Generalized Least Squares Regression Research Articles

The Effect of Bank Size, Net Interest Margin, and Capital Adequacy Ratio on Commercial Banks’ Return on Assets: Empirical Evidence from Tanzania

While the current body of literature offers valuable insights into the factors influencing bank financial performance, there is a significant paucity of empirical research focusing on least developed nations. This paper presents new evidence of the effect of bank size, capital adequacy ratio (CAR), and net interest margin (NIM) on banks’ return on assets (financial performance) from the perspective of Tanzania – a least-developed country. We employed the Random Effect, and the Generalized Least Squares (GLS) regression models utilizing a panel dataset spanning the period 2000 to 2022 of ten (10) Tanzanian commercial banks to examine the specific effect of the foregoing variables on commercial banks’ financial performance. The estimation results show that capital adequacy ratio (CAR) and bank size have positive significant effects on the financial performance of commercial banks in Tanzania. Whereas we found inconsistent results for the effect of NIM; while the random effect model shows a marginally significant positive effect on ROA, the GLS regression shows a significant negative effect, indicating that the effect of NIM could be either positive or negative depending on the context. Therefore, policymakers should prioritize measures aimed at promoting healthy levels of capital adequacy and encouraging the growth of larger banks while ensuring adequate oversight to mitigate potential risks associated with market dominance. Additionally, regulatory frameworks should be designed to foster competition and efficiency in the banking sector, facilitating a conducive environment for banks of all sizes to thrive and thus contribute to economic growth.

The Effects of Bank Specific Characteristics and Corporate Governance Mechanisms on Disclosure: An Empirical Investigation in the Banking Sector of Ethiopia

The objective of the study was to investigate the effect of bank-specific and corporate governance mechanisms on the financial and social disclosure level of Ethiopian commercial banks. To address this objective, six years of secondary data were collected from seventeen commercial banks. Financial and social disclosure levels, measured using an unweighted disclosure index, were used as dependent variables, while bank-specific characteristics (such as profitability, age, size, leverage, and liquidity) and corporate governance mechanisms (such as board size, board diversity, board independence, audit committee size, and audit committee independence) were used as independent variables. Generalized Least Squares (GLS) estimation was used to examine the association between dependent and independent variables and to test the hypotheses. The results evidenced by GLS regression revealed that profitability, bank size, and board size have a significantly positive effect on financial disclosure. Conversely, leverage, liquidity, and audit committee independence significantly negatively affect financial disclosure. However, age, board diversity, and audit committee size have no significant effect on the financial disclosure level of Ethiopian commercial banks. Moreover, the results documented from FGLS estimation indicate that profitability has a positive significant effect on social disclosure, whereas liquidity 2023and board independence have a significantly negative effect on social disclosure. However, age, bank size, leverage, board size, board diversity, and audit committee independence do not significantly affect the social disclosure level of Ethiopian commercial banks.

Green Finance Disclosure and Its Impact on Firm Profitability: A Case of KSE 100 Index Companies

The aim of the study was to investigate the green finance disclosure and its effect on the financial performance of KSE-100 listed companies in Pakistan. Green finance disclosure, Tobin's Q, and several control variables such as firm age, size and leverage were the variables tested and evaluated using Generalized Least Squares regression (GLS). Secondary data was gathered from the annual reports of Pakistan's KSE-100 Listed Companies for five years, from 2015 to 2019. The period was chosen because the Securities and Exchange Commission of Pakistan (SECP) has established laws and regulations to oversee top management, company operations, and other activities to improve the financial performance of the companies during this period. The findings show that green finance disclosure positively impacts the financial performance of Pakistan's KSE-100 Listed Companies. Similarly, over time, there is considerable variance in the number of green finance disclosures among Pakistan's various industries (manufacturing and non-manufacturing). In addition, the control variables of company size, age, and leverage positively affect the financial performance of Pakistan's KSE-100 Listed Companies. The study's findings have recommendations for the legislators or regulators to obligate all publicly traded firms in Pakistan registered with the SECP to include green financing information in their annual reports. Recommendations for future research work regarding various problems were provided, and it has significant implications for the top management of publicly traded firms, the SECP, academia, regulatory bodies, researchers, and other stakeholders.

