Winter Temperature Variability Research Articles

A genotype, environment and management (GxExM) analysis of adaptation in winter wheat to climate change in Denmark

Wheat yields in Europe have shown stagnating trends during the last two decades, partly attributed to climate change. Such developments challenge the needs for increased production, in particular at higher latitudes, to meet increasing global demands and expected productivity reductions at lower latitudes. Climate change projections from three General Circulation Models or GCMs (UKMO-HadGEM1, INM-GM3.0 and CSIRO-Mk3.1) for the A1FI SRES emission scenario for 2000 to 2100 were downscaled at a northern latitude location (Foulum, Denmark) using LARS-WG5.3. The scenarios accounted for changes in temperature, precipitation and atmospheric CO2 concentration. In addition, three temperature-variability scenarios were included assuming different levels of decreased temperature variability in winter and increased in summer. Crop yield was simulated for the different climate change scenarios by a calibrated version of AFRCWHEAT2 to model several combinations of genotypes (varying in crop growth, development and tolerance to water and nitrogen scarcity) and management (sowing dates and nitrogen fertilization rate). The simulations showed a slight improvement of grain yields (0.3–1.2Mgha−1) in the medium-term (2030–2050), but not enough to cope with expected increases in demand for food and feed. Optimum management added up to 1.8Mgha−1. Genetic modifications regarding winter wheat crop development exhibit the greatest sensitivity to climate and larger potential for improvement (+3.8Mgha−1). The results consistently points towards need for cultivars with a longer reproductive phases (2.9–7.5% per 1°C) and lower photoperiod sensitivities. Due to the positive synergies between several genotypic characteristics, multiple-target breeding programmes would be necessary, possibly assisted by model-based assessments of optimal phenotypic characteristics.

Holocene moisture variations across China and driving mechanisms: A synthesis of climatic records

Based on the review of 33 Holocene moisture reconstructions that passed quality scrutiny, temporal and spatial patterns of regional moisture variations are delineated. The regionally-averaged moisture index from Xinjiang demonstrates that the moisture index has been persistently climbing since ∼10 ka cal BP and that the period between ∼4 and ∼0 ka cal BP is the Holocene Moisture Optimum. Comparison of the moisture index of Xinjiang region with the winter climate of northern Europe leads us to propose that the Holocene moisture variations in Xinjiang region have been controlled by the winter temperature variations in the North Atlantic region. The regionally-averaged moisture index from the Tibetan Plateau shows that the moisture has been persistently declining since ∼11 ka cal BP and that the period between ∼11.5 and 7.5 ka cal BP was the Holocene Moisture Optimum. The parallel trends between the moisture level in the Tibetan Plateau and the Indian summer monsoon strength retrieved from the Arabian Sea suggest that the Tibetan Plateau has been under influence of the Indian summer monsoon throughout the Holocene. The regionally-averaged moisture index curves from Northern China and Southern China are the delayed reflections of the East Asian summer monsoon strength to the solar radiation. That is, the peak insolation was responded by the Holocene “Oceanic Thermal Optimum” with significant time lags and the “Oceanic Thermal Optimum” was then responded by the “Holocene Moisture Optimum” in southern China and northern China also with some time lags. The differences in the moisture-index curve shapes and in the durations of the “Holocene Moisture Optimum” between northern China and southern China suggest that the strength of the East Asian summer monsoon had gradually transgressed northward in the early Holocene and gradually regressed southward in the late Holocene.

Future trend of extreme value distributions of wintertime surface air temperatures over Korea and the associated physical changes

