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107 results for “mechanistic model”
Model and Data for the T&C-CROP Validation Paper: T&C-CROP: Representing mechanistic crop growth with a terrestrial biosphere model (T&C,v1.5): Model formulation and validation.
<p>Here included is the code used to run T&C-CROP as used for the GMD paper submission alongside with the necessary weather data and raw field data used as part of the validation exercise. </p> <p> </p>
The construction of small-scale, quasi-mechanistic spatial models of insect energetics in habitat restoration: a case study of beetles in Western Australia
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Data from: Powerful yet challenging: Mechanistic Niche Models for predicting invasive species potential distribution under climate change
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Data from: Mechanistic home range capture–recapture models for the estimation of population density and landscape connectivity
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Data from: Combined mechanistic modelling predicts changes in species distribution and increased co-occurrence of a tropical urchin herbivore and a habitat-forming temperate kelp
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Understanding complex spatial dynamics from mechanistic models through spatio-temporal point processes
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Worn region size of shoe outsole impacts human slips: Testing a mechanistic model
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Experimental evidence of warming-induced disease emergence and its prediction by a trait-based mechanistic model
<p>Predicting the effects of seasonality and climate change on the emergence and spread of infectious disease remains difficult, in part because of poorly understood connections between warming and the mechanisms driving disease. Trait-based mechanistic models combined with thermal performance curves arising from the Metabolic Theory of Ecology (MTE) have been highlighted as a promising approach going forward; however, this framework has not been tested under controlled experimental conditions that isolate the role of gradual temporal warming on disease dynamics and emergence. Here, we provide experimental evidence that a slowly warming host – parasite system can be pushed through a critical transition into an epidemic state. We then show that a trait-based mechanistic model with MTE functional forms can predict the critical temperature for disease emergence, subsequent disease dynamics through time, and final infection prevalence in an experimentally warmed system of <i>Daphnia </i>and a microsporidian parasite. Our results serve as a proof of principle that trait-based mechanistic models using MTE sub-functions can predict warming-induced disease emergence in data-rich systems – a critical step towards generalizing the approach to other systems.</p>
Data from: Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub-Antarctic insect
<p>Aim</p> <p>Correlative Species Distribution Models (SDMs) are subject to substantial spatio-temporal limitations when historical occurrence records of data-poor species provide incomplete and outdated information for niche modelling. Complementary mechanistic modelling techniques can, therefore, offer a valuable contribution to underpin more physiologically-informed predictions of biological invasions, the risk of which is often exacerbated by climate change. In this study we integrate physiological and human pressure data to address the uncertainties and limitations of correlative SDMs and to better understand, predict, and manage biological invasions.</p> <p>Location</p> <p>Western archipelagos of the Southern Ocean and martime Antarctica</p> <p>Taxon</p> <p>Eretmoptera murphyi (Chironomidae), invertebrates.</p> <p>Methods</p> <p>Mahalanobis Distances were used for correlative SDM construction for a species with few records. A mechanistic SDM was built around different fitness components (larval survival and life stage progression) as a function of temperature. SDM predictions were combined with human activity levels in Antarctica to generate a site vulnerability index to the colonization of E. murphyi. Future scenarios of ecophysiological suitability were built around the warming trends in the region.<br> Results Both SDMs converge to predict high environmental suitability in the species' native and introduced ranges. However, the mechanistic model indicates a slightly larger invasive potential based on larval performance at different temperatures. Human activity levels across the Antarctic Peninsula play a key role in discerning site vulnerabilities. Niche suitability in Antarctica grows considerably under long-term climate scenarios, leading to a substantially higher invasive threat to the Antarctic ecosystems. In turn changing conditions result on growing physiological mismatches with the environment in the native range on South Georgia.</p> <p>Main conclusions</p> <p>Long-term studies of invasion potential under climate benefit from integrating correlative predictions with physiological experiments, as the invasion potential varies depending on the area and the timescale examined. This study also highlights a conservation paradox whereby the accidental introduction of an insect represents a threat to the Antarctic ecoystems that contrasts with its endangered status at the native range.</p>
Data from: A mechanistic and empirically-supported lightning risk model for forest trees
