an expert elicitation

Forest management in the Sierra Nevada provides limited carbon storage potential: an expert elicitation SETH J. LALONDE,1, KATHARINE J. MACH,2 CHRISTA M. ANDERSON,2 EMILY J. FRANCIS,2 DANIEL L. SANCHEZ,1 CHARLOTTE Y. STANTON,1 PETER A. TURNER,1 AND CHRISTOPHER B. FIELD2 1

Carnegie Institution for Science, 260 Panama Street, Stanford, California 94305 USA 2 Stanford University, 473 Via Ortega, Stanford, California 94305 USA

Citation: Lalonde, S. J., K. J. Mach, C. M. Anderson, E. J. Francis, D. L. Sanchez, C. Y. Stanton, P. A. Turner, and C. B. Field. 2018. Forest management in the Sierra Nevada provides limited carbon storage potential: an expert elicitation. Ecosphere 9(7):e02321. 10.1002/ecs2.2321

Abstract. Analysis of long-term trends in forest carbon stocks is challenged by interactions among climate change, wildfire and other disturbances, forest management actions, and heterogeneous vegetation responses. For such circumstances where complex interactions make it difficult to encompass the full range of processes in any one mode of analysis, expert elicitation is a well-developed method for documenting judgments about uncertainty, based on available evidence, to inform ongoing decision-making. Applying this method for the Sierra Nevada, we evaluate subjective probabilistic estimates of trends in aboveground forest carbon for different management scenarios toward the goal of maximizing carbon stored, while also considering implications for wildfire risk. The analysis examines the effects of four treatments in isolation (thinning, timber harvesting, prescribed burning, managed wildfire), as well as a user-defined management portfolio allocating resources across five management practices (thinning, harvesting, prescribed burning, firefighting, and restoration). The expert elicitation suggests that aboveground forest carbon stocks will decline 8%, from 126 to 116 tC/ha, between 2030 and 2100 (median estimate across experts) assuming conventional forest management practices are continued. Out of all surveyed practices, the custom user-defined management portfolio results in the highest carbon stock of 129 tC/ha which is 11% higher than conventional practice in 2100 at the 50th percentile. The expert elicitation indicates less beneficial carbon sequestration outcomes than recent modeling studies. Suggesting co-benefits across objectives, 75 experts collectively estimate a 61% likelihood that managing for carbon also reduces wildfire risk. By contrast, decreases in carbon stocks are anticipated for large magnitudes of climate change or substantial decreases in forest management investments. Key words: climate change; disturbance; expert elicitation; forest carbon stock; forest management; fuel reduction treatment; mixed-conifer; prescribed fire; resilience; Sierra Nevada; thinning. Received 16 November 2017; revised 22 March 2018; accepted 16 April 2018. Corresponding Editor: Kristofer D. Johnson. Copyright: © 2018 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. E-mail: [email protected]

INTRODUCTION

infestations), and forest treatments (Canadell and Raupach 2008, Ager et al. 2010, McKinley et al. 2011, Peterson et al. 2014, Williams et al. 2016). Increasingly, forests are also being managed for their carbon, both to protect existing stocks and to increase them, as part of climate change mitigation policy (Pacala 2004, Woodbury et al. 2007, Manley and Maclaren 2012, Buizer and Lawrence

Despite advancements in scientific knowledge and assessment tools, progress in realizing longterm forest management objectives such as reducing wildfire risk is still uncertain, partly because of the intricate relationships among wildfire, climate change, disturbances (e.g., drought, pest ❖ www.esajournals.org

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and hydrological engineering (Mann et al. 2016, Balch et al. 2017). Projections of future fuel levels are complicated not only by fire regime but also by uncertain impacts of climate change and drought (Hurteau et al. 2014, Anderegg et al. 2015, Carnwath and Nelson 2016, Clark et al. 2016) as well as the potential for multidecadal changes in vegetation type, species composition, and stand density (Collins and Roller 2013, Earles et al. 2014, Coppoletta et al. 2016, Van Gunst et al. 2016). Predicting forest response to climate change and wildfire is difficult at the plot scale and is even more challenging over large spatial and temporal scales, where shifting controls, historical legacies, and data limitations increase uncertainties. The Forest Vegetation Simulator (FVS) and LANDIS-II are powerful, widely used tools useful for estimating forest states and trends, but the accuracy of projections from these models is invariably constrained by requisite assumptions, limited consideration of some of the relevant processes, and incomplete understanding of key processes (Hurteau and North 2009, Campbell et al. 2012, Earles et al. 2014, Liang et al. 2017). Constraining the uncertainty relevant to forest management is important in order to account for forest carbon emissions and sinks in climate mitigation policy. But the shortcomings of available modes of analysis, from missing data and processes to mismatched scales and heterogeneity, can limit application to real-time decisionmaking. By drawing from and complementing available literature and data, expert elicitation is a tool that can aid assessment and decisionmaking (Morgan et al. 2001, Mcdaniels et al. 2012). Expert elicitation documents the subjective probability judgments of experts on uncertain quantities through methods that minimize expert bias. It encompasses formal and informal expert knowledge and makes transparent the range of expert opinion on uncertainty and risk, thereby informing real-time decision-making on the basis of available evidence (Morgan 2014). Through an elicitation of relevant experts, we evaluate evidence-based judgments about California’s aboveground forest carbon trends, focusing on the Sierra Nevada. Our analysis addresses three main questions: (1) To what extent can forest management increase forest carbon stocks? (2) Does managing forests to maximize carbon stocks

