Economics of integrated harvests with biomass for energy in non-industrial forests in the northeastern US forest

Forest Policy and Economics 109 (2019) 102023

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Forest Policy and Economics journal homepage: www.elsevier.com/locate/forpol

Economics of integrated harvests with biomass for energy in non-industrial forests in the northeastern US forest

T

Thomas Buchholza,b,⁎, William S. Keetona,b,c, John S. Gunnd a

Gund Institute for Environment, University of Vermont, 617 Main Street, Burlington, VT 05405, USA Spatial Informatics Group, LLC, 2529 Yolanda Court., Pleasanton, CA 94566, USA c The Rubenstein School of Environment and Natural Resources, 343 Aiken Center, University of Vermont, 81 Carrigan Drive, Burlington, VT 05405, USA d New Hampshire Agricultural Experiment Station, University of New Hampshire, 131 Main Street, 210 Nesmith Hall, Durham, NH 03824, USA b

ARTICLE INFO

ABSTRACT

Keywords: Forest biomass Bioenergy Economics Logging costs Wood energy Northern hardwood forests

Economic drivers explaining the harvest of biomass for energy use in northeastern forests in the United States are not well understood. However, knowledge of these drivers is essential for bioenergy policy development, biomass supply estimates, and assessments of harvesting impacts on forest ecosystems and carbon stocks. Using empirical data from 35 integrated harvest sites in northeastern US non-industrial forests, we analyzed the economics of mixed wood product logging operations that included biomass for energetic use from both landowner and logging contractor perspectives. Results were highly variable but indicate that biomass harvest removal intensities were not explained by primary forest management objectives, harvest area, or harvested wood product quantity. Rather than harvest area or choice of machinery, we identified biomass harvest intensity as a main driver of profits for a harvest operation, as measured in hourly and total net income to the logging contractor. While biomass stumpage payments to the landowner were marginal, tree bole biomass constituted more than half (54%) of the extracted volume by weight, far outweighing biomass derived from tops and limbs only. Biomass harvests, therefore, might encourage logging contractors to intensify harvest removals rather than increase harvest area or choose a specific harvest type or method. Such intensification could have beneficial or detrimental impacts on a stand and needs to be addressed through further studies of potential consequences for biodiversity and various ecosystem services.

1. Introduction Harvesting woody ‘biomass’ for energetic use has been a major component of forest management in the northeastern United States (US) for decades. However, state-level commitments to reduce greenhouse gas emissions from fossil fuel use (Walker et al., 2013), desire for increased reliance on locally-sourced energy (Buchholz and Gunn, 2017) and a decline of other low-grade markets (Levesque and Kingsley, 2017) have triggered renewed interest in forest-derived biomass availability in the northeastern US. These modern uses include pellet and wood chip industrial applications, such as commercial building heating, district heating systems, and local electricity and/or heat production. For instance, in New York, where close to 40% of the harvested volume is for biomass markets, thermal applications consume over half of this supply and electricity generation takes approximately another third (North East State Foresters Association, 2013). Consequently, wood has remained a widely sought after and generally cost-

⁎

efficient alternative within the region's energy market (U.S. Energy Information Administration, 2019). A number of studies have examined current and future biomass supply potential in the region (BERC, 2010; Buchholz et al., 2011; Walker et al., 2013), biomass harvest implications for carbon cycles (Mika and Keeton, 2015; Walker et al., 2013) and post-harvest attributes of forest habitats (Littlefield and Keeton, 2012). State-level policies that used data from these studies have been enacted in the region to guide biomass harvests and use (Massachusetts Department of Energy Resources, 2012; North East State Foresters Association, 2012; Vermont Department of Forests, Parks and Recreation, 2015). As part of a global trend (World Bioenergy Association, 2017), these policies also frequently aim to encourage the expanding use of woody biomass energy in the northeastern US and reflect an interest in mitigating climate change by reducing the reliance on fossil fuels and strengthening local economies. Additionally, biomass markets will be required to financially support silvicultural activities necessary to restore degraded

Corresponding author at: Gund Institute for Environment, University of Vermont, 617 Main Street, Burlington, VT 05405, USA. E-mail address: [email protected] (T. Buchholz).

https://doi.org/10.1016/j.forpol.2019.102023 Received 20 May 2019; Received in revised form 5 September 2019; Accepted 7 September 2019 1389-9341/ © 2019 Elsevier B.V. All rights reserved.

