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Journal articles on the topic 'Biophysical modelling'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Yavuz, Mehmet, and Fuat Usta. "Importance of modelling and simulation in biophysical applications." AIMS Biophysics 10, no. 3 (2023): 258–62. http://dx.doi.org/10.3934/biophy.2023017.

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<abstract> <p>Mathematical modelling and simulation in biophysics and its applications in terms of both theoretical and biological/physical/ecological point of view arise in a number of research problems ranging from physical and chemical processes to biomathematics and life science. As known, the modeling of a biophysical system requires the analysis of the different interactions occurring among the different components of the system. This editorial article deals with the topic of this special issue, which is devoted to the new developments in the modelling and simulation in bioph

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Gango, Sergei, Svetlana Pan'kova, Vladimir Solovyev, Alexander Vanin, and Mikhail Yanikov. "TEACHING METHODS IN THE UNIVERSITY COURSE “BIOPHYSICS”." SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference 1 (May 25, 2018): 103. http://dx.doi.org/10.17770/sie2018vol1.3206.

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The article presents some methods and results of experimental teaching biophysics at Pskov State University (Russian Federation). The goal of any university is to train highly qualified specialists. To achieve this aim, the authors suggest following interdisciplinary approach to the educational process. Some topics of the lecture presentations, video clips and demonstration educational experiments as well as examples of computer modelling of biophysical processes are considered. Subjects of the real and virtual biophysical, biological and medical experimental tasks for students working in an e

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3

Dennis, J. A. "Editorial - Biophysical Modelling of Radiation Effects." Radiation Protection Dosimetry 46, no. 2 (1993): 75–78. http://dx.doi.org/10.1093/oxfordjournals.rpd.a081658.

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4

Dahms, Thorsten, Sylvia Seissiger, Christopher Conrad, and Erik Borg. "MODELLING BIOPHYSICAL PARAMETERS OF MAIZE USING LANDSAT 8 TIME SERIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 7, 2016): 171–75. http://dx.doi.org/10.5194/isprs-archives-xli-b2-171-2016.

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Open and free access to multi-frequent high-resolution data (e.g. Sentinel – 2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. <br><br> In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR), the leaf area index (LAI) and t

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Dahms, Thorsten, Sylvia Seissiger, Christopher Conrad, and Erik Borg. "MODELLING BIOPHYSICAL PARAMETERS OF MAIZE USING LANDSAT 8 TIME SERIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 7, 2016): 171–75. http://dx.doi.org/10.5194/isprsarchives-xli-b2-171-2016.

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Open and free access to multi-frequent high-resolution data (e.g. Sentinel – 2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. &lt;br&gt;&lt;br&gt; In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR), the leaf area i

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Jenkins, Meaghan E., Michael Bedward, Owen Price, and Ross A. Bradstock. "Modelling Bushfire Fuel Hazard Using Biophysical Parameters." Forests 11, no. 9 (2020): 925. http://dx.doi.org/10.3390/f11090925.

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Environmental gradients or biophysical parameters such as climate, topography and geology drive landscape-scale vegetation structure, species distribution and productivity. These gradients have the potential to provide detailed, fine-scale spatial prediction of the accumulation of bushfire fuels and hence fire hazard by elucidating patterns in field information in a consistent and repeatable way. Rapid visual assessment of bushfire fuel hazard via ratings provides fire and land management agencies with a measure of the probability of first attack success and general suppression difficulty of b

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Perthame, Benoit, Peter Markowich, and Jorge P. Zubelli. "Mathematical methods and modelling of biophysical phenomena." Mathematical and Computer Modelling 53, no. 7-8 (2011): 1359–62. http://dx.doi.org/10.1016/j.mcm.2010.07.012.

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8

Gérard, J. P., and C. C. Ling. "Biophysical modelling: implications for conformation radiation treatment." Radiotherapy and Oncology 29, no. 2 (1993): 165–66. http://dx.doi.org/10.1016/0167-8140(93)90241-y.

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9

Padarian, J., B. Minasny, and A. B. McBratney. "Online machine learning for collaborative biophysical modelling." Environmental Modelling & Software 122 (December 2019): 104548. http://dx.doi.org/10.1016/j.envsoft.2019.104548.

