Forest Carbon Assessment for the Green Mountain National Forest Alexa Dugan ([email protected]), Maria Janowiak ([email protected]) and Duncan McKinley ([email protected])

August 16, 2018

1.0 Introduction Carbon uptake and storage are some of the many services provided by forests and grasslands. Through the process of photosynthesis, growing plants remove carbon dioxide (CO2) from the atmosphere and store it in forest biomass (plant stems, branches, foliage, roots), and much of this organic material is eventually stored in forest soils. This absorption of carbon from the atmosphere (sequestration) helps modulate (GHG) concentrations in the atmosphere. Estimates of net annual storage of carbon indicate that forests in the United States (U.S.) constitute an important , removing more carbon from the atmosphere than they are emitting (Pan et al. 2011). Forests in the United States remove the equivalent of about 12-19 percent of annual emissions in the U.S. (EPA 2015, Janowiak et al. 2017). Forests are dynamic systems that naturally undergo fluctuations in carbon storage and emissions as forests establish and grow, die with age or disturbances, and re-establish and regrow. Forests release carbon dioxide into the atmosphere when they die, either through natural aging and competition processes or disturbance events (e.g., combustion from fires), and this process transfers carbon from living carbon pools to dead pools. These dead pools also release carbon dioxide through decomposition or combustion (fires). Management activities include timber harvests, thinning, and fuel reductions treatments that remove carbon from the forest ecosystem and transfer it to the wood products sector. Carbon can then be stored in commodities for a variable duration ranging from days to years, or, in the case of some structural timber, from many decades to centuries. Forests then re-establish and regrow, resulting in the uptake and storage of carbon from the atmosphere. Over the long term, through one or more cycles of disturbance and regrowth (if the forest regenerates after the disturbance), net carbon flux (the balance from accumulation and loss) is often zero. This happens when net carbon flux reaches zero—when re-growth of trees accumulates the same amount of carbon as was emitted as a result of disturbance or mortality (McKinley et al. 2011). Although disturbances, forest aging, and management are often the primary drivers of forest carbon dynamics in some , environmental factors such as atmospheric CO2 concentrations, climatic variability, and the availability of limiting forest nutrients like nitrogen (N) also influence forest growth (Caspersen et al. 2000, Pan et al. 2009). In this section, an assessment is described for baseline forest carbon stocks and the role of disturbances, management, and environmental factors in storing carbon in Green Mountain National Forest in Vermont. This assessment uses two recent U.S. Forest Service reports: the Baseline Report (USDA Forest Service 2015) and the Disturbance Report (USDA Forest Service in review). Both reports relied on Forest Inventory and Analysis (FIA) and several validated,

Forest Carbon Assessment for the Green Mountain National Forest Page 1 August 16, 2018 data-driven modeling tools to provide nationally consistent BOX 1. FOREST CARBON MODELS evaluations of forest carbon trends across the National Forest System. The Baseline Report Carbon Calculation Tool (CCT) applies the Carbon Calculation Tool (CCT) (Smith et al. 2010). Estimates carbon stocks by summarizing data from two CCT summarizes available FIA or more Forest Inventory and Analysis (FIA) survey years. data across multiple survey years Carbon stocks from 1990 to 2013 are estimated by linear to estimate forest carbon stocks interpolation between survey years and linear and flux (change in stocks) at the extrapolation since the most recent survey. CCT relies on scale of the national forest from allometric models to convert tree measurements to 1990 to 2013. The Baseline biomass and carbon. Report also provides information Forest Carbon Management Framework (ForCaMF) on carbon storage in harvested wood products (HWP) for each Integrates FIA data, Landsat-derived maps of disturbance Forest Service region. type and severity, and an empirical forest dynamics model (the Forest Vegetation Simulator) to assess the The Disturbance Report provides relative impacts of disturbances (harvests, insects, fire, a national forest-scale evaluation abiotic, disease). ForCaMF estimates how much more of the influences of disturbances non- would be on each national forest if and management activities using disturbances from 1990 to 2011 had not occurred. the Forest Carbon Management Framework (ForCaMF) model Integrated Terrestrial Ecosystem Carbon (InTEC) model (Healey et al. 2014, Healey et al. A process-based model that estimates relative effects of 2016, Raymond et al. 2015). This aging, disturbance, and non-disturbance factors including report also contains estimates of climate, CO2 fertilization, and nitrogen deposition on the long-term relative effects of carbon stocks. InTEC integrates FIA data, Landsat-derived disturbance and non-disturbance disturbance maps, additional datasets such as climate factors on carbon stock change records, and CO2 measurement to report carbon and accumulation, using the accumulation and stock changes from 1950 to 2011. Integrated Terrestrial Ecosystem Estimates of carbon stock change reported by InTEC are Carbon (InTEC) model (Chen et likely to differ from those reported by CCT because of al. 2000, Zhang et al. 2012). different data inputs and modeling processes. The key findings from these reports are summarized here. See Box 1 for descriptions of the carbon models used for these analyses. To infer future forest carbon dynamics, information from additional reports, including the Resource Planning Act (RPA) assessments and regional vulnerability assessments, provide information on potential future conditions. Collectively, these reports incorporate advances in data and analytical methods, representing the best available science to provide comprehensive assessments of National Forest System carbon trends.

Forest Carbon Assessment for the Green Mountain National Forest Page 2 August 16, 2018 Green Mountain National Forest (NF) has been administratively combined with nearby Finger Lakes NF in New York as a single unit. The combined administrative unit was also maintained for forest carbon modeling in both the Baseline and Disturbance Reports. Green Mountain NF accounts for nearly all of the total forested area (98 percent) and disturbances (99 percent) in the combined unit. Thus, merging data from Finger Lakes NF and Green Mountain NF has a minimal effect on carbon trends and interpretation. Finger Lakes NF is included in results presented here unless otherwise noted. 1.1 Background Green Mountain NF, in southwestern and central Vermont, consists of 451,259 acres of forestland, mostly of the Maple/Beech/Birch forest type (per recent FIA estimates)1. The carbon legacy of Green Mountain NF and other national forests in the region is tied to the history of Euro-American settlement, land management, and disturbances. As the first region to be widely settled in the United States, the forests of the Eastern Region (R9) have had a long history of intensive harvesting and conversion of forests to agriculture. For much of the 19th century, the U.S. timber industry was centered in the Northeast. By early 1900, some 300 years after Euro- Americans first settled the region, most of the forests had been heavily utilized for timber or cleared for agriculture. As the need for sustainable forest management became evident, the U.S. government began purchasing large areas of these overharvested and often submarginal lands in the eastern United States the early and mid-19th century to be established as national forests. Green Mountain NF was established in 1932. With the help of the Civilian Conservation Corps, millions of trees were planted across the region in an effort to restore forest vegetation and control erosion. This legacy of timber harvesting and early efforts to restore the forest is visible today, influencing forest age structures and carbon dynamics.

