The explosive growth of molecular sequence data has made it possible to estimate species divergence times under relaxed-clock models using genome-scale datasets with many gene loci. In order both to improve model realism and to best extract information about relative divergence times in the sequence data, it is important to account for the heterogeneity in the evolutionary process across genes or genomic regions. Partitioning is a commonly used approach to achieve those goals. We group sites that have similar evolutionary characteristics into the same partition and those with different characteristics into different partitions, and then use different models or different values of model parameters for different partitions to account for the among-partition heterogeneity. However, how to partition data in practical phylogenetic analysis, and in particular in relaxed-clock dating analysis, is more art than science. Here, we use computer simulation and real data analysis to study the impact of the partition scheme on divergence time estimation. The partition schemes had relatively minor effects on the accuracy of posterior time estimates when the prior assumptions were correct and the clock was not seriously violated, but showed large differences when the clock was seriously violated, when the fossil calibrations were in conflict or incorrect, or when the rate prior was mis-specified. Concatenation produced the widest posterior intervals with the least precision. Use of many partitions increased the precision, as predicted by the infinite-sites theory, but the posterior intervals might fail to include the true ages because of the conflicting fossil calibrations or mis-specified rate priors. We analyzed a dataset of 78 plastid genes from 15 plant species with serious clock violation and showed that time estimates differed significantly among partition schemes, irrespective of the rate drift model used. Multiple and precise fossil calibrations reduced the differences among partition schemes and were important to improving the precision of divergence time estimates. While the use of many partitions is an important approach to reducing the uncertainty in posterior time estimates, we do not recommend its general use for the present, given the limitations of current models of rate drift for partitioned data and the challenges of interpreting the fossil evidence to construct accurate and informative calibrations.

Morphological data are a fundamental source of evidence to reconstruct the Tree of Life, and Bayesian phylogenetic methods are increasingly being used for this task. Bayesian phylogenetic analyses require the use of evolutionary models, which have been intensively studied in the past few years, with significant improvements to our knowledge. Notwithstanding, a systematic evaluation of the performance of partitioned models for morphological data has never been performed. Here we evaluate the influence of partitioned models, defined by anatomical criteria, on the precision and accuracy of summary tree topologies considering the effects of model misspecification. We simulated datasets using partitioning schemes, trees, and other properties obtained from two empirical datasets, and conducted Bayesian phylogenetic analyses. Additionally, we reanalysed 32 empirical datasets for different groups of vertebrates, applying unpartitioned and partitioned models, and, as a focused study case, we rea...

This dataset was used to conduct the study with the title "Effect of Knowledge Differentiation and State Space Partitioning on Subjective Probability Estimation"

Although it is widely agreed that data from multiple sources are necessary to confidently resolve phylogenetic relationships, procedures for accommodating and incorporating heterogeneity in such data remain underdeveloped. We explored the use of partitioned, model-based analyses of heterogeneous molecular data in the context of a phylogenetic study of swallowtail butterflies (Lepidoptera: Papilionidae). Despite substantial basic and applied study, phylogenetic relationships among the major lineages of this prominent group remain contentious. We sequenced 3.3 kb of mitochondrial (COI/COII α 2.3 kb) and nuclear (EF-1α 1.0 kb) DNA for 22 swallowtails, including representatives of Baroniinae, Parnassiinae, and Papilioninae, and several moth and butterfly outgroups. Parsimony encountered considerable difficulty in resolving the deepest splits among these taxa. We therefore chose two outgroups whose relationships to each other and to Papilionidae were undisputed and undertook detailed likelihood analyses of alternative topologies. Following previous studies that have demonstrated substantial heterogeneity in the evolutionary dynamics among process partitions of these genes, we estimated evolutionary parameters separately for gene-based and codon-based partitions. These values were then used as the basis for examining the likelihoods of possible resolutions and rootings under several partitioned and unpartitioned likelihood models. Partitioned models gave significantly better fits to the data than did unpartitioned models, and supported different topologies. However, the most likely topology varied from model to model. The most likely ingroup topology under the best-fitting, six partition GTR + Γ model favors a paraphyletic Parnassiinae. However, when examining the likelihoods of alternative rootings of this tree relative to rootings of the classical hypothesis two rootings of the latter emerge as most likely. Of these two, the most likely rooting is within the Papilioninae, although a rooting between Baronia and the remaining Papilionidae is only nonsignificantly less likely.

