Ecosystem service multifunctionality of mixed conifer-broad-leaved forests under climate change and forest management based on matrix growth modelling

Climate change and forest management are recognized as pivotal factors influencing forest ecosystem services and thus multifunctionality.However,the magnitude and the relative importance of climate change and forest management effects on the multifunctionality remain unclear,especially for natural mixed forests.In this study,our objective is to address this gap by utilizing simulations of climate-sensitive transition matrix growth models based on national forest inventory plot data.We evaluated the effects of seven management scenarios(combinations of various cutting methods and intensities)on the future provision of ecosystem services and multifunctionality in mixed conifer-broad-leaved forests in northeastern China,under four climate scenarios(SSP1-2.6,SSP2-4.5,SSP5-8.5,and constant climate).Provisioning,regulating,cultural,and supporting services were described by timber production,carbon storage,carbon sequestration,tree species diversity,deadwood volume,and the number of large living trees.Our findings indicated that timber production was significantly influenced by management scenarios,while tree species diversity,deadwood volume,and large living trees were impacted by both climate and management separately.Carbon storage and sequestration were notably influenced by both management and the interaction of climate and management.These findings emphasized the profound impact of forest management on ecosystem services,outweighing that of climate scenarios alone.We found no single management scenario maximized all six ecosystem service indicators.The upper story thinning by 5%intensity with 5-year interval(UST5)management strategy emerged with the highest multifunctionality,surpassing the lowest values by more than 20%across all climate scenarios.In conclusion,our results underlined the potential of climate-sensitive transition matrix growth models as a decision support tool and provided recommendations for long-term strategies for multifunctional forest management under future climate change context.Ecosystem services and multifunctionality of forests could be enhanced by implementing appropriate management measures amidst a changing climate.

Studies on crop growth modelling and simulation models in China

There is a close relationship between agricultural production and environmental meteorological conditions. In the study of the correlation between them, the simulation models are paid more attention to the crop growth. In this paper the development of the studies on the crop growth dynamic simulation model in China is briefly reviewed. The relationships between meteorological conditions and each process of crop growth (such as photosynthesis, respiration, accumulation and distribution of assimilation products and growth of leaf area) are studied and simulated basing on the results from field experiments. Preliminary models for rice, wheat, maize and soybean have been developed, and some investigations about modelling methods, procedures and parameters in simulation models are made.

Modelling the response of larch growth to age,density,and elevation and the implications for multifunctional management in northwest China

Plantations of Rupprecht's larch(Larix principis-rupprechtii)have been widely established in the drylands of northwest and north China under traditional fastgrowing plantation management strategies.These strategies and the long-term logging ban have led to over-populated stands with lower structural and functional stability,less economic benefit and higher water consumption.To guide the sustainable management of larch plantations,field surveys and historical data compilation were undertaken in the Liupan Mountains of northwest China.The main influencing factors(stand structure and site condition)and their effects on mean tree height,mean DBH and timber volumes were determined based on up-boundary line analysis.Tree growth models coupling the effects of tree age,stand density,and elevation were established.Both height and DBH markedly increased initially and then slowly with tree age,decreased with stand density,and showed unimodal change with elevation.The coupled growth models accounted for72-78%of the variations in tree height,DBH and timber growth.Recommendations for future plantation management are:(1)prolong the rotation to at least 60 years to produce large-diameter,high-quality timber and maintain greater carbon stocks;(2)zone the target functions of stands by elevation;and,(3)reduce stand density for balanced supply of multiple ecosystem services.The growth models developed can predict growth response of larch plantations to density alteration under given ages and elevations,and assist the transformation from traditional management for maximum timber production to site-specific and multifunctional management with longer rotations and moderate tree density.

Extensive numerical simulations on competitive growth between the Edwards–Wilkinson and Kardar–Parisi–Zhang universality classes

Extensive numerical simulations and scaling analysis are performed to investigate competitive growth between the linear and nonlinear stochastic dynamic growth systems, which belong to the Edwards–Wilkinson(EW) and Kardar–Parisi–Zhang(KPZ) universality classes, respectively. The linear growth systems include the EW equation and the model of random deposition with surface relaxation(RDSR), the nonlinear growth systems involve the KPZ equation and typical discrete models including ballistic deposition(BD), etching, and restricted solid on solid(RSOS). The scaling exponents are obtained in both the(1 + 1)-and(2 + 1)-dimensional competitive growth with the nonlinear growth probability p and the linear proportion 1-p. Our results show that, when p changes from 0 to 1, there exist non-trivial crossover effects from EW to KPZ universality classes based on different competitive growth rules. Furthermore, the growth rate and the porosity are also estimated within various linear and nonlinear growths of cooperation and competition.

