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Institute
- Theodor-Boveri-Institut für Biowissenschaften (131) (remove)
Sonstige beteiligte Institutionen
- Albert-Ludwigs-Universität Freiburg (1)
- Goethe-Universität Frankfurt (1)
- Institut für Tierökologie und Tropenbiologie (1)
- Leuphana Universität Lüneburg (1)
- Mildred-Scheel-Nachwuchszentrum (1)
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- Universität Duisburg-Essen, Institut für Molekularbiologie, AG Becker-Flegler (1)
- Universität Göttingen (1)
EU-Project number / Contract (GA) number
- 695376 (1)
- 835102) (1)
- ERC-2018-ADG/NCI-CAD (1)
In times of environmental change species have two options to survive: they either relocate to a new habitat or they adapt to the altered environment. Adaptation requires physiological plasticity and provides a selection benefit. In this regard, the Western honeybee (Apis mellifera) protrudes with its thermoregulatory capabilities, which enables a nearly worldwide distribution. Especially in the cold, shivering thermogenesis enables foraging as well as proper brood development and thus survival. In this study, we present octopamine signaling as a neurochemical prerequisite for honeybee thermogenesis: we were able to induce hypothermia by depleting octopamine in the flight muscles. Additionally, we could restore the ability to increase body temperature by administering octopamine. Thus, we conclude that octopamine signaling in the flight muscles is necessary for thermogenesis. Moreover, we show that these effects are mediated by β octopamine receptors. The significance of our results is highlighted by the fact the respective receptor genes underlie enormous selective pressure due to adaptation to cold climates. Finally, octopamine signaling in the service of thermogenesis might be a key strategy to survive in a changing environment.
Drosophila’s lateral posterior neurons (LPNs) belong to a small group of circadian clock neurons that is so far not characterized in detail. Thanks to a new highly specific split‐Gal4 line, here we describe LPNs’ morphology in fine detail, their synaptic connections, daily bimodal expression of neuropeptides, and propose a putative role of this cluster in controlling daily activity and sleep patterns. We found that the three LPNs are heterogeneous. Two of the neurons with similar morphology arborize in the superior medial and lateral protocerebrum and most likely promote sleep. One unique, possibly wakefulness‐promoting, neuron with wider arborizations extends from the superior lateral protocerebrum toward the anterior optic tubercle. Both LPN types exhibit manifold connections with the other circadian clock neurons, especially with those that control the flies’ morning and evening activity (M‐ and E‐neurons, respectively). In addition, they form synaptic connections with neurons of the mushroom bodies, the fan‐shaped body, and with many additional still unidentified neurons. We found that both LPN types rhythmically express three neuropeptides, Allostatin A, Allostatin C, and Diuretic Hormone 31 with maxima in the morning and the evening. The three LPN neuropeptides may, furthermore, signal to the insect hormonal center in the pars intercerebralis and contribute to rhythmic modulation of metabolism, feeding, and reproduction. We discuss our findings in the light of anatomical details gained by the recently published hemibrain of a single female fly on the electron microscopic level and of previous functional studies concerning the LPN.
The exponential increase in the human population in tandem with increased food demand has caused agriculture to be the global‐dominant form of land use. Afrotropical drylands are currently facing the loss of natural savannah habitats and agricultural intensification with largely unknown consequences for bees. Here we investigate the effects of agricultural intensification on bee assemblages in the Afrotropical drylands of northern Tanzania. We disentangled the direct effects of agricultural intensification and temperature on bee richness from indirect effects mediated by changes in floral resources.
We collected data from 24 study sites representing three levels of management intensity (natural savannah, moderate intensive and highly intensive agriculture) spanning an extensive gradient of mean annual temperature (MAT) in northern Tanzania. We used ordinary linear models and path analysis to test the effects of agricultural intensity and MAT on bee species richness, bee species composition and body‐size variation of bee communities.
We found that bee species richness increased with agricultural intensity and with increasing temperature. The effects of agricultural intensity and temperature on bee species richness were mediated by the positive effects of agriculture and temperature on the richness of floral resources used by bees. During the off‐growing season, agricultural land was characterized by an extensive period of fallow land holding a very high density of flowering plants with unique bee species composition. The increase in bee diversity in agricultural habitats paralleled an increasing variation of bee body sizes with agricultural intensification that, however, diminished in environments with higher temperatures.
Synthesis and applications. Our study reveals that bee assemblages in Afrotropical drylands benefit from agricultural intensification in the way it is currently practiced. However, further land‐use intensification, including year‐round irrigated crop monocultures and excessive use of agrochemicals, is likely to exert a negative impact on bee diversity and pollination services, as reported in temperate regions. Moreover, several bee species were restricted to natural savannah habitats. To conserve bee communities and guarantee pollination services in the region, a mixture of savannah and agriculture, with long periods of fallow land should be maintained.
