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23 results for “Functionally useful plants”
Data, code and software to reproduce the article entitled "Modeling soil-plant functioning of intercrops using comprehensive and generic formalisms implemented in the STICS model"
<p>This is the data, code and software to reproduce the article entitled " Modeling soil-plant functioning of intercrops using comprehensive and generic formalisms implemented in the STICS model". Here is a summary of the paper:</p> <p>The growing demand for sustainable agriculture is raising interest in intercropping for its multiple potential benefits to avoid or limit the use of chemical inputs or increase the production per surface unit. Predicting the existence and magnitude of those benefits remains a challenge given the numerous interactions between interspecific plant-plant relationships, their environment and the agricultural practices. Soil-crop models are critical in understanding these interactions in dynamics during the whole growing season, but few models are capable of accurately simulating intercropping systems.</p> <p>In this study, we propose a set of simple and generic formalisms for simulating key interactions in intercropping systems that can be readily included into existing dynamic crop models. This requires simulating important processes such as development, light interception, plant growth, N and water balance, and yield formation in response to management practices, soil conditions, and climate. These formalisms were integrated into the STICS soil-crop model and evaluated using observed data of intercropping systems of cereal and legumes mixtures, including Faba bean-Wheat, Pea-Barley, Sunflower-Soybean, and Wheat-Pea mixtures. We demonstrate that the proposed formalisms provide a comprehensive simulation of soil-plant interactions in various types of bispecific intercrops. The model was found consistent and generic under a range of spring and winter intercrops (nRMSE = 25% for maximum leaf area index, 23% for shoot biomass at harvest, and 18% for yield).</p> <p>This is the first time a complete set of formalisms has been developed and published for simulating intercropping systems and integrated into a soil-crop model. With its emphasis on being generic, sufficiently accurate, simple, and easy to parameterize, STICS is well-suited to help researchers designing <em>in silico</em> the agroecological transition by virtually pre-screening sustainable, manageable intercrop systems adapted to local conditions.</p> <p> </p> <p> </p> <p> </p>
ARCHIMED-φ simulation files for the simulation of Design A from the article "When architectural plasticity fails to counter the light competition imposed by planting design: an in silico approach using a functional-structural model of oil palm"; in silico Plants journal
<p>Input files for the simulation of Design A in ARCHIMED-φ from the article "When architectural plasticity fails to counter the light competition imposed by planting design: an in silico approach using a functional-structural model of oil palm"; in silico Plants journal.</p> <p>See https://archimed-platform.github.io/archimed-phys-user-doc/ for more details on the model.</p> <p>Make a simulation by opening a terminal at the root of the folder and type: `java -jar .\archimed-phys.jar .\DesignA_MockUpA_seed1_MAP_72.yml`.</p>
Data from: Plant richness, land use and temperature differently shape invertebrate leaf-chewing herbivory on plant functional groups
<p class="MsoNormal">Nutrient demands of leaf-chewing invertebrate herbivores change with temperature, which causes shifts in herbivores' diets. Temperature may act differently on herbivore species, so that factors shaping herbivore species richness may modulate temperature effects on invertebrate herbivory among plant functional groups with different nutrient composition (C:N ratio low to high: legumes, non-leguminous forbs, grasses). Global warming urges a deeper understanding of temperature effects on herbivory among plant functional groups in different habitats and landscapes. This study obtained measures on proportional leaf area loss to leaf-chewing invertebrate herbivores ('herbivory') on three plant functional groups on 80 plots of open herbaceous vegetation adjacent to different habitat types (forest, grassland, arable field, settlement) along climate and land-use gradients in Bavaria, Germany. Herbivory was analysed with regard to habitat characteristics (habitat type, plant richness at species and family level, local mean temperature), landscape characteristics (proportion of grassland, landscape diversity; 0.2–3.0-km), climate (multi-annual mean temperature, 'MAT') and interactive effects of plant functional group, temperature and habitat or landscape characteristics. Herbivory on plant functional groups changed differently in response to plant richness (family level only) and habitat type, but not to differences in landscape characteristics and temperature – only on grassland plots, multi-annual mean temperature differentially affected herbivory among plant functional groups. Thus, abiotic and biotic factors can differently affect leaf-chewing herbivory on plant functional groups. Under current conditions, plant richness and habitat type more strongly affected herbivory among legumes, forbs and grasses than temperature and landscape-scale land use.</p>