Control of GaN inverted pyramids growth on c-plane patterned sapphire substrates

Growth of gallium nitride(GaN)inverted pyramids on c-plane sapphire substrates is benefit for fabricating novel devices as it forms the semipolar facets.In this work,GaN inverted pyramids are directly grown on c-plane patterned sapphire substrates(PSS)by metal organic vapor phase epitaxy(MOVPE).The influences of growth conditions on the surface morphol-ogy are experimentally studied and explained by Wulff constructions.The competition of growth rate among{0001},{1011},and{1122}facets results in the various surface morphologies of GaN.A higher growth temperature of 985 ℃ and a lowerⅤ/Ⅲratio of 25 can expand the area of{}facets in GaN inverted pyramids.On the other hand,GaN inverted pyramids with almost pure{}facets are obtained by using a lower growth temperature of 930℃,a higherⅤ/Ⅲratio of 100,and PSS with pattern arrangement perpendicular to the substrate primary flat.

The Impact of the Digital Economy on Financial Regulatory Costs: An Empirical Analysis Based on the Solow Growth Model

As a novel economic form,the digital economy is reshaping the financial regulatory landscape and significantly impacting regulatory costs.This paper incorporates the digital economy and financial regulatory costs into the classic Solow growth model,uncovering an inverted U-shaped relationship between them.A subsequent mechanism analysis explains the rationale behind this relationship.To empirically examine this relationship in China,the paper utilizes inter-provincial panel data from 2013 to 2021 and employs methodologies such as the two-way fixed effects and moderating effects models.These analyses have important implications for the sound and sustainable development of China’s financial industry.The findings indicate:(a)As China’s digital economy develops,its impact on financial regulatory costs follows an inverted U-shaped pattern,initially increasing and then declining.This conclusion remains valid after robustness tests.(b)The influence of the digital economy on regulatory costs depends on favorable external conditions.Specifically,the impact is more pronounced in regions and periods with better digital infrastructure and more abundant human capital.(c)Additionally,redundant resources moderate this impact,which can weaken the inverted U-shaped relationship.Our findings not only provide a theoretical foundation for understanding the impact of the digital economy on financial regulatory costs but also offer valuable policy insights for optimizing financial regulation in China.

Comparison of stand structure and growth between artificial and natural forests of Pinus sylvestiris var. mongolica on sandy land

Mongolian pine (Pinus sylvestiris Linnaeus var. mongolica Litvinov) as a valuable conifer tree species has been broadly introduced to the sandy land areas in 揟hree North?regions (North, northwest and northeast of China), but many problems occurred in the earliest Mongolian pine plantations in Zhanggutai, Zhangwu County, Liaoning Province (ZZL). In order to clarify the reason, comprehensive investigations were carried out on differences in structure characteristics, growth processes and ecological factors between artificial stands (the first plantation established in ZZL in 1950s) and natural stands (the origin forests of the tree species in Honghuaerji, Inner Mongolia) on sandy land. The results showed that variation of diameter-class distributions in artificial stands and natural stands could be described by Weibull and Normal distribution models, respectively. Chapman-Richards growth model was employed to reconstruct the growth process of Mongolian pine based on the data from field investigation and stem analysis. The ages of maximum of relative growth rate and average growth rate of DBH, height, and volume of planted trees were 11, 22 years, 8, 15 years and 35, 59 years earlier than those of natural stand trees, respectively. In respect of the incremental acceleration of volume, the artificial and natural stands reached their maximum values at 14 years and 33 years respectively. The quantitative maturity ages of artificial stands and natural stands were 43 years and 102 years respectively. It was concluded that the life span of the Mongolian pine trees in natural stands was about 60 years longer than those in artificial stands. The differences mentioned above between artificial and natural Mongolian pine forests on sandy land were partially attributed to the drastic variations of ecological conditions such as latitude, temperature, precipitation, evaporation and height above sea level. Human beings' disturbances and higher density in plantation forest may be ascribed as additional reasons. Those results may be potentially useful for the management and afforestation of Mongolian pine plantations on sandy land in arid and semi-arid areas.

