Methods

The ABMI defines human footprint as the visible alteration or conversion of native ecosystems to temporary or permanent residential, recreational, agricultural, or industrial landscapes. The definition includes all areas under human use that have lost their natural cover for extended periods of time, such as cities, roads, agricultural fields, and surface mines. It also includes land that is periodically reset to earlier successional conditions by industrial activities such as forest harvest areas and seismic lines. Some human land uses, such as grazing, hunting, and trapping, or the effects of pollution, are not yet accounted for in our human footprint analyses.

Areas of annual or perennial cultivation, including crops and tame pasture, as well as confined feeding operations and other high-density livestock areas.

Areas where vegetation or soil has been disturbed by the creation of mine sites, peat mines, pipelines, seismic lines, transmission lines, well sites, and wind-generation facilities. This footprint type is called “energy footprint” because most of this footprint type is associated with the energy industry.

Areas in forested landscapes where timber resource extraction has occurred for industrial purposes, including clear-cut and partial-cut logging methods.

The area of forestry footprint pro-rated for how much it has recovered for biodiversity, based on harvest area age and stand type (deciduous or conifer). A newly harvested area is considered to be 0% recovered, while mature forest is 100% recovered.   

Human-created waterbodies used for a variety of purposes, such as to extract fill (borrow-pits, sumps), water livestock (dugouts), transport water (canals), meet municipal needs (water supply, sewage), and store water (reservoirs).

Railways, roadways, and trails with hard surfaces such as cement, asphalt, or gravel, roads or trails without gravel or pavement, and the vegetation strips alongside transportation features.

Combines urban, rural, and industrial footprint types including residences, buildings, and disturbed vegetation and substrate associated with urban and rural settlements, such as housing, shopping centres, industrial areas, golf courses, and recreation areas, as well as bare ground cleared for industrial and commercial development.

Summary of six human footprint categories combined: agriculture, energy, forestry, human-created waterbodies, transportation, and urban/industrial.

Same definition as Total Human Footprint but replacing Forestry Footprint with Effective Forestry Footprint.

To report on the status of human footprint, the ABMI presents the percentage of land directly altered by human activities, ranging from 0% (no visible human footprint) to 100% (completely modified by human footprint). In general, cities and cultivated fields have high human footprint, while protected and undeveloped areas have low human footprint. Human footprint is summarized for total human footprint and by the six reporting categories.

Trend in human footprint in Norbord’s operating areas was assessed using the 3 × 7-km detailed inventory of human footprint available from 1950 to 2019. Trend is presented for total human footprint, effective human footprint, and by the seven reporting categories.

For forestry footprint and total human footprint (both status and trend), we also report on the area of their respective footprints after reducing the area of older forestry footprint based on how recovered it is, referred to as Effective Forestry Footprint and Effective Human Footprint.

The maps used to visualize human footprint in this report are based on the GIS Inventory of Provincial Human Footprint, circa 2018.

Seismic lines constructed prior to the use of Low-Impact-Seismic (LIS) construction methods. Conventional seismic lines were constructed using older technology that required the lines to be 5 to 8 meters in width to allow equipment to operate on the lines.

A line of underground and overground pipes, used for the delivery of petrochemicals, as well as the physical clearing around the pipeline(s).

All roadways paved with asphalt or concrete, roads surfaced with gravel and which serve as a main access route, as well as aircraft runways and interchange ramps.

Roadways surfaced with dirt and/or low vegetation which serve as minor access routes.

Utility corridors greater than 10 m wide with poles, towers, and lines for transmitting high voltage (> 69 kV) electricity.

A road or track for trains including active and abandoned tracks.

Summary of all linear footprint categories combined.

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. 

The edge distance is reduced as forestry footprint recovers (ages). This calculation is currently only applied to forestry but could include any human footprint types that are non-permanent and that can recover toward natural conditions, such as reclaimed or restored seismic lines, pipelines, well pads, etc.
 

For a detailed description of methods, see Azeria et al. (2019)^[4].

The BII is scaled between 0 and 100, with 100 representing no difference in expected abundance between current and reference conditions, and 0 representing current species abundance as far from reference conditions as possible. Intactness thus reveals deviations in species' abundance from intact conditions. Both downwards and upwards differences from reference conditions are viewed as deviations from intact conditions. For example, an intactness value of 50% means that the current species abundance is either half or twice as abundant as that predicted under reference conditions. The index is calculated as:

• current / reference × 100%, when current < reference (these are "decreaser" species whose relative abundance is lower in human footprint compared to reference conditions), or
• reference / current × 100%, when reference < current (these are "increaser" species whose relative abundance is higher in human footprint compared to reference conditions).