The global partition management software market is experiencing robust growth, driven by the increasing adoption of cloud computing, the proliferation of data storage devices, and the rising need for efficient data management across diverse platforms. The market, estimated at $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This growth is fueled by several key trends, including the expanding enterprise data centers requiring sophisticated partition management solutions, the increasing prevalence of hybrid cloud environments demanding seamless data migration and partitioning capabilities, and the growing demand for enhanced data security and recovery features integrated within partition management tools. Furthermore, the market is segmented by application (large enterprises and SMEs) and type (cloud-based and web-based), with cloud-based solutions gaining significant traction due to their scalability and accessibility. The market's growth is, however, tempered by certain restraints. The high initial investment required for advanced partition management software can be a barrier to entry for smaller businesses. Furthermore, the complexity of some software solutions can pose a challenge for less technically proficient users. Despite these restraints, the long-term outlook for the partition management software market remains positive, driven by continuous innovation, the integration of advanced features like AI-powered data management and automation capabilities, and the rising demand for efficient data organization and control in an increasingly data-centric world. The competitive landscape is marked by a mix of established players and emerging companies, each vying to offer superior functionality, ease of use, and competitive pricing. This competitive pressure is expected to further accelerate innovation and benefit end-users.

The estimation of the covariance matrix is a key concern in the analysis of longitudinal data. When data consists of multiple groups, it is often assumed the covariance matrices are either equal across groups or are completely distinct. We seek methodology to allow borrowing of strength across potentially similar groups to improve estimation. To that end, we introduce a covariance partition prior which proposes a partition of the groups at each measurement time. Groups in the same set of the partition share dependence parameters for the distribution of the current measurement given the preceding ones, and the sequence of partitions is modeled as a Markov chain to encourage similar structure at nearby measurement times. This approach additionally encourages a lower-dimensional structure of the covariance matrices by shrinking the parameters of the Cholesky decomposition toward zero. We demonstrate the performance of our model through two simulation studies and the analysis of data from a depression study. This article includes Supplementary Material available online.

Presentation. For more than a decade, graphs have been used to model the voting behavior taking place in parliaments. However, the methods described in the literature suffer from several limitations. The two main ones are that 1) they rely on some temporal integration of the raw data, which causes some information loss; and/or 2) they identify groups of antagonistic voters, but not the context associated with their occurrence. In this article, we propose a novel method taking advantage of multiplex signed graphs to solve both these issues. It consists in first partitioning separately each layer, before grouping these partitions by similarity. We show the interest of our approach by applying it to a European Parliament dataset. Particularly, we study the voting behavior of French and Italian MEPs on "Agriculture and Rural Development" (AGRI) during the 2012-13 legislative year.

These are the data used in the following paper:

N. Arınık, R. Figueiredo, and V. Labatut, “Multiple partitioning of multiplex signed networks: Application to European Parliament votes,” Social Networks, vol. 60, pp. 83–102, 2020. DOI: 10.1016/j.socnet.2019.02.001 ⟨hal-02082574⟩

Source code. The code source is accessible on GitHub: https://github.com/CompNet/MultiNetVotes

Citation. If you use these data our this source code, please cite the above paper.