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10

Holwill, M. E. J., G. F. Foster, T. Hamasaki, and P. Satir. "Biophysical aspects and modelling of ciliary motility." Cell Motility and the Cytoskeleton 32, no. 2 (1995): 114–20. http://dx.doi.org/10.1002/cm.970320209.

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11

Vincze, Janos, and Gabriella Vincze-Tiszay. "The Biophysical Modelling of the Stress Theory." Advances in Social Sciences Research Journal 10, no. 3 (2023): 344–51. http://dx.doi.org/10.14738/assrj.103.14350.

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Selye published a short note about his findings in Nature in 1936. Selye applied his famous theory of stress to everyday life. A stress-free state is equivalent to being dead. In our paper we write about the some directions in stress research and the stress syndromes in clinical medicine. We show that eustress suits to situations when the psychoneuroendocrine stimulation of the organism and its behavior is temperate, maintaining at an optimal level the physical and mental resources and the health status and inducing a positive adaptation to the environment. We give a comparative analysis betwe

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12

Vincze, Janos. "The Biophysical Modelling of the Human-time." American Journal of Biomedical Science & Research 19, no. 6 (2023): 729–32. http://dx.doi.org/10.34297/ajbsr.2023.19.002644.

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13

Hinrichsen, Hans-Harald, Mark Dickey-Collas, Martin Huret, Myron A. Peck, and Frode B. Vikebø. "Evaluating the suitability of coupled biophysical models for fishery management." ICES Journal of Marine Science 68, no. 7 (2011): 1478–87. http://dx.doi.org/10.1093/icesjms/fsr056.

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Abstract Hinrichsen, H-H., Dickey-Collas, M., Huret, M., Peck, M. A., and Vikebø, F. B. 2011. Evaluating the suitability of coupled biophysical models for fishery management. – ICES Journal of Marine Science, 68: 1478–1487. The potential role of coupled biophysical models in enhancing the conservation, management, and recovery of fish stocks is assessed, with emphasis on anchovy, cod, herring, and sprat in European waters. The assessment indicates that coupled biophysical models are currently capable of simulating transport patterns, along with temperature and prey fields within marine ecosyst

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14

Modolo, Julien, Alexandre Legros, Alex W. Thomas, and Anne Beuter. "Model-driven therapeutic treatment of neurological disorders: reshaping brain rhythms with neuromodulation." Interface Focus 1, no. 1 (2010): 61–74. http://dx.doi.org/10.1098/rsfs.2010.0509.

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Electric stimulation has been investigated for several decades to treat, with various degrees of success, a broad spectrum of neurological disorders. Historically, the development of these methods has been largely empirical but has led to a remarkably efficient, yet invasive treatment: deep brain stimulation (DBS). However, the efficiency of DBS is limited by our lack of understanding of the underlying physiological mechanisms and by the complex relationship existing between brain processing and behaviour. Biophysical modelling of brain activity, describing multi-scale spatio-temporal patterns

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Baltazar-Soares, Miguel, Hans-Harald Hinrichsen, and Christophe Eizaguirre. "Integrating population genomics and biophysical models towards evolutionary-based fisheries management." ICES Journal of Marine Science 75, no. 4 (2018): 1245–57. http://dx.doi.org/10.1093/icesjms/fsx244.

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Abstract Overfishing and rapid environmental shifts pose severe challenges to the resilience and viability of marine fish populations. To develop and implement measures that enhance species’ adaptive potential to cope with those pressures while, at the same time, ensuring sustainable exploitation rates is part of the central goal of fisheries management. Here, we argue that a combination of biophysical modelling and population genomic assessments offer ideal management tools to define stocks, their physical connectivity and ultimately, their short-term adaptive potential. To date, biophysical

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16

Dale, M., S. Krumdieck, and P. Bodger. "Global energy modelling — A biophysical approach (GEMBA) part 1: An overview of biophysical economics." Ecological Economics 73 (January 2012): 152–57. http://dx.doi.org/10.1016/j.ecolecon.2011.10.014.

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17

Palmer, Graham. "A Biophysical Perspective of IPCC Integrated Energy Modelling." Energies 11, no. 4 (2018): 839. http://dx.doi.org/10.3390/en11040839.

