Search

Changes are projected for the boreal biome with complex and variable effects on forest vegetation including drought‐induced tree mortality and forest loss. With soil and atmospheric conditions governing drought intensity, specific drivers of trees water stress can be difficult to disentangle across temporal scales. We used wavelet analysis and causality detection to identify potential environmental controls (evapotranspiration, soil moisture, rainfall, vapor pressure deficit, air temperature and photosynthetically active radiation) on daily tree water deficit and on longer periods of tree dehydration in black spruce and tamarack. Daily tree water deficit was controlled by photosynthetically active radiation, vapor pressure deficit, and air temperature, causing greater stand evapotranspiration. Prolonged periods of tree water deficit (multi‐day) were regulated by photosynthetically active radiation and soil moisture. We provide empirical evidence that continued warming and drying will cause short‐term increases in black spruce and tamarack transpiration, but greater drought stress with reduced soil water availability. Plain Language Summary: This research explores how climate change could impact the water stress experienced by black spruce and tamarack trees in the western boreal forest of Canada. We focused on a key measure called "tree water deficit" to understand if the trees were under stress due to insufficient water. We examined how tree water deficit relates to environmental factors such as temperature, sunlight, and soil moisture. The findings revealed that, on a daily basis, factors like sunlight and temperature cause trees to release more water into the air. However, over longer periods (days to weeks), the amount of water in the soil becomes crucial, suggesting that trees might face water stress during dry spells. So, while trees could grow more on hotter, sunnier days, they could also experience water stress and reduced growth if the soil becomes too dry for an extended period. This study helps us grasp how various factors interact to influence tree water stress in the boreal forest, providing insights important for managing these ecosystems in a changing climate. Key Points: A novel approach to determine environmental controls of tree water deficit across time scales with wavelet analysis and Granger causalitySoil moisture emerges as a significant control of tree water deficit in boreal trees at longer scales (multi‐days)Daily productivity gains with warming will be mitigated by decreased soil water availability in longer periods of tree water deficit [ABSTRACT FROM AUTHOR]

Climate change is increasing global atmospheric temperatures, which can reduce abundance and cause range shifts in species that are sensitive to warming. However, fine‐scale thermal heterogeneity can drive highly variable local responses to climate change, especially in freshwater environments that differ in groundwater inputs and geomorphology.We used temperature data collected during 2012–2021 from 10 small, pristine streams in eastern Canada to characterise thermal variation at a small spatial scale (~25 km2). We then used relationships between daily air and stream temperatures to reconstruct stream temperature since 1980, and assessed how thermal variation influenced the phenology and growth of brook trout (Salvelinus fontinalis).Air–stream temperature relationships varied considerably among streams despite their close proximity, with predicted summer temperatures differing up to 9.5°C between warmer rainfall‐dominated streams and cooler groundwater‐dominated streams. Rainfall‐dominated streams warmed more than twice as fast as groundwater‐dominated streams across all seasons since 1980, with nearly four‐fold differences in rates of warming evident during summer months. Fine‐scale thermal heterogeneity also shaped brook trout phenology, as juveniles in rainfall‐dominated streams were estimated to hatch and emerge much later (~70 and 40 days, respectively) and experience faster phenological shifts than in groundwater‐dominated streams. Relationships between juvenile brook trout size and accumulated degree‐days were positive, but slopes differed over two‐fold and did not vary systematically based on stream hydrology, suggesting more idiosyncratic impacts of warming on early growth.Collectively, our study illustrates how species responses to climate change in freshwater environments can be consistent in direction but vary substantially in magnitude owing to the influence of groundwater. Future climate change is likely to increase the thermal stress experienced by brook trout populations in warmer rainfall‐dominated streams, while potentially benefiting those in groundwater‐dominated streams where current temperatures are often suboptimal.Observed differences in the rates and ecological impacts of warming among streams suggest that fine‐scale thermal variation must be considered when forecasting effects of future climate change on stream fish population dynamics. [ABSTRACT FROM AUTHOR]