2014, Lundmark et al. 2014, Makkonen et al. 2015, Hoberg et al. 2016). For California’s climate change action in the natural and working lands sector, including forests is potentially relevant to helping achieve greenhouse gas (GHG) reduction targets. The state’s overarching goals are to secure its forests as resilient net sinks of carbon and to reduce emissions by 40% and 80% of 1990 GHG levels in 2030 and 2050, respectively; these are to be carried out under the policy framework of SB32 legislation (Pavley and Garcia 2016), the 2030 Target Scoping Plan (CARB 2017), and Forest Carbon Plan (FCAT 2017). Can the goals of reducing high-severity wildfire and enhancing carbon sequestration be achieved simultaneously or are they in conflict? Forest management, for example, through thinning or prescribed burning, is potentially applicable for achieving wildfire-risk and forest carbon goals. However, estimation of the longterm consequences of these activities on carbon stocks is difficult and hinges, for instance, upon model determination of wildfire probability and capacity for vegetation recovery post-wildfire (Law et al. 2004, Finney 2005, Campbell et al. 2012, Hurteau et al. 2016, Tempel et al. 2015, Stephens et al. 2016). For such circumstances where complex system interactions make it difficult to encompass the full range of processes in any one mode of analysis, expert elicitation is a welldeveloped method for documenting judgments about uncertainty based on the diversity of available evidence, from observations to model-based results. Here, we apply this method to explore and characterize expert perspectives on the state of knowledge for forest carbon storage potential in the Sierra Nevada. Conceptual frameworks such as the fire regime triangle provide a basis to forecast the odds of wildfire occurrence from three principal elements supporting combustion: ignition, fuels, and weather conditions (Moritz et al. 2005, Krawchuk et al. 2009, Parisien and Moritz 2009, Whitlock et al. 2010, Krawchuk and Moritz 2014). Still, models designed to evaluate future wildfire probability, based on these drivers, are challenged by the interacting roles of anthropogenic versus biophysical variables. Recent studies highlight the significant role of humans in wildfire ignition likelihood and in altering fire regimes through pathways such as fire suppression, land-cover change, ❖ www.esajournals.org

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also reduce wildfire risk? (3) How might large magnitudes of climate change or different forest management financial budgets alter outcomes? Based on the elicitation results, we discuss the implications of forest management in the Sierra Nevada to help realize California’s greenhouse gas reduction goals.

Aboveground forest carbon stock was the primary metric for the elicitation. Aboveground orest carbon, as defined in the survey, includes the quantity of aboveground forest carbon in live trees, standing dead trees, down woody material, and understory vegetation. It excludes carbon in soil and harvest of wood product materials.

METHODS

Structure of the expert elicitation

Through five multipart questions, the expert elicitation documented perspectives on the consequences of different approaches for managing aboveground forest carbon stocks and wildfire risk, while also considering implications of climate change and financial resources. Table 1 provides a classification summary of the survey questions. The complete expert elicitation is available for reference (Appendix S1: Expert Elicitation Protocol). In questions 1–3, experts estimated probability distributions for average aboveground forest carbon across the entire Sierra Nevada under different forest management practices. For each time frame, experts were required to specify three stock estimates: the median or best estimate, the minimum (defined by a 5% probability that the actual value is smaller), and the maximum (defined by a 5% probability that the actual value is larger). Expert judgments about uncertainty can be biased due to cognitive shortcuts especially when the questions provide an unintended anchor or starting point. To minimize these tendencies, the survey design encouraged experts to

Scope of the expert elicitation To facilitate the elicitation of expert judgments about forest carbon at a landscape scale in California with consideration to the diversity of its ecosystems, the geographic area of the study was restricted to the Sierra Nevada ecoregion (see map in Appendix S1: Expert Elicitation Protocol). This ecoregion is selected as it encompasses a significant landscape area studied by the research community, exhibiting well-defined and consistent behavior; it holds approximately 46% of the aboveground forest carbon stock in California (FIA 2016) and has a broad range of climate mitigation management options. Experts were requested to consider all forest land area across the ecoregion including both private and public lands as well as the wildland–urban interface. Forest carbon estimates were elicited for 2030, 2050, and 2100; these time periods were selected to coincide with target dates established in California’s Climate Change Scoping Plan (California Air Resources Board 2017).