2.0 Baseline Carbon Stocks and Flux 2.1 Forest Carbon Stocks and Stock Change According to results of the Baseline Report (Section 9.0), total ecosystem carbon stocks in Green Mountain NF increased from an estimated 26.5±4.4 Tg C in 1990 to 39.1±8.3 Tg C in 2013 (Fig. 1), a 48 percent increase in total carbon stocks over this period.2 Carbon stocks were fairly stable between 1990 and 1996 but increased steadily from 1997 to 2005. Carbon stocks continued to increase, but more slowly, from 2006 to 2013. Despite the uncertainty in these estimates

1 This estimate does not contain forested area in the Finger Lakes NF. Area estimate obtained using EVALIDator (https://apps.fs.usda.gov/Evalidator/evalidator.jsp) which queries the Forest Inventory & Analysis database. 2 This report uses carbon mass, not CO2 mass, because carbon is a standard unit and can easily be converted to any other unit. To convert carbon mass to CO2 mass, multiply by 3.67 to account for the mass of the O2. 1000 teragrams (Tg) =1 petagram (Pg) 1000 teragrams = 1 billion metric tonnes 1000 teragrams = 1 gigatonne 1 teragram = 1 million metric tonnes 1 teragram = 1 megatonne 1 megagram (Mg) = 1 metric tonne 1 metric tonne = 0.98 U.S. long ton 1 metric tonne per hectare = 0.4 U.S. long tons per acre carbon (C) mass * 3.67 = carbon dioxide (CO2) mass

Forest Carbon Assessment for the Green Mountain National Forest Page 3 August 16, 2018 reflected by the 95 percent 80 confidence intervals, there is a high degree of certainty that 60 carbon stocks in Green Mountain NF have increased 40 from 1990 to 2013 (Fig. 1). The annual carbon stock 20

Carbon Stocks (Tg) Stocks Carbon change can be used to evaluate whether a forest is a carbon 0 sink or a source in a given year. Carbon stock change is Year typically reported from the Figure 1. Estimated total forest carbon stocks for the baseline perspective of the atmosphere. period of 1990-2013 for Green Mountain NF, bounded by 95 A negative value indicates a percent confidence intervals (green) (figure from Appendix A.I, carbon sink: the forest is USDA Forest Service 2015). Carbon stock estimates include absorbing more carbon from stocks in Finger Lakes NF. the atmosphere (through growth) than it emits (via decomposition, mortality, or combustion). A positive value indicates a source: the forest is emitting more carbon than it takes up.

Annual carbon stock changes in Green Mountain NF from 1990 to 1996 were relatively stable, indicating that the forest was neither a carbon sink nor source. As carbon stocks began to increase in 1997, the forest shifted to a carbon sink of roughly 1.1 ± 0.42 Tg C per year through 2005. From 2006 to 2012, the rate of carbon stock increase then slowed, causing a slight decline in the carbon 4 3 sink (Fig. 2). The uncertainty between annual estimates can make 2 it difficult to determine whether the 1 forest is a sink or a source in a 0 specific year (i.e., uncertainty bounds -1 overlap zero) (Fig. 2). However, the -2 trend of increasing carbon stocks Stock Stock (Tg/Year) change -3 over this 23-year period (Fig. 1) strongly suggests that Green -4 Mountain NF is a carbon sink.

Year About 40 percent of forest carbon Figure 2. Carbon stock change from 1990 to 2012 for Green stocks in Green Mountain NF are Mountain NF, bounded by 95 percent confidence intervals stored in the aboveground portion of (green). A positive value indicates a carbon source, and a live trees, which includes all live negative value indicates a carbon sink (figure from Appendix woody vegetation at least 1 inch in A.II, USDA Forest Service 2015). Estimates include stock diameter (Fig. 3). Soil carbon, changes in Finger Lakes NF.

Forest Carbon Assessment for the Green Mountain National Forest Page 4 August 16, 2018 contained in organic material to a depth of 1 meter (excluding roots), is the second largest carbon pool, storing another 34 percent of forest Aboveground live 34% carbon stocks. Recently, new Belowground live 40% methods for measuring soil carbon Understory have found that the amount of carbon Standing dead stored in soils generally exceeds the Down dead Forest floor estimates derived from using the Soil methods of the CCT model (Domke 13% et al. 2017). 3% 8%

1% 1% The change in carbon stocks over time depends on several factors, Figure 3. Percentage of carbon stocks in each of the including growth rates, natural forest carbon pools for Green Mountain NF in 2013. ecosystem dynamics, and Estimates include carbon stocks in Finger Lakes NF. management activities. Changes in forested area may also affect whether forest carbon stocks are increasing or decreasing. The CCT estimates are based on FIA data, which may indicate changes in the total forested area from one year to the next. According to the FIA data used to develop these baseline estimates, the forested area in Green Mountain NF (including Finger Lakes NF) decreased from 363,784 acres in 1990 to 356,758 acres in 1995, and then steadily increased to 456,056 acres in 2013. When the forestland area increases, total ecosystem carbon stocks typically also increase, indicating a carbon sink. However, the CCT model used inventory data from two different databases. This may have led to inaccurate

120 Chippewa Huron-Manistee 100 Mark Twain Ottawa Shawnee 80 Superior Hiawatha 60 Hoosier Chequamegon-Nicolet 40 Wayne Carbon density (t/ac) density Carbon Midewin Tallgrass Prairie 20 Allegheny Green Mountain 0 Monongahela White Mountain

Year

Figure 4. Estimated carbon stock density (metric tonnes C per acre) across National Forest units in the Eastern Region from 1990 to 2013. Estimates for the Green Mountain NF include estimates from Finger Lakes NF.

Forest Carbon Assessment for the Green Mountain National Forest Page 5 August 16, 2018 estimates of changes in forested area, potentially altering the conclusion regarding whether or not forest carbon stocks are increasing or decreasing, and therefore, whether a forest is a carbon source or sink (Woodall et al. 2011).

Carbon density, which is an estimate of forest carbon stocks per unit area, can help identify the effects of changing forested area. In Green Mountain NF, carbon density increased from about 72.8 tonnes of carbon per acre in 1990 to 86.8 tonnes per acre in 2013 (Fig. 4). This increase in carbon density suggests that total carbon stocks may have indeed increased.

