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Response Variables (response + variable)
Kinds of Response Variables Selected AbstractsStream food web response to a salmon carcass analogue addition in two central Idaho, U.S.A. streamsFRESHWATER BIOLOGY, Issue 3 2008ANDRE E. KOHLER Summary 1. Pacific salmon and steelhead once contributed large amounts of marine-derived carbon, nitrogen and phosphorus to freshwater ecosystems in the Pacific Northwest of the United States of America (California, Oregon, Washington and Idaho). Declines in historically abundant anadromous salmonid populations represent a significant loss of returning nutrients across a large spatial scale. Recently, a manufactured salmon carcass analogue was developed and tested as a safe and effective method of delivering nutrients to freshwater and linked riparian ecosystems where marine-derived nutrients have been reduced or eliminated. 2. We compared four streams: two reference and two treatment streams using salmon carcass analogue(s) (SCA) as a treatment. Response variables measured included: surface streamwater chemistry; nutrient limitation status; carbon and nitrogen stable isotopes; periphyton chlorophyll a and ash-free dry mass (AFDM); macroinvertebrate density and biomass; and leaf litter decomposition rates. Within each stream, upstream reference and downstream treatment reaches were sampled 1 year before, during, and 1 year after the addition of SCA. 3. Periphyton chlorophyll a and AFDM and macroinvertebrate biomass were significantly higher in stream reaches treated with SCA. Enriched stable isotope (,15N) signatures were observed in periphyton and macroinvertebrate samples collected from treatment reaches in both treatment streams, indicating trophic transfer from SCA to consumers. Densities of Ephemerellidae, Elmidae and Brachycentridae were significantly higher in treatment reaches. Macroinvertebrate community composition and structure, as measured by taxonomic richness and diversity, did not appear to respond significantly to SCA treatment. Leaf breakdown rates were variable among treatment streams: significantly higher in one stream treatment reach but not the other. Salmon carcass analogue treatments had no detectable effect on measured water chemistry variables. 4. Our results suggest that SCA addition successfully increased periphyton and macroinvertebrate biomass with no detectable response in streamwater nutrient concentrations. Correspondingly, no change in nutrient limitation status was detected based on dissolved inorganic nitrogen to soluble reactive phosphorus ratios (DIN/SRP) and nutrient-diffusing substrata experiments. Salmon carcass analogues appear to increase freshwater productivity. 5. Salmon carcass analogues represent a pathogen-free nutrient enhancement tool that mimics natural trophic transfer pathways, can be manufactured using recycled fish products, and is easily transported; however, salmon carcass analogues should not be viewed as a replacement for naturally spawning salmon and the important ecological processes they provide. [source] Determination of the selenium requirement in kittens,JOURNAL OF ANIMAL PHYSIOLOGY AND NUTRITION, Issue 9-10 2003K. J. Wedekind Summary The purpose of this study was to determine the selenium (Se) requirement in kittens. Thirty-six specific-pathogen-free kittens (9.8 weeks old) were utilized in a randomized complete block design to determine the Se requirement in cats with gender and weight used as blocking criteria. Kittens were fed a low Se (0.02 mg/kg Se) torula yeast-based diet for 5 weeks (pre-test) after which an amino acid-based diet (0.027 mg Se/kg diet) was fed for 8 weeks (experimental period). Six levels of Se (0, 0.05, 0.075, 0.10, 0.20 and 0.30 mg Se/kg diet) as Na2SeO3 were added to the diet and were used to construct a response curve. Response variables included Se concentrations and Se-dependent glutathione peroxidase activities (GSHpx) in plasma and red blood cells (RBC) as well as plasma total T3 (TT3) and total T4 (TT4). No significant changes in food intake, weight gain or clinical signs of Se deficiency were noted. Estimates of the kitten's Se requirement (i.e. breakpoints) were determined for RBC and plasma GSHpx (0.12 and 0.15 mg Se/kg diet, respectively), but no definitive breakpoint was determined for plasma Se. Plasma TT3 increased linearly, whereas plasma TT4 and the ratio of TT4 : TT3 decreased in a quadratic fashion to dietary Se concentration. The requirement estimate determined in this study (0.15 mg Se/kg) for kittens is in close agreement with other species. As pet foods for cats contain a high proportion of animal protein with a Se bioavailability of 30%, it is recommended that commercial diets for cats contain 0.5 mg Se/kg DM. [source] OPTIMIZATION OF A CHOCOLATE PEANUT SPREAD USING RESPONSE SURFACE METHODOLOGY (RSM)JOURNAL OF SENSORY STUDIES, Issue 3 2004C.A. CHU ABSTRACT Response surface methodology was used to optimize formulations of chocolate peanut spread. Thirty-six formulations with varying levels of peanut (25-90%), chocolate (5-70%) and sugar (5-55%) were processed using a three-component constrained simplex lattice design. The processing variable, roast (light, medium, dark) was also included in the design. Response variables, measured with consumers (n = 60) participating in the test, were spreadability, overall acceptability, appearance, color, flavor, sweetness and texture/mouthfeel, using a 9-point hedonic scale. Regression analysis was performed and models were built for each significant (p < 0.01) response variable. Contour plots for each attribute, at each level of roast, were generated and superimposed to determine areas of overlap. Optimum formulations (consumer acceptance rating of , 6.0 for all attributes) for chocolate peanut spread were all combinations of 29-65% peanut, 9-41% chocolate, and 17-36% sugar, adding up to 100%, at a medium roast. Verification of two formulations indicated no difference between predicted and observed values. [source] Noncorrelated effects of seed predation and pollination on the perennial herb Ruellia nudiflora remain spatially consistentBIOLOGICAL JOURNAL OF THE LINNEAN SOCIETY, Issue 4 2009LUIS ABDALA-ROBERTS By simultaneously manipulating both seed predator and pollinator effects on the perennial herb Ruellia nudiflora at two sites in Yucatan (Mexico), the present study evaluated (1) whether a correlation (interaction) existed between seed predator and pollinator effects on R. nudiflora seed production and (2) whether such an interaction varied geographically. We used three populations per site, and a total of 20 plants per population (N = 120). Groups of five plants were randomly chosen at each population to simultaneously receive one of two seed predator and pollinator exclosure levels (present or excluded in each case). These two factors were fully crossed, resulting in each group being subjected