Peatland pools are freshwater bodies that are highly dynamic aquatic ecosystems because of their small size and their development in organic‐rich sediments. However, our ability to understand and predict their contribution to both local and global biogeochemical cycles under rapidly occurring environmental change is limited because the spatiotemporal drivers of their biogeochemical patterns and processes are poorly understood. We used (1) pool biogeochemical data from 20 peatlands in eastern Canada, the United Kingdom, and southern Patagonia and (2) multi‐year data from an undisturbed peatland of eastern Canada, to determine how climate and terrain features drive the production, delivering and processing of carbon (C), nitrogen (N), and phosphorus (P) in peatland pools. Across sites, climate (24%) and terrain (13%) explained distinct portions of the variation in pool biogeochemistry, with climate driving spatial differences in pool dissolved organic C (DOC) concentration and aromaticity. Within the multi‐year dataset, DOC, carbon dioxide (CO2), total N concentrations, and DOC aromaticity were highest in the shallowest pools and at the end of the growing seasons, and increased gradually from 2016 to 2021 in relation to a combination of increases in summer precipitation, mean air temperature for the previous fall, and number of extreme summer heat days. Given the contrasting effects of terrain and climate, broad‐scale terrain characteristics may offer a baseline for the prediction of small‐scale pool biogeochemistry, while broad‐scale climate gradients and relatively small year‐to‐year variations in local climate induce a noticeable response in pool biogeochemistry. These findings emphasize the reactivity of peatland pools to both local and global environmental change and highlight their potential to act as widely distributed climate sentinels within historically relatively stable peatland ecosystems. [ABSTRACT FROM AUTHOR]

Monarch butterflies (Danaus plexippus) undergo an iconic multi‐generational migration, traveling thousands of kilometers from the summer breeding grounds in southern Canada to overwintering sites in central Mexico. This migration phenomena can be affected by climate change, which may have important implications on fitness and ultimately populations status. We investigated the long‐term trends in fall migration phenology of monarchs using a 25‐year dataset collected along the coast of Lake Erie in Ontario, Canada. We also investigated local long‐term trends in weather covariates that have the potential to influence migration phenology at this site. Patterns in standardized daily counts of monarchs were compared with local weather covariates using two methods (i.e., monthly averages and moving windows) to assess difference in outputs between analytical approaches. Our results suggest that monarch migration timing (migration midpoint, average peak, first peak, and late passage) and weather covariates have been consistent over time, in direct contrast to a similar study in Cape May, New Jersey, which showed a significant increase in both fall temperature and a 16‐ to 19‐day shift in monarch migration timing. Furthermore, our results differed between analytical approaches. With respect to annual variability in air temperature, our monthly average analysis suggested that for each degree increase in September air temperature, late season passage would advance 4.71 days (±1.59 SE, p =.01). However, the moving window analysis suggested that this result is likely spurious and found no significant correlations between migration timing and any weather covariates. Importantly, our results caution against extrapolating the effects of climate change on the migration phenology of the monarch across study regions and the need for more long‐term monitoring efforts to better understand regional drivers of variability in migration timing. [ABSTRACT FROM AUTHOR]

Northern high latitudes are experiencing some of the greatest increases in air temperatures on Earth. Air temperatures (along with other modulating variables including precipitation and the onset of snowmelt) are influenced by atmospheric–oceanic circulation patterns, some of which are persistent and recurrent. One pattern in particular, the Arctic Dipole (AD) anomaly, is a persistent sea‐level pressure teleconnection pattern between the Canadian Archipelago and Barents Sea that has unknown impacts on local climate variability. These patterns may be important, especially in hydro‐ecologically sensitive areas such as Northwest Territories (NWT), Canada where permafrost thaw and ecosystem changes are influenced by interannual climate variability. The goal of this research is to determine the impacts of the AD on local climate (air temperature, precipitation, snowmelt) for a 66‐year period (1950–2015) spanning both latitudinal and longitudinal gradients across NWT from north to south and foothills to plains. Deviations during strong positive and negative modes of the AD index were calculated in reference to the complete 66‐year record. Results showed considerable year‐to‐year variability in the AD pattern, with more frequent strong negative modes during the 2000s. During 1950–2015, there were 64 and 56 occurrences of strong positive and strong negative AD modes, respectively, across all seasons. Spring and summer strong AD modes led to local air temperature anomalies of greater than 0.8°C compared with the long‐term (66 years) mean. Earlier onset of snowmelt, by an average of 3–5 days, was also noted during positive AD modes. Despite strong connectivity between the AD and local air temperature, we found less correspondence between the AD and seasonal precipitation. These findings improve understanding of the impacts of the AD on local weather and climate in NWT and suggest implications for ecosystem change, such as drying and shrubification of northern boreal peatlands and possible connectivity to teleconnection impacts on wildland fire. [ABSTRACT FROM AUTHOR]

