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9,882 results for “Scale”
Data from: Crop health is predicted by soil microbial diversity across phylogenetic scales
<p>Soils contain diverse living communities that provide key ecosystem functions in agroecosystems. In many systems, ecosystems functions are positively related to the taxonomic, phylogenetic, and functional diversity of the community. Despite calls to incorporate microbial diversity in measures of soil health, whether increased microbial diversity <em>per se</em> can predict increased crop health and productivity has rarely been documented. Here we used microbial communities from commercial potato fields varying in diversity and composition, and experimentally assessed their ability to promote crop yield under low or high nutrient conditions and to suppress a soil-borne pathogen. Across two independent sets of communities, we found that yields under low nutrient conditions were predicted by high initial microbial diversity measured at broad phylogenetic levels, consistent with greater niche complementarity among unrelated taxa leading to greater total resource use. However, disease suppression was inconsistently linked to diversity and explained as well or better by microbial composition rather than diversity <em>per se</em>. Ecosystem multifunctionality was predicted by high diversity at broad to intermediate phylogenetic scales. These results indicate that the diversity of microbial taxa may influence multiple soil functions; however, the mechanisms underlying the diversity-function relationships may vary.</p>
Results for Genome scale modeling of the protein secretory pathway reveals novel targets for improved recombinant protein production in yeast
<p>This dataset contains the original results for the paper "Genome scale modeling of the protein secretory pathway reveals novel targets for improved recombinant protein production in yeast". To reproduce all figures in this paper, this dataset is required. The scripts can be found in Github (https://github.com/SysBioChalmers/pcSecYeast)</p>
Data from: How far is enough? Prediction of the scale of effect for wild bees
<p class="MsoNormal"><span>A crucial issue for landscape ecologists is identifying the spatial extents at which a landscape affects species occurrence. Multi-scale analyses are usually conducted to identify the "scale of effect", that is, the spatial extent associated with the best relationship between landscape variables and species occurrence, which is assumed to be related to species traits. However, few guidelines exist to determine the range of distances to be investigated.</span></p> <p class="MsoNormal"><span>Based on the foraging distances of wild bee species, our main goal was to estimate the maximum distance of effect, that is, the distance beyond which the scale of effect for wild bee species is unlikely to be detected.</span></p> <p class="MsoNormal"><span>Using the InVEST pollination model, we (i) modelled bee categories with distinct foraging distances and identified the scale of effect on their simulated abundance (ii) defined an index, noted </span><span>λ</span><span>, that estimates the distance beyond which landscape composition has only negligible effects on simulated abundances. We validated our results by identifying the scale of effect on the abundances of 16 bee species collected in south-western France.</span></p> <p class="MsoNormal"><span>We detected a significant positive relationship between the average foraging distance (</span><span>α</span><span>) of the modelled bees and their scale of effect. The </span><span>λ</span><span> index was linearly related to the average foraging distances of bees (</span><span>λ</span><span>=5.4 </span><span>α</span><span>+253) and was above the identified scale of effect for the modelled bees. The </span><span>λ</span><span> was also found to be above the scale of effect for 93% of the observed bee species.</span></p> <p><span>Our results suggest that the </span><span>λ</span><span> index is a good estimator of the upper limit of the scale of effect for wild bees. The </span><span>λ</span><span> index could be used to identify the minimum distance between sampling sites before setting up an experiment and the maximum buffer size required in multi-scale analysis to detect the scale of effect.</span></p>
Multiple drivers of large‐scale lichen decline in boreal forest canopies
<p>Thin, hair-like lichens (<em>Alectoria, Bryoria, Usnea</em>) form conspicuous epiphyte communities across the boreal biome. These poikilohydric organisms provide important ecosystem functions and are useful indicators of global change. We analyse how environmental drivers influence changes in occurrence and length of these lichens on Norway spruce (<em>Picea abies</em>) over 10 years in managed forests in Sweden using data from >6000 trees. <em>Alectoria</em> and <em>Usnea</em> showed strong declines in southern-central regions, whereas Bryoria declined in northern regions. Overall, relative loss rates across the country ranged from 1.7% per year in <em>Alectoria </em>to 0.5% in <em>Bryoria</em>. These losses contrasted with increased length of <em>Bryoria </em>and <em>Usnea </em>in some regions. Occurrence trajectories (extinction, colonization, presence, absence) on remeasured trees correlated best with temperature, rain, nitrogen deposition, and stand age in multinomial logistic regression models. Our analysis strongly suggests that industrial forestry, in combination with nitrogen, is the main driver of lichen declines. Logging of forests with long continuity of tree cover, short rotation cycles, substrate limitation and low light in dense forests are harmful for lichens. Nitrogen deposition has decreased but is apparently still sufficiently high to prevent recovery. Warming correlated with occurrence trajectories of <em>Alectoria</em> and <em>Bryoria</em>, likely by altering hydration regimes and increasing respiration during autumn/winter. The large-scale lichen decline on an important host has cascading effects on biodiversity and function of boreal forest canopies. Forest management must apply a broad spectrum of methods, including uneven-aged continuous cover forestry and retention of large patches, to secure the ecosystem functions of these important canopy components under future climates. Our findings highlight interactions among drivers of lichen decline (forestry, nitrogen, climate), functional traits (dispersal, lichen colour, sensitivity to nitrogen, water storage), and population processes (extinction/colonization).</p>
