Tree mortality of five major species on Hokkaido Island, northern Japan

The mortality rates of five major tree species (Abies sachalinensis, Acer mono, Magnolia obovata, Quercus crispula, Tilia japonica) on Hokkaido Island, northern Japan were modeled using logistic regressions based on the long-term observation of 8929 individuals in 65 permanent plots. Individual size, recent growth, one-sided and two-sided interactions with neighbors, climatic and topographic factors were used as independent variables in the logistic regressions, and relevant variables were selected using the stepwise method. For all species analyzed, the final models significantly explained tree mortality rates. The regression analyses indicated that individual size and/or recent growth had effects on tree mortality. A significant effect of one-sided interaction on tree mortality was detected for three species, and a significant effect of two-sided interaction was detected for two species. The interactions with neighbors were not necessarily competitive. For all species analyzed, climatic and topographic factors affected tree mortality. The mortality models obtained can be used for forest dynamics simulations. One ecological question was examined using these models. Species that can grow fast in forest stands with smaller basal areas tended to have high mortality rates in forest stands with larger basal areas. Some ecological characteristics of the analyzed species are described based on the results of the regressions.     

Understanding home range behaviour and resource selection of invasive common brushtail possums (Trichosurus vulpecula) in urban environments

Because invasive species are often opportunistic and behaviourally flexible, they tend to be successful in urban landscapes, where they may use space differently than in their more traditional habitats. Consequently, control strategies developed for invasive pest species in non-urban areas may not succeed in an urban context. Using GPS tracking, we examined habitat use by an invasive pest, the brushtail possum (Trichosurus vulpecula) in residential New Zealand habitats; these habitats comprise a large proportion of the urban landscape and are currently not targeted for pest control. We predicted that home ranges of possums in residential areas would be larger than those in non-urban habitats due to lower densities of their primary food resource, plant material; that possums would prefer forest fragment habitat; and that they would avoid roads due to the mortality risk. Home range sizes estimated using mechanistic Brownian bridges and 100 % minimum convex polygons were smaller or similar in size to those recorded in rural and forest habitats. Resource utilization functions and the regression of utilization distribution probabilities against environmental variables showed that possums selected forest fragments primarily, followed by residential habitat characterised by large gardens with a degree of vegetative structural complexity. Roads were not avoided. Control operations should expand their scope to include residential areas containing mature, diverse vegetation rather than only focussing on forest fragments, a strategy that ignores biodiversity values in residential habitats, and is likely to be unsuccessful due to reinvasion potential from neighbouring residential areas.     

Stem Mortality Following Fire in Kalahari Sand Vegetation: Effects of Frost,Prior Damage,and Tree Neighbourhoods

Fire is a key factor affecting the survivorship and dynamics of woody plants in savannas, but few empirical studies in savanna vegetation have investigated correlates of mortality following fire at the level of individual stems. A study of stem mortality as a function of size, neighbourhood effects, and prior damage (mainly caused by elephants) was undertaken in an area of Kalahari sand vegetation in western Zimbabwe. Stem and whole-plant mortality were quantified for the dominant stems of 557 trees in 4 plots following dry season unplanned fires in 2001. Two plots were located in areas that had been affected by frost earlier in the season, and 2 in areas that had not. Mortality was also recorded for 1762 trees in 20 unburned reference plots, also classified according to the presence of frost damage. Mortality estimators were constructed with a maximum likelihood regression method. Whole-plant mortality was low (on the order of 1–2%) compared with stem mortality, which in burned plots approximated 100% for the smallest size classes and declined as a function of stem diameter. Fire-driven mortality was lower in stems protected by the crowns of larger trees than in stems that were in the open. There was also evidence to suggest that the effects of fire are exacerbated by the prior action of frost and elephant herbivory.     

