Among the portfolio of options available, managing forest carbon can be a low-cost, low-tech, and relatively simple approach to addressing climatic change. Over half of forests in the US are privately owned and may include individuals or family estates and trusts holding at least 1 acre of forest and at least 10 percent stocking density.
To work with these groups, carbon-offset project developers need to design strategies that engage diverse categories of forest owners, including family forest owners (FFOs).
Innovations in carbon accounting and aggregation have allowed for the emergence of boutique carbon-offset programs, such as the Natural Capital Exchange and the Family Forest Carbon Program, which generally focus on smaller landholders in the eastern US The management practices incentivised in many of these programs is delay in harvest (i.e., lengthening harvest cycles, changing harvest strategies, and optimal rotation).
However, forests in the US already offset up to 11 percent of total US greenhouse gas emissions due to longstanding slowdowns in harvesting.
Furthermore, up to 89 percent of the US timber supply comes from private forest lands, which means delaying harvest for additional carbon storage could have important implications for domestic timber supply.
With only a small fraction of FFOs enrolled in a carbon program, there is a limited amount of real data describing what owners may prefer in a contract and level of payment.
Stated preference studies have been the approach so far for assessing the potential. of new markets; however, these kinds of studies can be challenging to conduct when time and resources are limited. Benefit transfer (BT) methods are a useful way of employing values from existing studies to estimate preferred types of programs for FFOs. Estimating willingness to accept (WTA) values across a variety of FFOs and contracts may also help identify potential early adopters and the direction of innovation.
Reasons To Participate In Forest Carbon Payment Program
Studies examining landowners’ willingness to participate in a forest carbon payment program found choices are often a function of economic, social, and environmental factors.
For example, economic barriers to participation include low carbon prices and high opportunity costs and entry costs (e.g., requirements of a management plan and certification). Social factors include compatibility with other forest management objectives (e.g., timber production, recreational uses). The risk of a natural disturbance impacting carbon sequestration potential may increase liability risk due to accidental release.
Despite these challenges, many forest owners are still interested in preserving the environmental benefits associated with their forest, including carbon storage.
Carefully designed carbon incentive programs for FFOs could help promote climate-smart forestry, which is needed to help protect other forest ecosystem services, including wildlife habitat, soil quality, water storage, nutrient retention, filtration, and biodiversity conservation.
Because private forest owners maintain forests for multiple uses, many consider forest carbon storage an ancillary benefit.
This means that opportunities for carbon incentives need to be in line with other expectations for forest ownership. Identification of early adopters is important for understanding what categories of owners will likely establish the direction of forest carbon programs and climate change mitigation solutions.
Stated preference studies have consistently found that acceptable payment levels can vary depending on conservation goals, expected management activities, and program design.
Early adopters of new technology in agricultural fields tend to be more accepting of change and better-equipped to manage uncertainty and risk, among other qualities.
Illustrative of variation in forest owner response to risk is the finding that certain portions of FFOs refuse to take part in forest carbon programs at any price.
Since the diffusion of forest carbon incentives is still in the early stages, owners who have actually enrolled in a payments program offer a glimpse of who may be early adopters. Case studies reveal that these early adopters tend to be larger landholders that are actively working to advance biological conservation.
What it may take to engage other types of FFOs in forest carbon incentives is still unclear. Benefit transfer (BT) is a valuation method that uses econometric methods to transfer economic information from existing empirical research to a new policy or site where the value has not been assessed.
The BT method has been widely applied to the valuation of various ecological assets, including wetlands, forests, fishery resources, and biodiversity at various scales, including individual projects at micro level and a larger geographic scale at regional, country, or global levels.
It has also been used to inform a number of decisions, including private project cost–benefit analysis, green accounting for public decisions, and providing a technical/legal basis for compensation of environmental damage.
Regression analysis is a statistical method commonly used to transfer values from the data collected via a meta-analysis study. This approach allows for better understanding of interstudy variation in research outcomes by modelling the characteristics that are typically held constant within an individual study, such as valuation methodology, survey mode, time, and physical attributes of the study site.
To our knowledge, the meta-analysis and BT approach has never been employed to generate estimates of value for carbon contracts for different categories of FFOs.
The goal of this paper is to use existing studies to explore what kinds of forest carbon incentive levels and contracts may be preferred by a variety of forest owners. We used meta-analysis and BT methods to generate estimates of value and applied these values to a variety of contracts that may be preferred by architype categories of FFOs. Steps include:
1.Curate a collection of stated preference studies conducted in the US and focused on forest carbon incentives;
2.Examine the statistical relationship between willingness to accept payment (WTA) for forest carbon and study program features, including contract design and respondent characteristics;
3.Apply estimated values to contractual arrangements that may appeal to different categories of FFOs based on their values and management objectives.
Findings are expected to provide valuable insights for forest carbon policies and project developers regarding the design of forest carbon incentive and assistance programs.
