Methods

The backfill vegetation layer or reference/native vegetation layer pre-human disturbance was created by the ABMI through the amalgamation of existing information on vegetation, habitat and soil throughout Alberta. To obtain a seamless reference vegetation layer, vegetation in human footprint was replaced by vegetation predicted to be present in the absence of human footprint (i.e., human footprint was "backfilled" to native vegetation). More information on this product can be found here.

Forested vegetation is classified into six categories: upland deciduous, mixedwood, pine, or spruce (including true firs), and lowland treed bogs, treed fens, and treed swamps. For all forested vegetation classes, except for treed fens and treed swamps, we assigned age classes of 0–9 years, 10–19 years, 20–39 years, continuing in 20-year classes through to the oldest class of 160+ years. Non-forested vegetation is classified into nine categories: upland grass and shrubs, shrubby fens, bogs and swamps, graminoid fens, marshes, open wetlands and bare areas.

The ABMI’s backfill vegetation layer combined with the ABMI human footprint is used to summarize the effects of land base change on different vegetation types, and as part of statistical modeling to determine cumulative effects of human footprint (Biodiversity Intactness, Sector Effects) and land base change (Attribution) on species habitat. 

Results for 10 vegetation types are summarized in this analysis: 

• Upland forest types: deciduous, mixedwood, pine, White Spruce. 
• Lowland forest types: Black Spruce, treed fen
• Other vegetation types: swamp (treed and non-treed), open wetland (shrubby and graminoid), and upland grass and shrub.

In addition, we summarized information for old forests (both upland and lowland) which we define as stands greater than 120 years old.

To report on the status of vegetation (Section 2.2), the ABMI presents the percentage of each vegetation type directly after accounting for human footprint on the land base, ranging from 100% coverage of a vegetation type (no visible human footprint) to 0% (completely modified by human footprint). 

Trend in vegetation types in Tolko’s operating areas was assessed by overlaying the 3×7-km detailed inventory of human footprint onto the backfilled vegetation layer and summarizing percent area of vegetation types left undisturbed.  Results for trend in overall cover for the 10 vegetation types is available for: 1950, 1985, 2000, 2001, 2004–2021. Trend in old forest categories (>120 years) covers 2000–2021 because we are uncertain about how well we can “back-cast” forest ages to historical times.

To summarize land base changes between 2010 and 2021, the 2010 and 2021 wall-to-wall vegetation and human footprint maps were intersected, and transitions of land base cover types were summarized. Six causes of change are distinguished: 

1. Aging of native forest that is undisturbed over that span, 
2. Aging of harvest areas that existed in the first year, 
3. Fires, 
4. New forestry footprint, 
5. New non-forestry human footprint replacing native habitat and harvest areas, and
6. Changes in non-forestry human footprint that existed in the first year. 

Currently only undisturbed forest stands and forestry footprint age in the land base summaries. Other human footprint continues to exist unchanged unless it is replaced by a different type of human footprint; as a result, component 6 is always small. 

Through mapping all human footprint in the province, the HFI allows areas of native terrestrial habitat to be identified—in other words, those areas in the province that have not been visibly disturbed by humans, although natural disturbances (e.g., wildfire, insect outbreaks) and invisible effects of humans (e.g., pollution) still occur. Further, the ABMI can track the amount of interior native habitat that is effectively “away” from the influence of human footprint due to edge effects. To report on the status of native vegetation, we present:

• The percentage area of land cover that has no visible human footprint (although land uses like grazing may still occur). 
• The percentage area of interior native vegetation using three edge distances applied outwards from human footprint—50 m and 200 m following recommendations from Huggard and Kremsater (2015^[3]), and 500 m to represent the longest reported or policy-based edge effects, such as those for Woodland Caribou. These three edge distances are called “base” distances. The base distances are narrowed to account for two factors (for detailed methods see Huggard and Kremsater 2015^[2]).
• Width of human footprint. For narrow human footprint types like linear features, the edge influence that extends into native habitat is reduced because these openings have little surface wind, are shaded in most orientations, and are considered to be under “forest influence” for many species. As an exception, roads are assigned the full buffer distance regardless of road width, to conform to Government of Alberta methods for interior habitat.
• Recovery of forestry footprint. The edge distance is reduced as forestry footprint recovers (ages). 

See Section 2.6 for native habitat results.

Linear features are analyzed using polylines (lines centered on the width of the line) of these feature types, and are summarized as density of linear footprint in km/km². Some linear features, such as low-impact seismic lines, are not included. The ABMI is continuously working to improve linear footprint products, using the reference data and expertise of authorities with the Government of Alberta. Linear feature types are divided into the following categories for analysis:

See Section 2.7 for linear features results.

As part of their environmental stewardship, industries want to know how their activities change habitat suitability for species. Identifying the species most affected by an industrial sector can help in land use planning and, if necessary, in developing mitigation strategies. However, with several industries operating on the same land base, it can be difficult to tease out what effect each industry is having on different species. The ABMI combines our well-developed habitat models for species with land base information to infer the effects of different industrial sectors on many species^[5,6].

Values indicate how much habitat suitability for a species changes in the exact areas where a sector’s footprint occurs. It is the difference between the habitat suitability for a species in the native habitat prior to the footprint and habitat suitability for the species in the sector’s footprint. Results are interpreted as follows:

• If there is no suitable habitat at all for the species within the sector’s footprint, the local sector effect is -100%.
• If suitable habitat for the species does not change between native habitat and footprint, the effect is 0%.
• If a species prefers footprint, the effect is a positive percentage.

