MuSCA: a multi-scale model to explore carbon allocation in plants

ABSTRACTBackground and aimsCarbon allocation in plants is usually represented at a specific spatial scale, peculiar to each model. This makes the results obtained by different models, and the impact of their scale of representation, difficult to compare. In this work we developed a Multi Scale Carbon Allocation model (MuSCA) that can be applied at different, user-defined, topological scales of a plant, and used to assess the impact of each spatial scale on simulated results and computation time.MethodsModel multi-scale consistency and behavior were tested by applications on three realistic apple tree structures. Carbon allocation was computed at five spatial scales, spanning from the metamer (the finest scale, used as a reference) up to 1st order branches, and for different values of a sap friction coefficient. Fruit dry mass increments were compared across spatial scales and with field data.Key ResultsThe model showed physiological coherence in representing competition for carbon assimilates. Results from intermediate values of the friction parameter best fitted the field data. For these, fruit growth simulated at the metamer scale (considered as a reference) differed from about 1% at growth unit scale up to 35% at first order branch scale. Generally, the coarser the spatial scale the more fruit growth diverged from the reference and the lower the obtained within-tree fruit growth variability. Coherence in the carbon allocated across scales was also differently impacted, depending on the tree structure considered. Decreasing the topological resolution reduced computation time up to four orders of magnitude.ConclusionsMuSCA revealed that the topological scale has a major influence on the simulation of carbon allocation, suggesting that this factor should be carefully evaluated when using different carbon allocation models or comparing their results. Trades-off between computation time and prediction accuracy can be evaluated by changing topological scales.

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MuSCA: a multi-scale source–sink carbon allocation model to explore carbon allocation in plants. An application to static apple tree structures

Annals of Botany ◽

10.1093/aob/mcz122 ◽

2019 ◽

Vol 126 (4) ◽

pp. 571-585 ◽

Cited By ~ 2

Author(s):

F Reyes ◽

B Pallas ◽

C Pradal ◽

F Vaggi ◽

D Zanotelli ◽

...

Keyword(s):

Field Data ◽

Apple Tree ◽

Carbon Allocation ◽

Computation Time ◽

Fruit Growth ◽

Allocation Model ◽

Tree Structures ◽

First Order ◽

Multi Scale ◽

The Impact

Abstract Background and aims Carbon allocation in plants is usually represented at a topological scale, specific to each model. This makes the results obtained with different models, and the impact of their scales of representation, difficult to compare. In this study, we developed a multi-scale carbon allocation model (MuSCA) that allows the use of different, user-defined, topological scales of a plant, and assessment of the impact of each spatial scale on simulated results and computation time. Methods Model multi-scale consistency and behaviour were tested on three realistic apple tree structures. Carbon allocation was computed at five scales, spanning from the metamer (the finest scale, used as a reference) up to first-order branches, and for different values of a sap friction coefficient. Fruit dry mass increments were compared across spatial scales and with field data. Key Results The model was able to represent effects of competition for carbon assimilates on fruit growth. Intermediate friction parameter values provided results that best fitted field data. Fruit growth simulated at the metamer scale differed of ~1 % in respect to results obtained at growth unit scale and up to 60 % in respect to first order branch and fruiting unit scales. Generally, the coarser the spatial scale the more predicted fruit growth diverged from the reference. Coherence in fruit growth across scales was also differentially impacted, depending on the tree structure considered. Decreasing the topological resolution reduced computation time by up to four orders of magnitude. Conclusions MuSCA revealed that the topological scale has a major influence on the simulation of carbon allocation. This suggests that the scale should be a factor that is carefully evaluated when using a carbon allocation model, or when comparing results produced by different models. Finally, with MuSCA, trade-off between computation time and prediction accuracy can be evaluated by changing topological scales.

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8-Day and Daily Maximum and Minimum Air Temperature Estimation via Machine Learning Method on a Climate Zone to Global Scale

Remote Sensing ◽

10.3390/rs13122355 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2355

Author(s):

Linglin Zeng ◽

Yuchao Hu ◽

Rui Wang ◽

Xiang Zhang ◽

Guozhang Peng ◽

...

