Biology of Stigmacoccus asper (Hemiptera: Stigmacoccidae) in Colombian High-Andean Oak Forests

This research encompasses soil CO2 emission studies from forest and pasture couplets located in northwestern Spain, where two mature oak forest ecosystems partially cleared for pasture 5 or 50 years ago were selected to monitor soil C effluxes during 2 years. The CO2 exchanges in the soil–atmosphere interphase of forest and pasture plots were seasonally determined using portable infrared gas analysers. At the same time, soil samples from both forest and pasture ecosystems were used to carry out long-term incubations under laboratory conditions. Solid-state 13C-NMR with cross-polarization/magic angle spinning was applied to determine the deforestation effects on soil organic matter (SOM) composition. Pasture implantation caused a notable decline of the labile C pool and a decrease in the total soil C, with an increase in both the SOM humification and the relative concentration of phenolic and carboxyl C. After only 5 years, the deforestation caused a general decrease in the soil CO2 emissions with reduced seasonal fluctuations, these effects being even more intense 50 years after clearing. The correlation observed in oak forests between the CO2 measured in situ and the soil temperature, is masked in pasture ecosystems by the high summer soil dryness. After the partial disappearance of soil C stocks caused by deforestation, a new long-term C input/output equilibrium seems to be established, probably due to the joint adaptation of both SOM and microbial communities in the old pasture soil; however, the entire soil C retention capacity remains still degraded as compared with the original uncleared forest ecosystem.

1. Recently, a mutualistic relationship has been described between some dung beetles (Thorectes lusitanicus and Mycotrupes lethroides) and oak species (Quercus suber, Q. canariensis, and Q. rubra), which could be crucial for ensuring seedling recruitment and sustaining the equilibrium of oak populations. For T. lusitanicus, a diet based on acorns during the reproductive period improved resistance to low-temperature conditions and improved ovarian development. 2. In this paper, we conducted field and laboratory experiments to investigate the interaction between two potential acorn-eating beetles, Thorectes baraudi and Jekelius nitidus, with Quercus suber. We determined the feeding preferences of both beetle species and estimated the rates of acorn manipulation by beetles according to habitat structure and several characteristics of the acorn, such as seed size and acorn infestation by weevils. 3. Results demonstrated the positive interaction between the dung beetle Thorectes baraudi and Quercus trees. Thorectes baraudi was clearly more attracted to volatiles of acorns than to dung. Jekelius nitidus, on the contrary, was either not or anecdotally attracted to acorns. On the contrary, in the case of Jekelius nitidus, the acorn attraction could be considered anecdotal or even accidental. Our field results demonstrated the acorn burying behaviour of T. baraudi in the oak forests of the Cabaneros National Park (Spain), suggesting a potential role of this beetle species as an active secondary acorn disperser. 4. This unexpected behaviour could be particularly important in Mediterranean oak forests and savannahs, where most Quercus species are strongly recruitment limited because of serious overgrazing problems.

The effect of biopesticide compound spinosad in different concentrations was tested for the first time under laboratory conditions against the rapidly spreading forest pest, oak lace bug (Corythucha arcuata, Say 1832), and its effects were compared with the synthetic pesticide lambda-cyhalothrin. These results revealed a significant effect of spinosad at 2 mL/4 L and 2 mL/2 L water concentrations against C. arcuata nymphs. The mortality rate after 3 days was similar to synthetic insecticide effects and reached 94% and 98%, respectively. Overall, it can be concluded that spinosad is an effective biological method to control oak lace bug; treatments under field conditions should consider the high diversity of other insects in oak forests.

Individual pharmacokinetic parameters quantify the pharmacokinetics of an individual, while population pharmacokinetic parameters quantify population mean kinetics, interindividual kinetic variability, and residual variability, including intraindividual variability and measurement error. Individual pharmacokinetics are estimated by fitting a pharmacokinetic model to individual data. Population pharmacokinetic parameters have traditionally been estimated by doing this separately for each individual, and then combining the individual parameter estimates, the Standard Two Stage (STS) approach. Another approach, NONMEM, appropriately pools data across individuals and is therefore less dependent on individual parameter estimates. This study provides further evidence of NONMEM's validity and usefulness by comparing both approaches on simulated routine-type pharmacokinetic data arising from a monoexponential model. The estimates of population parameters (notably those describing interindividual variability) provided by the STS method are poorer than those provided by NONMEM, especially when there is considerable residual error. Further, NONMEM's estimates of population parameters do not require that the data be restricted to special types of routine data such as those obtained only at steady state, or only at peak or trough, nor do the estimates improve with such data. NONMEM's estimates do improve, however, when a data set is enhanced by the addition of single-observation-per-individual type data. Thus, population parameters can be estimated efficiently from data that simulate real clinical pharmacokinetic conditions.

