Forest Co-op - Serving the Forest Sector Since 1997

Forest Co-op Growth & Yield Science Unit

"Do we think? or do we know?" is an adage that resonates well with members of the Forest Co-op Growth and Yield Science Unit (GYSU). Since its inception in 1999, the GYSU has recognized that data are critical to making things happen, and the GYSU has carefully evaluated: the data it collects, the information products it supports and initiates, and the opportunities available to further leverage this vital asset. Dr. Edward Deming is often quoted as saying "In God we trust, all others bring data", and in this age of increasing scepticism, data that are available, accessible, transparent, and reliable are the keys to success.

As described in the section on the PGP Program (page 10), the GYSU has assembled information on a very large network of geo-referenced sample plots. But the GYSU also recognizes that just collecting and having data are not enough - data collection is not an end unto itself. In November 2009, members of the GYSU met for a productive two-day workshop to evaluate, update and reconfirm the GYSU’s founding principles and raison d’étre and to explore current and future uses for the Forest Co-op’s valuable plot network. Opportunities were explored to modify and augment data collection standards to make the dataset potentially even more valuable in light of emerging trends, fiscal realities, and future information needs. In particular, attributes that support industrial competitiveness through linkages to fibre value (wood quality) were identified, as were measurements tied to carbon accounting and ecosystem monitoring. Measurement priorities and principles were re-confirmed and new ones developed where required that will help guide in the planning of the field program for 2010 and beyond.

It was quickly comprehended by the members that tremendous potential exists in the data to fuel innovation and to help to create opportunity that will ultimately help to promote economic development. The structural changes happening in the forest industry were recognized as an opportunity to look beyond traditional information needs and position the GYSU to support the economic engines of the future. In a risk-averse economy, we only manage what we know, and uncertainty is anathema to development.

Data collection is not the only continuing, never-ending activity of the GYSU. Forest modeling is a growth industry, and the process of building, enhancing, improving and updating models is a constant testimony to the creativity of forest researchers, and ample proof that there is still much more to learn. In 2009, the GYSU saw the completion of the Benchmark Yield Curves Project for Northwestern Ontario by Dr. Margaret Penner as well as significant enhancements to the Structural Stand Density Management Models Project led by Dr. Peter Newton of the Canadian Wood Fibre Centre. Development of these significant new tools was only possible due to the size, scope and availability of the Forest Co-op data. In addition, the GYSU supported work by Keri Pidgen at Lakehead University towards her Master’s Thesis (plant community assembly 15-37 years after clearcutting, plus prescribed burning, and wildfire in jack pine forests of central Canada). This thesis, completed in December 2009, built on data and plots associated with the Forest Co-op Prescribed Burn Project, and points to the opportunity to leverage additional information and value from existing resources.

In this changing physical and economic environment, hallmarks of success for the GYSU have been in commitment to co-operation, constancy of purpose providing and improving the information used to support social, economic, and ecological decision-making in forest management, and the drive to facilitate creative use of the Forest Co-op data. Members of the GYSU invite you to view the detailed accounts of GYSU projects in this Annual Report. The GYSU welcomes new research partnerships that support the mandate of the Forest Co-op and its GYSU and will put our valuable resources, including the data, to work.