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opencc-zeroSep 2021View details →

Size, connectivity and edge effects of stream habitats explain spatiotemporal variation in brown trout (Salmo trutta) density

Ecological theory postulates that size and isolation of habitat patches impact the colonization/extinction dynamics that determine community species richness and population persistence. Given the key role of lotic habitats for life history completion in rheophilic fish, evaluating how the distribution of swift-flowing habitats affects the abundance and dynamics of subpopulations is essential. Using extensive electrofishing data, we show that merging island biogeography with meta-population theory, where lotic habitats are considered as islands in a lentic matrix, can explain spatiotemporal variation in occurrence and density of brown trout (Salmo trutta). Subpopulations in larger and less isolated habitat patches had higher average densities and smaller between-year density fluctuations. Larger habitat patches also had lower predicted risk of excessive zero catches, indicative of lower extinction risk. Trout density further increased with distance from the edge of adjacent lentic habitats with predator (Esox lucius) presence, suggesting that edge- and matrix-related mortality contributes to the observed patterns. These results can help reduce the negative impacts that habitat loss and fragmentation have on biodiversity, by stressing the importance of suitable habitat size and connectivity, and aid in prioritization of habitat restoration, dam removal and reintroduction programs aimed at vitalizing declining and locally extinct riverine fish populations.

opencc-by-4.0Sep 2021View details →

Supplementary Data for Paper "The Effect of Display Pixel Density on Minimum Legible Size of Fundamental Cartographic Symbols"

This is the result data of the user study described in the paper "The Effect of Display Pixel Density on Minimum Legible Size of Fundamental Cartographic Symbols". Author information and further metadata will be added after anonymous peer review. 27 participants, 4 displays, 6 tasks. Note that the data contains the station ID (A-D), which maps to Displays 1-4 as described in the paper: A - D2; B - D4; C - D1; D - D3; File description: <ul> <li>all_aggregated_users.csv: Thresholds for each task and station, for each participant. One row per participant, with fields for each station/task combination (27 rows).</li> <li>all_aggregated_thresholds.csv: Thresholds for each participant, task and station. One row per threshold value, thresholds for task #2 for participants #1-3 have been discarded, due to an error in the experiment configuration (see paper). (27 x 4 x 6 - 3 x 4 = 636 rows)</li> </ul>

opencc-by-4.0Oct 2022View details →

The Smart City as a Field of Innovation: Effects of Public-Private Data Collaboration on the Innovative Performance of Small and Medium-Sized Enterprises in China

