Land Use Strategies to Mitigate Climate Change in Carbon Dense Temperate Forests by Beverly E
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PO Box 2432, Corvallis OR 97339 www.corrim.org A review of PNAS paper entitled: Land use strategies to mitigate climate change in carbon dense temperate forests by Beverly E. Law, Tara W. Hudiburg, Logan T. Berner, Jeffrey J. Kent, Polly C. Buotte, and Mark E. Harmon, www.pnas.org/cgi/doi/10.1073/pnas.1720064115 with supporting documents found at: Law et al. 10.1073/pnas.1720064115 By: Elaine Oneil, PhD Director of Science and Sustainability CORRIM -The Consortium for Research on Renewable Industrial In summary: The [Law et al 2018 PNAS paper] is nearly opaque with respect to its underlying assumptions so assessing the validity and accuracy of the simulation modeling effort is onerous. What little is shared in the article regarding inputs to the simulation model ignores the latest developments in wood life cycle assessment and sustainable building design rendering the results at best inaccurate and most likely incorrect. Notwithstanding input errors, the simulation model arrives at unrealistic alternatives for maximizing carbon stored on the land base including the conversion of crop land, failure to acknowledge the risk of increased wildfires while assuming a growth benefit from CO2 fertilization as components of climate change, ignoring the realities of forest land economics as they pertain to reforestation and management effort. The methodology clearly ignores the reality of continued demand for infrastructure that supports our burgeoning population. It also ignores the economic benefits of Oregon’s forest sector which produces over 22% of the total US softwood products and nearly 34% of the total US solid softwood products, which means that stopping harvest in Oregon would create tremendous leakage as wood demand would be fulfilled elsewhere where forest productivity is much lower than it is in Oregon. In detail: First and foremost, this is a very opaque paper. The assumptions that underlay the assertions of impacts attributable to fire, harvest, and even to forest growth, rely on material buried in cited documents rather than in the text and/or supplementary materials. Supplementary materials provide only the model outputs which are based on methods in the cited papers, or indeed borrowed from the cited papers. This fact makes it onerous to assess the accuracy of the simulation modeling effort, and thus its relevance as a tool for policy makers who are examining what role the forest sector might play in a carbon mitigation strategy. That said, to the extent that I did look to the underlying model structure there were several cautionary elements that should be taken into consideration. The paper indicates that they conducted a lifecycle assessment to arrive at wood product and harvested carbon impacts. There is no indication in either the paper or the supporting documents that this is so. According to international standards (ISO 14040 and 14044) a life cycle assessment must at a minimum include four elements: goal and scope which identifies the functional unit, system boundaries, PNAS review - CORRIM assumptions and limitations, allocation methods and impact categories; a life cycle inventory analysis; an impact assessment; and an interpretation. LCA’s that do not explicitly address these elements are not life cycle assessments regardless of any assertion to the contrary. Given the scientific credentials of the authors, I am surprised that they would even entertain the idea that they are doing a life cycle assessment when that is clearly not the case. Within that context they also seem to be missing some key facts regarding service life of buildings ( eg even cross laminated timber buildings are only expected to last 30 years), decay rates of buildings (exponential at 2% per year – there are no economic models that would suggest that 2% of buildings are torn down within a year), and reforestation potential. Data on how they arrived at forest sector emissions is missing so there is no way to evaluate if it is modeled correctly. I.e. supplementary tables S3, S4, and S5 have no information on how they were derived (supplementary materials say that is in the text and the text says it is in the supplementary materials and provides no overview of inputs and outputs as required by an LCA (which authors assert this is)). As near as I can surmise the emissions include cutting all the trees, not replanting them (according to future projections and modeling description) which is not defensible under Oregon law, assuming a cut tree is an immediate emission, that most wood in service goes to the landfill within 30 years, and that substitution is not a relevant part of the wood use story. They cite a 2009 paper as their source for asserting that substitution is not a relevant factor, but that paper does not really address how they incorporate substitution at all. That same paper is referenced for how it accounts for harvested wood products, but there is no real accounting for harvested wood product longevity in the description of the simulation model used. In fact that simulation model indicates that it does not track what happens to the wood once it leaves the forest so somewhere there is either a missing reference or lack of explanation. On regeneration, there are substantial differences in the model predictions for growth in two regions (Fig S2 with an over prediction of growth by 75% of median value in the coast range and 100% of median value in Blue Mountains) that when propagated over a century will create increasing error rates with time. These two regions together account for nearly ½ the total carbon stocks in the state at the beginning of the simulation and since that median value is used in the monte carlo simulation it will propagate an overestimate of growth and long term carbon storage potential under a do nothing alternative which is the outcome that is predicted to provide the greatest carbon storage over the long term. There is also a mix of flux data and stock data reported as outputs and it isn’t clear (due to lack of transparency in the paper and supplemental materials) if those two are not confounded within the simulation model. The simulation model used is a climate model that uses as inputs the outputs from an ecosystem process model (I presume – it does not say how the inputs are processed) to calculate potential outcomes for future times under a number of different alternative scenarios. What goes into the ecosystem process model determines what comes out and is therefore what is fed into the climate model. This is an elegant method to examine ecosystem processes, make predictions, and understand inflexion points and uncertainty. Unfortunately outcomes often fail to stand up to scrutiny when compared to real world outcomes, particularly when it comes to using them to predict measurable outputs of products as the outputs are totally dependent on model specifications not piece size, volume, diameter distribution, or species - all of which drive harvest decision making processes. Page 2 of 3 PNAS review - CORRIM I am struck by the lack of articulating the economic likelihood of these simulation outcomes and how they stack up against recent (as in the past 50 years recent) forest harvest activities. The suggestion that harvest should be stopped on public lands is largely a moot point as harvest has been substantially reduced on public lands in Oregon since about 1993. A review of harvest trends over the past nearly 50 years shows a remarkably consistent harvest level on private lands over the entire period suggesting a sustainable harvest level as the period in question is longer than a rotation length. In fact growth, harvest and mortality data suggest that even when maintaining significant harvest rates these forests are accumulating more carbon stores than are removed. A comparison of recent trends for the USFS lands and private lands shows an increase in volume accumulated on public lands but with 3x more mortality than on private lands, based on plot remeasurements for the 1st 5 years of the 10 year FIA remeasurement period. Annual Change between 2001- NFS Private 2005 and 2011-2015 Net Removals 3.035 mmt C 27.909 mmt C Gross Growth 32.975 MMT C 36.838 Mortality 15.847 4.785 • Private lands harvested 9 times as much as national forest between 2001 and 2010 AND grew more on fewer acres. • Mortality 3 times as much on national forest than private lands in that same time period. Since 1993, the harvest on private land amounts to about 82% of total volume removed from about 53% of the total commercially available forested acres based on recent spatial analysis using land ownership data and harvest statistics for western Oregon forests. The volume grown on 10.7 million acres of private land is more than the volume grown on 19 million acres of public land according to the latest forest inventory and analysis data (2017 RPA). That same RPA data shows that conifer harvests in the Pacific coast supply 33.9% of all saw and veneer logs produced in the entire USA and 22.6% of all HWP (including pulp) in the entire USA. Oregon alone produces 5.8% of the world’s softwood lumber. To blithely suggest that that amount of harvested wood products would be available elsewhere without substantial leakage is not a defensible assumption. The analysis on wildfire impacts eliminates the data from the Biscuit fire citing that it is an anomalous occurrence (Fig S3). That model assumption will dramatically affect the outcomes of the simulation and is not substantiated given that the model runs are for a very extended time frame and large westside fires are becoming less anomalous given the doubling of the nationwide fire rate since 2000.