Table 1. Overview of expert elicitation questions for forest management in the Sierra Nevada. Question

Management scenario

Management goal

Elicited estimate

1 2A 2B 2C 2D 3A 3B 3C 4 5A 5B 5C

Conventional Thinning Timber harvesting Prescribed burning Managed wildfire Custom user-defined portfolio Custom user-defined portfolio Custom user-defined portfolio Custom user-defined portfolio Increase global mean temperature Halved budget funding Doubled budget funding

Carbon Carbon Carbon Carbon Carbon Carbon Carbon Carbon, wildfire risk Wildfire risk Carbon Carbon Carbon

Aboveground carbon stock Aboveground carbon stock Aboveground carbon stock Aboveground carbon stock Aboveground carbon stock Allocation of treatments Aboveground carbon stock Probability Allocation of treatments Probability Probability Probability

Notes: The expert elicitation survey consisted of 12 questions pertaining to various scenarios of forest management, climate change, and budget resources. Experts were asked to assess the scenario impacts on the two management goals of enhancing carbon stocks and reducing wildfire risk. Expert estimates were provided in measurement units of aboveground carbon stock, percent allocation, and probability. Refer to Appendix S1 for the survey in its entirety.

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make judgments based on systematically considering all factors and processes, as well as the full range of possible outcomes, openly considering upper and lower bounds. Question 1 concerns baseline estimates for aboveground forest carbon stock if current forest management practices continue over the century. The question included recent literature values for Sierra Nevada average aboveground carbon stock. These range from 44 to 210 tC/ha (Liu et al. 2011, Kellndorfer et al. 2012, Kocher and Beckwitt 2012, Wilson et al. 2013, USDA Forest Service 2015). Question 2 examines the implications of alternative forest management practices assuming a deliberate goal of maximizing carbon stock. The most common general forest management practices were included: timber harvesting and fuel reduction treatments such as thinning, prescribed burning, and managed wildfire. The survey did not specify details (i.e., frequency and extent) for each forest management practice so that experts could apply their judgments of maximum efficacy across possible application approaches. In question 3, experts define a custom management portfolio to achieve the goal of maximizing forest carbon. They additionally estimate the likelihood that managing for carbon will also reduce high-severity wildfire risk. Then, in question 4, experts further explore the compatibility of the two management goals by defining a custom management portfolio for the goal of reducing high-severity wildfire risk. In questions 1 through 4, experts were instructed to assume that global mean temperature increase stabilizes at 2°C above pre-industrial levels by 2100, without specific guidance on financial resources. Question 5 unravels the consequences of these pre-conditions by asking experts to express probabilistically how much their former stock estimates may change under three alternate scenarios: (1) Global mean temperature stabilizes at 4°C above pre-industrial levels by 2100, (2) budget resources are halved, and (3) budget resources are doubled. The baseline of the budget is the current level of funding assumed under the continued business as usual scenario.

were sought in the areas of forest management, fire ecology, forest carbon, and fuel reduction treatments for the Sierra Nevada. The survey was administered and deployed using an online expert elicitation tool developed by the non-profit organization, Near Zero (www. nearzero.org). This tool allowed us to engage a broad and diverse group of experts, and solicit quantitative, probabilistic estimates as well as rich qualitative comments. The survey design was also intended to be practical to complete in approximately half an hour. The survey was initially distributed on 21 March 2017. Three email reminders were sent before the survey period closed on 14 April 2017, after which participants were asked to clarify their responses as necessary.

Data aggregation All expert judgments were weighted equally at the data aggregation stage. A kernel density estimation, which is a non-parametric statistical method, was chosen to create probability distribution functions of the aboveground forest carbon stock from questions 1 through 3 (Rosenblatt 1956, Parzen 1962). The density function in the base stats package of R version 3.3.2 (R Core Team 2016) was applied to calculate the probability distribution functions. The mean value of all expert responses was used as the aggregate measure of the custom user-defined management portfolio allocations in questions 3 and 4 as well as for the three buckets of probabilities from question 5.