Data is increasingly considered to be a key component in stimulating innovation (Cockburn, Henderson, and Stern, 2019). Numerous promising possibilities have been opened up by rapidly emerging, data-intensive technologies, including the Internet of Things (IoT) and artificial intelligence. The analysis and interpretation of big data are critical in the growth of technology firms in terms of AI training and computing capabilities (Allam and Dhunny, 2019). Small and medium-sized enterprises (SMEs), with their limited resources internally, particularly face a serious challenge of implementing innovation that depends upon data. The smart city provides an important opportunity for creating data-driven innovation. Significant amounts of data are increasingly available from various sources through sophisticated devices and equipment scattered in smart cities. Many smart city projects across the globe provide rich opportunities for SMEs to explore data-driven innovation (Bresciani, Ferraris, and Del Giudice, 2018). China, in particular, has recently been active in collecting and utilizing various kinds of data in smart cities. The availability of and access to data help to improve the software development of firms in China, where massive amounts of data resources are held by the government (Beraja, Yang, and Yuchtman, 2022). In the process of smart city development, there are also many tasks that are complementary to each other, including connecting databases, building online platforms that connect different data coming from different data sources, operating online platforms, and providing products and services to citizens. These diverse kinds of tasks involved in smart city projects initiated by local governments have brought about new business opportunities for innovative SMEs in China. To implement the policies of encouraging the development of SMEs by the central government, municipal governments have introduced policies that give priority to SMEs in participating in smart city projects (Ministry of Industry and Information Technology, 2016). Those companies that have access to the data held by government agencies are expected to benefit from utilizing the rich data for creating innovative products and services. There were few empirical studies conducted, however, to examine how data are actually managed and provided in smart cities and how they affect companies’ innovative activities. It remains unclear how public agencies and private enterprises collaborate on data and how that influences the innovation performance of SMEs in China. In smart cities, different types of public-private collaboration are involved, including hardware purchase, platform building, platform operation, and data analysis. It is not yet well-understood how these different types of collaboration influence the innovative performance of SMEs. In this study, we intend to address how data are managed through collaboration between the government and companies in smart cities and how the mode of collaboration influences firms’ performance on innovation. By focusing on the case of SMEs in China, this research aims to shed light on what kinds of data are available and used in smart cities and how the government and enterprises collaborate on data to facilitate innovation. The analysis of this study utilizes data on more than eight million contracts extracted from the official procurement database of the government. Data on companies are assembled with regard to the registered capital, industry, software products, and patents in 1990-2021 from the Tianyancha website. A panel data is established with key characteristics of SMEs, software and patents outputs, and their record on obtaining different government contracts annually. The government contracts are divided into three categories, namely, data analysis, platform building, and equipment supply, based on keyword identifications. To deal with the unbalance between the treatment group (the companies that obtained government contracts) and the control group, we use propensity score matching (one-to-one nearest neighbor matching) to narrow down the sample size of the control group to that of the treatment group. Then we apply the traditional difference-in-difference (DID) and  DID with multiple time periods (Callaway & Sant’Anna, 2021) methods to examine whether there are significant differences in innovative outputs of software products and patents before and after the companies receive government contracts. We also compare how the innovation performance of companies differs based on the types of contracts these companies obtain. That makes it possible to identify what kinds of data collaboration would be effective in improving the innovative performance of SMEs. Our preliminary analysis of average treatment effect suggests that obtaining the government contracts, especially research contracts and platform building type of contracts, can effectively help improve the innovation performance when comparing between the control and treatment group. After checking the common support graph and doing a balance test, the outcome is solid. In general, based on the average treatment effect on the treated group, innovation performance, as measured by the number of patents and software productions, has shown a significant increase for those companies that obtain a research type of contract, whereas the increase is smaller for the platform building contractor and slight for the equipment purchase contractor. Government purchase of equipment that contains data-intensive technologies promotes the use of these products in smart cities. That, however, does not involve any substantive exchange or transfer of data possessed by the government and would not significantly contribute to stimulating innovation at firms. This study will have useful implications for establishing public-private collaboration on data for facilitating innovation in smart cities. Specifically, government procurement should also be viewed as a policy tool for improving China's technological innovation. According to our findings, research and platform development can successfully assist firms in improving their innovation performance. As a result, the government should grant enterprises access to additional data resources and data management related tasks if they want to see more industry structural transformation, as stated in the government documents.

opencc-zeroDec 2022View details →

Published correlational effect sizes in social and developmental psychology

The distribution of effect sizes may offer insights about the research done and reported in a scientific field. We have evaluated 12,412 manually collected correlation effect sizes (Sample 1) and 31,157 computer-extracted correlation effect sizes (Sample 2) published in journals focused on social or developmental psychology. Sample 1 consisted of 243 studies from 6 journals published in 2010 and 2019. Sample 2 consisted of 5,012 papers published in 10 journals between 2010–2019. The 25th, 50th and 75th effect size percentiles were 0.08, 0.17 and 0.33, and 0.17, 0.31, and 0.52 in Samples 1 and 2, respectively. Sample 2 percentiles were probably larger because Sample 2 only included effect sizes from the text but not from tables. In text, authors may have emphasized larger correlations. Large sample sizes were associated with smaller reported correlations. In Sample 1 about 70% of studies specified a directional hypothesis. In 2010, no papers had power calculations while in 2019, 14% of papers had power calculations. These data offer empirical insights into the distribution of reported correlations and may inform the interpretation of effect sizes. They also demonstrate the importance of computation of statistical power and highlight potential reporting bias.

opencc-zeroFeb 2023View details →

Data from: Contrasting long-term trends in juvenile abundance of a widespread cold-water salmonid along a latitudinal gradient: Effects of climate, stream size and migration strategy

