Dataset Information

Allocation pattern and accumulation potential of carbon stock in natural spruce forests in northwest China.

ABSTRACT: The spruce forests are dominant communities in northwest China, and play a key role in national carbon budgets. However, the patterns of carbon stock distribution and accumulation potential across stand ages are poorly documented.We investigated the carbon stocks in biomass and soil in the natural spruce forests in the region by surveys on 39 plots. Biomass of tree components were estimated using allometric equations previously established based on tree height and diameter at breast height, while biomass in understory (shrub and herb) and forest floor were determined by total harvesting method. Fine root biomass was estimated by soil coring technique. Carbon stocks in various biomass components and soil (0-100 cm) were estimated by analyzing the carbon content of each component.The results showed that carbon stock in these forest ecosystems can be as high as 510.1 t ha-1, with an average of 449.4 t ha-1. Carbon stock ranged from 28.1 to 93.9 t ha-1 and from 0.6 to 8.7 t ha-1 with stand ages in trees and deadwoods, respectively. The proportion of shrubs, herbs, fine roots, litter and deadwoods ranged from 0.1% to 1% of the total ecosystem carbon, and was age-independent. Fine roots and deadwood which contribute to about 2% of the biomass carbon should be attached considerable weight in the investigation of natural forests. Soil carbon stock did not show a changing trend with stand age, ranging from 254.2 to 420.0 t ha-1 with an average of 358.7 t ha-1. The average value of carbon sequestration potential for these forests was estimated as 29.4 t ha-1, with the lower aged ones being the dominant contributor. The maximum carbon sequestration rate was 2.47 t ha-1 year-1 appearing in the growth stage of 37-56 years.The carbon stock in biomass was the major contributor to the increment of carbon stock in ecosystems. Stand age is not a good predictor of soil carbon stocks and accurate evaluation of the soil carbon dynamics thus requires long-term monitoring in situ. The results not only revealed carbon stock status and dynamics in these natural forests but were helpful to understand the role of Natural Forest Protection project in forest carbon sequestration as well.

SUBMITTER: Yue JW

PROVIDER: S-EPMC5971841 | biostudies-other | 2018

REPOSITORIES: biostudies-other

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Allocation pattern and accumulation potential of carbon stock in natural spruce forests in northwest China.

Yue Jun-Wei JW Guan Jin-Hong JH Deng Lei L Zhang Jian-Guo JG Li Guoqing G Du Sheng S

PeerJ 20180525

<h4>Background</h4>The spruce forests are dominant communities in northwest China, and play a key role in national carbon budgets. However, the patterns of carbon stock distribution and accumulation potential across stand ages are poorly documented.<h4>Methods</h4>We investigated the carbon stocks in biomass and soil in the natural spruce forests in the region by surveys on 39 plots. Biomass of tree components were estimated using allometric equations previously established based on tree height ...[more]

PMID: 29844994

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Project description:BackgroundSevere canopy-removing disturbances are native to many temperate forests and radically alter stand structure, but biotic legacies (surviving elements or patterns) can lend continuity to ecosystem function after such events. Poorly understood is the degree to which the structural complexity of an old-growth forest carries over to the next stand. We asked how pre-disturbance spatial pattern acts as a legacy to influence post-disturbance stand structure, and how this legacy influences the structural diversity within the early-seral stand.MethodsTwo stem-mapped one-hectare forest plots in the Czech Republic experienced a severe bark beetle outbreak, thus providing before-and-after data on spatial patterns in live and dead trees, crown projections, down logs, and herb cover.ResultsPost-disturbance stands were dominated by an advanced regeneration layer present before the disturbance. Both major species, Norway spruce (Picea abies) and rowan (Sorbus aucuparia), were strongly self-aggregated and also clustered to former canopy trees, pre-disturbance snags, stumps and logs, suggesting positive overstory to understory neighbourhood effects. Thus, although the disturbance dramatically reduced the stand's height profile with ~100% mortality of the canopy layer, the spatial structure of post-disturbance stands still closely reflected the pre-disturbance structure. The former upper tree layer influenced advanced regeneration through microsite and light limitation. Under formerly dense canopies, regeneration density was high but relatively homogeneous in height; while in former small gaps with greater herb cover, regeneration density was lower but with greater heterogeneity in heights.ConclusionThese findings suggest that pre-disturbance spatial patterns of forests can persist through severe canopy-removing disturbance, and determine the spatial structure of the succeeding stand. Such patterns constitute a subtle but key legacy effect, promoting structural complexity in early-seral forests as well as variable successional pathways and rates. This influence suggests a continuity in spatial ecosystem structure that may well persist through multiple forest generations.

Project description:BackgroundForests provide the largest terrestrial sink of carbon (C). However, these C stocks are threatened by forest land conversion. Land use change has global impacts and is a critical component when studying C fluxes, but it is not always fully considered in C accounting despite being a major contributor to emissions. An urgent need exists among decision-makers to identify the likelihood of forest conversion to other land uses and factors affecting C loss. To help address this issue, we conducted our research in California, Colorado, Georgia, New York, Texas, and Wisconsin. The objectives were to (1) model the probability of forest conversion and C stocks dynamics using USDA Forest Service Forest Inventory and Analysis (FIA) data and (2) create wall-to-wall maps showing estimates of the risk of areas to convert from forest to non-forest. We used two modeling approaches: a machine learning algorithm (random forest) and generalized mixed-effects models. Explanatory variables for the models included ecological attributes, topography, census data, forest disturbances, and forest conditions. Model predictions and Landsat spectral information were used to produce wall-to-wall probability maps of forest change using Google Earth Engine.ResultsDuring the study period (2000-2017), 3.4% of the analyzed FIA plots transitioned from forest to mixed or non-forested conditions. Results indicate that the change in land use from forests is more likely with increasing human population and housing growth rates. Furthermore, non-public forests showed a higher probability of forest change compared to public forests. Areas closer to cities and coastal areas showed a higher risk of transition to non-forests. Out of the six states analyzed, Colorado had the highest risk of conversion and the largest amount of aboveground C lost. Natural forest disturbances were not a major predictor of land use change.ConclusionsLand use change is accelerating globally, causing a large increase in C emissions. Our results will help policy-makers prioritize forest management activities and land use planning by providing a quantitative framework that can enhance forest health and productivity. This work will also inform climate change mitigation strategies by understanding the role that land use change plays in C emissions.

Dataset Information

Allocation pattern and accumulation potential of carbon stock in natural spruce forests in northwest China.

Publications

Allocation pattern and accumulation potential of carbon stock in natural spruce forests in northwest China.

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