Environmental gradients generate and maintain biodiversity on Earth. Mountain slopes are among the most pronounced terrestrial environmental gradients, and the elevational structure of species and their interactions can provide unique insight into the processes that govern community assembly and function in mountain ecosystems. We recorded bumble bee–flower interactions over 3 years along a 1400‐m elevational gradient in the German Alps. Using nonlinear modeling techniques, we analyzed elevational patterns at the levels of abundance, species richness, species β‐diversity, and interaction β‐diversity. Though floral richness exhibited a midelevation peak, bumble bee richness increased with elevation before leveling off at the highest sites, demonstrating the exceptional adaptation of these bees to cold temperatures and short growing seasons. In terms of abundance, though, bumble bees exhibited divergent species‐level responses to elevation, with a clear separation between species preferring low versus high elevations. Overall interaction β‐diversity was mainly caused by strong turnover in the floral community, which exhibited a well‐defined threshold of β‐diversity rate at the tree line ecotone. Interaction β‐diversity increased sharply at the upper extreme of the elevation gradient (1800–2000 m), an interval over which we also saw steep decline in floral richness and abundance. Turnover of bumble bees along the elevation gradient was modest, with the highest rate of β‐diversity occurring over the interval from low‐ to mid‐elevation sites. The contrast between the relative robustness bumble bee communities and sensitivity of plant communities to the elevational gradient in our study suggests that the strongest effects of climate change on mountain bumble bees may be indirect effects mediated by the responses of their floral hosts, though bumble bee species that specialize in high‐elevation habitats may also experience significant direct effects of warming.
The mechanisms by which climatic changes influence ecosystem functions, that is, by a direct climatic control of ecosystem processes or by modifying richness and trait compositions of species communities, remain unresolved.
This study is a contribution to this discourse by elucidating the linkages between climate, land use, biodiversity, body size and ecosystem functions.
We disentangled direct climatic from biodiversity‐mediated effects by using dung removal by dung beetles as a model system and by combining correlative field data and exclosure experiments along an extensive elevational gradient on Mt. Kilimanjaro, Tanzania.
Dung removal declined with increasing elevation, being associated with a strong reduction in the richness and body size traits of dung beetle communities. Climate influenced dung removal rates by modifying biodiversity rather than by direct effects. The biodiversity–ecosystem effect was driven by a change in the mean body size of dung beetles. Dung removal rates were strongly reduced when large dung beetles were experimentally excluded.
This study underscores that climate influences ecosystem functions mainly by modifying biodiversity and underpins the important role of body size for dung removal.
Arthropod dark taxa provide new insights into diversity responses to bark beetle infestations
(2022)
Natural disturbances are increasing around the globe, also impacting protected areas. Although previous studies have indicated that natural disturbances result in mainly positive effects on biodiversity, these analyses mostly focused on a few well established taxonomic groups, and thus uncertainty remains regarding the comprehensive impact of natural disturbances on biodiversity. Using Malaise traps and meta‐barcoding, we studied a broad range of arthropod taxa, including dark and cryptic taxa, along a gradient of bark beetle disturbance severities in five European national parks. We identified order‐level community thresholds of disturbance severity and classified barcode index numbers (BINs; a cluster system for DNA sequences, where each cluster corresponds to a species) as negative or positive disturbance indicators. Negative indicator BINs decreased above thresholds of low to medium disturbance severity (20%–30% of trees killed), whereas positive indicator BINs benefited from high disturbance severity (76%–98%). BINs allocated to a species name contained nearly as many positive as negative disturbance indicators, but dark and cryptic taxa, particularly Diptera and Hymenoptera in our data, contained higher numbers of negative disturbance indicator BINs. Analyses of changes in the richness of BINs showed variable responses of arthropods to disturbance severity at lower taxonomic levels, whereas no significant signal was detected at the order level due to the compensatory responses of the underlying taxa. We conclude that the analyses of dark taxa can offer new insights into biodiversity responses to disturbances. Our results suggest considerable potential for forest management to foster arthropod diversity, for example by maintaining both closed‐canopy forests (>70% cover) and open forests (<30% cover) on the landscape.
Recent reports on insect decline have highlighted the need for long‐term data on insect communities towards identifying their trends and drivers.
With the launch of many new insect monitoring schemes to investigate insect communities over large spatial and temporal scales, Malaise traps have become one of the most important tools due to the broad spectrum of species collected and reduced capture bias through passive sampling of insects day and night. However, Malaise traps can vary in size, shape, and colour, and it is unknown how these differences affect biomass, species richness, and composition of trap catch, making it difficult to compare results between studies.
We compared five Malaise trap types (three variations of the Townes and two variations of the Bartak Malaise trap) to determine their effects on biomass and species richness as identified by metabarcoding.
