scholarly journals Simulating migration in dynamic vegetation models efficiently with LPJ-GM

2018 ◽  
Author(s):  
Veiko Lehsten ◽  
Michael Mischurow ◽  
Erik Lindström ◽  
Dörte Lehsten ◽  
Heike Lischke
Keyword(s):  
Large Scale ◽  
Grid Cells ◽  
Computationally Efficient ◽  
Climate Conditions ◽  
Small Areas ◽  
Seed Supply ◽  
Post Process ◽  
Seed Dispersal Kernel ◽  
Vegetation Models ◽  
And Migration

Abstract. Dynamic vegetation models are a common tool to assess the effect of climate and land use change on vegetation. While the current development aims to include more processes, e.g. the nitrogen cycle, the models still typically assume an ample seed supply allowing all species to establish once the climate conditions are suitable. A number of species have been shown to lag behind in occupying climatological suitable areas (e.g. after a change in the climate) as they need to arrive and establish at the newly suitable areas. Previous attempts to implement migration in dynamic vegetation models have allowed simulating either only small areas or have been implemented as post process, not allowing for feedbacks within the vegetation. Here we present two novel methods simulating migrating and interacting tree species which have the potential to be used for continental simulations. Both distribute seeds between grid cells leading to individual establishment. The first method uses an approach based on Fast Fourier transform while in the second approach we iteratively shift the seed production matrix and disperse seeds with a given probability. While the former method is computationally marginally faster, it does not allow for modification of the seed dispersal kernel parameters with respect to terrain features, which the latter method allows. We evaluate the increase in computational demand of both methods. Since dispersal acts at a scale no larger than 1 km, all dispersal simulations need to be performed at least at that scale. However, with the current available computational power it is not feasible to simulate the vegetation dynamics of a whole continent at that scale. We present an option to decrease the required computational costs, reducing the number of grid cells where the local dynamics is computed by simulating it only along migration transects. Evaluation of species patterns and migration speeds shows that although the simulation along transects reduces the migration speed slightly, both methods are reliable. Furthermore, both methods are sufficiently computationally efficient to allow large scale DGVM simulations with migration on entire continents.

scholarly journals LPJ-GM 1.0: simulating migration efficiently in a dynamic vegetation model

2019 ◽  
Vol 12 (3) ◽  
pp. 893-908 ◽  
Author(s):  
Veiko Lehsten ◽  
Michael Mischurow ◽  
Erik Lindström ◽  
Dörte Lehsten ◽  
Heike Lischke
Keyword(s):  
Large Scale ◽  
Fourier Transforms ◽  
Grid Cells ◽  
Large Area ◽  
Climate Conditions ◽  
Small Areas ◽  
Seed Supply ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation

Abstract. Dynamic global vegetation models are a common tool to assess the effect of climate and land use change on vegetation. Though most applications of dynamic global vegetation models use plant functional types, some also simulate species occurrences. While the current development aims to include more processes, e.g. the nitrogen cycle, the models still typically assume an ample seed supply allowing all species to establish once the climate conditions are suitable. Pollen studies have shown that a number of plant species lag behind in occupying climatological suitable areas (e.g. after a change in the climate) as they need to arrive at and establish in the newly suitable areas. Previous attempts to implement migration in dynamic vegetation models have allowed for the simulation of either only small areas or have been implemented as a post-process, not allowing for feedbacks within the vegetation. Here we present two novel methods simulating migrating and interacting tree species which have the potential to be used for simulations of large areas. Both distribute seeds between grid cells, leading to individual establishment. The first method uses an approach based on fast Fourier transforms, while in the second approach we iteratively shift the seed production matrix and disperse seeds with a given probability. While the former method is computationally faster, it does not allow for modification of the seed dispersal kernel parameters with respect to terrain features, which the latter method allows. We evaluate the increase in computational demand of both methods. Since dispersal acts at a scale no larger than 1 km, all dispersal simulations need to be performed at maximum at that scale. However, with the currently available computational power it is not feasible to simulate the local vegetation dynamics of a large area at that scale. We present an option to decrease the required computational costs through a reduction in the number of grid cells for which the local dynamics are simulated only along migration transects. Evaluation of species patterns and migration speeds shows that simulating along transects reduces migration speed, and both methods applied on the transects produce reasonable results. Furthermore, using the migration transects, both methods are sufficiently computationally efficient to allow for large-scale DGVM simulations with migration.

scholarly journals S2P3-R v2.0: computationally efficient modelling of shelf seas on regional to global scales

2021 ◽  
Author(s):  
Paul R. Halloran ◽  
Jennifer K. McWhorter ◽  
Beatriz Arellano Nava ◽  
Robert Marsh ◽  
William Skirving
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Climate Projections ◽  
Grid Cells ◽  
Computationally Efficient ◽  
Global Models ◽  
Shelf Seas ◽  
Shelf Sea

