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opencc-by-4.0Apr 2023View details →

Flnc: Machine Learning Improves the Identification of Novel Long Noncoding RNAs from Stand-Alone RNA-Seq Data

Flnc is software that can accurately identify full-length long noncoding RNAs (lncRNAs) from human RNA-seq data. lncRNAs are linear transcripts of more than 200 nucleotides that do not encode proteins. The most common approach for identifying lncRNAs from RNA-seq data which examines the coding abilities of assembled transcripts will result in a very high false-positive rate (30%-75%) of lncRNA identification. The falsely discovered lncRNAs lack transcriptional start sites and most of them are RNA fragments or result from transcriptional noise. Unlike the false-positive lncRNAs, true lncRNAs are full-length lncRNA transcripts that include transcriptional start sites (TSSs). To exclude these false lncRNAs, H3K4me3 chromatin immunoprecipitation sequencing (ChIP-seq) data had been used to examine transcriptional start sites of putative lncRNAs, which are transcripts without coding abilities. However, because of cost, time, and the limited availability of sample materials for generating H3K4me3 ChIP-seq data, most samples (especially clinical biospecimens) may have available RNA-seq data but lack matched H3K4me3 ChIP-seq data. This Flnc method solves the problem of lacking transcriptional initiation profiles when identifying lncRNAs. Flnc integrates seven machine-learning algorithms built with four genomic features. Flnc achieves state-of-the-art prediction power with a AUROC score over 0.92. Flnc significantly improves the prediction accuracy from less than 50% using the common approach to over 85% on five independent datasets without requiring matched H3K4me3 ChIP-seq data. In addition to the stranded polyA-selected RNA-seq data, Flnc can also be applied to identify lncRNAs from stranded RNA-seq data of ribosomal RNA depleted samples or unstranded RNA-seq data of polyA-selected samples.

opencc-by-4.0Apr 2023View details →

Dataset: Long Range Electron Transport Rates Depend on Wire Dimensions in Cytochrome Nanowires

The ability to redirect electron transport to new reactions in living systems opens possibilities to store energy, generate new products, or probe physiological processes. Recent work by Huang et al. showed that 3D crystals of small tetraheme cytochromes (STC) could transport electrons over nanoscopic to mesoscopic distances by an electron hopping mechanism. Such protein-based structures with multiple localized electron carriers are promising materials for nanowires. A potential barrier to protein nanowire adoption for handling long-range electron transport is that fluctuations at room temperature may distort the nanostructure, hindering efficient electron transport. To study these fluctuations at the nano- and mesoscopic scales, we carry out classical molecular dynamics simulations for a small fragment of a STC nanowire and measure the effective distance distribution for electron tunneling. From distance distributions, we develop a graph network representation for electron transport along nanowires with varying dimensions, and through stochastic methods determine the maximum electron flow that can be driven through these STC wires. Longer nanowires were capable of carrying less electron flow than shorter nanowires with the same diameter, as long electron transfer distances that occasionally arise reduce the efficiency for electron transport. Thicker nanowires permit more alternative transport pathways, increasing electron transport beyond the increase in cross-section. Thus, this model implies that the design of protein-based nanowires that depend on electron hopping between charge carriers must consider control of the inherent protein flexibility, as more flexible protein-protein interfaces impose a limit on the required minimum diameter to carry currents commensurate with conventional electronics.

opencc-zeroApr 2023View details →

Model for: Characterizing long‐term population conditions of the elusive red tree vole with dynamic individual‐based modeling