@Article{Arinik2020, author = {Arınık, Nejat and Figueiredo, Rosa and Labatut, Vincent}, title = {Multiple Partitioning of Multiplex Signed Networks: Application to {E}uropean {P}arliament Votes}, journal = {Social Networks}, year = {2020}, volume = {60}, pages = {83-102}, doi = {10.1016/j.socnet.2019.02.001},}----------------------------------------------Details.# RAW INPUT FILESThe 'itsyourparliament' folder contains all raw input files for further data processing. This is the same raw data that can be found in our previous Figshare repository: https://doi.org/10.6084/m9.figshare.5785833The folder structure is as follows:* itsyourparliament/** domains: There are 28 domain files. Each file corresponds to a domain (such as Agriculture, Economy, etc.) and contains corresponding vote identifiers and their "itsyourparliament.eu" links.** meps: There are 870 Members of Parliament (MEP) files. Each file contains the MEP information (such as name, country, address, etc.)** votes: There are 7513 vote files. Each file contains the votes expressed by MEPs# ROLLCALL NETWORKSThis folder contains two separate zip files regarding rollcall networks:- rollcall-networks: This folder contains only the rollcall networks that are used in the article.- all-rollcall-networks: For those who are interested in other countries or domains, we make available all rollcall networks that we can extract from raw data.Note that these rollcall networks constitute the layers of the input signed multplex network, as illustrated in Figure 1 of the article. Note also that we consider three vote types in our network extraction process: FOR, AGAINST and ABSTAIN.# ROLLCALL PARTITIONSNote that MEPs who voted similarly are connected together by positive links, and are connected by negative links to MEPs that voted differently from them. MEPs who did not vote at all (ABSENT) are isolates (nodes without anyneighbor). We identify the factions of similarly voting MEPs in the graph by solving the Correlation Clustering problem (CC).The rollcall partitions correspond to voting patterns, as illustrated in Figure 1 of the article.# ROLLCALL CLUSTERINGThis folder contains the results of Steps 3 and 4 of our workflow (see Figure 1 in the article). The structure of this folder is as follows:|_ votetypes=FAA/: 'FAA' means we consider three vote types in our analysis: FOR, AGAINST and ABSTAIN.|_ F.purity-k=2-sil=SILHOUETTE_SCORE|_ clu=CLUSTER_NO/|_ network: It corresponds to the network created through the similarity network-based approach, as explained in Section 4.4 of the article.|_ partition: It corresponds to the characteristic voting pattern, as explained in Section 4.4 of the article.----------------------------------------------

Funding: this research benefited from the support of the Agorantic FR 3621, as well as the FMJH Program PGMO and from the support to this program from EDF-THALES-ORANGE-CRITEO.

The dataset includes 30 minutes values of partitioned evaporation (E) and transpiration (T), T:ET ratios, and other ancillary datasets for three ET partitioning methods viz. Flux Variance Similarity (FVS) method, Transpiration Estimation Algorithm (TEA), and Underlying Water Use Efficiency (uWUE) method for three wheat sites. Three wheat sites had different grazing treatments. For example, Site 1 was Grain-only and Graze-grain wheat for the 2016-17 and 2017-18 growing seasons, respectively. Site 2 was Grain-only wheat for the 2017-18 growing season. Site 3 was Graze-grain and Graze-out wheat for the 2016-17 and 2017-18 growing seasons, respectively. The grain-only wheat system is a single purpose to produce wheat grains only. Graze-grain wheat system has a dual purpose as it serves as a pasture for grazing cattle from November to February and is used to produce wheat grains later. Graze-out wheat system is also a single purpose crop that is grazed by the cattle for the entire season to solely serve as a pasture. FVS method performed ET partitioning using the high frequency (10 Hz) data collected from Eddy Covariance Flux stations, located near the middle of each field. The high-frequency data were also processed using the EddyPro software to get good quality estimates of different fluxes at 30-minute intervals. The processed 30-min data were used by TEA and uWUE methods for ET partitioning. Ancillary hydro-meteorological variables including net radiation, air temperature, soil water content, relative humidity, and others, also have been included in this dataset. The study sites were located at the United States Department of Agriculture, Agricultural Research Service (USDA-ARS), Grazinglands Research Laboratory, El Reno, Oklahoma. All sites were rainfed. Resources in this dataset:Resource Title: FVS output and other met data and site info. File Name: FVS_output_and_other_met_data_and_site_info.xlsxResource Description: Output of FVS model along with corresponding meteorological data and site metadata.Resource Title: TEA output. File Name: TEA_output.xlsxResource Description: Out from TEA model along with site metadata.Resource Title: WUE output. File Name: uWUE_output.xlsxResource Description: Output of WUE model run along with site metadata.