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forests in the region for timber production and other ecosystem service values (Gunn et al., 2019). Despite this growing need for biomass, there is currently limited capacity to expand biomass extraction from secondary (e.g. sawmill residues) and tertiary wood sources (e.g. post-consumer waste; BaisMoleman et al., 2015). Biomass supply projections also indicate that forests in the northeastern US have little capacity to increase production in the near future (Canham et al., 2013), so meeting growing demands may be a challenge. The financial viability of the production of biomass (harvest, extraction, and transport) compounds the challenge of satisfying increasing demand. This is largely because biomass is a low-value product and is frequently only recovered as a co-product of timber/sawlog and/or pulpwood harvest operations (‘integrated harvests’), or processing of higher-value products such as lumber. The forest industry in the northeastern US is dominated by small-scale nonindustrial private forest (NIPF) ownerships. For instance, private forests account for over 75% of Vermont's forests. With industrial/corporate forests playing a minor role, > 80% of private forests (> 4 ha holdings) in Vermont are NIPF averaging around 25 ha in size (Butler et al., 2014). Forest harvests are typically conducted by a logging contractor who administers the tree marking, harvest operation, and transport to a wood processing facility. In this business model, the logging contractor pays stumpage to the landowners for the trees cut and pays for labor and machinery including log/biomass transport. Revenues to logging contractors from the sale of biomass often fails to cover the costs of extraction and transport. As such, direct returns from biomass to the landowner can be minimal. For instance, Cai et al. (2016) concluded that “revenues from harvesting biomass alone are unlikely to significantly influence the social availability of woody biomass.” Landowners in New York received over 90% of their revenue from sawtimber and < 5% from pulp or biomass (North East State Foresters Association, 2013). If i) harvesting biomass in non-industrial forests is of minimal economic value to both loggers and landowners are the dominant ownership type, it is important to understand the economic drivers of biomass harvesting in order to inform state-level policies for incentivizing sustainable biomass production. However, recent economic studies of logging in the region have not included biomass harvests in their analyses (Hiesl and Benjamin, 2013; Regula et al., 2018), focused on models for biomass processing logistics (Whalley et al., 2017), or relied on qualitative evaluations of ‘willingness-to-harvest’ (see Supplementary Information). To understand the economic drivers of biomass harvesting, we: i) collected field-based data on harvested wood product volumes (timber, pulp, biomass); ii) assessed biotic and abiotic site characteristics of harvest operations representative of the northeastern US; iii) calculated the volumetric distribution of forest products harvested; iv) analyzed the cost and profit structure of harvest operations from both logging contractors and landowners perspectives; and v) identified relationships between per ha harvest volume, harvest area, harvest method (whole tree vs. partial cut) and total biomass harvest volume.

Fig. 1. Map of the study sites (n = 35) (adapted from Mika and Keeton, 2013).

The sites were selected based on a range of criteria significant for this economic analysis: area of naturally regenerated stands, evidence of a recent (2007–2010) harvest with a biomass component (including firewood), and region-typical partial harvest operations (i.e. exclusion of clearcuts, see Sader and Legaard, 2008). The sites were largely multiaged from a history of partial harvesting and stands ranged in age from 40 to 130 years. Whole tree and non-whole tree operations were practiced on 25 and 10 sites, respectively (see Supplementary Information 1 for additional site-specific information). 2.2. Site and harvest characteristics A standardized survey collected information about: management objectives (timberland, maple syrup production, recreation), silvicultural prescription (crop tree release, single-tree harvest, commercial/pre-commercial thinning, shelterwood, group selection, salvage), whole tree harvest (WTH) or non-WTH, chipping location for WTH sites, harvested wood product volumes (timber, pulp, biomass chips, biomass/firewood) for bioenergy (industrial scale bioenergy for heat/ electricity, firewood), physical characteristics (e.g. harvest area), as well as number, type and size of harvesting machinery (chainsaw, tracked/wheeled single-grip/shear harvester, feller-buncher), type and size of transport machinery from felling to landing site (tracked/ wheeled grapple/cable skidder, forwarder), and type and size of landing machinery (slasher, delimber, loader). Harvest volumes were recorded by product type (timber, pulp, biomass; see Tables 1–3). Where applicable, we used a single-factor ANOVA for statistical analysis. Payments from the landowner to the logging contractor (e.g. for wildlife habitat improvements) were not recorded since our goal was to understand the incentive biomass (rather than other products or management objectives) may or may not provide for logging economics.

2. Methods

2.3. Logging economics

2.1. Site description

To understand economic drivers for biomass harvest, it is informative to examine biomass availability from a logging contractor's profit-maximizing perspective. On non-industrial forests in the northeastern US, logging contractor revenues are derived from i) the contractor selling harvested wood products (HWP) to an end user or processing facility and, ii) receiving supplementary payments from the landowner to achieve management objectives such as pre-commercial thinning. These revenues are used to pay for stumpage, labor, and other expenses. A logging contractor’s perspective is driven both by the biomass market price and extraction costs, including the fossil fuel market (Winchester and Ledvina, 2017) and competing low-grade wood product markets (Stevens, 2015).

The study area was located in the northern hardwood region of the northeastern US. The 35 harvest sites were predominantly in Vermont, but also included sites in New Hampshire and New York (Fig. 1). This dataset is identical to the one described in Mika and Keeton (2013) and Littlefield and Keeton (2012). Dominant species at the harvest sites included Acer saccharum (sugar maple), Fagus grandifolia (American beech), Betula alleghaniensis (yellow birch), and Tsuga canadensis (eastern hemlock) with significant components of Fraxinus americana (American white ash), Acer rubrum (red maple), and Pinus strobus (eastern white pine). 2

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Table 1 Site characteristics for live trees in unharvested stands including: forest types; percent slope; elevation (meters), aspect (degrees), percent conifer of basal area (BA); total basal area (m2/ha); quadratic mean diameter (QMD) at breast height (cm); aboveground live (AGL) biomass (Mg/ha); and percent canopy closure (Littlefield and Keeton, 2012). Site ID

Forest type

Slope (%)

Elevation (m)

Aspect (°)

Conifer share (% B)

BA (m2/ha)

QMD (cm)

AGL biomass (Mg/ha)