Abstract. The marine impacts of climate change on our societies will be largely felt through coastal waters and shelf seas. These impacts involve sectors as diverse as tourism, fisheries and energy production. Projections of future marine climate change come from global models. Modelling at the global scale is required to capture the feedbacks and large-scale transport of physical properties such as heat, which occur within the climate system, but global models currently cannot provide detail in the shelf-seas. Version 2 of the regional implementation of the Shelf Sea Physics and Primary Production (S2P3-R v2.0) model bridges the gap between global projections and local shelf-sea impacts. S2P3-R v2.0 is a highly simplified coastal shelf model, computationally efficient enough to be run across the shelf seas of the whole globe. Despite the simplified nature of the model, it can display regional skill comparable to state-of-the-art models, and at the scale of the global (excluding high-latitudes) shelf-seas can explain > 50 % of the interannual SST variability in ~60 % of grid cells, and > 80 % of interannual variability in ~20 % of grid cells. The model can be run at any resolution for which the input data can be supplied, without expert technical knowledge, and using a modest off-the-shelf computer. The accessibility of S2P3-R v2.0 places it within reach of an array of coastal managers and policy makers. S2P3-R v2.0 is set up to be driven directly with output from reanalysis products or daily atmospheric output from climate models such as those which contribute to the 6th phase of the Climate Model Intercomparison Project, making it a valuable tool for semi-dynamical downscaling of climate projections. The updates introduced into version 2.0 of this model are primarily focused around the ability to geographical relocate the model, model usability and speed, but also scientific improvements. The value of this model comes from its computational efficiency, which necessitates simplicity. This simplicity leads to several limitations, which are discussed in the context of evaluation at regional and global scales.

scholarly journals Efficient modeling of sun/shade canopy radiation dynamics explicitly accounting for scattering

2011 ◽  
Vol 4 (3) ◽  
pp. 1793-1808
Author(s):  
P. Bodin ◽  
O. Franklin
Keyword(s):  
Large Scale ◽  
Gross Primary Production ◽  
Global Radiation ◽  
Diffuse Radiation ◽  
Computationally Efficient ◽  
Radiation Scattering ◽  
Radiation Model ◽  
3 Dimensional ◽  
Plant Photosynthesis ◽  
Vegetation Models

Abstract. The separation of global radiation (Rg) into its direct (Rb) and diffuse constituents (Rd) is important when modeling plant photosynthesis because a high Rd:Rg ratio has been shown to enhance Gross Primary Production (GPP). To include this effect in vegetation models, the plant canopy must be separated into sunlit and shaded leaves, for example using an explicit 3-dimensional ray tracing model. However, because such models are often too intractable and computationally expensive for theoretical or large scale studies simpler sun-shade approaches are often preferred. A widely used and computationally efficient sun-shade model is a model originally developed by Goudriaan (1977) (GOU), which however does not explicitly account for radiation scattering. Here we present a new model based on the GOU model, but which in contrast explicitly simulates radiation scattering by sunlit leaves and the absorption of this radiation by the canopy layers above and below (2-stream approach). Compared to the GOU model our model predicts significantly different profiles of scattered radiation that are in better agreement with measured profiles of downwelling diffuse radiation. With respect to these data our model's performance is equal to a more complex and much slower iterative radiation model while maintaining the simplicity and computational efficiency of the GOU model.

scholarly journals Efficient modeling of sun/shade canopy radiation dynamics explicitly accounting for scattering

2012 ◽  
Vol 5 (2) ◽  
pp. 535-541 ◽  
Author(s):  
P. Bodin ◽  
O. Franklin
Keyword(s):  
Large Scale ◽  
Gross Primary Production ◽  
Global Radiation ◽  
Diffuse Radiation ◽  
Computationally Efficient ◽  
Radiation Scattering ◽  
Radiation Model ◽  
Complex Models ◽  
Plant Photosynthesis ◽  
Vegetation Models

Abstract. The separation of global radiation (Rg) into its direct (Rb) and diffuse constituents (Rg) is important when modeling plant photosynthesis because a high Rd:Rg ratio has been shown to enhance Gross Primary Production (GPP). To include this effect in vegetation models, the plant canopy must be separated into sunlit and shaded leaves. However, because such models are often too intractable and computationally expensive for theoretical or large scale studies, simpler sun-shade approaches are often preferred. A widely used and computationally efficient sun-shade model was developed by Goudriaan (1977) (GOU). However, compared to more complex models, this model's realism is limited by its lack of explicit treatment of radiation scattering. Here we present a new model based on the GOU model, but which in contrast explicitly simulates radiation scattering by sunlit leaves and the absorption of this radiation by the canopy layers above and below (2-stream approach). Compared to the GOU model our model predicts significantly different profiles of scattered radiation that are in better agreement with measured profiles of downwelling diffuse radiation. With respect to these data our model's performance is equal to a more complex and much slower iterative radiation model while maintaining the simplicity and computational efficiency of the GOU model.

