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256 results for “mass effects”
Data from: Widespread bird species show idiosyncratic responses in residual body mass to selective logging and edge effects in the Colombian Western Andes
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Effectiveness of seasonal malaria chemoprevention administered in a mass campaign in the Kedougou region of Senegal in 2016: a Case-control study
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The effects of body mass on immune cell concentrations of terrestrial mammals
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Effects of endurance flight on mitochondrial physiology, lean mass dynamics and flight muscle morphology in blackpoll warblers
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Experimental manipulation of scavenger and herbivore functional role and their effects on plant communities following mass mortality events
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Effects of intraspecific competition and body mass on diet specialisation in a mammalian scavenger
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A metacommunity approach for detecting species influenced by mass effect
<p>1. Mass effect, allowing species to persist in unfavourable habitats, and dispersal limitation, preventing species from reaching favourable habitats, are the two major dispersal processes. While dispersal limitation can be detected by experimental or modeling techniques, mass effect is more challenging to evaluate, which hampers our ability to disentangle the influence of the environment vs. dispersal on species distribution. This is undesirable for biomonitoring programs built on known species-environment relationships.</p> <p>2. We developed an approach for detection of species influenced by mass effect. We tested it on stream diatoms, a widely used taxonomic group for stream biomonitoring, from four French watersheds. This approach combined (1) an appropriate spatial framework, the Asymmetric Eigenvector Map (AEM), used in species distribution modeling to measure the relative influence of dispersal vs. niche processes, (2) an analysis of negative co-occurrence patterns to separate mass effect from dispersal limitation, and (3) a measurement of niche breadths to distinguish between non-spatially structured generalists and species influenced by mass effect.</p> <p>3. We propose that species characterized by low negative co-occurrence values, a high correlation to spatial factors and average to low niche breadths are sensitive to mass effect.</p> <p>4. Synthesis and applications: We suggest that the sensitivity of species towards mass effect should represent a new ecological trait to be considered for fundamental and applied issues concerning ecology and water quality assessment. Almost all of the species identified here as influenced by mass effect are contributing to the calculation of different diatom-based indices (e.g., Biological Diatom Index or Specific Pollution-sensitivity Index) and should be treated with caution when assigning ecological status classes to water bodies.</p>
Data from: Floral display and habitat fragmentation: effects on the reproductive success of the threatened mass-flowering Conospermum undulatum (Proteaceae)
1. Fragmentation of natural vegetation is currently one of the largest threats to plant populations and their interactions with pollinators. Plant reproductive susceptibility to habitat fragmentation has been investigated in many species; however, the response of wild mass-flowering species is poorly known, with research limited to mainly boreal plant species. 2. Here we studied twelve remnant populations of the threatened mass-flowering shrub Conospermum undulatum in the southwest Australian biodiversity hotspot, each presenting different population size, level of isolation, and floral display. We assessed the impact of fragmentation on: 1) fruit and seed production; and 2) seed germination. To gain a deeper understanding of factors influencing the reproductive success of C. undulatum we performed pollinator exclusion and self-pollination treatments to experimentally assess the mating system of this threatened shrub. 3. We found C. undulatum to be strictly self-incompatible and totally reliant on pollinators visiting with an outcrossed pollen load to complete the reproductive cycle. Further, we found that fruit production significantly decreased with decreasing floral display. A decrease in population size and floral display led to a decrease in seed output, while increasing isolation also led to a reduced production of seeds. Overall, seed germination was positively related to population size, and a negative relationship was found between germination and isolation. 4. Our results demonstrate the important relationship between pollinators and floral morphology in plants of southwest Australia that have coevolved with native pollinators and developed characteristic flower morphologies over long timeframes. The self-incompatible C. undulatum cannot rely on its mass-flowering trait to attract pollinators from co-flowering species, neither can it compensate for the lack of visitors by promoting geitonogamy. Consequently, fragmentation has a significant effect on the reproductive output of C. undulatum, and size, isolation, and floral display of populations should be considered when planning conservation actions for the species.