Variation of hair cortisol in two herds of migratory caribou (Rangifer tarandus): implications for health monitoring.

Migratory caribou (Rangifer tarandus sspp.) is an ecotype of conservation concern that is experiencing increased cumulative stressors associated with rapid climate change and development in Arctic Canada. Increasingly, hair cortisol concentrations (HCCs) are being used to monitor seasonal hypothalamic-pituitary-adrenal axis activity of ungulate populations; yet, the effect of key covariates for caribou (sex, season, sampling source, body location) are largely unknown. The objectives of this research were 4-fold: first, we assessed the impact of body location (neck, rump) sampling sites on HCC; second, we assessed key covariates (sex, sampling method, season) impacting HCCs of caribou; third, we investigated inter-population (Dolphin and Union (DU), Bluenose-East (BNE)) and inter-annual differences in HCC and fourth, we examined the association between HCCs and indices of biting insect activity on the summer range (oestrid index, mosquito index). We examined hair from 407 DU and BNE caribou sampled by harvesters or during capture-collaring operations from 2012 to 2020. Linear mixed-effect models were used to assess the effect of body location on HCC and generalized least squares regression (GLS) models were used to examine the impacts of key covariates, year and herd and indices of biting insect harassment. HCC varied significantly by body location, year, herd and source of samples (harvester vs capture). HCC was higher in samples taken from the neck and in the DU herd compared with the BNE, decreased linearly over time and was higher in captured versus hunted animals (P < 0.05). There was no difference in HCC between sexes, and indices of biting insect harassment in the previous year were not significantly associated with HCC. This study identifies essential covariates impacting the HCC of caribou that must be accounted for in sampling, monitoring and data interpretation.

Influence of hydroclimatic variability on dengue incidence in a tropical dryland area

Dengue is an endemic disease in more than 100 countries, but there are few studies about the effects of hydroclimatic variability on dengue incidence (DI) in tropical dryland areas. This study investigates the association between hydroclimatic variability and DI (2008-2018) in a large tropical dryland area. The area studied comprehends seven municipalities with populations ranging from 32,879 to 2,545,419 inhabitants. First, the precipitation and temperature impacts on interannual and seasonal DI were investigated. Then, the monthly association between DI and hydroclimatic variables was analyzed using generalized least squares (GLS) regression. The model's capability to reproduce DI given the current hydroclimatic conditions and DI seasonality over the entire time period studied were assessed. No association between the interannual variation of precipitation and DI was found. However, seasonal variation of DI was shaped by precipitation and temperature. February-July was the main dengue season period. A precipitation threshold, usually above 100 mm, triggers the rapid DI rising. Precipitation and minimum air temperature were the main explanatory variables. A two-month-lagged predictor was relevant for modeling, occurring in all regressions, followed by a non-lagged predictor. The climate predictors differed among the regression models, revealing the high spatial DI variability driven by hydroclimatic variability. GLS regressions were able to reproduce the beginning, development, and end of the dengue season, although we found underestimation of DI peaks and overestimation of low DI. These model limitations are not an issue for climate change impact assessment on DI at the municipality scale since historical DI seasonality was well simulated. However, they may not allow seasonal DI forecasting for some municipalities. These findings may help not only public health policies in the studied municipalities but also have the potential to be reproducible for other dryland regions with similar data availability.