Canopy closure (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 Mean

Pine Hardwood Northern Hardwood Maple-Basswood Oak Northern Hardwood Northern Hardwood Hemlock Hardwood Northern Hardwood Pine Hardwood Hemlock Hardwood Hemlock Hardwood Northern Hardwood Spruce-Northern Hardwood Pine Hardwood Hemlock Hardwood Sugar Maple Mesic Mixed Pine-Hardwood Spruce-Northern Hardwood Mesic Mixed Pine-Hardwood Spruce-Northern Hardwood Spruce-Northern Hardwood Northern Hardwood Northern Hardwood Hemlock Hardwood Northern Hardwood Northern Hardwood Beech-Maple Hemlock Hardwood Northern Hardwood Pine Hardwood Northern Hardwood Northern Hardwood Pine Hardwood Mesic Mixed Pine-Hardwood Spruce-Northern Hardwood Northern Hardwood N/A

23.1 12.3 17.6 15.8 24.9 5.2 10.5 7.0 14.1 12.3 10.5 21.3 10.5 0.0 48.8 3.5 19.4 3.5 14.1 8.7 17.6 12.3 10.5 19.4 7.0 8.7 23.1 12.3 10.5 21.3 19.4 3.5 8.7 21.3 14.1 14.1

233 248 219 277 596 165 439 230 155 156 244 407 292 306 538 209 467 377 385 438 542 422 315 542 434 478 135 544 269 397 393 463 333 415 601 362

234 221 50 179 30 205 96 114 245 326 183 26 66 139 53 39 156 147 265 280 243 212 229 189 244 253 47 235 240 181 75 77 254 32 223 N/A

28.9 7.9 8.9 3.4 10.7 50.5 9.6 26.2 43.5 41.2 5.5 52.1 18.1 66.7 1.7 10.9 43.9 3.2 17.6 9.4 0.0 0.0 33.9 4.7 0.0 8.3 49.2 4.4 27.6 5.1 0.0 25.4 3.1 2.3 3.3 17.9

24.9 28.9 25.8 27.1 32.1 46.4 33.5 26.2 31.7 15.6 31.6 33.5 38.1 41.3 26.6 31.6 23.5 28.5 19.5 29.4 28.5 26.4 22.6 29.4 35.0 20.7 37.3 31.2 34.9 22.4 23.9 27.1 29.8 19.7 28.0 28.9

23.9 21.6 17.6 20.9 16.7 27.4 17.7 23.9 30.0 21.3 19.0 16.1 19.4 27.2 21.0 18.7 17.1 21.8 19.7 18.1 19.8 21.7 24.1 25.1 21.7 13.7 22.8 17.6 20.7 17.1 20.6 13.7 16.9 15.4 18.6 20.2

152.4 185.7 162.5 177.0 202.5 303.7 217.5 158.6 213.9 106.2 189.4 205.1 253.4 244.7 206.4 187.6 123.1 202.0 114.8 189.1 186.7 185.3 143.9 190.3 240.1 140.3 218.2 209.2 203.8 145.4 171.3 148.1 175.7 113.4 182.2 184.3

67 87 84 84 95 97 94 71 83 46 88 86 96 89 88 93 69 91 59 80 80 88 64 89 94 67 93 98 86 72 81 80 91 65 93 82

to the operator. Other costs included machine mobilization ($500 and $2000 delivery costs for tractors and all other specialized forestry equipment, respectively). Since the logging contactors' income was based on an individual harvest site wood products' income, only indirect labor costs, including insurance, were considered as an additional expense variable and set at 30% of direct labor costs. We employed a contractor income of $14.7/h as reported by the Bureau of Labor Statistics (Bureau of Labor Statistics, 2018). This wage is representative for the region and changed < 2% between 2007 and 2010. As in other logging economics studies (e.g. Stewart and Nakamura, 2012), we were unable to identify harvest planning and permitting costs and therefore had to exclude these costs. Because each harvest operation used a unique combination of logging systems (felling, forwarding/skidding, operations at the landing site), we calculated a case-specific harvest cost based on machine rates and productivity (Table 5). This resulted in a baseline site with a harvest intensity of 65 gt/ha. Lacking site-specific data, this harvest intensity is reflective of the 2007–2012 average logging intensity for New York of 68 gt/ha (USDA USDA FS, 2015) and within the range of 27–67 gt/ha observed in New Hampshire from 2013 to 2017 (Evans, 2019). For a baseline harvest, total logging costs (felling, forwarding/ skidding, operations at the landing site) including a fixed labor rate ranged from $21/gt for WTH (using a large feller-buncher with grapple skidder forwarding, including chipping) to $29/gt for non-WTH (using chainsaws with cable forwarding, no chipping). Chipping costs of $8.6/ gt are at the lower end compared to data from other regions but reflect the established nature of the biomass industry in the study region where chipping equipment is usually written off due to its advanced age.