The Bayesian model averaging (BMA) method has been widely used for generating probabilistic climate projections. However, the averaging weights used in BMA can only reflect the spatially‐ and temporally‐averaged performance of each ensemble member, without the ability to address the spatiotemporal variations of model biases. This can lead to inevitable exaggeration or understatement of the contributions of individual members to the ensemble mean, thus reducing the robustness of the resulting probabilistic projections. Here we propose a new method to help address the neglected spatiotemporal variations of model biases. Through the proposed method, the BMA weights are used as prior distributions to drive the Bayesian discriminant analysis in order to generate refined weights for individual ensemble models according to their spatially‐ and temporally‐clustered performance. Through applying the proposed method to Canada, we demonstrate its effectiveness in generating robust probabilistic climate projections (e.g., the average R2 increases from 0.82 to 0.89). Plain Language Summary: Since no climate model is superior to others under all conditions, taking the advantages of multiple models is desired for robust climate projections. However, there exist significant spatial and temporal variations regarding the model performances. For example, an overall poorly‐performed model can still show promising results over a specific region or during a specific time period, while an overall well‐performed model does not necessarily perform well over all regions or in all years. Here we propose a new method to robustly address the spatiotemporal variations in the modeling performance of each ensemble member. Then we apply the proposed method to generate the probabilistic temperature projections over Canada. The proposed method can improve both the accuracy and reliability in ensemble‐based climate projections. Key Points: A discriminant‐BMA ensemble modeling approach is developed to synthesize the spatiotemporal variations of model biasesThe accuracy and reliability of probabilistic projections are both improved (e.g., the average R2 increases from 0.82 to 0.89)The temperature probabilistic projections based on regional climate models in three future periods are generated over Canada [ABSTRACT FROM AUTHOR]

To assess the potential change in agroclimatic indices in western Canada, this study used a convection-permitting Weather Research Forecasting (WRF) model to conduct simulations for the current climate (CTL, 2000-2015) and future climate under the RCP8.5 scenario based on a pseudo-global-warming (PGW) approach. Both CTL and PGW simulations were bias-corrected to the GEM-CaPA dataset using a multivariate quantile mapping method. An evaluation of the CTL simulation of daily maximum and minimum temperatures and precipitation during the growing season against the gridded observations has been performed, indicating good agreements in the spatial patterns of air temperature and precipitation in western Canada. The PGW-CTL differences in several selected agroclimatic indices were then examined. Due to rising temperatures, substantial increases in growing degree-days (GDD) by 800-1,200◦ days and reductions in frost days by 10 to 20 days, favouring regional crop production, are found in southern Alberta and Saskatchewan. However, globalwarming also poses great risks to Canadian agriculture by modifying heat accumulations and water availability during the growing season. Plant heat stress will substantially increase by ∼50◦ days in southern Alberta and Saskatchewan, offsetting the positive effects caused by the reduction in frost days and increase in GDD. The southern Canadian Prairies will experience statistically significant increases in the number of dry days and precipitation deficit, suggesting an exacerbation of water stress on the Canadian Prairies by global warming. [ABSTRACT FROM AUTHOR]

Arctic and boreal ecosystems play an important role in the global carbon (C) budget, and whether they act as a future net C sink or source depends on climate and environmental change. Here, we used complementary in situ measurements, model simulations, and satellite observations to investigate the net carbon dioxide (CO2) seasonal cycle and its climatic and environmental controls across Alaska and northwestern Canada during the anomalously warm winter to spring conditions of 2015 and 2016 (relative to 2010–2014). In the warm spring, we found that photosynthesis was enhanced more than respiration, leading to greater CO2 uptake. However, photosynthetic enhancement from spring warming was partially offset by greater ecosystem respiration during the preceding anomalously warm winter, resulting in nearly neutral effects on the annual net CO2 balance. Eddy covariance CO2 flux measurements showed that air temperature has a primary influence on net CO2 exchange in winter and spring, while soil moisture has a primary control on net CO2 exchange in the fall. The net CO2 exchange was generally more moisture limited in the boreal region than in the Arctic tundra. Our analysis indicates complex seasonal interactions of underlying C cycle processes in response to changing climate and hydrology that may not manifest in changes in net annual CO2 exchange. Therefore, a better understanding of the seasonal response of C cycle processes may provide important insights for predicting future carbon–climate feedbacks and their consequences on atmospheric CO2 dynamics in the northern high latitudes. [ABSTRACT FROM AUTHOR]