to one of four possible combinations: pollinators excluded/herbivores present; herbivores excluded/pollinators present; herbivores excluded/pollinators excluded; or control (neither excluded). Response variables were the number of seeds produced per plant and the proportion of attacked fruits by seed predators per plant. Seed predators had a large impact on R. nudiflora seed production but did not show any preference for fruits from plants not excluded from pollinators. In addition, the pollination treatment was not significant, indicating no effect of pollinators on reproductive success. These findings resulted in a nonsignificant herbivory × pollination interaction, which was consistent across sites, indicating lack of correlated selection of these two guilds on R. nudiflora seed production. © 2009 The Linnean Society of London, Biological Journal of the Linnean Society, 2009, 96, 800,807. [source] The Interplay between Climate Variability and Density Dependence in the Population Viability of Chinook SalmonCONSERVATION BIOLOGY, Issue 1 2006RICHARD W. ZABEL análisis de viabilidad poblacional; especies en peligro; Oncorhynchus tshawytscha Abstract:,The viability of populations is influenced by driving forces such as density dependence and climate variability, but most population viability analyses (PVAs) ignore these factors because of data limitations. Additionally, simplified PVAs produce limited measures of population viability such as annual population growth rate (,) or extinction risk. Here we developed a "mechanistic" PVA of threatened Chinook salmon (Oncorhynchus tshawytscha) in which, based on 40 years of detailed data, we related freshwater recruitment of juveniles to density of spawners, and third-year survival in the ocean to monthly indices of broad-scale ocean and climate conditions. Including climate variability in the model produced important effects: estimated population viability was very sensitive to assumptions of future climate conditions and the autocorrelation contained in the climate signal increased mean population abundance while increasing probability of quasi extinction. Because of the presence of density dependence in the model, however, we could not distinguish among alternative climate scenarios through mean , values, emphasizing the importance of considering multiple measures to elucidate population viability. Our sensitivity analyses demonstrated that the importance of particular parameters varied across models and depended on which viability measure was the response variable. The density-dependent parameter associated with freshwater recruitment was consistently the most important, regardless of viability measure, suggesting that increasing juvenile carrying capacity is important for recovery. Resumen:,La viabilidad de poblaciones esta influida por fuerzas conductoras como la denso dependencia y la variabilidad climática, pero la mayoría de los análisis de viabilidad poblacional (AVP) ignoran estos factores debido a limitaciones en la disponibilidad de datos. Adicionalmente, los AVP simplificados producen medidas limitadas de la viabilidad poblacional tales como la tasa anual de crecimiento poblacional (,) o el riesgo de extinción. Aquí desarrollamos un AVP "mecanicista" de Oncorhynchus tshawytscha en el que, con base en datos detallados de 40 años, relacionamos el reclutamiento de juveniles en agua dulce con la densidad de reproductores, y la supervivencia en el océano al tercer año con índices mensuales de condiciones oceánicas y climáticas a amplia escala. La inclusión de la variabilidad climática en el modelo produjo efectos importantes: la viabilidad poblacional estimada fue muy sensible a las suposiciones de condiciones climáticas futuras y la autocorrelación contenida en la señal climática aumentó la abundancia poblacional promedio al mismo tiempo que incrementó la probabilidad de cuasi extinción. Sin embargo, debido a la presencia de denso densidad en el modelo no pudimos distinguir entre escenarios climáticos alternativos a través de los valores promedio de ,, lo que enfatiza la importancia de considerar medidas múltiples para dilucidar la viabilidad poblacional. Nuestros análisis de sensibilidad demostraron que la importancia de parámetros particulares varió en los modelos y dependió de la medida de viabilidad utilizada como variable de respuesta. El parámetro de denso dependencia asociada con el reclutamiento en agua dulce consistentemente fue el más importante, independientemente de la medida de viabilidad, lo que sugiere que el incremento en la capacidad de carga de juveniles es importante para la recuperación. [source] P02 Analysis of coupled patch test reactions to nickel, cobalt and chromateCONTACT DERMATITIS, Issue 3 2004Janice Hegewald Concomitant sensitizations to Nickel, Cobalt and Chromate are often observed among patch test patients. However, the reasons for being sensitized to two or more of these substances are not completely understood. Examination of IVDK (http://www.ivdk.org) patch test results with multivariate procedures has been conducted to further elucidate the mechanisms involved with these sensitizations and potential exposure factors that may have led to the concomitant sensitizations. Gender, age, occupational dermatitis, and construction work were considered and examined with multivariate logistic regression models with the dependent response variable being concurrent reactions to a metal pair versus no reactions. In addition to the aforementioned anamnestic data, examination of a poly-sensitizations variable (reactions to 1, 2, or 3 standard series allergens other than Nickel, Cobalt or Chromate) provided information regarding general susceptibility to positive patch test reactions. Combined reactions to Cobalt and Chromate were strongly linked to construction work (OR = 11.23 (7.46, 16.90)) and occupational dermatitis. Female patch test patients had a higher odds of a positive patch test reaction to both Nickel and Cobalt (OR = 4.73 (3.81, 5.87)). Sensitization to other, unrelated standard series substances was associated with concurrent reactions to all of the metal pairs. The association between construction work and Cobalt-Chromate reactions corresponds with the hypothesis that cement exposures lead to cobalt-chromate sensitizations. Individual susceptibility to delayed-type sensitizations, as represented by the poly-sensitization variable, also appears to be associated with coupled sensitizations to metals and warrants further examination. [source] Tributaries influence recruitment of fish in large riversECOLOGY OF FRESHWATER FISH, Issue 4 2009B. M. Pracheil Abstract,,, Recent work demonstrates that tributary inputs are important community reorganisation points for river biota; however, no studies have examined the long-term effects of tributary inputs on fish population dynamics. This study examines nearly 40 years of young-of-year (yoy) paddlefish