Developing effective fumigation protocols to manage strongly phosphine-resistant Cryptolestes ferrugineus (Stephens) (Coleoptera: Laemophloeidae)

BACKGROUND The emergence of high levels of resistance in Cryptolestes ferrugineus (Stephens) in recent years threatens the sustainability of phosphine, a key fumigant used worldwide to disinfest stored grain. We aimed at developing robust fumigation protocols that could be used in a range of practical situations to control this resistant pest. RESULTS Values of the lethal time to kill 99.9% (LT99.9, in days) of mixed-age populations, containing all life stages, of a susceptible and a strongly resistant C. ferrugineus population were established at three phosphine concentrations (1.0, 1.5 and 2.0 mg L−1) and three temperatures (25, 30 and 35 °C). Multiple linear regression analysis revealed that phosphine concentration and temperature both contributed significantly to the LT99.9 of a population (P < 0.003, R2 = 0.92), with concentration being the dominant variable, accounting for 75.9% of the variation. Across all concentrations, LT99.9 of the strongly resistant C. ferrugineus population was longest at the lowest temperature and shortest at the highest temperature. For example, 1.0 mg L−1 of phosphine is required for 20, 15 and 15 days, 1.5 mg L−1 for 12, 11 and 9 days and 2.0 mg L−1 for 10, 7 and 6 days at 25, 30 and 35 °C, respectively, to achieve 99.9% mortality of the strongly resistant C. ferrugineus population. We also observed that phosphine concentration is inversely proportional to fumigation period in regard to the population extinction of this pest. CONCLUSION The fumigation protocols developed in this study will be used in recommending changes to the currently registered rates of phosphine in Australia towards management of strongly resistant C. ferrugineus populations, and can be repeated in any country where this type of resistance appears.

Investigating variation in bus ridership rates within localised areas of a sub-tropical city

This thesis makes a significant contribution to knowledge and understanding of 'Human Travel Behaviour' in relation to transportation research. It holds some important merits that have not been proposed before. It develops a new, comprehensive and meaningful relationship that includes bus transit ridership change due to weather variables, seasonality and transit quality of service within a single daily ridership rate estimation model. The research incorporated both temporal and spatial influences on ridership within a modelling structure, named as the Nested Model Structure. It provides a complete picture of ridership variation across the sub-tropical city of Brisbane, Australia.

Developing effective fumigation protocols to manage strongly phosphine-resistant Cryptolestes ferrugineus (Stephens) (Coleoptera: Laemophloeidae)

BACKGROUND The emergence of high levels of resistance in Cryptolestes ferrugineus (Stephens) in recent years threatens the sustainability of phosphine, a key fumigant used worldwide to disinfest stored grain. We aimed at developing robust fumigation protocols that could be used in a range of practical situations to control this resistant pest. RESULTS Values of the lethal time to kill 99.9% (LT99.9, in days) of mixed-age populations, containing all life stages, of a susceptible and a strongly resistant C. ferrugineus population were established at three phosphine concentrations (1.0, 1.5 and 2.0 mg L−1) and three temperatures (25, 30 and 35 °C). Multiple linear regression analysis revealed that phosphine concentration and temperature both contributed significantly to the LT99.9 of a population (P < 0.003, R2 = 0.92), with concentration being the dominant variable, accounting for 75.9% of the variation. Across all concentrations, LT99.9 of the strongly resistant C. ferrugineus population was longest at the lowest temperature and shortest at the highest temperature. For example, 1.0 mg L−1 of phosphine is required for 20, 15 and 15 days, 1.5 mg L−1 for 12, 11 and 9 days and 2.0 mg L−1 for 10, 7 and 6 days at 25, 30 and 35 °C, respectively, to achieve 99.9% mortality of the strongly resistant C. ferrugineus population. We also observed that phosphine concentration is inversely proportional to fumigation period in regard to the population extinction of this pest. CONCLUSION The fumigation protocols developed in this study will be used in recommending changes to the currently registered rates of phosphine in Australia towards management of strongly resistant C. ferrugineus populations, and can be repeated in any country where this type of resistance appears. © 2014 Commonwealth of Australia. Pest Management Science © 2014 Society of Chemical Industry

Positive associations of serum Perfluoroalkyl substances with uric acid and hyperuricemia in children from Taiwan

