The data analysis performed here was completed using datasets from the data.world website, which provided monthly weather data that was colledted collected within Canada between the years 1917 and 2023. This original data frame included 24 columns of various climate values and identifiers. The dataset was then pared down to include latitude, longitude, year, month, station name, temperature, precipitation, and snowfall. The idea was to use this data to observe and make predictions about changes in average values throughout the years, and how different values will interact with each other, both within and across seasons. This analysis provides insight into climate change and variability, and some overall insights into how weather patterns interact. Our group also looked at biodiversity richness across different land management types, and a community well-being index provided by the Canadian Census.
Some exploration done in this data set required visualizing all of the climate variables across January in order to look for patterns. The biodiversity richness dataset required linking attributes of the data like biodiversity richness and percent on indigenous lands or protected area to geographic areas, and then comparing information from different countries or different types of animals.
The questions Sarah had were if there is a significant change in average temperature for British Columbia since the year 1917? Which Station has seen the greatest amount of snowfall in Canada? Which Province recieves the greatest amount of rainfall?
Sarah concludes that, yes, there has been a significant change in average temperature for BC, Canada as the temerature variability ranges from 5 degrees Celsius to 9 degrees Celsius. However, this graph also shows that the overall average temperature change from the year 1917 to 2017 is only 1 degree Celsius. Another interesting fact is that there has been a general upward trend in the average temperature for BC since the mid to late 1970s. Sarah found that Newfoundland and Labrador, being in the lead by mere centimeters, recieves the greatest average amount of snowfall. Lastly, she found that while Nova Scotia recieves the most rainfall on average, it is British Columbia that recieves by far the most heavy rainstorms of any province.
How do climate values interact with one another? Is one value predictive of another? With this question, Allysa wanted to explore how climate values might correlate. Allysa's hypothesis was that warmer years would likely coincide with more precipitation and less snow, and colder years might result in less precipitation and more snow. I chose to take all of my values from winter(January), to keep this variable constant.
Visualisations of temperature versus snow, and temperature versus precipitation showed some patterns, with lower temperatures being predictive of lower snowfall values, as well as lower precipitation values from 2011 to 2018. The pattern appears to reverse after this point, making it difficult to make any concrete statements about the interaction. Precipitation and snowfall appeared to covary across the years, with high precipitation years correlating with high snowfall years overall. This leads me to the thought that precipitation and snowfall values are often correlated, but temperature interactions are more complex, and would require a longer projection to comment on effectively.
How does biodiversity richness compare amongst different land management types (across the three countries, and in Canada)
Indigenous land management resulted in higher or near equal levels of biodiversity richness than protected areas, and out-perfromed the random non-protected areas across all factors. Indigenous lands are important habitats especially in the 'near threatened' category of animals. Birds especially find refuge in Indigenous lands, with some species having almost 100% of their habitat found in indigenous lands. Even though the total amount of indigenous lands is smaller than protected areas, there is richer biodiversity and the animals most at risk are fairing better in indigenous lands than other areas (based on biodiversity richness score). This is interesting, as indigneous lands typically do not have the 'official' goal of conservation like protected areas do, but due to the ways they're are managed a greater number of life-forms can be supported in indigenous lands, which contrasts with the random areas with no protection which have the lowest bio-diversity across the board.
Some take aways from this analysis include an increased awareness for the complexities of climate interactions. While some patterns can be gleaned from short term projections, it is not likely that real and meaningful conclusions can be reached using short term data. Further analysis should include longer projections, and data taken across more seasons, in order to support and add to patterns that were seen in this analysis.
This project helped illustrate how further work could be done to link the human and environmental elements of climate change, and to be creative in how to find indicators of change. By seeing how much indigenous land management makes a difference in how many species can coexist in a place, and how much lower biodiversity is in areas that have no protection at all, it would be worthwhile to find ways to expand indigenous stewardship in order to help bring these benefits to a larger scale. It would have been ideal to link the biodiversity data with the community wellbeing index to show inter-relations between the human experience of climate change, but those skills would be more advanced than the level we are currently at.