Carbon density is also useful for comparing trends among units or ownerships with different forest areas. Similar to Green Mountain NF, most national forests in the Eastern region have experienced increasing carbon densities from 1990 to 2013. Carbon density in the Green Mountain NF has been similar to the average for the 15 national forest in the Eastern region. Differences in carbon density between units may be related to inherent differences in biophysical factors that influence growth and productivity, such as climatic conditions, elevation, and forest types. These differences may also be affected by disturbance and management regimes (see Section 3.0).

2.2 Uncertainty associated with baseline forest carbon estimates All results reported in this assessment are estimates that are contingent on models, data inputs, and assumptions and their respective uncertainties. Baseline estimates of total carbon stocks and carbon stock change include 95 percent confidence intervals derived using Monte Carlo simulations and shown by green highlighting (Figs. 1, 2). These confidence intervals indicate that 19 times out of 20, the carbon stock or stock change for any given year will fall within the green-highlighted zone. The uncertainties contained in the models, samples, and measurements can exceed 30 percent at the scale of a national forest, making it difficult to infer if or how carbon stocks are changing. However, uncertainty estimates for Green Mountain NF are relatively low, so it can be inferred with a high degree of certainty that carbon stocks are increasing. The baseline estimates that rely on FIA data include uncertainty associated with sampling error (e.g., area estimates are based on a network of plots, not a census), measurement error (e.g., species identification, data entry errors), and model error (e.g., associated with volume, biomass, and carbon models, interpolation between sampling designs). One such model error has resulted from a change in FIA sampling design, which led to an apparent change in forested area. Change in forested area may reflect an actual change in land use due to or deforestation. However, given that national forests have experienced little land-use change in recent years, the change in forested area incorporated into CCT is more likely a data artifact of altered inventory design and protocols. The inventory design changed from a periodic inventory, in which all plots were sampled in a single year, to a standardized, national, annual inventory, in which a proportion of all plots is sampled every year. The older, periodic inventory was conducted differently across states and tended to focus on timber lands with high productivity. Any data gaps identified in the periodic surveys, which were conducted prior to the late 1990s, were filled by assigning average carbon

Forest Carbon Assessment for the Green Mountain National Forest Page 6 August 16, 2018 densities calculated from the more complete, later inventories from the respective states (Woodall et al. 2013). The definition of what constitutes forested land also changed between the periodic and annual inventory in some states, which also may have contributed to apparent changes in forested area. In addition, carbon stock estimates contain sampling error associated with the cycle in which inventory plots are measured. FIA plots are remeasured about every 5 years in the eastern United States, and a full cycle is completed once every plot is measured at least once. However, sampling is designed such that partial inventory cycles provide usable, unbiased samples annually but with higher errors. These baseline estimates may lack some temporal sensitivity, because plots are not resampled every year, and recent disturbances may not be incorporated in the estimates if the disturbed plots have not yet been sampled. For example, if a plot was measured in 2009 but was clear-cut in 2010, that harvest would not be detected in that plot until it is remeasured in 2014. Therefore, effects of the harvest would show up in FIA/CCT estimates only gradually as affected plots are re-visited. In the interim, re-growth and other disturbances may mute the responsiveness of CCT to disturbance effects on carbon stocks. Although CCT is linked to a designed sample that allows straightforward error analysis, it is best suited for detecting broader and long-term trends. In contrast, the Disturbance Report (Section 3.0) integrates high-resolution, remotely-sensed disturbance data to capture effects of each disturbance event the year it occurred. This report identifies mechanisms that alter carbon stocks and provides information on finer temporal scales. Consequently, discrepancies in results may occur between the Baseline Report and the Disturbance Report (Dugan et al. 2017). 2.3 Harvested wood products carbon stocks On-site carbon sequestration through tree growth and biomass accumulation is not the only way in which carbon is stored. Harvested wood can be used for products such as lumber, panels, and paper that account for a significant amount of off-site carbon storage. Estimates of the contribution of the carbon stored in harvested wood products (HWP) are important for both national-level accounting and regional reporting (Skog 2008, Bergman et al. 2014). Products derived from the harvest of timber from national forests can reduce net carbon emissions to the atmosphere by substituting for more energy-intensive materials, including concrete, steel, and plastics. Much of the harvested carbon that is initially transferred out of the forest can also be recovered as the area where the harvest occurred regrows. The Baseline Report provides an assessment of carbon stored in the wood products sector for all national forests within each Forest Service region from 1912 to 2013. HWP carbon accounting was conducted by incorporating data on harvests on national forest lands documented in cut-and- sold reports within a production accounting system (Stockmann et al. 2012, Loeffler et al. 2014). This approach tracks the entire cycle of carbon, from harvest to timber products to primary wood products to disposal. HWP carbon pools include both products in use and products that have been discarded to solid waste disposal sites, such as landfills and dumps.

Forest Carbon Assessment for the Green Mountain National Forest Page 7 August 16, 2018 As more commodities 14 are produced and remain 12 in use, the amount of carbon stored in 10 products increases. As Products in use 8 more products are Products in SWDS 6 discarded, the carbon stored in solid waste 4 disposal sites increases. HWP HWP Carbon Stocks (Tg) 2 Products in solid waste disposal sites may 0 continue to store carbon 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 for many decades. In the Year national forests in the Figure 5. Estimated cumulative total carbon stored in HWP sourced Eastern Region, harvest from national forests in the Eastern Region. Carbon in HWP includes levels remained low products that are still in use and carbon stored at solid waste disposal until after the start of sites (SWDS) (Loeffler et al. 2014). World War II in the 1940s, when they began to increase, continuing to increase through the early 1970s (Figure 8 in USDA Forest Service, 2015). This increase in harvests also caused an increase in carbon storage in HWP from national forests the Eastern Region (Fig. 5). By 1973, HWP carbon stocks reached about 5 Tg C. Timber harvesting and subsequent carbon storage then declined in the mid to late 1970s, but later increased rapidly from the 1980s through the 1990s. Storage in products and landfills reached roughly 12 Tg C in 2001. However, because of a significant decline in harvesting in 2002 (to 1950s levels), carbon accumulation in the product sector has slowed, and carbon storage in products in use has declined slightly since 2002. In the Eastern Region, the contribution of national forest timber harvests to the HWP carbon pool exceeds the decay of retired products, causing a net increase in product-sector carbon stocks from 1912 to 2013. In 2012, the carbon stored in HWP was equivalent to roughly 1 percent of total forest carbon storage associated with national forests in the Eastern region. As with the baseline estimates of ecosystem carbon storage, the analysis of carbon storage in HWP also contains uncertainties. Sources of error that influence the amount of uncertainty in the estimates include: adjustment of historic harvests to modern national forests boundaries; factors used to convert the volume harvested to biomass; the proportion of harvested wood used for different commodities (e.g., paper products, saw logs); product decay rates; and the lack of distinction between methane and CO2 emissions from landfills. The approach also does not consider the substitution of wood products for emission-intensive materials or the substitution of bioenergy for fossil fuel energy. The collective effect of uncertainty was assessed using a Monte Carlo approach. Results indicated a ±0.05 percent difference from the mean at the 90 percent confidence level for 2013, suggesting that uncertainty is relatively small at this regional scale (Loeffler et al. 2014).