recruitment data to investigate the hypothesis that tributaries influence mainstem fish population dynamics. We generated hydrological variables from daily mean flow data (1965,2007) from an impounded reach of the mainstem Missouri River and from the Niobrara River, a relatively unaltered tributary, using Indicators of Hydrologic Alteration software. Three multiple regression models using natural-log transformed catch per unit effort (log cpue) as the response variable were created using (1) Missouri River-only flow variables, (2) Niobrara River-only flow variables and (3) Missouri River and Niobrara River flow variables. Flow variables from the Niobrara River explain a greater proportion of yoy paddlefish log cpue variability demonstrating that tributaries can positively impact fish population dynamics in altered rivers. [source] Statistical analysis of temperature impact on daily hospital admissions: analysis of data from Udine, ItalyENVIRONMETRICS, Issue 1 2006Francesco Pauli Abstract This article is devoted to the analysis of the relationship between the health status of an urban population and meteorological variables. The analysis considers daily number of hospital admissions, not due to surgery, regarding the population resident in the Municipality of Udine, aged 75 and over. Hourly records on temperature, humidity, rain, atmospheric pressure, solar radiation, wind velocity and direction recorded at an observation site located near the center of Udine are considered. The study also considers hourly measures of pollutant concentrations collected by six monitoring stations. All data are relative to the summer periods of years 1995,2003. Generalized additive models (GAM) are used in which the response variable is the number of hospital admissions and is assumed to be distributed as a Poisson whose rate varies as a possibly non-linear function of the meteorological variables and variables allowing for calendar effects and pollutant concentrations. The subsequent part of the analysis explores the distribution of temperature conditional on the number of daily admissions through quantile regression. A non-linear (N-shaped) relationship between hospital admissions and temperature is estimated; temperature at 07:00 is selected as a covariate, revealing that nighttime temperature is more relevant than daytime. The quantile regression analysis points out, as expected, that the distribution of temperature on days with more admissions has higher q -quantiles with q near unity, while a clear-cut conclusion is not reached for q quantiles with q near 0. Copyright © 2005 John Wiley & Sons, Ltd. [source] Impact of twenty-first century climate change on diadromous fish spread over Europe, North Africa and the Middle EastGLOBAL CHANGE BIOLOGY, Issue 5 2009G. LASSALLE Abstract Climate change is expected to drive species ranges towards the poles and to have a strong influence on species distributions. In this study, we focused on diadromous species that are of economical and ecological importance in the whole of Europe. We investigated the potential distribution of all diadromous fish regularly encountered in Europe, North Africa and the Middle East (28 species) under conditions predicted for twenty-first century climate change. To do so, we investigated the 1900 distribution of each species in 196 basins spread across all of Europe, North Africa and the Middle East. Four levels were used to semiquantitatively describe the abundance of species, that is missing, rare, common and abundant. We then selected five variables describing the prevailing climate in the basins, the physical nature of the basins and reflecting historical events known to have affected freshwater fish distribution. Logistic regressions with a four-level ordinal response variable were used to develop species-specific models. These predictive models related the observed distribution of these species in 1900 to the most explanatory combination of variables. Finally, we selected the A2 SRES scenario and the HadCM3 (Hadley Centre Coupled Model version 3) global climate model (GCM) to obtain climate variables (temperature and precipitation) at the end of this century. We used these 2100 variables in our models and obtained maps of climatically suitable and unsuitable basins, percentages of contraction or expansion for each species. Twenty-two models were successfully built, that is there were five species for which no model could be established because their distribution range was too narrow and the Acipenser sturio model failed during calibration. All the models selected temperature or/and precipitation as explanatory variables. Responses to climate change were species-specific but could be classified into three categories: little or no change in the distribution (five species), expansion of the distribution range (three species gaining suitable basins mainly northward) and contraction of the distribution (14 species losing suitable basins). Shifting ranges were in accordance with those found in other studies and underlined the high sensitivity of diadromous fish to modifications in their environment. [source] Thresholds of economic damage by clover seed weevil (Apion fulvipes Geoff.) and lesser clover leaf weevil (Hypera nigrirostris Fab.) on white clover (Trifolium repens L.) seed cropsGRASS & FORAGE SCIENCE, Issue 4 2008L. M. Hansen Abstract Severe reductions in the seed yield of white clover can occur because of feeding by the white clover seed weevil Apion fulvipes and the lesser clover leaf weevil Hypera nigrirostris which together can reduce the seed yield by more than 0·50. From 2002 to 2006 five field experiments were carried out to investigate the relationship between the density of these two weevil species and seed yield of white clover. Damage caused by the weevils was calculated as the difference in the number of weevils and the difference in seed yield between the average of insecticide-treated and untreated plots. Loss of seed yield was expressed as a proportion of the seed yield in insecticide-treated plots, which allowed for a comparison between years as yields in insecticide-treated plots varied. A multiple regression approach was chosen in which proportional loss in seed yield was the response variable and the weevils A. fulvipes and H. nigrirostris were the independent variables. Data obtained from the experiments were used to construct the following threshold model of economic damage: [source] Intensity modulation of TMS-induced cortical excitation: Primary motor cortexHUMAN BRAIN MAPPING, Issue 6 2006Peter T. Fox Abstract The intensity dependence of the local and remote effects of transcranial magnetic stimulation (TMS) on human motor cortex was characterized using positron-emission tomography (PET) measurements of regional blood flow (BF) and concurrent electromyographic (EMG) measurements of the motor-evoked potential (MEP). Twelve normal volunteers were studied