Overall intactness for a region is calculated by averaging intactness of species within each taxonomic group, then averaging the six taxonomic groups. Because increasers and decreasers both reduce intactness, a predicted increase in one species does not cancel out a predicted decrease in another species. Instead, both reduce intactness. We estimate intactness for 2018, based on native land cover and human footprint for 2018.

Intactness results are averages for the Northern Operating Area, Southern Operating Area, and Partner Operating Area. Specific locations within this region are nearly 0% intact (e.g., active industrial sites), and other sites are 100% intact (e.g., undeveloped forest and wetland habitat).

Any interpretations of biodiversity intactness must take the following into account:

• Intactness is based on species-habitat models that will change as analyses are refined and as more data are gathered.
• Intactness only shows the predicted effects of visible human footprint. Species' populations change for many other reasons. A "decreaser" species—one with lower abundance in human footprint—may in fact have an increasing population trend, if other aspects of its environment are improving. And vice versa for an "increaser" species. Measuring the actual trends of species is a long-term goal of ABMI monitoring.

• Intactness maps show the predicted average effect of the types of footprint in each area. We do not have information on the exact effects of footprint in each specific area, and we do not monitor actual changes in species in every location.
• Our models only reflect the immediate local effects of human footprint. There may be additional large-scale effects that we do not account for. For example, an extensive network of linear features and other human footprints may allow a species that prefers disturbed areas to spread through a region.
• This approach does not account for non-footprint effects (e.g., pollution, noise).

A sector’s effect on the regional population of a species shows how much the total population in the region is expected to have changed due to that sector’s footprint in the region. It is the difference between the species’ estimated total abundance in a reference landscape from which all human footprint has been removed, and the reference landscape with just that sector’s footprint added back in. Three factors determine a sector’s effect on the regional population of a species:

1. How much area is occupied by footprint from that sector. All else being equal, the more area a sector’s footprint occupies, the more effect it will have on the species;
2. How strongly—positively or negatively, or a mix of both—the species responds to each of the sector's footprint types;
3. How much of the sector's footprint is in higher- versus lower-quality habitat for the species. For example, species that live in old upland forest may be more affected by the forestry sector than the energy sector, because forestry focuses disturbance in older stands.

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.

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

Step 2. We define 6 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.
• Rural/Urban: Residential, industrial or recreational sites in rural or urban areas.
• 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.
• Human-created waterbodies: Larger bodies of water created by different sectors.
• Miscellaneous (not reported): Unidentified human footprint.

Step 3. We use 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 a species’ abundance in the reference map and the reference map plus the sector’s footprint. We use the differences in abundance in just the areas with the sector’s footprint to calculate the local footprint effect. We use the differences in total abundance over the whole region to calculate the sector’s effect on the regional population of the species.

There are two important caveats for the sector effects:

• The results are based on applying our habitat models to landbase information. The models have statistical uncertainty, and there may be errors in the landbase information. We do not yet have direct field measurements on actual trends in species’ abundances related to different industrial sectors.

• This is a fairly simple approach that does not account for non-footprint effects (e.g., pollution) or complexities like interactions between sectors (e.g., weedy species entering one sector’s footprint after they were introduced by another sector). We also have to use rules to account for areas where different sectors overlap (e.g., a well site in a cultivated field, forest harvest prior to an industrial development).

The ABMI reports on two aspects of landbase change: effects of landbase change on individual species and a roll-up of results for all bird species and habitat elements.

We use “vector diagrams” to show the effects of each type of landbase change on individual bird species and habitat elements. To interpret the vector 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:

1. new forestry, then 
2. the additional effect of old regenerating harvest areas, then 
3. new non-forestry human footprint, then
4. changes or disappearance of old non-forestry human footprint, then 
5. fires, and finally 
6. aging of undisturbed native forest.  

The endpoint is the net change predicted in that species from 2010 to 2018.

In this section we present roll-up figures for all bird species showing the effects of: 

• New versus regenerating old forestry, 
• Fires versus aging undisturbed stands, 
• Net human footprint versus net natural changes.

There are three important caveats for the landbase attribution analysis:

• These changes reflect the predicted changes in species due to changes in the landbase that we can map. Many other factors can also change species’ populations. We will be able to look into those when we have direct trend information, which we can then compare to the changes predicted from landbase change.

• These predicted effects of landbase change are based on the period 2010-2018.  Harvest rates, and particularly fires, vary over time. ABMI will soon have province-wide mapping for the year 2000, so that we can extend the attribution analysis over a longer time period.
• The results are based on ABMI habitat models, which are imperfect and improve over time as we collect more data.