Forest Carbon Assessment for the Green Mountain National Forest Page 8 August 16, 2018 3.0 Factors Influencing Forest Carbon 3.1 Effects of Disturbance The Disturbance Report builds on estimates in the Baseline Report by supplementing high- resolution, manually-verified, annual disturbance data from Landsat satellite imagery (Healey et al. 2018). The Landsat-derived product indicates that timber harvest has been the dominant disturbance type detected in Green Mountain NF from 1990 to 2011 (Fig. 6a). However, timber harvests affected only a relatively small area of the NF during this time. Based on the Landsat data, the largest harvest occurred in 1991, but total harvests in that year still accounted for only 0.25 percent of the total forested area (Fig. 6a) of the national forest (approximately 1,100 acres based on recent FIA-based forested area). From 1990 to 2011, some level of harvest occurred on a total of 1.4 percent of the forested area (6,000 acres). These harvests have been mostly partial cuts (from thinning stand density), which result in a 0–25 percent change in canopy cover (Fig. 6b).

1 1 (a) (b) Abiotic 4 Insect 3 2 Harvest 1

Percentage of foretdisturbed 0 0

Year Year Figure 6. Percentage of forested area disturbed in Green Mountain NF, 1991-2011, by (a) disturbance type including fire, harvests, insects, and abiotic (wind), and (b) magnitude classes, characterized by percentage change in canopy cover (CC) and categorized from least to greatest: (1) 0-25% CC, (2) 26-50% CC, (3) 51-75% CC, and (4) 76-100% CC (Figure 1j, Appendix A, USDA Forest Service, in review). Disturbed area estimates are for only Green Mountain NF and do not include disturbances or forested area in Finger Lakes NF. No fires occurred during this period. In 2011, Green Mountain NF also experienced an abiotic (wind) disturbance event, presumably tropical storm Irene, which damaged about 0.04 percent of the forested area (Fig. 6a). According to the Landsat product, insects affected a very small area of the forest following the storm. Other smaller-scale or low severity disturbances may have also occurred within the forest that were not substantial enough to be captured in this dataset. The Forest Carbon Management Framework (ForCaMF) incorporates Landsat disturbance maps summarized in Figure 6, along with FIA data in the Forest Vegetation Simulator (FVS) (Crookston and Dixon 2005). FVS is used to develop regionally representative carbon accumulation functions for each combination of forest type, initial carbon density class, and disturbance type and severity (including undisturbed) (Raymond et al. 2015). ForCaMF then

Forest Carbon Assessment for the Green Mountain National Forest Page 9 August 16, 2018 compares the undisturbed scenario with the carbon dynamics associated with the historical disturbances to estimate how much more carbon would be on each national forest if the disturbances and harvests during 1991-2011 had not occurred. ForCaMF simulates the effects of disturbance/management only on non-soil carbon stocks (i.e., vegetation, dead wood, forest floor). Like CCT, ForCaMF results supply 95 percent confidence intervals around estimates derived from a Monte Carlo approach (Healey et al. 2014). The ForCaMF model indicates that, by 2011, Green Mountain NF contained 0.22 metric tonnes per acre less carbon (non-soil) due to harvests since 1990 as compared to a hypothetical undisturbed scenario (Fig 7). As a result, non-soil carbon stocks in the forest would have been approximately 1 percent higher in 2011 if harvests had not occurred (Fig. 8). Across all national forests in the Eastern Region, harvest has been the most significant disturbance affecting carbon storage since 1990, 0.5 causing non-soil forest ecosystem 1) - 0 carbon stocks to be 3.8 percent lower by 2011 (Fig. 8). -0.5 Considering all All disturbances National Forests in Harvest the Eastern region, Wind -1 by 2011, abiotic factors (wind, ice Lost Potential Storage ac C Storage (t Potential Lost storms) accounted -1.5 for the loss of 0.48 1990 1993 1996 1999 2002 2005 2008 2011 percent of non-soil Year carbon stocks, fire Figure 7. Lost potential storage of carbon as a result of insect, harvest, and wind (abiotic) in Green Mountain NF, 1990–2011 (Figure 2j in Appendix A, 0.41 percent, and USDA Forest Service, in review). The zero line represents a hypothetical insects only 0.01 undisturbed scenario. Estimates for Green Mountain NF also contain percent. disturbance effects from Finger Lakes NF. The ForCaMF model does not track carbon stored in harvested wood after it leaves the forest ecosystem. Although harvests transfer carbon out of the forest ecosystem, most of that carbon is not lost or emitted directly to the atmosphere. Rather, it can be stored in wood products for a variable duration depending on the commodity produced, as the HWP model illustrated (Fig. 5). Harvested wood may also be burned to produce heat or electrical energy, or converted to liquid transportation fuels and chemicals that would otherwise come from fossil fuels. Wood products can also be substituted for other products that emit more GHGs in manufacturing, such as concrete and steel (Gustavsson et al. 2006, Lippke et al. 2011, McKinley et al. 2011). In the absence of commercial thinnings and harvests like those conducted in Green Mountain NF, forests will thin naturally from mortality-inducing disturbances or aging, resulting in dead trees decaying and emitting carbon to the atmosphere.

Forest Carbon Assessment for the Green Mountain National Forest Page 10 August 16, 2018 White Mountain Wind Insect Monongahela Harvest Fire Green Mountain All disturbances Allegheny Wayne Chequamegon-… Hoosier Hiawatha Superior Shawnee Ottawa Mark Twain Huron-Manistee Chippewa REGION 9

0% 1% 2% 3% 4% 5% 6% 7% 8%

2011 Non-Soil Carbon Storage Reduction Due to 1990-2011 Disturbances Figure 8. The degree to which 2011 carbon storage on each National Forest in the Eastern region was reduced by disturbances from 1990 to 2011 relative to a hypothetical baseline with no disturbance. Results were derived through the ForCaMF system (Healey et al. 2014; Raymond et al. 2015) and include all non-soil ecosystem pools (i.e., vegetation). Wind disturbances include all abiotic effects, such as storm, ice damage, and flooding.