by applying 3 Hz TMS to the hand region of primary motor cortex (M1hand). Three stimulation intensities were used: 75%, 100%, and 125% of the motor threshold (MT). MEP amplitude increased nonlinearly with increasing stimulus intensity. The rate of rise in MEP amplitude was greater above MT than below. The hemodynamic response in M1hand was an increase in BF. Hemodynamic variables quantified for M1hand included value-normalized counts (VNC), intensity (z-score), and extent (mm3). All three hemodynamic response variables increased nonlinearly with stimulus intensity, closely mirroring the MEP intensity-response function. VNC was the hemodynamic response variable which showed the most significant effect of TMS intensity. VNC correlated strongly with MEP amplitude, both within and between subjects. Remote regions showed varying patterns of intensity response, which we interpret as reflecting varying levels of neuronal excitability and/or functional coupling in the conditions studied. Hum Brain Mapp, 2005. © 2005 Wiley-Liss, Inc. [source] Calcium supplementation of breeding birds: directions for future researchIBIS, Issue 4 2004S. James Reynolds Calcium is an essential nutrient for avian reproduction. Calcium-rich foods are consumed by breeding birds for production of eggshells and for provisioning chicks that are mineralizing skeletal tissues. A number of studies have documented calcium-limited reproduction, and calcium supplementation has been employed over the last decade to demonstrate degrees, causes and consequences of calcium limitation. However, supplementation studies have produced equivocal findings resulting from an absence of calcium limitation in the study species, a poorly designed supplementation procedure or both. Prior to effective calcium supplementation, many factors need to be considered. Calcium-limited breeding in birds can only be detected by monitoring breeding attempts for more than one year and by ensuring that the measured breeding parameters are sensitive to calcium availability. Natural calcium availability needs to be estimated, and daily calcium budgets for the appropriate reproductive stages determined for the study species. Most crucially, if calcium limitation of breeding is caused by secondary calcium limitation (e.g. through heavy metal toxicity), calcium supplementation will probably be ineffective. Effective calcium supplementation will then be achieved through careful planning , a study over several years using appropriate supplements (i.e. naturally occurring ones used by breeding birds), applied at the appropriate time of year (i.e. prelaying and/or chick-rearing phases) and using a response variable that is highly sensitive to calcium availability. If properly planned and performed, calcium supplementation is a cost-effective and potent tool for the study of bird breeding biology. [source] Using habitat distribution models to evaluate large-scale landscape priorities for spatially dynamic speciesJOURNAL OF APPLIED ECOLOGY, Issue 1 2008Regan Early Summary 1Large-scale conservation planning requires the identification of priority areas in which species have a high likelihood of long-term persistence. This typically requires high spatial resolution data on species and their habitat. Such data are rarely available at a large geographical scale, so distribution modelling is often required to identify the locations of priority areas. However, distribution modelling may be difficult when a species is either not recorded, or not present, at many of the locations that are actually suitable for it. This is an inherent problem for species that exhibit metapopulation dynamics. 2Rather than basing species distribution models on species locations, we investigated the consequences of predicting the distribution of suitable habitat, and thus inferring species presence/absence. We used habitat surveys to define a vegetation category which is suitable for a threatened species that has spatially dynamic populations (the butterfly Euphydryas aurinia), and used this as the response variable in distribution models. Thus, we developed a practical strategy to obtain high resolution (1 ha) large scale conservation solutions for E. aurinia in Wales, UK. 3Habitat-based distribution models had high discriminatory power. They could generalize over a large spatial extent and on average predicted 86% of the current distribution of E. aurinia in Wales. Models based on species locations had lower discriminatory power and were poorer at generalizing throughout Wales. 4Surfaces depicting the connectivity of each grid cell were calculated for the predicted distribution of E. aurinia habitat. Connectivity surfaces provided a distance-weighted measure of the concentration of habitat in the surrounding landscape, and helped identify areas where the persistence of E. aurinia populations is expected to be highest. These identified successfully known areas of high conservation priority for E. aurinia. These connectivity surfaces allow conservation planning to take into account long-term spatial population dynamics, which would be impossible without being able to predict the species' distribution over a large spatial extent. 5Synthesis and applications. Where species location data are unsuitable for building high resolution predictive habitat distribution models, habitat data of sufficient quality can be easier to collect. We show that they can perform as well as or better than species data as a response variable. When coupled with a technique to translate distribution model predictions into landscape priority (such as connectivity calculations), we believe this approach will be a powerful tool for large-scale conservation planning. [source] Should biomass be considered more frequently as a currency in terrestrial arthropod community analyses?JOURNAL OF APPLIED ECOLOGY, Issue 2 2007MICHEL SAINT-GERMAIN Summary 1Community structure involving large taxonomical groups is frequently used to assess changes in ecosystems along environmental gradients or in response to disturbance. For terrestrial arthropods, abundance is generally used as the response variable in community data analyses; biomass, however, is generally a better indicator of the functionality of a species within a community, as it is strongly correlated with metabolism. 2In this study, we considered whether biomass should be used more often in community analyses with terrestrial arthropod biodiversity data, particularly when asking questions involving strong functional components. We selected 10 previously published and five unpublished Coleoptera abundance data sets, and produced biomass species-by-sample matrices using body length to body mass conversion equations, and then compared the results obtained using commonly used ecological analyses. 