Find research datasets worth reusing

opencc-zeroApr 2022View details →

The role of aerosol-radiation interaction in the meteorology prediction at the weather scale

<a name="OLE_LINK53"></a>The current capabilities of the numerical weather prediction (NWP) model to simulate aerosol-radiation interaction (ARI) impacts on weather prediction are still rarely considered compared with climate models. Here, the NWP model GRAPES_CUACE is used to evaluate the role of the ARI in meteorology prediction at the weather scale in China. The results show that the online calculation of ARI in the model can <a name="OLE_LINK99"></a>extensively improve the meteorology prediction accuracy involving temperature, wind, and pressure at most vertical <a name="OLE_LINK12"></a>levels in relatively clean, light, and heavy pollution stages. This improvement significantly occurs in the meteorology factors below 950 hPa prediction such as temperature at 2 m, 1000, and 950 hPa, and mean sea level pressure, particularly in heavy pollution areas and stages. <a name="OLE_LINK13"></a>Unlike temperature, the improvement of ARI in the predicted wind <a name="OLE_LINK52"></a>at the height of the boundary layer is more significant than near-surface. However, this improvement declines when the low-cloud exists.

opencc-by-4.0Apr 2022View details →

Coarse-scale soil moisture products over Qinghai-Tibet Plateau

This dataset provides three coarse-scale satellite soil moisture products including SMOS-IC, SMAP L3, and AMSR2 LPRM, covering the period from July to August between 2016 and 2018. All these files have been processed through the following steps, including quality control, file format conversion,  ascending and descending averaging, projection, resampling, and clipping based on the boundary of the Qinghai Tibet Plateau.

opencc-zeroDec 2021View details →

Genome-scale phylogeography resolves the native population structure of the Asian longhorned beetle, Anoplophora glabripennis (Motschulsky)

Human assisted movement has allowed the Asian longhorned beetle (ALB, Anoplophora glabripennis (Motschulsky)) to spread beyond its native range and become a globally regulated invasive pest. Within its native range of China and the Korean peninsula, human-mediated dispersal has also caused cryptic translocation of insects, resulting in population structure complexity. Previous studies used genetic methods to detangle this complexity but were unable to clearly delimit native populations which is needed to develop downstream biosurveillance tools. We used genome-wide markers to define historical population structure in native ALB populations and contemporary movement between regions. We used genotyping-by-sequencing to generate 6,102 single nucleotide polymorphisms (SNPs) and amplicon sequencing to genotype 53 microsatellites. In total, we genotyped 712 individuals from ALB's native distribution. We observed six distinct population clusters among native ALB populations, with a clear delineation between northern and southern groups. Most of the individuals from South Korea were distinct from populations in China. Our results also indicate historical divergence among populations and suggest limited large-scale admixture, but we did identify a restricted number of cases of contemporary movement between regions. We identified SNPs under selection and describe a clinal allele frequency pattern in a missense variant associated with glycerol kinase, an important enzyme in the utilization of an insect cryoprotectant. We further demonstrate that small numbers of SNPs can assign individuals to geographic regions with high probability, paving the way for novel ALB biosurveillance tools.

opencc-by-4.0Feb 2022View details →

Data for Embryo-scale epithelial buckling forms a propagating furrow that initiates gastrulation