Effects of introduced ungulates on forest understory communities in northern Patagonia are modified by timing and severity of stand mortality

Natural disturbances such as fires, windstorms, floods, and herbivory often act on plant communities, affecting their structure and the abundance and composition of their species. Most research has focused on the effects of single disturbances on plant communities whereas the synergistic effects of several disturbances have received less attention. In this study, we evaluated how timing and severity of tree mortality modified plant use by introduced deer and early post-mortality successional trajectories in northern Patagonian conifer forests. We sampled understory composition and deer use in Austrocedrus chilensis (ciprés de la cordillera) forest stands undergoing varying timing and severity of forest mortality as reconstructed using dendroecological techniques. In addition, we evaluated the effect of fallen logs on plant composition and deer use of plants by monitoring areas of massive dieback where fallen logs had been removed for fire hazard reduction, and nearby control areas not subjected to such removal. Stepwise regression analyses showed that history and severity of tree mortality strongly influence plant composition and deer use of plants. For deer use (with pellet counts and browsing index as response variables), results showed a positive relationship with degree of stand mortality and a negative relationship with cover of fallen logs. Similarly, cover of unpalatable shrub species was explained by canopy mortality history, whereas cover of palatable shrub species was positively associated with severity of canopy mortality. In areas where fallen logs had been removed, pellet counts were six times higher than those in control areas. Though total shrub species cover was similar between log removal and control areas, proportion of unpalatable shrubs increased in areas where fallen logs had been removed. In conclusion, deer use of plants was strongly limited by tall fallen logs, allowing palatable species to establish and grow. Fallen log removal accelerated deer entrance and changed understory composition toward more browse-resistant and unpalatable species. These results underscore the importance of considering the dynamics (timing, severity, and extent) of fallen woody debris influencing understory herbivory and post-disturbance succession. In addition, experimental results underpin the importance of maintaining snags and large woody debris in disturbed landscapes where salvage logging is a routine procedure.     

An analysis of heat effects in different subpopulations of Bangladesh

A substantial number of epidemiological studies have demonstrated an association between atmospheric conditions and human all-cause as well as cause-specific mortality. However, most research has been performed in industrialised countries, whereas little is known about the atmosphere–mortality relationship in developing countries. Especially with regard to modifications from non-atmospheric conditions and intra-population differences, there is a substantial research deficit. Within the scope of this study, we aimed to investigate the effects of heat in a multi-stratified manner, distinguishing by the cause of death, age, gender, location and socio-economic status. We examined 22,840 death counts using semi-parametric Poisson regression models, adjusting for a multitude of potential confounders. Although Bangladesh is dominated by an increase of mortality with decreasing (equivalent) temperatures over a wide range of values, the findings demonstrated the existence of partly strong heat effects at the upper end of the temperature distribution. Moreover, the study demonstrated that the strength of these heat effects varied considerably over the investigated subgroups. The adverse effects of heat were particularly pronounced for males and the elderly above 65 years. Moreover, we found increased adverse effects of heat for urban areas and for areas with a high socio-economic status. The increase in, and acceleration of, urbanisation in Bangladesh, as well as the rapid aging of the population and the increase in non-communicable diseases, suggest that the relevance of heat-related mortality might increase further. Considering rising global temperatures, the adverse effects of heat might be further aggravated.     

Geographic Analysis of Urologist Density and Prostate Cancer Mortality in the United States

Context

Financial and demographic pressures in US require an understanding of the most efficient distribution of physicians to maximize population-level health benefits. Prior work has assumed a constant negative relationship between physician supply and mortality outcomes throughout the US and has not addressed regional variation.

Methods

In this ecological analysis, geographically weighted regression was used to identify spatially varying relationships between local urologist density and prostate cancer mortality at the county level. Data from 1,492 counties in 30 eastern and southern states from 2006–2010 were analyzed.

Findings

The ordinary least squares (OLS) regression found that, on average, increasing urologist density by 1 urologist per 100,000 people resulted in an expected decrease in prostate cancer mortality of -0.499 deaths per 100,000 men (95% CI -0.709 to -0.289, p-value < 0.001), or a 1.5% decrease. Geographic weighted regression demonstrated that the addition of one urologist per 100,000 people in counties in the southern Mississippi River states of Arkansas, Mississippi, and Louisiana, as well as parts of Illinois, Indiana, and Wisconsin is associated with decrease of 0.411 to 0.916 in prostate cancer mortality per 100,000 men (1.6–3.6%). In contrast, the urologist density was not significantly associated with the prostate state mortality in the new England region.

Conclusions

The strength of association between urologist density and prostate cancer mortality varied regionally. Those areas with the highest potential for effects could be targeted for increasing the supply of urologists, as it associated with the largest predicted improvement in prostate cancer mortality.     