Keyword(s):

Spatial Scale ◽

Air Temperature ◽

Spatial Scales ◽

Model Performance ◽

Global Scale ◽

Scale Model ◽

Validation Dataset ◽

Daily Maximum ◽

Climate Zone ◽

Temporal And Spatial

Air temperature (Ta) is a required input in a wide range of applications, e.g., agriculture. Land Surface Temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) are widely used to estimate Ta. Previous studies of these products in Ta estimation, however, were generally applied in small areas and with a small number of meteorological stations. This study designed both temporal and spatial experiments to estimate 8-day and daily maximum and minimum Ta (Tmax and Tmin) on three spatial scales: climate zone, continental and global scales from 2009 to 2018, using the Random Forest (RF) method based on MODIS LST products and other auxiliary data. Factors contributing to the relation between LST and Ta were determined based on physical models and equations. Temporal and spatial experiments were defined by the rules of dividing the training and validation datasets for the RF method, in which the stations selected in the training dataset were all included or not in the validation dataset. The RF model was first trained and validated on each spatial scale, respectively. On a global scale, model accuracy with a determination coefficient (R2) > 0.96 and root mean square error (RMSE) < 1.96 °C and R2 > 0.95 and RMSE < 2.55 °C was achieved for 8-day and daily Ta estimations, respectively, in both temporal and spatial experiments. Then the model was trained and cross-validated on each spatial scale. The results showed that the data size and station distribution of the study area were the main factors influencing the model performance at different spatial scales. Finally, the spatial patterns of the model performance and variable importance were analyzed. Both daytime and nighttime LST had a significant contribution in the 8-day Tmax estimation on all the three spatial scales; while their contribution in daily Tmax estimation varied over different continents or climate zones. This study was expected to improve our understanding of Ta estimation in terms of accuracy variations and influencing variables on different spatial and temporal scales. The future work mainly includes identifying underlying mechanisms of estimation errors and the uncertainty sources of Ta estimation from a local to a global scale.

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Multi-Scale Numerical Analysis of the Field Efficiency of an Ocean Plastic Cleanup Array

Volume 2: CFD and VIV ◽

10.1115/omae2016-54926 ◽

2016 ◽

Author(s):

Bruno Sainte-Rose ◽

Laurent Lebreton ◽

Joao de Lima Rego ◽

Frank Kleissen ◽

Julia Reisser

Keyword(s):

Global Economy ◽

Spatial Scales ◽

Target Area ◽

Japanese Island ◽

Plastic Pollution ◽

Plastic Debris ◽

Multi Scale ◽

Effective Manner ◽

Field Efficiency ◽

The Impact

The impact of plastic pollution on marine ecosystems and global economy has been drawing public concern since the end of the 20th century. To mitigate this issue, The Ocean Cleanup (TOC) Foundation is developing technologies to extract, prevent, and intercept plastic debris from coastal and oceanic environments. The core technology being optimized is the use of floating booms placed perpendicular to the main ocean plastic flow so it can concentrate plastic debris to a point where it can be extracted, shipped and processed in a cost-effective manner. In order to optimize the system’s field efficiency (i.e. mass of ocean plastic captured per length of floating boom), a multi-scale approach has been elaborated, where temporal and spatial scales span over several orders of magnitude. Here we introduce this general multi-scale method alongside its assumptions and multi-scale models. We then describe two application examples, the first corresponding to our coastal pilot in the Japanese island of Tsushima and the second related to our main cleanup target area: the so-called Great Pacific Garbage Patch, situated between Hawaii and the US west coast.

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A multi-scale model to explore carbon allocation in plants

Acta Horticulturae ◽

10.17660/actahortic.2017.1160.41 ◽

2017 ◽

pp. 285-292 ◽

Cited By ~ 2

Author(s):

F. Reyes ◽

D. Gianelle ◽

B. Pallas ◽

E. Costes ◽

C. Pradal ◽

...

Keyword(s):

Carbon Allocation ◽

Scale Model ◽

Multi Scale

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Quantification of Myocyte Disarray in Human Cardiac Tissue

Frontiers in Physiology ◽

10.3389/fphys.2021.750364 ◽

2021 ◽

Vol 12 ◽

Author(s):

Francesco Giardini ◽

Erica Lazzeri ◽

Giulia Vitale ◽

Cecilia Ferrantini ◽

Irene Costantini ◽

...