A changing climate reshapes the range distribution of many organisms, and species with relatively low thermal optima, like many salmonids, are increasingly expected to face local population extinctions at lower latitudes. Understanding where and how fast these changes are happening is of pivotal importance for successful mitigation and conservation efforts. We used an extensive electrofishing database to explore temporal trends of brown trout juveniles (Salmo trutta L.) in 218 locations from 174 Swedish streams, over the last 30 years (1991–2020). We hypothesized that 1) declines in abundance have occurred predominately in the warmer, southern regions, while increases have occurred in the colder, northern regions, 2) larger stream sizes may partly offset negative effects of climate, and 3) migrating and resident populations are affected differently by a warming climate. We found that abundance of brown trout juveniles generally declined in warmer regions, especially in smaller streams (≤ 6 m wide), while the abundance increased in colder regions. In larger streams, negative effects of higher temperatures were seemingly buffered, as we found lower rates of decline or even positive trends. The rate of change (i.e. the slopes of the trends in abundance) was more pronounced towards the climate extremes and was on average zero in regions with a normal annual air temperature (average temperature over 30-year period) around 5–6 ºC. Warmer climate had stronger effects on migrating compared to resident populations, suggesting that climate-induced loss of stream connectivity could be an additional factor that hinders recruitment in anadromous populations in a changing climate. Considering predictions of increasing temperatures and frequency of summer droughts, management of cold-water salmonid populations should focus on conserving and restoring riparian vegetation, wetlands, climate and thermal refugia, and habitat integrity overall. Such measures may, however, not suffice for small streams at lower latitudes, unless hydrological connectivity is maintained.

opencc-zeroFeb 2023View details →

Data from: Effective population size in a partially clonal plant is not predicted by the number of genetic individuals

Estimating effective population size (Ne) is important for theoretical and practical applications in evolutionary biology and conservation. Nevertheless, estimates of Ne in organisms with complex life-history traits remain scarce because of the challenges associated with estimation methods. Partially clonal plants capable of both vegetative (clonal) growth and sexual reproduction are a common group of organisms for which the discrepancy between the apparent number of individuals (ramets) and the number of genetic individuals (genets) can be striking, and it is unclear how this discrepancy relates to Ne. In this study, we analysed two populations of the orchid Cypripedium calceolus to understand how the rate of clonal vs. sexual reproduction affected Ne. We genotyped >1,000 ramets at microsatellite and SNP loci, and estimated contemporary Ne with the linkage disequilibrium method, starting from the theoretical expectation that variance in reproductive success among individuals caused by clonal reproduction and by constraints on sexual reproduction would lower Ne. We considered factors potentially affecting our estimates, including different marker types and sampling strategies, and the influence of pseudoreplication in genomic datasets on Ne confidence intervals. The magnitude of Ne/Nramets and Ne/Ngenets ratios we provide may be used as reference points for other species with similar life-history traits. Our findings demonstrate that Ne in partially clonal plants cannot be predicted based on the number of genets generated by sexual reproduction, because demographic changes over time can strongly influence Ne. This is especially relevant in species of conservation concern, in which population declines may not be detected by only ascertaining the number of genets.

opencc-by-4.0Nov 2022View details →

The Effect of Size, Orientation and Temperature on the Deformation of Microcast Silver Crystals (Dataset)

Dataset corresponding to article "The Effect of Size, Orientation and Temperature on the Deformation of Microcast Silver Crystals" (DOI:<a href="https://doi.org/10.1016/j.actamat.2023.118817">https://doi.org/10.1016/j.actamat.2023.118817</a>) Borasi, L., Frasca, S., Charbon, E., & Mortensen, A. (2023). The Effect of Size, Orientation and Temperature on the Deformation of Microcast Silver Crystals. Acta Materialia, 118817.

opencc-zeroMar 2023View details →

Drivers of strong isolation and small effective population size at a leading range edge of a widespread plant

Climate change has influenced species distributions worldwide with upward elevational shifts observed in many systems. Leading range edge populations, like those at upper elevation limits, are crucial for climate change responses but can exhibit low genetic diversity due to founder effects, isolation, or limited outbreeding. These factors can hamper local adaptation at range limits. Using the widespread herb, Argentina anserina, we measured ecological attributes (population density on the landscape, area of population occupancy, and plant and flower density) spanning a 1000m elevation gradient, with high elevation populations at the range limit. We measured vegetative clonal potential in the greenhouse for populations spanning the gradient. We combined these data with a ddRAD-seq dataset to test the hypotheses that high-elevation populations would exhibit ecological and genomic signatures of leading range edge populations. We found that population density on the landscape declined towards the high elevation limit, as is expected towards range edges. However, plant density was elevated within edge populations. In the greenhouse, high-elevation plants exhibited stronger clonal potential than low-elevation plants, likely explaining increased plant density in the field. Phylogeographic analysis supported more recent colonization of high-elevation populations which were also more genetically isolated, had more extreme heterozygote excess, and had smaller effective population size than low. Results support that colonization of high elevations was likely accompanied by increased asexuality, contributing to a decline in effective population size. Despite high plant density in leading-edge populations, their small effective size, isolation, and clonality could constrain adaptive potential.