Daily winter temperatures in Korea have been analyzed via CSEOF analysis. Then, each PC time series was detrended and was fitted to an AR (autoregressive) model. Based on the identified AR model, an artificial time series of arbitrary length can be generated by using an arbitrary white-noise time series. In this way, one hundred new sets of PC time series were generated over the period of 1973–2058. Then, the trend for each PC time series was added back to the artificial PC time series extending the trend until 2058. Ultimately, artificial daily winter temperatures in Korea have been constructed by using the artificial PC time series and the original loading vectors derived from the observational data. The 100 new data sets have been investigated in order to understand the winter temperature variability 50 years into the future. Regression analysis in CSEOF space shows that temperature increase in Korea is associated with increased 850-hPa air temperature over most of the Asian domain (97°-153°E × 22°-73°N) and increased 850-hPa geopotential height in the southern part of the domain. As a result, southerly and southeasterly wind anomalies develop carrying positive temperature anomalies northward and northwestward. Both the 200-hPa air temperature and geopotential height changes indicate that there will be fairly significant northward shift of the jet stream in future. The standard deviation of the 200-hPa potential vorticity increases implying that shortwave trough and henceforth baroclinic instability will increase in future. Finally, GEV (Generalized Extreme Value) distribution and GPD (Generalized Pareto distribution) distribution have been compared between the observational records and the future records of the same length. The extreme value distributions based on the synthetic datasets show that warm extreme events will be more extreme in future and cold extreme events, on the other hand, will be less extreme. This study provides an estimate of future temperatures based on the observational data and serves as an independent baseline solution for comparisons with numerical model solutions.

Searching for the bull's eye: agents and targets of selection vary among geographically disparate cyanogenesis clines in white clover (Trifolium repens L.).

The recurrent evolution of adaptive clines within a species can be used to elucidate the selective factors and genetic responses that underlie adaptation. White clover is polymorphic for cyanogenesis (HCN release with tissue damage), and climate-associated cyanogenesis clines have evolved throughout the native and introduced species range. This polymorphism arises through two independently segregating Mendelian polymorphisms for the presence/absence of two required components: cyanogenic glucosides and their hydrolyzing enzyme linamarase. Cyanogenesis is commonly thought to function in herbivore defense; however, the individual cyanogenic components may also serve other physiological functions. To test whether cyanogenesis clines have evolved in response to the same selective pressures acting on the same genetic targets, we examined cyanogenesis cline shape and its environmental correlates in three world regions: southern New Zealand, the central United States and the US Pacific Northwest. For some regional comparisons, cline shapes are remarkably similar despite large differences in the spatial scales over which clines occur (40-1600 km). However, we also find evidence for major differences in both the agents and targets of selection among the sampled clines. Variation in cyanogenesis frequency is best predicted using a combination of minimum winter temperature and aridity variables. Together, our results provide evidence that recurrent adaptive clines do not necessarily reflect shared adaptive processes.

Impact of the dominant large‐scale teleconnections on winter temperature variability over East Asia

AbstractMonthly mean geopotential height for the past 33 DJF seasons archived in Modern Era Retrospective analysis for Research and Applications reanalysis is decomposed into the large‐scale teleconnection patterns to explain their impacts on winter temperature variability over East Asia. Following Arctic Oscillation (AO) that explains the largest variance, East Atlantic/West Russia (EA/WR), West Pacific (WP) and El Niño–Southern Oscillation (ENSO) are identified as the first four leading modes that significantly explain East Asian winter temperature variation. While the northern part of East Asia north of 50°N is prevailed by AO and EA/WR impacts, temperature in the midlatitudes (30°N–50°N), which include Mongolia, northeastern China, Shandong area, Korea, and Japan, is influenced by combined effect of the four leading teleconnections. ENSO impact on average over 33 winters is relatively weaker than the impact of the other three teleconnections. WP impact, which has received less attention than ENSO in earlier studies, characterizes winter temperatures over Korea, Japan, and central to southern China region south of 30°N mainly by advective process from the Pacific. Upper level wave activity fluxes reveal that, for the AO case, the height and circulation anomalies affecting midlatitude East Asian winter temperature is mainly located at higher latitudes north of East Asia. Distribution of the fluxes also explains that the stationary wave train associated with EA/WR propagates southeastward from the western Russia, affecting the East Asian winter temperature. Investigation on the impact of each teleconnection for the selected years reveals that the most dominant teleconnection over East Asia is not the same at all years, indicating a great deal of interannual variability. Comparison in temperature anomaly distributions between observation and temperature anomaly constructed using the combined effect of four leading teleconnections clearly show a reasonable consistency between them, demonstrating that the seasonal winter temperature distributions over East Asia are substantially explained by these four large‐scale circulation impacts.