We recorded HWP volumes using a variety of metrics (board feet for timber, cord and green short tons for pulp, green short tons for biomass, cord and green short tons for firewood). We normalized HWP volumes to green metric tonnes (gt) using a conversion rate of 0.155 MBF (1000 board feet)/gt based on regional averages and 0.418 cords/gt based on the average harvest site-specific hardwood/softwood mix. Harvest operations were conducted over a 3-year period between 2007 and 2010. All economic input variables were adjusted for inflation to 2010 US dollars in the analysis to account for inflation. Where possible, we retrieved regional stumpage and delivered-tothe-mill prices for timber, pulp and biomass (Table 4; Kingsley, 2011; Northern Woodlands Magazine, 2018; NYSDEC, 2018). Since available species- and dimension-specific harvest volume data were limited, we calculated a representative species-independent price index based on the regional harvest mix for a given year (Vermont Department of Forests, Parks and Recreation, 2018). Data on 2007 to 2010 timber stumpage payments was incomplete. Therefore, we calculated timber stumpage based on timber mill price and processing costs (felling, skidding/forwarding, handling at landing site, road transport). We assumed average transport costs of USD ($) 8.8/gt based on an average transport distance of 80 km (e.g. Whalley et al., 2017). 2.3.1. Machine rates and productivity, logging contractor net income Costs for harvest equipment were calculated based on a scheduledmachine-hour (SMH) basis, which is the actual time a machine is deployed to the field and which usually equates to around 2000 h per year (Brinker et al., 2002). SMH costs include all variable (fuel, spare parts, repairs) and fixed (financing, tax, depreciation) costs except wages paid 3

4

2009 2008 2010 2008 2008 2009 2010 2007 2010 2009 2010

2008 2008 2009 2009 2008 2009

2009 2007 2009 2008

2010 2008 2008 2007 2010 2008 2010 2010 2009 2010 2009 2009 2009

2 3 4 5 6 7 8 9 10 11 12

13 14 15 16 17 18

19 20 21 22

23 24 25 26 27 28 29 30 31 32 33 34 35

prod.

prod.

prod.

prod.

prod.

Timberland Timberland Timberland Timberland Timberland Timberland Timberland Timberland Timberland Timberland Timberland Timberland Timberland

Timberland Timberland Timberland Timberland

Timberland Timberland Timberland Maple syrup prod. Recreation Timberland

Maple syrup Timberland Maple syrup Timberland Timberland Timberland Maple syrup Timberland Maple syrup Timberland Maple syrup

Maple syrup prod.

Primary management objective

Crop tree release (also intermediate thinning) Single-tree selection Crop tree release (also single tree selection) Intermediate thinning Pre-commercial thinning Salvage logging (also single tree selection) Crop tree release (also small group selection) Single tree selection (also intermediate thinning) Crop tree release Crop tree release Crop tree release (also intermediate thinning and group selection) Single tree selection Single tree selection Shelterwood Crop tree release (also intermediate thinning) Group selection Single tree/small group selection and intermediate thinning Intermediate thinning Group selection Group selection Single tree/small group selection (also intermediate thinning) Intermediate thinning Shelterwood Small group selection and intermediate thinning Single tree selection Group selection (also intermediate thinning) Intermediate thinning (also group selection) Intermediate thinning and group selection Shelterwood Intermediate thinning Salvage logging and shelterwood Crop tree release and intermediate thinning Crop tree release and intermediate thinning Single tree/small group selection

Crop tree release (also intermediate thinning)

Treatment type

Cordwood production for manually fed wood stoves.

2009

1

a

Harvest year

Site ID

WTH WTH non-WTH WTH WTH WTH non-WTH WTH WTH WTH non-WTH non-WTH WTH

WTH WTH WTH WTH

non-WTH non-WTH WTH WTH WTH non-WTH

WTH WTH WTH WTH non-WTH non-WTH non-WTH WTH WTH WTH WTH

WTH

Harvest type

Landing Landing N/Aa Landing Landing Landing N/Aa Landing Landing Landing N/Aa N/Aa Landing

Landing Landing Landing Landing

site

site site site

site site site

site site

site site site site

Final destination Final destination Landing site Landing site Landing site N/Aa

Landing site Landing site Landing site Landing site Final destination N/A Final destination Landing site Landing site Landing site Landing site

Landing site

Chipping location

Chainsaw FB Chainsaw FB FB FB Chainsaw FB FB Chainsaw & FB FB Chainsaw Chainsaw

Chainsaw FB FB FB

Chainsaw & FB Chainsaw & FB FB Large FB FB FB

Large feller-buncher (FB) Chainsaw FB Chainsaw Large FB Chainsaw Chainsaw Chainsaw Chainsaw & large FB Chainsaw & large FB FB Large FB

Cutting equipment

Table 2 Forest management and harvest operation characteristics by site. Harvest types included whole-tree (WTH) and non-WTH harvest operations.

Cable tractor Grapple skidder Cable tractor Grapple skidder CT & GS Grapple skidder Cable tractor Grapple skidder Grapple skidder Grapple skidder CT & GS Cable tractor CT & GS

Cable tractor Grapple skidder CT & GS Grapple skidder

CT & Forwarder CT & Forwarder Grapple skidder Grapple skidder Grapple skidder Grapple skidder

Grapple skidder CT & GS

Cable tractor (CT) Grapple skidder Cable tractor CT & GS Cable tractor CT & GS CT & Forwarder

Large grapple skidder (GS)

Transport equipment (felling to landing site)

No Yes No Yes Yes Yes No Yes Yes Yes Yes No Yes

No Yes Yes Yes

Yes Yes Yes Yes Yes Yes

Yes Yes Yes Yes No Yes No Yes Yes Yes Yes

Yes

Slasher at landing

T. Buchholz, et al.

Forest Policy and Economics 109 (2019) 102023

Comment

2007

2008

2009

2010

Biomass Pulp Timber Pulp Biomass

Chipped, at mill gate At mill gate, logs At mill gate Stumpage Stumpagea

29 34 67.3 3.9 1.9

41 47 62.1 4.3 2.2

31 37 53.2 3.4 1.7

30 35 48.2 4.3 2.2

a

Estimates are region-wide. Biomass stumpage was in many cases as low as $1/gt.

