interactions display a relatively high extent of complementary specialisation at the community scale. We propose several mechanisms that generate complementarity. From the consumers' viewpoint, differences in flowering phenology and/or nutritional variation in floral resources (nectar, pollen) may explain a complementary role of different flower species. From the plant's viewpoint, temporal or environmental variation in the pollinator species' activities may contribute to complementary effects on pollination of plant communities. In addition, different species may also pollinate either more exposed or more sheltered flowers from the same plant individual, or vary in their functions within single flowers. So far, empirical evidence for complementary effects in general, and particularly mechanistic explanations of such effects are scant and will require comparative investigations at multiple scales in the future. Such studies will help us to understand if and how biodiversity maintains the quality and quantity of plant pollinator functional relationships
Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects
No full textAlthough artificial intelligence (AI) methods hold promise for medical imaging-based prediction tasks, their integration into medical practice may present a double-edged sword due to bias (i.e., systematic errors). AI algorithms have the potential to mitigate cognitive biases in human interpretation, but extensive research has highlighted the tendency of AI systems to internalize biases within their model. This fact, whether intentional or not, may ultimately lead to unintentional consequences in the clinical setting, potentially compromising patient outcomes. This concern is particularly important in medical imaging, where AI has been more progressively and widely embraced than any other medical field. A comprehensive understanding of bias at each stage of the AI pipeline is therefore essential to contribute to developing AI solutions that are not only less biased but also widely applicable. This international collaborative review effort aims to increase awareness within the medical imaging community about the importance of proactively identifying and addressing AI bias to prevent its negative consequences from being realized later. The authors began with the fundamentals of bias by explaining its different definitions and delineating various potential sources. Strategies for detecting and identifying bias were then outlined, followed by a review of techniques for its avoidance and mitigation. Moreover, ethical dimensions, challenges encountered, and prospects were discussed
Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions
No full textWith the advent of large language models (LLMs), the artificial intelligence revolution in medicine and radiology is now more tangible than ever. Every day, an increasingly large number of articles are published that utilize LLMs in radiology. To adopt and safely implement this new technology in the field, radiologists should be familiar with its key concepts, understand at least the technical basics, and be aware of the potential risks and ethical considerations that come with it. In this review article, the authors provide an overview of the LLMs that might be relevant to the radiology community and include a brief discussion of their short history, technical basics, ChatGPT, prompt engineering, potential applications in medicine and radiology, advantages, disadvantages and risks, ethical and regulatory considerations, and future directions
Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects
No full text: Although artificial intelligence (AI) methods hold promise for medical imaging-based prediction tasks, their integration into medical practice may present a double-edged sword due to bias (i.e., systematic errors). AI algorithms have the potential to mitigate cognitive biases in human interpretation, but extensive research has highlighted the tendency of AI systems to internalize biases within their model. This fact, whether intentional or not, may ultimately lead to unintentional consequences in the clinical setting, potentially compromising patient outcomes. This concern is particularly important in medical imaging, where AI has been more progressively and widely embraced than any other medical field. A comprehensive understanding of bias at each stage of the AI pipeline is therefore essential to contribute to developing AI solutions that are not only less biased but also widely applicable. This international collaborative review effort aims to increase awareness within the medical imaging community about the importance of proactively identifying and addressing AI bias to prevent its negative consequences from being realized later. The authors began with the fundamentals of bias by explaining its different definitions and delineating various potential sources. Strategies for detecting and identifying bias were then outlined, followed by a review of techniques for its avoidance and mitigation. Moreover, ethical dimensions, challenges encountered, and prospects were discussed
Evaluation metrics in medical imaging AI: fundamentals, pitfalls, misapplications, and recommendations
No full textRobust assessment of artificial intelligence (AI) models in medical imaging is paramount for reliable clinical integration. This international collaborative review paper provides an overview of key evaluation metrics across diverse tasks, including classification, regression, survival analysis, detection, and segmentation, as well as specialized metrics for calibration, foundation models, large language models, and synthetic images. Challenges of comparing models statistically and translating metric scores to clinical practice are also discussed. For each section, the paper outlines fundamental metrics, identifies common pitfalls and misapplications, and offers
recommendations for more robust evaluations. Key recommendations often involve utilizing multiple, complementary metrics tailored to the specific task and dataset properties, transparent reporting of methodology, and critically, considering the clinical utility and real-world implications of model performance. Ultimately, effective evaluation requires a comprehensive, context-aware approach that goes beyond statistical metrics to ensure
Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions
No full text: With the advent of large language models (LLMs), the artificial intelligence revolution in medicine and radiology is now more tangible than ever. Every day, an increasingly large number of articles are published that utilize LLMs in radiology. To adopt and safely implement this new technology in the field, radiologists should be familiar with its key concepts, understand at least the technical basics, and be aware of the potential risks and ethical considerations that come with it. In this review article, the authors provide an overview of the LLMs that might be relevant to the radiology community and include a brief discussion of their short history, technical basics, ChatGPT, prompt engineering, potential applications in medicine and radiology, advantages, disadvantages and risks, ethical and regulatory considerations, and future directions
Can natural enemy diversity ensure stable biological control in the future?