Winter thaw episodes, especially when accompanied by rain, can significantly deplete the winter snowpack, which is a critical water storage component in the mountainous headwater regions of the major river basins of western Canada. Here we identify the characteristic synoptic‐scale mid‐tropospheric atmospheric circulation regimes that tend to foster such extreme hydrologic events using self‐organizing map analysis of meteorological reanalysis data from 1949 to 2012. Daily winter 500 hPa geopotential height fields over the Pacific Ocean and western Canada are classified into 12 dominant synoptic types, for which conditional probabilities of above‐freezing temperatures and rainfall are then calculated and mapped using daily high‐resolution gridded data. Results show that above‐freezing surface air temperatures and rain events in winter are commonly associated with the occurrence of a ridge of high pressure over western Canada, which induces southwesterly advection of relatively warm, moist maritime air masses into the continental interior, and that the intensity and spatial footprint of the surface climate response is related to the strength and position of the ridge. Conversely, the development of a ridge of high pressure over the Pacific Ocean and adjacent trough of low pressure over western Canada, which favours northwesterly to westerly mid‐tropospheric flow over the continental interior in winter, tends to suppress the occurrence of above‐freezing temperatures and rain. The synoptic type most strongly associated with winter thaw and rain events underwent a statistically significant step‐change increase in mean frequency in 1977, accompanied by a corresponding step‐change decrease in the frequency of the dominant synoptic type depicting westerly (zonal) circulation, coinciding with a well‐documented shift to a positive phase of the Pacific Decadal Oscillation. [ABSTRACT FROM AUTHOR]

The discontinuous permafrost region of northwestern Canada is experiencing rapid warming resulting in dramatic land cover change from forested peatland permafrost terrain to treeless wetlands. Extensive research has been conducted throughout this region to gain insight into how climate‐induced land cover change will impact water resources and ecosystem function. This paper presents a hydrological and micrometeorological dataset collected in the Scotty Creek basin, Northwest Territories, Canada over the period of 01 October 2014 to 30 September 2015, a sample of the intensive and coordinated measurements collected annually at this site. Micrometeorological data collected from four stations, one located in each of the land cover types representative of those comprising the Scotty Creek basin including bog, channel fen, stable peat plateau and peat plateau undergoing rapid permafrost degradation and loss, are presented. Monitored micrometeorological variables include incoming and outgoing shortwave and longwave radiation, air temperature, relative humidity, wind speed, precipitation (rain and snow) and snow depth. Deep ground temperatures (~1–10 m below the ground surface) from a channel fen as well as disturbed sites common to the basin including a seismic line and winter road are presented. Water levels were also monitored in the representative land cover types over this period. This dataset is available from the Wilfrid Laurier University Library Research Data Repository (https://doi.org/10.5683/SP/OQDRJG) and can be used in coordination with other hydrological and micrometeorological datasets to examine spatio‐temporal effects of meteorological conditions on local hydrological responses across cold regions. [ABSTRACT FROM AUTHOR]

ABSTRACT: Parallel daily temperature observations at site pairs over a 5‐year period at 88 locations across Canada were used to derive and validate adjustments required during homogenization process. The data was first ‘aligned’ for compatible observing times at 12 locations (other locations do not have this problem). Then the homogenization adjustments were obtained using three procedures (Seasonal Bias, Monthly Interpolation and Quantile Matching) and two approaches (using parallel and neighbours observations). The root mean squared error (RMSE) between the daily temperatures of site 1 and site 2, and the percentage of days within 0.5 °C (PD05) between site 1 and site 2 were used to assess the uncertainty in the mean and extreme values, respectively. The instruments were not necessarily collocated as the distance between the two observing sites varied from 0 to 30 km. The results confirm that it is necessary to apply adjustments for known issues first, such as a different observing time. They also show that when a shift between site 1 and site 2 (defined by the annual mean of the daily temperature differences) is small [<0.25 standard deviation (SD)], the adjustments do not reduce the error between site 1 and site 2. When the shift size is between 0.25 and 0.5 SD, the adjustments derived from parallel observations help to reduce the uncertainty. When the shift is large (>0.5 SD), both approaches reduce the error, although the adjustments derived from parallel observations provide better results as compared to those computed from neighbour observations. The results also indicate that Quantile Matching adjustments can provide a better estimate of the adjustments than the other methods evaluated to indices of extreme temperature computed from the adjusted daily values; however, highly correlated neighbours are needed when the adjustments are based on neighbours observations. [ABSTRACT FROM AUTHOR]