<div class="abstract"> Old growth forests are declining globally, threatening dependent wildlife. Many arboreal old‐growth obligates, such as the threatened red tree vole, are difficult to monitor for changes in habitat occupancy, and abundance. Yet, conservation planning relies on this information to prevent population declines. We integrated a range of species, habitat, and landscape change information to develop a dynamic habitat‐population model. The spatial individual‐based model simulated dynamic patterns of occupancy that responded to annual habitat maps, describing 36 years of observed change. We simulated population dynamics and local movement to characterize changes in occupancy and abundance, and the capacity of remaining habitat to support red tree voles. Red tree vole redistribution patterns strongly corresponded to wildfire footprints and timber extraction locations. Population strongholds are likely to exist in clumped pockets of old‐growth forest that were unaffected by wildfire and in protected old forest reserves. However, the exact number and locations of local clusters remain uncertain. Simulated population losses occurred at different paces in different places, underscoring the need for recurring evaluation of population changes with field occupancy surveys and modeled evaluations that can anticipate potential connectivity and extirpation thresholds. This modeling approach was effective at leveraging existing information for a data‐light species to assess how historical changes to the quantity, quality, and configuration of habitat likely influenced the potential landscape capacity, species abundance, and distribution. Dynamic individual‐based modeling can benefit conservation planning for red tree vole and other reclusive forest species by providing biologically nuanced assessments of abundance and distribution. Such models can also project the long‐term benefits and impacts of spatially explicit land management plans. </div> <div class="abstract"></div>

opencc-zeroApr 2023View details →

Molecular epidemiology and risk factors for extended-spectrum β-lactamase-producing Enterobacterales in long-term care residents

<div class="abstract-content selected"> Objectives: We aimed to assess the burden of extended-spectrum β-lactamase (ESBL)-producing Enterobacterales in Swiss long-term care facilities (LTCFs) to describe the molecular epidemiology, describe the intra-institutional and regional clusters of resistant pathogens, and identify independent institution- and resident-level factors associated with colonization. Design: Cross-sectional study. Setting and participants: From August to October 2019, we performed a point prevalence study among residents from 16 LTCFs in Western and Eastern Switzerland (8 per region). Methods: Residents underwent screening for ESBL-producing Enterobacterales (ESBL-E); whole-genome sequencing (WGS) was performed. We gathered institution-level (eg, number of beds, staff-resident ratio, alcoholic hand rub consumption) and resident-level [eg, anthropometric data, time in facility, dependency, health care exposure, antibiotic treatment, proton-pump inhibitor (PPI) use] characteristics. Factors associated with colonization were identified using a generalized linear model. Results: Among 1185 eligible residents, 606 (51%) consented to the study. ESBL-E prevalence was 11.6% (70/606), ranging from 1.9% to 33.3% between institutions, with a median of 12.5% in the West and 6.9% in the East (P = .03). Among 59 Escherichia coli (from 58 residents), multilocus sequence type (ST) 131 was most common (n = 43/59, 73%), predominantly its subclone H30R1 (n = 37/43, 86%). WGS data identified multiple intra-institutional and regional clusters. Independent risk factors for ESBL carriage were previous ESBL colonization [adjusted odds ratio (aOR) 23.5, 95% confidence interval (CI) 6.6–83.8, P < .001), male gender (aOR 2.6, 95% CI 1.5–4.6, P = .002), and use of PPIs (aOR 2.2, 95% CI 1.2–3.8, P = .01). Conclusions and implications: Overall ESBL-E prevalence in Swiss LTCF residents is low. Yet, we identified several clusters of residents with identical pathogens within the same institution. This implies that particularly affected institutions might benefit from targeted infection control interventions. PPI use was the only modifiable factor associated with carriage of ESBL producers. This study adds to the growing list of adverse outcomes associated with PPIs, calling for action to restrict their use in the long-term care setting. </div>

opencc-by-4.0Apr 2022View details →

Persistent serum protein signatures define an inflammatory subcategory of long COVID