An estimate of avian mortality at communication towers in the United States and Canada

Avian mortality at communication towers in the continental United States and Canada is an issue of pressing conservation concern. Previous estimates of this mortality have been based on limited data and have not included Canada. We compiled a database of communication towers in the continental United States and Canada and estimated avian mortality by tower with a regression relating avian mortality to tower height. This equation was derived from 38 tower studies for which mortality data were available and corrected for sampling effort, search efficiency, and scavenging where appropriate. Although most studies document mortality at guyed towers with steady-burning lights, we accounted for lower mortality at towers without guy wires or steady-burning lights by adjusting estimates based on published studies. The resulting estimate of mortality at towers is 6.8 million birds per year in the United States and Canada. Bootstrapped subsampling indicated that the regression was robust to the choice of studies included and a comparison of multiple regression models showed that incorporating sampling, scavenging, and search efficiency adjustments improved model fit. Estimating total avian mortality is only a first step in developing an assessment of the biological significance of mortality at communication towers for individual species or groups of species. Nevertheless, our estimate can be used to evaluate this source of mortality, develop subsequent per-species mortality estimates, and motivate policy action.     

Do well-connected landscapes promote road-related mortality?

Cost surface (CS) models have emerged as a useful tool to examine the interactions between landscapes patterns and wildlife at large-scale extents. This approach is particularly relevant to guide conservation planning for species that show vulnerability to road networks in human-dominated landscapes. In this study, we measured the functional connectivity of the landscape in southern Portugal and examined how it may be related to stone marten road mortality risk. We addressed three questions: (1) How different levels of landscape connectivity influence stone marten occurrence in montado patches? (2) Is there any relation between montado patches connectivity and stone marten road mortality risk? (3) If so, which road-related features might be responsible for the species’ high road mortality? We developed a series of connectivity models using CS scenarios with different resistance values given to each vegetation cover type to reflect different resistance to species movement. Our models showed that the likelihood of occurrence of stone marten decreased with distance to source areas, meaning continuous montado. Open areas and riparian areas within open area matrices entailed increased costs. We found higher stone marten mortality on roads in well-connected areas. Road sinuosity was an important factor influencing the mortality in those areas. This result challenges the way that connectivity and its relation to mortality has been generally regarded. Clearly, landscape connectivity and road-related mortality are not independent.     

Variation and classification of human age patterns of mortality: analysis using competing hazards models

The structure of variation in human mortality patterns is explored using a five-parameter competing hazards model and standard multivariate taxonomic procedures. The data consist of 281 national life tables representing a wide range of environmental and cultural regions of the world. A general or average age pattern of mortality was generated for the entire sample using multiple regression procedures. A K mean cluster analysis conducted on the residuals of the regression analysis identified seven distinct models of mortality that differ in characteristic ways from the general pattern. Four of the seven clusters have age patterns of mortality similar to the north, east, south, and west regions of the Coale and Demeny model life tables. The remaining three clusters represent regions of the world and age patterns of mortality that are not represented in the Coale and Demeny model life tables.     

Impact of the UK colorectal cancer screening pilot studies on incidence, stage distribution and mortality trends

Objective: To assess the impact of the UK colorectal cancer guaiac faecal occult blood test screening pilot studies on incidence trends, stage distribution and mortality trends. Design: Ecological study. Setting: Scotland and the West Midlands. Data: We extracted anonymised colorectal cancer (ICD-10 C18–C20) registration (1982–2006) and death records (1982–2007), along with corresponding mid-year population estimates. Intervention: Residents of the screening pilot areas, in the age group 50–69 years, were offered biennial guaiac faecal occult blood test screening from 2000 onwards. Screening was not offered routinely in non-pilot areas until the start of the roll-out of the national screening programmes in England and in Scotland in 2006 and 2007, respectively. Main outcome measures: We analysed trends in age-specific incidence and mortality rates, and Dukes’ stage distribution. Within each country/region, we compared the screening pilot areas to non-screening pilot (‘control’) areas using Chi square tests and Poisson regression modelling. Results: Following the start of the screening pilots, as expected in the prevalent round of a new screening programme, in the pilot areas there was a short-lived increase in incidence of colorectal cancer among 50–69 year olds except for females in the West Midlands. A trend towards earlier stage and less advanced disease was also observed, with males showing significant increases in Dukes’ A and corresponding decreases in Dukes’ C in the screening pilot areas (all P < 0.03). With the exception of females in the West Midlands, mortality rates for colorectal cancer decreased significantly and at a faster rate in the populations invited for screening. Conclusion: The existence of a natural control population not yet invited for screening provided a unique opportunity to assess whether the benefits of colorectal cancer screening, beyond the setting of a randomised controlled trial, could be detected using routinely collected statistics. Our analysis suggests that screening will fulfil its aim of reducing mortality from colorectal cancer.     