A sector’s effect on the regional habitat suitability for a species shows how much the habitat suitability in the region is predicted to have changed due to that sector’s footprint in the region. It is the difference between the habitat suitability for the species in the reference landscape with all human footprint removed, and the reference landscape with just that sector’s footprint added back in. Three factors determine a sector’s effect on the regional habitat suitability for a species: 

• How much area that industry’s footprint occupies. All else being equal, the more area a sector’s footprint occupies, the more effect it will have on habitat.
• The local sector effect of that sector on the species (described above). Habitat suitability for a given species may be reduced in one sector’s footprint, remain the same in another’s, and increase in other footprint.
• The habitat types that the industry operates in. A sector’s effect on the regional habitat suitability for a species will be greater if the industry operates more in good habitat for the species. For example, two forest species might both avoid agricultural areas, but one lives in aspen stands and the other in Black Spruce. Agriculture will have a much greater effect on the regional habitat suitability for the aspen species, because agricultural clearings are often in aspen stands and rarely in Black Spruce.

The species most negatively affected by an industrial sector will therefore be species that are least tolerant of that sector’s footprint, and that prefer to live in habitat types where more of the sector’s footprint occurs. People interested in knowing which species are the most affected by an industrial sector—positively or negatively—should look at the regional sector effects.

Step 1. We develop habitat models for species based on ABMI field data.

Step 2. We define six industrial sectors:

• Agriculture. Cultivated crops or pastures.
• Forestry. Age and stand type of harvest areas are tracked to account for recovery.
• Energy. Mines, well sites, pipelines, transmission lines, seismic lines and associated facilities.
• Transportation. All roads and rail lines. We cannot distinguish roads made specifically for other sectors, such as roads to access harvest areas or well sites.
• Urban/Industrial. Residential, industrial or recreational sites in rural or urban areas.
• Miscellaneous (not reported). Includes human-created water and unidentified human footprint.

Step 3. We use the ABMI’s reference map of current native vegetation with human footprint removed, and create another map with a sector’s footprint added back in. 

Step 4. We apply the habitat models to predict habitat suitability for a species in the reference map and the reference map plus the sector’s footprint. We use the differences in habitat suitability in just the areas with the sector’s footprint to calculate the local sector effect. We use the differences in total abundance over the whole region to calculate the sector’s effect on the regional habitat suitability for the species.

See Section 3.2 for sector effects results.

The ABMI is continuing to collect data to meet our long-term goal of showing trends in species’ abundances. Until those direct trend estimates are available, we can report trends in species habitat predicted from changes in the land base. We used habitat models for species to predict their abundance using complete maps of native vegetation and human footprint in Tolko's Southern Operating Area in 2010, and then again for 2021, and report the predicted change in the species over that time. Six causes of change are distinguished: 

1. Aging of native forest that is undisturbed over that span, 
2. Aging of harvest areas that existed in the first year, 
3. Fires, 
4. New forestry footprint, 
5. New non-forestry human footprint (human footprint) replacing native habitat and harvest areas, and
6. Changes in non-forestry human footprint that existed in the first year. 

Currently only undisturbed native vegetation and forestry footprint ages in the land base summaries. Other human footprint continues to exist unchanged unless it is replaced by a different type of human footprint. Component 6 is therefore always small.

We use “arrow diagrams” to show the effects of each type of land base change on species, as well as habitat elements. To interpret the arrow diagrams, follow the arrows from the top of the figure, starting at 0% change, to the bottom to see the predicted effects on the species of:

• new forestry, then 
• the effect of old regenerating harvest areas, then 
• new non-forestry human footprint, then
• changes or disappearance of old non-forestry human footprint, then 
• fires, and finally 
• aging of undisturbed native forest. 

The endpoint is the net change predicted in that species from 2010 to 2021.

For each taxonomic group we present figures which compare the effects of:

1. Forestry: New forestry footprint (harvested between 2010 and 2021), regenerating old forestry footprint (harvested before 2010 and continuing to regenerate), and combined forestry effect.
2. Other human footprint: New non-forestry footprint (created between 2010 and 2021), old (present before 2010), and net effect of non-forestry footprint.
3. All human footprint combined.
4. Natural processes: Fire (areas burned between 2010 and 2021), aging of undisturbed stands, and net change from these natural processes.
5. All land base changes combined.
6. 2023 Fire: areas burned in 2023.

We highlight the effects of each type of land base change on species habitat in the Southern Operating Area.

See Section 3.3 for species habitat change results.

Species of conservation concern are defined here as species that meet at least one of the following criteria:

• federally listed as Endangered, Threatened or Special Concern under Canada’s Species at Risk Act (SARA);
• provincially listed as Endangered or Threatened under Alberta’s Wildlife Act;
• recommended for listing federally by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC), or provincially by Alberta’s Endangered Species Conservation Committee (ESCC) as Endangered, Threatened, or Special Concern;
• ranked as At Risk, May Be At Risk, or Sensitive in the Alberta Wild Species General Status Listing;
• ranked as S1 or S2 by the Alberta Conservation Information System (ACIMS).

See Section 4.4 for information on species of conservation concern in the Southern Operating Area, including status ranks, occurrence information, and biodiversity intactness scores for those species with enough detections. 

Note that intactness is a measure of the predicted effects of local human footprint on habitat suitability; it is not a measure of population trend. Further, the ABMI cannot assess the status of all species of conservation concern in Tolko’s Southern Operating Area for one of two reasons. First, by virtue of their rarity, some species of conservation concern were simply not detected or were not detected with enough frequency to adequately assess their status. Second, the ABMI monitoring protocols are not designed to monitor some species groups, such as owls, waterfowl, and bats, that include some species of conservation concern. 

Data were collected from 2003 through 2019 for birds and mosses; 2015 through 2021 for mammals; and 2003 through 2021 for lichens and vascular plants.