Loblolly Pine Checklots: Clarity or Confusion?

Making an informed decision about how seedling performance is measured is critical for a customer to make the right decision for their new forest.  ArborGen provides specific performance measurements and includes checklot information when reporting gains. Understanding the loblolly pine checklot system is a key factor in deciding on the best seedling for the optimal return on your investment. A seedling vendor should provide correct and relevant checklot information when reporting gains but if not, the customer should ask for it.

When selecting seedlings for pine plantation establishment, one of the essential decisions a customer will make is the level of genetic performance that is desired.  Often times a customer will have several families from which to choose and they may range significantly in their trait performance levels.  This seems like a straightforward process where a customer can review the families for sale and compare performance scores for traits like volume gain, stem straightness, or disease resistance.  However, this can become a confusing or frustrating process because there is not a single checklot to which we can compare all trees.  It is important to spend a few minutes to understand how checklots work in tree improvement programs in the southeastern United States.

What is a checklot?  Also called a control, these are seedlots or families that are included in genetic field trials and used as benchmarks.  Checklots may be mixes that represent wild type or unimproved material from a certain region or they may be a single family or set of families that represent levels of improvement.

A majority of the loblolly pine families that are available in the marketplace today originated from cooperative tree improvement programs such as the N.C. State University Cooperative Tree Improvement Program or the Western Gulf Forest Tree Improvement Program led by the Texas A&M Forest Service.  These programs have included standard checklots to represent unimproved pine or previous generations of improved pine. For each region or provenance a set of checklots are included in progeny tests so comparisons can be made to a standard seedlot. For someone making decisions about the genetics of loblolly pine it is critical to understand when comparisons are “apples to apples” or “apples to oranges”.  For most cases, the seedling customer should use the checklot from the area where the seedlings are going to be planted. For instance, if the planting site is southeast Georgia, the CC4 Checklot should be used while CC5 checklot should be used in south Alabama as indicated on the map in Figure 1.

Figure 1. A checklot zone map used by the N.C. State University Cooperative Tree Improvement Program.

Multiple Checklots in the Same Region
Multiple checklots have been included in genetic trials which means that most families can be compared to more than one checklot, even within the same provenance. There can be multiple gain values for each family but the actual genetic potential of the family has not changed. The gain value changes because the relative performance of the checklot is changing. In Figure 2 we have an example of Family A with a breeding value of 150 being compared to 3 checklots (Check1, Check2, and Check3). The gain compared to Check3 is most impressive at 114% but the breeding value of the family is 150 no matter which checklot is used to report that gain.

If one vendor provides gains against the unimproved coastal South Carolina checklot and another vendor provides scores against the unimproved Coastal Georgia checklot, the customer cannot make a meaningful comparison. It is possible that in today’s market an uninformed customer could think they are comparing different families but could actually be comparing the same family against different checklots. This is essential information that should be requested from the seedling vendor.

Moving Genetics to Other Regions
Another opportunity for confusion is when a family tested in one region is being offered for sale in another region. For example, if a Coastal family is being offered for sale in the Piedmont the genetic gain for that family over a coastal checklot in the coastal plain is not very informative for how the family will grow in the Piedmont region. This does not mean the family will not grow well in the Piedmont but the gain against a checklot in another region is not informative. This is another case of “apples to oranges” if the scores for the Coastal family are compared to scores for the Piedmont families that might also be for sale.

Opportunity for Third Party Verification
While having multiple checklots can be a point of confusion, in some regions there are opportunities for 3rd party verification of gain values for the customer which helps provide some assurance of genetic performance. In particular, the NC State University Cooperative Tree Improvement Program has established a standard approach to reporting gains called the Loblolly Pine Performance Rating System TM, or PRS (http://www.treeimprovement.org). Cooperative members can supply scores in a standard format that are generated by the cooperative and provide the information necessary to understand a family’s performance in growth, disease resistance, and stem form as compared to one of the cooperative checklots. The PRS is currently available for the North Atlantic Coastal Plain & Northern Piedmont, the Southern Piedmont & Upper Gulf Coastal Plain, and the Southern Atlantic & Lower Gulf Coastal Plains.

Chart 2 below compares a genetic family to three checklots. 

Figure 2. Comparing families against different checklots. The genetic value for family A does not change but the gain will vary depending on which checklot is selected.



 

Dr. Patrick Cumbie is manager of Pine development for ArborGen.  Patrick has been involved in forest tree breeding research and development for more than 12 years. His career has largely focused on coordinating and implementing accelerated breeding programs of loblolly Pine. Before joining ArborGen in 2010, Patrick worked in both industry and university based research programs.  He has received his BS in Forest Management, MS in Forestry and PhD in Forestry at North Carolina State University.

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