PDF file: Annual Report 2002/2003 - Scottish Crop Research Institute

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Environment Figure 3 Frost on a windscreen. Simple mechanisms can create rich, life like patterns. the whole. If we are to predict the future survival of an ecosystem accurately then we must capture the key interactions between individuals. Much of nature is non-linear and yet much of mathematics is dedicated to linear problems, because analytical solutions can usually be found to the linear problems but rarely to the former. The power of computers has enabled us to explore non-linear systems in much greater depth. Rich and complex behaviour can emerge from the simplest of non-linear systems. An example of this is the chaotic behaviour that can arise from a simple but powerful ecological model of population growth. The population grows in proportion to its size, initially doubling in each life cycle. However, the population as a whole has finite food supply. As the population expands, food becomes limited and rates of mortality exceed those of birth. The behaviour of this model is critically dependent on the reproductive potential of the individual. For low values, mortality always exceed birth rates and the population becomes extinct. For moderate values, stable population densities are reached. At higher rates, the behaviour changes dramatically from a single stable population to cycling through sets of fixed densities: first one bifurcation, where the population oscillates between two densities on alternate life cycles, and then more bifurcations. Each doubling requiring smaller and smaller increases in reproductive potential until the system becomes “chaotic”. In chaos, the population is constantly changing at each life cycle and never revisits an earlier density. Although chaotic, the range of densities is restricted and some regions are more likely to be visited than others. The behaviour seems random but is not. In principle, if one knew the population precisely at one point in time then one could predict all future populations. The problem is that the smallest error in this estimate is rapidly magnified over a few life cycles and predictability lost. This behaviour is an intrinsic property of the system and not caused by any external, fluctuating influences. Weather exhibits similar changes in behaviour, moving from relatively stable states where long term-forecasts are reliable to more turbulent, chaotic states where forecasts are limited to a day or two and with much less confidence. Models are simplified representations of reality with the ability to predict. We often use the familiar to describe the unfamiliar, but must be wary of any preconceptions and assumptions made. It is important to consider the whole, how the components interact, in order to discover the emergent properties of a system. We must be aware that even the simplest biological systems can exhibit a rich behaviour – an apparent population crash may be an intrinsic property of the system rather than an indication of an external, adverse influence. We aim to combine mathematical modeling with biological experimentation while keeping an open mind when studying systems. 132
Biomathematics and Statistics Scotland (BioSS) D.A. Elston & J.W. McNicol Biomathematics and Statistics Scotland (BioSS) contributes statistical and mathematical expertise to the SEERAD-sponsored research programme. BioSS staff are based in Edinburgh, Aberdeen, Ayr and Dundee to facilitate close collaboration with scientists at the five SABRIs and all three SAC sites. BioSS research is carried out under three themes, namely ‘Systems Modelling and Risk’, ‘Spatial and Temporal Models’ and ‘Statistical Genomics and Bioinformatics’. The last of these is led from SCRI, and was the subject of a workshop with our French counterparts, INRA’s Département de Biométrie et Intelligence Artificielle. Detection of putatitive recombinant sequences in multiple alignment data has been the target of three statistical methods developed at SCRI during recent years. With the appointment of a Bioinformatics programmer, we started to develop a Java-based graphical interface, called TOPALi, to these methods that would run on all computer platforms. The initial version allows plotting of the graphs in real time, and the estimation and visualization of phylogenetic trees. Our future plans include the automation of many aspects of the analysis. BioSS also increased its efforts in Microbial Genomics via a joint BioSS/SCRI PhD studentship to analyse the newly sequenced Erwinia carotovora genome. Initial work has been on the detection of regulatory elements using existing statistical methods, including Weight Matrices and Hidden Markov Models. In linkage disequilibrium mapping, a model has been developed to simulate the flow of genetic markers through a plant breeding population. Our aim is to create a simulated barley population to see if the reduced recombination rate in barley makes the 133
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Scottish Crop Research Institute ®
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The Scottish Crop Research Institut
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Contents Biomathematics and Statist
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Introduction upon the Commissioner
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Introduction ® Scottish Crop Resea
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Report of the Director John R. Hill
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Director’s Report tion from dismi
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Director’s Report paper A revised
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Director’s Report and the relatio
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Director’s Report Member States A
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Director’s Report US subsidies fr
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Director’s Report regions of the
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Director’s Report of silver and m
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Director’s Report tions. Obscenel
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Director’s Report participation.