Readme: This repository consists of the input data, figure source data and R-code to perform analysis and generate figures of the manuscript   Abstract: Long COVID or post-acute sequelae of SARS-CoV-2 (PASC) is a clinical syndrome featuring diverse symptoms that can persist for months following acute SARS-CoV-2 infection. The aetiologies may include persistent inflammation, unresolved tissue damage or delayed clearance of viral protein or RNA, but the biological differences they represent are not fully understood. Here we evaluate the serum proteome in samples, longitudinally collected from 55 PASC individuals with symptoms lasting ≥60 days after onset of acute infection, in comparison to samples from symptomatically recovered SARS-CoV-2 infected and uninfected individuals. Our analysis indicates heterogeneity in PASC and identified subsets with distinct signatures of persistent inflammation. Type II interferon signaling and canonical NF-κB signaling (particularly associated with TNF), appear to be the most differentially enriched signaling pathways, distinguishing a group of patients characterized also by a persistent neutrophil activation signature. These findings help to clarify biological diversity within PASC, identify participants with molecular evidence of persistent inflammation, and highlight dominant pathways that may have diagnostic or therapeutic relevance, including a protein panel that we propose as diagnostic utility for differentiating inflammatory and non-inflammatory PASC.

opencc-zeroApr 2023View details →

Data from: Long-term grazing intensity by reindeer alters the response of the soil micro-food web to simulated climate change in subarctic tundra

Top-down control by nematodes over soil microorganisms – considered stronger over bacteria than fungi - may dampen microbial responses to global changes in tundra. To test whether large grazers alter the responses of belowground trophic networks to global changes, we employed factorial warming and nitrogen fertilization treatments in adjacent sites with different reindeer grazing intensities for the past 50 years. Lightly grazed tundra is dominated by dwarf shrubs and a more fungal-based microbial community, while in heavily grazed tundra, high reindeer densities during autumn migration have induced shift into graminoids and more bacterial-based microbial community. We analysed the soil micro-food web, i.e., the nematode density, trophic structure, and species composition as well as fungal, bacterial and total phospholipid fatty acids (PLFAs) after four growing seasons of warming and fertilization both before and during reindeer migration. We predicted that bacterivore densities are higher and fungivore densities lower under heavy than light grazing (i.e., nematode populations before migration reflect grazing effects via the base of food web), whereas reindeer migration induces negative impact on nematode densities under heavy grazing (i.e., disturbance by trampling is the driving factor). We further predicted that nematodes negate treatment effects on microbial biomass to a stronger extent in the bacterial-based heavily grazed than the fungal-based lightly grazed tundra. Fungivore densities were higher under light than heavy grazing, but nematodes did not respond to trampling. Warming increased fungivores and the fungal PLFAs irrespective of grazing and timing, but under heavy grazing, increased bacterivores while the bacterial PLFAs remained steady. Fertilization increased carnivores and influenced nematode species composition, diversity and maturity interactively with warming. Our data suggest that large grazers affect tundra soil nematodes via bottom-up effects through microbial community composition and biomass, which in turn may alter the strength of their top-down control soil bacteria under climate warming.

Data from: Compensatory growth is accompanied by changes in insulin-like growth factor-1 but not markers of cellular aging in a long-lived seabird

Developing organisms often plastically modify growth in response to environmental circumstances, which may be adaptive, but is expected to entail long-term costs. However, the mechanisms that mediate these growth adjustments and any associated costs are less well understood. In vertebrates, one mechanism that may be important in this context is the highly conserved signaling factor insulin-like growth factor-1 (IGF-1), which is often positively related to post-natal growth and negatively related to longevity. To test this idea, we exposed captive Franklin's gulls (Leucophaeus pipixcan) to a physiologically relevant nutritional stressor by restricting food availability during post-natal development and examined the effects on growth, IGF-1, and two potential biomarkers of cellular and organismal aging (oxidative stress, and telomeres). During food restriction, experimental chicks gained body mass more slowly and had lower IGF-1 levels than controls. Following the food restriction, experimental chicks underwent compensatory growth, which was accompanied by an increase in IGF-1 levels. Interestingly however, there were no significant effects of the experimental treatment or of variation in IGF-1 levels on oxidative stress or telomeres. These findings suggest that IGF-1 is responsive to changes in resource availability but is not associated with increased markers of cellular aging during development in this relatively long-lived species.