The ForCaMF analysis was conducted over a relatively short time. After a forest is harvested, it will eventually regrow and recover the carbon removed from the ecosystem in the harvest. However, several decades may be needed to recover the carbon removed, depending on the type of harvest (e.g., clear-cut versus partial cut), as well as the conditions prior to harvest (e.g., forest type and amount of carbon). The time required to recover to pre-disturbance stocking increases with both increased removal of biomass and amount of pre-harvest aboveground live-tree carbon (Raymond et al. 2015). In some cases, removing carbon from forests for human use can result in a lower net contribution of GHGs to the atmosphere than if the forest was not managed (McKinley et al. 2011, Bergman et al. 2014, Skog et al. 2014). Therefore, the Intergovernmental Panel on recognizes wood as a renewable resource that can provide a mitigation benefit to climate change (IPCC 2000). ForCaMF quantifies and compares the effects of different disturbance trends for each forest from 1990 to 2011, providing an estimate of how much more carbon the forest would have if observed

Forest Carbon Assessment for the Green Mountain National Forest Page 11 August 16, 2018 fire, harvest, or insect trends had not occurred. This estimate helps to identify the biggest local threats to continued carbon storage and puts the recent impact of those threats into perspective. However, factors such as stand age, , and climate may affect overall carbon change in ways that are independent of disturbance trends. The purpose of the InTEC work was to reconcile recent disturbance impacts with these other factors (Sections 3.2, 3.3).

18% 3.2 Effects of Forest Aging (a) Aspen/Birch InTEC models the effects of forest 16% Maple/Beech/Birch 14% Elm/Ash/Cottonwood disturbances, aging, mortality, and Oak/Gum/Cypress 12% subsequent regrowth on carbon Oak/hickory 10% Oak/pine stocks over time. The model uses 8% Spruce/Fir inventory-derived maps of stand White/Red/Jack pine 6% age, Landsat-derived disturbance 4% maps (Section 3.1), and equations

Percentage offorested area 2% describing the relationship between 0% productivity and stand age. Stand age serves as a proxy for disturbances. When a forested stand 10 is disturbed by a severe, stand- (b) 9 replacing event, the age of the stand 8 resets to zero and the forest begins 1) - 7 to regrow. Thus, peaks of stand

1 yr 6 - establishment can indicate stand- 5 replacing disturbance events that 4 3 promoted regeneration. NPP (t C ha 2 The stand-age distribution for 1 Green Mountain NF that was 0 0 20 40 60 80 100 120 140 160 180 200 220 240 derived from 2011 FIA and Common Stand Exam data Stand age (years) Figure 9. (a) Stand age distribution in 2011 and (b) net indicates a pulse of stand primary productivity (NPP)-stand age curves for forest type establishment occurring 80 to 120 groups in Green Mountain National Forest (from Figures 1-2 years before 2011 (1890–1930) in Appendix C.14, USDA Forest Service, in review). Age (Fig. 9a). This period of elevated structure does not include stands from the Finger Lakes NF. stand regeneration came after decades of intensive logging and large wildfires in the late 1800s and early 1900s (Ward et al. 2013). Policies focusing on restoring forests after decades of overharvesting and conversion of forest to agriculture enabled these stands to establish, survive, and accumulate carbon. Stands regrow and recover at different rates depending on forest type and site conditions. Forests are typically most productive when they are young to middle-aged. Then productivity peaks and

Forest Carbon Assessment for the Green Mountain National Forest Page 12 August 16, 2018 10 declines or stabilizes as the canopy closes and forests experience higher rates of mortality and respiration. The 5 relationship between forest productivity and stand age can be represented by net 0 primary productivity (NPP)-age curves All effects Disturbance/aging (Fig. 9b). The maple/beech/birch stands -5 Climate

Accumulated (Tg) C that established in the late 1800s to early CO2 1900s would have been most productive N deposition -10 when they were around 30–60 years old, 1950 1960 1970 1980 1990 2000 2010 indicating that stands in Green Mountain Year NF were growing at relatively high Figure 10. Accumulated carbon in Green Mountain NF productivity from the 1920s through the due to individual disturbance/aging, non-disturbance mid-1900s. factors, and all factors combined for 1950–2011, excluding carbon accumulated pre-1950 (Figure 4d in InTEC model results show that Green Appendix C.4, USDA Forest Service, in review). Mountain NF was accumulating carbon steadily at the start of the analysis in the 1950s through the mid-1970s as a result of regrowth following disturbances and heightened productivity of the young to middle-aged forests (Fig. 10). This trend has been widely observed in eastern U.S. forests (Birdsey et al. 2006). However, as more stands reached older age classes, they experienced age-related declines in productivity (Fig. 9b), corresponding to a decline in carbon accumulation beginning in the late 1970s (Fig. 10). Stand establishment declined significantly over the past 60 years (Fig. 9a), further reducing the rate of carbon accumulation. Few new stands have established in Green Mountain NF over the past 20 years. Aging forests, coupled with low rates of new stand establishment, may cause the rate of carbon accumulation in Green Mountain NF to continue to decline slightly in the future, a trend projected for many forests across the United States (Birdsey et al. 2006, Wear and Coulston et al. 2015, RPA 2016). Of all the factors modeled in InTEC, historical disturbance dynamics, forest regrowth and recovery, and aging in Green Mountain NF have collectively been responsible for nearly all (up to 99 percent) carbon accumulation from the 1950s to mid-1980s (Fig. 10). However, the effects of disturbance and aging have declined relative to other factors in recent decades as forests have matured and non-disturbance factors have become more important. In 2011, disturbance and aging (and regrowth) was responsible for 38 percent of the net carbon accumulation in Green Mountain NF.

3.3 Effects of Climate and Environment The InTEC model also isolates the effects of non-disturbance factors, which include climate (temperature and precipitation), atmospheric carbon dioxide (CO2) concentrations, and nitrogen (N) deposition on forest carbon stock change and accumulation. Since 1950, annual precipitation and temperature conditions have fluctuated considerably. Annual precipitation on Green

Forest Carbon Assessment for the Green Mountain National Forest Page 13 August 16, 2018 Mountain NF has generally increased since the 1950s, with the highest total precipitation in 2011. Average annual temperatures show a less apparent trend, although temperatures were somewhat elevated in the early 1950s as well as in the 2000s (Figure 3a, b in Appendix C.4, USDA Forest Service, in review). The modeled effects of variability in temperature and precipitation on carbon stocks have varied from year to year, but overall, climate since 1950 has had a small positive effect on carbon stocks in Green Mountain NF (Fig. 10). However, several years of high temperatures over the last decade of the analysis (Figure 3b in Appendix C.4, USDA Forest Service, in review) may have caused a subtle decline in total carbon accumulation (Fig. 10). Warmer temperatures can increase forest carbon emissions through enhanced soil microbial activity and higher respiration (Ju et al. 2007, Melillo et al. 2017); they can also reduce soil moisture through increased evapotranspiration, causing lower growth rates.