SAR Data Assimilation for Crop Biomass Simulation Based on Crop Growth Model

Biomass from SAR data was assimilated into crop growth model to describe relationship between crop biomass and crop growth time to improve estimation accuracy of biomass. In addition, inverse model was established in order to estimate biomass according to relationship between biomass and backscattering coefficients from SAR data. Based on cost function, parameters of growth model were optimized as per conjugate gradient method, minimizing the differences between estimated biomass and inversion values from SAR data. The results indicated that the simulated biomass using the revised growth model with SAR data was consistent with the measured one in time distribution and even higher in accuracy than that without SAR data. Hence, the key parameters of crop growth model could be revised by real-time growth information from SAR data and accuracy of the simulated biomass could be improved accordingly.

Evaluation of unconstrained and constrained mathematical functions to model girth growth of rubber trees (Hevea brasiliensis) using young agemeasurements

No attempt has been made to date to model growth in girth of rubber tree （Hevea brasiliansis）. We evaluated the few widely used growth functions to identify the most parsimonious and biologically reasonable model for describing the girth growth of young rubber trees based on an incomplete set of young age measurements. Monthly data for girth of immature trees （age 2 to 12 yearsi from two locations were sub- jected to modelling. Re-parameterized, unconstrained and constrained growth functions,of Richards （RM）, Gompertz （GM） and the monomo- lecular ＇model ^（MM） were fitted to data. Duration of growth was the firsf constraint introduced. In the stagel We attempted a population aver- age （PA） model to capture the trend in growth. The best PA model was fitted as a subject specific （SS） model. We used appropriate error vari- ance-covariance structure to account for correlation due to repeated measurements over time. Unconstrainecl functions underestimated the asymptotic maximum that did not reflective carrying capacity of the locations. Underestimafions were attributed to the partial set＇ of meas- urements made during the early growth phase of the trees. MM proved superior to RM and GM. In the randomcoefficient models, both Gf and Go appeared to be influenced by tree level effects. Inclusion of diagonal definite positive matrix removed the correlation between random effects. The results were similar at both locations. In the overall assessment MM appeared as the candidate model for studying the girth-age relationships in Hevea trees. Based on the fitted model we conclude that, in Hevea trees, growth rate is maintained at maximum value at to, then decreases until the final state at dG/dt 〉 0, resulting in yield curve with no period of accelerating growth. One physiological explanation is that photosynthetic activity in Hevea trees decreases as girth increases and constructive metabolism is larger than destructive metabolism.

The generalized Chapman-Richards function and applications to tree and stand growth

The generalized Chapman-Richards model was derived from the Chapman-Richards function in which parameters h, k and m were unconstrained. Based on the structure of solutions and biological interpretations, the model could be classified into eight cases (three categories) at all and among them only 4 kinds of cases are suitable in forestry that represent four typical growth patterns of trees and stands. For each of 4 equations, the model properties and biological interpretations for parameters were discussed in detail. The generalized Chapman-Richards model was capable of describing a wide range of growth curves that was asymptotic or nonasymptotic, with or without inflection point. In order to illustrate the versatility of the model, it was fitted to a group of data sets concerning the DBH growth of cryptomeria plantations with 4 initial densities and the DBH and height growth of natural Korean pine tree. Comparing the generalized Chapman-Richards function and the Schnute model, it was found that the parameters and expressions of the two models were interchangeable in theory, and the fitting results were explicitly identical in empirical applications.

Rice Yield Estimation by Integrating Remote Sensing with Rice Growth Simulation Model

Since remote sensing can provide information on the actual status of an agricultural crop, the integration between remote sensing data and crop growth simulation models has become an important trend for yield estimation and prediction.The main objective of this research was to combine a rice growth simulation model with remote sensing data to estimate rice grain yield for different growing seasons leading to an assessment of rice yield at regional levels. Integration between NOAA (National Oceanic and Atmospheric Administration) AVHRR (Advanced Very High Resolution Radiometer) data and the rice growth simulation model ORYZA1 to develop a new software, which was named as Rice-SRS Model, resulted in accurate estimates for rice yield in Shaoxing, China, with an estimation error reduced to 1.03% and 0.79% over-estimation and 0.79% under-estimation for early, single and late season rice, respectively. Selecting suitable dates for remote sensing images was an important factor which could influence estimation accuracy. Thus, given the different growing periods for each rice season, four images were needed for early and late rice, while five images were preferable for single season rice.Estimating rice yield using two or three images was possible, however, if images were obtained during the panicle initiation and heading stages.