This is the data and code corresponding to <a href="https://doi.org/10.1038/s41467-022-30493-3">Embryo-scale epithelial buckling forms a propagating furrow that initiates gastrulation</a>, Nature Comms. 13:3348. Code The file Surface_Evolver_script.txt is ... the Surface Evolver script, use with <a href="http://facstaff.susqu.edu/brakke/evolver/evolver.html">Ken Brakke's Surface Evolver</a> Data sources The figure panels are based on the datafiles listed below, visualised either with <a href="http://facstaff.susqu.edu/brakke/evolver/evolver.html">Ken Brakke's Surface Evolver </a>or with <a href="http://www.gnuplot.info/">gnuplot 5</a>. When the datafiles listed do not contain the primary data, they contain a commented last line which is the command line for the software <a href="https://doi.org/10.5281/zenodo.5911337">datamerge</a> to generate it from other datafiles found in the Data_sources subdirectory. Figure 1 Fig. 1c : data provided in <code>data_for_Fig_1g.tsv</code> Fig. 1f : visualisation from Surface Evolver file <code>Young100dixPoisson000Step013.dmp</code> Fig. 1g : <code>myosin_profile_us_only.pdf</code> generated with gnuplot script <code>myosin_profile.plot</code> Figure 2 Fig. 2a : <code>strain_profile_100_0_time_013.pdf</code> generated with gnuplot script <code>strain_profile.plot</code> Fig. 2b : visualisation from Surface Evolver file <code>Young100dixPoisson000Step013.dmp</code> Fig. 2c : <code>stress_profile_100_0_time_013.pdf</code> gnuplot script <code>stress_profile.plot</code> Fig. 2d : visualisation from Surface Evolver file <code>Young100dixPoisson000Step063.dmp</code> Figure 3 Fig. 3a : <code>myosin_area.pdf</code> generated with gnuplot script <code>area_AP_DV_paper.plot</code> Fig. 3b : <code>area_stripes_t=-1.pdf</code> generated with gnuplot script <code>area_AP_DV_paper.plot</code> Fig. 3c : <code>only_AP_stripes_t=-1.pdf</code> generated with gnuplot script <code>area_AP_DV_paper.plot</code> Fig. 3d : <code>only_DV_stripes_t=-1.pdf</code> generated with gnuplot script <code>area_AP_DV_paper.plot</code> Fig. 3e : visualisation from Surface Evolver file <code>Young100dixPoisson000Step013.dmp Young100dixPoisson000Step063.dmp Young100dixPoisson000Step163.dmp Young100dixPoisson000Step213.dmp</code> Figure 4 Fig. 4a : visualisation from Surface Evolver file <code>Young100dixPoisson000Step213.dmp</code> Fig. 4b : <code>furrow_propagation.pdf</code> generated with gnuplot script <code>furrow_propagation.plot</code> Fig. 4c : <code>rate_of_furrowing_t=3.pdf</code> generated with gnuplot script <code>furrow_propagation.plot</code> Fig. 4f : <code>curvature.pdf</code> generated with gnuplot script <code>curvature.plot</code> Figure 5 Fig. 5a : visualisation from Surface Evolver file <code>Young100dixPoisson000Step013.dmp Young100dixPoisson000Step063.dmp Young100dixPoisson000Step113.dmp Young100dixPoisson000Step163.dmp Young100dixPoisson000Step213.dmp</code> Fig. 5b : visualisation from Surface Evolver file <code>Young100dixPoisson000Step013.dmp Young100dixPoisson000Step140.dmp</code> Fig. 5d : <code>stress_laserablations_profile_100_0_time_063.pdf</code> generated with gnuplot script <code>stress_profile_for_laser_ablations.plot</code> Fig. 5e : <code>laser_ablation_recoil.pdf</code> generated with gnuplot script <code>laser_ablation_recoil.plot</code> Supp Figure 1 Fig. S1a : <code>time_profile_FINI_100_0.pdf</code> generated with gnuplot script <code>time_profile_stress.plot</code> Fig. S1b : visualisation from Surface Evolver file <code>Young100dixPoisson000Step013.dmp</code> Fig. S1d : visualisation from Surface Evolver file <code>Young100dixPoisson000Step063.dmp</code> Fig. S1e : <code>strain_profile_100_0_time_063.pdf</code> gnuplot script <code>strain_profile.plot</code> Fig. S1f : <code>stress_profile_100_0_time_063.pdf</code> gnuplot script <code>stress_profile.plot</code> Supp Figure 1 Fig. S2a : <code>area_stripes_time_evolution.pdf</code> generated with gnuplot script <code>area_AP_DV_paper.plot</code> Fig. S2b : <code>area_stripes_time_evolution_SPIM.pdf</code> generated with gnuplot script <code>area_AP_DV_paper.plot</code> Supp Figure 3 Fig. S3a : visualisation from Surface Evolver file <code>Young100dixPoisson000Step213.dmp</code> Fig. S3c : <code>AP_binned_strain.pdf</code> generated with gnuplot script <code>AP_binned_strain.plot</code> Fig. S3d : <code>furrow_propagation_experimental.pdf</code> generated with gnuplot script <code>plot_furrow.plot</code> Fig. S3e : <code>curvature_DV_indiv.pdf</code> generated with gnuplot script <code>curvature.plot</code> Fig. S3f : <code>depth_Gastrulation_ordi_Wild_Type_STITCHED_100_0.pdf</code> generated with gnuplot script <code>depth.plot</code>

opencc-by-4.0Apr 2022View details →

PS+ VIP_up-scaling manufacturing technology flowchart

PS+ VIP_up-scaling manufacturing technology flowchart

opencc-by-4.0Apr 2022View details →

PS+ STM_up-scaling manufacturing technology flowchart

PS+ STM_up-scaling manufacturing technology flowchart

Icequake-magnitude scaling relationship along a rift within the Ross Ice Shelf, Antarctica

This data set contains the icequake catalog used for Huang et al. (2022).