Plasticity and evolution shape the scaling of metabolism and excretion along a geothermal temperature gradient
<p>Physiological rates are heavily dependent on temperature and body size. Most current predictions of organisms' response to environmental warming are based on the assumption that key physiological rates like metabolism and excretion scale independently with body size and temperature and will not evolve. However, temperature is a significant driver for phenotypic variability in the allometric scaling and thermal sensitivity of physiological rates within ectotherm species, suggesting that evolution may play a role in shaping these parameters.</p> <p>We common-reared six populations of western mosquitofish that have recently established (~100 years ago) in geothermal springs along a broad thermal gradient (19-33°C) to determine whether these scaling parameters are affected by evolutionary and/or plastic responses to warming over ecological timescales. Each population was reared at four different temperatures (23, 26, 30 and 32°C). We measured routine metabolic and nitrogen excretion rates on mosquitofish across a wide body size range.</p> <p>We found evidence for plasticity, but not evolution, increasing the allometric scaling of metabolic rate with temperature. Plasticity in metabolism allometry reflected a decrease in thermal sensitivity at smaller body sizes.</p> <p>We found evidence for evolution of phenotypic plasticity on the allometry of excretion rate, reflecting evolutionary differences in how thermal sensitivity varies with body size across different populations.</p> <p>Evolutionary differences in excretion rate scaling did not influence the relationship between excretion and metabolism across rearing temperatures, suggesting that warming does not affect the balance between mosquitofish energy demands and nutrient recycling rates.</p>
FIGURE 31 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 31. Puto subericola (Vayssière), adult female, reproduced from Danzig & Gavrilov-Zimin (2014: 160, Fig. 2.1.1-8) with the authors' permissions. Note that each trochanter has three campaniform sensilla on each surface.
FIGURE 30 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 30. Ortheziolacoccus jermyi (Kozár & Miller), adult female, reproduced from Kozár & Miller (2000: 27, Fig. 8) with permission from John Wiley and Sons.
FIGURE 29 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 29. Matileortheziola angolaensis (Kozár & Foldi), adult female, reproduced from Kozár and Foldi (2000: 253, Fig. 1), rights reserved - with permission of Revue française d'Entomologie (N.S.).
FIGURE 27 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 27. Ortheziolamameti kosztarabi (Kozár & Miller), adult female, reproduced from Kozár & Miller (2000: 28, Fig. 9) with permission from John Wiley and Sons.
FIGURE 26 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 26. Orthezia urticae (Linnaeus), adult female, reproduced from Kozár (2004: 375, Fig. 158) with permission from Agrártudományi Kutatóközpont.
FIGURE 24 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 24. Newsteadia angustilinea Miller & Kozár, adult female, reproduced from Miller & Kozár (2002: 210, Fig. 2) with permission from D.R. Miller.
FIGURE 23 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 23. Insignorthezia insignis (Browne), adult female, modified from Kozár (2004: 307, Fig. 129) with permission from Agrártudományi Kutatóközpont. AS: abdominal spiracles; A: appearance in life from Green (1922: Plate CLXXIV, 2 and 4).
FIGURE 22 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 22. Gigantococcus and Icerya pores from Unruh & Gullan (2008: 16-18, parts of Table 2), © Magnolia Press, www. mapress.com/j/zt, reproduced with permission of the copyright holder.
FIGURE 9 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 9. Monophlebidae: Iceryini, adult female anatomy, from Unruh & Gullan (2007: 14, Fig. 1), © Magnolia Press, www. mapress.com/j/zt, reproduced with the copyright holder's permission.
FIGURE 18 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 18. Walkeriana floriger (Walker), adult female, developed from Morrison (1928: 142, Fig. 68). Note that this illustration shows the genotype, a species that does not occur in Africa.
FIGURE 16 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 16. Palaeococcus fuscipennis (Burmeister) ex Gavrilov-Zimin (2018: 172, Fig. 9.4.15.), reproduced with the author's permission.
FIGURE 10 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 10. Icerya seychellarum Westwood, adult female, from Williams & Watson (1990: 24, Fig. 5), reproduced with permission of the authors and CABI.
FIGURE 13 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 13. "Steatococcus" hystrix Gavrilov-Zimin & Stekolshikov, adult female, from Gavrilov-Zimin & Stekolshikov (2018: 866), reproduced with permission from Pleiades Publishing, Ltd.
FIGURE 5 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 5. Porphyrophora hirsutissima (Hall), adult female, from Vahedi & Hodgson (2007: 61, Fig. 14), reproduced with permission from the Editor, Journal of Natural History, A: antenna; B: foreleg; C: hind leg.
FIGURE 2 in Towards identification of the scale insects (Hemiptera: Coccomorpha) of continental Africa: 2. Checklists and keys to six archaeococcoid families
FIGURE 2. Margarodidae, morphology of adult female; Dimargarodes tanganyicus Jakubski from Vahedi & Hodgson (2007: 32, Fig. 3), reproduced with permission © Trustees of the Natural History Museum, London, U.K.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.