Overall biomass chip processing costs of $16–$24/gt depend on harvest type (WTH, non-WTH) and equipment. These costs are comparable to estimates for the region ($12–33 $/gt; Whalley et al., 2017) or in other non-clearcut operations in similar natural forests in Missouri (Saunders et al., 2012). To account for productivity changes when deviating from the average logging intensity, we developed a harvest cost adjustment curve in collaboration with regional harvest operations experts (Fig. 2). If large equipment was used (feller-buncher or grapple skidder), we assumed a harvest cost reduction of 30% per gt to account for productivity increases. We further assumed that non-WTH adds 30% to forwarding costs. None of the surveyed sites had slopes exceeding 20%, therefore there was no need to consider harvesting on steep slopes. 5

b

Product type

a

Table 4 Forest product prices in 2010 $/gt by year. Stumpage and mill price reflect regional species' mix for a given year (Kingsley, 2011; Northern Woodlands Magazine, 2018; NYSDEC, 2018).

10.5 8.6 16.0 12.0e 19.1 19.1

– 11 16 4 133 59 45 3 4 – 18 – 33 46 – – – 3 2 – 10 – 12 10 181 – 4 – 15 – – 24 25 21 7 21

69.7b 71.0e

37 34 73 13 25 29 – 2 36 45 49 18 17 23 47 38 22 – 16 32 21 90 42 62 – 66 22 45 – 62 34 10 – – 14 29

Slasher/loader Roadside chippingd

4 – – 1 – 68 – – 49 – – – – – 90 – 28 – – 21 10 67 – – – – – 45 – 37 20 – 25 21 – 16

Brinker et al. (2002); Long et al. (2002) RE Consulting, INRS LLC (2007); Wang et al. (2004) Brinker et al. (2002) Brinker et al. (2002); RE Consulting, INRS LLC (2007); Wang et al. (2004) Brinker et al. (2002); Hiesl and Benjamin (2013); RE Consulting, INRS LLC (2007) Brinker et al. (2002); Hiesl and Benjamin (2013) Aman et al. (2011); Whalley et al. (2017)

2 11 42 8 8 39 32 26 – 21 23 – 116 162 38 28 39 3 20 27 10 34 67 22 20 2 18 26 13 25 13 14 5 10 21 27

2.9 2.9 8.6 11.0 6.1

34% 30% 48% 15% 57% 51% 32% 18% 38% 41% 38% 12% 49% 51% 61% 36% 62% 3% 31% 39% 24% 59% 57% 42% 47% 46% 45% 44% 19% 64% 36% 41% 39% 35% 24% 39%

26.1 6.8 8.6 5.4 11.3

49 20 7 121 46 30 8 6 28 40 4 24 61 32 5 109 16 20 28 52 101 4 20 43 5 34 61 24 12 16 14 121 30 61 30 37

19.1 19.1 19.1 19.1 19.1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 Mean

59.0b 1.4c 57.1b 40.2b,c 49.7b,c

Cordwood (gt/ha)

Feller-buncher Chainsaw Grapple tractor/skidder Cable tractor/skidder Forwarder

Biomass (gt/ha)

Source

Pulp (gt/ ha)

Harvest cost (2010 $/gta)

Timber (gt/ha)

Harvest productivity (gt/SMH)

Volume removed (% of unharvested stand vol.)

Harvest labor cost (2010 $/SMH)

Harvest size (ha)

Harvest machine cost (2010 $/SMH)

Site ID

Machine type

Table 5 Harvest cost and productivity assumptions based on literature. Scheduled machine hour (SMH) costs include financing, insurance and maintenance and resale value. Labor costs included indirect costs as 30% of direct labor costs. We assumed a 30% productivity increase if larger-than-usual equipment was used.

Table 3 Harvest volume characteristics (green metric tonnes; gt). Biomass is defined as tree boles or wood chips for bioenergy applications while cordwood is sold for manually fed wood stoves in the residential market.

Independent of forest product (timber, pulp, biomass) except for chipping. Brinker et al. (2002). c RE Consulting, INRS LLC (2007) and Wang et al. (2004). d Including all machinery required on landing site to feed chipper. e While roadside chippers can have much higher costs (e.g. Whalley et al., 2017) and productivity measured by productive machine hour, their typically low utilization rate (Aman et al., 2011) results in reduced units per SMH.

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(n = 20) and timber (n = 2) at all. On average, biomass, pulp and timber harvest volumes equaled 48, 14, and 27 gt/ha constituting 54%, 15%, and 30% of total harvest, respectively. Employing a single-factor ANOVA, we found no relationship between the primary forest management objective, harvest area (ha), and HWP quantity or product distribution. The average logging intensity for all sites, as measured by volume removals, was 89 gt/ha. Since no logging intensity data for the region around Vermont were available, we compared our findings with data from the neighboring states. Average logging intensity at our sites was twice the average logging intensity of 42 gt/ha for New Hampshire (Evans, 2019) and one third higher than the 2007–2012 average of 68 gt/ha for New York (USDA FS, 2015) during the analyzed time frame. For both WTH and non-WTH operations, biomass volumes were mainly derived from bole wood. Biomass volume exceeded tree top and limb volume (typically around 30% of total stand biomass in the region; Fahey et al., 2005) by a multifold for most harvest operations independent of size (Fig. 3b). This high share of biomass in total harvest volume suggests that biomass is partly a driver of harvest operations and is not just a coincidental byproduct. Therefore, it is likely responsible for some processing costs. Biomass harvesting minimally impacted a landowner's overall income: On average, 78% of stumpage income was generated by timber, while biomass and pulp provided only 14% and 8%, respectively (Fig. 3c).