Effectiveness of traps and attractants in mass capture of Hypothenemus hampei in Sao Tome Island
<p>In this sense, we studied the bio-ecology of the CBB, in particular the presence of immature stages and adult of CBB during the development of the coffee berry, and to quantify population levels, as well as CBB infestation, natural enemies and penetration rates inside developing coffee berries in six coffee plantations of CECAFEB located in three regions (Districts) and one in the Centre of Technological and Agricultural Investigation of Sao Tome and Principe-Experimental Base of Industrial Crops (CIAT/STP-BECI). We also evaluate attractants in home-made traps baited for mass capture of the CBB in three coffee plantations of CECAFEB located in two regions (Districts).</p>
Data from: Berry production drives bottom-up effects on body mass and reproductive success in an omnivore
Obligate herbivores dominate studies of the effects of climate change on mammals, however there is limited empirical evidence for how changes in the abundance or quality of plant food affect mammalian omnivores. Omnivores can exploit a range of different food resources over the course of a year, but they often rely on seasonally restricted highly nutritious fruiting bodies during critical life stages. Brown bears Ursus arctos in Sweden are dependent on berries for fattening before entering hibernation. We used a ten-year time series to evaluate the effect of temperature and snow on annual variation in berry abundance and how this variation affected bears. We found marked interannual variation in berry production of bilberry Vaccinium myrtillus and lingonberry V. vitis-idaea, that we could attribute in part to temperature during plant dormancy and flowering and precipitation during fruit ripening. Both, autumn weights of female bears and spring weights of yearling bears increased linearly with bilberry abundance. When bilberry abundance was low, lightweight female bears had a lower reproductive success than females in better condition. This effect vanished when food abundance was above average, indicating that lightweight females could compensate for their initial weight during good bilberry years. Our study highlights the importance of considering individuals' dynamic responses to variation in food availability, which leave some more vulnerable to food shortage than others. Individual life-history heterogeneity in response to resource variation likely affects long-term population recruitment. Our findings emphasize that Scandinavian bears can be dependent on a single food resource during a critical period of the year and are therefore less resilient to environmental change than expected for an omnivore. Future climate scenarios predict ambiguous trends for weather covariates that affected crucial stages of berry phenology, preventing a clear prognosis of how climate change may affect long-term bilberry production.
Mass ratio effects underlie ecosystem responses to environmental change
1. Random species loss has been shown experimentally to reduce ecosystem function, sometimes more than other anthropogenic environmental changes. Yet, controversy surrounds the importance of this finding for natural systems where species loss is non-random. 2. We compiled data from 16 multi-year experiments located at a single site in native tallgrass prairie. These experiments included responses to 11 anthropogenic environmental changes, as well as non-random biodiversity loss - either the removal of uncommon/rare plant species or the most common (dominant) species. 3. As predicted by the mass ratio hypothesis, loss of a dominant species had large impacts on productivity that were comparable to other anthropogenic drivers. In contrast, the loss of uncommon/rare species had small effects on productivity despite having the largest effects on species richness. 4. The anthropogenic drivers that had the largest effects on productivity – nitrogen, irrigation, and fire – experienced not only loss of species but also significant changes in the abundance and identity of dominant species. 5. Synthesis. These results suggest that mass ratio effects rather than species loss per se is an important determinant of ecosystem function with environmental change.