Data from: Plant richness, land use and temperature differently shape invertebrate leaf-chewing herbivory on plant functional groups
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Studies of NH4+ and NO3- uptake ability of subalpine plants and resource-use strategy identified by their functional traits
<p>Data for the preprint "Studies of NH4+ and NO3- uptake ability of subalpine plants and resource-use strategy identified by their functional traits.”, by Legay N. , Grassein F., Arnoldi C., Segura R., Laîné P., Lavorel S., Clément J.C.</p>
Dataset for paper "Interpreting the shifts in forest structure, plant community composition, diversity, and functional identity by using remote sensing-derived wildfire severity"
<p>Interpreting the shifts in forest structure, plant community composition, diversity, and functional identity by using remote sensing-derived wildfire severity . New collected data</p>
Beyond species richness and community composition: Using plant functional diversity to measure restoration success in jarrah forest
<p>Aim: The importance of restoring ecosystem functions to native systems that have been degraded, damaged or destroyed is increasingly recognised. Yet few studies have measured the effect of restoration efforts on ecosystem functioning or the functional diversity (FD) that underpins it. Here we assessed change in FD of restored assemblages one to 25 years after the onset of post-mine restoration.</p> <p>Location: Northern Jarrah (<i>Eucalyptus marginata</i> Donn ex Sm.) Forest bioregion of south-western Australia.</p> <p>Methods: Functional richness, evenness, divergence and dispersion were derived from five plant functional traits relevant to community reassembly. Effects of three explanatory variables (i.e., age, year restoration was initiated, and time since fire) on six response variables (i.e., four FD indices, species richness, and compositional similarity to nearby reference forest) were analysed using linear mixed models for a dataset with repeated measures of plots through time (n= 810 plots), and linear models for a sub-set of one-time measures of different aged assemblages (i.e., space-for-time approach; n= 490 plots).</p> <p>Results: Functional evenness and functional dispersion increased with age, while functional divergence and functional richness decreased with age. Functional dispersion increased with time since fire, while functional richness decreased with time since fire. Species richness decreased with age, but at 25-years, species richness was comparable to that observed in reference forest. In contrast, similarity showed no relationship with age of restored forest, and at 25-years, similarity of restored forest to reference was low compared with similarity of reference forest to itself. Three of four FD indices had not reached those of reference jarrah forest 25-years after restoration had been initiated.</p> <p>Conclusions: Reassembly of FD suggests importance of environmental filtering and high functional redundancy. A longer time frame may be needed to assess FD of restored assemblages, and in the meantime, species richness is not an adequate surrogate of FD.</p>
Estimating global GPP from the plant functional type perspective using a machine learning approach
<p><span>The long-term monitoring of gross primary production (GPP) is crucial to the assessment of the carbon cycle of terrestrial ecosystems. In this study, a well-known machine learning model (Random Forest, RF) is established to reconstruct the global GPP dataset named ECGC_GPP. The model distinguished nine functional plant types, including C3 and C4 crops, using eddy fluxes, meteorological variables, and leaf area index as training data of the RF model. Based on ERA5_Land and the corrected GEOV2 data, the global monthly GPP dataset at a 0.05-degree resolution from 1999 to 2019 was estimated. The results showed that the RF model could explain 74.81% of the monthly variation of GPP in the testing dataset, of which the average contribution of Leaf Area Index (LAI) reached 41.73%. The average annual and standard deviation of GPP during 1999–2019 were 117.14 ± 1.51 Pg C yr<sup>-1</sup>, with an upward trend of 0.21 Pg C yr<sup>-2</sup> (<em>p</em> < 0.01). By using the plant functional type classification, the underestimation of cropland is improved. Therefore, ECGC_GPP provides reasonable global spatial patterns and long-term trends of annual GPP.</span></p>
Beyond species richness and community composition: Using plant functional diversity to measure restoration success in jarrah forest
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Land-use impacts on plant functional diversity throughout Europe