Fig. 2. Logging cost depending on harvest intensity. We used alternate curve fitting to select the best fit for data points vetted by regional experts.

3. Results 3.1. Landowner perspective: harvest volumes and stumpage payments The 35 harvest areas analyzed varied in size from 4 to 121 ha (median: 28 ha) and had been subjected to a range of silvicultural treatments (group selection, salvage logging, single-tree selection, crop tree release, shelterwood, thinnings), including both WTH and nonWTH. Seven of the harvest operations were on land primarily used for maple syrup production, one was on land managed primarily for recreation, and the remainder were on land managed for other forest products. Twelve of the sites were under some form of certification, either Forest Stewardship Council, Vermont Family Forests, American Tree Farm System, Northeast Organic Farmers Association (maple sugar producers only), or a combination of these (see Mika and Keeton, 2013 for more information). The volumes removed varied considerably across sites and forest products (Fig. 3a). Biomass volumes dominated the distribution of HWPs by weight with some harvest operations producing no pulp

3.2. Logging contractor perspective: HWPs price and processing costs Median HWP processing costs were $32, $40, $40, and $59 per gt for biomass chips, biomass logs (biomass transported as tree boles and chipped post road transport), pulp and timber, respectively (Fig. 4a). While we assumed costs to be constant per gt independent of the HWP, fluctuations across HWPs (e.g. forwarding costs) were caused by differences in site-specific harvest intensity and machine productivities. Median processing costs for biomass chips, saw logs and pulp logs were higher than the price paid for the delivered HWP product.

Fig. 3. (a) Harvest volumes by forest product; (b) Biomass as percentage of total harvest volume by weight for whole tree harvest (WTH) and non- WTH compared to biomass from tops only (Fahey et al., 2005); (c) Stumpage by product; and (d) logging effort. For stumpage and logging effort assumptions Tables 4 and 5. 6

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Fig. 4. HWP price (delivered) and median processing costs by cost category (a); HWP processing cost variability and HWP price (delivered; b). All costs include direct and indirect labor costs. Landing costs include sorting, debranching, cutting-to-length and truck loading. Chipping costs were only included if chipping was performed at the landing. While costs were assumed to be constant per gt independent of the HWP, fluctuations across HWPs (e.g. forwarding costs) related to differences in harvest site intensity and machine productivities.

While overall processing costs showed a considerable range for each HWP, 50% of harvests had HWP costs that fluctuated around $6 (biomass chips, pulp, timber) to $9 (biomass logs) per gt (Fig. 4b). Biomass log costs had higher median processing costs compared to biomass chips, mostly due median landing costs for whole logs ($12/gt) that were higher than fixed chipping costs ($8.6/gt). For biomass chips, pulp, and timber, the median processing costs matched the delivered price; costs yielded a wage to the logging contractor averaging $14.70/h (Fig. 4a). Median processing costs for biomass logs were below the delivered market price and therefore provided average logging wages below this wage threshold. The higher processing costs of biomass logs are driven by i) higher landing costs (sorting, delimbing, cutting-to-length, loading) for logs compared to wood chips as well as ii) site-specific harvest volumes affecting economies of scale, such as machinery mobilization costs. Other HWP processing costs fluctuated (Fig. 4b) and were influenced by choice of logging equipment, logging intensity (Fig. 2), and harvest area, which impacted per-unit machinery mobilization costs due to economies of scale. Biomass processing accounted for a large proportion of the income of logging contractors. This was because the median logging effort (in total hours) for biomass harvests exceeded the combined logging effort for harvesting timber and pulp (Fig. 3d). The greater number of hours invested in biomass harvest versus a timber-only harvest, therefore, could offset lower hourly wages. A similar logic applied to income generated through HWP transport – the higher volume of biomass harvests versus pulp/timber led to increased incomes for transporters.

key input metrics to further understand these dynamics. The relationship of logging intensity driving increased revenues for logging contractors was not sensitive to i) the harvest cost multiplier assumptions presented in Fig. 2, ii) doubling of transport distance (change from 50 to 100 km), doubling of stumpage payments, or iii) change in productivity assumptions when using large processing equipment (change from a 30% productivity increase to a 10%–50% productivity increase). In other words, this relationship held up even when assuming the same logging productivity for low or high intensity harvests or variations in transport distance and overall equipment productivity. For low-intensity harvest operations, net income appeared to be considerably below average logging contractor income. In this context, it is important to note that revenues to the logging contractor are derived from i) selling HWPs and ii) receiving supplementary payments from the landowner to achieve management objectives. Therefore, while logging contractor loss-making is documented in the region (Regula et al., 2018), negative income could also be explained by harvest operations driven by forest treatment objectives, such as maple syrup production, salvage logging, wildlife habitat improvement, or pre-commercial thinning. Net hourly income was also affected by harvest type. The hourly net income potential tended to be similar for mechanized harvest systems as compared to manual harvest systems (Fig. 5d). This was not offset by an average 15% increase in harvest intensity when using mechanized harvest systems (manual vs. mechanized harvest operations produced 80 and 92 gt/ha, respectively). The average harvest area was comparable for both mechanized and manual harvest systems (∼38 ha).

