Log scaling training comes to NIC’s Campbell River campus

NIC’s Coastal Log Scaling program prepares you to measure and categorize logs by species and grade. The 12-week program begins this February in Campbell River.

NIC is bringing its Coastal Log Scaling training program to Campbell River to meet demand for people who want to combine working outdoors with log measurement, grading and data entry.

The 12-week program starts this February.

Log scalers play a vital role in BC’s forest industry, measuring and categorizing logs by species and grade to determine their volume and value with the BC metric scale.

“We make sure all logs harvested are accurately scaled and graded and are processed in a way that makes the most of the resource,” said Scott McKillop, NIC’s Coastal Log Scaling instructor. “The BC metric scales drive the stumpage system, or tax the crown puts on logs coming out of the forest.”

The training is a combination of in-class learning and fieldwork. Students learn how to identify log species, grade logs and learn the steps involved in weight scaling.

“It brings together the physical work with calculations and data entry,” McKillop said. “It’s a great job for people looking for that mental engagement who also enjoy working in the outdoors.”

The BC Labour Market Outlook: 2018 Edition forecasts 2,000 job openings in forestry and logging, including support activities, by 2028.

“It’s a great program for people who might already be working in the industry, but want to expand their skills,” said McKillop. “Understanding how to properly value logs is an advantage when you work in the forest sector.”

Career opportunities range from government work to private forestry companies.

“With some companies you’ll have your home base you work out of, with others there’s opportunities to travel all over the coast,” he said.

For more information on NIC’s Coastal Log Scaling program, or to apply, visit https://www.nic.bc.ca/programs/continuing-education-and-training/vocational-training/coastal-log-scaling-program.

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