Results & Discussion
Variations in temeprature and precipitation
From the analysis of the climate data, it is concluded that from 2010-2023 there were changes to both temperature and precipitation values seen in Alberta; however, trends do not follow a consistent pattern across the province for all data considered. For precipitation, there is no general trend in the amount received, with differences seen between ecoregions (Fig. 10). There are also large fluctuations in the annual amount seen between the ecoregions, with most of the later years (2015-2023) following the same general trend of shifts between ecoregions, with varying amounts of precipitation received.
The SWE trends are variable across the province, with some ecoregions seeing increases and other ecoregions seeing decreases in the maximum amount received in one year (Fig. 11). Similar to precipitation, there is a general trend following the SWE in later years (2015-2023) across ecoregions. There also exists large interannual variations within the years considered.
Figure 10. Yearly trends in total precipitation (mm) across four ecoregions in Alberta (Boreal=red, Foothills=light blue, Grassland=green, Parkland=dark blue). Calculated as the average total precipitation received from May to October in a particular year within the ecoregion.
Figure 11. Yearly trends in snow water equivalent (cm) across four ecoregions in Alberta (Boreal=red, Foothills=light blue, Grassland=green, Parkland=dark blue). Calculated as the average maximum amount received from September to August within the ecoregion.
Temperature follows a similar trend across all ecoregions, with there being an increase in minimum and maximum annual temperatures from May-October across the province (Fig. 12 & Fig. 13). Across all ecoregions, the Grassland has the highest average temperatures, with the Foothills having the lowest in every year from 2010-2023. There also exists variation within these values.
Figure 12. Yearly trends in maximum average temperature (°C) across four ecoregions in Alberta (Boreal=red, Foothills=light blue, Grassland=green, Parkland=dark blue). Calculated as the average of the average maximum temperatures recorded from May to October in a particular year within the ecoregion.
Figure 13. Yearly trends in minimum average temperature (°C) across four ecoregions in Alberta (Boreal=red, Foothills=light blue, Grassland=green, Parkland=dark blue). Calculated as the average of the minimum temperatures recorded from May to October in a particular year within the ecoregion.
Variations in blue-green algae blooms seen across Alberta and across years
For the algae blooms, there is no overall trend of algal blooms seen in the different ecoregions, with large interannual variations being the normal (Fig. 14). Highest average total cyanobacterial cell counts were recorded in the Boreal most years. Years without overlapping error bars are ecoregions which are significantly different from each other in respect to algae blooms.
Figure 14. Yearly trends in average total cyanobacterial cell counts least square means across four ecoregions in Alberta (Boreal=red, Foothills=light blue, Grassland=green, Parkland=dark blue). Calculated as the average of all records of cyanobacteria in samples from May to October within the particular year and ecoregion, with a linear model looking at the impact of total cyanobacterial cell count in relation to the ecoregion and year. Error bars represent the standard error of the data.
Precipitation and temperature impacts to blue-green algae blooms
Considering the cyanobacteria response to different temperature and precipitation variables allows specific annual trends to be illustrated. Firstly, impacts from precipitation depend on the ecoregion being considered (Fig. 15). As illustrated below, the Boreal and Parkland ecoregion have a slight increase in total cyanobacterial cell count when precipitation increases, with the Foothills and Grassland ecoregion seeing the opposite trend. These are very small impacts as the trend lines do not have a steep slope in either direction.
Figure 15. Trends in total cyanobacteria in respect to precipitation across the ecoregions of Alberta. Each point represents a year of data collection, with error bars being the standard errors of the respective data.
For the SWE, there is a slight increase in cyanobacteria with increasing snow seen in the Boreal, Foothills, and Parkland ecoregions, with this trend being the largest in the Parkland (Fig. 16). The Grassland has the opposite trend, with decreasing cyanobacteria in years with more snow.
Figure 16. Trends in total cyanobacteria in respect to SWE across the ecoregions of Alberta. Each point represents a year of data collection, with error bars being the standard errors of the respective data.
Both maximum and minimum temperature appear to have the same effect of the respective ecoregion, with the Foothills and Grassland ecoregions seeing an increase in cyanobacteria with increasing temperatures, and the Boreal and Parkland seeing a slight decrease (Figs. 17 & 18).
Figure 17. Trends in total cyanobacteria in respect to minimum temperatures across the ecoregions of Alberta. Each point represents a year of data collection, with error bars being the standard errors of the respective data.
Figure 18. Trends in total cyanobacteria in respect to maximum temperatures across the ecoregions of Alberta. Each point represents a year of data collection, with error bars being the standard errors of the respective data.
When comparing the least square means obtained in a correlation analysis, all climate variables are only weakly correlated to cyanobacteria growth as indicated by the Kendall Tau in Table 5. Any Kendall tau with a value between 0.00 and 0.05 has a negligible correlation, values between 0.06 and 0.26 are weakly correlated. Given this, precipitation and SWE are weakly positively correlated with cyanobacteria growth, and maximum temperature is weakly negatively correlated with cyanobacteria. Maximum temperature has both the lowest p-value and tau value, indicating the highest impact of these variables to cyanobacteria growth.
Table 5. Results of a correlation analysis using Kendall method to determine the correlation, if any, between precipitation, temperature, and cyanobacteria cell growth.