In addition to climate, the availability of CO2 and N can alter forest growth rates and subsequent carbon uptake and accumulation (Caspersen et al. 2000, Pan et al. 2009). Increased fossil fuel combustion, expansion of agriculture, and urbanization have caused a significant increase in both CO2 and N emissions. The InTEC model incorporated annual global estimates of atmospheric CO2 concentrations (Keeling et al. 2009) and National Forest-scale observations of annual N deposition (National Atmospheric Deposition Program, Pan et al. 2009) to estimate the effects of CO2 and N availability on carbon stocks within a complex process modeling framework (e.g., Chen et al. 2001, Zhang et al. 2012). According to the model, higher CO2 has consistently had an increasingly positive effect on carbon stocks in Green Mountain NF, tracking an increase in atmospheric CO2 concentrations worldwide. In 2011, the CO2 effect resulted in carbon gains that were comparable to losses associated with disturbance and aging (Fig. 10). While the model estimates that CO2 had an increasingly positive effect, a precise quantification of this effect is less certain (Zhang et al. 2015). The effects of elevated CO2 on carbon accumulation was greater than both N deposition and climate combined. Nonetheless, there is still substantial debate regarding the actual influence of CO2 on terrestrial carbon stocks, warranting additional study (Jones et al. 2014). Modeled estimates indicate that overall N deposition had a small positive effect on carbon accumulation in the Green Mountain NF (Fig. 10). Like CO2, the actual magnitude of this effect remains uncertain. Estimates from inventory data in the northeast and north-central U.S. confirm that N deposition has enhanced growth among most tree species, subsequently increasing forest carbon accumulation (Thomas et al. 2010). Although N deposition generally enhances tree growth, it can also decrease growth in some species for a variety of reasons, such as leaching of soil-base cations, increased vulnerability to secondary stressors, and suppression by more competitive species (Thomas et al. 2010), and some regional studies have documented negative effects on forest productivity associated with chronically high levels of N deposition in the northeast US (Aber et al. 1998, Pardo et al. 2011). Policies limiting nitrous oxide emissions have led to a decline in N deposition since the 1990s (Figure 3b in Appendix C.13, USDA Forest Service, in review; Strock et al. 2014). The InTEC model simulated that rates of carbon accumulation associated with N deposition decreased as deposition rates declined.

Forest Carbon Assessment for the Green Mountain National Forest Page 14 August 16, 2018 Uncertainty analyses such as the Monte Carlo are not commonly conducted for process-based models because of significant computational requirements. National-scale sensitivity analyses of InTEC inputs and assumptions (Zhang et al. 2015) and calibration with observational datasets (Zhang et al. 2012) suggest that model results produce a reasonable range of estimates of the total effect. However, partitioning of the non-disturbance and disturbance effects may be less certain, and uncertainties at finer scales are likely to be even higher. Furthermore, results from the InTEC model may differ substantially from CCT estimates (Section 2.1), given the different datasets, modeling approaches, and parameters applied (Dugan et al. 2017). For example, results of CCT indicate that carbon stocks have been increasing across the Green Mountain NF since 1990, but InTEC results show a decrease. CCT is almost entirely rooted in empirical data, whereas InTEC involves more abstraction, data inputs, and modeling beyond simply summarizing ground data. Therefore, although InTEC is used here to provide information on the relative effects of disturbance and non-disturbance factors, CCT is recommended for estimates of carbon stocks and stock changes.

4.0 Future Carbon Conditions 4.1 Prospective Forest Aging Impacts The retrospective analyses presented in the previous sections can provide an important basis for understanding how various factors may influence carbon storage in the future. For example, compared to other factors, disturbance, aging, and regrowth had the largest effect on carbon trends in Green Mountain NF since 1950 (Fig. 10). The Green Mountain NF age structure indicates that roughly 76 percent of stands are over 80 years old, and few stands are young (Fig. 9a). If the forest continues on this aging trajectory, more stands will reach a slower growth stage in coming years and decades (Fig. 9b), potentially causing carbon accumulation to decline in the future. However, while past trends are informative, they can also be limited in their applicability given changes in climate and other pressures that cause stress on forest ecosystems. The Resources Planning Act (RPA) assessment (USDA Forest Service 2016) provides regional projections of forest carbon trends across the United States. These RPA estimates are based on a new approach that uses the annual FIA system developed in the early 2000s to estimate carbon stocks backward to 1990 and forward to 2060 (Woodall et al. 2015, USDA Forest Service 2016). The RPA assessment considers economic factors affecting potential land-use change and associated effects on rates of carbon accumulation or loss. For example, the RPA reference scenario assumes forest area will continue to expand at current rates until 2022, when it will begin to decline as forests are increasingly converted to other uses. However, because these projections are conducted regionally, they include all forestland ownerships, including federal, tribal, state, and private ownerships. National Forests tend to have higher carbon densities than private lands and may be subject to different land management objectives and practices. For RPA’s North Region (equivalent to Forest Service’s Eastern Region boundary, but includes all land ownerships), projections indicate that the rate of carbon sequestration may start to decline in the 2020s, mostly due to the loss of forestland (land-use change), and to a lesser extent through forest aging and increased disturbances (Fig. 11). At the global and national scales,