Dynamics of island mass effect: detection input & output data
<p>"dynamic_IMEdetection.zip" contains a dynamic island mass effect detection software package.</p> <p>To run:</p> <ul> <li>Unzip "dynamic_IMEdetection.zip"</li> <li>Download input data</li> <li>change path, region to process, and options in "main_dynamicIME_detection.m" to work with the location of the unzipped "dynamic_IME_input_output_data" directory.</li> <li>Run "main_dynamicIME_detection.m"</li> </ul> <p>"dynamic_IME_input_output_data.zip" contains the input data and ouput IME and BO masks of the "dynamic_IMEdetection" software for four case studies:</p> <ul> <li>I04 = Rapa Nui</li> <li>I07 = Society Islands</li> <li>I09 = Samoa</li> <li>I18 = Fiji-Tonga</li> </ul> <p>Input data are custom multi-satellite products computed using the custom-made satellite binning software found here: <a href="../doi/10.5281/zenodo.13376824">10.5281/zenodo.13376824</a>.</p> <p>Output IME and BO masks are computed using the dynamic IME detection software (i.e. "dynamic_IMEdetection") which works with the original naming (i.e. "I04", "I07", "I09", and "I18") and subdirectory path of of the share data "dynamic_IME_input_output_data".</p> <p>Output IME/BO mask, chlorophyll concentration, and modelled surface current timeseries in *.gif format:</p> <ul> <li>RapaNui_8Dbin_20160520-0712_20161205-2230_map-time-series.gif = Rapa Nui between 2016/05/20 and 2016/12/05</li> <li>SocietyIsl_8Dbin_20160622-1012_20170209-0945_map-time-series.gif = Society Islands between 2016/06/22 and 2017/02/09</li> <li>Samoa_8Dbin_20160810-1115_20170226-1030_map-time-series.gif = Samoa between 2016/08/10 and 2017/02/26</li> <li>FijiTonga_8Dbin_20170218-1240_20170906-1205_map-time-series.gif = Fiji - Tonga between 2017/02/18 and 2017/09/06</li> </ul>
Fig. 3 in Effects of the Naturally Occurring Parasitic NematodeChondronema passaliLeidy on Lifting Strength and Captivity-Related Body Mass Patterns in the Horned Passalus Beetle,Odontotaenius disjunctus(Illiger) (Coleoptera: Passalidae)
Fig. 3. Comparison of maximum lifting strength between Odontotaenius disjunctus with and without Chondronema passali across three weeks of study. Whiskers above and below means represent 95% confidence intervals.
Fig. 4 in Effects of the Naturally Occurring Parasitic NematodeChondronema passaliLeidy on Lifting Strength and Captivity-Related Body Mass Patterns in the Horned Passalus Beetle,Odontotaenius disjunctus(Illiger) (Coleoptera: Passalidae)
Fig. 4. Patterns of weight loss in Odontotaenius disjunctus with or without Chondronema passali across three weeks of study. Beetles lost 11% of their initial body mass when placed in captivity (A), which was not fully regained at the end of three weeks. Parasitized beetles tended to lose less mass than did non-parasitized beetles; this effect was not significant at Week 1 (B), but was significant at Week 3 (C). Whiskers above and below means in A represent standard errors; those in B and C represent 95% confidence intervals.
Fig. 1 in Effects of the Naturally Occurring Parasitic NematodeChondronema passaliLeidy on Lifting Strength and Captivity-Related Body Mass Patterns in the Horned Passalus Beetle,Odontotaenius disjunctus(Illiger) (Coleoptera: Passalidae)
Fig. 1. Depiction of lifting force measurement in this study. Beetles were positioned under a vertically mounted force gauge, using pins on either side of their body (A). The experimenter gently tapped the elytra which stimulated upward lifting. Force readings (B) were obtained over a five-minute period, and the maximum reading was retained for analyses. Further details of this device and procedure are given by (Davis 2014).
Fig. 2 in Effects of the Naturally Occurring Parasitic NematodeChondronema passaliLeidy on Lifting Strength and Captivity-Related Body Mass Patterns in the Horned Passalus Beetle,Odontotaenius disjunctus(Illiger) (Coleoptera: Passalidae)
Fig. 2. Relationship between body size (initial body mass) and maximum lifting strength (at Week 1) in Odontotaenius disjunctus.
