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63 results for “co-existence”
Model-based fMRI reveals co-existing specific and generalized concept representations
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Raw data: Specialized metabolites accumulation pattern in buckwheat is strongly influenced by accession choice and co-existing weeds
<p>Screening suitable allelopathic crops and crop genotypes that are competitive with weeds can be a sustainable weed control strategy to reduce the massive use of herbicides. In this study, three accessions of common buckwheat <em>Fagopyrum esculentum</em> Moench. (Gema, Kora, and Eva) and one of Tartary buckwheat <em>Fagopyrum tataricum</em> Gaertn. (PI481671) were screened against the germination and growth of the herbicide-resistant weeds <em>Lolium rigidum </em>Gaud. and <em>Portulaca oleracea</em> L. The chemical profile of the four buckwheat accessions was characterised in their shoots, roots, and root exudates in order to know more about their ability to sustainably manage weeds and the relation of this ability with the polyphenol accumulation and exudation from buckwheat plants. Our results show that different buckwheat genotypes may have different capacities to produce and exude several types of specialized metabolites, which lead to a wide range of allelopathic and defence functions in the agroecosystem to sustainably manage the growing weeds in their vicinity. The ability of the different buckwheat accessions to suppress weeds was accession-dependent without differences between species, as the common (Eva, Gema, and Kora) and Tartary (PI481671) accessions did not show any species-dependent pattern in their ability to control the germination and growth of the target weeds. Finally, Gema appeared to be the most promising accession to be evaluated in organic farming due to its capacity to sustainably control target weeds while stimulating the root growth of buckwheat plants.</p>
Terrestrial paleoclimate reconstruction of the UK Neogene (?Langhian to Piacenzian) comparing CREST, CRACLE and the Co-existence Approach
<p><strong>Abstract </strong></p> <p>The first detailed reconstruction of the terrestrial paleoclimate development of the UK Neogene (?Langhian to Piacenzian) is presented. The paleoclimate data are derived from the paleobotanical record using two probability-based reconstruction techniques CREST (Climate REconstruction SofTware) (Chevalier et al. 2014) and CRACLE (Climate Reconstruction Analysis using Coexistence Likelihood Estimation) (Harbert & Nixon 2015) that use Bayesian and likelihood estimation probability respectively. The results of these reconstructions are presented alongside reconstructions using the widely-applied Co-existence Approach (CA) (Utescher et al. 2014) for comparison. While all three techniques use the climate requirements of their Nearest Living Relatives as the basis of their reconstruction, they use different database observations. CREST and CRACLE use the GBIF (Global Biodiverstiy Information Facility) (GBIF, 2021) as well as WorldClim inputs for the 19 bioclimate variables used by BIOCLIM (<a href="http://www.worldclim.org/bioclim">http://www.worldclim.org/bioclim</a>). Meanwhile, the CA uses the Palaeoflora database, meaning the input for the three models is different. The reconstructions for the UK Neogene palaeoclimate come from 4 localities (12 samples total) spanning the Middle Miocene (Langhian) to Pliocene (Piacenzian): Trwyn y Parc, Anglesey (Middle Miocene), Brassington Formation, Derbyshire (Serravallian-Tortonian), Coralline Crag Formation (latest Zanclean-earliest Piacenzian) and Red Crag Formation (Piacenzian-Gelasian) of southeast England. We present CREST and CRACLE reconstructions of Mean Annual Temperature (MAT), Mean Temperature of Warmest Quarter (MTWQ), Mean