Regional carbon cycle responses to 25 years of variation in climate and disturbance in the US Pacific Northwest

Turner, David P.; Ritts, William D.; Kennedy, Robert E.; Gray, Andrew N.; Yang, Zhiqiang

doi:10.1007/s10113-016-0956-9

Cited by 12 publications

(11 citation statements)

References 71 publications

(79 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…, Turner et al. , ). Although these models have characterized important aspects of forest ecology and atmosphere–biosphere dynamics, their simplified representation of species composition and canopy structure may affect their simulation of natural forest stands of the Pacific Northwest in important ways.…”

Section: Introductionmentioning

confidence: 99%

“…For example, in Biome‐BGC, only one plant functional type (PFT) occupies each site, and no distinct age or size classes are represented (Turner et al. , ). 3‐PG is a physiologically based stand growth model developed principally for plantation forestry applications but applied widely across the Pacific Northwest (Landsberg and Waring , Waring et al.…”

Section: Introductionmentioning

confidence: 99%

“…Although these models have characterized important aspects of forest ecology and atmosphere-biosphere dynamics, their simplified representation of species composition and canopy structure may affect their simulation of natural forest stands of the Pacific Northwest in important ways. For example, in Biome-BGC, only one plant functional type (PFT) occupies each site, and no distinct age or size classes are represented (Turner et al 2015(Turner et al , 2016. 3-PG is a physiologically based stand growth model developed principally for plantation forestry applications but applied widely across the Pacific Northwest (Landsberg andWaring 1997, Waring et al 2011).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Linking tree physiological constraints with predictions of carbon and water fluxes at an old‐growth coniferous forest

et al. 2019

View full text Add to dashboard Cite

Old‐growth coniferous forests of the Pacific Northwest are among the most productive temperate ecosystems and have the capacity to store large amounts of carbon for multiple centuries. To date, there are considerable gaps in modeling ecosystem fluxes and their responses to physiological constraints in these old‐growth forests. These model shortcomings limit our ability to understand and project how the old‐growth forests of the Pacific Northwest will respond to global climate change. This study applies the cohort‐based Ecosystem Demography Model 2 (ED2) to the Wind River Experimental Forest (Washington, USA), a well‐studied old‐growth Douglas‐fir–western hemlock ecosystem. ED2 is calibrated and validated using an extensive suite of forest inventory, eddy covariance, and biophysical observations. ED2 is able to reproduce observed forest composition and canopy structure, and carbon, water, and energy fluxes at the site. In the simulations, the effect of limited water supply on ecosystem carbon fluxes is mediated primarily by the forest's gross primary productivity (GPP) response, rather than its heterotrophic respiration response. The simulation indicates that stomatal conductance is mainly determined by soil moisture during periods of low vapor pressure deficit (VPD). However, when VPD is high, stomatal conductance is greatly reduced regardless of soil moisture status. During summer droughts, reduced soil moisture and increased VPD result in considerable stomatal closure and GPP reduction, which in turn decreases net carbon uptake. Cohort‐based scheme integrates all canopy layers (species) that have distinct sensitivity to microclimate and respond distinctly to drought. This study is an initial first step to explore the potential importance of cohort‐based model in simulating forest with complex structure, and to lay the foundation for applying cohort‐based model at regional scales across the Pacific Northwest.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Linking tree physiological constraints with predictions of carbon and water fluxes at an old‐growth coniferous forest

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Actual NPP is the net solar energy accumulated by vegetation under the double influences of climatic conditions and anthropogenic activities, while potential NPP is the net energy fixed by vegetation, which is solely driven by climatic factors (Haberl et al 2007). Various models have been widely developed to estimate NPP at multiple scales, which mainly including climate-based models (e.g., Miami model (Lieth 1975), Thornthwaite Memoria model (Lieth and Box 1972) and Zhou Guangsheng model (Zhou and Zhang 1996)), process-based models (e.g., TEM (McGuire et al 1995), BIOME-BGC (Turner et al 2016)) as well as light use efficiency models (e.g., CASA (Potter et al 1993)). Due to the different mechanisms of the models, their applicability and accuracy differ on different scales.…”

Section: Introductionmentioning

confidence: 99%

Impacts of land conversion and management measures on net primary productivity in semi-arid grassland