opencc-zeroApr 2023View details →

Quantifying the effects sizes of common controls on methane emissions from an ombrotrophic peat bog

Northern wetlands and bogs are a large source of biogenic methane (CH4) to the atmosphere and shape climate. There is then substantial interest in quantifying the effect sizes of controls on bog CH4 emissions. Yet quantification is complicated because wetland emissions are, like the controls that regulate them, spatially and temporarily heterogeneous within individual wetland systems. To account for this heterogeneity, we established 55 measurement plots in a sampling design that had extensive spatial, and repeated temporal, coverage over one ombrotrophic bog. This coverage allowed us to robustly estimate the effect sizes of known environmental controls on CH4 emissions such as temperature, water table depth (WTD), and plant functional composition. As expected, 89% of the cumulative measured flux came from 16% of the plots, with consistently high CH4 emissions over two consecutive growing seasons. Soil temperature exhibited the strongest control on emissions, while WTD and vegetation composition had much smaller relative effects compared to temperature. Interestingly, at high temperatures, WTD was a strong determinant of whether a plot had high vs. lower emissions. Despite temperature's large effect size, the controls we measured only explained ~29% of the variance in CH4 fluxes. Overall, our data confirm observations from other wetlands that CH4 emissions are highly variable at local scales, and yet our data also reveal that effect sizes can be quantified robustly within this heterogeneity. Highly-replicated, local designs may therefore be useful for generating data that can serve to help refine wetland CH4 emissions uncertainties.

opencc-by-4.0May 2023View details →

Data set related to the manuscript "Investigating particle size effects on NMR spectra of ions diffusing in porous carbons through a mesoscopic model"

Graphical files in the agr format for all the figures in the manuscript entitled "Investigating particle size effects on NMR spectra of ions diffusing in porous carbons through a mesoscopic model". Examples of input files for the lattice simulations are also provided.

opencc-by-4.0Jun 2022View details →

Code and source data for the paper: "Heat over heritability: increasing body size in response to global warming is not stabilized by genetic effects in Bechstein's bats"

The first two script include code for the model building testing different fixed effect strucutes. The next two script includes all code for the descriptive analysis, all figures, as well as the animal models that compare heritabilty between the different environments (Q1-Q4) as well as between the birth environments differentials of mothers and daughters. Data contain the pedigree ('pedigree_Model_cod.csv'), further information ('pedigree_information_cod.csv) and weather data ('Weather_summer.csv')

opencc-zeroJul 2023View details →

Data from: Body size-dependent effects on the distribution patterns of phoretic mite species assemblages on Rhynchophorus ferrugineus (Olivier, 1790)

Phoretic mites attach to different body parts of the red palm weevil (RPW), Rhynchophorus ferrugineus (Olivier, 1790), to disperse. However, the question of how the patterns of attachment sites are formed remains intriguing. Here, we examined RPW-associated phoretic mites in four districts in Northern Portugal (macrohabitat), and investigated the patterns of mite distribution on six body parts of RPW (microhabitat). At the macrohabitat level, we detected seven phoretic mite taxa using the RPW host in each of the four studied districts, all documented for the first time in association with this invasive exotic species in Portugal. However, their relative abundance (species evenness) varied between districts, as did species diversity. All examined weevils carried mites, and the prevalence of the different taxa did not differ between districts or sex of weevils. Measured by mean abundance and degree of aggregation, Centrouropoda sp. proved to be the dominant taxon, while Acarus sp. and Curculanoetus rhynchophorus were considered common subordinate taxa and Uroovobella sp., Mesostigmata, Nenteria extremica and Dendrolaelaps sp. sparse taxa. At the microhabitat level, all taxa were present on all body parts of the RPW; the highest abundance was in a region encompassing the inner surface of the elytra and the membranous hind wings (subelytral space). Analysis of niche overlap revealed that the distribution patterns of phoretic mite taxa on the RPW were not randomly structured. In the subelytral space, interspecific coexistence of mites increased as a function of body size difference with the dominant Centrouropoda sp. We found that in the subelytral space the large dominant species Centrouropoda sp. displaced the larger species Uroobovella sp. and the similarly sized species Nenteria extremica, but coexisted with smaller taxa.