In this study, high‐resolution projections of temperature and precipitation changes over Canada were developed through the Providing Regional Climates for Impact Studies (PRECIS) model under Representative Concentration Pathways (RCPs). In detail, the PRECIS model was employed to conduct simulations for the historical period over the entirety of Canada, driven by the boundary conditions from both ERA‐Interim (1979–2011) and HadGEM2‐ES (1959–2005). The performance of PRECIS simulations in reproducing historical climatology of Canada was then validated through comparison with observed temperature and precipitation over the baseline period (1986–2005). The boundary conditions from HadGEM2‐ES under RCP4.5 and RCP8.5 was used to drive PRECIS for simulating climatic variables over Canada for the period of 2006–2099. Future climate projections of temperature and precipitation as well as their extreme indices over two time‐slices (i.e. 2046–2065 and 2076–2095) were extracted and analysed. The results could help investigate how the regional climate over Canada will respond to global warming as well as the spatio‐temporal characteristics of plausible climate changes in the Canadian context. The validation results demonstrate that the PRECIS model is effective in reproducing the historical climatological patterns of annual mean temperature and total precipitation across Canada. Projections of temperature and precipitation for the two future periods indicate that there will be an apparent increasing pattern over Canada. The projected changes derived in this study can provide decision‐makers with valuable information to evaluate possible impacts on economic, social and environmental sectors at regional and local scales. [ABSTRACT FROM AUTHOR]

This study tests various applications of a new technique for infilling sparse monthly climate data which combines temperature anomalies from gridded observational and reanalysis data sets with baseline climatologies from short-instrumental records. Out-of-sample comparisons between infilled and observed climate data for 53 stations in northeastern Canada suggests that mean absolute errors using the proposed method are ±1 and ±0.5 °C on monthly and annual timescales, respectively. Evaluation of several gridded data sets used to guide infilling suggests that ERA-Interim ( ERAI) and modern-era retrospective reanalysis ( MERRA) reanalyses are the most suitable for this purpose in the Labrador-Ungava region. [ABSTRACT FROM AUTHOR]

We present a new 23-site network of white spruce ring-width chronologies near boreal treeline in Old Crow Flats, Yukon Territory, Canada. Most chronologies span the last 300 years and some reach the mid-16th century. The chronologies exhibit coherent growth patterns before the 1930s. However, since the 1930s, they diverge in trend and exhibit one of two contrasting, but well-replicated patterns we call Group 1 and Group 2. Over the instrumental period (1930-2007) Group 1 sites were inversely correlated with previous-year July temperatures while Group 2 sites were positively correlated with growth-year June temperatures. At the broader northwestern North America ( NWNA) scale, we find that the Group 1 and Group 2 patterns are common to a number of white spruce chronologies, which we call NWNA 1 and NWNA 2 chronologies. The NWNA 1 and NWNA 2 chronologies also share a single coherent growth pattern prior to their divergence (ca. 1950s). Comparison of the NWNA 1/ NWNA 2 chronologies against gridded 20th-century temperatures for NWNA and reconstructed northern hemisphere summer temperatures ( ad 1300-2000) indicates that all sites responded positively to temperature prior to the mid-20th century (at least back to ad 1300), but that some changed to a negative response ( NWNA 1) while others maintained a positive response ( NWNA 2). The spatial extent of divergence implies a large-scale forcing. As the divergence appears to be restricted to the 20th century, we suggest that the temperature response shift represents a moisture stress caused by an anomalously warm, dry 20th-century climate in NWNA, as indicated by paleoclimatic records. However, because some sites do not diverge and are located within a few kilometres of divergent sites, we speculate that site-level factors have been important in determining the susceptibility of sites to the large-scale drivers of divergence. [ABSTRACT FROM AUTHOR]

The article reports on near-surface-temperature lapse rates on the Prince of Wales Icefield in Ellesmere Island in Canada. In this study, screen temperatures were monitored from May 2001 to April 2003 in 25 sites in this location. It is posed that surface-temperature lapse rate in the region are systematically less than the free-air lapse rates that are commonly adopted for extrapolations of sea-level temperature to higher altitudes. Lastly, the low surface-temperature lapse rates and their systematic synoptic variability have essential implications for applications that involve downscaling of surface- or boundary-layer temperatures.