Direct inhibition of maintenance respiration in western hemlock roots exposed to ambient soil carbon dioxide concentrations

Root respiration often exhibits a direct and immediate decline with increasing concentrations of ambient soil carbon dioxide concentration ([CO(2)]), and recent evidence suggests this decline may be attributable to a decline in maintenance respiration within the root. If true, this concept could provide a clue to the biochemical process underlying respiratory inhibition as well as improve our knowledge of the timing and degree to which this inhibition occurs in nature. To test the hypothesis that maintenance respiration exhibits a direct, negative response to increasing [CO(2)], we measured total respiration in intact root systems of western hemlock (Tsuga heterophylla (Raf.) Sarg.) seedlings grown at different relative growth rates and exposed to soil [CO(2)]s ranging from 91 to 7008 &mgr;mol mol(-1). Analysis of covariance was used to separate maintenance from total respiration. Total respiration declined exponentially with increasing [CO(2)]. Maintenance respiration, which comprised 85% of total respiration over all treatments, also declined exponentially with increasing [CO(2)]. Growth respiration was not inhibited at any [CO(2)]. These findings may explain why roots of some fast-growing species do not show [CO(2)] inhibition.     

Shoot development and dieback in progenies of Nothofagus obliqua

Shoot growth and dieback were compared among progenies of nursery-grown seedlings of Nothofagus obliqua belonging to seven progenies of the same provenance (Quila-Quina, Argentina). First-year shoots consisted of one growth unit (GU) and second-year shoots of one or two GUs. The probability of development of two GU was similar for all progenies. Progenies were different in terms of shoot size, terminal bud abscission, the extent of shoot dieback after shoot extension and the node of origin of the relay shoot on the first shoot. Plants with a second-year shoot consisting of two GUs had a thicker stem and more nodes than those with single-GU shoots. The selection of N. obliqua seed trees based on architectural traits suitable for forestry development at specific sites must contemplate variability among progenies and their probabilities of successful development under different conditions.     

A regression-based equivalence test for model validation: shifting the burden of proof

Model validation is often realized as a test of how well model predictions match a set of independent observations. One would think that the burden of proof should rest with the model, to force it to show that it can make accurate predictions. Further, one would think that increasing the sample size ought to increase the model's ability to demonstrate its utility. Traditional statistical tools are inappropriate for this because they default to the case that the model and the data are no different, and their ability to detect differences increases with the sample size. These traditional tools are optimized to detect differences, rather than similarities. We present an alternative strategy for model validation that is based on regression and statistical tests of equivalence. Equivalence tests reverse the usual null hypothesis: they posit that the populations being compared are different and use the data to prove otherwise. In this sense, equivalence tests are lumping tests, whereas the traditional statistical tests are splitting tests. To date, model validation with equivalence tests has focused on comparisons of means. Our proposed test checks not only for similarity of means, but also for similarity between individual predictions and observations. The strategy is demonstrated using three case studies that differ in their modeling objectives, and for varied sample sizes. The proposed strategy provides a formal means of model validation that is superior to traditional statistical tests in each case.     

Changes in understory species diversity during theNothofagus pumilio forest management cycle

Human commercial activities must be compatible with sustainable management to achieve species conservation in the natural environment. After harvesting, diversity and abundance of understory species differ substantially from the pre-harvest situation. Have knowledge of the changes that logging produces in all components of the system allows us to develop management alternatives with reduced impacts. The objective of this work was to evaluate changes in density, biomass and diversity of understory species along a forest shelterwood cut system management cycle in aNothofagus pumilio forest. Six forest management situations (postharvesting stands and different phases of forest development) were sampled in a pureN. pumilio forest of Tierra del Fuego (Argentina) of middle-high site class (fromclass I toIII). Species number, density and biomass were modified substantially after a shelterwood cut. These were being greatest after cutting and falling substantially when the forest canopy closes during theinitial growth phase, returning to values similar to this virgin forest when themature phase was reached. The impact of the forest management on understory species diversity is analyzed and discussed. The silvicultural practices applied toN. pumilio forest in Tierra del Fuego permit the introduction of alien flora to the system, and produce great changes during the forest management cycle. To Celina Matteri, Itatí Ferraro, and Rosa Kofalt for their aid in taxonomical identification. To Juan Manuel Cellini, Ricardo Vukasovic and Gregorio Martínez Pastur for their participation in the field work; and to the sawmillLos Castores, Universidad Nacional de la Patagonia Austral, Centro Austral de Investigaciones Científicas and Instituto Nacional de Tecnología Agropecuaria for the institutional and financial support.     