We reviewed the literature to synthesize what is known about the use of fire to maintain and restore oak forests, woodlands, and savannas of the upper Midwestern United States, with emphasis on Minnesota, Wisconsin, and Michigan. Included are (1) known physical and ecological effects of fire on oaks from acorn through seedling, established sapling, and mature stages of the life cycle; (2) the use of fire to modify competitive interactions between oaks and mesic forest species (e.g., maple), between oaks and pines, and between oaks and grasses; (3) interaction of fire with other disturbances such as windthrow and harvesting, invasive species, and deer browsing; and (4) climate change. Throughout the report, we discuss the advantages and limitations of fire use in oak forests. We incorporate lessons learned from long-term experiments with fire, from historical evidence of fire over the centuries, and processes in areas where natural disturbances occur. We provide a brief summary of the use of fire to restore mixed oak-maple forests, mixed oak forests, mixed pine-oak forests, and oak savannas, along with take-home lessons about the complex relationships between oaks and fire.

The English grain aphid, Sitobion avenae (Fabricius), is a severe pest of wheat plants in temperate countries. Therefore, we carried out primary screening to assess the resistance or susceptibility of 23 commonly grown wheat varieties to this aphid at greenhouse and laboratory conditions in Iran. Also, population attributes of this aphid were evaluated on six wheat varieties, namely Saysonz, Arta, Moghan3, Zagros, Sardari and Shirodi. The aphids were colonized on the Hirmand wheat variety in a growth chamber at 20 ± 1°C, 60 ± 5% R.H. and a photoperiod of 14:10 (L:D). The tested varieties were grouped into three major classes including A (e.g., Shirodi, Falat and Moghan2), B (e.g., Sardari, Zagros and Tagan) and C (e.g., Arta, Saysonz, Moghan3 and Pishtaz). Also, the results of the life history traits showed that the developmental time of nymphal stage ranged from 7.5 days on Zagros to 10.8 days on Saysonz. The intrinsic rate of increase (r m ) of S. avenae varied from 0.133 (day−1) on Saysonz to 0.210 (day−1) on Shirodi. Jackknife estimates of other population parameters on these varieties were evaluated. As a result, our findings showed that the varieties Saysonz, Arta and Moghan3 were partially resistant against S. avenae, whereas Shirodi, Zagros and Sardari were relatively susceptible.

Glomeris marginata (Villers) is a widespread inhabitant of litter layers in temperate deciduous forests with both mor and mull conditions. In oak forests in The Netherlands it occurs frequently, at densities of 5–10 mature individuals per square meter. G. marginata feeds mainly on moderately decomposed litter. Under laboratory conditions, about 90% of the ingested leaf litter is returned to the soil as faecal pellets measuring approximately 1.5–2.0 × 1.0–1.5 mm and consisting mainly of leaf fragments with a surface area of up to 1 mm2. The decomposition of pellets of G. marginata on a diet of hazel leaves was studied by Nicholson et al. (1966).

This study comprehensively evaluates the antioxidant, enzyme inhibition, antiproliferative and phenolic compound analyses of the mushroom species Hortiboletus rubellus. Samples were collected from oak forests in Yalova province of Turkey and extracted under appropriate laboratory conditions. Antioxidant capacity assessments were carried out using total antioxidant status (TAS), total oxidant status (TOS), DPPH radical scavenging activity and ferric reducing antioxidant power (FRAP) tests. The results show that H. rubellus has a significant antioxidant potential. Within the scope of enzyme inhibition analyses, the inhibition potential on acetylcholinesterase (AChE), butyrylcholinesterase (BChE), α-amylase and α-glucosidase enzymes was evaluated and it was determined that the mushroom showed promise in terms of neuroprotective and antidiabetic effects. In antiproliferative activity tests, H. rubellus was found to have dose-dependent cytotoxic effect on A549 lung cancer cell line. In addition, phenolic component analyses were performed by LC-MS/MS method and it was determined that the mushroom contains phenolic components important for health such as gallic acid, protocatechuic acid, quercetin. The findings show that H. rubellus has the potential to be used in functional food and pharmaceutical areas.

