Rhett Jackson, from the Warnell School of Forestry and Natural Resources at University of Georgia, visited us today for a departmental seminar. His topic on forestry best management practices (BMPs) was interesting especially the question at the heart of his talk…how good is good enough? The point he made is that while there are some impacts associated with forest operations such as increased sedimentation, these effects are often short lived and minor considering other land-use impacts. In addition, they are sometimes quite difficult to detect in the first place and we don’t always know how these possibly minor impacts affect ecosystem processes. BMP effectiveness can be site-dependent and problem areas are often limited to only a very small portion of the watershed. Do we need more research on forestry BMPs? His points are all well taken, but we could still use guidance on how one BMP or suite of BMPs stack up against each other. Ultimately, without BMPs we’d be in a heck of lot of trouble and knowing more about their efficiencies, cost-benefits, and maintenance or improvement of ecological integrity will help us improve guidance for management.
A recent National Research Council report had this to say about forestry BMPs:
Although “best” connotes an ideal condition or superior approach, in fact, BMPs are most often negotiated compromises between parties with economic interests in management activities and those with interests in environmental protection. The balance between these two continually evolving sides is a “best” compromise.
NRC (2008), Hydrologic effects of a changing forest landscape, 168 pp., National Academies Press, Washington DC.
2 thoughts on “How good is good enough?”
The NRC quote you posted is very interesting. When I came back from the seminar and explained it to another forestry student in my office, his comment was on the same lines. He was saying the problem isn’t ineffective BMPs, it is BMPs not being used properly (or at all).
So maybe the metric used to evaluate BMPs should include some measure of how easy they are to use or some kind of historic data about how often they are actually utilized in the field…
Right. That’s why states essentially use implementation rates to evaluate effectiveness or as in the Chesapeake Bay model, to assign loading factors for forestry, but does that always work or is it the best strategy?
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