Reviewing The Stated Preference Studies
To conduct the research, we firstly reviewed the stated preference studies. The literature review and meta-analysis procedures were conducted following the recommendations as shown in Appendix A.
Google Scholar and Science Hub were the primary databases, and the search was conducted using keywords such as ‘Private Forest landowners’, ‘Willingness to Accept (WTA)’, ‘carbon sequestration’, ‘carbon market programs’, ‘private forests in the US’, ‘voluntary offset markets’, and ‘forest management for ecosystem services’.
The criteria for inclusion in the study was: (1) used stated preference methods to generate WTA values for participating in a voluntary carbon-offset program, (2) conducted in the US, and (3) the respondents are private forests landowners. Over 70 peer-reviewed articles, conference papers, book chapters, and grey literature were reviewed; however, 22 primary studies were found to be relevant to the subject, and 13 contained WTA data that could serve as a dependent variable for use in a regression analysis.
This meta-analysis comprises five sequential steps with specific principles as briefly discussed below.
Step 1: Developing the research question
Our meta-analysis began with a distinctly formulated research question (e.g., hypothesis) after identifying the research gap in the topic of interest. The research question was derived from a detailed assessment of relevant studies. The scope of our study was specified by defining the number of primary studies, review articles, and existing metanalysis in the related field. The study of important ideas and principles, conflicts, and controversies that need to be resolved and some prominent variables were conducted prior to the review.
Step 2: Literature search for review
The comprehensive review of all relevant research was performed following the common search strategy of keyword search in electronic database. Additional details are available in the method section. The relevant studies were manually screened by reading the abstract method and result sections. For instance, the studies reporting willingness to accept payment value for forest carbon in the US were considered. Further, grey literatures were also reviewed to avoid the selection and publication bias that could underestimate the true effect size (correlation coefficients and standardised mean differences).
Step 3: Coding the important information from studies
A specific coding strategy was performed to track the attributes of selected studies. Considerable attention was paid to the variables and studies that were coded for program attributes, study features, and respondent’s characteristics. The codes were formulated according to the type of data available (binary, categorical, and continuous) in the studies. Willingness to accept payment value served as dependent variable in our study. This value is a summary statistic from the primary literatures and was assessed using different conversion procedures such as converting the value to same unit, changing to its inflated value for the year 2020, etc.
Step 4: Systematic data analysis
Once the dataset was formulated, a general analysis was conducted, resulting in a statistical summary. Further, we performed meta-analysis with regression to identify relationships between variables using STATA software. The latest version of STATA presents built-in functions to execute several meta-analytical assessments or to generate various plots. Outlier analysis and bias tests were conducted prior to the model selection. For example, a weighting variable was created to adjust the responses in order to eliminate the response and sample bias. We applied the results of our empirical model as a benefit transfer to represent WTA values of new contracts and scenarios in the US.
Step 5: Directing future research with clear conclusion
At the end, results from the meta-analysis were used to serve as a useful guide to future research. Directions and research avenues are briefly discussed to address key weakness and to complement current knowledge within the research area.
Data Analysis & Methodologies Used In Research
And then, we summarised the studies estimating forest owner willingness to accept (WTA) payment for managing forest carbon.
Most studies came from the southeastern US (41.6%) followed by the Northeast (36.11%). The remainder came from Southwest, Midwest, and Northwest, respectively.
Implementation dates ranged from 1994 to 2019, and data were collected from landowners using survey methods. Most of the studies involved mail surveys (80.5%), followed by web and a telephone survey. Sample sizes ranged from 141 to 1032 complete responses (mean = 594), representing the opinions of 21,119 respondents in total. Response rates for the mail surveys averaged 39.3 percent.
Methodologies used to generate estimates of WTA values included contingent valuation, dichotomous choice, best–worst choice modelling case, and attribute choice experiment. Nine studies produced multiple WTA observations, and four studies provided a single observation of WTA. Two studies described variation in WTA by constructing demand curves based on percent willing to enrol under different payment levels.
For these studies, a weighted means method was used to construct a single WTA value for use in the regression analysis.
The contract features described in the studies included options such as length of contract, whether there was a withdrawal option or not (penalty), type of ecosystem service (i.e., carbon sequestration or other ecosystem services), and requirement of management plan and management restrictions, such as delay in harvest.
Contract length was the most common contract attribute, and lengths ranged from one to 50+ years. All the studies reported socio-economic data about the respondents, including the respondent’s ethnicity, gender, age, education, number of acres owned, and tenure length, but the format used varied across studies.
Willingness to accept observations were understood to be the minimum monetary amount that an owner is willing to accept as a compensation to change their forest management activities to enhance carbon sequestration services.
The summary statistic for WTA reported in each study served as the dependent variable in the meta-analysis. To make them comparable, all mean WTA values were converted into an annual payment per acre in 2020 USD and transformed by taking the natural log. A total of 17 independent variables were developed for testing to help explain important variation in WTA.
These variables represented different contract attributes, respondent characteristics, and study characteristics. Contract attributes included length of contract, withdrawal penalty, management plan, and management restrictions.
