Net atmospheric impacts of forest bioenergy production and utilization in Finnish boreal conditions

The net CO₂ exchange of forests was investigated to study net atmospheric impact of forest bioenergy production (BP) and utilization in Finnish boreal conditions. Net CO₂ exchange was simulated with a life cycle assessment tool over a 90‐year period and over the whole Finland based on National Forest Inventory data. The difference in the net exchanges between the traditional timber production (TP) and BP regime was considered the net atmospheric impact of forest bioenergy utilization. According to the results, forests became net sources of CO₂ after about 20 years of simulation, and the net exchange was higher in the BP regime than in the TP regime until the middle of the simulation period. From 2040 onwards, the net exchange started to decrease in both regimes and became higher in the TP regime, excluding the last decade of the simulation. The shift of forests to becoming a CO₂ source reflected the decrease in CO₂ sequestration due to the increasing share of recently harvested and seedling stands that are acting as sources of CO₂, and an increase of emissions from degradation of wood products. When expressed in terms of radiative forcing, the net atmospheric impact was on average 19% less for bioenergy compared with that for coal energy over the whole simulation period. The results show the importance of time dependence when considering dynamic forest ecosystems in BP and climate change mitigation. Furthermore, the results emphasize the dualistic role and possibilities of forest management in controlling the build and release of carbon into and from the stocks and in controlling the rate of the build speed, i.e. growth. This information is needed in identifying the capability and possibilities of ecosystems to produce biomass for energy, alongside other products and ecosystem services (e.g. pulp wood and timber), and simultaneously to mitigate climate change.     

Improved classification of Alzheimer's disease data via removal of nuisance variability

Diagnosis of Alzheimer's disease is based on the results of neuropsychological tests and available supporting biomarkers such as the results of imaging studies. The results of the tests and the values of biomarkers are dependent on the nuisance features, such as age and gender. In order to improve diagnostic power, the effects of the nuisance features have to be removed from the data. In this paper, four types of interactions between classification features and nuisance features were identified. Three methods were tested to remove these interactions from the classification data. In stratified analysis, a homogeneous subgroup was generated from a training set. Data correction method utilized linear regression model to remove the effects of nuisance features from data. The third method was a combination of these two methods. The methods were tested using all the baseline data from the Alzheimer's Disease Neuroimaging Initiative database in two classification studies: classifying control subjects from Alzheimer's disease patients and discriminating stable and progressive mild cognitive impairment subjects. The results show that both stratified analysis and data correction are able to statistically significantly improve the classification accuracy of several neuropsychological tests and imaging biomarkers. The improvements were especially large for the classification of stable and progressive mild cognitive impairment subjects, where the best improvements observed were 6% units. The data correction method gave better results for imaging biomarkers, whereas stratified analysis worked well with the neuropsychological tests. In conclusion, the study shows that the excess variability caused by nuisance features should be removed from the data to improve the classification accuracy, and therefore, the reliability of diagnosis making.     

Do allopatric male Calopteryx virgo damselflies learn species recognition?

There is a growing amount of empirical evidence that premating reproductive isolation of two closely related species can be reinforced by natural selection arising from avoidance of maladaptive hybridization. However, as an alternative for this popular reinforcement theory, it has been suggested that learning to prefer conspecifics or to discriminate heterospecifics could cause a similar pattern of reinforced premating isolation, but this possibility is much less studied. Here, we report results of a field experiment in which we examined (i) whether allopatric Calopteryx virgo damselfly males that have not encountered heterospecific females of the congener C. splendens initially show discrimination, and (ii) whether C. virgo males learn to discriminate heterospecifics or learn to associate with conspecifics during repeated experimental presentation of females. Our experiment revealed that there was a statistically nonsignificant tendency for C. virgo males to show initial discrimination against heterospecific females but because we did not use sexually naïve individuals in our experiment, we were not able to separate the effect of innate or associative learning. More importantly, however, our study revealed that species discrimination might be further strengthened by learning, especially so that C. virgo males increase their association with conspecific females during repeated presentation trials. The role of learning to discriminate C. splendens females was less clear. We conclude that learning might play a role in species recognition also when individuals are not naïve but have already encountered potential conspecific mates.     