Implications for state GHG reduction targets To ascertain the effects of forest management for addressing California’s SB32 target goals, a three-step calculation was performed. First, carbon flux was calculated by taking the difference of aggregated mean expert opinion estimates of aboveground forest carbon stocks between successive target years (2017–2030, 2030–2050, and 2050–2100). Second, the total carbon sequestration potential was computed by multiplying the flux estimates for each target year (2030, 2050, and 2100) by the total forest area in the Sierra Nevada, ~3.94 Mha (Christensen et al. 2016). Third, the contribution of aboveground forest carbon sequestration at each target year was estimated as a percentage of the state’s 1990 GHG emission levels of 431 Mt CO2 (CARB 2007).

Survey deployment Experts were identified through a literature review and discussions with key specialists. Both practitioner expertise and research expertise ❖ www.esajournals.org

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RESULTS AND DISCUSSION

describe the contributing factors to these longterm decreases. Cited factors include decreased vegetation productivity and conversion to less carbon-dense species (Experts 1, 20, 25, 33, 57) and increased probability of higher severity fires along with drought, disease, and insect disturbances (Experts 2, 23, 25, 26, 30, 38, 42, and 63). While the aggregate pool for the baseline scenario implies a general decrease in aboveground carbon stock under conventional forest management, some individual experts projected positive trends. For example, 13 experts of 63 respondents provide estimates where 5th, 50th, and 95th percentile values all increase from 2030 to 2100, and 10 additional experts had higher estimates just for the 95th percentile values. Experts anticipating potential increases in aboveground carbon stock attributed the response to climate change (Experts 48 and 60) and more resilient forest stocks assuming a restoration effort is instituted prior to 2050 (Experts 39 and 65; Appendix S1: Tables S4 and S5).

Survey responses The expert elicitation on Sierra Nevada’s forest carbon was distributed to 269 experts. 81 survey submissions were received; 75 of those completed all questions, equating to a response rate of 28%. Appendix S1: Table S1 lists the experts who completed the elicitation. Randomized numeric identifiers are used to represent individual experts; this labeling scheme is used consistently throughout all figures. Thirteen of the 75 respondents did not provide all stock estimates necessary to create and compare probability distributions across all forest management survey scenarios. Thus, results about aboveground forest carbon stock estimates draw from a subset of 62 experts. All other results are based on answers from 75 respondents. The 75 completed survey responses encompassed experts from academics (33), government (26), non-profit (8), and business/industry (8; Appendix S1: Fig. S1). The top five declared areas of expertise, in order, are forest management, fire ecology, forest disturbances, carbon cycle, and fuel reduction treatments (Appendix S1: Fig. S2). Among the 188 non-respondents, 34 outlined reasons for not taking the survey; 70% identified a lack of carbon storage expertise and/or difficulty with estimates at the scale of the Sierra Nevada as the primary factor for declining participation. Other stated reasons for not participating include the survey taking too long to complete, concerns about contradictory science and contentiousness of issues, and apprehension about the value of expert elicitation.

Aboveground forest carbon stock under different management approaches We compared various management scenarios against the conventional management approach at both the individual expert and aggregate pool levels. Individual expert estimates of forest carbon stock under all surveyed management approaches are available in Appendix S1: Figs. S3–S7. Additionally, Appendix S1: Table S2 summarizes the delta values of the alternative option from the conventional; positive values indicate a gain while negative values indicate a loss in carbon stock respectively. The total count of experts reflecting positive and negative delta values is also shown at the bottom of the table. The total counts reflect that the majority of experts do not expect alternative management options to result in positive delta values in 2030 and 2050; in 2100, there is a majority count of positive deltas for thinning (34), prescribed burning (35), and the custom user-defined plan (49). At the aggregate pool level, the 50th percentile carbon stock estimates for the alternative forest management options range from 6% less to 11% more than under the conventional business as usual approach (Fig. 2) for all three target dates. The management practices with the largest increases in aboveground forest carbon stock are

Decline in carbon stocks under conventional forest management In the baseline scenario (continuation of current forest management practices), expert estimates suggest that aboveground carbon stock in the Sierra Nevada will diminish (Fig. 1). The aggregated 5th and 50th percentile stock values decline between 2030 and 2100; they decrease by 42% and 8%, respectively. In parallel, the uncertainty increases over time; the range measured from the 5th and 95th percentile of aboveground carbon stock in 2030 is from 45.3 to 240.7 tC/ha and in 2100 extends from 26.3 to 246 tC/ha. The qualitative comments (Appendix S1: Table S6) ❖ www.esajournals.org