SCM files for "Representing Effects of Surface Heterogeneity in a Multi-Plume Eddy Diffusivity Mass Flux Boundary Layer Parameterization"
<p>Supporting files for manuscript "Representing Effects of Surface Heterogeneity in a Multi-Plume Eddy Diffusivity Mass Flux Boundary Layer Parameterization" by N.P. Arnold.</p> <p>The data consists of source code modifications relative to v11.2.0 of the GEOS GCM, modified boundary conditions for running single column model experiments, and netcdf model output from those experiments.</p>
Lipidomics and metabolomics datasets for "Adverse effects of arsenic uptake in rice metabolome and lipidome revealed by untargeted liquid chromatography coupled to mass spectrometry (LC-MS) and regions of interest multivariate curve resolution"
<p><strong>Files description</strong></p> <p>Raw files for lipidomics and metabolics studies on the impact of arsenic exposure on rice growth.</p> <p>File details on the worksheets lipids_files.xlsx and metabolomics_files.xlsx</p> <p>Files have been organized as follows:</p> <p><strong>Lipidomics</strong></p> <blockquote> <p>1) Control samples: lip_controls.rar<br> 2) Watering low As exposure: lip_water_1.rar<br> 3) Watering high As exposure: lip_water_1000.rar<br> 4) Soil low As exposure: lip_soil_5.rar<br> 5) Soil high As exposure: lip_soil_50.rar<br> 6) QC samples: lip_qcs.rar</p> </blockquote> <p><strong>Metabolomics (positive ionization mode)</strong></p> <blockquote> <p>1) Control samples: met_pos_controls.rar<br> 2) Watering low As exposure: met_pos_water_1.rar<br> 3) Watering high As exposure: met_pos_water_1000.rar<br> 4) Soil low As exposure: met_pos_soil_5.rar<br> 5) Soil high As exposure: met_pos_soil_50.rar<br> 6) QC samples: met_pos_qcs.rar</p> </blockquote> <p><strong>Metabolomics (negative ionization mode)</strong></p> <blockquote> <p>1) Control samples: met_neg_controls.rar<br> 2) Watering low As exposure: met_neg_water_1.rar<br> 3) Watering high As exposure: met_neg_water_1000.rar<br> 4) Soil low As exposure: met_neg_soil_5.rar<br> 5) Soil high As exposure: met_neg_soil_50.rar<br> 6) QC samples: met_neg_qcs.rar<br> </p> </blockquote> <p> </p> <p><strong>Experimental details</strong></p> <blockquote> <p><strong>Arsenic Exposure</strong></p> <p>Arsenic was supplied through two main routes: watering with contaminated water or soil containing arsenic. In addition, this new study includes metabolomic as well as lipidomic analysis, in order to have a more global overview of arsenic exposure.</p> <p>For the watering treatment, during the first 11 days, rice was irrigated with Milli-Q water. From that day until harvesting, plants were watered with 1 and 1000 μM of As (V) for the two concentration levels of exposure, and with Milli-Q water for control samples. The lowest concentration was established at 1 μM as it is the limit of the acceptable arsenic concentration in water by European legislation. The upper concentration was set at 1000 μM, a threshold established to ensure that the experiment was performed under sub-lethal arsenic concentration for the plant, based on previous studies.</p> <p>For the soil treatment, two containers were prepared with 1 kg of soil two days before planting. Soil from the container was exposed to two arsenic concentration levels (5 and 50 mg L<sup>-1</sup>). Once sowing, rice was irrigated the whole growth period with a solution containing 0.001 μM of As (V). The lowest arsenic limit in this treatment was set at 5 mg L<sup>-1</sup> as a maximum value of common arsenic leaches without toxic characteristics, although background soil content of arsenic varies between one and 40 ppm according to the US food and drug administration (FDA) report. The highest arsenic limit was established to 50 mg L<sup>-1</sup>, as a considerably high arsenic content in the soil, slightly above the maximum frequently encountered levels.</p> <p><strong>Lipidomic Analysis</strong></p> <p>The lipidomic analysis was performed using a Waters Acquity UPLC system (Waters Corporation, MA, USA), connected to a Waters LCT Premier orthogonal accelerated time of flight mass spectrometer (Waters), operated in both positive and negative electrospray (ESI) ionization modes. Full scan spectra were acquired from 50 to 1500 Da.</p> <p>The chromatographic column employed was a Kinetex C8 (100 x 2.1 mm, 1.7 μm) (Phenomenex) under the following conditions (already used in [47]): temperature at 30˚C, injection volume at 10 μL, and flow rate at 0.3 mL min<sup>-1</sup>. Mobile phases selected were (A) MeOH 1mM ammonium formate, and (B) H<sub>2</sub>O 2mM ammonium formate, both at 0.2% formic acid. The gradient started at 80% A, increased to 90% A in 3 min, from 3 to 6 min remained at 90% A, changed to 99 % A until minute 15, remained constant 1 min, and returned to initial conditions until minute 20.