Relationship between Net Primary Productivity and Forest Stand Age under Different Site Conditions and Its Implications for Regional Carbon Cycle Study

Wang, Bin; Li, Mingze; Wang, Fan; Yu, Ying; Chen, Jing M.

doi:10.3390/f9010005

Cited by 21 publications

(18 citation statements)

References 40 publications

(52 reference statements)

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“…While at the fine scale, similar factors control the macroscopic patterns of biodiversity, the habitat selection by species is controlled primarily by biophysical and climatic factors [40,41]. However, the correlation between these factors and NPP is low because of the similar macroscopic biogeography conditions [42]. Therefore, at present, the interrelationship between vegetation productivity, biodiversity, and regulating ecosystem services is not clear.…”

Section: Discussionmentioning

confidence: 99%

Exploring the Relationships between Key Ecological Indicators to Improve Natural Conservation Planning at Different Scales

Zhang

Ouyang

2019

Forests

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Biodiversity, regulating ecosystem services (RES), and vegetation productivity are key indicators to instruct natural conservation planning. Decision makers often hope that ecosystems can be protected by focusing on certain key indicators, which requires an understanding of the relationships between the indicators. Using individual case studies, many have argued that these indicators commonly have significant relationships. However, these relationships at different spatial scales are unclear. Therefore, in this study, biodiversity and ecosystem services are modelled by the ecological niche model, the universal soil loss equation, and the equation of water balance in two study areas at different scales. The influence of vegetation productivity on the spatial pattern of other ecological indicators in the two areas is examined by a spatial lag model. The contributions of the driving factors on biodiversity distribution at both scales are identified by a boosted regression tree (BRT) model. The results showed that at the fine scale, the spatial correlations were strongest for species richness, especially mammalian species richness, and water retention. However, biodiversity had no significant relationship with vegetation productivity. In contrast, at a coarser scale, the correlation was stronger between plant diversity and regulating ecosystem services. In addition, plant diversity was significantly correlated with vegetation productivity. These differences between scales were controlled by various explanatory variables. At the fine scale, biophysical and climatic factors had the strongest effects on biodiversity distribution, while Net Primary Productivity (NPP) and ecoregion also had relatively high influences on biodiversity at the coarse scale. This demonstrates the critical importance of spatial scale in selecting conservation indicators. We suggest that rare mammalian species richness or flagship mammal species are suitable as conservation surrogates in fine-scale conservation planning. However, at a coarser scale, selecting vegetation patches with more rare plant species and high productivity for each ecoregion is a workable alternative method for conservation planning.

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Section: Discussionmentioning

confidence: 99%

Exploring the Relationships between Key Ecological Indicators to Improve Natural Conservation Planning at Different Scales

Zhang

Ouyang

2019

Forests

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“…The biomass-age relationship has been a widely used method for estimating forest BCS at the national and regional scales [21,24,52,53]. Early studies indicated that the biomass-age relationship could be described using a logistic [24,54], Richards [55,56] or Korf [43] function. It is hard to establish biomass-age relationships using a uniform expression at present.…”

Section: Methodology For Forest Bcs Estimationmentioning

confidence: 99%

“…Fitting the biomass-age relationship Statistical analysis is commonly used to fit the biomass-age relationship. Widely used regression models include Gompertz, Logistic, Korf, Mitscherlich, and Richards growth functions [22,43]. Previous studies have reported that biomass-age relationships greatly change through environmental gradients and among different forest types [21,24].…”

Section: Calculation Of Forest Bcsmentioning

confidence: 99%

Sustained Biomass Carbon Sequestration by China’s Forests from 2010 to 2050

Zhang

Chen

et al. 2018

Forests

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China’s forests have functioned as important carbon sinks. They are expected to have substantial future potential for biomass carbon sequestration (BCS) resulting from afforestation and reforestation. However, previous estimates of forest BCS have included large uncertainties due to the limitations of sample size, multiple data sources, and inconsistent methodologies. This study refined the BCS estimation of China’s forests from 2010 to 2050 using the national forest inventory data (FID) of 2009−2013, as well as the relationships between forest biomass and stand age retrieved from field observations for major forest types in different regions of China. The results showed that biomass–age relationships were well-fitted using field data, with respective R2 values more than 0.70 (p < 0.01) for most forest types, indicating the applicability of these relationships developed for BCS estimation in China. National BCS would increase from 130.90 to 159.94 Tg C year−1 during the period of 2010−2050 because of increases in forest area and biomass carbon density, with a maximum of 230.15 Tg C year−1 around 2030. BCS for young and middle-aged forests would increase by 65.35 and 15.38 Tg C year−1, respectively. 187.8% of this increase would be offset by premature, mature, and overmature forests. During the study period, forest BCS would increase in all but the northern region. The largest contributor to the increment would be the southern region (52.5%), followed by the southwest, northeast, northwest, and east regions. Their BCS would be primarily driven by the area expansion and forest growth of young and middle-aged forests as a result of afforestation and reforestation. In the northern region, BCS reduction would occur mainly in the Inner Mongolia province (6.38 Tg C year−1) and be caused predominantly by a slowdown in the increases of forest area and biomass carbon density for different age–class forests. Our findings are in broader agreement with other studies, which provide valuable references for the validation and parameterization of carbon models and climate-change mitigation policies in China.

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“…The sum of autotrophic respiration and NPP is gross primary productivity (GPP). GPP is a parameter that is not directly measured and also measurement of autotrophic respiration is laborious (Gower et al, 1999;Berberoğlu et al, 2007;Ardö, 2015;Chen et al, 2016;Wang et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Determining the Interactions of Black Pine Net Primary Productivity and Forest Stand Parameters in Northern Turkey

Bulut¹,

Şatır²,

Günlü³

2019

Appl. Ecol. Env. Res.

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Net primary productivity (NPP) is a vital dataset to assess carbon cycling, carbon budget and interpreting global warming. There are many approaches to calculate NPP, and Carnegie-Ames-Stanford approach (CASA) is one of the most popular approaches that was applied in this study. Black pine forest NPP was calculated with the CASA model in a transection zone between humid black sea and dry middle Anatolia region of Turkey for the year of 2016. Model parameters and homogeneity were tested with one-way ANOVA. Results was showed that annual NPP values were varied from 194 to 1213 (g C m -2 year -1 ) for pure black pine stands. Model validation was made with stand increment, growing stock, and stand carbon values. Correlation co-efficiencies were obtained to be 0.92 and 0.85 respectively. It was found that NPP was higher in young stands where the mass accumulation potential was higher than areas, where crown closure was between 11% and 70%. According to this study, young stands should be established in the forests that were operated with the highest NPP objective. NPP models that can be used on a global scale is required intense data and time consuming. In addition, it has been determined that mechanical models which are allowed more practical calculation and can be used with the stand parameters easily.

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Relationship between Net Primary Productivity and Forest Stand Age under Different Site Conditions and Its Implications for Regional Carbon Cycle Study

Cited by 21 publications

References 40 publications

Exploring the Relationships between Key Ecological Indicators to Improve Natural Conservation Planning at Different Scales

Exploring the Relationships between Key Ecological Indicators to Improve Natural Conservation Planning at Different Scales

Sustained Biomass Carbon Sequestration by China’s Forests from 2010 to 2050

Determining the Interactions of Black Pine Net Primary Productivity and Forest Stand Parameters in Northern Turkey

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