<ol> <li>Tree death due to lightning influences tropical forest carbon cycling and tree community dynamics. However, the distribution of lightning damage among trees in forests remains poorly understood. </li> <li>We developed models to predict direct and secondary lightning damage to trees based on tree size, crown exposure, and local forest structure. We parameterized these models using data on the locations of lightning strikes and censuses of tree damage in strike zones, combined with drone-based maps of tree crowns and censuses of all trees within a 50-ha forest dynamics plot on Barro Colorado Island, Panama. </li> <li>The likelihood of a direct strike to a tree increased with larger exposed crown area and higher relative canopy position (emergent > canopy >>> subcanopy), whereas the likelihood of secondary lightning damage increased with tree diameter and proximity to neighboring trees. The predicted frequency of lightning damage in this mature forest was greater for tree species with larger average diameters.</li> <li>These patterns suggest that lightning influences forest structure and the global carbon budget by nonrandomly damaging large trees. Moreover, these models provide a framework for investigating the ecological and evolutionary consequences of lightning disturbance in tropical forests.</li> </ol> <p><b>Synthesis:</b> Our findings indicate that the distribution of lightning damage is stochastic at large spatial grain and relatively deterministic at smaller spatial grain (<15 m). Lightning is more likely to directly strike taller trees with large crowns and secondarily damage large neighboring trees that are closest to the directly struck tree. The results provide a framework for understanding how lightning can affect forest structure, forest dynamics, and carbon cycling. The resulting lightning risk model will facilitate informed investigations into the effects of lightning in tropical forests.</p>
Data from: Higher rates of pre‐breeding condition gain positively impacts clutch size: a mechanistic test of the condition‐dependent individual optimization model
1. A combination of timing of and body condition (i.e., mass) at arrival on the breeding grounds interact to influence the optimal combination of the timing of reproduction and clutch size in migratory species. This relationship has been formalized by Rowe et al. in a condition-dependent individual optimization model (American Naturalist, 1994, 143, 689-722), which has been empirically tested and validated in avian species with a capital-based breeding strategy. 2. This model makes a key, but currently untested prediction; that variation in the rate of body condition gain will shift the optimal combination of laying date and clutch size. This prediction is essential because it implies that individuals can compensate for the challenges associated with late timing of arrival or poor body condition at arrival on the breeding grounds through adjustment of their life history investment decisions, in an attempt to maximize fitness. 3. Using an 11-year data set in arctic-nesting common eiders (Somateria mollissima), quantification of fattening rates using plasma triglycerides (an energetic metabolite), and a path analysis approach, we test this prediction of this optimization model; controlling for arrival date and body condition, females that fatten more quickly will adjust the optimal combination of lay date and clutch size, in favour of a larger clutch size. 4. As predicted, females fattening at higher rates initiated clutches earlier and produced larger clutch sizes, indicating that fattening rate is an important factor in addition to arrival date and body condition in predicting individual variation in reproductive investment. However, there was no direct effect of fattening rate on clutch size (i.e., birds laying on the same date had similar clutch sizes, independent of their fattening rate). Instead, fattening rate indirectly affected clutch size via earlier lay dates, thus not supporting the original predictions of the optimization model. 5. Our results demonstrate that variation in the rate of condition gain allows individuals to shift flexibly along the seasonal decline in clutch size to presumably optimize the combination of laying date and clutch size.
Mechanistic insights into silver-gold nanoalloy formation by two-dimensional population balance modeling
<p>This is the raw data for the manuscript:</p><p>Mechanistic insights into silver-gold nanoalloy formation by two-dimensional population balance modeling<br><br>Abstract:<br><br>The large-scale synthesis of nanoparticles (NPs) with defined properties requires detailed understanding of the underlying formation mechanisms and kinetics. The formation mechanisms of bimetallic NPs are still not sufficiently understood due to the complex reaction chemistry, which makes the control of the supersaturation within the reactor, as the thermodynamic driving force, challenging. Particle size, chemical composition, and the distribution of the elements within the particles change dynamically during particle formation. In this work, we propose a mechanism for the formation of bimetallic silver-gold alloy NPs via a green liquid-phase co-reduction synthesis and develop a two-dimensional population balance model to quantitatively describe the evolution of particle size, composition, and optical properties. We shed light on the complex multi-stage formation mechanism of a highly relevant bimetallic NP system and lay the foundation for tailoring the process conditions to achieve desired optical particle properties and to develop predictive property-process relationships.</p><p> </p><p>All data are sorted according to their appearance in the figures of the main manuscript.</p>