Scale-dependent species-area relationship: niche-based versus stochastic processes in a typical subtropical forest

Determining the patterns and drivers of the small-scale species-area relationship (SAR) is crucial for improving our understanding of community assembly and biodiversity patterns. Niche-based and stochastic processes are two principal categories of mechanisms potentially driving SARs. However, their relative importance has rarely been quantified rigorously owing to scale-dependence and the simplified niche volumes often used. In a fully mapped, 24-ha plot of a typical subtropical forest, we built the SARs and well-defined niche-hyper-volumes of a broad range of environmental variables at scales of 10 - 70 m (cell sizes). We then simulated passive sampling and partitioned the variances of the SAR slopes to disentangle the two contrasting mechanisms. We found that the small-scale SAR best followed a power-law relationship, consistent with large-scale SARs. The SAR slope declined with increasing scale; it was lower than expected under passive sampling at scales below 30 m and higher at larger scales. Environmental niches explained more (39%-64%) of the slope at larger scales, exceeding 50% at scales > 30 m, and these niches always captured the majority of the structured slopes. Environmental position (environmental mean values) effects were steady in absolute strength across scales and explained most (98%-68%) of the niche effect, but this proportion decreased with increasing scale. The effect of environmental heterogeneity increased with spatial scales, starting to rise at the 30 m scale after controlling for environmental position. Excluding soil properties from analyses strongly reduced these niche effects, highlighting the importance of soils for structuring the small-scale SAR. There was also substantial stochasticity in the SAR slopes, which was only partially explained by passive sampling. Synthesis: Our results show that the small-scale SAR in the studied subtropical forest follows a power-law, exhibits a scale shift in slope at 30 m, and is strongly shaped by niche effects that are dominated by environmental position relative to heterogeneity. However, soil heterogeneity controls the increase of niche effect and shift in the SAR slope with increasing spatial scales. Hence, edaphic factors can be responsible for scale-dependence in small-scale SARs, thereby linking small-scale and large-scale SARs.

Diet analysis of bats killed at wind turbines suggest large-scale losses of trophic interactions

Agricultural practice has led to landscape simplification and biodiversity decline, yet recently, energy producing infrastructures, such as wind turbines, have been added to these simplified agroecosystems, turning them into multi-functional energy-agroecosystems. Here, we studied the trophic interactions of bats killed at wind turbines using a DNA metabarcoding approach to shed light on how turbine-related bat fatalities may possibly feedback on local habitats. Specifically, we identified insect DNA in the stomachs of common noctule bats (Nyctalus noctula) killed by wind turbines in Germany to infer in which habitats these bats hunted. Common noctule bats consumed a wide variety of insects from different habitats, ranging from aquatic to terrestrial ecosystems (e.g. wetlands, farmland, forests, and grasslands). Agricultural and silvicultural pest insects made up about 20% of insect species consumed by the studied bats. Our study suggests that the potential damage of wind energy production goes beyond the loss of bats and the decline of bat populations. Bat fatalities at wind turbines may lead to the loss of trophic interactions and ecosystem services provided by bats, which may add to the functional simplification and impaired crop production, respectively, in multi-functional ecosystems.

Spatial variability and driving factors of ecosystem services balance at watershed scale in the Lancang River Valley, Southwest China

Revealing the spatio-temporal change of the supply, demand and balance of ecosystem services (ES) associated with human activities and land use changes is of great significance for watershed ecosystem management. Taking the Lancang River Valley as a case, we explicitly studied the ES spatial characteristics using the land use/land cover (LULC) matrix model, Optimized Hot Spot Analysis and landscape pattern analysis. Further, we screened out the dominant explanatory variables which had significant influence on ES supply, demand and balance by means of Geographical Weighted Regression (GWR) method at pixel scale. The results showed that the ES demand intensity varied little throughout the watershed while the downstream ES supply capacity and balance value were greater than upstream. Meanwhile, the hotspots of ES supply and demand were mainly distributed in the south part but coldspots in the north part. Human activity factors integrating landscape pattern variables were verified to have negative impact on ES balance in general. Among them, the Largest Patch Index (LPI) had a negative influence of majority pixels while GDP, cultivated land ratio and Area Weighted Average Patch Fractal Dimension (AWAPFD) had positive effects on a few pixels. This study will provide scientific support for regional ecosystem service trade-off and regulation at multiple scales.