Characterization of grain growth behaviors by BP-ANN and Sellars models for nickle-base superalloy and their comparisons

In order to deeply understand the grain growth behaviors of Ni80A superalloy,a series of grain growth experiments were conducted at holding temperatures ranging from 1223 to 1423 K and holding time ranging from 0 to 3600 s.A back-propagation artificial neural network(BP-ANN)model and a Sellars model were solved based on the experimental data.The prediction and generalization capabilities of these two models were evaluated and compared on the basis of four statistical indicators.The results show that the solved BP-ANN model has better performance as it has higher correlation coefficient(r),lower average absolute relative error(AARE),lower absolute values of mean value(μ)and standard deviation(ω).Eventually,a response surface of average grain size to holding temperature and holding time is constructed based on the data expanded by the solved BP-ANN model,and the grain growth behaviors are described.

Comparison of six statistical approaches in the selection of appropriate fish growth models

The performance of six statistical approaches,which can be used for selection of the best model to describe the growth of individual fish,was analyzed using simulated and real length-at-age data.The six approaches include coefficient of determination(R2),adjusted coefficient of determination(adj.-R2),root mean squared error(RMSE),Akaike's information criterion(AIC),bias correction of AIC(AICc) and Bayesian information criterion(BIC).The simulation data were generated by five growth models with different numbers of parameters.Four sets of real data were taken from the literature.The parameters in each of the five growth models were estimated using the maximum likelihood method under the assumption of the additive error structure for the data.The best supported model by the data was identified using each of the six approaches.The results show that R2 and RMSE have the same properties and perform worst.The sample size has an effect on the performance of adj.-R2,AIC,AICc and BIC.Adj.-R2 does better in small samples than in large samples.AIC is not suitable to use in small samples and tends to select more complex model when the sample size becomes large.AICc and BIC have best performance in small and large sample cases,respectively.Use of AICc or BIC is recommended for selection of fish growth model according to the size of the length-at-age data.

A derivation of the generalized Korf growth equation and its application

Based on the biological hypothesis of tree growth, the generalized Korf growth equation, was derived theoretically. From a standpoint of applications, the equation can be used in two ways associated with the power exponent ofp, and two types of growth equations: the Korf-A (p>1) and the Korf-B (O<p<1) were developed and between them, there is the Gompertz equation (p=1) to separate each other. All of the three types of equations are independent. It was concluded that the Korf-A equation could be used to describe the growth of trees, of which inflection point is between 0 andA/e, while the Korf-B equation with the inflection point betweenA/e andA could be applied to describe the biological population growth. It was found that the Korf-A equation had a better property in describing the growth process of a tree or a stand and its applications to predicting height growth and stand self-thinning showed general good fitness.

Individual-tree diameter growth model for Korean pine plantations based on optimized interpolation of meteorological variables

To explore the influence of meteorological variables on the growth of Korean pine(Pinus koraiensis Sieb.et Zucc.) plantations and provide a scientific reference for the production and management of Korean pine,three approaches to interpolate meteorological variables during the growing season(i.e.,May-September) were compared in Heilongjiang Province,China.Optimized meteorological variable interpolation results were then combined with stand and individual tree variables,based on data from 56 sample plots and 2886 sample trees from Korean pine plantations in two regions of the province to develop an individualtree diameter growth model(Model I) and an individualtree diameter growth model with meteorological variables(Model Ⅱ) using a stepwise regression method.Moreover,an individual-tree diameter growth model with regional effects(Model Ⅲ) was developed using dummy variables in the regression,and the significance of introducing these dummy variables was verified with an F-test statistical analysis.The models were validated using an independent data set,and the predictive performance of the three models was assessed via the adjusted coefficient of determination(R_(a)^(2)) and root mean square error(RMSE).The results suggest that the growth increment in tree diameter of Korean pine plantations was significantly correlated with the natural logarithm of initial diameter(ln D),stand basal area(BAS),logarithmic deformation of the stand density index(ln SDI),ratio of basal area of trees larger than the subject tree to their initial diameter at breast height(DBH)(BAL/D),and the maximum growingseason precipitation(Pgmax).The individual-tree diameter growth models of Korean pine plantations developed in this study will provide a good basis for estimating and predicting growth increments of Korean pine forests over larger areas.