Forest Carbon Assessment for the Green Mountain National Forest Page 15 August 16, 2018 changes in land use— especially the conversion of forests to non-forest land— have a substantial effect on carbon stocks. Converting forest land to a non-forest use removes a very large amount of carbon from the forest and inhibits future carbon sequestration. However, National Forests tend to experience low rates of land-use change, and so Projections of forest carbon stock changes in the North Figure 11. forest land acreage would Region (equivalent to the boundaries of Eastern Region, R9, but not be expected to change includes all land tenures) for the RPA reference scenario (Figure 8-8 substantially within the in USDA Forest Service 2016). Actual net sequestration of forests is Green Mountain NF in the the total carbon stock change minus losses associated with land- future. Therefore, on use change. Solid green line: net sequestration; brown dashed line: national forest lands, the land use transfer; blue-dashed line: total carbon stock change. projected carbon trends may resemble the “net sequestration” trend in Fig. 11, which isolates the effects of forest aging, disturbance, and regrowth from land use transfers. Across the broader region, land conversion for development on private ownerships is a concern (Thompson et al. 2017, Shifley et al. 2016), and this activity can cause carbon losses (FAOSTAT 2013). 4.2 Prospective Climate and Environmental impacts The observational evidence described above and in previous sections highlights the role of natural forest development and succession as the major driver of historic and current forest carbon sequestration that is occurring at the Green Mountain NF and elsewhere in across the region. Several other modeling studies that have been conducted across the region simulate future changes in forest growth, biomass, and carbon through the middle or end of the 21st century (e.g., Ollinger et al. 2008, Thompson et al. 2011, Tang et al. 2014,Duveneck et al. 2017, Janowiak et al. 2018). Although these studies may include multiple ownerships and vary in the degree that they incorporate the potential for carbon changes from forest harvest and natural disturbances, they all include scenarios of climate change. From this robust collection of work, the collective evidence points to continued forest growth and recovery from past disturbances as the major driver of landscape-scale forest carbon gains for many decades into the future, in the absence of major disturbances from climate change or other causes (Shifley et al. 2016, Duveneck et al. 2017, Janowiak et al. 2018). Climate change introduces additional uncertainty about how forests—and forest carbon sequestration and storage—may change in the future. Climate change causes many direct alterations of the local environment, such as changes in climate variables like temperature and

Forest Carbon Assessment for the Green Mountain National Forest Page 16 August 16, 2018 precipitation, and it has indirect effects on a wide range of ecosystem processes (Vose et al. 2012). Further, disturbance rates are projected to increase with climate change (Joyce et al. 2014), making it challenging to use past trends to project the effects of disturbance and aging on forest carbon dynamics. A climate change vulnerability assessment of New England and northern New York (Janowiak et al. 2018), which encompasses the Green Mountain NF, describes projected changes in forest ecosystems through the end of the 21st century that could affect forest productivity and, ultimately, carbon sequestration and storage. Climate change is expected to cause temperatures to continue to rise in all seasons, increasing mean temperatures as well as the frequency of heat waves. Growing season length is expected to increase by several weeks under various climate scenarios, and a longer growing season may enhance forest growth and carbon sequestration, where water supply is adequate and temperatures do not exceed biological thresholds (McMahon et al. 2010, Janowiak et al. 2018). Elevated temperatures may increase and reduce soil moisture through increased evapotranspiration, which would negatively affect growth rates and carbon accumulation (Ju et al. 2007, Melillo et al. 2017). Modeled results of recent climate effects using the InTEC model indicate that years with elevated temperatures have generally had a negative effect on carbon uptake in the Green Mountain NF (Fig. 10). Mean annual precipitation in New England and northern New York is projected to increase, although seasonal precipitation projections are less certain. Winter precipitation is projected to increase the most, though the amount of precipitation falling as snow is expected to decline as temperatures warm. More intense precipitation and extreme storm events are expected to continue increasing in this region. The potential for reduced soil moisture and drought is also predicted to increase, especially later in the growing season as increased temperatures drive evapotranspiration (Campbell et al. 2009, Zhao and Dai 2016, Berg et al. 2017). Although a longer growing season may increase annual biomass accumulation, could offset these potential growth enhancements and increase the potential for other forest stressors. Drought- stressed trees may also be more susceptible to insects and pathogens (Dukes et al. 2009), which can significant reduce carbon uptake (Kurz et al. 2008, Amato et al. 2011, Healey et al. 2014). Changes in climate are expected to drive many other changes in forests through the next century, including changes in forest establishment and composition (Janowiak et al. 2018). Altered temperature, precipitation, and growing season may affect the ability of some species to germinate and regenerate (Walck et al. 2011, Anderson-Teixeira et al. 2013, Iverson et al. 2017,Petrie et al. 2017). Some northern tree species are expected to be particularly vulnerable in the future as climate conditions drive declines or failures in species establishment or habitat suitability (Iverson et al. 2017, Janowiak et al. 2018). Model projections suggest that many northern conifer species, including balsam fir, red spruce, and black spruce, are the most vulnerable to climate change—particularly at lower elevations or more southerly locations and at the end of this century. The potential for future declines of northern species increase the risk of carbon losses in forest communities dominated by these species, particularly under scenarios of greater warming (Ollinger et al. 2008, Duveneck et al. 2017, Janowiak et al. 2018,). Further,

Forest Carbon Assessment for the Green Mountain National Forest Page 17 August 16, 2018 climate-driven failures in species establishment further reduce the ability of forests to recover carbon lost after mortality-inducing events or harvests. Although future climate conditions also allow for other future-adapted species to increase, there is greater uncertainty about how well these species will be able to take advantage of new niches that may become available (Duveneck et al. 2017, Iverson et al. 2017).

Lastly, CO2 emissions are projected to increase through 2100 under even the most conservative emission scenarios (IPCC 2014). Several studies point to the beneficial effects of carbon dioxide fertilization, particularly in deciduous forests. Several models, including the InTEC model (Figure 10), project greater increases in forest productivity when the CO2 fertilization effect is included in modeling (Aber et al. 1995, Ollinger et al. 2008, Pan et al. 2009, Zhang et al. 2012). Often, the models project that CO2 fertilization has a greater effect on forest productivity than does climate change. However, the effect of increasing levels of atmospheric CO2 on forest productivity is transient and can be limited by the availability nitrogen and other nutrients. Long- term studies examining the relationship between increased atmospheric CO2 and soil nitrogen availability show that forests initially respond with higher productivity and growth, but the effect is greatly diminished or lost within 5 years in most forests (Norby et al. 2010). There has been considerable debate regarding the effects of elevated CO2 on forest growth and biomass accumulation (e.g., Körner et al. 2005, Norby et al. 2010, Jones et al. 2014, Zhu et al. 2016). Further, productivity increases under elevated CO2 could be offset by losses from limate-related stress or disturbance. Given the complex interactions among forest ecosystem processes, disturbance regimes, climate, and nutrients, it is difficult to determine precisely how forests and carbon trends will respond to novel future conditions. Furthermore, the effects of future conditions on forest carbon dynamics may change over time. As climate change persists for several decades, critical thresholds may be exceeded, causing unanticipated responses to some variables like increasing temperature and CO2 concentrations. The effects of changing conditions will almost certainly vary by species and forest type. Some factors may enhance forest growth and carbon uptake, whereas others may hinder the ability of forests to act as a carbon sink, potentially causing various influences to offset each other. Thus, it will be important for forest managers to continue to monitor forest responses to these changes and potentially alter management activities to better enable forests to better adapt to future conditions.