</p> <p><strong>Metabolomic analysis</strong></p> <p>The metabolomic analysis was performed using a Waters Acquity UPLC system connected to a Q-Exactive (Thermo Fisher Scientific, Hemel Hempstead, UK) equipped with a quadrupole-Orbitrap mass analyzer. Electrospray (ESI) was used as an ionization source in both positive and negative ion modes. Full scan mass range was set from <em>m/z</em> 90 to 1000, and all ion fragmentation (AIF) was performed with normalized collision energy (NCE) of 35 eV.</p> <p>The column employed was an HILIC TSK gel amide-80 column (250 x 2.0 mm i.d., 5 μm) provided by Tosoh Bioscience (Tokyo, Japan), under the following experimental conditions (already employed in [45]): flow rate at 0.15 mL min<sup>-1</sup>, at room temperature, and 5 μL injection volume. Mobile phases were (A) AcN, and (B) 5 mM ammonium acetate, adjusted at pH 5.5 with acetic acid. The gradient employed was: starting conditions at 25% B, then increased until 30% B in 8 min; a 60% B was reached at 10 min, held for 2 min more and then back to 25% B until minute 14 min; lastly, a re-equilibration step was added and from 14 to 20 min at 25% B.</p> </blockquote> <p> </p> <p><strong>Funding:</strong> This research was funded by the Spanish Ministry of Science and Innovation (MCI, Grant CTQ2017-82598-P) and Severo Ochoa Project CEX2018-000794-S (funded by MCIN/AEI/ 10.13039/501100011033), and supported from the Catalan Agency for Management of University and Research Grants (AGAUR, Grant 2017SGR753). MPC was funded by a predoctoral FPU 16/02640 scholarship from the Spanish Ministry of Education and Vocational Training (MEFP). </p> <p> </p>
Data from: Transgenerational genetic effects help explain latitudinal variation in seed mass and germination timing in Plantago lanceolata
<p>We know little about the underlying genetic control of phenotypic patterns of seed traits across large-scale geographic and environmental gradients. Such knowledge is important for understanding the evolution of populations within species and for improving species conservation. Therefore, to test for genetic variation in <em>P. lanceolata</em>, we made reciprocal crosses between northern and southern genotypes that span the species' range in Europe. Results provide evidence of transgenerational genetic effects on seed mass and germination timing. Northern mothers produced larger seeds with delayed germination, in contrast to southern mothers, which produced smaller seeds with accelerated germination. Maternal latitude affected both the seed coat, solely maternal tissue, and embryo/endosperm tissues. Thus, latitudinal variation in seed size and germination timing can be explained, in part, by the direct influence of maternal genotype, independent of zygotic genes that parents pass directly to the embryo and endosperm. Data suggest that researchers exploring the existence and evolution of large-scale geographic variation within species test for transgenerational genetic effects. Also, data suggest that transgenerational control of seed traits should be considered when developing procedures designed to facilitate species conservation and restoration.</p>
Data from: Effects of landscape complexity on pollinators are moderated by pollinators' association with mass-flowering crops
Conserving and restoring semi-natural habitat, i.e. enhancing landscape complexity, is one of the main strategies to mitigate pollinator decline in agricultural landscapes. However, we still have limited understanding of how landscape complexity shapes pollinator communities in both crop and non-crop habitat, and whether pollinator responses to landscape complexity vary with their association with mass-flowering crops. Here, we surveyed pollinator communities on mass-flowering leek crops and in nearby semi-natural habitat in landscapes of varying complexity. Surveys were done before and during crop bloom and distinguished between pollinators that visit the crop frequently (dominant), occasionally (opportunistic) or not at all (non-crop). Forty-four percent of the species in the wider landscape were also observed on leek flowers. Crop pollinator richness increased with local pollinator community size and increasing landscape complexity, but relationships were stronger for opportunistic than for dominant crop pollinators. Relationships between pollinator richness in semi-natural habitats and landscape complexity differed between groups with the most pronounced positive effects on non-crop pollinators. Our results indicate that while dominant crop pollinators are core components of crop pollinator communities in all agricultural landscapes, opportunistic crop pollinators largely determine species-richness responses and complex landscapes are local hotspots for both biodiversity conservation and potential ecosystem service-provision.
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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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.