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18

Watt, D. E. "Heavy particle track structure parameters for biophysical modelling." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 93, no. 2 (1994): 215–21. http://dx.doi.org/10.1016/0168-583x(94)95690-1.

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19

Yatskou, M. M., and V. V. Apanasovich. "Data analysis in complex biomolecular systems." Informatics 18, no. 1 (2021): 105–22. http://dx.doi.org/10.37661/1816-0301-2021-18-1-105-122.

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The biomolecular technology progress is directly related to the development of effective methods and algorithms for processing a large amount of information obtained by modern high-throughput experimental equipment. The priority task is the development of promising computational tools for the analysis and interpretation of biophysical information using the methods of big data and computer models. An integrated approach to processing large datasets, which is based on the methods of data analysis and simulation modelling, is proposed. This approach allows to determine the parameters of biophysic

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20

Staaterman, Erica, and Claire B. Paris. "Modelling larval fish navigation: the way forward." ICES Journal of Marine Science 71, no. 4 (2013): 918–24. http://dx.doi.org/10.1093/icesjms/fst103.

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Abstract Recent advances in high-resolution ocean circulation models, coupled with a greater understanding of larval behaviour, have increased the sophistication of individual-based, biophysical models used to study the dispersal of larvae in the sea. Fish larvae, in particular, have the ability to swim directionally and increasingly fast during ontogeny, indicating that they may not only disperse, but also migrate using environmental signals. How and when larvae use local and large-scale cues remains a mystery. Including three-dimensional swimming schemes into biophysical models is becoming e

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21

Donges, Jonathan F., Wolfgang Lucht, Sarah E. Cornell, et al. "Taxonomies for structuring models for World–Earth systems analysis of the Anthropocene: subsystems, their interactions and social–ecological feedback loops." Earth System Dynamics 12, no. 4 (2021): 1115–37. http://dx.doi.org/10.5194/esd-12-1115-2021.

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Abstract. In the Anthropocene, the social dynamics of human societies have become critical to understanding planetary-scale Earth system dynamics. The conceptual foundations of Earth system modelling have externalised social processes in ways that now hinder progress in understanding Earth resilience and informing governance of global environmental change. New approaches to global modelling of the human World are needed to address these challenges. The current modelling landscape is highly diverse and heterogeneous, ranging from purely biophysical Earth system models, to hybrid macro-economic

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22

Morin, D. L., M. Cross, V. R. Voller, W. H. Douglas, and R. DeLong. "Biophysical stress analysis of restored teeth: modelling and analysis." Dental Materials 4, no. 2 (1988): 77–84. http://dx.doi.org/10.1016/s0109-5641(88)80095-2.

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23

Reis, Ana, Joana P. F. Teixeira, Ana M. G. Silva, Mariana Ferreira, Paula Gameiro, and Victor de Freitas. "Modelling Hyperglycaemia in an Epithelial Membrane Model: Biophysical Characterisation." Biomolecules 12, no. 10 (2022): 1534. http://dx.doi.org/10.3390/biom12101534.

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Biomimetic models are valuable platforms to improve our knowledge on the molecular mechanisms governing membrane-driven processes in (patho)physiological conditions, including membrane permeability, transport, and fusion. However, current membrane models are over simplistic and do not include the membrane’s lipid remodelling in response to extracellular stimuli. Our study describes the synthesis of glycated dimyristoyl-phosphatidylethanolamine (DMPE-glyc), which was structurally characterised by mass spectrometry (ESI-MS) and quantified by NMR spectroscopy to be further incorporated in a compl

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24

Espig, M., S. C. Finlay-Smits, E. D. Meenken, D. M. Wheeler, and M. Sharifi. "Uncertainty in and around biophysical modelling: insights from interdisciplinary research on agricultural digitalization." Royal Society Open Science 7, no. 12 (2020): 201511. http://dx.doi.org/10.1098/rsos.201511.

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Agricultural digitalization is providing growing amounts of real-time digital data. Biophysical simulation models can help interpret these data. However, these models are subject to complex uncertainties, which has prompted calls for interdisciplinary research to better understand and communicate modelling uncertainties and their impact on decision-making. This article develops two corresponding insights from an interdisciplinary project in a New Zealand agricultural research organization. First, we expand on a recent Royal Society Open Science journal article (van der Bles et al . 2019 Royal

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25

Nasiri, Hamid R., Neil M. Bell, Keith I. E. McLuckie, et al. "Targeting a c-MYC G-quadruplex DNA with a fragment library." Chem. Commun. 50, no. 14 (2014): 1704–7. http://dx.doi.org/10.1039/c3cc48390h.

