Jesse D. Henderson

Long-term carbon storage by forests is important for climate mitigation, yet storage durability faces threats from natural disturbances whose causal impacts are not well quantified. We use the staggered timing of two Category 4 hurricanes that struck different regions of Louisiana—Laura in 2020 and Ida in 2021—to estimate the causal effect of severe hurricane damage on forest carbon stocks. Using parish-level data from the USDA forest inventory and analysis program covering all 64 Louisiana parishes over 2017–2024 and a doubly robust difference-in-differences estimator, we find that hurricane damage reduced live biomass carbon by 7%–8%: aboveground live carbon declined 7.3% and belowground live carbon 7.7%, results robust to both cluster-robust and wild cluster bootstrap inference. Total forest carbon—nearly half of which is held in a slow-changing soil pool—declined by 3.5% (95% CI: −6.9% to −0.2%); this aggregate effect is significant under cluster-robust inference but not under the wild cluster bootstrap appropriate for our small number of treated clusters. Effects persisted across the four-year post-treatment period with no evidence of recovery. Live carbon losses were concentrated on private forests (−7.9%, P = 0.022), with no detectable change on public forests (+0.9%, P = 0.892), though this private–public difference is not statistically significant (interaction P = 0.493). We measure changes in carbon stocks rather than net flux to the atmosphere. Because private lands make up 86% of Louisiana’s forestland and underpin most carbon offset programs, the magnitude and persistence of these losses suggest that nature-based climate solutions in hurricane-prone regions face greater hurricane-related risks than current carbon-offset frameworks recognize.

We examine spatial linkages among quarterly prices for southern yellow pine sawtimber. Regional prices for several Southeastern US markets are compared to a central market---South Georgia. An extensive literature evaluating spatial price linkages has progressed from simple linear models to increasingly nonlinear models. We extend this literature by adopting generalized additive models, which permit a nonparametric representation of price linkages. We suspect nonlinearity among spatially distinct markets due to the presence of unobserved transactions costs, which are likely to be substantial for bulky goods such as sawtimber. We utilize linear cointegration models and find a strong degree of equilibrating reactions to price shocks, though important exceptions exist. We then estimate simple error correction models that measure the time required for such equilibrating reactions. Finally, we estimate fully nonlinear models of price linkages. We find that spatially distinct markets for pine sawtimber are largely integrated and responsive to isolated shocks in individual markets.

While extreme weather events are often localized, the potential effects on global forests can be far reaching due to the interconnected nature of forest product markets. To better understand these dynamics, this study leverages historical forest‐based wind damage data in the United States and applies this information as shocks within a global forest sector outlook model. A large, localized wind event modeled as a shock to the US South creates a one‐time increase of 18.7 million m³ from salvage harvest operations, equal to over 4% of national harvest. This crowds out traditional harvest activities, leading to downward pressure on prices in the short run, followed by a persistent effect that could take approximately 25 years to dissipate from markets. Average annual wind damage contributes downward pressure on roundwood prices between 1% and 4% in the United States, and this effect is distributed to other countries. The findings suggest that large, localized shocks reverberate across regions and wood product markets due to their interconnected supply chains and trade patterns, and these impacts have important temporal dynamics. Another key result is that the magnitude of these effects are offset by endogenous market reactions in other markets. In other words, unaffected regions change their harvesting patterns in order to compensate for changes in the availability of fiber, shedding light on the importance of capturing global channels as large shocks materialize in changes in market dynamics internationally. Monte Carlo simulations suggest a wide confidence band on salvage harvest rates and prices.

The timber supply chain encompasses the processes involved in the sustainable extraction, processing, and distribution of timber products. This complex network involves coordination among forest owners, loggers, sawmills, wholesalers, and retailers to ensure efficient flow from forest to end consumers. Understanding the gaps and barriers in the timber supply chain is essential for promoting economic growth, environmental sustainability, and social responsibility within the forestry industry. In this paper, we employ a game theory approach to explore the interactions among forest landowners (suppliers), wood-using mills (demand for timber), and a carbon offset aggregator (demand for carbon) as market agents to provide insights about the trade-offs faced by forest landowners. We develop a timber supply chain model based on common landowner decision criteria, such as maximizing forest value, in the US South. In this model, landowners harvest timberland to maximize their profit while taking carbon sequestration into account. Our study examines the trade-off between timber harvesting and harvest deferral for carbon sequestration based on landowners' environmental awareness. A Bertrand game has been designed to determine the Nash equilibrium pricing strategy for timber price and carbon price- based on forest structure and landowners' environmental awareness. Our findings indicate a positive association between carbon sequestration and landowners' willingness to participate in carbon programs. Our findings help to analyze the future trends in the timber market, including supply levels, demand growth, and price movements. This line of inquiry can provide valuable insights for aggregators and forest products mills on strategically planning which wood basins are more suitable for their needs. Additionally, it allows landowners to better comprehend an additional income source (carbon offsets) and complement it with more established sources of income.

This study expands the spatial scope of the Subregional Timber Supply (SRTS) model to include states in the central hardwood region and examine critical market tipping points of high-grade (large diameter) white oak under a set of illustrative scheduled demand scenarios. In light of the growing concern for future white oak timber supply, we illustrate the sensitivity of future inventory tipping points to market structure and price responsiveness. Particularly, we examined the importance of market demand parameters, including growth rates for product demand and supply/demand elasticities, in influencing future inventory trajectories in different subregions over the projection horizon. Results of this study indicate that more elastic demand and more inelastic supply response concomitantly defers the time before inventory culminates. This modeling framework shows promise in examining key ecological, climatic, and economic interrelationships that will drive future resource changes. Study Implications: This study examines critical market tipping points of high-grade white oak growing stock in the central hardwood region under alternative demand growth scenarios. The main finding of this article is that high-quality white oak inventory tipping points depend critically on the annual rate of increase in quantity demanded and on the sensitivity of supply and demand to changes in white oak log prices. This study helps better inform white oak–dependent stakeholders on sustainability assessment and highlights how policy design that incorporates both management and market interventions could help maintain the white oak resource base.