Timber production assessment of a plantation forest: An integrated framework with field-based inventory, multi-source remote sensing data and forest management history

Timber production is the purpose for managing plantation forests, and its spatial and quantitative information is critical for advising management strategies. Previous studies have focused on growing stock volume (GSV), which represents the current potential of timber production, yet few studies have investigated historical process-harvested timber. This resulted in a gap in a synthetical ecosystem service assessment of timber production. In this paper, we established a Management Process-based Timber production (MPT) framework to integrate the current GSV and the harvested timber derived from historical logging regimes, trying to synthetically assess timber production for a historical period. In the MPT framework, age-class and current GSV determine the times of historical thinning and the corresponding harvested timber, by using a "space-for-time" substitution. The total timber production can be estimated by the historical harvested timber in each thinning and the current GSV. To test this MPT framework, an empirical study on a larch plantation (LP) with area of 43,946 ha was conducted in North China for a period from 1962 to 2010. Field-based inventory data was integrated with ALOS PALSAR (Advanced Land-Observing Satellite Phased Array L-band Synthetic Aperture Radar) and Landsat-8 OLI (Operational Land Imager) data for estimating the age-class and current GSV of LP. The random forest model with PALSAR backscatter intensity channels and OLI bands as input predictive variables yielded an accuracy of 67.9% with a Kappa coefficient of 0.59 for age-class classification. The regression model using PALSAR data produced a root mean square error (RMSE) of 36.5 m(3) ha(-1). The total timber production of LP was estimated to be 7.27 x 10(6) m(3), with 4.87 x 10(6) m(3) in current GSV and 2.40 x 10(6) m(3) in harvested timber through historical thinning. The historical process-harvested timber accounts to 33.0% of the total timber production, which component has been neglected in the assessments for current status of plantation forests. Synthetically considering the RMSE for predictive GSV and misclassification of age-class, the error in timber production were supposed to range from -55.2 to 56.3 m(3) ha(-1). The MPT framework can be used to assess timber production of other tree species at a larger spatial scale, providing crucial information for a better understanding of forest ecosystem service. (C) 2016 Elsevier B.V. All rights reserved.ArticleINTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION.52:155-165(2016)journal articl

Accuracies of field CO2–H2O data from open-path eddy-covariance flux systems: assessment based on atmospheric physics and biological environment

Ecosystem CO2–H2O data measured by infrared gas analyzers in open-path eddy-covariance (OPEC) systems have numerous applications, such as estimations of CO2 and H2O fluxes in the atmospheric boundary layer. To assess the applicability of the data for these estimations, data uncertainties from analyzer measurements are needed. The uncertainties are sourced from the analyzers in zero drift, gain drift, cross-sensitivity, and precision variability. These four uncertainty sources are individually specified for analyzer performance, but so far no methodology exists yet to combine these individual sources into a composite uncertainty for the specification of an overall accuracy, which is ultimately needed. Using the methodology for closed-path eddy-covariance systems, this overall accuracy for OPEC systems is determined from all individual uncertainties via an accuracy model and further formulated into CO2 and H2O accuracy equations. Based on atmospheric physics and the biological environment, for EC150 infrared CO2–H2O analyzers, these equations are used to evaluate CO2 accuracy (±1.22 mgCO2 m−3, relatively ±0.19 %) and H2O accuracy (±0.10 gH2O m−3, relatively ±0.18 % in saturated air at 35 ∘C and 101.325 kPa). Both accuracies are applied to conceptual models addressing their roles in uncertainty analyses for CO2 and H2O fluxes. For the high-frequency air temperature derived from H2O density along with sonic temperature and atmospheric pressure, the role of H2O accuracy in its uncertainty is similarly addressed. Among the four uncertainty sources, cross-sensitivity and precision variability are minor, although unavoidable, uncertainties, whereas zero drift and gain drift are major uncertainties but are minimizable via corresponding zero and span procedures during field maintenance. The accuracy equations provide rationales to assess and guide the procedures. For the atmospheric background CO2 concentration, CO2 zero and CO2 span procedures can narrow the CO2 accuracy range by 40 %, from ±1.22 to ±0.72 mgCO2 m−3. In hot and humid weather, H2O gain drift potentially adds more to the H2O measurement uncertainty, which requires more attention. If H2O zero and H2O span procedures can be performed practically from 5 to 35 ∘C, the H2O accuracy can be improved by at least 30 %: from ±0.10 to ±0.07 gH2O m−3. Under freezing conditions, the H2O span procedure is impractical but can be neglected because of its trivial contributions to the overall uncertainty. However, the zero procedure for H2O, along with CO2, is imperative as an operational and efficient option under these conditions to minimize H2O measurement uncertainty.</p