3Correlations between species abundance and biomass varied from strong to poor, depending on the taxa considered and on the sampling method used. We show that abundance and biomass can produce different results in community data analysis and lead to alternative interpretations for data sets with poor abundance to biomass correlations. 4Synthesis and applications. When dealing with databases showing poor abundance to biomass relationships, the question of the relevance of using biomass instead of abundance emerges, and the choice of the response variable to be used in analyses should be considered carefully. At the very least, when studying terrestrial arthropod biodiversity, one should consider the use of biomass with simple conversion equations that do not require obtaining the mass of individual specimens. This approach may lead to different interpretations. For research questions in which trophic interactions may play an important role, biomass may provide a broader and more accurate picture of the processes driving changes in community structure. [source] Predicting habitat distribution and frequency from plant species co-occurrence dataJOURNAL OF BIOGEOGRAPHY, Issue 6 2007Christine Römermann Abstract Aim, Species frequency data have been widely used in nature conservation to aid management decisions. To determine species frequencies, information on habitat occurrence is important: a species with a low frequency is not necessarily rare if it occupies all suitable habitats. Often, information on habitat distribution is available for small geographic areas only. We aim to predict grid-based habitat occurrence from grid-based plant species distribution data in a meso-scale analysis. Location, The study was carried out over two spatial extents: Germany and Bavaria. Methods, Two simple models were set up to examine the number of characteristic plant species needed per grid cell to predict the occurrence of four selected habitats (species data from FlorKart, http://www.floraweb.de). Both models were calibrated in Bavaria using available information on habitat distribution, validated for other federal states, and applied to Germany. First, a spatially explicit regression model (generalized linear model (GLM) with assumed binomial error distribution of response variable) was obtained. Second, a spatially independent optimization model was derived that estimated species numbers without using spatial information on habitat distribution. Finally, an additional uncalibrated model was derived that calculated the frequencies of 24 habitats. It was validated using NATURA2000 habitat maps. Results, Using the Bavarian models it was possible to predict habitat distribution and frequency from the co-occurrence of habitat-specific species per grid cell. As the model validations for other German federal states were successful, the models were applied to all of Germany, and habitat distribution and frequencies could be retrieved for the national scale on the basis of habitat-specific species co-occurrences per grid cell. Using the third, uncalibrated model, which includes species distribution data only, it was possible to predict the frequencies of 24 habitats based on the co-occurrence of 24% of formation-specific species per grid cell. Predicted habitat frequencies deduced from this third model were strongly related to frequencies of NATURA2000 habitat maps. Main conclusions, It was concluded that it is possible to deduce habitat distributions and frequencies from the co-occurrence of habitat-specific species. For areas partly covered by habitat mappings, calibrated models can be developed and extrapolated to larger areas. If information on habitat distribution is completely lacking, uncalibrated models can still be applied, providing coarse information on habitat frequencies. Predicted habitat distributions and frequencies can be used as a tool in nature conservation, for example as correction factors for species frequencies, as long as the species of interest is not included in the model set-up. [source] Stress-induced dynamic adjustments of reproduction differentially affect fitness components of a semi-arid plantJOURNAL OF ECOLOGY, Issue 1 2008Cristina F. Aragón Summary 1Summer drought stress is considered the primary constraint to plant performance in Mediterranean ecosystems. However, little is known about the implications of summer stress for plant reproduction under real field conditions and, particularly, for the regulatory mechanisms of maternal investment in reproduction. 2The relationship between plant physiological status at different reproductive stages over the course of the summer drought period and final reproductive output was modelled in the Mediterranean semi-arid specialist Helianthemum squamatum. 3Plant physiological status, assessed by the chlorophyll fluorescence-based parameter Fv/Fm, and soil moisture content beneath each plant, were determined in the field at five key phenological moments in a total of 88 plants. We used Generalized Linear Mixed Models to evaluate the effect of plant physiological status at those different dates on several components of reproduction (number of flowers and seeds per plant, fruit-set and intra-fruit seed abortion). We included soil moisture as an additional predictor to statistically control its potential effect on reproduction. 4Fv/Fm measured at midday was a significant predictor of reproductive output, but its significance varied over time and with the specific reproductive response variable. Fv/Fm measured at the onset of flowering was positively related to the number of flowers and seeds per plant, whereas Fv/Fm at the fruiting peak positively affected fruit-set. Soil moisture content was only significant when measured before flowering, being positively related to total flowers and seeds. The effect of stress on reproductive output acted either at an early stage of the reproductive season, by varying the number of flowers produced and seed primordia initiated, or at a later stage, by adjusting the number or ripe fruits. 