Supplementary data and code for "A network toxicology approach for mechanistic modelling of nanomaterial hazard and adverse outcomes"
<p>This repository contains the relevant data and code supporting the study "A network toxicology approach for mechanistic modelling of nanomaterial hazard and adverse outcomes". Files are password protected during the revision process. A completely public version of the repository will be availble after the revision process is completed. </p> <p>In detail, the uploaded archive folder contains the following data sources:</p> <ul> <li>the relevant code and supporting data (code_to_upload and supporting_data);</li> <li>supplementary materials of the paper, including: <ul> <li>individual enrichment results of the 93 exposures to the 31 ENMs (enrichments_results);</li> <li>comparison between the mechanism of action retrieved from differentially expressed genes and network modelling (network_comparison_results);</li> <li>overrepresented network edges in categories of networks (overrepresented_structures)</li> </ul> </li> </ul>
Two-pool mechanistic CDOM model for the global ocean
<p>This includes all model inputs, outputs, and scripts to run the model for the paper "Quantifying biogeochemical controls of open ocean CDOM from a global mechanistic model." Currently under review at JGR Oceans.</p>
Investigating solute transport and reaction using a mechanistically coupled geochemical and geophysical modeling approach
<p>This repository encompasses the acquired data for the five experiments of reactive percolation in a column with geoelectrical monitoring. The input and output files of the reactive transport simulations are also given. In addition, five movies of the reaction rate evolving with time are also part of this dataset. The files are:</p> <ul> <li><strong>physicochemical_data.xlsx</strong>: the ionic concentrations, alkalinity, pH, and electrical conductivity from the collected water samples, the pH monitored at two locations in the column, and the inlet and outlet water conductivity and temperature. Porosity and formation factor calculated from the measured calcium concentration are also given.</li> <li><strong>sp-data-exp1-exp2-exp3.xlsx</strong>: the self-potential (SP) method has been used to monitor the reactive percolation for experiments 1, 2, and 3.</li> <li><strong>sip-data-exp4.xlsx </strong>and <strong>sip-data-exp5.xlsx</strong>: the spectral induced polarization (SIP) method has been used to monitor the reactive percolation for experiments 4 and 5.</li> <li><strong>output_exp</strong><em><strong>X</strong></em><strong>.zip</strong>: compressed folders of all output files for the reactive transport simulations using Crunchflow software.</li> <li><strong>1DcalciteFT_ex<em>X</em>.in</strong>: input files for the reactive transport simulation using CrnchFlow software.</li> <li><strong>OldRifleDatabaseLiLi_nicole.dbs</strong>: database for the reactive transport simulation using CrnchFlow software.</li> <li><strong>video-rate-exp</strong><em><strong>X</strong></em><strong>.avi</strong>: movies of the reaction rate along the column and evolving with time for the complete duration of each experiment.</li> </ul>
Fig. 8 Fitness landscape for models 7 and 8 in Modelling sympatric speciation by means of biologically plausible mechanistic processes as exemplified by threespine stickleback species pairs
Fig. 8 Fitness landscape for models 7 and 8. Relative fitness is a function of trait T1 and trait T2. Epistasis is modelled as follows:
Fig. 5 The probability that a female accepts a in Modelling sympatric speciation by means of biologically plausible mechanistic processes as exemplified by threespine stickleback species pairs
Fig. 5 The probability that a female accepts a male as a mate is a function of the morphological difference between them, and her stringency of choosiness S (here T ¼ S þ 0: 25), as in model 4 (variants applied in models 6 and 8). In the figure, 3 values of S are shown; S can have all values that are averages of two allelic values (from 64 or 256 equidistant values from 0 to 1)
Fig. 3 Model 1. a in Modelling sympatric speciation by means of biologically plausible mechanistic processes as exemplified by threespine stickleback species pairs
Fig. 3 Model 1. a Typical initial distribution of the allelic values at generation 0. b Typical distribution of the allelic values at generation 100. c Typical distribution of T, the phenotypic values, at generation 100. Nm = Nf =100; σ =0.25; μ = 1%; n = 256 alleles. Similar results were obtained in 20 out of 20 replicate simulations with σ =0.25, in 13 out of 20 replicate simulations with σ =0.5, and in 0 out of 10 replicate simulations with σ =1
Fig. 6 Model 4 in Modelling sympatric speciation by means of biologically plausible mechanistic processes as exemplified by threespine stickleback species pairs
Fig. 6 Model 4: Reinforcement of stringency of assortative mating. Columns: 1 Typical distribution of morphology alleles; 2 typical distribution of morphology phenotypes T; 3 typical distribution of stringency of choosiness alleles. Rows: 1 Generation 0, 2 generation
Mechanistic Study of Ethanol Decomposition on Co3O4(111) and Pd/Co3O4(111) Model Catalysts
<p>SRPES, NAP-XPS, and TPD data for ethanol adsorption and decomposition on Co3O4(111) and pd/Co3O4.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.