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Fig. 1. Aggregated and individual expert estimates of aboveground forest carbon stock over time in the Sierra Nevada assuming conventional management. Panel A shows the pooled distribution across experts, derived using


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(Fig. 1. Continued) kernel density estimation and represented as a box and whisker plot. The 50th percentile values across experts are 126.2, 124.0, and 116.3 tC/ha in years 2030, 2050, and 2100, respectively. Five recent stock estimates provided in the survey are shown in yellow, and the mean value of these estimates, 130 tC/ha, is shown in red. Panel B displays experts’ individual responses, where the lowest value for each expert represents a minimum value such that there is an estimated 5% probability that the true value falls below this value (the 5th percentile); the middle value represents the median value or the 50th percentile; the highest value represents a maximum value such that there is an estimated 5% probability that the actual value falls above this value (the 95th percentile).

has the highest median value of aboveground carbon, whereas the timber harvesting plan has the lowest. In general, the 5th and 50th percentile estimates aggregated across experts suggest that prescribed burning is the best individual treatment plan; the 95th percentile estimate under thinning is slightly higher than prescribed burning in year 2100.

prescribed burning and the custom user-defined plan, which are 5% and 11% higher, respectively, than the baseline median value in 2100. The 5th and 95th percentile pooled values for the treatment plans demonstrate comparatively more substantial increases in carbon stock. The 5th percentile value for prescribed burning and the custom user-defined plan are 28% and 34% greater than the baseline minimum in 2100, and similarly, the 95th percentile values for prescribed burning and the custom user-defined plan are 6% and 16% greater than the baseline maximum in 2100. The custom user-defined plan

Implications for California’s SB32 emission reduction goals The mean aboveground carbon stock estimates across experts indicate that none of the survey

Fig. 2. Aggregated expert estimates of aboveground forest carbon stock over time in the Sierra Nevada under alternative management practices. Probability distributions across experts, derived using kernel density estimation, are represented as a box and whisker plot for each management practice at years 2030, 2050, and 2100.


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LALONDE ET AL. Table 2. Aggregated expert estimates of aboveground forest carbon in the Sierra Nevada for different management practices. Aboveground forest carbon flux (tC ha 1 yr 1) Management practice 1. Conventional

2A. Thinning

2B. Timber harvesting

2C. Prescribed burning

2D. Managed wildfire

3B. Custom user-defined portfolio

Mt CO2/yr across Sierra Nevada

Year

Mean

SD

Mean

SD

Percentage of California 1990 CO2eq GHG emissions

2030† 2050 2100 2030† 2050 2100 2030† 2050 2100 2030† 2050 2100 2030† 2050 2100 2030† 2050 2100

0.5 0.1 0.1 0.9 0.1 0.02 1.4 0.003 0.05 0.6 0.01 0.1 0.9 0.1 0.1 0.7 0.2 0.1

1.7 1.3 1.3 1.7 1.2 1.4 1.6 1.2 1.3 1.7 1.2 1.3 1.7 1.2 1.3 1.7 1.3 1.4

6.4 2.0 2.1 12.3 1.1 0.3 20.6 0.04 0.6 9.2 0.1 0.8 12.2 1.4 1.1 10.1 3.0 1.2

23.9 18.0 19.0 23.7 17.7 19.9 23.2 16.6 18.8 23.6 17.3 18.6 23.7 17.4 17.9 24.0 18.8 20.6

1.49 0.47 0.48 2.85 0.25 0.07 4.78 0.01 0.15 2.14 0.02 0.18 2.84 0.32 0.26 2.35 0.70 0.27

Notes: Carbon flux was calculated by using the aggregated expert opinion estimates of aboveground forest carbon stocks between successive target years. The total carbon sequestration potential was computed by multiplying the flux estimates by the total amount of forest land in the Sierra Nevada, ~3.94 Mha. The potential contribution of aboveground forest carbon sequestration at each target year was estimated as a percentage of the state’s 1990 greenhouse gas (GHG) emission levels of 431 MtCO2eq. Emissions reductions from 1990 levels are positive, while emissions increases are negative. SD, standard deviation. † Year 2030 fluxes were derived using a present-day stock estimate of 130 tC/ha, the mean value of the recent literature values cited in the survey.