Cao

Xiao

et al. 2020

Ecosyst Health Sustain

View full text Add to dashboard Cite

Ecological restoration measures implemented in China have profoundly impacted vegetation NPP. This study aimed to estimate the effects of the land conversion and management measures on the grassland ecosystem in semi-arid regions. Land use data were employed from 2000 to 2015 to compare land conversion and coverage changes in Xilingol grassland. Then, the contributions of land conversion and management policies were quantified by assessing the difference between actual NPP and climate-induced NPP changes. The results indicated that the grassland area had a net loss of 534.42 km 2 , and the net area of increased vegetation coverage was 74,683.05 km 2 . Furthermore, the total NPP increased by 8,010.73 Gg C·yr −1 (1 Gg = 10 9 g), of which the human activities, including grazing management measures (+6,809.40 Gg C·yr −1 ) and land conversion (45.72 Gg C·yr −1 ) contributed to 85.58% of the increase in NPP. Transformation from desert and farmland dominated grassland expansion and NPP increase, while urbanization and desertification caused large grassland reduction and NPP loss. The grazing management increased vegetation NPP in most regions except for some regions in the desert steppe and the farming-pastoral zone. Related policies should be further adjusted to strengthen the management of the desert steppe and farming-pastoral regions. ARTICLE HISTORY

show abstract

“…In addition, large levels of tree cover tend to develop quickly after disturbance in productive vegetation types, which can saturate the Landsat signal, such that forest biomass and carbon continue to increase as stands mature, with little to no change in spectral signatures [15]. Nevertheless, the Landsat record can be used to estimate time since disturbances that originated after 1972 and can be combined with extensive information on forest density and change from NFIs to estimate flux at regional scales [16]. The time-series may also be used to estimate flux directly from the changes in spectral signature, which is the focus of this paper.…”

Section: Introductionmentioning

confidence: 99%

Integrating TimeSync Disturbance Detection and Repeat Forest Inventory to Predict Carbon Flux

Gray

Cohen

Yang

et al. 2019

Forests

Self Cite

View full text Add to dashboard Cite

Understanding change in forest carbon (C) is important for devising strategies to reduce emissions of greenhouse gases. National forest inventories (NFIs) are important to meet international accounting goals, but data are often incomplete going back in time, and the amount of time between remeasurements can make attribution of C flux to specific events difficult. The long time series of Landsat imagery provides spatially comprehensive, consistent information that can be used to fill the gaps in ground measurements with predictive models. To evaluate such models, we relate Landsat spectral changes and disturbance interpretations directly to C flux measured on NFI plots and compare the performance of models with and without ground-measured predictor variables. The study was conducted in the forests of southwest Oregon State, USA, a region of diverse forest types, disturbances, and landowner management objectives. Plot data consisted of 676 NFI plots with remeasured individual tree data over a mean interval (time 1 to time 2) of 10.0 years. We calculated change in live aboveground woody carbon (AWC), including separate components of growth, mortality, and harvest. We interpreted radiometrically corrected annual Landsat images with the TimeSync (TS) tool for a 90 m × 90 m area over each plot. Spectral time series were divided into segments of similar trajectories and classified as disturbance, recovery, or stability segments, with type of disturbance identified. We calculated a variety of values and segment changes from tasseled cap angle and distance (TCA and TCD) as potential predictor variables of C flux. Multiple linear regression was used to model AWC and net change in AWC from the TS change metrics. The TS attribution of disturbance matched the plot measurements 89% of the time regarding whether fire or harvest had occurred or not. The primary disagreement was due to plots that had been partially cut, mostly in vigorous stands where the net change in AWC over the measurement was positive in spite of cutting. The plot-measured AWC at time 2 was 86.0 ± 78.7 Mg C ha−1 (mean and standard deviation), and the change in AWC across all plots was 3.5 ± 33 Mg C ha−1 year−1. The best model for AWC based solely on TS and other mapped variables had an R2 = 0.52 (RMSE = 54.6 Mg C ha−1); applying this model at two time periods to estimate net change in AWC resulted in an R2 = 0.25 (RMSE = 28.3 Mg ha−1) and a mean error of −5.4 Mg ha−1. The best model for AWC at time 2 using plot measurements at time 1 and TS variables had an R2 = 0.95 (RSME = 17.0 Mg ha−1). The model for net change in AWC using the same data was identical except that, because the variable being estimated was smaller in magnitude, the R2 = 0.73. All models performed better at estimating net change in AWC on TS-disturbed plots than on TS-undisturbed plots. The TS discrimination of disturbance between fire and harvest was an important variable in the models because the magnitude of spectral change from fire was greater for a given change in AWC. Regional models without plot-level predictors produced erroneous predictions of net change in AWC for some of the forest types. Our study suggests that, in spite of the simplicity of applying a single carbon model to multiple image dates, the approach can produce inaccurate estimates of C flux. Although models built with plot-level predictors are necessarily constrained to making predictions at plot locations, they show promise for providing accurate updates or back-calculations of C flux assessments.

show abstract

Regional carbon cycle responses to 25 years of variation in climate and disturbance in the US Pacific Northwest

Cited by 12 publications

References 71 publications

Linking tree physiological constraints with predictions of carbon and water fluxes at an old‐growth coniferous forest

Linking tree physiological constraints with predictions of carbon and water fluxes at an old‐growth coniferous forest

Impacts of land conversion and management measures on net primary productivity in semi-arid grassland

Integrating TimeSync Disturbance Detection and Repeat Forest Inventory to Predict Carbon Flux

Contact Info

Product

Resources

About