Interest Rate and Bank Risk-Taking: The Role of Income Diversity

This research examines the impact of interest rates on the risk-taking appetite of banks in Egypt and how income diversity influences their risk-taking. Furthermore, it contributes to the literature by investigating the association between the interacting effect of interest rate and income diversity shares on bank risk-taking. The sample includes 22 banks operating in Egypt spanning from 2011 to 2020. For the analysis, the cross-sectional time-series generalized least squares regression (GLS) approach is employed. The results reveal that low-interest rates exacerbate bank risk-taking. In addition, larger income diversity restricts the risk-taking behavior of banks. Importantly, the results show that banks with higher levels of income diversity push for less risky positions during the low-interest rate period. Hence, the results provide valuable insights into the importance of the moderating role of income diversity strategies. The results are robust to different proxies of bank risk-taking. The policy implications from this research indicate that bank managers and regulators in Egypt as well as in similar emerging economies shall promote income diversity strategies to ensure the safety and soundness of the banking system at times of low-interest rates.

The relationship between cross-border acquisitions and R&D investments by Indian firms – substituting or complementing

PurposeEmerging economy firms seek strategic assets through cross-border acquisitions (CBAs) to upgrade their capabilities. The paper explores the relation between emerging economy firms' investments in CBAs and subsequent investments in domestic R&D. It investigates the underlying mechanism that links a firm's decision to pursue CBAs and the outcomes from the CBAs. The main idea behind the study is that firms have higher possibility of creating value from cross-border acquisitions when they simultaneously invest in domestic R&D though both investments are constrained by financial and managerial resources.Design/methodology/approachThe hypotheses are tested on a panel data set of 296 Indian firms over a period of 13 years (2003–2015). The authors use a two-stage Heckman procedure for testing their hypotheses. In the first stage, a probit model predicts the probability of a firm being a cross-border acquirer. The second stage model is estimated by a pooled-data GLS (generalized least squares) regression technique.FindingsThe authors find a nonlinear (inverted U-shaped) relationship between firm's investments in CBAs and domestic R&D. This suggests a complementary relation between investments in CBAs and a firm's domestic R&D at lower levels of investments in CBAs. At higher levels of investments in CBAs, CBA investments begin to substitute for firm's domestic R&D investments. For firms with higher international product-market experience and those operating in the hi-tech industry, the relationship between investments in CBAs and domestic R&D is complementary even at higher levels of CBA investments.Originality/valueThe study highlights the role of an emerging market firm's investment in domestic R&D as a link between the decision to invest in CBAs and related outcomes thereof. Emerging market firms face resource constraints while pursuing simultaneous investments in CBAs and R&D, but investment in R&D is essential for realizing the acquisition objectives. The authors also establish the significance of industry context and experiential learning in deciding the allocation of resources between CBAs and internal R&D.

Species Identification of Shed Snake Skins by Scanning Electron Microscopy, with Verification of Intraspecific Variations and Phylogenetic Comparative Analyses of Microdermatoglyphics

Shed skins of snakes have practical applications and can provide information on biodiversity. We examined shed skins or scales stripped from 53 native species of snakes from Taiwan and adjacent islands and 13 foreign species, verified the intraspecific variation of microstructures on the scales, conducted phylogenetic comparative analyses of microdermatoglyphics, and developed a guide and key to identify shed skins by scanning electron microscopy. We examined several microstructural characteristics of scales including the form and dimensions of oberhautchen cells, denticulations, microridges, nanopits, and nanochannels. Furthermore, we noted scale shape and presence or absence of rounded tubercles on the scales. The microstructures of apical (and central) regions of scales were similar to each other, but different from those on basal and lateral margins, the keel, or apical pits. The microdermatoglyphics on cranial scales (cephalic shields) differed from those on scales from other regions of the body. Those from the dorsal and dorsolateral surfaces of the body, and the dorsal surface of the tail were similar, as were those on scales from the ventral surfaces of the body and tail. For adults or juveniles, there was no significant ontogenetic variation in many microdermatoglyphic characteristics. By conducting phylogenetic mapping, we found that symmetrical (dorsal) scales without apical pit organs or rounded tubercles, keelless and rounded scales, flat microdermatoglyphic patterns (without longitudinal microridges), (sub)lamellate oberhautchen cells, cell borders without denticulations or with tiny and keelless denticulations, and relatively small nanopits at denticulation joints or covering cells, are likely to be plesiomorphic character states. We also examined character evolution models based on the microdermatoglyphics and their phylogenetic signals, conducted phylogenetic generalized least-squares regressions to examine the correlations among snake habitat type and the morphological traits on scales, and confirmed a hypothesis that the evolution of scale microstructures is dominated by both phylogenetic and functional (ecological) constraints. This study also indicates that scale microstructure can be used to identify snakeskin products, roadkill specimens and fragmented samples, scale remnants in predator feces, and wild snake sloughs.