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A fragment library was screened against the human c-MYC promoter G-quadruplex. Ten fragment hits had a significant concordance between a biophysical assay, in silico modelling and c-MYC expression inhibition.

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26

Foley, Naomi S., Claire W. Armstrong, Viktoria Kahui, Eirik Mikkelsen, and Siv Reithe. "A Review of Bioeconomic Modelling of Habitat-Fisheries Interactions." International Journal of Ecology 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/861635.

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This paper reviews the bioeconomic literature on habitat-fisheries connections. Many such connections have been explored in the bioeconomic literature; however, missing from the literature is an analysis merging the potential influences of habitat on both fish stocks and fisheries into one general, overarching theoretical model. We attempt to clarify the nature of linkages between the function of habitats and the economic activities they support. More specifically, we identify theoretically the ways that habitat may enter the standard Gordon-Schaefer model, and nest these interactions in the g

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27

Kaufmann, Robert. "Biophysical and marxist economics: Learning from each other." Ecological Modelling 38, no. 1-2 (1987): 91–105. http://dx.doi.org/10.1016/0304-3800(87)90046-9.

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28

Forzieri, Giovanni, and Filippo Catani. "Scale-dependent relations in land cover biophysical dynamics." Ecological Modelling 222, no. 17 (2011): 3285–90. http://dx.doi.org/10.1016/j.ecolmodel.2011.06.010.

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29

Gadda, Giacomo, Parvin Mohammadyari, Mauro Gambaccini, and Angelo Taibi. "Advances on the Modelling of Blood Flows and Pressures in Humans through a New Multiscale Mathematical Model." Proceedings 26, no. 1 (2019): 16. http://dx.doi.org/10.3390/proceedings2019026016.

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30

Ottero, Monica. "Biophysical Modelling of Frequency Dependent Neural Entrainment and Its Persistence." International Journal of Psychophysiology 168 (October 2021): S55—S56. http://dx.doi.org/10.1016/j.ijpsycho.2021.07.168.

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31

Tøndel, Kristin, Sander Land, Steven A. Niederer, and Nicolas P. Smith. "Quantifying inter‐species differences in contractile function through biophysical modelling." Journal of Physiology 593, no. 5 (2015): 1083–111. http://dx.doi.org/10.1113/jphysiol.2014.279232.

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32

Kearney, Michael R., and Warren P. Porter. "NicheMapR - an R package for biophysical modelling: the microclimate model." Ecography 40, no. 5 (2016): 664–74. http://dx.doi.org/10.1111/ecog.02360.

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33

Dale, M., S. Krumdieck, and P. Bodger. "Global energy modelling — A biophysical approach (GEMBA) Part 2: Methodology." Ecological Economics 73 (January 2012): 158–67. http://dx.doi.org/10.1016/j.ecolecon.2011.10.028.

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34

Asadi, Haniyeh, Kaka Shahedi, Ben Jarihani, and Roy Sidle. "Rainfall-Runoff Modelling Using Hydrological Connectivity Index and Artificial Neural Network Approach." Water 11, no. 2 (2019): 212. http://dx.doi.org/10.3390/w11020212.

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The input selection process for data-driven rainfall-runoff models is critical because input vectors determine the structure of the model and, hence, can influence model results. Here, hydro-geomorphic and biophysical time series inputs, including Normalized Difference Vegetation Index (NDVI) and Index of Connectivity (IC; a type of hydrological connectivity index), in addition to climatic and hydrologic inputs were assessed. Selected inputs were used to develop Artificial Neural Networks (ANNs) in the Haughton River catchment and the Calliope River catchment, Queensland, Australia. Results sh

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35

Schlüter, Daniela K., Ignacio Ramis-Conde, and Mark A. J. Chaplain. "Multi-scale modelling of the dynamics of cell colonies: insights into cell-adhesion forces and cancer invasion from in silico simulations." Journal of The Royal Society Interface 12, no. 103 (2015): 20141080. http://dx.doi.org/10.1098/rsif.2014.1080.