Keyword(s):

Spatial Scale ◽

Cardiac Tissue ◽

Spatial Scales ◽

Three Dimensional ◽

Structural Data ◽

Multi Scale ◽

Tissue Organization ◽

Human Cardiac Tissue ◽

Microscopy Techniques ◽

Scale Of Analysis

Proper three-dimensional (3D)-cardiomyocyte orientation is important for an effective tension production in cardiac muscle. Cardiac diseases can cause severe remodeling processes in the heart, such as cellular misalignment, that can affect both the electrical and mechanical functions of the organ. To date, a proven methodology to map and quantify myocytes disarray in massive samples is missing. In this study, we present an experimental pipeline to reconstruct and analyze the 3D cardiomyocyte architecture in massive samples. We employed tissue clearing, staining, and advanced microscopy techniques to detect sarcomeres in relatively large human myocardial strips with micrometric resolution. Z-bands periodicity was exploited in a frequency analysis approach to extract the 3D myofilament orientation, providing an orientation map used to characterize the tissue organization at different spatial scales. As a proof-of-principle, we applied the proposed method to healthy and pathologically remodeled human cardiac tissue strips. Preliminary results suggest the reliability of the method: strips from a healthy donor are characterized by a well-organized tissue, where the local disarray is log-normally distributed and slightly depends on the spatial scale of analysis; on the contrary, pathological strips show pronounced tissue disorganization, characterized by local disarray significantly dependent on the spatial scale of analysis. A virtual sample generator is developed to link this multi-scale disarray analysis with the underlying cellular architecture. This approach allowed us to quantitatively assess tissue organization in terms of 3D myocyte angular dispersion and may pave the way for developing novel predictive models based on structural data at cellular resolution.

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The adaptive value of habitat preferences from a multi-scale spatial perspective: insights from marsh-nesting avian species

PeerJ ◽

10.7717/peerj.3164 ◽

2017 ◽

Vol 5 ◽

pp. e3164 ◽

Cited By ~ 8

Author(s):

Jan Jedlikowski ◽

Mattia Brambilla

Keyword(s):

Habitat Selection ◽

Spatial Scales ◽

Habitat Preferences ◽

Nest Survival ◽

Scale Model ◽

Vegetation Density ◽

Multi Scale ◽

Adaptive Value ◽

Single Scale ◽

Scale Models

BackgroundHabitat selection and its adaptive outcomes are crucial features for animal life-history strategies. Nevertheless, congruence between habitat preferences and breeding success has been rarely demonstrated, which may result from the single-scale evaluation of animal choices. As habitat selection is a complex multi-scale process in many groups of animal species, investigating adaptiveness of habitat selection in a multi-scale framework is crucial. In this study, we explore whether habitat preferences acting at different spatial scales enhance the fitness of bird species, and check the appropriateness of single vs. multi-scale models. We expected that variables found to be more important for habitat selection at individual scale(s), would coherently play a major role in affecting nest survival at the same scale(s).MethodsWe considered habitat preferences of two Rallidae species, little crake (Zapornia parva) and water rail (Rallus aquaticus), at three spatial scales (landscape, territory, and nest-site) and related them to nest survival. Single-scale versus multi-scale models (GLS and glmmPQL) were compared to check which model better described adaptiveness of habitat preferences. Consistency between the effect of variables on habitat selection and on nest survival was checked to investigate their adaptive value.ResultsIn both species, multi-scale models for nest survival were more supported than single-scale ones. In little crake, the multi-scale model indicated vegetation density and water depth at the territory scale, as well as vegetation height at nest-site scale, as the most important variables. The first two variables were among the most important for nest survival and habitat selection, and the coherent effects suggested the adaptive value of habitat preferences. In water rail, the multi-scale model of nest survival showed vegetation density at territory scale and extent of emergent vegetation within landscape scale as the most important ones, although we found a consistent effect with the habitat selection model (and hence evidence for adaptiveness) only for the former.DiscussionOur work suggests caution when interpreting adaptiveness of habitat preferences at a single spatial scale because such an approach may under- or over-estimate the importance of habitat factors. As an example, we found evidence only for a weak effect of water depth at territory scale on little crake nest survival; however, according to the multi-scale analysis, such effect turned out to be important and appeared highly adaptive. Therefore, multi-scale approaches to the study of adaptive explanations for habitat selection mechanisms should be promoted.

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Spatial Scale Dependence of Ecological Factors That Regulate Functional and Phylogenetic Assembly in a Mediterranean High Mountain Grassland

Frontiers in Ecology and Evolution ◽

10.3389/fevo.2021.622148 ◽

2021 ◽

Vol 9 ◽

Author(s):

David S. Pescador ◽

Francesco de Bello ◽

Jesús López-Angulo ◽

Fernando Valladares ◽

Adrián Escudero

Keyword(s):