Metadata for: Environmental adaptations by the intertidal Antarctic cyanobacterium Halotia branconii CENA392 as revealed using long-read genome sequencing

Antarctica poses numerous challenges to life such as cold shock, low nutrient concentrations and periodic desiccation over a wide range of extreme temperatures. Cyanobacteria survive this harsh environment having evolved adaptive metabolic plasticity to become the dominant primary producers. The type strain cyanobacterium Halotia branconii CENA392 was isolated from an Antarctic intertidal seashore. The complete circular genome of this strain is presented herein, which was assembled using long sequence reads. The genome encoded some stress-related genes associated with low-temperature adaptation and biosynthesis of mycosporine-like amino acid (MAA) photoprotective compounds. Empirical experimentation demonstrated constitutive production of the MAA porphyra-334 and total carotenoids without exposure to low temperatures or ultraviolet radiation stress. Phylogenetic analysis provided insights on the taxonomic placement and the evolutionary history of some annotated genes. These data exemplify the importance of generating complete quality genome sequences of microorganisms isolated from extreme intertidal environments, facilitating in-depth evaluation of ecological and taxonomic inferences.

Effects of long-term fixed fire regimes on African savanna vegetation biomass, vertical structure and tree stem density

<ol> <li>Fire plays an integral role in shaping the vegetation structure of savanna ecosystems. However, effects of fire regime characteristics, such as frequency and season of burn, on savanna vegetation structure, biomass and tree abundance across landscape types are largely unknown. </li> <li>We used high-resolution airborne Light Detection and Ranging (LiDAR) to investigate the long-term effects of fire manipulation on savanna vegetation in Kruger National Park, South Africa. We analysed the effects of fire exclusion and experimental burns every 1, 2, 3, 4 and 6 years and during different seasons on aboveground biomass (AGB), tree stem densities and vegetation vertical height profiles across a rainfall gradient and on contrasting geologies. </li> <li>Across savanna types, and especially in drier savannas, fire season was more influential for constraining AGB than was fire frequency. Plots experiencing fires during the late- and mid-dry season had 44.50% and 43.60%, respectively, lower AGB relative to unburnt plots than wet-season fires. However, in mesic savannas, fire frequency interacted with fire season to influence AGB: plots subjected to high frequency, dry season fires had 55.35% lower AGB than unburnt plots, whereas plots burnt in the wet season at lower frequencies had lower AGB (24.40% lower than unburnt plots) than plots subjected to high frequency, wet-season fires (13.74% lower AGB than unburnt plots). </li> <li>Fire regimes had variable effects on tree densities, and effects varied with savanna type. Woody vertical vegetation profiles showed the largest differences in response to dry season fires, with the greatest divergence in vegetation height classes < 5m. </li> <li>Synthesis and applications. Understanding the influence of fire regimes on vegetation structure has important implications for the management of savanna heterogeneity, and for predicting trajectories of change in savanna vegetation as fire regimes vary with climate change. We show that the magnitude of the effect of fire on woody vegetation structure varies with savanna context. Our results suggest that heterogeneous vegetation structure can be achieved by applying fires in the dry season in mesic savannas, whereas in dry savannas, variation in fire regimes is less consequential for constraining biomass accumulation and altering vegetation structure. </li> </ol>

opencc-by-4.0May 2023View details →

Tailored machine learning for evaluating the long-term diabetes risk in older individuals: Findings from The Irish Longitudinal Study on Ageing (TILDA)

The original data for "Tailored machine learning for evaluating the long-term diabetes risk in older individuals: Findings from The Irish Longitudinal Study on Ageing (TILDA)" that published in BMJ Open.

opencc-by-4.0Nov 2020View details →

Figure 1. A in Genetic Relationships of Long-nosed Potoroos Potorous tridactylus (Kerr, 1792) from the Bass Strait Islands, with Notes on the Subspecies Potorous tridactylus benormi Courtney, 1963

Figure 1. A map of Bass Strait and the Bass Strait Islands.