Cerambyx cerdo (Cc) is a protected saproxylic beetle in Europe, although it is increasingly reported as an oak 'pest'. Cc ecological features are relatively well known, but, its reproductive biology is still poorly understood. Hence, we investigated the reproductive traits of Cc under laboratory conditions. In females, body length was 44.1 ± 0.9 mm, 28-53 (mean ± SE, range); fecundity 143 ± 11 eggs, 33-347; fertility 78 ± 1%, 65-93; oviposition period 44 ± 3 days, 13-128 and longevity 59 ± 5 days, 16-157. Fecundity was positively correlated with female size, longevity and oviposition period. Daily fecundity was 3.5 ± 0.2 eggs/day, 0.9-6.5 showing a fluctuating synovigenic pattern with a slight decreasing trend over time. Egg length was 3.74 ± 0.01 mm, 2.3-6.0 and egg volume 5.45 ± 0.04 mm3, 2.4-9.6. Egg size was correlated with female size, but, the relative size of eggs was larger in smaller females. Incubation time was 13.5 ± 0.1 days, 7-28. Hatching was superior in larger eggs and neonate size was positively correlated to egg volume. Females were polyandrous (up to 19 matings), but, multiple mating did not enhance fecundity or fertility. In males, body length was 41.8 ± 0.8 mm, 29-53 and longevity 49 ± 3 days, 9-124. Male longevity was unrelated to body size. Males were polygynous (up to 16 matings) and mating number did not affect male longevity. Overall, females were larger and lived longer than males. Cc reproductive traits are compared with those other Cerambycidae, especially with the congeneric pest Cerambyx welensii. Our data may be valuable to improve the protection/management measures of Cc in dehesa woodlands and other oak forests.

Estimation of population parameters using the generalized moment estimators under probability proportional to size sampling scheme requires that the specification parameter, k defining these moments differs from one population to the other due to varying statistical properties of the study and measure of size variables. In this study, the approximate value of the specification parameter that minimizes the anticipated mean squared error is derived and is recommended for use in determining the best estimator for target populations in probability proportional to size (PPS) sampling especially, when the correlation between the study and auxiliary (measure of size) variables is being exploited. Empirical results also confirm that the specification parameter is a useful guide in defining appropriate estimator in PPS multi-character surveys. Key words: Moment, estimation, specification parameter, transformation, correlation.

Scientific articles published 30 years earlier can be interesting to revisit for various reasons. Lewontin’s classic article on the analysis of variance in human behavioural genetics warrants continued attention for perhaps the worst of them: the article makes several correct observations that continue to remain under-appreciated in some research and much discussion about the causal role of genes in human outcomes. 1 The lucidity of Lewontin’s arguments has historically proven no match for the allure of overly simple characterizations of outcomes as being x% due to genes and (1 x)% not due to genes. 2 Moreover, Lewontin’s main points speak beyond questions about genetics and could even be said to prefigure the best parts of more recent complaints about regression analysis as a tool for causal inference in observational studies. 3 The problem is manifested in the social statistics analogue of an optical illusion: when one says x% of variance in some outcome (say, depression) is attributable to genes, one appears to be making a statement about the ultimate nature of that outcome. Heritability estimates are estimates of population parameters, however, meaning that they depend crucially on how genotypes and environments are distributed in the studied population. When calculations are made on oddly composed samples and with little information about either genotypes or environments, appropriate interpretation of precise heritability estimates can become downright mysterious. Likewise, discussions of the ‘effect’ of a risk factor on a disease are typically based on estimates of population-specific ‘average causal effects’. 4 Whenever genetic effects vary across environments and the effects of risk factors vary across persons, simple answers follow only when questions are posed in terms of aggregate characterizations of particular populations, and such answers may change radically as populations or their aggregate circumstances change. Lewontin recognized that population-dependent estimates are a poor substitute for actually understanding the specific action and interactions of causes. Lewontin erred, however, in declaring heritability estimates to be ‘useless’. Estimates of population parameters are perfectly meaningful and possibly useful when properly recognized for what they are. 5 As importantly, the cumulation of high heritability outcomes from many studies have together had the genuinely useful consequence of making headway against various unfortunate, if often well-intentioned, resistances to contemplating the genetic contribution to behaviour that remain all too pervasive in some quarters of social science. This has provided a better foundation for social science to engage data and research with genotypic measures as they become increasingly available. 6