No full textNatural enemy diversity generally strengthens biological control, but individual studies have found anything from positive to negative effects. However, most studies investigating the impacts of natural enemy diversity on pest suppression have focused on short term effects, while ignoring the stability in pest suppression across time and space. Theory predicts that a high diversity of redundant species (i.e., species currently doing the same job) should stabilize ecosystem functioning, since different species are likely to be important during different environmental conditions. This implies that a high natural enemy diversity should provide an insurance against global environmental change. We will here present how generalist predators contribute to stability of aphid biological control in Swedish barley fields under varying landscape complexity and climate change. We have found that ground dwelling predators such as spiders and carabids can reduce aphid pest damage with 50% in such fields, and that the level of aphid biological control is higher in more complex landscapes (Rusch et al. 2013). In recent work, exploring feeding preferences of the most common carabid and spider species on over ten prey types with molecular gut content analysis we have confirmed that these species are highly generalistic and that a high diversity of predators contribute to aphid biological control (Roubinet et al. 2017). Our preliminary analyses suggest that the level of redundancy in aphid predation increases with landscape complexity, suggesting that barley fields in complex landscapes not only currently has more effective aphid biological control but that the stability of aphid control is likely to be higher in such landscapes. We are currently investigating the climate niches of different predators in relation to temperature and rainfall. These niches will be combined into climate niches for predator communities in different types of landscapes and we will test if the level of climate resilience (Kühsel and Blüthgen 2015) in predator communities is higher in complex landscapes. Finally, we will conduct mesocosm experiments under different climate scenarios to test if predator communities with different levels of redundancy and climate resilience really contribute to more stable biological control of aphids.
(1) Rusch, A., Bommarco, R., Jonsson, M., Smith, H.G. & Ekbom, B. 2013. Flow and stability of natural pest control services depend on landscape complexity and crop rotation in the landscape. J Appl Ecol 50, 345-354.
(2) Roubinet, E., Birkhofer, K., Malsher, G., Staudacher, K., Ekbom, B., Traugott, M. & Jonsson, M. 2017. Diet of generalist predators reflects effects of cropping period and farming system on extra- and intraguild prey. Ecol Appl 27, 1167-1177.
(3) Kühsel, S. & Blüthgen N. 2015 High diversity stabilizes the thermal resilience of pollinator communities in intensively managed grasslands. Nature Comm 2015. 6: p. 7989.peerReviewedunknown accessibilityei tietoa saavutettavuudest
Aspat (Muğla) yöresinde bulunan Hymenoptera-Zar Kanatlılar (Insecta) takımına ait türler üzerinde faunistik çalışmalar
No full textMayıs 2009 ayları arasında yürütülmüştür. Çalışma sonunda Vespidae familyasına bağlı 6, Formicidae familyasına bağlı 2, Apidae, Pompilidae, Tiphiidae ve Mutillidae familyalarına bağlı 3'er, Chrysididae ve Tenthredinidae familyasına bağlı 2'şer, Sphecidae, Ichneumonidae, Crabronidae, Scoliidae ve Gasteruptiidae familyalarına bağlı 1'er tür olmak üzere toplam 29 tür tespit edilmiştir. Bu türlerden Odynerus melanocephalus armeniacus (Morawitz, 1885), Euodynerus (Euodynerus) curictensis Bluethgen, 1940, Myrmilla (Myrmilla) caucasica (Kolenati, 1846), Tropidotilla litoralis (Petagna, 1787), Mutilla quinquemaculata Cyrillo, 1787, Priocnemis fallax Verhoeff, 1922, Priocnemis (Priocnemis) parvula Dahlbom, 1845, Agenioideus (Schizanoplius) excisus (Morawitz, 1890), Podalonia hirsuta mervensis Radoszkowski, 1887, Anomalon cruentatum (Geoffroy, 1785), Pseudospinolia uniformis (Dahlbom, 1854), Chrysis inaequalis Dahlbom, 1845, Meria dorsalis (Fabricius, 1804), Tiphia persica Turner, 1908, Lestica subterranea (Fabricius, 1775) ve Gasteruption jaculator (Linnaeus, 1758) türlerinin Muğla ilinde bulunduğu ilk kez tespit edilmiştir. En çok yakalanan türler arasında Vespula germanica Linnaeus, 1793 (99 örnek), Vespa orientalis Linnaeus, 1771 (94 örnek), Apis mellifera Linnaeus, 1758 (30 örnek), Tenthredo zonula Klug, 1817 (10 örnek) ve Macrophya (Macrophya) postica (Brullé, 1832) (10 örnek) bulunmaktadır. A. excisus (Morawitz, 1890), P. parvula Dahlbom, 1845, P. fallax Verhoeff, 1922, P. uniformis (Dahlbom, 1854), Ancistrocerus auctus (Fabricius, 1793), T. litoralis (Petagna, 1787), M. (Myrmilla) caucasica (Kolenati, 1846), L. subterranea (Fabricius, 1775), Colpa (Heterelis) quinquecincta quinquecincta (Fabricius, 1793), A. cruentatum (Geoffroy, 1785), E. (Euodynerus) curictensis Bluethgen, 1940, T. persica Turner, 1908, M. quinquemaculata Cyrillo, 1787, C. inaequalis Dahlbom, 1845, G. jaculator (Linnaeus, 1758) ve Messor structor (Latreille, 1798) türlerine ait sadece birer örnek toplanmıştır. Çalışma sonunda 291 örnek toplanmıştır. Bunlardan 200 örnek % 68,73 oranla besin tuzak yöntemiyle; 50 örnek % 17,18 oranla atrap yöntemiyle; 27 örnek % 9,28 oranla elle ve 14 örnek % 4,81 oranla çukur tuzak yöntemiyle yakalanmıştır. Çalışmada incelenen her tür için morfolojileri, yayılışları ve etiket bilgileri verilmiştir. Toplanan materyal E.Ü. Tabiat Tarihi Müzesi ve E.Ü. Ziraat Fakültesi Bitki Koruma Bölümü Prof. Dr. Niyazi Lodos Böcek Müzesi'nde korunmaktadır
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