Know Thy Enemy: Experience Affects Elk Translocation Success in Risky Landscapes

ABSTRACT To maximize success, reintroduction programs generally select predator-free release areas having high habitat quality. Past studies provide little insight into recovery efforts where multiple, potentially novel, mortality hazards occur. The ability of translocated animals to cope with novel environments can be affected by both pre- and postrelease experiences with habitat and mortality risks. We experimentally released elk (Cervus elaphus) having different background experiences into an area where predators and hunters were prevalent and habitat quality varied. Using a competing risks approach, we predicted the postrelease survival of individuals and their fidelity to release areas as a function of animal source and postrelease encounters with forage resources and areas used by wolves (Canis lupus) or humans. Mortality patterns were consistent with prerelease exposure to mortality risks but not habitat differences among source areas. Wolf predation, poaching, and legal Native hunting were equivalent in magnitude and accounted for the majority of elk mortalities. Familiarity with either wolves or hunters prior to release yielded first-year survival rates 1.9-2.2 times greater than observed for animals naive to both risks. These 2 primary sources of mortality traded off temporally as well as spatially given the proximity of roads, which wolves avoided. The prevalence of forage resources in release areas increased fidelity to release sites but coincided with higher mortality risk during the critical first year, potentially setting an ecological trap for animals naïve to local risks. Translocated individuals largely mediated their respective vulnerabilities over time, showing second-year survival rates equivalent to resident elk. In addition to using source populations that are able to adjust to mortality risks in release areas, spatial and temporal variation in mortality risks might be exploited when planning releases to increase the success of translocations into risky landscapes. (JOURNAL OF WILDLIFE MANAGEMENT 71(2):541–554; 2007)     

Quantifying Spatial Disparities in Neonatal Mortality Using a Structured Additive Regression Model

Background

Neonatal mortality contributes a large proportion towards early childhood mortality in developing countries, with considerable geographical variation at small areas within countries.

Methods

A geo-additive logistic regression model is proposed for quantifying small-scale geographical variation in neonatal mortality, and to estimate risk factors of neonatal mortality. Random effects are introduced to capture spatial correlation and heterogeneity. The spatial correlation can be modelled using the Markov random fields (MRF) when data is aggregated, while the two dimensional P-splines apply when exact locations are available, whereas the unstructured spatial effects are assigned an independent Gaussian prior. Socio-economic and bio-demographic factors which may affect the risk of neonatal mortality are simultaneously estimated as fixed effects and as nonlinear effects for continuous covariates. The smooth effects of continuous covariates are modelled by second-order random walk priors. Modelling and inference use the empirical Bayesian approach via penalized likelihood technique. The methodology is applied to analyse the likelihood of neonatal deaths, using data from the 2000 Malawi demographic and health survey. The spatial effects are quantified through MRF and two dimensional P-splines priors.

Results

Findings indicate that both fixed and spatial effects are associated with neonatal mortality.

Conclusions

Our study, therefore, suggests that the challenge to reduce neonatal mortality goes beyond addressing individual factors, but also require to understanding unmeasured covariates for potential effective interventions.     

Social deprivation and premature mortality: regional comparison across England.

OBJECTIVE--To investigate the pattern and size of the relationship between social deprivation in electoral wards and premature mortality for each health region in England. DESIGN--Ecological study using 1981 census variables and data on mortality for 1981-5. SETTING--14 regional health authorities in England. MAIN OUTCOME MEASURE--Mortality under the age of 65 years from all causes, coronary heart disease, and smoking related diseases in men and women. RESULTS--Increasing deprivation was significantly associated with mortality from all causes, coronary heart disease, and smoking related diseases. The relationship was linear with no apparent threshold. Correlation coefficients were generally greater for deaths from all causes and smoking related diseases and for men compared with women. The slope of the relationship between deprivation and mortality varied among regions. Variations in mortality still existed between regions for equal levels of deprivation. CONCLUSION--Deprivation of an area and premature mortality are strongly linked. The effects of deprivation can be seen throughout the range of affluence and are not limited to the poorest areas. Current targets for reducing coronary heart disease mortality may be achievable if the mortality in poor areas can be reduced to the rates in affluent areas.     