Genetics of microenvironmental sensitivity of body weight in rainbow trout (Oncorhynchus mykiss) selected for improved growth

Microenvironmental sensitivity of a genotype refers to the ability to buffer against non-specific environmental factors, and it can be quantified by the amount of residual variation in a trait expressed by the genotype's offspring within a (macro)environment. Due to the high degree of polymorphism in behavioral, growth and life-history traits, both farmed and wild salmonids are highly susceptible to microenvironmental variation, yet the heritable basis of this characteristic remains unknown. We estimated the genetic (co)variance of body weight and its residual variation in 2-year-old rainbow trout (Oncorhynchus mykiss) using a multigenerational data of 45,900 individuals from the Finnish national breeding programme. We also tested whether or not microenvironmental sensitivity has been changed as a correlated genetic response when genetic improvement for growth has been practiced over five generations. The animal model analysis revealed the presence of genetic heterogeneity both in body weight and its residual variation. Heritability of residual variation was remarkably lower (0.02) than that for body weight (0.35). However, genetic coefficient of variation was notable in both body weight (14%) and its residual variation (37%), suggesting a substantial potential for selection responses in both traits. Furthermore, a significant negative genetic correlation (-0.16) was found between body weight and its residual variation, i.e., rapidly growing genotypes are also more tolerant to perturbations in microenvironment. The genetic trends showed that fish growth was successfully increased by selective breeding (an average of 6% per generation), whereas no genetic change occurred in residual variation during the same period. The results imply that genetic improvement for body weight does not cause a concomitant increase in microenvironmental sensitivity. For commercial production, however, there may be high potential to simultaneously improve weight gain and increase its uniformity if both criteria are included in a selection index.     

Synthesis and Enzymatic Deprotection of Fully Protected 2′‐5′ Oligoadenylates (2‐5A): Towards a Prodrug Strategy for Short 2‐5A

Fully protected pA2′p5′A2′p5′A trimers 1a and 1b have been prepared as prodrug candidates for a short 2′‐5′ oligoadenylate, 2‐5A, and its 3′‐O‐Me analog, respectively. The kinetics of hog liver carboxyesterase (HLE)‐triggered deprotection in HEPES buffer (pH 7.5) at 37° has been studied. The deprotection of 1a turned out to be very slow, and 2‐5A never appeared in a fully deprotected form. By contrast, a considerable proportion of 1b was converted to the desired 2‐5A trimer, although partial removal of the 3′‐O‐[(acetyloxy)methyl] group prior to exposure of the adjacent phosphodiester linkage resulted in 2′,5′→3′,5′ phosphate migration and release of adenosine as side reactions.     

Survival of male Tengmalm’s owls increases with cover of old forest in their territory

The loss and fragmentation of forest habitats have been considered to pose a worldwide threat to the viability of forest-dwelling animals, especially to species that occupy old forests. We investigated whether the annual survival of sedentary male Tengmalm’s owls Aegolius funereus was associated with the cover of old coniferous forests in Finland. Survival and recapture probabilities varied annually with density changes in populations of the main prey (Microtus voles). When this variation was controlled for, and relationships between survival and proportions of the three different forest age classes (old-growth, middle-aged, and young) were modeled separately, the old-growth model was the most parsimonious. Survival increased with the cover of old forest, although the extent of old forest within owl territories was relatively small (mean ∼12%, range 2–37%). This association, however, varied among years and appeared especially in years of increasing vole abundance. At such times, old forests may sustain high populations of bank voles Clethrionomys glareolus, shrews and small passerines. In addition, old forests may serve as refuges against large avian predator species, such as Ural owls Strix uralensis and goshawks Accipiter gentilis. Our results suggest that changes in habitat quality created by agriculture and forestry may have the potential to reduce adult survival, an essential component of fitness and population viability.     