Global Warming ◽

Organic Carbon ◽

Spatial Scale ◽

Community Assembly ◽

Species Interactions ◽

Species Turnover ◽

Spatial Scales ◽

Ecological Factors ◽

Functional Heterogeneity ◽

Multi Scale

Understanding how functional and phylogenetic patterns vary among scales and along ecological gradients within a given species pool is critical for inferring community assembly processes. However, we lack a clear understanding of these patterns in stressful habitats such as Mediterranean high mountains where ongoing global warming is expected to affect species fitness and species interactions, and subsequently species turnover. In this study, we investigated 39 grasslands with the same type of plant community and very little species turnover across an elevation gradient above the treeline at Sierra de Guadarrama National Park in central Spain. In particular, we assessed functional and phylogenetic patterns, including functional heterogeneity, using a multi-scale approach (cells, subplots, and plots) and determined the relevance of key ecological factors (i.e., elevation, potential solar radiation, pH, soil organic carbon, species richness, and functional heterogeneity) that affect functional and phylogenetic patterns at each spatial scale. Overall, at the plot scale, coexisting species tended to be more functionally and phylogenetically similar. By contrast, at the subplot and cell scales, species tended to be more functionally different but phylogenetically similar. Functional heterogeneity at the cell scale was comparable to the variation across plots along the gradient. The relevance of ecological factors that regulate diversity patterns varied among spatial scales. An increase in elevation resulted in functional clustering at larger scales and phylogenetic overdispersion at a smaller scale. The soil pH and organic carbon levels exhibited complex functional patterns, especially at small spatial scales, where an increase in pH led to clustering patterns for the traits related to the leaf economic spectrum (i.e., foliar thickness, specific leaf area, and leaf dry matter content). Our findings confirm the presence of primary environmental filters (coldness and summer drought at our study sites) that constrain the regional species pool, suggesting the presence of additional assembly mechanisms that act at the smallest scale (e.g., micro-environmental gradients and/or species interactions). Functional and phylogenetic relatedness should be determined using a multi-scale approach to help interpret community assembly processes and understand the initial community responses to environmental changes, including ongoing global warming.

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Iterative guided image fusion

PeerJ Computer Science ◽

10.7717/peerj-cs.80 ◽

2016 ◽

Vol 2 ◽

pp. e80 ◽

Cited By ~ 11

Author(s):

Alexander Toet

Keyword(s):

Image Fusion ◽

Spatial Scale ◽

Spatial Scales ◽

Small Scale ◽

Computationally Efficient ◽

Multi Scale ◽

Saliency Maps ◽

Spatial Consistency ◽

Guided Filtering ◽

Fusion Scheme

We propose a multi-scale image fusion scheme based on guided filtering. Guided filtering can effectively reduce noise while preserving detail boundaries. When applied in an iterative mode, guided filtering selectively eliminates small scale details while restoring larger scale edges. The proposed multi-scale image fusion scheme achieves spatial consistency by using guided filtering both at the decomposition and at the recombination stage of the multi-scale fusion process. First, size-selective iterative guided filtering is applied to decompose the source images into approximation and residual layers at multiple spatial scales. Then, frequency-tuned filtering is used to compute saliency maps at successive spatial scales. Next, at each spatial scale binary weighting maps are obtained as the pixelwise maximum of corresponding source saliency maps. Guided filtering of the binary weighting maps with their corresponding source images as guidance images serves to reduce noise and to restore spatial consistency. The final fused image is obtained as the weighted recombination of the individual residual layers and the mean of the approximation layers at the coarsest spatial scale. Application to multiband visual (intensified) and thermal infrared imagery demonstrates that the proposed method obtains state-of-the-art performance for the fusion of multispectral nightvision images. The method has a simple implementation and is computationally efficient.

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Tripping over spatial scales: a comment on Guay et al. (2000)

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f01-148 ◽

2001 ◽

Vol 58 (10) ◽

pp. 2105-2107 ◽

Cited By ~ 5

Author(s):

John G Williams

Keyword(s):

Spatial Scale ◽

Hydrodynamic Model ◽

Field Data ◽

Spatial Scales ◽

Hydrodynamic Modeling ◽

Velocity Fields ◽

Two Dimensional ◽

Biological Models ◽

Habitat Models

Guay et al. (2000.Can.J.Fish.Aquat.Sci.57:20652075) report a test of numerical habitat models (NHMs) that combine two-dimensional hydrodynamic modeling of the depth and velocity fields of a stream reach with simple biological models. The hydrodynamic model was tested with field data from randomly chosen points in the stream, and the overall models were tested with observations of fish in a "verification" section of the stream. This is a proper procedure, but the execution and interpretation of the test seem flawed, largely by a misunderstanding of the spatial scales appropriate. The NHMs used by Guay et al. make predictions for patches or "tiles" at a scale of 125 m2; the hydrodynamic component of the NHMs needs to be tested at the same spatial scale.

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