Discussion
From Figures 15 to 18, it can be seen how there are impacts to total cyanobacterial cell counts from specific precipitation and temperature influences. Looking at each ecoregion individually, increases in precipitation, SWE, and decreases in temperature lead to increases in blooms in the Boreal. For the Foothills, decreasing precipitation, any quantity of snow, and increasing temperatures lead to more algae blooms. The Grassland ecoregion sees an increase in blooms with decreasing precipitation, snow, and increasing temperatures. Finally, the Parkland has increased blooms with increasing precipitation, snow, and decreasing temperatures.
When considering data like this, an increase in precipitation tends to be linked with a decrease in temperature for increased blooms, or vice versa (increase in temperature and decrease in precipitation with increased blooms). The Boreal and Parkland ecoregions have the same results, with increasing precipitation and decreasing temperatures favouring increases in blooms, with the opposite seen in the Foothills and Grassland ecoregions. When considering the correlations between the climate variables and cyanobacteria, the similar Kendall tau values indicate that they are all weakly correlated and that they have similar impacts to growth. Maximum temperature appears to be the biggest driver, but this is still only a weakly negative value.
From what is seen above, increases in total cyanobacterial cell counts may be influenced by temperature and precipitation, but these cannot be directly linked. One explanation is the combined effect of temperature and precipitation changes. Ecoregions may have various levels of susceptibility to changes in temperature or precipitation, which may lead to changes that are not able to be quantified with general annual trends. There is also the potential for increases in precipitation in a slightly warmer year to mask the effects that might have been seen if one of the variables were different.
Another explanation is the cumulative effect built up over multiple years, both in temperature and precipitation. Only considering annual data does not allow for variations in daily data to be examined, such as when precipitation events occurred (ie. if most of the precipitation was received within a brief period); the presence of prolonged droughts, wet periods, and extreme temperatures; and the daily fluctuations in temperature (ie. what the range of temperatures seen in a day are). Further, annual data analysis does not show the changes in extreme events or allow it to be determined if daily increases in cyanobacterial counts are linked to extreme precipitation events followed by droughts, which can create conditions favourable for extreme bloom events (warm, shallow, stationary water). Further, as only 14 years were considered, climate trends cannot be discussed.
One final influence on the presence of cyanobacteria blooms is the surrounding land use. Certain ecoregions considered (ie. Grassland and Parkland) have higher percentages of agricultural usage on the land (Image 7). The higher quantities of fertilizers used will impact the trophic conditions of water bodies in the area, with excess nutrients often leached into the soil or being removed during runoff events. The eutrophication of the waters with the added nutrients (Nitrogen and Phosphorus) may be increasing cyanobacteria counts in certain areas with higher agriculture intensity, and biasing the results.
Image 7. Green and white areas of Alberta. Green areas represent forestry as the main industry and is mainly public land, whereas white areas have the main industry as agriculture and are mostly privately owned28.
Conclusion
With these added considerations, it is evident that there are more influences than just yearly temperature and precipitation values impacting cyanobacterial blooms in Alberta. This enforces the importance of considering numerous factors when looking at anthropogenic-caused environmental changes and ensuring that the scale of data that is analyzed will show the desired results. There also needs to be consideration given to holes present in the data set, certain ecoregions having more samples completed, and the possibility of uneven sampling that focuses on regions more prone to blue-green algae blooms. Addressing these in future studies will enable more detailed and complete results.
The results from this study can be summarized as follows to answer the research objectives:
How has the temperature and precipitation changed in Alberta from 2010-2023?
The data analyzed illustrated a clear change in these variables over the 14 years considered. There is a general increase in temperatures across the province, with small interannual variations. Precipitation is not following a consistent trend, with large interannual fluctuations seen in all ecoregions. There appears to be a cycle of a few years with higher levels of precipitation, followed by a few years with less. Generally, all four ecoregions follow the same general annual trends. Snow water equivalent was found to be the most variable, with earlier years considered having more variation between ecoregions then the latter. This also appears to follow a trend of alternating years of increased amount of snow received.
How have blue-green algae blooms changed during this period?
Overall, algae blooms have varied greatly during the period considered. Most years the Boreal ecoregion had the greatest least square means of the total cyanobacterial cell count, but this was only significantly higher in 4 years. There is also a high level of variance within each ecoregion for each year.
How do the changes in temperature and precipitation impact blue-green algae blooms across the natural ecoregions of Alberta?
Precipitation increases led to increases in algae blooms in the Boreal and Parkland ecoregions and decreases in the Foothills and Grassland ecoregions. There is a large spread of data for precipitation, with this just characterizing the general trends. This is only weakly correlated with algae growth.
SWE increases led to an increase in algae blooms in the Parkland ecoregion, little to no impact in both the Boreal and Foothills, and a decrease in the Grassland. There is increased variability in the Foothills, Grassland, and Parkland ecoregions, and minimal in the Boreal as illustrated by the error bars. This is only weakly correlated with algae growth.
Temperature follows the same trend for both maximum and minimum. There is a positive relationship seen between temperature increases and cyanobacteria increases in the Foothills and Grassland ecoregions, with the opposite being seen in the Boreal and Parkland ecoregions. This is only weakly correlated with algae growth, but has the strongest impact out of the variables considered.
Future research in this area should consider both a more detailed (e.g., daily) and coarser (e.g., century) timescale to better understand the yearly trends along with increased accuracy in predicting future outcomes. Taking into consideration the surrounding land use will further increase the understanding of impacts on algae growth. Having this added information will allow for a better analysis to be done and will hopefully lead to more concrete results to better inform the public about the blue-green algae bloom growth that could be expected in the coming years and help in strategizing algal bloom controls.