Temperature of Coldest Quarter (MTCQ), Mean Annual Precipitation (MAP) and precipitation seasonality (CoV ×100). The CA does not reconstruct MTWQ, MTCQ or precipitation seasonality. Instead, the CA reconstructs Warmest Month Mean Temperature (WMMT) and Coldest Month Mean Temperature (CMMT). The proportion of rainfall falling in the wettest months of the year (RMPwet(%)) was used as a proxy for precipitation seasonality following the methodology of Jacques et al. (2011) and Utescher et al. (2015). The CREST R-code output provides 0.5 and 0.95 (2-σ) uncertainties as well as an optimum and mean for each variable. The CRACLE R-code output provides both parametric and non-parametric joint likelihoods (P-CRACLE and N-CRACLE) with 0.95 (2-σ) uncertainties and a mean that is based on P-CRACLE. The CA generates a minimum and maximum likelihood which together comprise the coexistence interval. The Neogene climate reconstruction of the UK shows a cooling trend from the Langhian to the Pliocene-Pleistocene boundary. CREST and CRACLE produce trends and values consistent with Co-existence Approach data with 0.95 uncertainties overlapping with the CA coexistence interval.</p> <p><strong>File Descriptions </strong></p> <p>Table S1 displays the complete reconstruction for the UK Neogene using CREST, CRACLE and the Co-existence Approach.<br> Table S2 displays detailed site information including: modern and paleo latitude and longitude, dating technique, modern climatology and fossil assemblage diversity (number of fossil taxa versus number of NLRs used for climate reconstruction). Modern climatology has been included to serve as a comparison to the reconstructed Neogene climate. This data has been extracted from WorldClim 2.1 (Fick & Hijmans, 2017).<br> Data Set S1 contains the list of fossil spore and pollen taxa per site and associated Nearest Living Relatives (NLRs), where identifiable, used as the input for CREST, CRACLE and the Co-existence Approach. Relic taxa are included and highlighted in red.<br> Data Set S2 is included to show the effect relic taxa have on paleoclimate reconstructions. The relic taxa are removed following the protocol of Utescher et al. (2014) whereby known relic taxa are removed from analyses to avoid biased reconstructions. Relic taxa removed from analyses include <em>Cathaya</em>, <em>Cryptomeria</em>, <em>Pinus sylvestris</em> and <em>Sciadopitys </em>when present.<br> Data Set S3 is included to show the effects of removing family-level identifications in CRACLE reconstructions. Removing families is shown to generate a less informative reconstruction. Including both genera- and family-level classifications of NLR (Nearest Living Relative) is recommended, however we suggest identifying NLRs (Nearest Living Relatives) to genera-level wherever possible.</p>
Fig. 2. A in Macro-parasites and micro-parasites co-exist in rodent communities but are associated with different community-level parameters
Fig. 2. A histogram of the counts of individual rodents that were uninfected or infected with B. burgdorferi sensu lato with certain macro-parasite infections. The types of infection were: no tick or helminth burden on an individual rodent (No macro-parasite), helminth burden only (Helminth Only), tick burden only (Tick Only), or both ticks and helminths were found on individual rodent (Tick & Helminth). The colors denote for N. fuscipes (blue) and Peromyscus species (yellow). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1. A in Macro-parasites and micro-parasites co-exist in rodent communities but are associated with different community-level parameters
Fig. 1. A boxplot of the mean macro-parasite burden across N. fuscipes and Peromyscus species. The log of helminth (left panel) and tick (right panel) counts on individual rodents were used for visualization purposes.