Air temperature equation derived from sonic temperature and water vapor mixing ratio for air flow sampled through closed-path eddy-covariance flux systems

Air temperar (T) plays a fundamental role in many aspects of the flux exchanges between the atmosphere and ecosystems. Additionally, it is critical to know where (in relation to other essential measurements) and at what frequency T must be measured to accurately describe such exchanges. In closed-path eddy-covariance (CPEC) flux systems, T can be computed from the sonic temperature (Ts) and water vapor mixing ratio that are measured by the fast-response senosrs of three-dimensional sonic anemometer and infrared gas analyzer, respectively. T then is computed by use of either T = Ts( 1+0.51 q), where q is specific humidity, or T = Ts( 1 + 0.32e∕ P) − 1 , where e is water vapor pressure and P is atmospheric pressure. Converting q and e/P into the same water vapor mixing ratio analytically reveals the difference between these two equations. This difference in a CPEC system could reach ±0.18 K, bringing an uncertainty into the accuracy of T from both equations and raises the question of which equation is better. To clarify the uncertainty and to answer this question, the derivation of T equations in terms of Ts and H2O-related variables is thoroughly studied. The two equations above were developed with approximations. Therefore, neither of their accuracies were evaluated, nor was the question answered. Based on the first principles, this study derives the T equation in terms of Ts and water vapor molar mixing ratio (c H2O) without any assumption and approximation. Thus, this equation itself does not have any error and the accuracy in T from this equation (equation-computed T) depends solely on the measurement accuracies of Ts and c H2O . Based on current specifications for Ts and c H2O in the CPEC300 series and given their maximized measurement uncertainties, the accuracy in equation-computed T is specified within ±1.01 K. This accuracy uncertainty is propagated mainly (±1.00K) from the uncertainty in Ts measurements and little (±0.03K) from the uncertainty in c H2O measurements. Apparently, the improvement on measurement technologies particularly for Ts would be a key to narrow this accuracy range. Under normal sensor and weather conditions, the specified accuracy is overestimated and actual accuracy is better. Equation-computed T has frequency response equivalent to high-frequency Ts and is insensitive to solar contamination during measurements. As synchronized at a temporal scale of measurement frequency and matched at a spatial scale of measurement volume with all aerodynamic and thermodynamic variables, this T has its advanced merits in boundary-layer meteorology and applied meteorology

Based on Atmospheric Physics and Ecological Principle to Assess the Accuracies of Field CO2 /H2O Measurements From Infrared Gas Analyzers in Closed-Path Eddy-Covariance Systems

Field CO2 /H2O measurements from infrared gas analyzers in closed-path eddy-covariance systems have wide applications in earth sciences. Knowledge about exactness of these measurements is required to assess measurement applicability. Although the analyzers are specified with uncertainty components (zero drift, gain drift, cross-sensitivities, and precision), exactness for individual measurements is unavailable due to an absence of methodology to comprehend the components as an overall uncertainty. Adopting an advanced definition of accuracy as a range of all measurement uncertainty sources, the specified components are composited into a model formulated for studying analyzers’ CO2 /H2O accuracy equations. Based on atmospheric physics and environmental parameters, the analyzers are evaluated using the equations for CO2 accuracy (±0.78 µmolCO2 mol−1, relatively ±0.18%) and H2O accuracy (±0.15 mmolH2 O mol−1). Evaluation shows that precision and cross-sensitivity are minor uncertainties while zero and gain drifts are major uncertainties. Both drifts need adjusting through zero/span procedures during field maintenance. The equations provide rationales to guide and assess the procedures. H2O span needs more attentions under humid conditions. Under freezing conditions while H2O span is impractical, this span is fortunately unnecessary. Under the same conditions, H2O zero drift dominates H2O measurement uncertainty. Therefore, automatic zero becomes a more applicable and necessary tactic. In general cases of atmospheric CO2 background, automatic CO2 zero/ span procedures can narrow CO2 accuracy by 36% (±0.74 to ± 0.47 µmolCO2 mol−1). Automatic/manual H2 O zero/span procedures can narrow H2O accuracy by 27% (±0.15 to ±0.11 mmolH2O mol−1). While ensuring system specifications, the procedures guided by equations improve measurement accuracies