Robust intervals for some environmental applications

In their paper, Christensen et al. 1 used data from a large Danish survey to examine the impact of non-response on estimated rates of morbidity and mortality. The key findings of this study were that non-respondents were at increased risks of all forms of morbidity/mortality when compared with respondents. Furthermore, there was evidence of heterogeneity in morbidity/mortality rates depending on the type of non-response, with those respondents who were non-contactable (n = 1539) having hazards of morbidity/mortality which were 2.51–7.70 times higher than respondents. At first sight, these figures seem alarming, and suggest substantial bias in the sample and a serious mis-estimation of morbidity/mortality rates. These conclusions are, however, somewhat misleading, and the findings are shaped by two factors that affect the interpretation of analyses using hazard rates and tests of significance. The first feature of the study design is that the overall sample (n = 39 540) is large. The use of a large sample implies that even small between-group differences will be found to be significant. The second feature of the design is that the base rates for morbidity/mortality are low, ranging from 0.10% (drug-related mortality) to 12.75% (all-cause mortality). The low base rate of morbidity/mortality implies that relatively small differences in the number of deaths between the respondent and non-respondent populations may generate large hazard rates. These features are illustrated in Table 1, which presents rates of morbidity/mortality in the respondent and each of the non-respondent groups and the total population. These comparisons show that in terms of rates of morbidity/mortality there were only small differences between the respondents and non-respondents. Although it is clear from Table 1 that there were generally small differences between groups in terms of morbidity/mortality, it is also the case that, for some applications, biases caused by using the respondent sample to calculate rates of morbidity/mortality may be of substantive importance. For example, the overall rate of mortality for the total sample was 12 746.58 deaths per 100 000, whereas the estimated rate from the respondent data was 11 249.64 per 100 000, a mortality rate that is 11.7% lower. This suggests that for some applications, such as investigations of mortality in large samples, the use of respondent-only data may lead to conceptually important differences in estimates. One interesting aspect of the analysis of the sources of bias in the present paper is the suggestion that much of the non-respondent group can be accounted for by those who were non-contactable. These findings suggest that in terms of reducing sample selection biases a major priority should be placed on minimizing rates of non-contact. In assigning this priority, however, there are a number of issues that need to be considered. Perhaps the most important issue to consider is the trade-off between overall sample size and risks of non-contact. As a general rule in most survey settings, as sample size increases the resources available to trace difficult-to-contact respondents decrease. For example, in the present study it could be proposed that rates of non-contact could have been reduced by reducing the sample size by (for example) 50% and spending the funding saved on improved methods of respondent tracing. The literature in this area suggests that there are a number of strategies that can be used to reduce non-contact rates in surveys. These include the use of personally addressed hand-signed letters 2, using repeat contact via telephone and mailing 3, using monetary incentives 4 or using face-to-face contact 5. A final issue that needs consideration is that the paper by Christensen et al. examines the impacts of non-response on estimates of population rates. While estimation of population rates is of general interest, the focus of many longitudinal studies is upon the associations between risk factors and outcomes. There is considerable reason to believe that estimates of such associations are less likely to be influenced by sample attrition than estimates of population rates. As shown by Gustavson et al., for sample attrition to adversely affect estimates of associations high levels of attrition must exist in both the risk factor and outcome measures 6. In summary, the paper by Christensen et al. 1 adds to the growing literature on sample attrition in longitudinal research. Consistent with most previous research, the study found that the impacts of sample attrition on estimates of population statistics are detectable but relatively modest. These findings clearly suggest that findings from longitudinal studies subject to attrition should be treated as providing 'ballpark' estimates of population parameters, and that care should be taken in drawing inferences based on these estimates. None.

Objective: Construction of a geographic filter for identification in MEDLINE of studies with Spanish filiation, through a modular structure (filter A and/or B).Methods: We used the Boolean Association of different equations. E1: Spain in different languages. E2: Autonomous communities. E3: Spanish cities of more than 100000 inhabitants. E4: Spanish cities where a hospital is located. The pattern of comparison was the filter published by Sanz-Valero et al (Med Segur Trab. 2008;54:75-83). The study sample was obtained through the estimation of population parameters with simple random sampling without replacement. In order to assess the adequacy of the results, the precision and sensitivity indicators were calculated.Results: From the application of the filters, the following data were obtained: filter A 534353, filter B 407315 and filter pattern 437688 references. The adequacy of the results was calculated with precision and sensitivity indicators, the one of filter A was 82.12%, filter B 100% and of the pattern 96.63%. The relevance of 82.12%, 100% and 96.63% respectively and the sensitivity of 100.26%, 93.06% and 96.63%.Conclusion: It was proved the suitability of the proposed filter, with high sensitivity and relevance, noting the validity of the filter used as a «gold standard».

When running a computer simulation it is often a matter of debate whether the run length is sufficient to yield an 'acrruate' estimate of population parameters. Since the run could continue indefinitely, the population is potentially infinite and no limited sample will provide perfect point estimates. However, confidence intervals can be computed in the customary fashion, with options to vary sample size, confidence level and degree of precision. For example, suppose it is desired to estimate the true utilization rate, ϕ, for some facility. The simulation run yields the sample utilization rate, [EQUATION], for the total run length. If the assumptions of the Central Limit Theorem can be applied,[EQUATION]where 100 (l - α) is the level of confidence selected and the sample size is assumed to exceed 30 to justify the general use of z statistics.