Data from: An environmental habitat gradient and within-habitat segregation enable co-existence of ecologically similar bird species
<p>Niche theory predicts that ecologically similar species can co-exist through multidimensional niche partitioning. However, due to the challenges of accounting for both abiotic and biotic processes in ecological niche modelling, the underlying mechanisms that facilitate co-existence of competing species are poorly understood. In this study, we evaluated potential mechanisms underlying the co-existence of ecologically similar bird species in a biodiversity-rich transboundary montane forest in east-central Africa by computing niche overlap indices along an environmental elevation gradient, diet, forest strata, activity patterns, and within-habitat segregation across horizontal space. We found strong support for abiotic environmental habitat niche partitioning, with 55% of species pairs having separate elevation niches. For the remaining species pairs that exhibited similar elevation niches, we found that within-habitat segregation across horizontal space and to a lesser extent vertical forest strata provided the most likely mechanisms of species co-existence. Co-existence of ecologically similar species within a highly diverse montane forest was determined primarily by abiotic factors (e.g., environmental elevation gradient) that characterize the Grinnellian niche and secondarily by biotic factors (e.g., vertical and horizontal segregation within habitats) that describe the Eltonian niche. Thus, partitioning across multiple levels of spatial organization is a key mechanism of co-existence in diverse communities.</p>
Data from: An environmental habitat gradient and within-habitat segregation enable co-existence of ecologically similar bird species
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Genomic data, part 1, of "Secondary contact rather than co-existence – Erebia butterflies in the Alps"
<p>Secondary contact zones are ideal systems to study the processes that govern the evolution of reproductive barriers, especially at advanced stages of the speciation process. An increase in reproductive isolation resulting from selection against maladaptive hybrids is thought to contribute to reproductive barrier buildup in secondary contact zones. While such processes have been invoked for many systems, it remains unclear to which extent they influence contact zone dynamics in nature. Here, we study a very narrow contact zone between the butterfly species <em>Erebia</em> <em>cassioides </em>and <em>E.</em> <em>tyndarus</em> in the Swiss Alps. We quantified phenotypic traits related to wing shape and reproduction as well as ecology in order to compare the degree of intra- and interspecific differentiation. Even though only very few first-generation hybrids occur, we find no strong indications for current reinforcing selection, suggesting that if reinforcement occurred in our system, it likely operated in the past. Additionally, we show that both species differ less in their ecological niche at the contact zone than elsewhere, which could explain why co-existence between these butterflies may currently not be possible.</p>
Genomic data, part 2, of "Secondary contact rather than co-existence – Erebia butterflies in the Alps"
<p>Secondary contact zones are ideal systems to study the processes that govern the evolution of reproductive barriers, especially at advanced stages of the speciation process. An increase in reproductive isolation resulting from selection against maladaptive hybrids is thought to contribute to reproductive barrier buildup in secondary contact zones. While such processes have been invoked for many systems, it remains unclear to which extent they influence contact zone dynamics in nature. Here, we study a very narrow contact zone between the butterfly species <em>Erebia</em> <em>cassioides </em>and <em>E.</em> <em>tyndarus</em> in the Swiss Alps. We quantified phenotypic traits related to wing shape and reproduction as well as ecology in order to compare the degree of intra- and interspecific differentiation. Even though only very few first-generation hybrids occur, we find no strong indications for current reinforcing selection, suggesting that if reinforcement occurred in our system, it likely operated in the past.<strong> </strong>Additionally, we show that both species differ less in their ecological niche at the contact zone than elsewhere, which could explain why co-existence between these butterflies may currently not be possible.</p>
Data from: Understanding carnivore interactions in a cold arid trans-Himalayan landscape: What drives co-existence patterns within predator guild along varying resource gradients?
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Data from: Gut microbiota provide co-existing strategies for two species of symmetrically distributed rodents in competition for food
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Data from: Effects of niche overlap on co-existence, fixation, and invasion in a population of two interacting species
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Data from: Soil biota and chemical interactions promote co-existence in co-evolved grassland communities
1. Plant populations can exhibit local adaptation to their abiotic environment, such as climate and soil properties, as well as biotic components such as the chemical signatures of dominant plant species and mutualistic and pathogenic microbial populations. While patterns of local adaptation in individual species are widely recorded, the importance of microevolutionary processes for plant community assembly and function is poorly understood. 2. Here we examined how a history of long-term co-existence, and thus potential for local co-adaptation, influenced the process of plant community assembly. Soil inocula and seeds of eight plant species were collected from three calcareous grasslands with a long history of grazing within a single geographical region. Mesocosm communities were established using local genotypes from a single site or an artificial mixture of genotypes from two different sites. To investigate the role of root exudates and local ("home") and non-local ("away") soil biota as mediators of plant species co-existence, the population origin treatment was combined with the addition of activated carbon, which is known to adsorb exudates from soil, and sterilisation of soil inocula. Individual-, species- and mesocosm-level responses were measured over the course of three growing seasons. 3. We found that root exudates promoted seedling survival, species co-existence and productivity in assemblages of genotypes originating from the same community but had a weak impact in mixed, novel communities. Soil biota promoted the growth of subordinate forbs and restrained the growth of dominant graminoids, particularly in communities composed of local genotypes. The effects of population origin were significant in the first two years of the experiment but were not detectable in the third year when interbreeding and new seedling establishment took place. Plant genotypes coupled with "home" microbial inoculum experienced a stronger reduction in growth compared with genotypes exposed to "away" inoculum, indicating that plants experienced home-field disadvantage in interactions with soil biota. 4. Synthesis. Our study demonstrates that the mechanisms of initial grassland community assembly depend on community history, with belowground chemical interactions and plant interactions with soil biota becoming stronger drivers of dynamics in established and potentially co-evolved communities.