Growth model of cavity generated by the projectile impacting liquid-filled tank

The high-speed impact of a projectile on a liquid-filled tank causes the hydraulic ram,in which a cavity is formed.To study the growth characteristics of the cavity,the formation mechanism of the cavity is analyzed.The effect of Reynolds number and Mach number on drag coefficient is considered,the axial and radial growth models of the cavity are established respectively.The relative errors between the cavity length calculated by the axial growth model,the cavity diameter calculated by the radial growth model and Ma L.Y.test results are less than 20%,which verifies the effectiveness of the axial and radial growth models.Finally,numerical simulation is carried out to study the growth characteristics of the cavity caused by the projectile impacting the satellite tank at the velocity of 4000 m/s.The cavity length and diameter calculated by the axial and radial growth models agree well with those obtained by simulation results,indicating that the cavity length and diameter in satellite tank can be accurately calculated by the axial and radial growth models.

Discrete Software Reliability Growth Modeling for Errors of Different Severity Incorporating Change-point Concept

Several software reliability growth models （SRGM） have been developed to monitor the reliability growth during the testing phase of software development. In most of the existing research available in the literatures, it is considered that a similar testing effort is required on each debugging effort. However, in practice, different types of faults may require different amounts of testing efforts for their detection and removal. Consequently, faults are classified into three categories on the basis of severity： simple, hard and complex. This categorization may be extended to r type of faults on the basis of severity. Although some existing research in the literatures has incorporated this concept that fault removal rate （FRR） is different for different types of faults, they assume that the FRR remains constant during the overall testing period. On the contrary, it has been observed that as testing progresses, FRR changes due to changing testing strategy, skill, environment and personnel resources. In this paper, a general discrete SRGM is proposed for errors of different severity in software systems using the change-point concept. Then, the models are formulated for two particular environments. The models were validated on two real-life data sets. The results show better fit and wider applicability of the proposed models as to different types of failure datasets.

Effect of growth rate on microstructure and solute distribution of Al-Zn-Mg alloy

An Al-5.3%Zn-5.3%Mg alloy was unidirectionally solidified to determine morphological transition and solute distribution by a modification of the Bridgman technique for crystal growth with growth rates ranging from 4-500 μm/s and a temperature gradient of 25 K/cm. It was determined that growth rates from 6.5-9.5 μm/s generated a cell morphology, where the lower limit corresponds to the plane front to cellular transition and the upper limit indicates the cellular to columnar dendrite transition. The microstructures of the alloys solidified from 30 μm/s to growth rates less than 500 μm/s were mainly composed of columnar dendrites, while the microstructures solidified at growth rates greater than 500 μm/s were equiaxed. Regarding experimental results on solute distribution, a prediction of the model developed by Rappaz and Boettinger for dendrite solidification of multicomponent alloys was applied with excellent agreement. Results of solute distribution were employed to derive the precipitation fraction of τ-phase needed to increase the electrochemical properties of the alloy to be used as an Al-sacrificial anode.

Effects of Lvy noise and immune delay on the extinction behavior in a tumor growth model

The combined effects of Ltvy noise and immune delay on the extinction behavior in a tumor growth model are explored, The extinction probability of tumor with certain density is measured by exit probability. The expression of the exit probability is obtained using the Taylor expansion and the infinitesimal generator theory. Based on numerical calculations, it is found that the immune delay facilitates tumor extinction when the stability index α〈 1, but inhibits tumor extinction when the stability index α 〉 1. Moreover, larger stability index and smaller noise intensity are in favor of the extinction for tumor with low density. While for tumor with high density, the stability index and the noise intensity should be reduced to promote tumor extinction.

A Knowledge Model-and Growth Model-Based Decision Support System for Wheat Management

By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and management indices to variety types, ecological environments and production levels were analysed and extracted, and a dynamic knowledge model with temporal and spatial characters for wheat management(WheatKnow)was developed. By adopting the soft component characteristics as non language relevance , re-utilization and portable system maintenance. and by further integrating the wheat growth simulation model(WheatGrow)and intelligent system for wheat management, a comprehensive and digital knowledge model, growth model and component-based decision support system for wheat management(MBDSSWM)was established on the platforms of Visual C++ and Visual Basic. The MBDSSWM realized the effective integration and coupling of the prediction and decision-making functions for digital crop management.