The global partition management software market is experiencing robust growth, driven by the increasing adoption of cloud computing, virtualization, and the expanding need for efficient data management across diverse organizational structures. The market, estimated at $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This growth is fueled by several key factors. The rise of large-scale data centers necessitates sophisticated partition management tools for optimal resource allocation and performance. Simultaneously, the growing prevalence of hybrid cloud environments and the need for seamless data migration across platforms are creating significant demand for versatile and reliable software solutions. Furthermore, small and medium-sized enterprises (SMEs) are increasingly adopting these tools to improve data organization and simplify IT management tasks, contributing to market expansion. The web-based segment is currently the leading contributor to market revenue, owing to its accessibility and cost-effectiveness, while the cloud-based segment is anticipated to demonstrate the highest growth rate during the forecast period due to its scalability and enhanced security features. Geographic expansion into rapidly developing economies in Asia Pacific and the Middle East & Africa also contributes to the overall market expansion. However, certain restraints affect market growth. These include the high initial investment costs for advanced software solutions, the availability of free open-source alternatives, and the complexity of managing partitions in heterogeneous environments. Despite these challenges, the ongoing digital transformation across industries and the increasing reliance on data-driven decision-making ensure that the partition management software market will maintain a positive trajectory in the coming years. The market is witnessing a trend towards AI-powered automation in partition management tasks, improving efficiency and reducing the need for specialized IT personnel. Furthermore, vendors are focusing on enhanced user interfaces and improved integration capabilities with other enterprise software, furthering the market's evolution. The continued development of innovative features and solutions will drive substantial growth in the global partition management software market, creating considerable opportunities for industry players.

See manuscript for more information.

We measured shoot architecture, photosynthesis, survival and growth by seedlings of three shade-tolerant species of maple (Acer pensylvanicum, A. rubrum, A. saccharum) in an experimental test of the gap partitioning hypothesis. Trees were felled to create a total of six cleared, elliptical canopy gaps of two sizes (8m x 12m, 75m2; 16m x 24m, 300m2). Naturally-established, undamaged, unbranched seedlings (15-30 cm tall, 10-20+ years old) of the three study species (2160 total, 720 per species) were transplanted into five plot locations (center and NW, NE, SW, and SE gap edges) within all six gaps and matching understory sites one year before gap creation. All plots were weeded regularly and spaded annually along the edges to remove above and below-ground competition. Measurements of microclimates and Non-competitive seedling responses were made over one year before and two years following gap release.

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The GO Partition Database was designed to feature ontology partitions with GO terms of similar specificity. The GO partitions comprise varying numbers of nodes and present relevant information theoretic statistics, so researchers can choose to analyze datasets at arbitrary levels of specificity. The GO Partition Database, featuring GO partition sets for functional analysis of genes from human and ten other commonly-studied organisms with a total of 131,972 genes.

The data set is collected to evaluate if two parasitoids (Spathius galinae and Tetrastichus planipennisi), introduced for biocontrol of the invasive emerald ash borer (EAB), Agrilus planipennis, into North America have established niche-partitioning, co-existing populations following their sequential or simultaneous field releases to 12 hard-wood forests located in Midwest and Northeast regions of the United States. Ash trees of various sizes (large, pole-size and saplings) were debarked meter by meter in early spring of 2019 (Michigan sites) or fall of 2019 (Northeast states: Connecticut, Massachusetts and New York). Detailed data collection procedures can be found in the associated publication in Biological Control. Resources in this dataset:Resource Title: Niche partitioning and coexistence of parasitoids of the same feeding guild introduced for biological control of an invasive forest pest - Michigan data. File Name: Michigan 2019-EAB Parasitoid Niche Partition-Raw.csvResource Description: Michigan DatasetResource Software Recommended: JMP,url: https://www.JMP.com Resource Title: Niche partitioning and coexistence of parasitoids of the same feeding guild introduced for biological control of an invasive forest pest - Northeast states data. File Name: NE Dataset 2019-EAB Parasitoid Niche Partition-Raw.csvResource Description: Northeast States Data setResource Title: Niche partitioning and coexistence of parasitoids of the same feeding guild introduced for biological control of an invasive forest pest - Data Dictionary. File Name: Data Dictionary for Parasitoid niche partitioning study from Biological Control.docxResource Description: Data dictionary