Spatial and temporal regeneration patterns within gaps in the primary forests vs. secondary forests of Northeast China

Forest gaps play an important role during forest succession in temperate forest ecosystems. However, the differences in spatial distribution and replacement patterns of woody plants (trees and shrubs) between primary and secondary forests remain unclear during the gap-filling processes, especially for temperate forests in Northeast China. We recorded 45,619 regenerated trees and shrubs in young gaps (&lt;10 years), old gaps (10~20 years), and closed forest stands (i.e., filled gaps) in the primary broadleaved Korean pine (Pinus koraiensis Sieb. Rt Zucc.) forests vs. secondary forests (degraded from primary forests). The gap-filling processes along horizontal (Cartesian coordinate system) and vertical (lower layer: 0~5 m, medium layer: 5~10 m, and upper layer: &gt;10 m) dimensions were quantified by shade tolerance groups of trees and shrubs. We found that gap age, competition between species, and pre-existing regeneration status resulted in different species replacement patterns within gaps in primary vs. secondary forests. Gap formation in both primary and secondary forests increased species richness, with 33, 38, 39, and 41 in the primary closed stands, primary forest gaps, secondary closed stands, and secondary forest gaps, respectively. However, only 35.9% of species in primary forest gaps and 34.1% in secondary forest gaps successfully reached the upper layer. Based on the importance values (IVs) of tree species across different canopy heights, light-demanding trees in the upper layer of the secondary forests were gradually replaced by intermediate and shade-tolerant trees. In the primary forests, Korean pine exhibited intermittent growth patterns at different canopy heights, while it had continuous regeneration along vertical height gradients in the secondary forests. The differences in Korean pine regeneration between the primary and secondary forests existed before gap formation and continued during the gap-filling processes. The interspecific competition among different tree species gradually decreased with increasing vertical height, and compared to the primary forests, the secondary forests showed an earlier occurrence of competition exclusion within gaps. Our findings revealed the species replacement patterns within gaps and provided a further understanding of the competition dynamics among tree species during the gap-filling processes

Size-Dependent Patterns of Seed Rain in Gaps in Temperate Secondary Forests, Northeast China

Secondary forests have become the major forest type worldwide, and are experiencing various disturbances and exhibiting obvious vegetation degradation (e.g., reduced biodiversity and decreased productivity) compared with primary forests. Forest gap is a common small-scale disturbance in secondary forests. Promoting natural regeneration under gap disturbance is an important approach to recover biodiversity and ecosystem services for temperate secondary forests. The gap size is the crucial characteristic controlling natural regeneration of many tree species. However, little is known about the spatiotemporal pattern of seed rain for gravity-dispersed and wind-dispersed tree species in gaps of varying sizes. The objectives of this study were to determine how seed rain of dominant tree species depend on gap size, and consequently, to explore some gap-based silviculture solutions for restoring secondary forests from the view of seed dispersal. The spatial distribution of seed rain in gaps with three sizes (large gaps of 250&#8315;350 m2, medium gaps of 150&#8315;250 m2, and small gaps of &lt;150 m2), the temporal dynamics of seed rain over three years, and the relationship between seed rain and soil seed banks were explored in temperate secondary forests. The results showed that more than 90% of the seeds in seed rain were wind-dispersed, and their seed rain density and the contribution of seed rain to soil seed bank in medium gaps reached the highest (p = 0.03). The results suggest that establishing medium-sized gaps (i.e., gap size with 150&#8315;250 m2) in the secondary forests is more favorable for improving the natural regeneration potential (arrival of seeds and forming soil seed bank) of gap-dependent and wind-dispersed species (e.g., Acer mono) in gaps

Changes in soil phosphorus fractions after 9 years of continuous nitrogen addition in a Larix gmelinii plantation