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Estimating global GPP from the plant functional type perspective using a machine learning approach
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Data from: Using soil amendments and plant functional traits to select native tropical dry forest species for the restoration of degraded Vertisols
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Dataset used for the submitted manuscript "The hump-shaped effect of plant functional diversity on the biological control of a multi-species pest community"
<p>Dataset</p>
Data from: Plant functional types broadly describe water use strategies in the Caatinga, a seasonally dry tropical forest in northeast Brazil
<ol> <li><span>In seasonally dry tropical forests, plant functional type can be classified as deciduous low wood density, deciduous high wood density, or evergreen high wood density species. While deciduousness is often associated with drought-avoidance and low wood density is often associated with tissue water storage, the degree to which these functional types may correspond to diverging and unique water use strategies has not been extensively tested. </span></li> <li><span>We examined (1) tolerance to water stress, measured by pre-dawn and mid-day leaf water potential; (2) water use efficiency, measured via foliar δ<sup>13</sup>C; and (3) access to soil water,<i> </i>measured via stem water δ<sup>18</sup>O.</span></li> <li><span>We found that deciduous low wood density species maintain high leaf water potential and low water use efficiency. Deciduous high wood density species have lower leaf water potential and variable water use efficiency. Both groups rely on shallow soil water. Evergreen high wood density species have low<i> </i>leaf water potential, higher water use efficiency, and access alternative water sources. These findings indicate that deciduous low wood density species are drought avoiders, with a specialized strategy for storing root and stem water. Deciduous high wood density species are moderately drought tolerant, and evergreen high wood density species are the most drought tolerant group. </span></li> <li><span><i>Synthesis. </i>Our results broadly support the plant functional type framework as a way to understand water use strategies, but also highlight species-level differences. </span></li> </ol>
Data from: Land-use intensification effects on functional properties in tropical plant communities
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Data from: Increased snowfall weakens complementarity of summer water use by different plant functional groups
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Data from: Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits
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Data from: Land use intensity indirectly affects ecosystem services mainly through plant functional identity in a temperate forest
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Data from: Plant functional types broadly describe water use strategies in the Caatinga, a seasonally dry tropical forest in northeast Brazil
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Data from: Using plant functional distances to select species for restoration of mining sites
1. Plant facilitation, an ecological interaction that benefits at least one species without harming the other, is increasingly used as a restoration tool. To restore degraded habitats under a facilitation framework, practitioners must correctly select both the benefactor (nurse) and the beneficiary (facilitated) species. 2. Based on community assembly and species coexistence theory, we propose selecting plant species that largely differ in a suite of functional traits so that competition is minimized and facilitation maximized due to functional complementarity. To apply this guideline in a pilot restoration experiment performed in metalliferous mine tailings in South-Eastern Spain, we first built the plant-plant facilitative interaction network naturally occurring in a set of 12 tailings. After characterizing each species with 20 morphological and physiological traits, we verified that facilitative interactions were predominantly established between functionally distant species. 3. Then, we designed a sowing experiment combining 50 nurse-facilitated species pairs separated by a wide range of functional distances. The success of seedling establishment significantly increased with the functional distance between the nurse and the facilitated plant species. 4. Synthesis and applications. We encourage to use ecological facilitation together with trait-based species selection to design restoration programmes based on the principle of increasing functional distance between target species. This method may not only promote the restoration of the plant cover but also impact paramount ecosystem functions, thus being an efficient low cost restoration practice in abiotically stressful ecosystems.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.