To investigate the risk of hyperuricemia in relation to Perfluoroalkyl substances (PFASs) in children from Taiwan, 225 Taiwanese children aged 12-15 years were recruited from 2009 to 2010. Linear and logistic regression models were employed to examine the influence of PFASs on serum uric acid levels. Findings revealed that eight of ten PFASs analyses were detected in > 94% of the participants' serum samples. Multivariate linear regression models revealed that perfluorooctanic acid (PFOA) was positively associated with serum uric acid levels (β=0.1463, p<0.05). Of all the PFASs analyses, only PFOA showed a significant effect on elevated levels of hyperuricemia (aOR=2.16, 95%CI: 1.29-3.61). When stratified by gender, the association between serum PFOA and uric acid levels was only evident among boys (aOR=2.76, 95%CI: 1.37-5.56). In conclusion, PFOA was found to be associated with elevated serum levels of uric acid in Taiwanese children, especially boys. Further research is needed to elucidate these links.

Effects of transit quality of service characteristics on daily bus ridership

A case study of Brisbane, the capital city of Queensland, Australia, explored how explicit measures of transit quality of service (e.g., service frequency, service span, and travel time ratio) and implicit environmental predictors (e.g., topographic grade factor) influenced bus ridership. The primary hypothesis tested was that bus ridership was higher in suburbs with high transit quality of service than in suburbs with limited service quality. Multiple linear regression, used to identify a strong positive relationship between route intensity (bus-km/h-km2) and bus ridership, indicated that both increased service frequency and spatial route density corresponded to higher bus ridership. Additionally, the travel time ratio (i.e., the ratio of in-vehicle transit travel time to in-vehicle automobile travel time) had a significant negative association with suburban ridership: transit use declined as travel time ratio increased. In contrast, topographic grade and service span did not significantly affect suburban bus ridership. The study findings enhance the fundamental understanding of traveler behavior, which is informative to urban transportation policy, planning, and provision.

Intuitive interaction in a mixed reality system

Tangible physical systems are more intuitive than Intangible virtual Systems. Mixed reality systems are considered as an alternative to virtual systems, bringing advantages of tangible systems into an interaction. However, past research has mainly focussed on technical aspects of incorporating pervasive-ness and immersive-ness in the virtual systems. This paper reports on an empirical study of intuitive Interaction in a Mixed Reality game system for children and the design aspects that could facilitate intuitive Interaction in such systems. A related samples Friedman’s test showed that the Mixed Reality game system demonstrated more intuitive interactions than non-intuitive Interactions. A linear regression analysis further established that the variation in intuitive Interaction in the Mixed Reality system could be statistically significantly explained primarily by physical affordances offered by the Mixed Reality system and to a lesser extent by the perceived affordances in the system. Design guidelines to develop intuitive Mixed Reality systems are discussed. These guidelines should allow designers to exploit the wonders of advances in technology and at the same time allow users to directly interact with the physical real world. This will allow users to access maximal physical affordances, which are primary contributors to intuitive interaction in Tangible and Mixed Reality systems.

Ion channel gene variants predisposing to severe human ventricular arrhythmias

Congenital long QT syndrome (LQTS) with an estimated prevalence of 1:2000-1:10 000 manifests with prolonged QT interval on electrocardiogram and risk for ventricular arrhythmias and sudden death. Several ion channel genes and hundreds of mutations in these genes have been identified to underlie the disorder. In Finland, four LQTS founder mutations of potassium channel genes account for up to 40-70% of genetic spectrum of LQTS. Acquired LQTS has similar clinical manifestations, but often arises from usage of QT-prolonging medication or electrolyte disturbances. A prolonged QT interval is associated with increased morbidity and mortality not only in clinical LQTS but also in patients with ischemic heart disease and in the general population. The principal aim of this study was to estimate the actual prevalence of LQTS founder mutations in Finland and to calculate their effect on QT interval in the Finnish background population. Using a large population-based sample of over 6000 Finnish individuals from the Health 2000 Survey, we identified LQTS founder mutations KCNQ1 G589D (n=8), KCNQ1 IVS7-2A>G (n=1), KCNH2 L552S (n=2), and KCNH2 R176W (n=16) in 27 study participants. This resulted in a weighted prevalence estimate of 0.4% for LQTS in Finland. Using a linear regression model, the founder mutations resulted in a 22- to 50-ms prolongation of the age-, sex-, and heart rate-adjusted QT interval. Collectively, these data suggest that one of 250 individuals in Finland may be genetically predisposed to ventricular arrhythmias arising from the four LQTS founder mutations. A KCNE1 D85N minor allele with a frequency of 1.4% was associated with a 10-ms prolongation in adjusted QT interval and could thus identify individuals at increased risk of ventricular arrhythmias at the population level. In addition, the previously reported associations of KCNH2 K897T, KCNH2 rs3807375, and NOS1AP rs2880058 with QT interval duration were confirmed in the present study. In a separate study, LQTS founder mutations were identified in a subgroup of acquired LQTS, providing further evidence that congenital LQTS gene mutations may underlie acquired LQTS. Catecholaminergic polymorphic ventricular tachycardia (CPVT) is characterized by exercise-induced ventricular arrhythmias in a structurally normal heart and results from defects in the cardiac Ca2+ signaling proteins, mainly ryanodine receptor type 2 (RyR2). In a patient population of typical CPVT, RyR2 mutations were identifiable in 25% (4/16) of patients, implying that noncoding variants or other genes are involved in CPVT pathogenesis. A 1.1 kb RyR2 exon 3 deletion was identified in two patients independently, suggesting that this region may provide a new target for RyR2-related molecular genetic studies. Two novel RyR2 mutations showing a gain-of-function defect in vitro were identified in three victims of sudden cardiac death. Extended pedigree analyses revealed some surviving mutation carriers with mild structural abnormalities of the heart and resting ventricular arrhythmias suggesting that not all RyR2 mutations lead to a typical CPVT phenotype, underscoring the relevance of tailored risk stratification of a RyR2 mutation carrier.