International audienceThe key message N addition decreased soil inorganic P availability, microbial biomass P, and acid phosphatase activity in the larch plantation. Soil inorganic P availability decreased after N addition due to the changes in both microbial properties and plant uptake.• Context Soil phosphorus (P) availability is considered an important factor in influencing the biomass production of plants. Sustained inputs of nitrogen (N) through atmospheric deposition or N fertilizers, particularly in temperate forests, may change the composition and availability of P and thus affect long-term forest productivity.• Aims The objective of this study was to assess soil P availability, P fractions, and microbial properties including microbial biomass P and acid phosphatase activity after 9 consecutive years of N addition in a larch (Larix gmelinii) plantation, northeastern China.• Methods From 2003 to 2011, NH4NO3 was added to replicate plots (three 20 m × 30 m plots) in the larch plantation each year at a rate of 100 kg N ha−1 year−1. Soil samples from 0–10-cm and 10–20-cm depths were collected in N addition plots and control (no N addition) plots.• Results N addition significantly decreased soil NaHCO3-Pi (Pi is inorganic P), microbial biomass P, and acid phosphatase activity but increased the NaOH-Pi concentration. N addition appeared to induce a decrease in soil inorganic P availability by changing pH and P uptake by trees. In addition, N addition significantly decreased the NaOH-Po (Po is organic P) concentration, possibly because of increased P mineralization. However, the total P and other P fractions were unaffected by N fertilization.• Conclusion Our results suggested that N addition enhanced P uptake by trees, whereas it reduced soil inorganic P availability as well as microbial biomass and activity related to soil P cycling in the larch plantation

Impacts of the world’s largest afforestation program (Three-North Afforestation Program) on desertification control in sandy land of China

In order to control the desertification, large-scale afforestation programs have been attempted worldwide. Among them, China initiated the world’s largest afforestation program, Three-North Afforestation Program (TNAP, 1978–2050), in which the afforestation in sandy land has been questioned during the first 40 years. In fact, the contribution of the TNAP to vegetation establishment and its effectiveness in desertification control still remain unclear, which limited the further construction of the program. To answer the questions, we detected the dynamics of vegetation distribution (forest, shrubland, and grassland) and desertification status (slight, moderate, severe, and extremely severe) during 1978–2017 in the sandy land (45.5 million ha), by visual interpretation of 5-period remote sensing images with validation based on 3,100 sample plots from field surveys and 15,175 sample plots from the National Forest Resource Inventory. Vegetation degradation was identified by analysis combining the trends of net primary productivity and precipitation use efficiency. By Geographical Detector model, the driving forces of vegetation degradation (climate change, human activities, vegetation type, and sandy land type) were ranked and the contributions of the influential factors (climate change, human activities, and vegetation dynamics) to desertification changes were estimated. The results showed that for the 40 years, vegetation coverage increased by 0.5%, with increasing 113.8% and 338.8% of forest and shrubland, but decreasing 9.0% of grassland. Desertification area had little change while the overall intensity decreased. The TNAP contributed to desertification dynamics by 10.3%, which is lower than expected. Vegetation type was the dominant factor of vegetation degradation in general. Forest is less suitable for afforestation in sandy land than shrubland and grassland because of its lower stand establishment rate, higher degradation rate, and less contribution to desertification control. Thus, adjusting vegetation type to match local conditions (e.g., use shrub-land, grassland, and native species) and improving the vegetation resistance (e.g., transform monoculture forests into mixed forests, and make proper proportion for forest, shrubland, and grassland) was suggested. Our study provided specific and feasible strategies for further planning and implementation of TNAP, and references for vegetation restoration of sandy lands worldwide

Mapping Spatial Distribution of Larch Plantations from Multi-Seasonal Landsat-8 OLI Imagery and Multi-Scale Textures Using Random Forests

The knowledge about spatial distribution of plantation forests is critical for forest management, monitoring programs and functional assessment. This study demonstrates the potential of multi-seasonal (spring, summer, autumn and winter) Landsat-8 Operational Land Imager imageries with random forests (RF) modeling to map larch plantations (LP) in a typical plantation forest landscape in North China. The spectral bands and two types of textures were applied for creating 675 input variables of RF. An accuracy of 92.7% for LP, with a Kappa coefficient of 0.834, was attained using the RF model. A RF-based importance assessment reveals that the spectral bands and bivariate textural features calculated by pseudo-cross variogram (PC) strongly promoted forest class-separability, whereas the univariate textural features influenced weakly. A feature selection strategy eliminated 93% of variables, and then a subset of the 47 most essential variables was generated. In this subset, PC texture derived from summer and winter appeared the most frequently, suggesting that this variability in growing peak season and non-growing season can effectively enhance forest class-separability. A RF classifier applied to the subset led to 91.9% accuracy for LP, with a Kappa coefficient of 0.829. This study provides an insight into approaches for discriminating plantation forests with phenological behaviors