A comprehensive survey of Retzius periodicities in fossil hominins and great apes

Recent studies have provided great insight into hominin life history evolution by utilizing incremental lines found in dental tissues to reconstruct and compare the growth records of extant and extinct humans versus other ape taxa. Among the hominins, studies that have examined Retzius periodicity (RP) variation have come to contradictory conclusions in some instances. To clarify RP variation among hominins and better place this variation in its broader evolutionary context, we conduct the most comprehensive analysis of published RP values for hominins and great apes to date. We gathered all available data from the literature on RP data from extant humans, great apes, and fossil hominins and assessed their variation using parametric and nonparametric analyses of variance. We also performed phylogenetic generalized least-squares regressions of RP data for these taxa as well as a larger set of hominoids for which RP data have been published against data for body mass, encephalization, and mean semicircular canal radius (a proxy for metabolic rate). Our results show that modern humans have a mean RP significantly differing from that of other hominins. Pongo also is significantly different from nearly all other taxa in all analyses. Our results also demonstrate that RP variation among hominins scales with respect to body mass, encephalization, and semicircular canal radius similarly to other hominids but that modern humans and Pongo stand out in this regard. Operating within the hypothesis that RP reflects autonomic biorhythms that regulate multiple life history variables, our results reinforce the idea that Homo sapiens has evolved a life history distinct from other hominins, even from other members of Homo, and suggest that many of these life history differences may be driven by hypothalamic output from the brain.

Operational Bayesian GLS Regression for Regional Hydrologic Analyses

AbstractThis paper develops the quasi‐analytic Bayesian analysis of the generalized least squares (GLS) (B‐GLS) model introduced by Reis et al. (2005, https://doi.org/10.1029/2004WR003445) into an operational and statistically comprehensive GLS regional hydrologic regression methodology to estimate flood quantiles, regional shape parameters, low flows, and other statistics with spatially correlated flow records. New GLS regression diagnostic statistics include a Bayesian plausibility value, pseudo adjusted R2, pseudo analysis of variance table, and two diagnostic error variance ratios. Traditional leverage and influence are extended to identify rogue observations, address lack of fit, and support gauge network design and region‐of‐influence regression. Formulas are derived for the Bayesian computation of estimators, standard errors, and diagnostic statistics. The use of B‐GLS and the new diagnostic statistics are illustrated with a regional log‐space skew regression analysis for the Piedmont region in the Southeastern U.S. A comparison of ordinary, weighted, and GLS analyses documents the advantages of the Bayesian estimator over the method‐of‐moment estimator of model error variance introduced by Stedinger and Tasker (1985, https://doi.org/10.1029/WR021i009p01421). Of the three types of analyses, only GLS considers the covariance among concurrent flows. The example demonstrates that GLS regional skewness models can be highly accurate when correctly analyzed: The B‐GLS average variance of prediction is 0.090 for South Carolina (92 stations), whereas a traditional ordinary least squares analysis published by the U.S. Geological Survey yielded 0.193 (Feaster &amp; Tasker, 2002, https://doi.org/10.3133/wri024140). B‐GLS provides a statistical valid framework for the rigorous analysis of spatially correlated hydrologic data, allowing for the estimation of parameters and their actual precision and computation of several diagnostic statistics, as well as correctly attributing variability to the three key sources: time sampling error, model error, and signal.