Conditional cold avoidance drives between-population variation in germination behaviour in Calluna vulgaris

Across their range, widely distributed species are exposed to a variety of climatic and other environmental conditions, and accordingly may display variation in life history strategies. For seed germination in cold climates, two contrasting responses to variation in winter temperature have been documented: first, an increased ability to germinate at low temperatures (cold tolerance) as winter temperatures decrease, and secondly a reduced ability to germinate at low temperatures (cold avoidance) that concentrates germination towards the warmer parts of the season. Germination responses were tested for Calluna vulgaris, the dominant species of European heathlands, from ten populations collected along broad-scale bioclimatic gradients (latitude, altitude) in Norway, covering a substantial fraction of the species' climatic range. Incubation treatments varied from 10 to 25 °C, and germination performance across populations was analysed in relation to temperature conditions at the seed collection locations. Seeds from all populations germinated rapidly and to high final percentages under the warmer incubation temperatures. Under low incubation temperatures, cold-climate populations had significantly lower germination rates and percentages than warm-climate populations. While germination rates and percentages also increased with seed mass, seed mass did not vary along the climatic gradients, and therefore did not explain the variation in germination responses. Variation in germination responses among Calluna populations was consistent with increased temperature requirements for germination towards colder climates, indicating a cold-avoidance germination strategy conditional on the temperature at the seeds' origin. Along a gradient of increasing temperatures this suggests a shift in selection pressures on germination from climatic adversity (i.e. low temperatures and potential frost risk in early or late season) to competitive performance and better exploitation of the entire growing season.

Where Are the Bluebirds of the Bluegrass? Eastern Bluebird Decline in Central Kentucky

Eastern bluebird (Sialia sialis) populations are increasing across most of the species' range; however, we document a decline in a bluebird population in central Kentucky, where state and local Christmas Bird Count and Breeding Bird Survey data indicate bluebirds are declining throughout the Ohio River valley region. We examined several possible hypotheses for this decline, including habitat loss, nest cavity loss, increased competition from other species, and variation in winter temperature using long term nesting data gathered at one study site in central Kentucky. We found that bluebird abundance was positively correlated with mean temperature during the previous winter. Our data suggest bluebirds in central Kentucky are declining because they are susceptible to cold winters and are experiencing increased nest box competition.

The variability of winter temperature, its impacts on society, and the potential use of seasonal forecasts in Finland

The variability of winter temperature, its impacts on society, and the potential use of seasonal forecasts in Finland

Seasonal prediction and predictability of the Asian winter temperature variability

Efforts have been made to appreciate the extent to which we can predict the dominant modes of December–January–February (DJF) 2 m air temperature (TS) variability over the Asian winter monsoon region with dynamical models and a physically based statistical model. Dynamical prediction was made on the basis of multi-model ensemble (MME) of 13 coupled models with the November 1 initial condition for 21 boreal winters of 1981/1982–2001/2002. Statistical prediction was performed for 21 winters of 1981/1982–2001/2002 in a cross-validated way and for 11 winters of 1999/2000–2009/2010 in an independent verification. The first four observed modes of empirical orthogonal function analysis of DJF TS variability explain 69 % of the total variability and are statistically separated from other higher modes. We identify these as predictable modes, because they have clear physical meaning and the MME reproduces them with acceptable criteria. The MME skill basically originates from the models’ ability to capture the predictable modes. The MME shows better skill for the first mode, represented by a basin-wide warming trend, and for second mode related to the Arctic Oscillation. However, the statistical model better captures the third and fourth modes, which are strongly related to El Niño and Southern Oscillation (ENSO) variability on interannual and interdecadal timescales, respectively. Independent statistical forecasting for the recent 11-year period further reveals that the first and fourth modes are highly predictable. The second and third modes are less predictable due to lower persistence of boundary forcing and reduced potential predictability during the recent years. In particular, the notable decadal change in the monsoon–ENSO relationship makes the statistical forecast difficult.

Changes in European summer temperature variability revisited

Summer temperature variability has been projected to increase in Central Europe in response to anthropogenic greenhouse gas forcing. Based on an unprecedented set of global and regional climate models from the ENSEMBLES project, we assess the robustness of these projections on interannual to daily time scales. In comparison to previous analyses using PRUDENCE simulations, we find a more diverse climate change signal for interannual summer temperature variability and a clear dependence upon present‐day model performance. Models that realistically represent present‐day variability, tend to consistently project increasing interannual variability at the end of the 21st century. We demonstrate that the partitioning of latent and sensible heat fluxes controlled by soil moisture is crucial to understand the projected changes across the multi‐model experiment. The projected increase in daily summer temperature variability is more robust and consistently simulated by all models. Likewise, all models consistently project reduced daily temperature variability in winter. Thus, it is a robust signal across the entire ensemble that in summer and south‐central Europe hot extremes warm stronger than the mean, and in winter and northern Europe cold extremes warm stronger than mean temperatures.