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Studying the biophysical interactions between cells is crucial to understanding how normal tissue develops, how it is structured and also when malfunctions occur. Traditional experiments try to infer events at the tissue level after observing the behaviour of and interactions between individual cells. This approach assumes that cells behave in the same biophysical manner in isolated experiments as they do within colonies and tissues. In this paper, we develop a multi-scale multi-compartment mathematical model that accounts for the principal biophysical interactions and adhesion pathways not on

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36

Gomez-Tames, Jose, Ilkka Laakso, and Akimasa Hirata. "Review on biophysical modelling and simulation studies for transcranial magnetic stimulation." Physics in Medicine & Biology 65, no. 24 (2020): 24TR03. http://dx.doi.org/10.1088/1361-6560/aba40d.

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37

Friedland, Werner, Pavel Kundrát, Janine Becker, and Markus Eidemüller. "BIOPHYSICAL SIMULATION TOOL PARTRAC: MODELLING PROTON BEAMS AT THERAPY-RELEVANT ENERGIES." Radiation Protection Dosimetry 186, no. 2-3 (2019): 172–75. http://dx.doi.org/10.1093/rpd/ncz197.

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ABSTRACT The biophysical simulation tool PARTRAC has been primarily developed to model radiation physics, chemistry and biology on nanometre to micrometre scales. However, the tool can be applied in simulating radiation effects in an event-by-event manner over macroscopic volumes as well. Benchmark simulations are reported showing that PARTRAC does reproduce the macroscopic Bragg peaks of proton beams, although the penetration depths are underestimated by a few per cent for high-energy beams. PARTRAC also quantifies the increase in DNA damage and its complexity along the beam penetration depth

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38

Olascoaga, M. J., N. Idrisi, and A. Romanou. "Biophysical isopycnic-coordinate modelling of plankton dynamics in the Arabian Sea." Ocean Modelling 8, no. 1-2 (2005): 55–80. http://dx.doi.org/10.1016/j.ocemod.2003.12.002.

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39

Paganetti, H., and M. Goitein. "Biophysical modelling of proton radiation effects based on amorphous track models." International Journal of Radiation Biology 77, no. 9 (2001): 911–28. http://dx.doi.org/10.1080/09553000110066059.

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40

Carbajales-Dale, M., S. Krumdieck, and P. Bodger. "Erratum: Global energy modelling — A biophysical approach (GEMBA) part 2: Methodology." Ecological Economics 117 (September 2015): 212. http://dx.doi.org/10.1016/j.ecolecon.2015.06.010.

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41

Popova, E. E., and M. A. Srokosz. "Modelling the ecosystem dynamics at the Iceland-Faeroes Front: Biophysical interactions." Journal of Marine Systems 77, no. 1-2 (2009): 182–96. http://dx.doi.org/10.1016/j.jmarsys.2008.12.005.

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42

Galvanovskis, Juris, Matthias Braun та Patrik Rorsman. "Exocytosis from pancreatic β-cells: mathematical modelling of the exit of low-molecular-weight granule content". Interface Focus 1, № 1 (2010): 143–52. http://dx.doi.org/10.1098/rsfs.2010.0006.

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Pancreatic β-cells use Ca 2+ -dependent exocytosis of large dense core vesicles to release insulin. Exocytosis in β-cells has been studied biochemically, biophysically and optically. We have previously developed a biophysical method to monitor release of endogenous intragranular constituents that are co-released with insulin. This technique involves the expression of ionotropic membrane receptors in the β-cell plasma membrane and enables measurements of exocytosis of individual vesicles with sub-millisecond resolution. Like carbon fibre amperometry, this method allows fine details of the relea

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Bouman, B. A. M., R. A. J. Plant, and A. Nieuwenhuyse. "Quantifying economic and biophysical sustainability trade-offs in tropical pastures." Ecological Modelling 120, no. 1 (1999): 31–46. http://dx.doi.org/10.1016/s0304-3800(99)00066-6.

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BRAUN, HANS A., KARL VOIGT, J. CHRISTIAN KRIEG, and MARTIN T. HUBER. "INDICATIONS OF PHYSIOLOGICAL AND PATHOPHYSIOLOGICAL RELEVANCE OF NOISE AND CHAOS." Fluctuation and Noise Letters 04, no. 01 (2004): L207—L217. http://dx.doi.org/10.1142/s021947750400180x.