Buprenorphine waiver uptake among nurse practitioners and physician assistants: The role of existing waivered prescriber supply

BackgroundBuprenorphine is an effective pharmacotherapy for the treatment of opioid use disorder (OUD), but recent increases in the rate of OUD in the U.S. have outpaced the supply of clinicians waivered to prescribe buprenorphine. To increase the supply of buprenorphine prescribers, the Comprehensive Addiction and Recovery Act expanded buprenorphine prescribing waiver eligibility beyond physicians to nurse practitioners (NP) and physician assistants (PA) in 2017. Little is known about patterns of waiver uptake among NPs and PAs. This study examined associations between the existing supply of waivered prescribers and waiver uptake among NPs and PAs in U.S. states. MethodsNP and PA waiver uptake was evaluated as the number of NPs or PAs obtaining an initial buprenorphine prescribing waiver per 10,000 state residents from January 2017 to December 2018 using data from the Buprenorphine Waiver Notification System. NP and PA waiver uptake was estimated as a function of existing waivered prescriber supply, OUD treatment capacity, and other state characteristics using generalized least squares (GLS) regression. Results28,010 NPs and PAs have become waivered to prescribe buprenorphine since January 2017. GLS regressions indicated that waivered prescriber supply was significantly, positively associated with both NP (b = 0.101 p < 0.001) and PA (b = 0.030, p < 0.001) waiver uptake. Results suggest an addition of ten waivered prescribers to existing supply was associated with an increase of one waivered NP, and an addition of thirty-three waivered prescribers to existing supply was associated with an increase of one waivered PA. ConclusionsNP and PA waiver uptake is strongly associated with the existing supply of waivered prescribers in a state, suggesting NPs and PAs may be more likely to acquire waivers in states with a high existing supply of buprenorphine prescribers. Additional policy solutions are needed to scale up the supply of buprenorphine prescribers in underserved states.

Lepidosaurian diversity in the Mesozoic-Palaeogene: the potential roles of sampling biases and environmental drivers.

Lepidosauria is a speciose clade with a long evolutionary history, but there have been few attempts to explore its taxon richness through time. Here we estimate patterns of terrestrial lepidosaur genus diversity for the Triassic–Palaeogene (252–23 Ma), and compare observed and sampling-corrected richness curves generated using Shareholder Quorum Subsampling and classical rarefaction. Generalized least-squares regression (GLS) is used to investigate the relationships between richness, sampling and environmental proxies. We found low levels of richness from the Triassic until the Late Cretaceous (except in the Kimmeridgian–Tithonian of Europe). High richness is recovered for the Late Cretaceous of North America, which declined across the K–Pg boundary but remained relatively high throughout the Palaeogene. Richness decreased following the Eocene–Oligocene Grande Coupure in North America and Europe, but remained high in North America and very high in Europe compared to the Late Cretaceous; elsewhere data are lacking. GLS analyses indicate that sampling biases (particularly, the number of fossil collections per interval) are the best explanation for long-term face-value genus richness trends. The lepidosaur fossil record presents many problems when attempting to reconstruct past diversity, with geographical sampling biases being of particular concern, especially in the Southern Hemisphere.