Data describing forest owners in each study were arranged into categories representing relevant distributions of age, gender, race, educational status, income from the timber, acres owned, and length of tenure.
When data from studies describing owner characteristics were incompatible or incomplete, state level data from the National Woodland Owners survey 2006, 2013, and 2018 were used as a substitute. Information on the study region, data collection methods, sample size, survey questions, and respondent’s rate were coded using percent or category codes.
Study response rate metrics were used to create a weighting variable to control for differences in study quality. A fractional weight was used to control the influence of multiple observations from a single study.
Due to the small number of observations, a robust regression model was employed using STATA 15.1. Robust regression is an alternative to least squares regression when using small data sets with large variation in data distributions.
Final models include only significant variables, and model selection was based on R-squared and root mean square error.
To generate a discount rule for early adopters, we used the studies that reported WTA metrics using demand curves.
Percent enrolment at different price points indicated that at least half of forest owners were willing to accept up to 75 percent less compared to the other half of forest owners. To account for this variation in the benefit transfer, we calculated a second estimate for early adopters by applying a 75 percent discount rule to mean WTA values.
The following benefit transfer procedure was used to assign values to carbon contracts expected to appeal to three categories of forest owners. These categories are intended to represent different forest owner archetypes and include the passive forest owner, the conservation-oriented forest owner, and the timber production-oriented forest owner.
These categories were based on the findings of a related study that linked willingness to pay/accept behaviours with different motivations and management objectives. Those with conservation or social responsibility motives were less sensitive to potential financial losses compared to those with timber-production motives.
Other differences among these groups may also be related to how land use and expected benefits are prioritised.
Owners with limited knowledge and skills in forest management can be expected to be more passive or less proactive in forest management.
However, there is reason to expect that passive owners may still act as early adopters in a carbon payments program. Passive owners may see carbon payments as a new and easy source of supplemental income compared to arranging a timber harvest every five to 10 years.
Because they are less invested in timber production as a primary goal, the opportunity cost of delaying harvest may be perceived as minimal.
However, passive owners may also see longer contracts as increasing other types of opportunity costs and would want greater compensation for longer contracts. Passive owners are also less likely to have a forest management plan and may want financial compensation in order to adopt a management plan.
Some conservation-oriented forest owners could also be early adopters if climate stewardship is perceived as being part of forest stewardship. These owners may have some knowledge and skills in forest management and already have a forest management plan, so modifying the plan could be relatively easy and not require large compensation.
They may also see carbon incentives as a better way to finance forest management activities compared to timber harvesting (because the payments may be more regular, or harvesting may not be compatible with their management objectives); therefore, a delay in harvest may not be associated with a large opportunity cost.
Conservation-oriented owners may also be less resistant to longer contracts, especially if it is in line with their legacy planning objectives, but some compensation would still be needed to represent important land values.
Timber production-oriented owners may also have some knowledge and skills in forest management but could still be later adopters of forest carbon payment programs. This is because the perceived or real opportunity costs associated with delaying harvest and managing for carbon may be more strongly felt. Longer contracts could also increase opportunity costs by delaying harvest to a rotation age that is beyond their lifetime. These owners may also have a management plan already in place, so modifying the plan may not be costly to do.
Summary And Recommendations
The meta-analysis presented here highlights the importance of contract features on forest owner choices, with a special focus on different categories of forest owners. A fair number of WTA estimates are within the range of current payment levels for forest carbon, but the values were more often associated with conservation-oriented and passive owners with larger landholdings.
Timber-production-oriented owners’ resistance towards carbon payment programs may help soften implications of delay in harvest on domestic timber supply, but this is uncertain since production-oriented owners are also a minority category of FFOs.
Furthermore, assumptions about how delays in harvest can lead to additional carbon storage are difficult to justify for many FFOs since passive owners’ intentions about harvesting are unknown even to them.
Outreach and education programs for all types of owners will be important for helping cultivate more informed economic actors around forest carbon and encourage future investment in forest ownership.
An increase in the price of carbon may also help attract more participants by helping remove some of the barriers to participation (e.g., obtaining a forest management plan) and economies of scale issues. Incentives that encourage climate smart forestry while supporting other management objectives (e.g., wildlife habitat) could be structured as a cost-share arrangement rather than a direct payments approach, which tends to be more difficult to validate.
There is also the need for investors to consider approaches that do not require storing carbon in the forest, since there may be limits to the capacity of private forests serving as a carbon sink while also providing other important ecosystems services. Encouraging the production of long-lived wood products could help store forest carbon offsite and offset the use of substitutes with a larger carbon footprint.
Future studies should examine how long-lived wood products could be wrapped into a carbon offset project and determine under what conditions (e.g., percent enrolled) carbon programs may start to interfere with domestic timber supplies.
Research is also needed to understand a broader set of factors on choice, such as perceived legitimacy of the program on offer and the preferences of underserved forest owners and owners in countries outside the US.