5Synthesis. Our results show a direct relationship between physiological status and reproduction, and highlight the importance of the timing of stress for reproductive success. They also show that small departures from the physiological optimum at specific reproductive stages may cause significant decreases in the reproductive output. We suggest that the dynamic adjustment of reproduction in response to stress is adaptive in fluctuating and unpredictable Mediterranean semi-arid environments, where an adequate temporal distribution of maternal resources determines the species' ability to withstand severe environmental conditions. [source] Applying the Liu-Agresti Estimator of the Cumulative Common Odds Ratio to DIF Detection in Polytomous ItemsJOURNAL OF EDUCATIONAL MEASUREMENT, Issue 4 2003Randall D. Penfield Liu and Agresti (1996) proposed a Mantel and Haenszel-type (1959) estimator of a common odds ratio for several 2 × J tables, where the J columns are ordinal levels of a response variable. This article applies the Liu-Agresti estimator to the case of assessing differential item functioning (DIF) in items having an ordinal response variable. A simulation study was conducted to investigate the accuracy of the Liu-Agresti estimator in relation to other statistical DIF detection procedures. The results of the simulation study indicate that the Liu-Agresti estimator is a viable alternative to other DIF detection statistics. [source] OPTIMIZATION OF A CHOCOLATE PEANUT SPREAD USING RESPONSE SURFACE METHODOLOGY (RSM)JOURNAL OF SENSORY STUDIES, Issue 3 2004C.A. CHU ABSTRACT Response surface methodology was used to optimize formulations of chocolate peanut spread. Thirty-six formulations with varying levels of peanut (25-90%), chocolate (5-70%) and sugar (5-55%) were processed using a three-component constrained simplex lattice design. The processing variable, roast (light, medium, dark) was also included in the design. Response variables, measured with consumers (n = 60) participating in the test, were spreadability, overall acceptability, appearance, color, flavor, sweetness and texture/mouthfeel, using a 9-point hedonic scale. Regression analysis was performed and models were built for each significant (p < 0.01) response variable. Contour plots for each attribute, at each level of roast, were generated and superimposed to determine areas of overlap. Optimum formulations (consumer acceptance rating of , 6.0 for all attributes) for chocolate peanut spread were all combinations of 29-65% peanut, 9-41% chocolate, and 17-36% sugar, adding up to 100%, at a medium roast. Verification of two formulations indicated no difference between predicted and observed values. [source] Ion-pair mediated transport of angiotensin, neurotensin, and their metabolites in liquid phase microextraction under acidic conditionsJOURNAL OF SEPARATION SCIENCE, JSS, Issue 11 2005J. Léon E. Reubsaet Abstract This paper discusses the behaviour of angiotensin 1 and neurotensin together with their metabolites in a three-phase liquid phase microextraction under acidic conditions. Variations in donor phase, organic phase, and acceptor phase are studied with extraction recovery as response variable. It is proved that for all peptides the transport across the organic phase is mediated by heptane-1-sulphonic acid. n -Octanol gave overall best results as organic phase. A donor phase volume of 1.0 mL was chosen as a compromise between optimal recovery and robustness of the LPME device. The optimal pH of the donor phase (using acceptor phase of pH 2) was found to be different for the peptides, which opens opportunities for selective sample preparation. Decreasing the acceptor phase pH to 1.0 resulted in increased extraction recoveries. On using 1.0 mL of donor phase containing 50 mM heptane-1-sulphonic acid pH 3, n -octanol as organic phase immobilized in the pores of the fibre, and 20 ,L of acceptor phase containing 0.1 mol/L HCl, extraction recoveries up to 82% (enrichment factor = 41) were achieved. To our knowledge this is the first report on liquid phase microextraction of angiotensins and neurotensins. [source] A spatial model for the needle losses of pine-trees in the forests of Baden-Württemberg: an application of Bayesian structured additive regressionJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 1 2007Nicole H. Augustin Summary., The data that are analysed are from a monitoring survey which was carried out in 1994 in the forests of Baden-Württemberg, a federal state in the south-western region of Germany. The survey is part of a large monitoring scheme that has been carried out since the 1980s at different spatial and temporal resolutions to observe the increase in forest damage. One indicator for tree vitality is tree defoliation, which is mainly caused by intrinsic factors, age and stand conditions, but also by biotic (e.g. insects) and abiotic stresses (e.g. industrial emissions). In the survey, needle loss of pine-trees and many potential covariates are recorded at about 580 grid points of a 4 km × 4 km grid. The aim is to identify a set of predictors for needle loss and to investigate the relationships between the needle loss and the predictors. The response variable needle loss is recorded as a percentage in 5% steps estimated by eye using binoculars and categorized into healthy trees (10% or less), intermediate trees (10,25%) and damaged trees (25% or more). We use a Bayesian cumulative threshold model with non-linear functions of continuous variables and a random effect for spatial heterogeneity. For both the non-linear functions and the spatial random effect we use Bayesian versions of P -splines as priors. Our method is novel in that it deals with several non-standard data requirements: the ordinal response variable (the categorized version of needle loss), non-linear effects of covariates, spatial heterogeneity and prediction with missing covariates. The model is a special case of models with a geoadditive or more generally structured additive predictor. Inference can be based on Markov chain Monte Carlo techniques or mixed model technology. [source] Generalized additive models for location, scale and shapeJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 3 2005R. A. Rigby Summary., A general class of statistical models for a univariate response variable is presented which we call the generalized additive model for location, scale and shape (GAMLSS). The model assumes independent observations of the response variable y given the parameters, the explanatory variables and the values of the random effects. The distribution for the response variable in the GAMLSS can be selected from a very general family of distributions including highly skew or kurtotic continuous and discrete distributions. The systematic part of the model is expanded to allow modelling not only of the mean (or location) but also of the other parameters of the distribution of y, as parametric and/or additive nonparametric (smooth) functions of explanatory variables and/or random-effects terms. Maximum (penalized) likelihood estimation is used to fit the (non)parametric models. A Newton,Raphson or Fisher scoring algorithm is used to maximize the (penalized) likelihood. The additive terms in the model are fitted by using a backfitting algorithm. Censored data are easily incorporated into the framework. Five data sets from different fields of application are analysed to emphasize the generality of the GAMLSS class of models. [source] Non-parametric habitat models with automatic interactionsJOURNAL OF VEGETATION SCIENCE, Issue 6 2006Bruce McCune Abstract Questions: Can a statistical model be designed to represent more directly the nature of organismal response to multiple interacting factors? Can multiplicative kernel smoothers be used for this purpose? What advantages does this approach have over more traditional habitat modelling methods? Methods: Non-parametric multiplicative