Raw data from: Environmental variation structures reproduction and recruitment in long-lived mega-herbivores: Galapagos Giant Tortoises

Understanding drivers of vital rates is important for testing life history theory, predicting population dynamics, and guiding conservation. Migratory, long-lived animals are important to life history theory because they present an extreme among trade-offs in vital rates: delayed maturity, low fecundity, variable recruitment rates, and long generation times. Understanding how vital rates respond to environmental variation has been elusive for such species because of difficulties in studying wide-ranging animals over extended periods. Populations that live on elevation gradients can provide tractable study systems because considerable environmental change occurs over small geographic distances. Galapagos tortoises are an iconic example; they are long-lived, migrate seasonally, face multiple anthropogenic threats, and have cryptic early life history stages for which vital rates are unknown. From 2012–2021, we studied the reproductive ecology of two species of Galapagos tortoises along elevation gradients that coincided with substantial change in climate and vegetation productivity. Specifically, we 1) measured physical and reproductive condition of adult females, 2) tracked the movements of 33 adult females using GPS telemetry, and re-located them seasonally to measure condition, 3) recorded nest temperatures, clutch characteristics, and egg survival from 107 nests, and 4) used radio telemetry to re-locate 104 hatchlings to monitor growth, survival, and movements. We also monitored temperature, rainfall, and primary productivity from field and remotely sensed data along the elevation gradient. Adult females were either elevational migrants or year-round lowland residents. Migrants had higher body condition than residents, and body condition was positively correlated with fecundity. Nests occurred in the hottest, driest part of the tortoise's range, between 6–165m elevation. Clutch size increased with elevation, egg survival declined, and hatchling survival and growth were highest at intermediate elevations. Hatchlings dispersed rapidly between 100–750 m from their nests before becoming sedentary in ranges <0.05 ha. Environmental variability mediated by elevation influenced adult fecundity and juvenile recruitment. Predicted future climates will profoundly impact the relationships between elevation and vital rates of Galapagos tortoises and other species living on elevation gradients. Resilience will be maximized by ensuring connectivity of foraging and reproductive areas within current and possible future elevational ranges of these species.

Data from: Drought-induced relocation of ant colonies and its consequences for the long-term spatial ecology of a population under stress

<ol> <li>Maintaining a central refuge such as a nest or burrow can offer protection against environmental stressors but comes at the expense of the capacity to disperse to new locations. This trade-off with mobility can be detrimental when environmental conditions become adverse for extended periods, necessitating animals to relocate in order to track shifting niche envelopes.</li> <li>Long-lived ant colonies that invest in the construction of large nests are especially susceptible to changing environmental conditions. The Australian meat ant, Iridomyrmex purpureus, build large terrestrial nests at sites that balance shade and solar exposure.</li> <li>Long-term study of a population of meat ants showed low nest turnover and a stable spatial distribution of nests across typical rainfall years. With the onset of drought, a dramatic surge in the production of new nests occurred through a process of budding that far exceeded historic trends. This appears to have allowed colonies to relocate nests into areas with more favourable microclimate conditions in a strategy reminiscent of the production of runners in stressed plants. The consequence has also been the packing of nests into a narrow habitable zone that has resulted in an apparent increase in competition among large rival colonies. Following the break in drought and the thinning of some nests through abandonment, competition has progressively eased in later years.</li> <li>The surge in nest budding triggered by acute environmental stress in this population offers a possible strategy for long-lived colonies to effectively migrate across the landscape. With changes in environmental conditions becoming more frequent and severe with the climate crisis, any strategy available to central place foragers to track windows of preferred conditions are likely to become increasingly important.</li> </ol>

Data on the association between garlic mustard and the plant community from a long-term observational dataset in Illinois, U.S.A.