Risk factors associated with lambing traits

The objective of this study was to establish the risk factors associated with both lambing difficulty and lamb mortality in the Irish sheep multibreed population. A total of 135 470 lambing events from 42 675 ewes in 839 Irish crossbred and purebred flocks were available. Risk factors associated with producer-scored ewe lambing difficulty score (scale of one (no difficulty) to four (severe difficulty)) were determined using linear mixed models. Risk factors associated with the logit of the probability of lamb mortality at birth (i.e. binary trait) were determined using generalised estimating equations. For each dependent variable, a series of simple regression models were developed as well as a multiple regression model. In the simple regression models, greater lambing difficulty was associated with quadruplet bearing, younger ewes, of terminal breed origin, lambing in February; for example, first parity ewes experienced greater (P<0.001) lambing difficulty (1.56±0.02) than older ewes. The association between lambing difficulty and all factors persisted in the multiple regression model, and the trend in fixed effects level solutions did not differ from the trend observed in the simple regression models. In the simple regression analyses, a greater odds of lamb mortality was associated with male lambs (1.31 times more likely of death than females), lambs of very light (2 to 3 kg) and very heavy (>7.0 kg) birth weights, quadruplet born lambs and lambs that experienced a more difficult lambing (predicted probability of death for lambs that required severe and veterinary assistance of 0.15 and 0.32, respectively); lambs from dual-purpose breeds and born to younger ewes were also at greater risk of mortality. In the multiple regression model, the association between ewe parity, age at first lambing, year of lambing and lamb mortality no longer persisted. The trend in solutions of the levels of each fixed effect that remained associated with lamb mortality in the multiple regression model, did not differ from the trends observed in the simple regression models although the differential in relative risk between the different lambing difficulty scores was greater in the multiple regression model. Results from this study show that many common flock- and animal-level factors are associated with both lambing difficulty and lamb mortality and management of different risk category groups (e.g. scanned litter sizes, ewe age groups) can be used to appropriately manage the flock at lambing to reduce their incidence.     

Habitat connectivity for conserving cervids in a multifunctional landscape

Habitat fragmentation is a considerable threat to biodiversity worldwide. To minimize the effects of fragmentation, it is important to identify and conserve the existing habitat connections that facilitate dispersal and gene flow among populations. Connected populations are more resilient to the changing environment that affects local populations due to greater demographic stability and higher genetic diversity. Our study is the first attempt to identify the crucial habitats facilitating the dispersal of two key sympatric cervids - spotted deer Axis axis and sambar Rusa unicolor in central India. We use species distribution models followed by landscape pattern analyses and connectivity analyses to delineate the essential habitats. Thereafter, we estimated the relative contribution of habitats outside protected areas in maintaining the ecological network, using graph-based metrics. We then locate and predict the areas that have a high risk of human-influenced cervid mortality using a Bayesian regression model that accounts for spatial structure in the data. The results show that about 55% of the core habitats, integrated across both species, lie outside the protected areas and are important in maintaining the ecological network for these cervids. Some peripheral habitats have an increased risk of anthropogenic cervid mortality, which poses high demographic risk. There is an urgent need to regulate the nature and intensity of human activities in areas of human-wildlife coexistence to maintain habitat connectivity and ensure the survival of wildlife populations. Our results on cervids complement analyses on connectivity for large carnivores and thus enables one to account for important trophic interactions among wildlife species in land use planning.     