Insect biomass varied by 20%–55%, not strictly following trap size but varying with trap type. Total species richness was 20%–38% higher in the three Townes trap models compared to the Bartak traps. Bartak traps captured lower richness of highly mobile taxa but increased richness of ground‐dwelling taxa. The white roofed Townes trap captured a higher richness of pollinators.
We find that biomass, total richness, and taxa group specific richness are all sensitive to Malaise trap type. Trap type should be carefully considered and aligned to match monitoring and research questions. Additionally, our estimates of trap type effects can be used to adjust results to facilitate comparisons across studies.
Abiotic factors are generally assumed to determine whether species can exist at the extreme ends of environmental gradients, for example, at high elevations, whereas the role of biotic interactions is less clear. On temperate mountains, insect‐pollinated plant species with bilaterally symmetrical flowers exhibit a parallel elevational decline in species richness and abundance with bees. This suggests that the lack of mutualistic interaction partners sets the elevational range limits of plants via a reduction in reproductive success. We used the bee‐pollinated mountain plant Clinopodium alpinum (Lamiaceae), which blooms along a continuous 1000‐m elevational gradient and has bilaterally symmetrical flowers, as a model to test the predicted parallel elevational decline in flower visitation and seed production. Although the community of flower visitors changed with elevation, the flower visitation rate by the most frequent visitors, bumble bees (33.8% of legitimate visits), and the overall rate of flower visitation by potential pollinators did not vary significantly with elevation. However, we discovered that nectar robbing by bumble bees and nectar theft by ants, two interactions with potentially negative effects on flowers, sharply increased with elevation. Seed set depended on pollinators across elevations and followed a weak hump‐shaped pattern, peaking at mid‐elevations and decreasing by about 20% toward both elevational range edges. Considering the mid‐ and high elevations, elevational variation in seed production could not be explained by legitimate bee visitation rates but was inversely correlated with the frequency of nectar robbing. Our observations challenge the hypothesis that a decrease in the availability of pollinators limits seed production of bee‐flowered plants at high elevations but suggest that an increase in negative interactions (nectar robbing and larceny) constrains reproductive success.
Green plants are equipped with photoreceptors that are capable of sensing radiation in the ultraviolet‐to‐blue and the red‐to‐far‐red parts of the light spectrum. However, plant cells are not particularly sensitive to green light (GL), and light which lies within this part of the spectrum does not efficiently trigger the opening of stomatal pores. Here, we discuss the current knowledge of stomatal responses to light, which are either provoked via photosynthetically active radiation or by specific blue light (BL) signaling pathways. The limited impact of GL on stomatal movements provides a unique option to use this light quality to control optogenetic tools. Recently, several of these tools have been optimized for use in plant biological research, either to control gene expression, or to provoke ion fluxes. Initial studies with the BL‐activated potassium channel BLINK1 showed that this tool can speed up stomatal movements. Moreover, the GL‐sensitive anion channel GtACR1 can induce stomatal closure, even at conditions that provoke stomatal opening in wild‐type plants. Given that crop plants in controlled‐environment agriculture and horticulture are often cultivated with artificial light sources (i.e. a combination of blue and red light from light‐emitting diodes), GL signals can be used as a remote‐control signal that controls stomatal transpiration and water consumption.
Purpose
Image acquisition and subsequent manual analysis of cardiac cine MRI is time-consuming. The purpose of this study was to train and evaluate a 3D artificial neural network for semantic segmentation of radially undersampled cardiac MRI to accelerate both scan time and postprocessing.
Methods
A database of Cartesian short-axis MR images of the heart (148,500 images, 484 examinations) was assembled from an openly accessible database and radial undersampling was simulated. A 3D U-Net architecture was pretrained for segmentation of undersampled spatiotemporal cine MRI. Transfer learning was then performed using samples from a second database, comprising 108 non-Cartesian radial cine series of the midventricular myocardium to optimize the performance for authentic data. The performance was evaluated for different levels of undersampling by the Dice similarity coefficient (DSC) with respect to reference labels, as well as by deriving ventricular volumes and myocardial masses.
Results
Without transfer learning, the pretrained model performed moderately on true radial data [maximum number of projections tested, P = 196; DSC = 0.87 (left ventricle), DSC = 0.76 (myocardium), and DSC =0.64 (right ventricle)]. After transfer learning with authentic data, the predictions achieved human level even for high undersampling rates (P = 33, DSC = 0.95, 0.87, and 0.93) without significant difference compared with segmentations derived from fully sampled data.
Conclusion
A 3D U-Net architecture can be used for semantic segmentation of radially undersampled cine acquisitions, achieving a performance comparable with human experts in fully sampled data. This approach can jointly accelerate time-consuming cine image acquisition and cumbersome manual image analysis.