management practices will have a substantial impact on California’s SB32 GHG reduction goals since emission increases are anticipated for most management scenarios (Table 2). Even when extrapolating potential carbon sequestration to account for all of Sierra Nevada forest land area, the largest reductions relative to 1990 emission levels, using mean estimates, are 0.3% for thinning in year 2050 and 0.7% and 0.3% for the custom user-defined portfolio in 2050 and 2100, respectively. While they were not addressed in this elicitation, it is possible that the estimates for whole ecosystem carbon stocks (including soils, roots, litter, and coarse woody debris) or total carbon including harvested products might lead to greater storage potential.

many cases irrespective of management practices. In some ways, these results align with the statewide spatial inventory analysis showing loss of aboveground carbon from 2001 to 2010 (Gonzalez et al. 2015). At the same time, the elicitation estimates reflect smaller carbon storage potential relative to three recent model-based studies. Two recent studies have modeled the future carbon stocks in the Sierra Nevada, focusing on interactions of climate change and wildfire. Sleeter et al. (2015) predict that aboveground live forest carbon decreases from 67 to 63 tC/ha from 2030 to 2100 undergoing combined climate and land change with IPCC’s A1B emission scenario. Liang et al. (2017) project that aboveground forest carbon is between 80 and 95 tC/ha in 2100, with 93–85% of the mid- to high elevations remaining a carbon sink through the century. For the Lake Tahoe Basin, Loudermilk et al. (2016) examine the interactions of climate change, wildfire, and fuel treatments, concluding that fuel

Comparison of expert-elicitation carbon stock estimates with empirical and model-based results The elicitation results suggest a continued decrease in aboveground forest carbon stock, in ❖ www.esajournals.org

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Compatibility of managing for carbon and reducing wildfire risk

treatments can increase carbon stocks 25– 37.5 tC/ha by 2100 achieving a net carbon gain within five to six decades. What explains the contrast between the results of the modeling studies and the more pronounced estimation of carbon sources in the elicitation? There is no way to be certain. The conceptual frameworks experts used for the elicitation allow for a wide range of possible future changes. For example, expert elicitation has a broader scope with respect to disturbance types since the model studies exclude mortality associated with drought, disease, and insect outbreaks. Additionally, the other studies make some limiting assumptions about fire disturbances such as computing results based on historical distributions or only considering large-scale wildfire simulations. Another factor is the diversity of evidence in the literature regarding the consequences of fuel reduction treatments. Some studies suggest that fuel reduction treatments will result in a net carbon loss as compared to untreated forests subject to wildfire because a large fraction of forest carbon is not consumed during wildfires. Reducing potential wildfire hazard often requires treating more forest than is ultimately burned (Mitchell et al. 2009, Ager et al. 2010, Campbell et al. 2012, Restaino and Peterson 2013). In contrast, others indicate that fuel reduction treatments may yield a net carbon gain compared to untreated stands due to a reduction in emissions and mortality associated with wildfire (Hurteau et al. 2008, Hurteau and North 2009, Stephens et al. 2009, 2012, Wiedinmyer and Hurteau 2010, Hudiburg et al. 2011, North and Hurteau 2011, Carlson et al. 2012, Dore et al. 2016, Loudermilk et al. 2016). Moreover, the outcome for carbon balance can be contingent on factors like the fire return interval (Winford and Gaither 2012), fire severity (Hurteau and Brooks 2001, Campbell et al. 2012), frequency of large fires (Chiono et al. 2017), and interactions among different types of disturbances (Loehman et al. 2014). Comments from the experts emphasize the issues of scale and natural disturbance in driving continued mean net carbon sources (Appendix S1: Tables S9, S12, S15, S18, and S21). As expert 61 frankly asserts, “Great uncertainty related to fire severity and frequency. Both will likely increase. I don’t see management greatly affecting their impacts on C stock.” ❖ www.esajournals.org