The impact of a biological invasion on native communities is expected to be uneven across invaded landscapes due to differences in local abiotic conditions, invader abundance, and traits and composition of the native community. One way to improve predictive ability about the impact of an invasive species given variable conditions is to exploit known mechanisms driving invasive species' success. Invasive plants frequently exhibit allelopathic traits, which can be directly toxic to plants or indirectly impact them via disruption of root symbionts, including mycorrhizal fungi. The indirect mechanism – mutualism disruption – is predicted to impact plants that rely on mycorrhizas but not affect non-mycorrhizal plant species. To assess whether invader-driven mutualism disruption explains observed changes in native plant communities, we analyzed long-term (1998–2018) plant cover data from forest plots across the state of Illinois. We evaluated native plant communities experiencing a range of abundance of invasive allelopathic garlic mustard (Alliaria petiolata) and varying environmental conditions. Consistent with the mutualism disruption hypothesis, we showed that as garlic mustard abundance increased over time in 0.25 m2 sampling quadrats, the abundance of mycorrhizal plant species decreased, but non-mycorrhizal plant species did not. Over space and time, garlic mustard abundance predicted plant abundances and diversity at the quadrat level, but this relationship was not present at a larger scale when quadrats were aggregated within sites. Garlic mustard's impact on the plant community was highly localized, yet it was as important as abiotic variables for predicting local plant diversity. We showed that garlic mustard abundance was a key predictor of patterns of plant diversity across invasion intensity and environmental heterogeneity in a way that is consistent with mutualism disruption. Our work indicates that the mutualism disruption hypothesis can provide generalizable predictions of the impacts of allelopathic invasive plants that are evident at a broad spatial scale.

Long read isoforms with A-to-I edits for H1975 cell line

FLAIR2 was used to determine isoform models sequenced from H1975 cells using R2C2 cDNA nanopore sequencing. RNA sequence variants observed in the data were called with longshot and integrated into FLAIR2 isoform models.

Replication data for Temperature variability and long-run economic development

Description This dataset contains the processed data used for the statistical analysis in Linsenmeier, M. (2023): Temperature variability and long-term economic development, published in the Journal of Environmental Economics and Management. The main data on nightlights stem from the satellites of the Visible Infrared Imaging Radiometer Suite (VIIRS). The data are downloaded as annual composites (vcm) of version V1 (Elvidge et al., 2017). For robustness tests, also annual composites of version V2 are used (Elvidge et al., 2021). Additional data on nightlights are taken from the U.S. Air Force Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) of Version 4. Data on the global distribution of crop land and pasture land (Ramankutty et al., 2008) are taken from NASA (Ramankutty et al., 2010). Data on population are from the Gridded Population of the World (GPW) dataset version 4.0 (CIESIN, 2018). Data on elevation are from the Global Land One-kilometer Base Elevation (GLOBE) dataset in version 1 provided by the National Oceanic and Atmospheric Administration (NOAA) (Hastings et al., 1999). Data on terrain ruggedness are from a global dataset with a resolution of 1 km (Shaver et al., 2018). Data on distances from the nearest coast are from NASA. Distance from inland water bodies are from the GloboLakes dataset (Carrea et al., 2015). Finally, data on weather are from ERA5 reanalysis (Hersbach et al. 2018). All datasets are spatially aggregated to the grid cells of the ERA5 reanalysis. Acknowledgements The data contain modified Copernicus Climate Change Service information 2020. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains. Image and data processing by Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines. DMSP data collected by US Air Force Weather Agency. Bibliography <ul> <li>Carrea, L., Embury, O., andMerchant, C.(2015). GloboLakes: High-resolution global limnology data. Center for Environmental Data Analysis. http://catalogue.ceda.ac.uk/uuid/06cef537c5b14a2e871a333b9bc0b482.</li> <li>CIESIN (2018). Gridded Population of the World, Version 4 (GPWv4): Population Count, Revision 11.</li> <li>Elvidge, C. D., Baugh, K., Zhizhin, M., Hsu, F. C., and Ghosh, T. (2017). VIIRS night-time lights. International Journal of Remote Sensing, 38(21):5860–5879.</li> <li>Elvidge, C.D, Zhizhin, M., Ghosh T., Hsu FC, Taneja J. Annual time series of global VIIRS nighttime lights derived from monthly averages:2012 to 2019. Remote Sensing 2021, 13(5), p.922, doi:10.3390/rs13050922.</li> <li>Hastings, D. A., Dunbar, P. K., Elphingstone, G. M., Bootz, M., Murakami, H., Maruyama, H., Masaharu, H., Holland, P., Payne, J., Bryant, N. A., et al. (1999). The global land one-kilometer base elevation (GLOBE) digital elevation model, version 1.0. National Oceanic and Atmospheric Administration, National Geophysical Data Center, 325.</li> <li>Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2018): ERA5 hourly data on single levels from 1959 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). (Accessed in January 2021), 10.24381/cds.adbb2d47</li> <li>Ramankutty, N., Evan, A., Monfreda, C., and Foley, J. (2010). Global Agricultural Lands: Pastures, 2000. Global Agricultural Lands Dataset.</li> <li>Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A. (2008). Farming the Planet: 1. Geographic Distribution of Global Agricultural Lands in the Year 2000: Global Agricultural Lands in 2000. Global Biogeochemical Cycles, 22(1).</li> <li>Shaver, A., Carter, D. B., and Shawa, T. W. (2018). Terrain ruggedness and land cover: Improved data for most research designs. Terrain Ruggedness and Land Cover Dataset.</li> </ul>

