Validation of Forest Vegetation Simulator Model Finds Overprediction of Carbon Growth in California

Herbert, Claudia; Fried, Jeremy S.; Butsic, Van

doi:10.3390/f14030604

Cited by 4 publications

(1 citation statement)

References 19 publications

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“…Comprehensive models use ecologically significant estimation models combined with remotely sensed data to estimate forest AGB. These models employ ecological succession as the theoretical basis and allow dynamic simulation of forest vegetation changes [204], including the widely used FAREAST, LANDIS/LANDIS-II, FVS, and SORTIE-ND models [199][200][201][202][203]. For instance, based on the FAREAST model, Wang et al [205] used the distribution range of Picea crassifolia on different elevation gradients to simulate the elevation distribution characteristics of biomass carbon in young and middle-aged forests in the western, central, and eastern Qilian Mountains.…”

Section: Comprehensive Modelingmentioning

confidence: 99%

Review of Remote Sensing-Based Methods for Forest Aboveground Biomass Estimation: Progress, Challenges, and Prospects

Tian

et al. 2023

Forests

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Quantifying forest aboveground biomass (AGB) is essential for elucidating the global carbon cycle and the response of forest ecosystems to climate change. Over the past five decades, remote-sensing techniques have played a vital role in forest AGB estimation at different scales. Here, we present an overview of the progress in remote sensing-based forest AGB estimation. More in detail, we first describe the principles of remote sensing techniques in forest AGB estimation: that is, the construction and use of parameters associated with AGB (rather than the direct measurement of AGB values). Second, we review forest AGB remotely sensed data sources (including passive optical, microwave, and LiDAR) and methods (e.g., empirical, physical, mechanistic, and comprehensive models) alongside their limitations and advantages. Third, we discuss possible sources of uncertainty in resultant forest AGB estimates, including those associated with remote sensing imagery, sample plot survey data, stand structure, and statistical models. Finally, we offer forward-looking perspectives and insights on prospective research directions for remote sensing-based forest AGB estimation. Remote sensing is anticipated to play an increasingly important role in future forest AGB estimation and carbon cycle studies. Overall, this comprehensive review may (1) benefit the research communities focused on carbon cycle, remote sensing, and climate change elucidation, (2) provide a theoretical basis for the study of the carbon cycle and global climate change, (3) inform forest ecosystems and carbon management, and (4) aid in the elucidation of forest feedbacks to climate change.

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Section: Comprehensive Modelingmentioning

confidence: 99%

Review of Remote Sensing-Based Methods for Forest Aboveground Biomass Estimation: Progress, Challenges, and Prospects

Tian

et al. 2023

Forests

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Sapling recruitment as an indicator of carbon resiliency in forests of the northern USA

Harris,

Woodall,

D'Amato

2024

Ecology and Evolution

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Tree regeneration shapes forest carbon dynamics by determining long‐term forest composition and structure, which suggests that threats to natural regeneration may diminish the capacity of forests to replace live tree carbon transferred to the atmosphere or other pools through tree mortality. Yet, the potential implications of tree regeneration patterns for future carbon dynamics have been sparsely studied. We used forest inventory plots to investigate whether the composition of existing tree regeneration is consistent with aboveground carbon stock loss, replacement, or gain for forests across the northeastern and midwestern USA, leveraging a recently developed method to predict the likelihood of sapling recruitment from seedling abundance tallied within six seedling height classes. A comparison of carbon stock predictions from tree and seedling composition suggested that 29% of plots were poised to lose carbon based on seedling composition, 55% were poised for replacement of carbon stocks (<5 Mg ha−1 difference) and 16% were poised to gain carbon. Forests predicted to lose carbon tended to be on steeper slopes, at lower latitudes, and in rolling upland environments. Although plots predicted to gain and lose carbon had similar stand ages, carbon loss plots had greater current carbon stocks. Synthesis and applications. Our results demonstrate the utility of considering tree regeneration through the lens of carbon replacement to develop effective management strategies to secure long‐term carbon storage and resilience in the context of global change. Forests poised to lose C due to climate change and other stressors could be prioritized for regeneration strategies that enhance long‐term carbon resilience and stewardship.

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Field estimation of fallen deadwood volume under different management approaches in two European protected forested areas

Rousseau,

Adiningrat,

Skidmore

et al. 2024

Forestry: An International Journal of Forest Research

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Fallen deadwood is essential for biodiversity and nutrient cycling in forest ecosystems. In modern forest management, there is growing interest in developing accurate and efficient methods for field estimation of deadwood volume due to its many benefits (e.g. carbon storage, habitat creation, erosion control). The most common methods for deadwood inventories are fixed-area sampling (FAS) and line-intersect sampling (LIS) methods. While the estimations of deadwood volume by LIS generally show results comparable to FAS estimations, active management (e.g. production forestry clearcutting, logging, and thinning activities) can impair LIS accuracy by changing local deadwood patterns. Yet, the comparison of LIS and FAS methods has typically focused on production forests where deadwood is limited and deadwood volumes are comparably low. In this study, we assessed fallen deadwood volume in two large national parks—one being a more actively managed landscape (including, e.g., selective thinning for maintaining cultural–historical values and enhancing recreational opportunities) with overall lower levels of fallen deadwood, and the other having a strict non-intervention approach with higher levels of deadwood. No significant differences between average FAS and LIS estimations of deadwood volumes were detected. Additional experimentations using simulated data under varied stand conditions confirmed these results. Although line-intersect sampling showed a slight overestimation and some variability at the individual plot level, it remains an efficient, time-saving field sampling method providing comparable results to the more laborious fixed-area sampling. Line-intersect sampling may be especially suitable for rapid field inventories where relative changes in deadwood volume rather than absolute deadwood volumes are of large interest. Due to its practicality, flexibility, and relative accuracy, line-intersect sampling may gain wider use in natural resource management to inform national park managers, foresters, and ecologists.

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Validation of Forest Vegetation Simulator Model Finds Overprediction of Carbon Growth in California

Cited by 4 publications

References 19 publications

Review of Remote Sensing-Based Methods for Forest Aboveground Biomass Estimation: Progress, Challenges, and Prospects

Review of Remote Sensing-Based Methods for Forest Aboveground Biomass Estimation: Progress, Challenges, and Prospects

Sapling recruitment as an indicator of carbon resiliency in forests of the northern USA

Field estimation of fallen deadwood volume under different management approaches in two European protected forested areas

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