opencc-zeroJul 2023View details →

Data for: Developmental plasticity in anurans: meta-analysis reveals effects of larval environments on size at metamorphosis and timing of metamorphosis

Many anuran amphibians (frogs and toads) rely on aquatic habitats during their larval stage. The quality of this environment can significantly impact the overall lifetime fitness and dynamics of the population. Over 450 studies have been published on the impact of the environment on anuran developmental plasticity, yet we lack a synthesis of these effects across different environments. We conducted a meta-analysis and used a comparative approach to understand whether developmental plasticity in response to different larval environments produces predictable changes in metamorphic phenotypes. We analyzed data from 124 studies spanning 80 anuran species and six larval environments and showed that interspecific variation in mass at metamorphosis and the duration of the larval period is partly explained by the type of environment experienced during the larval period. Phylogenetic relationships among species were not associated with variation in mass at metamorphosis plasticity or duration of the larval period plasticity. Larval environments tended to reduce mass at metamorphosis relative to control conditions, with the degree of change depending on the identity and severity of environmental change. Higher temperatures and lower water levels shortened the duration of the larval period, whereas less food and higher densities increased the duration of the larval period. Our results provide a foundation for future studies on developmental plasticity, especially in response to global changes. This study provides motivation for additional work that links developmental plasticity with fitness consequences within and across life stages, as well as how the outcomes described here are altered in compounding environments.

Figure 5 in Medium and large sized mammals and the effect of habitat heterogeneity from a Caatinga shrubby forest at Serra de Santa Catarina, Paraíba, Brazil

Figure 5. Non-metric Multidimensional Scaling of medium-large mammal community structure according to different phytophysiognomies (a) and presence of water bodies (b), recorded in the Serra de Santa Catarina, Northeast Brazil, between August 2012 and November 2014. The ANOSIM (one-way) analysis showed no difference between phytophysiognomies (R = 0.1124, p> 0.05) and a significant difference between the presence of water bodies (R = 0.3907, p <0.05).

Figure 4 in Medium and large sized mammals and the effect of habitat heterogeneity from a Caatinga shrubby forest at Serra de Santa Catarina, Paraíba, Brazil

Figure 4. Average of abundance of medium-large mammal species according to different phytophysiognomies (a) and presence of water bodies (b), recorded in the Serra de Santa Catarina, Northeast Brazil, between August 2012 and November 2014. The Mann-Whitney analysis showed no difference between both phytophysiognomies (U = 29.5, p> 0.05) and presence of water bodies (U = 48.5, p> 0.05).

Figure 2 in Medium and large sized mammals and the effect of habitat heterogeneity from a Caatinga shrubby forest at Serra de Santa Catarina, Paraíba, Brazil

Figure 2. Different habitats analyzed in Serra de Santa Catarina, Paraíba, Brazil. A = Arboreal; B = Shrub; C = Arboreal-shrub; D = Water spot with a capuchin monkey in the foreground.

Figure 1 in Medium and large sized mammals and the effect of habitat heterogeneity from a Caatinga shrubby forest at Serra de Santa Catarina, Paraíba, Brazil

Figure 1. Study area, the Serra de Santa Catarina, extreme West of Paraíba state, northeastern Brazil. In light gray Caatinga biome and in dark gray Atlantic Forest Biome; in green, Serra de Santa Catarina limits.

Figure 3 in Medium and large sized mammals and the effect of habitat heterogeneity from a Caatinga shrubby forest at Serra de Santa Catarina, Paraíba, Brazil

Figure 3. Rarefaction curve for camera-trap sampling to medium-large mammal species of the Serra de Santa Catarina, Paraíba, northeastern Brazil, sampled between August 2012 and November 2014. Observed richness (S = 10 ± 1.76) has no significant difference to estimated richness (S = 12.97 ± 1.7) through the non-parametric Jackknife 1. Sample unit were defined as days with effective records in different camera-traps.