Microarchitecture sensitive empirical models for compiler optimizations.

This paper proposes the use of empirical modeling techniques for building microarchitecture sensitive models for compiler optimizations. The models we build relate program performance to settings of compiler optimization flags, associated heuristics and key microarchitectural parameters. Unlike traditional analytical modeling methods, this relationship is learned entirely from data obtained by measuring performance at a small number of carefully selected compiler/microarchitecture configurations. We evaluate three different learning techniques in this context viz. linear regression, adaptive regression splines and radial basis function networks. We use the generated models to a) predict program performance at arbitrary compiler/microarchitecture configurations, b) quantify the significance of complex interactions between optimizations and the microarchitecture, and c) efficiently search for'optimal' settings of optimization flags and heuristics for any given microarchitectural configuration. Our evaluation using benchmarks from the SPEC CPU2000 suits suggests that accurate models (< 5% average error in prediction) can be generated using a reasonable number of simulations. We also find that using compiler settings prescribed by a model-based search can improve program performance by as much as 19% (with an average of 9.5%) over highly optimized binaries.

The effects of the 2004 reduction in the price of alcohol on alcohol-related harm in Finland : A natural experiment based on register data

Changes in alcohol pricing have been documented as inversely associated with changes in consumption and alcohol-related problems. Evidence of the association between price changes and health problems is nevertheless patchy and is based to a large extent on cross-sectional state-level data, or time series of such cross-sectional analyses. Natural experimental studies have been called for. There was a substantial reduction in the price of alcohol in Finland in 2004 due to a reduction in alcohol taxes of one third, on average, and the abolition of duty-free allowances for travellers from the EU. These changes in the Finnish alcohol policy could be considered a natural experiment, which offered a good opportunity to study what happens with regard to alcohol-related problems when prices go down. The present study investigated the effects of this reduction in alcohol prices on (1) alcohol-related and all-cause mortality, and mortality due to cardiovascular diseases, (2) alcohol-related morbidity in terms of hospitalisation, (3) socioeconomic differentials in alcohol-related mortality, and (4) small-area differences in interpersonal violence in the Helsinki Metropolitan area. Differential trends in alcohol-related mortality prior to the price reduction were also analysed. A variety of population-based register data was used in the study. Time-series intervention analysis modelling was applied to monthly aggregations of deaths and hospitalisation for the period 1996-2006. These and other mortality analyses were carried out for men and women aged 15 years and over. Socioeconomic differentials in alcohol-related mortality were assessed on a before/after basis, mortality being followed up in 2001-2003 (before the price reduction) and 2004-2005 (after). Alcohol-related mortality was defined in all the studies on mortality on the basis of information on both underlying and contributory causes of death. Hospitalisation related to alcohol meant that there was a reference to alcohol in the primary diagnosis. Data on interpersonal violence was gathered from 86 administrative small-areas in the Helsinki Metropolitan area and was also assessed on a before/after basis followed up in 2002-2003 and 2004-2005. The statistical methods employed to analyse these data sets included time-series analysis, and Poisson and linear regression. The results of the study indicate that alcohol-related deaths increased substantially among men aged 40-69 years and among women aged 50-69 after the price reduction when trends and seasonal variation were taken into account. The increase was mainly attributable to chronic causes, particularly liver diseases. Mortality due to cardiovascular diseases and all-cause mortality, on the other