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Director’s Report heads of state
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Director’s Report Philippines (2.
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Director’s Report Food Aid Famine
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Director’s Report adoption of unh
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Director’s Report economy propose
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Director’s Report (herbicides, in
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Director’s Report by a combinatio
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Director’s Report mended a study
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Director’s Report notes, bulletin
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Director’s Report research instit
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Director’s Report Ireland. Also i
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Director’s Report tats, most nota
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Director’s Report shares of total
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Director’s Report tonnes in 1999.
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Director’s Report Relative Import
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Director’s Report cheap food-stuf
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Director’s Report culturally-rela
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Director’s Report on large parts
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Director’s Report minimum input s
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Director’s Report organic farming
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Viruses - evolving organisms ? Viru
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Viruses - evolving organisms ? CLCu
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Viruses - evolving organisms ? a) b
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Barley Crop Development formation o
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Barley Crop Development Year Total
Page 81 and 82: Barley Crop Development on a year t
Page 83 and 84: GM herbicide-tolerant crops Some pe
Page 85 and 86: GM herbicide-tolerant crops and som
Page 87 and 88: GM herbicide-tolerant crops mitted
Page 89 and 90: GM herbicide-tolerant crops 12 Squi
Page 91 and 92: Mechanisms & Processes Peronospora
Page 93 and 94: Mechanisms & Processes Proteomic an
Page 95 and 96: Mechanisms & Processes High-through
Page 97 and 98: Mechanisms & Processes Studying pla
Page 99 and 100: Mechanisms & Processes Phytoene pea
Page 101 and 102: Mechanisms & Processes New discover
Page 103 and 104: Mechanisms & Processes in these cel
Page 105 and 106: Mechanisms & Processes d). This dat
Page 107 and 108: Genes to Products ic enzymes (use o
Page 109 and 110: Genes to Products Carotenogenesis i
Page 111 and 112: Genes to Products accumulation in s
Page 113 and 114: Genes to Products Retrotransposons
Page 115 and 116: SH43 SL03 SH44 SH12 B20 SL22 B47 B0
Page 117 and 118: Management of genes and organisms i
Page 119 and 120: Environment Functional diversity in
Page 121 and 122: Environment Plant root biomechanics
Page 123 and 124: Environment Microbial and microfaun
Page 125 and 126: Environment The role and importance
Page 127 and 128: Environment duced from barley mixtu
Page 129 and 130: Environment IOBC GMO Guidelines Pro
Page 131: Environment Mathematical modelling
Page 135 and 136: Research services Analytical facili
Page 137 and 138: Research services Division of Finan
Page 139 and 140: Research services Information Techn
Page 141 and 142: Research services Estate, Glasshous
Page 143 and 144: Research services Engineering and M
Page 145 and 146: Research services MRS will: strengt
Page 147 and 148: Research services Health and Safety
Page 149 and 150: Publications Blok, V.C. 2002. Progr
Page 151 and 152: Publications Phenotype/genotype ass
Page 153 and 154: Publications for virus-transmitting
Page 155 and 156: Publications Muckenschnabel, I., Go
Page 157 and 158: Publications rich grassland. Procee
Page 159 and 160: Publications Woodford, J.A.T., Fent
Page 161 and 162: Statement of health & safety policy
Page 163 and 164: The Governing Body The Governing Bo
Page 165 and 166: The Governing Body development and
Page 167 and 168: Staff Theme 2 - Genes to Products T
Page 169 and 170: Staff Division of Finance and Admin
Page 171 and 172: Staff Resignations Name Unit Band M
Page 173 and 174: Staff Editorial Duties Name Positio
Page 175 and 176: Staff Name Position Committee or Or
Page 177 and 178: SCRI Research Programme 2002-2003 S
Page 179 and 180: Research Projects SCR/587/02 SCR/58
Page 181 and 182: Meteorological Records D. Petrie &
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List of Abbreviations AAB ACRE ADAS
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