Precessional dynamics of geometrically scaled magnetostatic spin waves in two-dimensional magnonic fractals

Open data for "Precessional dynamics of geometrically scaled magnetostatic spin waves in two-dimensional magnonic fractals" published in PRB 105, 174415 (2022)

A benchmark dataset of diurnal- and seasonal-scale radiation, heat and CO2 fluxes in a typical East Asian monsoon region

A benchmark dataset include 30-min meteorology and eddy flux variables at four sites with two typical surface types (i.e., SX-cropland, DT-cropland, XZ-suburb, and DS-suburb) in the Yangtze River Delta of China. SX-cropland: 15 Jul 2015–24 Apr 2019 DT-cropland: 1 Dec 2014–30 Nov 2017 XZ-suburb: 27 Mar 2014–22 Jan 2017 DS-suburb: 16 Apr 2011–1 Jan 2019

Development and validation of a Community Resilience Scale for Youth (CRS-Y) Community Resilience Scale for Regional Youth

The purpose of this article is to present the development and validation of a Community Resilience Scale for Youth (CRS-Y) among a Portuguese sample of nearly 4000 young people growing up in regions on the border with Spain. The scale was developed for young people to assess their perception of the resilience of regional communities in terms of positive development and purposeful experiences for young people. Resilient communities, under a social ecological approach, are those able to move forward on social change and transformation. This concept is especially remarkable in more challenging contexts such as border regions of mainland Portugal which are characterised by economic, social, educational, and cultural disadvantages while discovering possibilities of resilience through promising local dynamics. A multi-step approach was used to develop this scale of 12-item scale. Items were generated based on an in-depth literature review and research previously conducted with young people in these contexts. The overall sample was randomly divided into two subsamples of 1828 and 1735 young people each. Principal component analysis was performed with one of the subsamples and yielded a three-factor structure, explaining 61.5% of the total variance. Confirmatory factor analysis performed on the second showed good fit indexes. Furthermore, internal consistency of the three proposed components, gauged either by Cronbach’s alpha or McDonald’s omega, indicated good reliability. Given the results, the CRS-Y is a valid and reliable tool showing adequate psychometric properties. This scale will be useful for schools and policy makers at the local level. Indicators such as the promotion of opportunities to participate and be recognised, collective trust and the promotion of shared values and protection are relevant in assessing regional communities’ resilience and informing youth policies.   The scoring and interpretation guidelines for this scale should be as follows: The Community Resilience Scale for Youth (CRS-Y) was developed for young people to assess their perception of the resilience of regional communities in terms of positive development and purposeful experiences for young people. The scale consists of 12 items rated on a 5-point Likert scale (1=low agreement to 5=high agreement), where participants indicate their level of agreement with each statement about their community.  Items are grouped into a total score [MEAN(Factor1,Factor2,Factor3)] and three factors/dimensions:  Factor 1-Promotion of opportunities and collective trust [5 items; MEAN(Item1,Item2,Item3,Item4,Item5)]; Factor 2-Promotion of shared values and protection [4 items; MEAN(Item6,Item7,Item8,Item9)]; Factor 3-Promotion of intercommunity trust and ties [3 items; MEAN(Item10,Item11,Item12)].  Higher scores indicate a greater perception of the resilience of regional communities in terms of positive development and purposeful experiences for young people.

