DEEDI Paddock Modelling Program

The project objective is to undertake paddock modelling across the Great Barrier Reef catchments to determine magnitude of sediment and particulate nutrient reductions from agricultural lands to GBR lagoon achieved over 5 years. Discussions, development and design of a plan (including a monitoring, evaluation, reporting and improvement plan) for GRASP paddock modelling will be undertaken to determine changes in water quality as a result of land management practices adopted by pastoralists. Biophysical outputs will be derived from range of land types, starting conditions and grazing management strategies. GRASP derived outputs will then be incorporated into water models to determine sediment and nutrient estimates for the catchments.

Macadamia Modelling Scoping Study

Investigate the feasibility and utility of a macadamia physiological model.

Developing Queensland 3D Tropical Fruits and Nuts modelling capabilities

Development of 3D functional structural plant models for macadamias and other tropical fruit and nuts.

Computational Modelling of the Vacuum Drying of Australian Hardwoods

Computational Modelling of the Vacuum Drying of Australian Hardwoods.

Modelling drought mortaility in spotted gum.

Increased climate variability and the need to establish production forests at more marginal sites requires an understanding of the mechanisms of drought death in production species so that predictions of growth and survival are robust and defendable.

Gene to Phenotype Integrative Science and Modelling Applied to Pioneer elite

This project aims to use simulatiion modelling to improve our understanding of the genetics and physiology of complex traits with a view to increasing the rate of genetic gain in plant breeding programs.

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

Hierarchical Bayesian modelling of plant pest invasions with human-mediated dispersal

Hierarchical Bayesian models can assimilate surveillance and ecological information to estimate both invasion extent and model parameters for invading plant pests spread by people. A reliability analysis framework that can accommodate multiple dispersal modes is developed to estimate human-mediated dispersal parameters for an invasive species. Uncertainty in the observation process is modelled by accounting for local natural spread and population growth within spatial units. Broad scale incursion dynamics are based on a mechanistic gravity model with a Weibull distribution modification to incorporate a local pest build-up phase. The model uses Markov chain Monte Carlo simulations to infer the probability of colonisation times for discrete spatial units and to estimate connectivity parameters between these units. The hierarchical Bayesian model with observational and ecological components is applied to a surveillance dataset for a spiralling whitefly (Aleurodicus dispersus) invasion in Queensland, Australia. The model structure provides a useful application that draws on surveillance data and ecological knowledge that can be used to manage the risk of pest movement.

Wet season resting - economic insights from scenario modelling

Pasture degradation, particularly that attributable to overgrazing, is a significant problem across the northern Australian rangelands. Although grazing studies have identified the scope for wet season resting strategies to be used to rehabilitate degraded pastures, the economic outcome of these strategies has not been extensively demonstrated. An exploratory study of the prospective economic value of wet season resting is presented using an economic simulation model of a 28000 ha beef enterprise located in the Charters Towers region of north-eastern Australia to explore seven hypothetical scenarios centred on the projected performance of a wet season resting strategy. A series of 20-year simulations for a range of pasture recovery profiles, stocking capacity, animal productivity responses, beef prices and agistment options are compared with a baseline scenario of taking no action. Estimates of the net present value of the 20-year difference in total enterprise gross margins between the various resting options and the 'do nothing' option identify that wet season resting can offer a positive economic return for the range of scenarios examined, although this is contingent on the assumptions that are made concerning the trajectories of change in carrying capacity and animal productivity. Some implications for management and policy making to support the practical implementation of wet season resting strategies are discussed.

Economic modelling of grazing systems in the Fitzroy and Burdekin catchments

The Great Barrier Reef (GBR) is the largest reef system in the world; it covers an area of approximately 2,225,000 km² in the northern Queensland continental shelf. There are approximately 750 reefs that exist within 40 km of the Queensland coast. Recent research has identified that poor water quality is having negative impacts on the GBR (Haynes et al. 2007). The Fitzroy Basin covers 143,000 km² and is the largest catchment draining into the GBR as well as being one of the largest catchments in Australia (Karfs et al. 2009). The Burdekin Catchment is the second largest catchment entering into the GBR and covers 133,432 km².The prime determinant for the changes in water quality entering into the GBR have been attributed to grazing, with beef production the largest single land use industry comprising 90% of the land area (Karfs et al. 2009). Extensive beef production contributes over $1 billion dollars to the national economy annually and employs over 9000 people, many in rural communities (Gordon 2007). ‘Economic modelling of grazing systems in the Fitzroy and Burdekin catchments’ was a joint project with the Fitzroy Basin Association and the Queensland Department of Employment Economic Development and Innovation. The project was formed under the federally funded Caring For Our Country and the Reef Rescue programs. The project objectives were as follows; * Quantifying the costs of over-utilising available pasture and the resulting sediment leaving a representative farm for four of the major land systems in the Burdekin or Fitzroy catchments and identifying economically optimal pasture utilisation rates * Estimating the cost of reducing pasture utilisation rates below the determined optimal * Using this information, guide the selection of appropriate tools to achieve reduced utilisation rates e.g. extension process versus incentive payments or a combination of both * Model the biophysical and economic impacts of altering grazing systems to restore land condition e.g. from C condition to B condition for four land systems in the Burdekin or Fitzroy catchments.