A systematic investigation of geostatistical image fusion for the improvement of the spectral fidelity and spatial detail in Landsat MS imagery

ABSTRACTThis is the first systematic investigation into the assumptions of image fusion using regression Kriging (RK) – a geostatistical method – illustrated with Landsat MS (multispectral) and SPOT (Satellite Pour l’Observation de la Terre) panchromatic images. The efficiency of different linear regression and Kriging methods in the fusion process is examined by visual and quantitative indicators. Results indicate a trade-off between spectral fidelity and spatial detail preservation for the GLS (generalized least squares regression) and OLS (ordinary least squares regression) methods in the RK process: OLS methods preserve more spatial detail, while GLS methods retain more spectral information from the MS images but at a greater computational cost. Under either OK (ordinary Kriging) or UK (universal Kriging) with either OLS or GLS, the spherical variogram improves spatial details from the panchromatic image, while the exponential variogram maintains more spectral information from the MS image. Overall, RK-based fusion methods outperform conventional fusion approaches from both the spectral and spatial point of view.

Evaluating the Relationship between White-Tailed Deer and Environmental Conditions using Spatially Autocorrelated Data in Tropical Dry Forests of Central Mexico

Ordinary least-square (OLS) regression is fundamental to quantitative research in many ecological disciplines. However, spatially explicit methods have recently been proposed that allow the incorporation of spatial autocorrelation into ecological models. We compared the spatial error simultaneous autoregressive model (SARerr) and generalized least squares regression (GLS) with the results of simple and multiple OLS regressions, to analyze the relationship between white-tailed deer ( Odocoileus virginianus) population density and environmental conditions in two regions dominated by tropical dry forests in central Mexico. The spatially explicit methods presented better goodness of fit than the OLS regression; we also observed a miscalculation in the probabilities obtained with the OLS regression, which in this method led to an incorrect interpretation. In general, we suggest the application of spatially explicit methods to analyze species-habitat relationships when SAC is observed in model residuals. We also discuss the management implications of these results.

Standing on the shoulders of apes: Analyzing the form and function of the hominoid scapula using geometric morphometrics and finite element analysis.

The aim was to analyze the relationship between scapular form and function in hominoids by using geometric morphometrics (GM) and finite element analysis (FEA). FEA was used to analyze the biomechanical performance of different hominoid scapulae by simulating static postural scenarios. GM was used to quantify scapular shape differences and the relationship between form and function was analyzed by applying both multivariate-multiple regressions and phylogenetic generalized least-squares regressions (PGLS). Although it has been suggested that primate scapular morphology is mainly a product of function rather than phylogeny, our results showed that shape has a significant phylogenetic signal. There was a significant relationship between scapular shape and its biomechanical performance; hence at least part of the scapular shape variation is due to non-phylogenetic factors, probably related to functional demands. This study has shown that a combined approach using GM and FEA was able to cast some light regarding the functional and phylogenetic contributions in hominoid scapular morphology, thus contributing to a better insight of the association between scapular form and function.

Short- and Long-Term Effectiveness of a Subject's Specific Novel Brain and Vestibular Rehabilitation Treatment Modality in Combat Veterans Suffering from PTSD.

Treatment for post-traumatic stress disorder (PTSD) in combat veterans that have a long-term positive clinical effect has the potential to modify the treatment of PTSD. This outcome may result in changed and saved lives of our service personnel and their families. In a previous before-after-intervention study, we demonstrated high statistical and substantively significant short-term changes in the Clinician Administered DSM-IV PTSD Scale (CAPS) scores after a 2-week trial of a subject's particular novel brain and vestibular rehabilitation (VR) program. The long-term maintenance of PTSD severity reduction was the subject of this study. We studied the short- and long-term effectiveness of a subject's particular novel brain and VR treatment of PTSD in subjects who had suffered combat-related traumatic brain injuries in terms of PTSD symptom reduction. The trial was registered as ClinicalTrials.gov Identifier: NCT02003352. We analyzed the difference in the CAPS scores pre- and post-treatment (1 week and 3 months) using our subjects as their matched controls. The generalized least squares (GLS) technique demonstrated that with our 26 subjects in the 3 timed groups the R (2) within groups was 0.000, R (2) between groups was 0.000, and overall the R (2) was 0.000. The GLS regression was strongly statistically significant z = 21.29, p < 0.001, 95% CI [58.7, 70.63]. The linear predictive margins over time demonstrated strong statistical and substantive significance of decreasing PTSD severity scores for all timed CAPS tests. Our investigation has the promise of the development of superior outcomes of treatments in this area that will benefit a global society. The length of the treatment intervention involved (2 weeks) is less that other currently available treatments and has profound implications for cost, duration of disability, and outcomes in the treatment of PTSD in combat veterans.