ICSME 2024 Research Track: "What Happened to my Models?" History-Aware Co-Existence and Co-Evolution of Metamodels and Models
<p> </p> <h1>ICSME 2024 Research Track: “What Happened to my Models?” History-Aware Co-Existence and Co-Evolution of Metamodels and Models</h1> <p> </p> <p>This repository provides the dataset and results for the evaluation of the paper “What Happened to my Models?” of the ICSME 2024 Research track.<br>The dataset consists of the following files:</p> <ul> <li><strong>RQ1-Type-Refactors.zip </strong>contains the operations and refactoring performed on each of the given metamodels used by our approach in RQ1.</li> <li><strong>RQ1-Type-Results.zip</strong>: contains the group results of RQ1 as shown in our paper with additional metrics of other operations not highlighted in our paper due to space limitations.</li> <li><strong>RQ2-3-PlantUML-Models.zip</strong>: contains the 250 PlantUML models and the metamodel. This folder contains the co-evolved PlantUML models, the operations performed during the co-evolution, their metrics and the state of the models bore and after the co-evolution. </li> <li><strong>RQ2-3-PlantUML-Results.zip:</strong> contains the group results of RQ2 and RQ3 as shown in our paper with additional metrics of other operations not highlighted in our paper due to space limitations</li> <li><strong>RQ2-3-FHIR-Models.zip</strong>: contains the 1180 FHIR models and the metamodel. This folder contains the co-evolved FHIR models, the operations performed during the co-evolution, their metrics and the state of the models bore and after the co-evolution.</li> <li><strong>RQ2-3-Results.zip:</strong> contains the grouped results of RQ2 and RQ3 as presented in our paper.</li> <li><strong>Additionalnformation.pdf:</strong> contains additional information on how to read the files extracted by our approach, i.e., how to read the models and operations and how our executable refactoring catlaog works since we only focused on Property Refactorings in the paper.</li> <li><strong>Results.pdf</strong>: Contains an overview of the results (the results from our paper + additional results)</li> <li><strong>Tools.zip: </strong>Contains the tools used for the evalution. For an explaination how to use it read the <strong>Additionalnformation.pdf, </strong>see below<strong> </strong>or contact the authors</li> </ul> <p><strong>Running the tools:</strong></p> <p><em>Windows 10/11<br></em><em>JDK 20 or above</em></p> <p>The tools consist of two programs: </p> <ul> <li><strong>importer.jar<br></strong>This file is used to import a FHIR or PlantUML file into the server and co-evolve it.</li> <li><strong>server_FHIR_.jar<br></strong>The server stores the models and co-evolves them. The files provided already have the metamodels preloaded, that are used in RQ2 and RQ3, i.e., FHIR_STU3 contains the FHIR metamodel version DSTU2 and STU3 and our hybrid PlantUML, while FHIR_ synthetic contains the FHIR metamodel DSTU2 and our synthetically created one.</li> </ul> <p><strong>How to use the Tools</strong></p> <p>First, start the server by starting the jar. The server also has an experimental GUI mode that allows engineers to check the types and instances that were created. <em><strong>Note: </strong>This mode is currently under development and is still unstable. The mode <em>is accessible</em> by adding -gui as a parameter.</em></p> <p><em>java -jar server_FHIR_STU3.jar -gui</em></p> <p>Otherwise, just run the server normally:</p> <p><em>java -jar server_FHIR_STU3.jar</em></p> <p>After the server has booted up, it exports InstanceTypes and operations created for the FHIR and PlantUML metamodels. Next, you start the importer. The importer has two modes: the PlantUML mode, where it imports a PlantUML state machine and co-evolves it and the FHIR mode, where it imports an FHIR file and co-evolves it into either STU3 or our synthetic version (depending on which of the preloaded servers is running). Just run the tool by providing either FHIR or PlantUML, the imported file and the path where the output should be stored.