Landscape-scale soil erosion modelling and ecological restoration for a mountainous watershed in Sichuan, China

Sichuanissa Tiibetin ylängön metsäkato on pysähtynyt mutta eroosio-ongelmat jatkuvat Viikin tropiikki-instituutin tutkija Ping ZHOU kartoitti trooppisen metsänhoidon alaan kuuluvassa väitöskirjatyössään maaperän eroosioalttiutta ja sen riippuvuutta metsäkasvillisuudesta Jangtsen tärkeää sivuhaaraa Min-jokea ympäröivällä n. 7400 neliökilometrin suuruisella valuma-alueella Sichuanin Aba-piirikunnassa. Aineistonaan hän käytti muun muassa satelliittikartoitustietoja ja mittaustuloksia yli 600 maastokoealalta. Tutkimuksen nimi suomeksi on "Maaperän eroosion mallinnus ja vuoristoisen valuma-alueen ekologinen ennallistaminen Sichuanissa Kiinassa". Aikaisempien tutkimusten perusteella oli tiedossa että metsien häviäminen tällä alueella pysähtyi jo 1980-luvun alussa. Sen jälkeen on metsien pinta-ala hitaasti kasvanut etupäässä sen vuoksi, että teollinen puunhakkuu luonnonmetsissä kiellettiin kokonaan v. 1998 ja 25 astetta jyrkemmillä rinteillä myös maatalouden harjoittaminen on saatu lopetetuksi viljelijöille tarjottujen taloudellisten houkuttimien avulla. Täten myös pelto- ja laidunmaata on voitu ennallistaa metsäksi. Ping Zhou pystyi jakamaan 5700 metrin korkeuteen saakka kohoavan vuoristoalueen eroosioalttiudeltaan erilaisiin vyöhykkeisiin rinteen kaltevuuden, sademäärän, kasvipeitteen ja maalajin perusteella. Noin 15 prosentilla tutkitun valuma-alueen pinta-alasta, lähinnä Min-joen pääuomaa ympäröivillä jyrkillä rinteillä, eroosioriski oli suuri tai erittäin suuri. Eri tyyppisellä kasvillisuudella oli hyvin erilainen vaikutus eroosioalttiuteen, ja myös alueen sijainti vuoriston eri korkeuksilla vaikutti eroosioon. Säästyneet lähes luonnontilaiset havumetsät, joita on etupäässä vuoriston ylimmissä osissa 2600-4000 metrin korkeudella, edistävät tehokkaasti metsän luontaista uudistumista ja levittäytymistä vaurioituneille alueille. Säilyneiden metsien puulajikoostumus antoi tutkimuksessa mahdollisuuden ennustaa metsien tulevaa kehitystä koko tutkitulla valuma-alueella sen eri korkeusvyöhykkeissä ja eri maaperätyypeillä. Ennallistamisen kannalta ongelmallisimpia olivat alueet joilta metsäpeite oli lähinnä puiden teollisen hakkuun vuoksi kokonaan hävinnyt ja joilla maaperä yleisesti oli eroosion pahoin kuluttama. Näillä alueilla ei ole tehty juuri mitään uudistamis- tai ennallistamistoimenpiteitä. Niillä metsien ennallistaminen vaatii myös puiden tai pensaiden istuttamista. Tähän sopivia ovat erityisesti ilmakehän typpeä sitovat lajit, joista alueella kasvaa luontaisena mm. sama tyrnilaji joka esiintyy myös Suomessa. Työssä tutkittiin yli kahdeksankymmenen paikallisen luontaisen puulajin (joista peräti noin kolmannes on havupuulajeja) ekologisia ominaisuuksia ja soveltuvuutta metsien ennallistamiseen. Avainasemassa työn onnistumisen kannalta ovat nyt paikalliset asukkaat, joiden maankäytön muutokset ovat jo selvästi edistänet luonnonmetsän ennalleen palautumista. Suomen Akatemia rahoitti vuosina 2004-2006 VITRI:n tutkimushanketta, josta Ping Zhou'n väitöskirjatyö muodosti keskeisen osan. Kenttätyö Sichuanissa avasi mahdollisuuden hedelmälliseen monitieteiseen yhteistyöhön ja tutkijavaihtoon Kiinan tiedeakatemian alaisen Chengdun biologiainstituutin (CIB) kanssa; tämä tieteellinen kanssakäyminen jatkuu edelleen.