Predicting Grizzly Bear Density in Western North America

Conservation of grizzly bears (Ursus arctos) is often controversial and the disagreement often is focused on the estimates of density used to calculate allowable kill. Many recent estimates of grizzly bear density are now available but field-based estimates will never be available for more than a small portion of hunted populations. Current methods of predicting density in areas of management interest are subjective and untested. Objective methods have been proposed, but these statistical models are so dependent on results from individual study areas that the models do not generalize well. We built regression models to relate grizzly bear density to ultimate measures of ecosystem productivity and mortality for interior and coastal ecosystems in North America. We used 90 measures of grizzly bear density in interior ecosystems, of which 14 were currently known to be unoccupied by grizzly bears. In coastal areas, we used 17 measures of density including 2 unoccupied areas. Our best model for coastal areas included a negative relationship with tree cover and positive relationships with the proportion of salmon in the diet and topographic ruggedness, which was correlated with precipitation. Our best interior model included 3 variables that indexed terrestrial productivity, 1 describing vegetation cover, 2 indices of human use of the landscape and, an index of topographic ruggedness. We used our models to predict current population sizes across Canada and present these as alternatives to current population estimates. Our models predict fewer grizzly bears in British Columbia but more bears in Canada than in the latest status review. These predictions can be used to assess population status, set limits for total human-caused mortality, and for conservation planning, but because our predictions are static, they cannot be used to assess population trend.     

Nonparametric methods for incorporating genomic information into genetic evaluations: an application to mortality in broilers

Four approaches using single-nucleotide polymorphism (SNP) information (F(infinity)-metric model, kernel regression, reproducing kernel Hilbert spaces (RKHS) regression, and a Bayesian regression) were compared with a standard procedure of genetic evaluation (E-BLUP) of sires using mortality rates in broilers as a response variable, working in a Bayesian framework. Late mortality (14-42 days of age) records on 12,167 progeny of 200 sires were precorrected for fixed and random (nongenetic) effects used in the model for genetic evaluation and for the mate effect. The average of the corrected records was computed for each sire. Twenty-four SNPs seemingly associated with late mortality were included in three methods used for genomic assisted evaluations. One thousand SNPs were included in the Bayesian regression, to account for markers along the whole genome. The posterior mean of heritability of mortality was 0.02 in the E-BLUP approach, suggesting that genetic evaluation could be improved if suitable molecular markers were available. Estimates of posterior means and standard deviations of the residual variance were 24.38 (3.88), 29.97 (3.22), 17.07 (3.02), and 20.74 (2.87) for E-BLUP, the linear model on SNPs, RKHS regression, and the Bayesian regression, respectively, suggesting that RKHS accounted for more variance in the data. The two nonparametric methods (kernel and RKHS regression) fitted the data better, having a lower residual sum of squares. Predictive ability, assessed by cross-validation, indicated advantages of the RKHS approach, where accuracy was increased from 25 to 150%, relative to other methods.     

Unemployment and mortality in Denmark, 1970-80.

Relative mortality in the period 1970-80 was studied among Danish men and women who were unemployed and employed on the day of the 1970 census. The study population consisted of the total labour force in the age range 20-64 on 9 November 1970--that is, about 2 million employed and 22,000 unemployed people. Relative mortality was analysed by a multiplicative hazard regression model (as a natural extension of the standardised mortality ratio) and a multiplicative regression model with extra-Poisson variation. A significantly increased death rate (40-50%) was found among the unemployed after adjusting for occupation, housing category, geographical region, and marital state. Analysis of five main causes of death showed increased mortality from all causes, but especially from suicide or accidents. In areas where the local unemployment rate was comparatively high the relative mortality among the unemployed was lower. The increased mortality among the unemployed was interpreted as a consequence of health related selection as well as increased susceptibility associated with the psychosocial stress of unemployment.     

Using Penalized Splines to Model Age‐ and Season‐of‐Birth‐Dependent Effects of Childhood Mortality Risk Factors in Rural Burkina Faso

Several previous studies have identified risk factors for childhood mortality in high risk areas, such as Sub‐Saharan Africa. Among these are lifestyle factors related for example to nutrition or sanitation. Other factors are related to social class, ethnicity and poverty in general. Few studies have investigated a dependence of these factors by age and season of birth which is the focus in this study. We perform a survival analysis of 9121 children born between 1998 and 2001 in a rural area of western Burkina Faso. The whole population is under demographic surveillance since 1993. All cause mortality is used as the endpoint and follow‐up information until the age of five years is available. Recently developed spline regression methods are used for the analysis. Ethnic group, religion, age of mother, twin status, sex, and distance to next health center are used as covariates all of which having a clear effect on survival in standard Cox regression analysis. With penalized spline regression, a more detailed risk pattern is observed. Ethnicity is more related to death at early age, as well as age of mother. The effect of the risk factors considered also appear to be related with season of birth (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)