The map shows survey locations (+) and detections (dots). Natural regions are shown as different background colors. Note: off-grid sites are plotted at the nearest systematic site location, and the number of detections indicated and the actual number of dots in the map might be different.Download raw data
Models were used to show how species' relative abundance differed among vegetation and human footprint types in the Boreal and Foothills regions of Alberta (see methods and manual). Models were only created for species that had at least 20 detections using data from ABMI. Predicted species abundance in each habitat type is shown with bars. Vertical lines indicate 90% confidence intervals. Dots within the forested habitat types show predicted species abundance in cutblocks of various ages.
It was not possible to create complex habitat association models for species detected fewer than 20 times in southern Alberta study area. For these species, a coarse index of habitat use was determined as the proportion of detections in each native vegetation and human footprint type in comparison to the proportional availability of the habitat types (see methods and manual). An index value <0 indicates lower than expected proportion of detections in that habitat type; and index value >0 indicates a higher than expected proportion. Due to the coarseness of the analyses, maps of predicted habitat abundance were not created for these species.
The effect of each type of human development (herein called a sector) on a species relative abundance is the product of the area of the sector's footprint (width of the bars), and the average "per unit area" effect of that sector's footprint on the species relative abundance (height of the bars). The area of footprint for a sector is the sum of the footprint belonging to it. The average effect is the difference between the predicted current and reference abundances in that sector's footprint type based on the species' model. The sector effect is higher when: 1) The sector's footprint occupies more area, 2) The species is strongly affected by that sector's footprint, and 3) The footprint is created in high quality habitat for the species. Note that soft linear footprint types are classified based on the sector to which they belong (Energy: seismic lines, pipelines, power lines; Transportation: road verges). The sector effects are based on empirical models for the species, and have uncertainty, especially for less common species. Sector effects only include direct effects of footprint, not indirect effects (e.g., pollution, noise, access effects) or possible cumulative effects where two or more sectors interact. Where two or more footprint types are overlaid, the calculation only includes the footprint type that is "on top" (e.g., a wellsite in a cultivated field, or a road in a forestry harvest area) (see methods and manual).
Habitat association models, plus models describing how species varied spatially and with climate gradients were used to predict species abundance in 1 km2 spatial units under reference conditions (see methods and manual). Predictions of relative abundance of the species in each 1 km2 unit were made after all human footprint in the 1 km2 unit had been 'backfilled' based on native vegetation in the surrounding area. Pixels depicted in red are predicted to have the highest abundance for the species, grading through light tan to dark blue where the species is predicted to be less abundant or absent. This figure has uncertainty due to uncertainty in the models and in the underlying vegetation map.
Habitat association models, plus models describing how species varied spatially and with climate gradients were used to predict species abundance in 1 km2 spatial units under current conditions (see methods and manual). Predictions of relative abundance of the species in each 1 km2 unit were made based on the vegetation and human footprint present in the 1 km2 unit in 2012. Pixels depicted in red are predicted to have the highest abundance for the species, grading through light tan to dark blue where the species is predicted to be less abundant or absent. This figure has uncertainty due to uncertainty in the models and in the underlying vegetation map (see uncertainty map below).
For each 1 km2 unit the difference between predicted current and reference conditions was determined (see methods and manual). In 1 km2 units depicted in green the species was predicted to have higher abundance under present conditions than under reference conditions, with the opposite true for 1 km2 units depicted in pink. The intensity of green and pink depict the relative magnitude of increase or decrease for the species between reference and current conditions. This figure has uncertainty due to uncertainty in the models and in the underlying vegetation map.
To highlight the degree of uncertainty in the models, we estimated the prediction standard error for each township based on bootstrap predictions of current abundance. 10 km x 10 km units depicted in red have the higheststandard error, while 10 km x 10 km units in dark green have the lowest (see methods and manual).
Information from Alberta Biodiversity Monitoring Institute (ABMI) plots was used to conduct the modeling described in this website.
ABMI (2017). Western Mountain Ash (Sorbus scopulina). ABMI Species Website, version 5.0 (2017-07-13). URL: http://species.abmi.ca/pages/species/vplants/Sorbus.scopulina.html.