opencc-zeroJun 2023View details →

Data from: What makes a good pollinator? Abundant and specialized insects with long flight periods transport the most strawberry pollen

<ol> <li>Despite the importance of insect pollination to produce marketable fruits, insect pollination management is limited by insufficient knowledge about key crop pollinator species. This lack of knowledge is due in part to: 1) the extensive labour involved in collecting direct observations of pollen-transport, 2) the variability of insect assemblages over space and time, and 3) the possibility that pollinators may need access to wild plants as well as crop floral resources.</li> <li>We address these problems using strawberry in the UK as a case study. First, we compare two proxies for estimating pollinator importance: flower visits and pollen transport. Pollen-transport data might provide a closer approximation of pollination service, but visitation data are less time-consuming to collect. Second, we identify insect parameters that are associated with high importance as pollinators, estimated using each of the proxies above. Third, we estimated insects' use of wild plants as well as the strawberry crop.</li> <li>Overall, pollinator importances estimated based on easier-to-collect visitation data were strongly correlated with importances estimated based on pollen loads. Both frameworks suggest that bees Apis and Bombus and hoverflies Eristalis are likely to be key pollinators of strawberries, although visitation data underestimate the importance of bees.</li> <li>Moving beyond species identities, abundant, relatively specialised insects with long active periods are likely to provide more pollination service. </li> <li>Most insects visiting strawberry plants also carried pollen from wild plants, suggesting that pollinators need diverse floral resources.</li> <li>Identifying essential pollinators or pollinator parameters based on visitation data will reach the same general conclusions as those using pollen transport data, at least in monoculture crop systems. Managers may be able to enhance pollination service by preserving habitats surrounding crop fields to complement pollinators' diets and provide habitats for diverse life stages of wild pollinators.</li> </ol>

Data and code for "Competitive hierarchies in bryozoan assemblages mitigate network instability by keeping short and long feedback loops weak"