hand, decreased considerably among the-over-69-year-olds. The increase in alcohol-related mortality in absolute terms among the 30-59-year-olds was largest among the unemployed and early-age pensioners, and those with a low level of education, social class or income. The relative differences in change between the education and social class subgroups were small. The employed and those under the age of 35 did not suffer from increased alcohol-related mortality in the two years following the price reduction. The gap between the age and education groups, which was substantial in the 1980s, thus further broadened. With regard to alcohol-related hospitalisation, there was an increase in both chronic and acute causes among men under the age of 70, and among women in the 50-69-year age group when trends and seasonal variation were taken into account. Alcohol dependence and other alcohol-related mental and behavioural disorders were the largest category in both the total number of chronic hospitalisation and in the increase. There was no increase in the rate of interpersonal violence in the Helsinki Metropolitan area, and even a decrease in domestic violence. There was a significant relationship between the measures of social disadvantage on the area level and interpersonal violence, although the differences in the effects of the price reduction between the different areas were small. The findings of the present study suggest that that a reduction in alcohol prices may lead to a substantial increase in alcohol-related mortality and morbidity. However, large population group differences were observed regarding responsiveness to the price changes. In particular, the less privileged, such as the unemployed, were most sensitive. In contrast, at least in the Finnish context, the younger generations and the employed do not appear to be adversely affected, and those in the older age groups may even benefit from cheaper alcohol in terms of decreased rates of CVD mortality. The results also suggest that reductions in alcohol prices do not necessarily affect interpersonal violence. The population group differences in the effects of the price changes on alcohol-related harm should be acknowledged, and therefore the policy actions should focus on the population subgroups that are primarily responsive to the price reduction.

Männyn neulaskadon arviointi laserkeilauksella

Leaf and needle biomasses are key factors in forest health. Insects that feed on needles cause growth losses and tree mortality. Insect outbreaks in Finnish forests have increased rapidly during the last decade and due to climate change the damages are expected to become more serious. There is a need for cost-efficient methods for inventorying these outbreaks. Remote sensing is a promising means for estimating forests and damages. The purpose of this study is to investigate the usability of airborne laser scanning in estimating Scots pine defoliation caused by the common pine sawfly (Diprion pini L.). The study area is situated in Ilomantsi district, eastern Finland. Study materials included high-pulse airborne laser scannings from July and October 2008. Reference data consisted of 90 circular field plots measured in May-June 2009. Defoliation percentage on these field plots was estimated visually. The study was made on plot-level and methods used were linear regression, unsupervised classification, Maximum likelihood method, and stepwise linear regression. Field plots were divided in defoliation classes in two different ways: When divided in two classes the defoliation percentages used were 0–20 % and 20–100 % and when divided in four classes 0–10 %, 10–20 %, 20–30 % and 30–100 %. The results varied depending on method and laser scanning. In the first laser scanning the best results were obtained with stepwise linear regression. The kappa value was 0,47 when using two classes and 0,37 when divided in four classes. In the second laser scanning the best results were obtained with Maximum likelihood. The kappa values were 0,42 and 0,37, correspondingly. The feature that explained defoliation best was vegetation index (pulses reflected from height > 2m / all pulses). There was no significant difference in the results between the two laser scannings so the seasonal change in defoliation could not be detected in this study.