regression (NPMR) was developed from the premises that: the response variable has a minimum of zero and a physiologically-determined maximum, species respond simultaneously to multiple ecological factors, the response to any one factor is conditioned by the values of other factors, and that if any of the factors is intolerable then the response is zero. Key features of NPMR are interactive effects of predictors, no need to specify an overall model form in advance, and built-in controls on overfitting. The effectiveness of the method is demonstrated with simulated and real data sets. Results: Empirical and theoretical relationships of species response to multiple interacting predictors can be represented effectively by multiplicative kernel smoothers. NPMR allows us to abandon simplistic assumptions about overall model form, while embracing the ecological truism that habitat factors interact. [source] Mixture and mixture,process variable experiments for pharmaceutical applicationsPHARMACEUTICAL STATISTICS: THE JOURNAL OF APPLIED STATISTICS IN THE PHARMACEUTICAL INDUSTRY, Issue 4 2004Christine M. Anderson-Cook Abstract Many experiments in research and development in the pharmaceutical industry involve mixture components. These are experiments in which the experimental factors are the ingredients of a mixture and the response variable is a function of the relative proportion of each ingredient, not its absolute amount. Thus the mixture ingredients cannot be varied independently. A common variation of the mixture experiment occurs when there are also one or more process factors that can be varied independently of each other and of the mixture components, leading to a mixture,process variable experiment. We discuss the design and analysis of these types of experiments, using tablet formulation as an example. Our objective is to encourage greater utilization of these techniques in pharmaceutical research and development. Copyright © 2004 John Wiley & Sons Ltd. [source] Selecting explanatory variables with the modified version of the Bayesian information criterionQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 6 2008gorzata Bogdan Abstract We consider the situation in which a large database needs to be analyzed to identify a few important predictors of a given quantitative response variable. There is a lot of evidence that in this case classical model selection criteria, such as the Akaike information criterion or the Bayesian information criterion (BIC), have a strong tendency to overestimate the number of regressors. In our earlier papers, we developed the modified version of BIC (mBIC), which enables the incorporation of prior knowledge on a number of regressors and prevents overestimation. In this article, we review earlier results on mBIC and discuss the relationship of this criterion to the well-known Bonferroni correction for multiple testing and the Bayes oracle, which minimizes the expected costs of inference. We use computer simulations and a real data analysis to illustrate the performance of the original mBIC and its rank version, which is designed to deal with data that contain some outlying observations. Copyright © 2008 John Wiley & Sons, Ltd. [source] A unified approach to estimation of nonlinear mixed effects and Berkson measurement error modelsTHE CANADIAN JOURNAL OF STATISTICS, Issue 2 2007Liqun Wang Abstract Mixed effects models and Berkson measurement error models are widely used. They share features which the author uses to develop a unified estimation framework. He deals with models in which the random effects (or measurement errors) have a general parametric distribution, whereas the random regression coefficients (or unobserved predictor variables) and error terms have nonparametric distributions. He proposes a second-order least squares estimator and a simulation-based estimator based on the first two moments of the conditional response variable given the observed covariates. He shows that both estimators are consistent and asymptotically normally distributed under fairly general conditions. The author also reports Monte Carlo simulation studies showing that the proposed estimators perform satisfactorily for relatively small sample sizes. Compared to the likelihood approach, the proposed methods are computationally feasible and do not rely on the normality assumption for random effects or other variables in the model. Une stratégie d'estimation commune pour les modèles non linéaires à effets mixtes et les modèles d'erreur de mesure de Berkson Les modèles à effets mixtes et les modèles d'erreur de mesure de Berkson sont très usités. Ils par-tagent certaines caractéristiques que l'auteur met à profit pour élaborer une stratégie d'estimation commune. II considère des modèles dans lesquels la loi des effets aléatoires (ou des erreurs de mesure) est paramé-trique tandis que celles des coefficients de régression aléatoires (ou de variables exogènes non observées) et des termes d'erreur ne le sont pas. II propose une estimation des moindres carrés au second ordre et une approche par simulation fondées sur les deux premiers moments conditionnels de la variable endogène, sachant les variables exogènes observées. Les deux estimateurs s'avèrent convergents et asymptotiquement gaussiens sous des conditions assez générales. L'auteur fait aussi état d'études de Monte-Carlo attestant du bon comportement des deux estimations dans des échantillons relativement petits. Les méthodes proposées ne posent aucune difficulté particulière au plan numérique et au contraire de l'approche par vraisemblance, ne supposent ni la normalité des effets aléatoires, ni celle des autres variables du modèle. [source] Goodness-of-fit tests for parametric models in censored regressionTHE CANADIAN JOURNAL OF STATISTICS, Issue 2 2007Juan Carlos Pardo-Fernández Abstract The authors propose a goodness-of-fit test for parametric regression models when the response variable is right-censored. Their test compares an estimation of the error distribution based on parametric residuals to another estimation relying on nonparametric residuals. They call on a bootstrap mechanism in order to approximate the critical values of tests based on Kolmogorov-Smirnov and Cramér-von Mises type statistics. They also present the results of Monte Carlo simulations and use data from a study about quasars to illustrate their work. Tests d'ajustement pour des modèles de régression paramétriques sujets à censure Les auteurs proposent un test permettant de juger de l'adéquation d'un modèle de régression paramétrique dont la variable réponse est sujette à une censure à droite. Leur test compare une estimation de la loi des erreurs déduite de résidus paramétriques à une autre estimation fondée sur des résidus non paramétriques. Ils font appel à une technique de rééchantillonnage pour approximer les valeurs critiques de tests fondés sur des statistiques de type Kolmogorov-Smirnov