AcknowledgementsJae Olgivie, University of New Brunswick; Charlene Nielsen,University of Alberta; Michelle Marler, Bill Sperling and RebeccaRobinson.
Funding provided by AI‐EES, COSIA, Nexen,and NSERC with in kind support from ESRD.
The Federal government is initiating a caribou recoverystrategy that requires 65% of woodland caribou habitat to beundisturbed as defined by being at least 500 m from anyanthropogenic disturbance (Environment Canada, 2012).The extensive network of seismic lines with these buffersoften represents the largest single disturbance footprint forcaribou.
Woodland Caribou in decline:
Marxan Z (Watts et al., 2008) was used to identify andprioritize key areas for restoration of seismic lines usingzones. Key to prioritization is the consideration of:• Previously identified priority restoration areas for caribou
habitat• Probability of natural forest regeneration on seismic lines• Bitumen pay thickness identifying areas likely to be
continually developed and disturbed• Linear feature density to identify cost-benefits to caribou
Zones were defined as active reclamation (activerestoration), natural regeneration (passive restoration) andzones available for industrial development. Differentscenarios were compared by altering costs and targets tooptimize restoration of 50% of all current conventionalseismic lines in the study area (total lines = 2545 km, target= 1273 km).
Spatially optimizing seismic line restoration whenaccounting for natural regeneration could result insignificant cost savings and benefits to woodlandcaribou.
Spatially optimizing restoration:
Predicting Patterns of Regeneration on Seismic Lines to Inform Restoration Planning in Boreal Forest Habitats
van Rensen, C.K., Nielsen, S.E., White, B., Vinge, T., Lieffers, V.J.
Mapping of oil reserves involves the use of seismic lines (lineardisturbances) to determine size of reserves. These lineardisturbances fragment forests and in many cases fail toregenerate trees even decades following their use. With thecontinued rise in anthropogenic disturbances, regeneration ofseismic lines is necessary for the conservation of biodiversity.
Modelling seismic line regeneration:
van Rensen et al. (2015) Natural regeneration of forest vegetation on legacyseismic lines in Alberta’s oil sands region. Biological Conservation 184:127–135.
Factors affecting early forest regeneration using LiDAR, foreststand databases and a disturbance inventory of 4350 km ofseismic lines over a 1,806 km2 region (density of 2.4 km/km2) ofnortheast Alberta were investigated.
Regeneration to a 3 m height was modelled using generalizedlinear models (GLMs) with a logit link (1= regenerated, 0= notregenerated). Regeneration to 3 m was inversely related toterrain wetness (Wet Areas Mapping), line width, distance fromroads (as a proxy for human use of lines), and the lowlandecosites. Overall, terrain wetness and the presence of fenecosites had the strongest negative effect on regenerationpatterns; the wettest sites failed to recover even after 50 yearspost-disturbance.
Predictions of future regeneration rates on existing linessuggested that approximately one-third of existing lineardisturbance footprints in this boreal landscape will remainun-regenerated 50 years later resulting in persistent habitatfragmentation.
Vegetation heights on seismic lines were obtained using a LiDAR-derived Canopy Height Model (2 m resolution)
Ground photograph illustrating typical conventional seismic line disturbance for a wet (j) ecosite in the boreal forests of northeast Alberta, Canada (56̊ 29′ 35″ N, 111 ̊ 18′ 26″ W).
Maps:
Maps illustrating regeneration probability to 3 m vegetation height if disturbed by 2-D seismic line exploration (left) after 10, 30 and 50 years post-disturbance. Maps on the right illustrate predicted presence and absence of regeneration to 3 m height after 10, 30, and 50 years post-disturbance using optimal classification thresholds (MaxKappa). Line width and orientation were held at their mean values (6.8 m, 45 ⁰).
Selection frequency of a scenario including constraints for bitumen pay thickness, linear feature density, regeneration probability and caribou habitat (scenario 4) run for 200 iterations in Marxan with Zones for passive restoration zones (top) and active restoration zones (bottom). 50% of seismic lines were zoned for restoration. Planning units in blue were selected less frequently than planning units in orange or red.
Best solution from Marxan with Zones. Planning units were zoned for available (black), passive restoration (yellow) and active restoration (red). This scenario targeted the restoration of 50% of 2D seismic lines that were less than 3 m height of vegetation and includes costs for regeneration probability, bitumen pay thickness, linear feature density and targets for priority restoration areas for caribou.