Cloud-Based Multimedia Content Protection System

2020 ◽  
pp. 164-169
Author(s):  
B. Aparna ◽  
S. Madhavi ◽  
G. Mounika ◽  
P. Avinash ◽  
S. Chakravarthi
Keyword(s):  
Large Scale ◽  
Protection System ◽  
Multimedia Content ◽  
Computationally Efficient ◽  
Content Protection ◽  
Protection Systems ◽  
Multimedia Content Protection ◽  
High Scalability ◽  
Cloud Infrastructures ◽  
Rapid Deployment

We propose a new design for large-scale multimedia content protection systems. Our design leverages cloud infrastructures to provide cost efficiency, rapid deployment, scalability, and elasticity to accommodate varying workloads. The proposed system can be used to protect different multimedia content types, including videos, images, audio clips, songs, and music clips. The system can be deployed on private and/or public clouds. Our system has two novel components: (i) method to create signatures of videos, and (ii) distributed matching engine for multimedia objects. The signature method creates robust and representative signatures of videos that capture the depth signals in these videos and it is computationally efficient to compute and compare as well as it requires small storage. The distributed matching engine achieves high scalability and it is designed to support different multimedia objects. We implemented the proposed system and deployed it on two clouds: Amazon cloud and our private cloud. Our experiments with more than 11,000 videos and 1 million images show the high accuracy and scalability of the proposed system. In addition, we compared our system to the protection system used by YouTube and our results show that the YouTube protection system fails to detect most copies of videos, while our system detects more than 98% of them.

scholarly journals GIANA allows computationally-efficient TCR clustering and multi-disease repertoire classification by isometric transformation

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hongyi Zhang ◽  
Xiaowei Zhan ◽  
Bo Li
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Large Scale ◽  
Cell Receptor ◽  
Alignment Algorithm ◽  
Computationally Efficient ◽  
Antigen Specificity ◽  
Non Invasive ◽  
Isometric Transformation ◽  
Specific Receptors

AbstractSimilarity in T-cell receptor (TCR) sequences implies shared antigen specificity between receptors, and could be used to discover novel therapeutic targets. However, existing methods that cluster T-cell receptor sequences by similarity are computationally inefficient, making them impractical to use on the ever-expanding datasets of the immune repertoire. Here, we developed GIANA (Geometric Isometry-based TCR AligNment Algorithm) a computationally efficient tool for this task that provides the same level of clustering specificity as TCRdist at 600 times its speed, and without sacrificing accuracy. GIANA also allows the rapid query of large reference cohorts within minutes. Using GIANA to cluster large-scale TCR datasets provides candidate disease-specific receptors, and provides a new solution to repertoire classification. Querying unseen TCR-seq samples against an existing reference differentiates samples from patients across various cohorts associated with cancer, infectious and autoimmune disease. Our results demonstrate how GIANA could be used as the basis for a TCR-based non-invasive multi-disease diagnostic platform.

scholarly journals Social Media in and Around a Temporary Large-Scale Refugee Shelter in the Netherlands

2021 ◽  
Vol 7 (2) ◽  
pp. 205630512110249
Author(s):  
Peer Smets ◽  
Younes Younes ◽  
Marinka Dohmen ◽  
Kees Boersma ◽  
Lenie Brouwer
Keyword(s):  
Social Media ◽  
The Netherlands ◽  
Crisis Communication ◽  
Asylum Seekers ◽  
Large Scale ◽  
State Policies ◽  
Refugee Crisis ◽  
Top Down ◽  
And Migration

During the 2015 refugee crisis in Europe, temporary refugee shelters arose in the Netherlands to shelter the large influx of asylum seekers. The largest shelter was located in the eastern part of the country. This shelter, where tents housed nearly 3,000 asylum seekers, was managed with a firm top-down approach. However, many residents of the shelter—mainly Syrians and Eritreans—developed horizontal relations with the local receiving society, using social media to establish contact and exchange services and goods. This case study shows how various types of crisis communication played a role and how the different worlds came together. Connectivity is discussed in relation to inclusion, based on resilient (non-)humanitarian approaches that link society with social media. Moreover, we argue that the refugee crisis can be better understood by looking through the lens of connectivity, practices, and migration infrastructure instead of focusing only on state policies.

scholarly journals Prevalence and genetic diversity of avian haemosporidian parasites in wild bird species of the order Columbiformes