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In recent years biophysical approaches have had particular impact on the progress in physiological and biological research. In systems biology such progress is often associated with the terms "noise" and "chaos". The introduction of these physically based concepts into life sciences has essentially been promoted by the work of Frank Moss and his group. This paper provides evidence of the physiological relevance of such biophysically based approaches with examples from quite different physiological and pathophysiological functions like temperature transduction in peripheral sensory receptors an

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Nelson, Rohan, Philip Kokic, and Holger Meinke. "From rainfall to farm incomes—transforming advice for Australian drought policy. II. Forecasting farm incomes." Australian Journal of Agricultural Research 58, no. 10 (2007): 1004. http://dx.doi.org/10.1071/ar06195.

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Australian drought policy is focussed on providing relief from the immediate effects of drought on farm incomes, while enhancing the longer term resilience of rural livelihoods. Despite the socioeconomic nature of these objectives, the information systems created to support the policy have focussed almost exclusively on biophysical measures of climate variability and its effects on agricultural production. In this paper, we demonstrate the ability of bioeconomic modelling to overcome the moral hazard and timing issues that have led to the dominance of these biophysical measures. The Agricultur

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46

Neuwirthová, Eva, Zuzana Lhotáková, Petr Lukeš, and Jana Albrechtová. "Leaf Surface Reflectance Does Not Affect Biophysical Traits Modelling from VIS-NIR Spectra in Plants with Sparsely Distributed Trichomes." Remote Sensing 13, no. 20 (2021): 4144. http://dx.doi.org/10.3390/rs13204144.

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In this study, we examine leaf reflectance as the main optical property used in remote sensing of vegetation. The total leaf reflectance consists of two main components: a diffuse component, originating from the leaf interior, and a component reflected directly from the leaf surface. The latter contains specular (mirror-like) reflectance (SR) and surface particle scattering, driven by the surface roughness. Our study aimed to (1) reveal the effects of key leaf structural traits on SR in 400–2500 nm, and (2) compare the performance of PLSR models of leaf biophysical properties based on the tota

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47

Piotrowski, Łukasz, Julianna Krasowska, and Krzysztof W. Fornalski. "Mechanistic Modelling of DNA Damage Repair by the Radiation Adaptive Response Mechanism and Its Significance." BioMedInformatics 3, no. 1 (2023): 150–63. http://dx.doi.org/10.3390/biomedinformatics3010011.

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The radiation adaptive response effect is a biophysical phenomenon responsible for the enhancement of repair processes in irradiated cells. This can be observed in dedicated radiobiological experiments, e.g., where the small priming dose of ionising radiation is given before the high challenging one (the so-called Raper–Yonezawa effect). The situation is more complicated when the whole complex system (the organism) is taken into consideration; many other mechanisms make the adaptive response weaker and—in some cases—practically insignificant. The recently published simplified Monte Carlo model

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48

Manzoni, Stefano, Annalisa Molini, and Amilcare Porporato. "Stochastic modelling of phytoremediation." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 467, no. 2135 (2011): 3188–205. http://dx.doi.org/10.1098/rspa.2011.0209.

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Leaching of heavy metals and other contaminants from soils poses a significant environmental threat as it affects the quality of downstream water bodies. Quantifying these losses is particularly important when employing phytoremediation approaches to reduce soil contamination, as contaminant escaping the system through leaching cannot be taken up by vegetation. Despite its undoubted importance, the role of such hydrologic forcing has seldom been fully considered in models describing the long-term contaminant mass balance during phytoremediation. The partitioning of contaminants between leachin

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Guadagno, C. R., D. Millar, R. Lai, et al. "Use of transcriptomic data to inform biophysical models via Bayesian networks." Ecological Modelling 429 (August 2020): 109086. http://dx.doi.org/10.1016/j.ecolmodel.2020.109086.

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50

Le Port, A., JC Montgomery, and AE Croucher. "Biophysical modelling of snapper Pagrus auratus larval dispersal from a temperate MPA." Marine Ecology Progress Series 515 (November 18, 2014): 203–15. http://dx.doi.org/10.3354/meps10973.

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