This repository contains all scripts and data files to reproduce the analysis of the manuscript "Competitive hierarchies in bryozoan assemblages mitigate network instability by keeping short and long feedback loops weak" Abstract Competitive hierarchies in diverse ecological communities have long been thought to lead to instability and prevent coexistence. However, system stability has never been tested and the relation between hierarchy and instability has never been explained in complex competition networks parameterised with data from direct observation. Here we test model stability of 30 multispecies bryozoan assemblages, using estimates of energy loss from observed interference competition to parameterise both the inter- and intraspecific interactions in the competition networks. We find that all competition networks are unstable. However, instability is mitigated considerably by asymmetries in the energy loss rates brought about by hierarchies of strong and weak competitors. This asymmetric organisation results in asymmetries in the interaction strengths, which reduces instability by keeping the weight of short (positive) and longer (positive and negative) feedback loops low. Our results support the idea that interference competition leads to instability and exclusion but demonstrate that this is not because of, but despite, competitive hierarchy. Data Our data set contains records of overgrowth competition in 30 high-latitude bryozoan assemblages. Rocks were collected by hand from shallow subtidal coastal locations at Rothera Island, West Antarctic Peninsula, Signy Island in the maritime Antarctic and Spitsbergen in the Arctic. For each assemblage, the data set contains one .csv file with abundance per species and one .csv file containing the species-contact-matrix. All bryozoans were identified to species and counted, giving abundance data in colonies per species. Then, all pairwise contests between colonies were classified as win, draw or loss and the results were compiled in the species-contact-matrices. For details, see the methods section of the paper. Analysis The analysis is subdivided into the following sections: <ul> <li>0 Random matrices: Stability of random matrices with symmetric and asymmetric interactions.</li> <li>1 Preparation: Define functions to calculate asymmetry measures and set plotting parameters</li> <li>2 Read and process raw data: Converts raw data to Jacobian matrices</li> <li>3 Analysis of empirical matrices: Calculates stability, asymmetry measures, loop weights of empirical matrices.</li> <li>4 Analysis of randomised matrices: Randomises empirical matrices and analyses the effect on stability, asymmetry measures and loop weights.</li> <li>5 Sensitivity: Effect of model assumptions (cost-values / replacement of missing values) on the results.</li> </ul> Details on how to reproduce the full analysis, including all figures and tables in the manuscript can be found in the ReadMe file.

opencc-zeroJun 2023View details →

Cold acclimation threshold induction temperatures of switchgrass ecotypes grown under a long and short photoperiod

Plants can cold-acclimate to enhance their freezing tolerance by sensing declining temperature and photoperiod cues. However, the factors influencing genotypic variation in the induction of cold acclimation are poorly understood among perennial grasses. We hypothesized that the more northern upland switchgrass (Panicum virgatum L.) ecotype develops a higher degree of freezing tolerance by initiating cold acclimation at higher temperatures as compared with the coastal and southern lowland ecotypes. First, we determined the optimal method for assessing freezing tolerance and the length of exposure to 8/4°C required to induce the maximum level of freezing tolerance in the most northern upland and most southern lowland genotypes. We characterized the maximum freezing tolerance of eight upland, three coastal and five lowland genotypes grown for 21 d at 8/4°C and a 10 or 16 h photoperiod. Next, we identified the temperature required to induce cold acclimation by exposing the 16 genotypes for 7 d at 20 to 6°C constant temperatures under a 10 or 16 h photoperiod. Cold acclimation initiated at temperatures 5 and 7°C higher in upland than coastal and lowland genotypes. Among upland genotypes the shorter photoperiod induced cold acclimation at a 1°C higher temperature. Genotypes originating from a more northern latitude initiate cold acclimation at higher temperatures and develop higher maximum freezing tolerances. An earlier response to declining temperatures may provide the upland ecotype with additional time to prepare for winter and provide an advantage when plants are subjected to the rapid changes in fall temperature associated with injurious frosts.

Reproducibility Report for the paper "Vibration signal-assisted endpoint detection for long-stretch, ultraprecision polishing processes"

This reproducibility report includes the datasets and computer code used for reproducing the results in the paper, Jin, Bukkapatnam, Hayes, and Ding, 2023, “Vibration signal-assisted endpoint detection for long-stretch, ultraprecision polishing processes,” ASME Transactions, Journal of Manufacturing Science and Engineering, Vol.145, pp. 061007.