2021 ◽  
Author(s):  
Yvonne R. Schumm ◽  
Dimitris Bakaloudis ◽  
Christos Barboutis ◽  
Jacopo G. Cecere ◽  
Cyril Eraud ◽  
...  
Keyword(s):  
Host Species ◽  
Large Scale ◽  
Phylogenetic Reconstruction ◽  
Bird Species ◽  
Avian Species ◽  
Blood Parasites ◽  
Migration Strategy ◽  
Haemosporidian Parasites ◽  
Multiplex Pcr Assay ◽  
And Migration

AbstractDiseases can play a role in species decline. Among them, haemosporidian parasites, vector-transmitted protozoan parasites, are known to constitute a risk for different avian species. However, the magnitude of haemosporidian infection in wild columbiform birds, including strongly decreasing European turtle doves, is largely unknown. We examined the prevalence and diversity of haemosporidian parasites Plasmodium, Leucocytozoon and subgenera Haemoproteus and Parahaemoproteus in six species of the order Columbiformes during breeding season and migration by applying nested PCR, one-step multiplex PCR assay and microscopy. We detected infections in 109 of the 259 screened individuals (42%), including 15 distinct haemosporidian mitochondrial cytochrome b lineages, representing five H. (Haemoproteus), two H. (Parahaemoproteus), five Leucocytozoon and three Plasmodium lineages. Five of these lineages have never been described before. We discriminated between single and mixed infections and determined host species-specific prevalence for each parasite genus. Observed differences among sampled host species are discussed with reference to behavioural characteristics, including nesting and migration strategy. Our results support previous suggestions that migratory birds have a higher prevalence and diversity of blood parasites than resident or short-distance migratory species. A phylogenetic reconstruction provided evidence for H. (Haemoproteus) as well as H. (Parahaemoproteus) infections in columbiform birds. Based on microscopic examination, we quantified parasitemia, indicating the probability of negative effects on the host. This study provides a large-scale baseline description of haemosporidian infections of wild birds belonging to the order Columbiformes sampled in the northern hemisphere. The results enable the monitoring of future changes in parasite transmission areas, distribution and diversity associated with global change, posing a potential risk for declining avian species as the European turtle dove.

An Efficient Preconditioner for Linear System Solution in Multi-Domain Modeling of the Circulatory System

2013 ◽  
Author(s):  
Mahdi Esmaily Moghadam ◽  
Yuri Bazilevs ◽  
Tain-Yen Hsia ◽  
Alison Marsden
Keyword(s):  
Strong Coupling ◽  
Large Scale ◽  
Computational Cost ◽  
Circulatory System ◽  
Flow Simulation ◽  
Global Dynamics ◽  
Domain Modeling ◽  
Computationally Efficient ◽  
Lumped Parameter ◽  
System Solution

A closed-loop lumped parameter network (LPN) coupled to a 3D domain is a powerful tool that can be used to model the global dynamics of the circulatory system. Coupling a 0D LPN to a 3D CFD domain is a numerically challenging problem, often associated with instabilities, extra computational cost, and loss of modularity. A computationally efficient finite element framework has been recently proposed that achieves numerical stability without sacrificing modularity [1]. This type of coupling introduces new challenges in the linear algebraic equation solver (LS), producing an strong coupling between flow and pressure that leads to an ill-conditioned tangent matrix. In this paper we exploit this strong coupling to obtain a novel and efficient algorithm for the linear solver (LS). We illustrate the efficiency of this method on several large-scale cardiovascular blood flow simulation problems.

A Low-Fidelity Stochastic Model of Viral Spread in Aircraft to Assess Risk Mitigation Strategies

2021 ◽  
Author(s):  
Leigh McCue
Keyword(s):  
Large Scale ◽  
Risk Mitigation ◽  
Mitigation Strategies ◽  
Traffic Network ◽  
Computationally Efficient ◽  
Passenger Compartment ◽  
Stochastic Effects ◽  
Viral Spread ◽  
Risk Mitigation Strategies ◽  
Baseline Health

Abstract The purpose of this work is to develop a computationally efficient model of viral spread that can be utilized to better understand influences of stochastic factors on a large-scale system - such as the air traffic network. A particle-based model of passengers and seats aboard a single-cabin 737-800 is developed for use as a demonstration of concept on tracking the propagation of a virus through the aircraft's passenger compartment over multiple flights. The model is sufficiently computationally efficient so as to be viable for Monte Carlo simulation to capture various stochastic effects, such as number of passengers, number of initially sick passengers, seating locations of passengers, and baseline health of each passenger. The computational tool is then exercised in demonstration for assessing risk mitigation of intervention strategies, such as passenger-driven cleaning of seating environments and elimination of middle seating.

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