Time-series analysis of delta13C from tree rings. I. Time trends and autocorrelation

Univariate time-series analyses were conducted on stable carbon isotope ratios obtained from tree-ring cellulose. We looked for the presence and structure of autocorrelation. Significant autocorrelation violates the statistical independence assumption and biases hypothesis tests. Its presence would indicate the existence of lagged physiological effects that persist for longer than the current year. We analyzed data from 28 trees (60-85 years old; mean = 73 years) of western white pine (Pinus monticola Dougl.), ponderosa pine (Pinus ponderosa Laws.), and Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. glauca) growing in northern Idaho. Material was obtained by the stem analysis method from rings laid down in the upper portion of the crown throughout each tree's life. The sampling protocol minimized variation caused by changing light regimes within each tree. Autoregressive moving average (ARMA) models were used to describe the autocorrelation structure over time. Three time series were analyzed for each tree: the stable carbon isotope ratio (delta(13)C); discrimination (delta); and the difference between ambient and internal CO(2) concentrations (c(a) - c(i)). The effect of converting from ring cellulose to whole-leaf tissue did not affect the analysis because it was almost completely removed by the detrending that precedes time-series analysis. A simple linear or quadratic model adequately described the time trend. The residuals from the trend had a constant mean and variance, thus ensuring stationarity, a requirement for autocorrelation analysis. The trend over time for c(a) - c(i) was particularly strong (R(2) = 0.29-0.84). Autoregressive moving average analyses of the residuals from these trends indicated that two-thirds of the individual tree series contained significant autocorrelation, whereas the remaining third were random (white noise) over time. We were unable to distinguish between individuals with and without significant autocorrelation beforehand. Significant ARMA models were all of low order, with either first- or second-order (i.e., lagged 1 or 2 years, respectively) models performing well. A simple autoregressive (AR(1)), model was the most common. The most useful generalization was that the same ARMA model holds for each of the three series (delta(13)C, delta, c(a) - c(i)) for an individual tree, if the time trend has been properly removed for each series. The mean series for the two pine species were described by first-order ARMA models (1-year lags), whereas the Douglas-fir mean series were described by second-order models (2-year lags) with negligible first-order effects. Apparently, the process of constructing a mean time series for a species preserves an underlying signal related to delta(13)C while canceling some of the random individual tree variation. Furthermore, the best model for the overall mean series (e.g., for a species) cannot be inferred from a consensus of the individual tree model forms, nor can its parameters be estimated reliably from the mean of the individual tree parameters. Because two-thirds of the individual tree time series contained significant autocorrelation, the normal assumption of a random structure over time is unwarranted, even after accounting for the time trend. The residuals of an appropriate ARMA model satisfy the independence assumption, and can be used to make hypothesis tests.     

Estimating CO(2) flux from snowpacks at three sites in the Rocky Mountains

Soil surface CO(2) flux (F(s)) is the dominant respiratory flux in many temperate forest ecosystems. Snowpacks increase this dominance by insulating the soil against the low temperature to which aboveground components are exposed. However, measurement of F(s) in winter may be impeded by snow cover. Likewise, developing annual F(s) models is complicated by seasonal variation in root and microbial metabolism. We compared three methods of measuring sub-snow F(s): (1) dynamic chamber measurements at the upper snowpack surface (F(snow)), (2) dynamic chamber measurements at the soil surface via snowpits (F(soil)), and (3) static estimates based on measured concentrations of carbon dioxide ([CO(2)]) and conductance properties of the snowpack (F(diffusional)). Methods were compared at a mid-elevation forest in northeastern Washington, a mid-elevation forest in northern Idaho, and a high-elevation forest and neighboring meadow in Wyoming. The methods that minimized snowpack disturbance, F(diffusional) and F(snow), yielded similar estimates of F(s). In contrast, F(soil) yielded rates two to three times higher than F(snow) at the forested sites, and seven times higher at the subalpine meadow. The ratio F(soil)/F(snow) increased with increasing snow depth when compared across all sites. Snow removal appears to induce elevated soil flux as a result of lateral CO(2) diffusion into the pit. We chose F(snow) as our preferred method and used it to estimate annual CO(2) fluxes. The snowpack was present for 36% of the year at this site, during which time 132 g C m(-2), or 17% of the annual flux, occurred. We conclude that snowpack CO(2) flux is quantitatively important in annual carbon budgets for these forests and that the static and dynamic methods yield similar and reasonable estimates of the flux, as long as snowpack disturbance is minimized.     