et Cramér-von Mises. Ils présentent aussi les résultats d'une étude de Monte-Carlo et illustrent leur propos à l'aide de données issues de travaux portant sur les quasars. [source] Estimation of regression parameters in missing data problemsTHE CANADIAN JOURNAL OF STATISTICS, Issue 2 2006Donald L. Mcleish Abstract Let Y be a response variable, possibly multivariate, with a density function f (y|x, v; ,) conditional on vectors x and v of covariates and a vector , of unknown parameters. The authors consider the problem of estimating , when the values taken by the covariate vector v are available for all observations while some of those taken by the covariate x are missing at random. They compare the profile estimator to several alternatives, both in terms of bias and standard deviation, when the response and covariates are discrete or continuous. Estimation des paramètres de régression en I'absence de certaines données Soit Y une variable réponse uni- ou multi-dimensionnelle et soit f(y|x, v; ,) sa densité étant donné des vecteurs x et v de covariables et un vecteur , de paramètres inconnus. Les auteurs s'intéressent à l'estimation de , lorsque la valeur de v est disponible pour toutes les observations, mais que certaines valeurs de x sont manquantes au hasard. Us comparent l'estimateur profil à diverses autres solutions, tant en terme de biais que d'écart-type, selon que la variable réponse et les covariables sont discrètes ou continues. [source] Variable strength of top-down effects in Nothofagus forests: bird predation and insect herbivory during an ENSO eventAUSTRAL ECOLOGY, Issue 4 2009C. NOEMI MAZIA Abstract Predators are thought to play a key role in controlling herbivory, thus having positive indirect effects on plants. However, evidence for terrestrial trophic cascades is still fragmentary, perhaps due to variation in top-down forces created by environmental heterogeneity. We examined the magnitude of predation effects on foliar damage by chewing insects and mean leaf size, by excluding birds from saplings in ,dry' and ,wet'Nothofagus pumilio forests in the northern Patagonian Andes, Argentina. The experiment lasted 2 years encompassing a severe drought during the La Niña phase of a strong El Niño/Southern Oscillation event, which was followed by unusually high background folivory levels. Insect damage was consistently higher in wet than in dry forest saplings. In the drought year (1999), bird exclusion increased folivory rates in both forests but did not affect tree leaf size. In the ensuing season (2000), leaf damage was generally twice as high as in the drought year. As a result, bird exclusion not only increased the extent of folivory but also significantly decreased sapling leaf size. The latter effect was stronger in the wet forest, suggesting compensation of leaf area loss by dry forest saplings. Overall, the magnitude of predator indirect effects depended on the response variable measured. Insectivorous birds were more effective at reducing folivory than at facilitating leaf area growth. Our results indicate that bird-initiated trophic cascades protect N. pumilio saplings from insect damage even during years with above-normal herbivory, and also support the view that large-scale climatic events influence the strength of trophic cascades. [source] KERNEL DENSITY ESTIMATION WITH MISSING DATA AND AUXILIARY VARIABLESAUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 3 2009Suzanne R. Dubnicka Summary In most parametric statistical analyses, knowledge of the distribution of the response variable, or of the errors, is important. As this distribution is not typically known with certainty, one might initially construct a histogram or estimate the density of the variable of interest to gain insight regarding the distribution and its characteristics. However, when the response variable is incomplete, a histogram will only provide a representation of the distribution of the observed data. In the AIDS Clinical Trial Study protocol 175, interest lies in the difference in CD4 counts from baseline to final follow-up, but CD4 counts collected at final follow-up were incomplete. A method is therefore proposed for estimating the density of an incomplete response variable when auxiliary data are available. The proposed estimator is based on the Horvitz,Thompson estimator, and the propensity scores are estimated nonparametrically. Simulation studies indicate that the proposed estimator performs well. [source] Critical thresholds associated with habitat loss: a review of the concepts, evidence, and applicationsBIOLOGICAL REVIEWS, Issue 1 2010Trisha L. Swift A major conservation concern is whether population size and other ecological variables change linearly with habitat loss, or whether they suddenly decline more rapidly below a "critical threshold" level of habitat. The most commonly discussed explanation for critical threshold responses to habitat loss focus on habitat configuration. As habitat loss progresses, the remaining habitat is increasingly fragmented or the fragments are increasingly isolated, which may compound the effects of habitat loss. In this review we also explore other possible explanations for apparently nonlinear relationships between habitat loss and ecological responses, including Allee effects and time lags, and point out that some ecological variables will inherently respond nonlinearly to habitat loss even in the absence of compounding factors. In the literature, both linear and nonlinear ecological responses to habitat loss are evident among simulation and empirical studies, although the presence and value of critical thresholds is influenced by characteristics of the species (e.g. dispersal, reproduction, area/edge sensitivity) and landscape (e.g. fragmentation, matrix quality, rate of change). With enough empirical support, such trends could be useful for making important predictions about species' responses to habitat loss, to guide future research on the underlying causes of critical thresholds, and to make better informed management decisions. Some have seen critical thresholds as a means of identifying conservation targets for habitat retention. We argue that in many cases this may be misguided, and that the meaning (and utility) of a critical threshold must be interpreted carefully and in relation to the response variable and management goal. Despite recent interest in critical threshold responses to habitat loss, most studies have not used any formal statistical methods to identify their presence or value. Methods that have been used include model comparisons using Akaike information criterion (AIC) or t -tests, and significance testing for changes in slope or for polynomial effects. The judicious use of statistics to help determine the shape of ecological relationships would permit greater objectivity and more comparability among studies. [source] | ||||||||||||||||||||||||||||||||||||||||