Social Media as a Form of Organizational Knowledge Sharing

This study investigates the role of social media as a form of organizational knowledge sharing. Social media is investigated in terms of the Web 2.0 technologies that organizations provide their employees as tools of internal communication. This study is anchored in the theoretical understanding of social media as technologies which enable both knowledge collection and knowledge donation. This study investigates the factors influencing employees’ use of social media in their working environment. The study presents the multidisciplinary research tradition concerning knowledge sharing. Social media is analyzed especially in relation to internal communication and knowledge sharing. Based on previous studies, it is assumed that personal, organizational, and technological factors influence employees’ use of social media in their working environment. The research represents a case study focusing on the employees of the Finnish company Wärtsilä. Wärtsilä represents an eligible case organization for this study given that it puts in use several Web 2.0 tools in its intranet. The research is based on quantitative methods. In total 343 answers were obtained with the aid of an online survey which was available in Wärtsilä’s intranet. The associations between the variables are analyzed with the aid of correlations. Finally, with the aid of multiple linear regression analysis the causality between the assumed factors and the use of social media is tested. The analysis demonstrates that personal, organizational and technological factors influence the respondents’ use of social media. As strong predictive variables emerge the benefits that respondents expect to receive from using social media and respondents’ experience in using Web 2.0 in their private lives. Also organizational factors such as managers’ and colleagues’ activeness and organizational guidelines for using social media form a causal relationship with the use of social media. In addition, respondents’ understanding of their responsibilities affects their use of social media. The more social media is considered as a part of individual responsibilities, the more frequently social media is used. Finally, technological factors must be recognized. The more user-friendly social media tools are considered and the better technical skills respondents have, the more frequently social media is used in the working environment. The central references in relation to knowledge sharing include Chun Wei Choo’s (2006) work Knowing Organization, Ikujiro Nonaka and Hirotaka Takeuchi’s (1995) work The Knowledge Creating Company and Linda Argote’s (1999) work Organizational Learning.

Detecting Earnings Management Using Neural Networks

Detecting Earnings Management Using Neural Networks. Trying to balance between relevant and reliable accounting data, generally accepted accounting principles (GAAP) allow, to some extent, the company management to use their judgment and to make subjective assessments when preparing financial statements. The opportunistic use of the discretion in financial reporting is called earnings management. There have been a considerable number of suggestions of methods for detecting accrual based earnings management. A majority of these methods are based on linear regression. The problem with using linear regression is that a linear relationship between the dependent variable and the independent variables must be assumed. However, previous research has shown that the relationship between accruals and some of the explanatory variables, such as company performance, is non-linear. An alternative to linear regression, which can handle non-linear relationships, is neural networks. The type of neural network used in this study is the feed-forward back-propagation neural network. Three neural network-based models are compared with four commonly used linear regression-based earnings management detection models. All seven models are based on the earnings management detection model presented by Jones (1991). The performance of the models is assessed in three steps. First, a random data set of companies is used. Second, the discretionary accruals from the random data set are ranked according to six different variables. The discretionary accruals in the highest and lowest quartiles for these six variables are then compared. Third, a data set containing simulated earnings management is used. Both expense and revenue manipulation ranging between -5% and 5% of lagged total assets is simulated. Furthermore, two neural network-based models and two linear regression-based models are used with a data set containing financial statement data from 110 failed companies. Overall, the results show that the linear regression-based models, except for the model using a piecewise linear approach, produce biased estimates of discretionary accruals. The neural network-based model with the original Jones model variables and the neural network-based model augmented with ROA as an independent variable, however, perform well in all three steps. Especially in the second step, where the highest and lowest quartiles of ranked discretionary accruals are examined, the neural network-based model augmented with ROA as an independent variable outperforms the other models.

Components of fractionated stallion seminal plasma and the effects of seminal plasma on sperm longevity

Seminal plasma (SP) is the fluid portion of semen, secreted by the epididymides and the accessory glands before and during ejaculation. The stallion s ejaculate is a series of jets that differ in sperm concentration, semen volume and biochemical composition. Before the actual ejaculation, a clear and watery pre-sperm fluid is secreted. The first three jets form the sperm-rich fractions, and contain ¾ of the total number of sperm. The semen volume and sperm concentration in each of the jets decrease towards the end of the ejaculation, and the last jets are sperm-poor fractions with a low sperm concentration. The aims of these studies were to examine the effects of the different SP fractions, and the presence of SP, on sperm survival during storage. Pre-sperm fluid, and semen fractions with a high (sperm-rich) and low (sperm-poor) sperm concentration were collected in five experiments. The levels of selected enzymes, electrolytes and proteins in different SP fractions were determined. These studies also aimed at assessing the individual variation in the levels of the selected SP components and in the effects of SP on spermatozoa. The association between the components of SP and semen quality, sperm longevity, and fertility was examined with a stepwise linear regression analysis. Compared to samples containing SP during storage, centrifugation and the subsequent removal of SP reduced sperm motility parameters during 24 h of cooled storage in all SP fractions, but sperm membrane integrity was not affected. Some of the measured post-thaw motility parameters were also higher in samples containing SP compared to samples stored without SP. In contrast, the proportion of DNA-damaged spermatozoa was greater in the samples stored with SP than those without SP, and this effect was seen in both sperm-rich and sperm-poor fractions. There were no differences in DNA integrity between fractions stored with SP, but the sperm-rich fraction showed less DNA damage than the sperm-poor fraction after SP removal. The differences between fractions in sperm motility after cooled storage were non-significant. The levels of alkaline phosphatase, acid phosphatase and β-glucuronidase were higher in the sperm-rich fractions compared to the sperm-poor fractions, while the concentrations of calcium and magnesium were higher in sperm-poor fractions than in sperm-rich fractions. The concentrations of sodium and chloride were highest in pre-sperm fluid. In the sperm-poor fraction, the level of potassium was associated with the maintenance of sperm motility during storage. The levels of alkaline and acid phosphatase were associated with sperm concentration and the total number of spermatozoa in the ejaculates. None of the measured SP components were correlated to the first cycle pregnancy rate. In summary, the removal of SP improved DNA integrity after cooled storage compared with samples containing SP. There were no differences in the maintenance of sperm motility between the sperm-rich and sperm-poor fractions and whole ejaculates during cooled storage, irrespective of the presence of SP. The lowest rate of DNA damage was found in the sperm-rich fractions stored without SP. In practice, the results presented in this thesis support the use of individual modifications of semen processing techniques for cooled transported semen from subfertile stallions.