Genomewide association studies have contributed immensely to our understanding of the genetic basis of complex traits. One major conclusion arising from these studies is that most traits are controlled by many loci of small effect, confirming the infinitesimal model of quantitative genetics. A popular approach to test for polygenic architecture involves so‐called “chromosome partitioning” where phenotypic variance explained by each chromosome is regressed on the size of the chromosome. First developed for humans, this has now been repeatedly used in other species, but there has been no evaluation of the suitability of this method in species that can differ in their genome characteristics such as number and size of chromosomes. Nor has the influence of sample size, heritability of the trait, effect size distribution of loci controlling the trait or the physical distribution of the causal loci in the genome been examined. Using simulated data, we show that these characteristics have major influence on the inferences of the genetic architecture of traits we can infer using chromosome partitioning analyses. In particular, small variation in chromosome size, small sample size, low heritability, a skewed effect size distribution and clustering of loci can lead to a loss of power and consequently altered inference from chromosome partitioning analyses. Future studies employing this approach need to consider and derive an appropriate null model for their study system, taking these parameters into consideration. Our simulation results can provide some guidelines on these matters, but further studies examining a broader parameter space are needed.

Aim: Invasive species have the potential to alter hydrological processes by changing the local water balance. However, general patterns of how rainfall is partitioned into interception, throughfall and stemflow for invasive species worldwide have been seldom explored. We (a) describe the percentage of interception, throughfall and stemflow for the invasive woody plant species; (b) analyse the influence of morphological attributes (i.e., life-form, bark roughness, leaf type, leaf phenology and leaf area index) of invasive species on rainfall partitioning; and (c) compare the rainfall partitioning fluxes for co-occurring invasive and native species, testing whether these fluxes variation depends on water availability of the study location.

Location: Global.

Time period: Present.

Major taxa studied: Plants.

Methods: We compiled data of 100 studies that assessed rainfall partitioning by invasive species (N=67) and registered their morphological attributes. By means of a meta-analysis we compared the rainfall partitioning by native and invasive species (N=47 comparisons) and assessed how their fluxes were affected by water availability.

Results: Interception, throughfall and stemflow ranged from 1.6 - 59.5%, 39.1 - 92.7% and 0.1 - 31.6% of total rainfall, respectively. The bark roughness and leaf type were the most important attributes driving rainfall partitioning fluxes. While rough-barked species constrain rainfall inputs by promoting higher losses due to interception, smooth-barked species with broadleaves enhance the amount of rainwater reaching the soil by maximizing stemflow. For pair-wise comparisons, invasive species have higher stemflow values than native species for both drylands and humid areas, and higher throughfall in drylands, but less in humid areas.

Main conclusions: Our findings suggest that specific morphological attributes of invasive species determine higher localized water inputs, which may represent an ecohydrological advantage, particularly in water-limited ecosystems. These insights also suggest that the ecological role of stemflow, throughfall and interception should be considered in future plant invasions research.

Relationships among representatives of the five major Hawaiian Drosophila species groups were examined using data from eight different gene regions. A simultaneous analysis of these data resulted in a single most-parsimonious tree that (1) places the adiastola picture-winged subgroup as sister taxon to the other picture-winged subgroups, (2) unites the modified-tarsus species group with flies from the Antopocerus species group, and (3) places the white-tip scutellum species group as the most basal taxon. Because of the different gene sources used in this study, numerous process partitions can be erected within this data set. We examined the incongruence among these various partitions and the ramifications of these data for the taxonomic consensus, prior agreement, and simultaneous analysis approaches to phylogenetic reconstruction. Separate analyses and taxonomic consensus appear to be inadequate methods for dealing with the partitions in this study. Although detection of incongruence is possible and helps elucidate particular areas of disagreement among data sets, separation of partitions on the basis of incongruence is problematic for many reasons. First, analyzing all genes separately and then either presenting them all as possible hypotheses or taking their consensus provides virtually no information concerning the relationships among these flies. Second, despite some evidence of incongruence, there are no clear delineations among the various gene partitions that separate only heterogeneous data. Third, to the extent that problematic genes can be identified, these genes have nearly the same information content, within a combined analysis framework, as the remaining nonproblematic genes. Our data suggest that significant incongruence among data partitions may be isolated to specific relationships and the "false" signal creating this incongruence is most likely to be overcome by a simultaneous analysis. We present a new method, partitioned Bremer support, for examining the contribution of a particular data partition to the topological support of the simultaneous analysis tree.