5.0 Forest Carbon Summary An assessment of forest carbon stocks and factors that influence carbon accumulation is critical for understanding how forests may respond to changing environmental and management conditions. The long-term capacity of forest ecosystems and wood products to sequester and store carbon depends in large part on their resilience, adaptive capacity, and utilization of timber (McKinley et al. 2011). Under a changing climate, forests are expected to be increasingly at risk of a variety of stressors, including moisture stress, forest insects and diseases, invasive species, and extreme weather events (e.g., Kurz et al. 2008, Allen et al. 2010, Vose et al. 2012, Janowiak et al. 2018). While, maintaining resilient forest structures and composition will not eliminate those forests stressors, doing so can reduce the occurrence of significant disruptions that may

Forest Carbon Assessment for the Green Mountain National Forest Page 18 August 16, 2018 cause large or long-term carbon losses (Millar et al. 2007, Millar and Stephenson 2015, Swanston et al. 2016). Ensuring that forests ecosystems are capable of adapting to changing conditions will help forests sequester carbon and store it more securely over the long term, while also providing woody biomass to help reduce fossil fuel use. This forest carbon narrative for Green Mountain NF provides a snapshot of baseline carbon stocks and the effects of various factors on forest carbon dynamics. Key findings include: • From a carbon perspective, forests in Green Mountain NF are thriving. Aside from expected, natural age-related slowing of carbon sequestration, forests have not experienced recent negative effects from disturbances or environmental conditions. • Forest ecosystem carbon stocks increased by about 48 percent between 1990 and 2013, thus maintaining a carbon sink. • Timber harvesting has been the dominant disturbance type in the forest. However, harvests have been relatively small, typically affecting less than 0.25 percent of forested area annually. Harvests have also been mostly of low intensity and characterized by less than 25 percent reductions in canopy cover. • Carbon losses from the forest ecosystem associated with harvests from 1990 to 2011 have been small compared to the total amount of carbon stored in the forest, causing the loss of roughly 1 percent of non-soil carbon by 2011. However, these estimates do not account for either the continued storage of harvested carbon in wood products or substitution effects. • Carbon storage in HWPs and landfills has increased since the early 1900s. However, recent declines in timber harvesting have caused the rate of carbon accumulation in the product sector to decline. If current trends continue, the decay of retired products may exceed the addition of carbon to the HWP pool, causing the product sector to be a net source of carbon. • Forests are mostly middle-aged and older, which reflects recovery from over-harvesting and clearing of land for agriculture in the late 1800s and early 1900s. Young to middle- aged stands are generally productive and accumulate carbon rapidly. Although older forests store more carbon, the rate of carbon uptake and sequestration tends to decline as forests age due to increasing mortality and respiration. • Historical disturbance dynamics, forest regrowth and recovery, and forest aging have been most responsible for driving carbon accumulation trends since 1950.

• Some models have found that increasing atmospheric CO2 concentrations has significantly enhanced forest growth and subsequent carbon accumulation. However, the impact of CO2 on forest growth is still quite uncertain and requires additional research. • The InTEC model suggests that N deposition had a positive influence on carbon stocks in Green Mountain NF, although smaller than the effects of disturbance/aging and CO2 fertilization. However some studies have found that chronically elevated levels of N

Forest Carbon Assessment for the Green Mountain National Forest Page 19 August 16, 2018 deposition can decrease growth and carbon accumulation in some forest types. • Of the disturbance and non-disturbance factors assessed, climate has had the smallest and most variable effect on forest carbon accumulation. Elevated temperatures, particularly over the last decade, have caused a decline in carbon accumulation. • Continued forest aging is expected to slow the growth rates and carbon sequestration. Projections from the RPA assessment also indicate a potential age-related decline in forest carbon stocks in the Eastern region (all land ownerships) beginning in the 2020s. • The effects of future climate and atmospheric conditions are complex and remain uncertain. Projected elevated temperatures and potential moistures stress may hinder future forest carbon accumulation. However, a longer growing season and potential growth enhancements due to CO2 concentrations could partially offset declines in biomass and carbon accumulation caused by age-related or climate-induced productivity declines. The IPCC has summarized the contributions of global human activity sectors to climate change in its Fifth Assessment Report (IPCC 2014). From 2000 to 2009, forestry and other land uses 3 contributed just 12 percent of human-caused global CO2 emissions. The forestry sector contribution to GHG emissions has declined over the last decade (FAOSTAT 2013, IPCC 2014, Smith et al. 2014). Globally, the largest source of GHG emissions in the forestry sector is deforestation (Pan et al. 2011, Houghton et al. 2012, IPCC 2014), defined as the removal of all trees to convert forested land to other land uses that either do not support trees or allow trees to regrow for an indefinite period (IPCC 2000). However, the United States is experiencing a net increase in forest land in recent decades because of the reversion of agricultural lands back to forest, a trend expected to continue for at least another decade (Wear et al. 2013, USDA Forest Service 2016).

Estimates of forested area in Green Mountain NF are similar to broader patterns in the U.S. and have remained stable or increased slightly since 1991. Forested area in Green Mountain NF will not be converted into a developed or agricultural condition or otherwise undergo a loss of forested area. In fact, forest stands are being retained and harvested to maintain conditions that support enhanced tree growth and productivity, contributing to long-term carbon uptake and storage. In 2010, U.S. forests removed about 206 teragrams of carbon from the atmosphere after accounting for natural emissions, such as wildfire and decomposition (US EPA, 2015).

Timber harvesting in Green Mountain NF is not considered a major source of carbon emissions. Climate change is a global phenomenon because major GHGs4 mix well throughout the planet’s lower atmosphere (IPCC 2013). Emissions of GHGs in 2010 were estimated at 13,336 ± 1,227 teragrams C globally (IPCC 2014) and 1,881 teragrams C nationally (US EPA, 2015). In this

3 Fluxes from forestry and other land use (FOLU) activities are dominated by CO2 emissions. Non-CO2 from FOLU are small and mostly due to peat degradation releasing methane and were not included in this estimate.

4 Major greenhouse gases released a result of human activity include: carbon dioxide, methane, nitrous oxide, and hydrofluorocarbons and perfluorocarbons.

Forest Carbon Assessment for the Green Mountain National Forest Page 20 August 16, 2018 context, timber harvesting in Green Mountain NF makes an extremely small contribution to overall emissions, reducing potential carbon stocks on the forest by about 1 percent since 1991. Moreover, because local emissions mix readily into the global pool of GHGs, it is difficult to ascertain the indirect effects of emissions from single or multiple projects on global climate. Therefore, at global and national scales, the direct and indirect contribution of Green Mountain NF to GHGs and climate change would be negligible. Because the direct and indirect effects would be negligible, the contribution of management activities to cumulative effects on global GHGs and climate change would also be negligible.

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