3.2.1. Economies of scale: wood products volume and impact on income Logging costs per unit of HWP were not driven by harvest area or harvest type. With comparable median logging costs of $21/gt and $22/gt for WTH and non-WTH, there was no apparent relationship between the type of harvest and area of a cut vs. harvest costs to the logging contractor (Fig. 5a). One non-WTH site was an outlier with logging costs of $119/gt. This site had the lowest volume removal (127 gt), resulting in an outsized share of mobilization costs, and lowest net income from HWPs for the logging contractor (Fig. 3b) and was characterized by the lowest harvest intensity (6 gt/ha, Fig. 5c). All nonWTH operations shipped biomass logs rather than biomass chips produced on site, which presumably offset increased forwarding costs for non-WTH. Logging intensity was the primary driver of increased revenues for logging contractors. This finding suggests that sites with biomass removal have a higher volume removal intensity than average harvest operations without a biomass component. While the harvested acreage had no discernable impact on the logging contractor's hourly income (Fig. 5b), this income nonetheless appeared to increase with an increased harvest intensity (Fig. 5c; R2 = 0.68). This holds true for both WTH and non-WTH (Fig. 5c). We performed a sensitivity analysis on

4. Discussion Despite increasing interest in wood biomass energy, the financial dynamics of biomass harvests are not well understood. This holds true for both the basic harvest and logging economics as well as the income incentives necessary for landowners to sell biomass. Previous studies investigating these dynamics often focused on property structure (parcel size, ownership), variation in site and stand level conditions, or landowner's willingness to harvest rather than logging economics (see also Supplementary Information 2). While biomass harvest economics have been identified as a main factor limiting bioenergy development (Vermont Legislative Council, 2012), research into this topic is limited in scope or has relied on modeling (Baker et al., 2019; White et al., 2013). In contrast, our study used empirical data from actual harvest sites and integrated, mixed-product logging operations. Economics of these logging operations were analyzed from both landowner and logging contractor's perspectives and including both WTH and non-WTH harvests. Results were highly variable but suggest that biomass harvest intensities were not explained by primary forest management objectives, harvested area, or overall HWP quantity or product distribution. In fact, the sites employed in this study spanned the dominant range of

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Fig. 5. Logging costs and economies of scale: (a) Logging costs vs. type of harvest and harvest area, (b) Hourly net income to logging contractor vs. harvest intensity, (c) and (d) Hourly net income to logging contractor vs. type of harvest. Actual net income by site was calculated based on processing costs (Table 5), stumpage costs (Table 4) and hourly effort/ productivity (Table 5). The outlier in (b)–(d) was a low-intensity, low-volume cut where machinery mobilization costs constituted over 50% of total processing costs vs. a 10% average for all other sites.

net-loss harvest operations, rather than generate direct stumpage income, might be a better incentive for a NIPF landowner's willingness to remove biomass. Examples include pre-commercial thinning and harvest objectives unrelated to HWPs, such as maple syrup production, or wildlife habitat improvement (Stewart and Nakamura, 2012).

ownerships, landowner objectives, and participation in different types of certification (fewer than half our sites). And as is typical in the region, biomass was in all cases just one of many products. Thus, our results are highly relevant to harvesting scenarios in which biomass provides an important margin of revenue that helps make integrated operations financially viable.

4.2. Logging costs are high

4.1. Stumpage income is low

From a logging contractor's perspective, HWP processing costs were highly variable with a median of $32, $40, $40, and $59 per gt for biomass chips, biomass logs, pulp and timber, respectively. Compared to timber and pulpwood, biomass processing was responsible for a large amount of contractor income since the median logging effort (in total hours) for biomass harvests (9 h/ha) exceeded the combined logging effort for harvesting timber and pulp (4 h/ha). All HWPs except biomass logs met at least the average region-specific logging wage of $14.70/h. Overall, the harvest costs found here are well within the range of reported harvest cost estimates. This holds true for the northeastern US of $20–$50/gt for timber only (Northern Woodlands Magazine, 2018; Regula et al., 2018; Whalley et al., 2017) as well as a range of $24–$31/gt for mixed- product harvests as reported in mountainous terrain in Europe (Valente et al., 2014). Biomass processing costs presented in our study are in line with other reported numbers for non-clearcut harvest operations in other hardwood dominated forests as well. For instance, we calculated a median processing cost of $30/gt for biomass chips, excluding transport; Saunders et al. (2012) reported a cost $25/gt in Missouri. In contrast, a US-wide study (Kizha and Han, 2016) observed lower pretransportation biomass processing costs ($15/gt) but comparable timber ($43–47/gt vs. $48/gt observed here). The lower processing costs for biomass in that study might be explained by the fact that biomass was often forest residue and therefore not all processing costs were allocated to biomass. In contrast, our analysis allocated processing costs to all HWP according to their share to overall harvested tonnage. Because of the higher fixed initial mobilization costs when employing mechanized harvest equipment, there is a financial incentive to intensify harvests. This provides a rationale for Mika and Keeton's