An initial hypothesis of our study was that the management goals of enhancing carbon and reducing wildfire risk could not be combined. While the experts do not, in aggregate, expect management to increase forest carbon stocks, surprisingly they estimated a 61% probability (median estimate across experts) that managing for carbon will also reduce wildfire risk (Fig. 3A). Many experts commented about the high likelihood of making these goals complementary through fuel reduction treatments that create more stable forest structures, lessen fire risk, and increase sequestration in live carbon pools (see 24 qualitative comments in Appendix S1: Table S22). Other experts, however, assigned lower probabilities to the likelihood of carbon/wildfire synergy. Their comments offer counterarguments: For example, maximizing biomass may lead to fuel accumulation thereby increasing wildfire risk, and the benefits of treatment effects are uncertain in a changing climate (Appendix S1: Tables S23 and S24). The average allocation for a custom userdefined portfolio of resources reinforces the assessment that prescribed fire is a preferred tool for managing carbon (Fig. 3B). Prescribed burning receives the most resources in the custom portfolio, whether the goal is managing carbon or reducing wildfire risk, and for both 2020 and 2050. In fact, the allocation of resources to prescribed burning increases between 2020 and 2050 from 27% to 34% in the portfolio optimized for carbon. Comments about the value of prescribed burning point to its potential to secure resilient forest biomass densities and decrease risks of catastrophic wildfire (Experts 13, 39, 41, 50, 57; Appendix S1: Table S25). A striking feature of the custom user-defined portfolios is that they include some resources for each practice. Comments about the value of a diverse portfolio of management practices include factors like protecting carbon stocks, developing well-diversified forest age classes, and lowering densities to strengthen resistance against disturbances (see 18 qualitative comments in Appendix S1: Table S29). The similarity in custom user-defined portfolios for carbon versus wildfire-risk goals provides further support for their compatibility (Fig. 3B). The portfolios are distinguished, however, by greater 9

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Fig. 3. Synergies between managing for carbon and wildfire risk. Panel (A) shows the aggregated expert estimates of the probability that managing for carbon also reduces wildfire risk. Aggregation is based on kernel density estimation and represented as a box and whisker plot. Panel (B) illustrates expert allocations of resources for both management objectives: managing for carbon and managing for wildfire risk. Average allocations across experts are shown.

congruence emerges in the emphasis on making decisions about forest treatments at the local level (Stephens et al. 2010, 2016). Another comes from the value of utilizing prescribed fire and managed wildfire as approaches to restoring forest structure (Hurteau and North 2009, North et al. 2012, 2015) And finally, many studies point to the vital importance of designing treatments to achieve forest structures that reduce catastrophic wildfire risk (Schoennagel and Nelson

allocation to prescribed burning and thinning for the goal of reducing high-severity wildfire. A reason for this difference may be that reducing highseverity wildfire necessitates vegetation removal and thereby more vigorous burning and thinning (Expert 13; Appendix S1: Table S30). The conclusions about the diversity of custom user-defined portfolios and the complementarity between carbon and wildfire-risk goals are congruent with existing literature. One thread of ❖ www.esajournals.org

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Climate change and budget effects on carbon stock estimates

2011, Ager et al. 2010, Calkin et al. 2015, Stephens et al. 2016, Vaillant and Reinhardt 2017).

Greater magnitudes of climate change and substantially decreased resources for forest management pose risks for aboveground forest carbon stock (Fig. 4). For a 4°C global temperature increase relative to pre-industrial levels, experts estimate a 62% probability (mean estimate across experts) of much less aboveground forest carbon stock, as compared to a 2°C scenario. Comments

Scope and system boundary limitations This expert elicitation focuses on opportunistic synergies to manage carbon and reduce highseverity wildfire risk. An overall forest management strategy is also dependent on consideration of other factors such as funding, air quality restrictions on burning, and balance of management objectives (Hudiburg et al. 2011, North et al. 2012). Evaluating the co-benefits of forest carbon sequestration for these other objectives is a logical next step for analysis. As expert 75 remarks, “These are complex and difficult questions, and the answers are dependent upon land use and management goals. Commercial/Industrial timber harvest will continue to play an important role in California, a state where we consume more wood products than we produce. Firefighting will always be necessary to protect lives and assets. Public lands have to be managed for multiple uses. So the solutions are different on different lands. If your shared goals are to maintain ecosystem resilience and health, continue providing ecosystem services to society, and utilize forests as a mitigation against climate change, there is no one-size fits all solution.” Our analysis accounts for the aboveground forest carbon, excluding the pool of harvested wood products. In the custom user-defined portfolio for managing carbon, timber harvesting received the least emphasis. However, if a large proportion of harvested timber ends up in wood products with slow decay rates, then timber harvesting can contribute to carbon sinks in wood products. Furthermore, wood construction has additional GHG benefits, when wood displaces alternative materials that have higher embodied emissions (Experts 9, 20, 28 and 75). As expert 75 noted, “Also, considering the effect of timber harvest on AG stock without the concomitant storage of C in wood products or energy production makes me nervous. In an idealized sense, commercial harvest maximizes growth but balances that with removals, plus puts C into many durable products.” These caveats highlight the need for research on the life cycle of harvested wood products, including an emphasis on coordination among the bioenergy, forestry, land-use, and life cycle analysis communities. ❖ www.esajournals.org

Fig. 4. Implications of large magnitudes of climate change and of budget changes for aboveground carbon stock in the Sierra Nevada. Experts considered three additional scenarios, across the different forest management practices: 4°C global mean temperature increase above pre-industrial levels, halved forest management budget, and doubled forest management budget. For each of these scenarios, experts estimated the probability of much more, similar, and much less aboveground carbon stock, as compared to their previous estimates of aboveground carbon stock (Fig. 2). Average estimates across experts are shown.