A KCNJ10 mutation previously identified in the Russell group of terriers also occurs in Smooth-Haired Fox Terriers with hereditary ataxia and in related breeds

Background

Hereditary ataxias with similar phenotypes were reported in the Smooth-Haired Fox Terrier, the Jack Russell Terrier and the Parson Russell Terrier. However, segregation analyses showed differing inheritance modes in these breeds. Recently, molecular genetic studies on the Russell group of terriers found independent mutations in KCNJ10 and CAPN1, each associated with a specific clinical subtype of inherited ataxia. The aim of this study was to clarify whether or not Smooth-Haired Fox Terriers with hereditary ataxia and dogs of other related breeds harbor either of the same mutations. A sub goal was to update the results of KCNJ10 genotyping in Russell group terriers.

Findings

Three Smooth-Haired Fox Terriers with hereditary ataxia and two Toy Fox Terriers with a similar phenotype were all homozygous for the KCNJ10 mutation. The same mutation was also found in a heterozygous state in clinically unaffected Tenterfield Terriers (n = 5) and, in agreement with previous studies, in Jack Russell Terriers, Parson Russell Terriers, and Russell Terriers.

Conclusions

A KCNJ10 mutation, previously associated with an autosomal recessive spinocerebellar ataxia in Jack Russell Terriers, Parson Russell Terriers, and Russell Terriers segregates in at least three more breeds descended from British hunting terriers. Ataxic members of two of these breeds, the Smooth-Haired Fox Terrier and the Toy Fox Terrier, were homozygous for the mutation, strengthening the likelihood that this genetic defect is indeed the causative mutation for the disease known as “hereditary ataxia” in Fox Terriers and “spinocerebellar ataxia with myokymia, seizures or both” in the Russell group of terriers.     

Demographic factors associated with the diet quality of older US men: baseline data from the Osteoporotic Fractures in Men (MrOS) study

OBJECTIVE: Throughout the world, the proportion of the male population aged 65 years and older is increasing. Yet, we have limited information regarding diet quality and predictors of diet quality in this segment of the population. The objectives of the current analyses are to describe the diet quality of a cohort of men >65 years of age, and identify lifestyle factors associated with poor diet quality. METHODS: We present a cross-sectional analysis of the diet quality of 5928 men, aged 65-100 years, who are participants in the Osteoporotic Fractures in Men (MrOS) cohort study. Dietary intake was determined using a modified Block 98 food-frequency questionnaire. Diet quality was calculated using the previously validated Diet Quality Index-Revised (DQI-R). Univariate and multivariate modelling was used to estimate the variance in diet quality predicted by a number of sociodemographic factors, including age, race/ethnicity, body mass index (BMI), marital status, education, smoking status, physical activity, self-perceived health and nutritional supplement use. RESULTS: Overall, we found that in this geographically diverse group of older men, diet quality was low, with a mean modified DQI-R for the entire study population of 62.5 (standard deviation 13.1) out of an ideal of 100. Further, younger age, very low total calorie intake (< or = 1187 kcal day- 1), higher BMI, residence in a North or Southeast community, being of African-American or Hispanic race, being less educated, not using dietary supplements and smoking were each significant independent predictors of a poorer diet. CONCLUSION: These data may prove useful in both understanding the dietary intake of older US men as it relates to published dietary guidelines, and for targeting future dietary intervention programmes.