Development of foreign direct investment in Finland

During 1990 to 2009, Foreign Direct Investment (FDI henceforth) in Finland has fluctuated greatly. This paper focused on analyzing the overall development and basic characteristics of Foreign Direct Investment in Finland, covering the period from 1990 to present. By comparing FDI in Finland with FDI in other countries, the picture of Finland’s FDI position in the world market is clearer. A lot of statistical data, tables and figures are used to describe the trend of Foreign Direct Investment in Finland. All the data used in this study were obtained from Statistics Finland, UNCTAD, OECD, World Bank and International Labor Office, Investment map website and etc. It is also found that there is a big, long-lasting and increasing imbalance of the inward FDI and outward FDI in Finland, the performance of outward FDI is stronger than the inward FDI in Finland. Finland’s position of FDI in the world is rather modest. And based on existing theories, I tried to analyze the factors that might determine the size of the inflows of FDI in Finland. The econometric model of my thesis is based on time series data ranging from 1990 to 2007. A Log linear regression model is adopted to analyze the impact of each variable. The regression results showed that Labor Cost and Investment in Education have a negative influence on the FDI inflows into Finland. Too high labor cost is the main impediment of FDI in Finland, explaining the relative small size of FDI inflows into Finland. GDP and Economy openness have a significant positive impact on the inflows of FDI into Finland; other variables do not emerge as significant factor in affecting the size of FDI inflows in Finland as expected. Meanwhile, the impacts of the most recent financial and economic crisis on FDI in the world and in Finland are discussed as well. FDI inflows worldwide and in Finland have suffered from a big setback from the 2008 global crisis. The economic crisis has undoubtedly significant negative influence on the FDI flows in the world and in Finland. Nevertheless, apart from the negative impact, the crisis itself also brings in chances for policymakers to implement more efficient policies in order to create a pro-business and pro-investment climate for the recovery of FDI inflows. . The correspondent policies and measures aiming to accelerate the recovery of the falling FDI were discussed correspondently.

Non-industrial private forest landowners’ choices of timber management strategies.

The factors affecting the non-industrial, private forest landowners' (hereafter referred to using the acronym NIPF) strategic decisions in management planning are studied. A genetic algorithm is used to induce a set of rules predicting potential cut of the landowners' choices of preferred timber management strategies. The rules are based on variables describing the characteristics of the landowners and their forest holdings. The predictive ability of a genetic algorithm is compared to linear regression analysis using identical data sets. The data are cross-validated seven times applying both genetic algorithm and regression analyses in order to examine the data-sensitivity and robustness of the generated models. The optimal rule set derived from genetic algorithm analyses included the following variables: mean initial volume, landowner's positive price expectations for the next eight years, landowner being classified as farmer, and preference for the recreational use of forest property. When tested with previously unseen test data, the optimal rule set resulted in a relative root mean square error of 0.40. In the regression analyses, the optimal regression equation consisted of the following variables: mean initial volume, proportion of forestry income, intention to cut extensively in future, and positive price expectations for the next two years. The R2 of the optimal regression equation was 0.34 and the relative root mean square error obtained from the test data was 0.38. In both models, mean initial volume and positive stumpage price expectations were entered as significant predictors of potential cut of preferred timber management strategy. When tested with the complete data set of 201 observations, both the optimal rule set and the optimal regression model achieved the same level of accuracy.