P13 An international comparison of mobile phone subscribership and motor vehicle crash injuries

BackgroundMobile phone use while driving has been associated with a substantially higher likelihood of motor vehicle crash risk and is the focus of numerous traffic safety policies and initiatives worldwide in recent years. Although prior studies have examined the relationship of distracted driving and crash risk using national data, few if any studies have explored cross-national differences in mobile phone use on motor vehicle crash rates. We use longitudinal data for 23 countries to examine the association between rates of mobile phone subscribership and injuries and fatalities on public roadways. MethodsRoad safety data are reported by the Organization for Economic Co-operation and Development (OECD). We examine 23 OECD countries for the 11-year period, 2001–2011. Generalized least squares (GLS) regression is used to examine logged nonfatal injuries and fatalities per 100,000 population with the log number of mobile phone subscribers per 100 people, adjusting for number of motor vehicles (cars, buses, other), percent urban population, unemployment rate, GDP per capita, year and country fixed effects. ResultsFrom 2001 to 2011, countries experienced a 23.3% decline in rates of motor vehicle injuries—decreasing from 394.2 to 302.5 per 100,000 population. However, trends in motor vehicle crash injuries varied across countries. For example, Denmark and France experienced a more than 50% decrease in injury rates since 2001, but rates in Australia increased 4.4%, from 151.6 to 158.3 per 100,000 population. Mobile phone subscribership increased substantially in this period, but rates and growth also varied significantly across countries. For example, in Switzerland, an average of 10 persons per 100 have a mobile phone; this compares to 77.2 in Great Britain. Growth rates in subscribership ranged from 22.3% in Iceland to nearly 200% in Estonia and Turkey in the study period. GLS regression analysis suggests a significant and positive association between rates of mobile phone subscribership and motor vehicle crash injuries. A 10% increase in subscribers per 100 people is predicted to result in an increase of 12.0% (p<.001) and 7.5% (p<.001) in crash injuries and fatalities per 100,000 people, respectively. ConclusionsWe present evidence that increasing rates of mobile phone subscribership may be associated with motor vehicle crash injuries. Distracted driving is a problem worldwide and, thus, more cross-national efforts are needed to identify best practices in policy implementation to help address this problem.

Elevation-dependent responses of tree mast seeding to climate change over 45 years.

We use seed count data from a New Zealand mono-specific mountain beech forest to test for decadal trends in seed production along an elevation gradient in relation to changes in climate. Seedfall was collected (1965 to 2009) from seed trays located on transect lines at fixed elevations along an elevation gradient (1020 to 1370 m). We counted the number of seeds in the catch of each tray, for each year, and determined the number of viable seeds. Climate variables were obtained from a nearby (<2 km) climate station (914-m elevation). Variables were the sum or mean of daily measurements, using periods within each year known to correlate with subsequent interannual variation in seed production. To determine trends in mean seed production, at each elevation, and climate variables, we used generalized least squares (GLS) regression. We demonstrate a trend of increasing total and viable seed production, particularly at higher elevations, which emerged from marked interannual variation. Significant changes in four seasonal climate variables had GLS regression coefficients consistent with predictions of increased seed production. These variables subsumed the effect of year in GLS regressions with a greater influence on seed production with increasing elevation. Regression models enforce a view that the sequence of climate variables was additive in their influence on seed production throughout a reproductive cycle spanning more than 2 years and including three summers. Models with the most support always included summer precipitation as the earliest variable in the sequence followed by summer maximum daily temperatures. We interpret this as reflecting precipitation driven increases in soil nutrient availability enhancing seed production at higher elevations rather than the direct effects of climate, stand development or rising atmospheric CO2 partial pressures. Greater sensitivity of tree seeding at higher elevations to changes in climate reveals how ecosystem responses to climate change will be spatially variable.