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ascribe the high probability of diminished carbon stock to increased evaporative demand, highseverity fires, vegetation type conversion, and mortality related to the increased temperature (Appendix S1: Table S37). The forecast for lower stocks under greater warming is consistent with the modeling study results of Loudermilk et al. 2016 for the Lake Tahoe Basin. At the same time, experts estimate 30% probability of similar stock levels; precipitation, CO2 fertilization, and management are mentioned variables that may counterbalance or enhance productivity (Appendix S1: Table S36). For the case of halving the budget for fuel reductions, firefighting, and restoration, experts estimate a 61% probability of much less and 32% probability of similar (mean estimate across experts) aboveground forest carbon stock. Comments point to the prospect that forests would become even more dense and exposed to larger high-severity fires (Experts 1, 16, 23, 28, 35, 39, 49 and 65; Appendix S1: Table S40). Others expect that budget cuts would have little influence on carbon stock based on historical experience with firefighting and fuel reduction treatments (Experts 13, 25, 50; Appendix S1: Table S39). Estimates are more diverse about the consequences of doubling budget; the probability results for less stock, similar stock, and more stock are 26%, 40%, and 33%, respectively. The broad spectrum of expert perspectives on potential carbon stock outcomes stemming from an increased budget hinges upon factors such as strategy effectiveness and allocation of resources toward firefighting versus fuel reduction (Appendix S1: Tables S41, S42, S43).

While every step to increase forest carbon can yield multiple benefits, the potential changes in aboveground forest carbon constitute a very small fraction of the emissions reductions necessary to meet California’s SB32 climate mitigation policy goals. These results imply that the bulk of greenhouse gas emissions reductions would need to be achieved in other sectors, such as electricity generation, transportation, and industry. The experts conclude, with 61% likelihood, that the objectives of managing for carbon and reducing wildfire risk are complementary. Suggested synergies between carbon and wildfire goals underscore the importance of further evaluating forest carbon sequestration in the context of achieving multiple objectives and co-benefits. Comprehensive life cycle analysis with expanded system boundaries is also important for optimizing strategic goals incorporating forest carbon pools. However, the evaluated benefits of effective forest management are put in jeopardy if global warming is not limited to the low end of the possible range or if forest management is under-resourced. Expert elicitation provides a powerful way to capture expert judgment on topics where mechanisms are incompletely understood, projections depend on a wide range of future trends, or models reflect only a subset of the relevant processes. It can be especially useful for providing caution about the accuracy of model results, for generating ballpark estimates, and for identifying aspects of a topic that need additional research. It can be complementary to other approaches, especially in nudging formal calculations to account for broader ranges of mechanisms and the full range of possible outcomes.

CONCLUSION

ACKNOWLEDGMENTS

The range of our expert elicitation estimates signify that forest management practices will have minimal impact on aboveground forest carbon stocks between year 2030 and 2100. Based on the survey estimates, aboveground forest carbon in the Sierra Nevada is forecast to decrease 8% between 2030 and 2100 (median estimate across experts) assuming conventional forest management practices are continued. Across the surveyed management practices, the custom user-defined management portfolio results in the highest carbon stocks, leading to 11% greater carbon than conventional practice in 2100 at the 50th percentile. ❖ www.esajournals.org

For help administering the online survey platform, we thank Michael Mastrandrea and Seth Nickell of Near Zero. For discussion of key research areas, we thank Max Moritz, Jon Keeley, Meg Krawchuk, James Randerson, and LeRoy Westerling. For assistance in test trialing the survey, we thank Alisa Keyser, Ian McCullough, Garrett Meigs, Alexandria Pivovaroff, Dave Passovoy, and Dan Porter. For comments on the survey content, we thank Dave Marvin, Tadashi Moody, Nadia Tase, and David Sapsis. For suggestions of experts, we thank again Max Moritz and Tadashi Moody. This research was funded by the S.D. Bechtel, Jr. Foundation. Additionally, P.A.T. and D.L.S. were supported by the David and

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Lucile Packard Foundation, and K.J.M. was supported by the Alexander von Humboldt Foundation.

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SUPPORTING INFORMATION Additional Supporting Information may be found online at: http://onlinelibrary.wiley.com/doi/10.1002/ecs2. 2321/full


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