Island biogeography at the meso-scale: distance from forest edge affects choice of patch size by ovipositing treefrogs

Diversity in habitat patches is partly driven by variation in patch size, which affects extinction, and isolation, which affects immigration. Patch size also affects immigration as a component of patch quality. In wetland ecosystems, where variation in patch size and inter-patch distance is ubiquitous, relationships between size and isolation may involve trade-offs. We assayed treefrog oviposition at three patch sizes in arrays of two types, one where size increased with distance from forest (dispersed), and one with all patches equidistant from forest (equidistant), testing directly for an interaction between patch size and distance, which was highly significant. Medium patches in dispersed arrays received more eggs than those in equidistant arrays as use of typically preferred larger patches was reduced in dispersed arrays. Our results demonstrate a habitat selection trade-off between preferred large and less-preferred medium patches across small-scale variation in isolation. Such patch size/isolation relationships are critical to community assembly and to understanding how diversity is maintained within a metapopulation and metacommunity framework, especially as wetland habitat becomes increasingly rare and fragmented. These results bring lessons of Island Biogeography, writ large, to bear on questions at small scales where ecologists often work, and where habitat restoration is most often focused.

Long distance migration is a major factor driving local adaptation at continental scale in a Pacific Salmon

Inferring the genomic basis of local adaptation is a long-standing goal of evolutionary biology. Beyond its fundamental evolutionary implications, such knowledge can guide conservation decisions for populations of conservation and management concern. Here, we investigated the genomic basis of local adaptation in the Coho salmon (Oncorhynchus kisutch) across its entirety North American range. We hypothesized that extensive spatial variation in environmental conditions and the species' homing behavior may promote the establishment of local adaptation. We genotyped 7,829 individuals representing 217 sampling locations at more than 100,000 high-quality RADseq loci to investigate how recombination might affect the detection of loci putatively under selection and took advantage of the precise description of the demographic history of the species from our previous work to draw accurate population genomic inferences about local adaptation. Results indicated that genetic differentiation scans and genetic-environment association analyses were both significantly affected by variation in recombination rate as low recombination regions displayed increased rate of outliers. By taking these confounding factors into consideration, we revealed that migration distance was the primary selective factor driving local adaptation and partial parallel divergence among distant populations. Moreover, we identified several candidates SNP associated with long distance migration and altitude including gene known to be involved in adaptation to altitude in other species. The evolutionary implications of our findings are discussed along with conservation applications.

Mechanism underlying the millennial scale variation of offshore sediment transport in the North Yellow Sea

Sediment cores YC10 (length: 548 cm, water depth: 54 m) and YC26 (length: 435 cm, water depth: 15 m) were collected by hammer drilling on a fishing vessel from the NYS in July 2016. The sediment cores were split lengthwise, described, photographed, and subsampled in the lab. They were sliced into thin sections for trace element analyses at intervals of 4–10 cm according to the age model. The samples were freeze-dried under vacuum, and the fine fraction (< 63 μm) was sieved from the bulk samples for further geochemical analysis. The number of samples for REEs in cores YC10 and YC26 was 71 and 80, respectively, while those for Sr-Nd isotopes were 12 and 14, respectively.

opennotspecifiedMay 2022View details →

FIG. 2 in Analysis of the diversity and distributional patterns of coleopteran families on a global scale

FIG. 2. Cluster analyses and corresponding regionalisation schemata based on (a) a streamlined but nevertheless fairly comprehensive dataset excluding very widespread families and family-poor ecoregions; (b) endemic-rich ecoregions only.

opennotspecifiedMay 2022View details →

FIG. 1 in Analysis of the diversity and distributional patterns of coleopteran families on a global scale

FIG. 1. Global patterns of coleopteran family diversity and endemism. (a) family richness; (b) weighted endemism.

Life-history stage and the population genetics of the tiger mosquito Aedes albopictus at a fine spatial scale

As a widespread vector of disease, the mosquito species Aedes albopictus Skuse (Diptera: Culicidae) is a high priority for both public health and invasive species research and management. Like all mosquitoes, A. albopictus has a complex life history with aquatic egg, larval, and pupal stages and a terrestrial adult stage. This requires targeted management strategies for each life stage, coordinated across time and space. Researchers use population genetics to inform control of A. albopictus. However, these studies do not consider the impact on life stage on population genetic characteristics and subsequent conclusions. Our objective was to examine whether the life stage impacted patterns of A. albopictus genetic diversity and differentiation at a spatial scale relevant to management efforts. We first conducted a literature review of field-caught A. albopictus population genetic papers and identified 74 peer-reviewed publications, none of which compared results between life stages. We them examined population genetic patterns of egg and adult A. albopictus at five sites in Wake County, North Carolina USA using 8,425 single nucleotide polymorphisms. We found that level of genetic diversity and connectivity between sites varied between adults and eggs. This warrants further study and is critical for research aimed at informing local management.