</p> <p><strong><em>FHIR-Mode:</em></strong></p> <p><em>java -jar importer.jar FHIR C:\Users\Admin\Desktop\Aaron697_Brekke496_2fa15bc7-8866-461a-9000-f739e425860a.json C:\Users\Admin\Desktop\results</em></p> <p><strong>PlantUML Mode:</strong></p> <p><em>java -jar importer.jar PlantUML C:\Users\Admin\Desktop\branch.puml C:\Users\Admin\Desktop\results</em></p> <p><em><strong>Note: </strong></em><em>Please run both the tool and the server in a command line to receive additional information about the importing and co-evolution since the tool is otherwise without a user interface.</em></p> <p> </p>
FIGURE 5. Drapetis males. Left mid femur, SEM images showing modified cuticle. A. D in Co-existing species of Drapetis Meigen in Skåne (S Sweden) with description of a new species and a key to males of NW European species (Diptera: Hybotidae)
FIGURE 5. Drapetis males. Left mid femur, SEM images showing modified cuticle. A. D. completa Kovalev; B. D. exilis Meigen; C. D. infitialis Collin; D. D. exilis, detail of anterior cuticle; E. D. infitialis, detail of anterior cuticle. Scales: A = 1 μm, C = 10 μm.
FIGURE 6. Drapetis males. Left mid femur, SEM images showing modified cuticle. A. D in Co-existing species of Drapetis Meigen in Skåne (S Sweden) with description of a new species and a key to males of NW European species (Diptera: Hybotidae)
FIGURE 6. Drapetis males. Left mid femur, SEM images showing modified cuticle. A. D. parilis Collin; B. D. pusilla Loew; C. D. parilis, detail of anterior cuticle; D. D. pusilla, detail of antero-dorsal cuticle. Scales: C, D = 10 μm.
FIGURE 4 in Co-existing species of Drapetis Meigen in Skåne (S Sweden) with description of a new species and a key to males of NW European species (Diptera: Hybotidae)
FIGURE 4. Drapetis abrollensis sp. nov. Right midleg, SEM images showing modified cuticle. A. Femur and tibia; B. Subapical cuticle of femur; C. Ventral edge of tibia; D. Detail of C showing accumulations of brochosomes. Scales: A = 0.1 mm; C = 1 μm.
FIGURE 3. Drapetis males. Legs. A. D in Co-existing species of Drapetis Meigen in Skåne (S Sweden) with description of a new species and a key to males of NW European species (Diptera: Hybotidae)
FIGURE 3. Drapetis males. Legs. A. D. assimilis (Fallén), right hind femur; B. D. pusilla Loew, left fore femur; C. D. abrollensis sp. nov., right mid femur and tibia. Scale = 0.1 mm.
FIGURE 2. Drapetis males. Right wing. A. D in Co-existing species of Drapetis Meigen in Skåne (S Sweden) with description of a new species and a key to males of NW European species (Diptera: Hybotidae)
FIGURE 2. Drapetis males. Right wing. A. D. assimilis (Fallén); B. D. abrollensis sp. nov.; C. D. incompleta Collin. Scale = 0.1 mm.
FIGURE 1 in Co-existing species of Drapetis Meigen in Skåne (S Sweden) with description of a new species and a key to males of NW European species (Diptera: Hybotidae)
FIGURE 1. Drapetis abrollensis sp. nov. Male terminalia. A. Right epandrial lamella with projections on apical border, right lateral view; B. Epandrium with cerci, dorsal view; C. Left surstylus, left lateral view; D. Epandrium and hypandrium, ventral view. Abreviations: ej = ejaculatory apodeme; hy = hypandrium; lc = left cercus; lel = left epandrial lamellae; ls 1 = left surstylus 1; ls 2 = left surstylus 2; p1, p2 = projections of the right epandrial lamella; rc = right cercus; rel = right epandrial lamella. Scale = 0.1 mm.
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