While biomass stumpage accounted on average for only 14% ($93/ ha) of the payments to the landowner, biomass from roundwood, tops and limbs constituted on average 54% (48 gt/ha) of the extracted volume by weight, far outweighing biomass derived from tops and limbs only. In cases where biomass was restricted to tops and limbs the role of biomass stumpage payments was marginal. Given that stumpage income was small, landowner incentives to increase biomass extraction volumes might be derived from increased payments to logging contractors for net-loss harvest operations, such as pre-commercial thinnings. Our results, therefore, did not support the hypothesis that landowners might deliberately harvest more biomass from their forests, thus making more volume available for energy generation, at least not in the northeastern US. These results are supported by other studies and not restricted to the US (Bohlin and Roos, 2002; North East State Foresters Association, 2013). Our results indicate that biomass stumpage incomes averaging $98/ha have a limited impact on a landowners' willingness to harvest biomass in the northeastern US which is in line with previous findings (Cai et al., 2016; see also Supplementary Information). In cases where biomass harvesting is restricted to tops and limbs, biomass stumpage income would be especially marginal. At the same time, our results are supported by previous research showing that biomass can compete with existing markets for non-timber quality log sections (Johnston and van Kooten, 2014; Du and Runge, 2014). Pulp and biomass markets compete partly for the same raw material. Only small fluctuations in processing costs and delivered prices for biomass vs. pulp creates overlap of potential buyers. Increasing biomass removal subsidies/payments to reduce costs for 8

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(2013) findings that larger equipment tends to intensify biomass extraction. The fixed cost of aging machinery,1 the need to employ machinery once purchased, or the increased speed of harvest operations could all account for the overall lower net incomes from mechanized harvesting. Anecdotal evidence also points to similar dynamics with wood chipping operations, where wood qualifying for other highervalue markets is at times diverted to wood chips to provide sufficient volume. In general, we found that for the logging contractor, biomass harvest intensity appears to be a main driver making a harvest operation profitable as measured in hourly and total net income. If this results in increased harvest pressure, there could be negative consequences for important habitat attributes, such as standing dead and downed coarse woody debris (Janowiak and Webster, 2010; Littlefield and Keeton, 2012). There could also be unintended greenhouse emissions consequences, depending on the specifics of energy substitutions and overall effects on landscape-scale carbon stocking (Buchholz et al., 2016; Buchholz et al., 2014; Hamburg et al., 2019; Mika and Keeton, 2015). These relationships, therefore, support the need for biomass harvesting guidelines designed to ensure sustainability, habitat provisioning, and desirable greenhouse gas emission outcomes (Evans and Perschel, 2009; Lattimore et al., 2009). Indeed, Vermont and Maine recently published voluntary guidelines of this nature. Our findings contribute to a better understanding of the drivers of biomass supply and thus will help inform state-level efforts to expand sustainable biomass production. Many states have or are in the process of developing biomass harvest guidelines, designed to encourage renewable energy production while minimizing greenhouse gas emissions and detrimental ecological impacts. At the same time, a biomass market can provide a financial incentive to conserve working forests by supporting long-term improvements in timber quality and support forest restoration (Ducey et al., 2013). To mitigate the potentially negative effects of economic drivers promoting increased harvest intensity, decision-makers may want to provide incentives to logging contractors to keep harvest intensities within desirable ranges. These might encourage, for example, retention of tops or a portion of residuals and dead, dying, and poorly formed standing trees, or use of equipment more likely to minimize negatives effects on habitat (Littlefield and Keeton, 2012), GHG emissions (Mika and Keeton, 2013), and forest productivity (Curzon et al., 2014). Additionally, processing biomass chips typically requires larger landings (frequently around 1 ha and therefore is an important consideration in terms of planning to minimize overall operational footprint essential for accurate forecasting of future biomass supply as well as ensuring the sustainability of wood energy production in the US Northeast. Overall, the future of the forests in the northeastern US will not only be driven by a change in forest product markets and logging infrastructure, but also by an imminent intergenerational transfer of forest ownership and further parcellation (Connelly et al., 2007; MarkowskiLindsay et al., 2012). From a policy perspective, the results of this study support the idea that the logging industry - not the landowner - will have a greater impact on biomass volumes and forest management. This is because the economic benefits of a biomass market accrue first to the logging contractor (and the transportation industry) and only secondarily to the landowner.

assistance of Donald Tobi and participating foresters and landowners. We are particularly grateful to the field crew, including Anna Mika, Caitlin Littlefield, Isabel Beavers, and Emily Potter. We thank William VanDoren for sharing thoughts on logging economics in the northeastern US. We received helpful feedback from Jenna Jadin on an earlier version of this article for style as well as from an anonymous reviewer on content. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.forpol.2019.102023. References Aman, A.L., Baker, S.A., Greene, W.D., 2011. Productivity and product quality measures for chippers and grinders on operational Southern US timber harvests. Int. J. For. Eng. 22. Bais-Moleman, A.L., Sikkema, R., Vis, M., Reumerman, P., Theurl, M.C., Erb, K.-H., 2015. Assessing wood use efficiency and greenhouse gas emissions of wood product cascading in the European Union. J. Clean. 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Acknowledgments This research was supported by grants from the Northeastern States Research Cooperative, the USDA McIntire-Stennis Forest Research Program, the National Science Foundation (Award ID 0613884), and support to John Gunn from the New Hampshire Agricultural Experiment Station. It would not have been possible without the 1 Machinery in the northeastern US has frequently over 7000 h and is assumed to be as ‘written off’; see also Leon and Benjamin (2012).

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