The 20th century cooling trend over the southeastern United States

Portions of the southern and southeastern United States, primarily Mississippi, Alabama, and Georgia, have experienced century-long (1895–2007) downward air temperature trends that occur in all seasons. Superimposed on them are shifts in mean temperatures on decadal scales characterized by alternating warm (1930s–1940s, 1990s) and cold (1900s; 1960s–1970s) regimes. Regional atmospheric circulation and SST teleconnection indices, station-based cloud cover and soil moisture (Palmer drought severity index) data are used in stepwise multiple linear regression models. These models identify predictors linked to observed winter, summer, and annual Southeastern air temperature variability, the observed variance (r2) they explain, and the resulting prediction and residual time series. Long-term variations and trends in tropical Pacific sea temperatures, cloud cover, soil moisture and the North Atlantic and Arctic oscillations account for much of the air temperature downtrends. Soil moisture and cloud cover are the primary predictors of 59.6 % of the observed summer temperature variance. While the teleconnections, cloud cover and moisture data account for some of the annual and summer Southeastern cooling trend, large significant downward trending residuals remain in winter and summer. Comparison is made to the northeastern United States where large twentieth century upward air temperature trends are driven by cloud cover increases and Atlantic Multidecadal Oscillation (AMO) variability. Differences between the Northeastern warming and the Southeastern cooling trends in summer are attributable in part to the differing roles of cloud cover, soil moisture, the Arctic Oscillation and the AMO on air temperatures of the 2 regions.

우리나라 겨울철 기온과 북반구 대기 순환과의 상관성 분석

This study investigates the relationship between the Korean temperature and the atmospheric circulation such as Arctic Oscillation, Siberian High and Aleutian Low during the winter (December-January) for the period of 1970-2011. It is found that all indices to represent aforementioned circulations are significantly correlated with Korean winter temperature for the period of 1970 - 2011. There are marked contrasts in such relationship, however, before and after the mid-1980s when a significant regime shift of Korean winter temperature occurred. While Korean winter temperature has a close relationship with Arctic Oscillation after the mid-1980s, its relationship with Siberian High and Aleutian Low is weakened. The composite analysis between a positive and negative phase of Arctic Oscillation before and after the mid-1980s is conducted to examine a recent strengthening of Arctic Oscillation-Korean winter temperature relationship. It is found that the structural changes of low-level wind and the geopotential height at 500 hPa between the two phases of Arctic Oscillation are more effective to influence Korean winter temperature after the mid-1980s. This may induce a close relationship between the Korean winter temperature variability and Arctic Oscillation after the mid-1980s compared to before the mid-1980s.

Winter temperature variations over the middle and lower reaches of the Yangtze River since 1736 AD

Abstract. We present statistically reconstructed mean annual winter (December–February) temperatures from the middle and lower reaches of the Yangtze River (24° N–34° N, 108° E–123° E within mainland China) extending back to 1736. The reconstructions are based on information regarding snowfall days from historical documents of the Yu-Xue-Fen-Cun archive recorded during the Qing Dynasty (1644–1911). This information is calibrated with regional winter temperature series spanning the period from 1951 to 2007. The gap from 1912 to 1950 is filled using early instrumental observations. With the reference period of 1951–2007, the 18th century was 0.76 °C colder, and the 19th century was 1.18 °C colder. However, since the 20th century, the climate has been in a warming phase, particularly in the last 30 yr, and the mean temperature from 1981 to 2007 was 0.25 °C higher than that of the reference period of 1951–2007, representing the highest temperatures of the past 300 yr. Uncertainty existed for the period prior to 1900, and possible causes of this uncertainty, such as physical processes involved in the interaction between temperature and snowfall days and changing of observers, are discussed herein.