Cholesterol substitution increases the structural heterogeneity of caveolae

Caveolin-1 binds cholesterol and caveola formation involves caveolin-1 oligomerization and cholesterol association. The role of cholesterol in caveolae has so far been addressed by methods that compromise membrane integrity and abolish caveolar invaginations. To study the importance of sterol specificity for the structure and function of caveolae, we replaced cholesterol in mammalian cells with its immediate precursor desmosterol by inhibiting 24-dehydrocholesterol reductase. Desmosterol could substitute for cholesterol in maintaining cell growth, membrane integrity, and preserving caveolar invaginations. However, in desmosterol cells the affinity of caveolin-1 for sterol and the stability of caveolin oligomers were decreased. Moreover, caveolar invaginations became more heterogeneous in dimensions and in the number of caveolin-1 molecules per caveola. Despite the altered caveolar structure, caveolar ligand uptake was only moderately inhibited. We found that in desmosterol cells, Src kinase phosphorylated Cav1 at Tyr(14) more avidly than in cholesterol cells. Taken the role of Cav1 Tyr(14) phosphorylation in caveolar endocytosis, this may help to preserve caveolar uptake in desmosterol cells. We conclude that a sterol C24 double bond interferes with caveolin-sterol interaction and perturbs caveolar morphology but facilitates Cav1 Src phosphorylation and allows caveolar endocytosis. More generally, substitution of cholesterol by a structurally closely related sterol provides a method to selectively modify membrane protein-sterol affinity, structure and function of cholesterol-dependent domains without compromising membrane integrity.     

Biomechanical testing in experimental bone interventions--May the power be with you

Total variation in any measured variable, in conjunction with expected treatment effect, defines the minimum sample size (minSS) required to detect the expected effect with statistical confidence should the effect truly exist. A comprehensive literature survey of 3472 original studies was carried out to identify studies with biomechanical testing of whole bones. Total variation in common biomechanical traits and expected treatment effects in typical interventions were statistically determined. According to this survey, total variation in biomechanical traits between different species of experimental animals was similar, justifying the use of rat femur as a model in further analyses. Due to poorer precision, stiffness and energy absorption assessment require substantially larger sample size than breaking load. Due to same reason, minSS for femoral neck compression test is considerably larger than for femoral shaft three-point bending test. For the bending test, minSS to show a 10% treatment effect in the breaking load with 80% statistical power is 11rats/group, while corresponding minSS is 23 for the stiffness, and 53 for the energy absorption. For the femoral neck compression test, minSSs are 16, 51, and 134rats/group, respectively. Among the reviewed studies, the mean sample size was 11animals/group. This underscores the need for considerably larger sample sizes in experimental bone interventions which employ mechanical traits as primary outcome variables. In particular, poor precision and generally small expected treatment effects compromise the utility of stiffness and energy absorption assessments in experimental bone interventions.     

Carbon fluxes from a tropical peat swamp forest floor

A tropical ombrotrophic peatland ecosystem is one of the largest terrestrial carbon stores. Flux rates of carbon dioxide (CO₂) and methane (CH₄) were studied at various peat water table depths in a mixed‐type peat swamp forest floor in Central Kalimantan, Indonesia. Temporary gas fluxes on microtopographically differing hummock and hollow peat surfaces were combined with peat water table data to produce annual cumulative flux estimates. Hummocks formed mainly from living and dead tree roots and decaying debris maintained a relatively steady CO₂ emission rate regardless of the water table position in peat. In nearly vegetation‐free hollows, CO₂ emission rates were progressively smaller as the water table rose towards the peat surface. Methane emissions from the peat surface remained small and were detected only in water‐saturated peat. By applying long‐term peat water table data, annual gas emissions from the peat swamp forest floor were estimated to be 3493±316 g CO₂ m^?2 and less than 1.36±0.57 g CH₄ m^?2. On the basis of the carbon emitted, CO₂ is clearly a more important greenhouse gas than CH₄. CO₂ emissions from peat are the highest during the dry season, when the oxic peat layer is at its thickest because of water table lowering.