Estimation of utility values from visual analog scale measures of health in patients undergoing cardiac surgery

IntroductionIn health economic evaluations, mapping can be used to estimate utility values from other health outcomes in order to calculate quality adjusted life-years. Currently, no methods exist to map visual analog scale (VAS) scores to utility values. This study aimed to develop and propose a statistical algorithm for mapping five dimensions of health, measured on VASs, to utility scores in patients suffering from cardiovascular disease.MethodsPatients undergoing coronary artery bypass grafting at Aalborg University Hospital in Denmark were asked to score their health using the five VAS items (mobility, self-care, ability to perform usual activities, pain, and presence of anxiety or depression) and the EuroQol 5 Dimensions questionnaire. Regression analysis was used to estimate four mapping models from patients’ age, sex, and the self-reported VAS scores. Prediction errors were compared between mapping models and on subsets of the observed utility scores. Agreement between predicted and observed values was assessed using Bland–Altman plots.ResultsRandom effects generalized least squares (GLS) regression yielded the best results when quadratic terms of VAS scores were included. Mapping models fitted using the Tobit model and censored least absolute deviation regression did not appear superior to GLS regression. The mapping models were able to explain approximately 63%–65% of the variation in the observed utility scores. The mean absolute error of predictions increased as the observed utility values decreased.ConclusionWe concluded that it was possible to predict utility scores from VAS scores of the five dimensions of health used in the EuroQol questionnaires. However, the use of the mapping model may be inappropriate in more severe conditions.

Projected northern rocky mountain annual streamflow for 2000-2099 under the B1, A1B and A2 SRES emissions scenarios

THE B1, A1B AND A2 SRES EMISSIONS SCENARIOS Jeannine-Marie St. Jacques1*, Suzan Lapp1*, Yang Zhao2, Elaine M. Barrow1 and David J. Sauchyn1; 1Prairie Adaptation Research Collaborative (P.A.R.C.), Room 120, 2 Research Drive, Regina, SK, Canada, S4S 7H9; 2Department of Mathematics and Statistics, University of Regina, Regina, Saskatchewan, Canada, S4S 0A2; *Corresponding authors’ e-mail: stjacqje@uregina.ca, lapp200s@uregina.ca. ABSTRACT The 20th century hydroclimatology of the northern Rocky Mountains is heavily influenced by recurring large-scale climate patterns: the Pacific Decadal Oscillation (PDO), the El NinoSouthern Oscillation (ENSO), and the Arctic Oscillation/North Atlantic Oscillation (AO/NAO). Hence, northern Rocky Mountain river discharge variability can be successfully modeled by regression techniques using these climate indices as predictors. Generalized least squares (GLS) regression addresses residual autocorrelation and allows reliable significance testing of any predictor coefficients, and hence, is highly suitable for hydrological modeling. We developed GLS regression equations which captured a major portion of streamflow variability for ten centennial-length northern Rocky Mountain annual discharge records. Both unregulated and paired regulated and naturalized flows were examined. Using archived global climate model runs from the Coupled Model Intercomparison Project Phase 3 (CMIP3), we projected the PDO, ENSO and NAO for the 21st century for the B1, A1B and A2 SRES emission scenarios. These projected climate indices were used as inputs into the GLS equations, giving projected northern Rocky Mountain river discharges for the 21st century. These projections showed generally declining trends in surface water availability for 20002099. Researchers have projected increases in summer warmth and typically decreasing summer precipitation, and increases in winter precipitation and temperature for this region under greenhouse forcing. Our results suggest that in the competition between these two opposing effects on surface water availability, the former will dominate.