Seasonal prediction skill of ECMWF System 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere Winter

The seasonal prediction skill for the Northern Hemisphere winter is assessed using retrospective predictions (1982–2010) from the ECMWF System 4 (Sys4) and National Center for Environmental Prediction (NCEP) CFS version 2 (CFSv2) coupled atmosphere–ocean seasonal climate prediction systems. Sys4 shows a cold bias in the equatorial Pacific but a warm bias is found in the North Pacific and part of the North Atlantic. The CFSv2 has strong warm bias from the cold tongue region of the eastern Pacific to the equatorial central Pacific and cold bias in broad areas over the North Pacific and the North Atlantic. A cold bias in the Southern Hemisphere is common in both reforecasts. In addition, excessive precipitation is found in the equatorial Pacific, the equatorial Indian Ocean and the western Pacific in Sys4, and in the South Pacific, the southern Indian Ocean and the western Pacific in CFSv2. A dry bias is found for both modeling systems over South America and northern Australia. The mean prediction skill of 2 meter temperature (2mT) and precipitation anomalies are greater over the tropics than the extra-tropics and also greater over ocean than land. The prediction skill of tropical 2mT and precipitation is greater in strong El Nino Southern Oscillation (ENSO) winters than in weak ENSO winters. Both models predict the year-to-year ENSO variation quite accurately, although sea surface temperature trend bias in CFSv2 over the tropical Pacific results in lower prediction skill for the CFSv2 relative to the Sys4. Both models capture the main ENSO teleconnection pattern of strong anomalies over the tropics, the North Pacific and the North America. However, both models have difficulty in forecasting the year-to-year winter temperature variability over the US and northern Europe.

Longitudinal trends in climate drive flowering time clines in North American Arabidopsis thaliana

Introduced species frequently show geographic differentiation, and when differentiation mirrors the ancestral range, it is often taken as evidence of adaptive evolution. The mouse-ear cress (Arabidopsis thaliana) was introduced to North America from Eurasia 150–200 years ago, providing an opportunity to study parallel adaptation in a genetic model organism. Here, we test for clinal variation in flowering time using 199 North American (NA) accessions of A. thaliana, and evaluate the contributions of major flowering time genes FRI, FLC, and PHYC as well as potential ecological mechanisms underlying differentiation. We find evidence for substantial within population genetic variation in quantitative traits and flowering time, and putatively adaptive longitudinal differentiation, despite low levels of variation at FRI, FLC, and PHYC and genome-wide reductions in population structure relative to Eurasian (EA) samples. The observed longitudinal cline in flowering time in North America is parallel to an EA cline, robust to the effects of population structure, and associated with geographic variation in winter precipitation and temperature. We detected major effects of FRI on quantitative traits associated with reproductive fitness, although the haplotype associated with higher fitness remains rare in North America. Collectively, our results suggest the evolution of parallel flowering time clines through novel genetic mechanisms.

Wintertime Temperature Variability over Kingdom of Saudi Arabia

Mean wintertime temperature (December, January, February) recorded at 26 weather stations distributed across Kingdom of Saudi Arabia (KSA) were analyzed to reveal spatial and temporal patterns of long-term trends. The behavior of wintertime temperature since 1979 is examined with regard to the persistence, non-linear trends and inter-decadal variations. The coefficient of variability (COV) of winter temperature decreases gradually from north to south of KSA. The higher values of COV occur north and northeast of KSA. The higher values of winter COV over north and north east of KSA is due to the effect of the Traveling Mediterranean depressions and its interaction with the inverted-V shape trough of the Sudan low. Relationship between COV and latitudes is highly significant, while with longitudes is not significant. The Mann-Kendal statistical rank test illustrates that positive trends (warming) in winter temperature series occur over the all stations and the trends are significant at mid and southern region of the KSA. Recent warming has only occurred during the last two decades at most stations. While cooling in wintertime surface temperature appears for the short period of about 5 years, 1979-1983 and 1988-1993. These trends are in general consistence with trends in the global mean surface temperature.