Carbon partitioning in plants may be viewed as a dynamic process composed of the many interactions between sources and sinks. The accumulation and distribution of fixed carbon is not dictated simply by the sink strength and number but is dependent upon the source, pathways, and interactions of the system. As such, the study of carbon partitioning through perturbations to the system or through focus on individual traits may fail to produce actionable developments or a comprehensive understanding of the mechanisms underlying this complex process. Using the recently published sorghum carbon-partitioning panel, we collected both macroscale phenotypic characteristics such as plant height, above-ground biomass, and dry weight along with microscale compositional traits to deconvolute the carbon-partitioning pathways in this multipurpose crop. Multivariate analyses of traits resulted in the identification of numerous loci associated with several distinct carbon-partitioning traits, which putatively regulate sugar content, manganese homeostasis, and nitrate transportation. Using a multivariate adaptive shrinkage approach, we identified several loci associated with multiple traits suggesting that pleiotropic and/or interactive effects may positively influence multiple carbon-partitioning traits, or these overlaps may represent molecular switches mediating basal carbon allocating or partitioning networks. Conversely, we also identify a carbon tradeoff where reduced lignin content is associated with increased sugar content. The results presented here support previous studies demonstrating the convoluted nature of carbon partitioning in sorghum and emphasize the importance of taking a holistic approach to the study of carbon partitioning by utilizing multiscale phenotypes.

In this study, we combined two actual evapotranspiration datasets (ET), one obtained from a root zone water balance model and another from an energy balance model, to partition annual ET into green (rainfall-based) and blue (surface/groundwater) water sources. Time series maps of green water ET (GWET) and blue water ET (BWET) are produced for the conterminous United States (CONUS) over 2001–2015.

1. How demographic factors lead to variation or change in growth rates can be investigated using life table response experiments (LTRE) based on structured population models. Traditionally, LTREs focused on decomposing the asymptotic growth rate, but more recently decompositions of annual 'realized' growth rates have gained in popularity.
2. Realized LTREs have been used particularly to understand how variation in vital rates translates into variation in growth for populations under long-term study. For these, complete population models may be constructed by combining data in an integrated population model (IPM). IPMs are also used to investigate how temporal variation in environmental drivers affect vital rates. Such investigations have usually come down to estimating covariate coefficients for the effects of environmental variables on vital rates, but formal ways of assessing how they lead to variation in growth rates have been lacking.
3. We extend realized LTREs in two ways. First, we further partition the contributions from vital rates into contributions from temporally varying factors that affect them. The decomposition allows us to compare the resultant effect on the growth rate of different environmental factors that may each act via multiple vital rates. Second, we show how realized growth rates can be decomposed into separate components from environmental and demographic stochasticity. The latter is typically omitted in LTRE analyses.
4. We illustrate how to use the approach in an IPM for data from a 26-year study on northern wheatears (Oenanthe oenanthe), a migratory passerine bird breeding in an agricultural landscape. For this population, consisting of around 50–120 breeding pairs per year, we partition variation in realized growth rates into environmental contributions from temperature, rainfall, population density, and unexplained random variation via multiple vital rates, and from demographic stochasticity.
5. The case study suggests that variation in first-year survival via the random component, and adult survival via temperature are two main factors behind environmental variation in growth rates. More than half of the variation in growth rates is suggested to come from demographic stochasticity, demonstrating the importance of this factor for populations of moderate size.

This dataset contains the experiment data for straight cylinder and curved cylinder experiments undertaken - experimental values used for graphs generated are given. For straight cylinder experiments, the data includes simulation experiment data which includes rivulet formation rate, stemflow formation rate and stemflow volume (as percentages of total). It also includes the separate height (lambda as a function of flow rate/inclination angle/length along cylinder) and velocity estimation experimental data. For curved cylinder experiments, the pour point formation rate data is given for 13 degree and 20 degree curved cylinders.