Soil carbon modelling as a tool for carbon balance studies in forestry

Soils represent a remarkable stock of carbon, and forest soils are estimated to hold half of the global stock of soil carbon. Topical concern about the effects of climate change and forest management on soil carbon as well as practical reporting requirements set by climate conventions have created a need to assess soil carbon stock changes reliably and transparently. The large spatial variability of soil carbon commensurate with relatively slow changes in stocks hinders the assessment of soil carbon stocks and their changes by direct measurements. Models therefore widely serve to estimate carbon stocks and stock changes in soils. This dissertation aimed to develop the soil carbon model YASSO for upland forest soils. The model was aimed to take into account the most important processes controlling the decomposition in soils, yet remain simple enough to ensure its practical applicability in different applications. The model structure and assumptions were presented and the model parameters were defined with empirical measurements. The model was evaluated by studying the sensitivities of the model results to parameter values, by estimating the precision of the results with an uncertainty analysis, and by assessing the accuracy of the model by comparing the predictions against measured data and to the results of an alternative model. The model was applied to study the effects of intensified biomass extraction on the forest carbon balance and to estimate the effects of soil carbon deficit on net greenhouse gas emissions of energy use of forest residues. The model was also applied in an inventory based method to assess the national scale forest carbon balance for Finland’s forests from 1922 to 2004. YASSO managed to describe sufficiently the effects of both the variable litter and climatic conditions on decomposition. When combined with the stand models or other systems providing litter information, the dynamic approach of the model proved to be powerful for estimating changes in soil carbon stocks on different scales. The climate dependency of the model, the effects of nitrogen on decomposition and forest growth as well as the effects of soil texture on soil carbon stock dynamics are areas for development when considering the applicability of the model to different research questions, different land use types and wider geographic regions. Intensified biomass extraction affects soil carbon stocks, and these changes in stocks should be taken into account when considering the net effects of forest residue utilisation as energy. On a national scale, soil carbon stocks play an important role in forest carbon balances.

Complex carbohydrates: 2. The modes of binding of complex carbohydrates to concanavalin A - a computer modelling approach

The probable modes of binding of some complex carbohydrates, which have the trimannosidic core structure (Man3GlcNAc2), to concanavalin A (Con A) have been determined using a computer modelling technique. These studies show that Con a can bind to the terminal mannose residues of the trimannosidic core structure and to the internal mannosyl as well as to the terminal N-acetylglucosamine residues of the N-acetylglucosamine substituted trimannosidic core structure. The oligosaccharide with terminal mannose residues can bind in its minimum energy conformers, whereas the oligosaccharide with internal mannosyl and terminal N-acetylglucosamine residues can bind only in higher energy conformers. In addition the former oligosaccharide forms more hydrogen bonds with Con A than the latter. These results suggest that, for these oligosaccharides, the terminal mannose residue has a much higher probability of reaching the binding site than either the internal mannosyl or the terminal N-acetylglucosamine residues. The substitution of a bisecting N-acetylglucosamine residue on these oligosaccharides, affects significantly the accessibility of the residues which bind to Con A and thereby reduces their binding affinity. It thus seems that the binding affinity of an oligosaccharide to Con A depends not only on the number of sugar residues which possess free 3-, 4- and 6-hydroxyl groups but also on the accessibility of these sugar residues to Con A. This study also reveals that the sugar binding site of Con A is small and that the interactions between Con A and carbohydrates are extended slightly beyond the single sugar residue that is placed in the binding site.

The importance of modelling heterogeneity in complex disease: application to NIMH Schizophrenia Genetics Initiative data

As for other complex diseases, linkage analyses of schizophrenia (SZ) have produced evidence for numerous chromosomal regions, with inconsistent results reported across studies. The presence of locus heterogeneity appears likely and may reduce the power of linkage analyses if homogeneity is assumed. In addition, when multiple heterogeneous datasets are pooled, inter-sample variation in the proportion of linked families (alpha) may diminish the power of the pooled sample to detect susceptibility loci, in spite of the larger sample size obtained. We compare the significance of linkage findings obtained using allele-sharing LOD scores (LOD(exp))-which assume homogeneity-and heterogeneity LOD scores (HLOD) in European American and African American NIMH SZ families. We also pool these two samples and evaluate the relative power of the LOD(exp) and two different heterogeneity statistics. One of these (HLOD-P) estimates the heterogeneity parameter alpha only in aggregate data, while the second (HLOD-S) determines alpha separately for each sample. In separate and combined data, we show consistently improved performance of HLOD scores over LOD(exp). Notably, genome-wide significant evidence for linkage is obtained at chromosome 10p in the European American sample using a recessive HLOD score. When the two samples are combined, linkage at the 10p locus also achieves genome-wide significance under HLOD-S, but not HLOD-P. Using HLOD-S, improved evidence for linkage was also obtained for a previously reported region on chromosome 15q. In linkage analyses of complex disease, power may be maximised by routinely modelling locus heterogeneity within individual datasets, even when multiple datasets are combined to form larger samples.