Modeling range dynamics in heterogeneous landscapes: invasion of the hemlock woolly adelgid in eastern North America

Range expansion by native and exotic species will continue to be a major component of global change. Anticipating the potential effects of changes in species distributions requires models capable of forecasting population spread across realistic, heterogeneous landscapes and subject to spatiotemporal variability in habitat suitability. Several decades of theory and model development, as well as increased computing power and availability of fine-resolution GIS data, now make such models possible. Still unanswered, however, is the question of how well this new generation of dynamic models will anticipate range expansion. Here we develop a spatially explicit stochastic model that combines dynamic dispersal and population processes with fine-resolution maps characterizing spatiotemporal heterogeneity in climate and habitat to model range expansion of the hemlock woolly adelgid (HWA; Adelges tsugae). We parameterize this model using multiyear data sets describing population and dispersal dynamics of HWA and apply it to eastern North America over a 57-year period (1951-2008). To evaluate the model, the observed pattern of spread of HWA during this same period was compared to model predictions. Our model predicts considerable heterogeneity in the risk of HWA invasion across space and through time, and it suggests that spatiotemporal variation in winter temperature, rather than hemlock abundance, exerts a primary control on the spread of HWA. Although the simulations generally matched the observed current extent of the invasion of HWA and patterns of anisotropic spread, it did not correctly predict when HWA was observed to arrive in different geographic regions. We attribute differences between the modeled and observed dynamics to an inability to capture the timing and direction of long-distance dispersal events that substantially affected the ensuing pattern of spread.

Photosynthetic efficiency of native flora under natural stress in cold desert areas of Himachal Pradesh

Deserts of cold are related more to the physiographic causes because of their location and are characterized by natural stress conditions such as high altitude, aspect, subzero winter temperature (-20o to -30oC), high daily and seasonal diurnal temperature variations, high IR and UV radiations, reduced O2 and CO2 levels, soil moisture frozen during early spring, etc., which hinder the photosynthetic activities. Under such stress conditions, only few species possess the capability to survive. The study deals with the estimation of the photosynthetic rate, transpiration rate and water use efficiency of natural flora and the introduced species.

Environmental signals in a highly resolved ice core from James Ross Island, Antarctica

[1] The accumulation, isotopic and chemical signals of an ice core from James Ross Island, Antarctica, are investigated for the interval from 1967 to 2008. Over this interval, comparison with station, satellite and reanalysis data allows for a detailed assessment of the environmental information preserved in the ice. Accumulation at James Ross Island is enhanced during years when the circumpolar westerlies are weak, allowing more precipitation events to reach the northeastern Antarctic Peninsula. The stable water isotope composition of the ice core has an interannual temperature dependence consistent with the spatial isotope-temperature gradient across Antarctica, and preserves information about both summer and winter temperature variability in the region. Sea salts in the ice core are derived from open water sources in the marginal sea ice zone to the north of James Ross Island and transported to the site by strengthened northerly and westerly winds in the winter. A strong covariance with temperature means that the sea salt record may be able to be utilized, in conjunction with the isotope signal, as an indicator of winter temperature. Marine biogenic compounds in the ice core are derived from summer productivity within the sea ice zone to the south of James Ross Island. This source region may have become significant only in recent decades, when the collapse of nearby ice shelves established new sites of open water with high summer productivity. These findings provide a foundation for interpreting the environmental signals in the James Ross Island ice core, which extends though the whole Holocene and represents the oldest ice core that has been recovered from the Antarctic Peninsula region.

Contribution of late spring Eurasian snow cover extent to Canadian winter temperatures

AbstractThis study examines intercontinental linkages between late spring and early summer Eurasian snow cover extent (SCEss) anomalies and the following winter temperature anomalies over Canada for the 1972–2006 period. The structure of the second interannual mode of Canadian winter temperatures variability captures the SCEss related modulation. The North Atlantic winter atmospheric circulation changes associated with the SCEss, resembling the negative phase of the North Atlantic Oscillation (NAO), suggest a possible pathway for the SCEss influences on the Canadian winter temperatures.Regression and composite analyses show that the SCEss relate robustly to the Canadian winter climate. Larger‐than‐normal SCEss is associated with below normal winter temperatures in south‐central Canada and above normal temperatures over northeastern Canada. Predictive skill of Canadian winter temperatures based on a cross‐validated regression model shows that the SCEss offers the predictive potential over regions of Canada where El Niño‐Southern Oscillation (ENSO) related skill is weak or nonexistent. Analysis of winter extreme minimum temperatures, by a non‐stationary generalized extreme value model, with the SCEss as a covariate, exhibits statistically significant changes over Canada resembling a pattern similar to that of winter mean temperatures. Wavelet analysis shows significant coherence between the SCEss and the second mode of winter temperature variability in the 8–12‐year band. Copyright © 2011 Crown in the right of Canada. Published by John Wiley & Sons, Ltd