Research of Future Directions and Considerations for Implementation of the Forest City Strategy

A “Forest City” (FC) is an urban area that has a significant amount of forest cover. It is now a green urban development strategy that is supported by numerous nations. This essay compares the many FC implementation strategies used in developed and developing countries and explores potential future paths for this tactic. The variations between FC in terms of measurement targets, air purification, street trees, and forestry development are thoroughly compared in this research. This essay goes on to explore FC’s potential in the future regarding policy changes and the environment based on this comparison. Therefore, this essay focuses on the necessity of considering industrial innovation, encouraging biodiversity, lowering greenhouse gas emissions, paying attention to forest restructuring, and being more responsive to the issues provided by urbanization in the future global implementation of FC.

The Regional Climate Effects of Replacing Farmland and Re-greening the Desertification Lands with Forest or Grass in West China

The West Development Policy being implemented in China causes significant land use and land cover (LULC) changes in West China, of which the two most important types of LULC change are replacing farmland and re-greening the desertification land with forest or grass. This paper modifies the prevailing regional climate model (RCM) by updating its lower boundary conditions with the up-to-date satellite database of the Global Land Cover Characteristics Database (GLCCD) created by the United States Geological Survey and the University of Nebraska-Lincoln. The modified RCM is used to simulate the possible regional climate changes due to the LULC variations. The preliminary results can be summarized as that the two main types of LULC variation, replacing farmland and greening the desertification lands with forest or grass in west China, will affect the regional climate mostly in northwest and north China, where the surface temperature will decrease and the precipitation will increase. The regional climate adjustments in South, Southwest China and on the Tibet Plateau are uncertain.

Assessing the influence of the minimum measured diameter on forest spatial patterns and nearest neighborhood relationships

Forest structure analysis is important for understanding the properties and development of a forest community,and its outcomes can be influenced by how trees are measured in sampled plots.Although there is a general consensus on the height at which tree diameter should be measured[1.3 m:diameter at breast height(DBH)],the minimum measureddiameter(MMD)often varies in different studies.In this study,we assumed that the outcomes of forest structure analysis can be influenced by MMD and,to this end,we applied g(r)function and stand spatial structural parameters(SSSPs)to investigate how different MMDs affect forest spatial structure analysis in two pine-oak mixed forests(30 and 57 years old)in southwest China and one old-growth oak forest(>120years old)from northwest China.Our results showed that 1)MMD was closely related to the distribution patterns of forest trees.Tree distribution patterns at each observational scale(r=0-20 m)tended tobecome random as the MMD increased.The older the community,the earlier this random distribution pattern appeared.2)As the MMD increased,neighboring trees became more regularly distributed around a reference tree.In most cases,however,nearest neighbors of a reference tree were randomly distributed.3)Tree species mingling decreased with increasing diameter,but it decreased slowly in older forests.4)No correlations can be found between individual tree size differentiation and MMD.We recommend that comparisons of spatial structures between communities would be more effective if using a unified MMD criterion.

Importance of Comprehensive Ecological Restoration of Mountains,Rivers,Forests,Farmland,Lakes and Grass:A Case Study of the Shichuan River

With China's economic development and population growth,China's ecological environment continues to deteriorate.The comprehensive ecosystem restoration of the Shichuan River aims to build an ecosystem containing"mountains,rivers,forests,farmland,lakes and grass"by determining scientific and reasonable thickness of foreign soil,pollution restoration,ecological reconstruction,safeguard measures,etc.It brings new vitality to local ecological environment remodeling and economic development.

Construction of Forest and Grass Industry Economic Belt Using Land Resources in Road Side Slope

The construction of expressway and high-speed rail is at the sacrifice of the soil ecological environment. It brings about much damaged land and bare slope. It is necessary to restore vegetation and rebuild landscape. In the design of target plant community and configuration plants,it is required to select as far as possible plants that can blossom and bear fruit or pods. Then seeds of these plants can be harvested,processed and sold,and applied for other projects,so as to develop into a complete forest and grass seed industry chain. This not only reasonably utilizes land resources,but also provides a new approach to the problem of insufficient fine forest seed sources in China. This paper discussed the use of land resources in road side slope and forest and grass seed selection and breeding technology,and elaborated the industrialized development paths for forest and grass seed industries in road side slope. Finally,it arrived at following recommendations.( i) The construction of forest and grass industry economic belt using land resources in road side slope can realize maximum land value. Building a road can help people there get rich,and the type of land and water cultivates its type of forest and grass.( ii) It can make up for the losses incurred from construction of expressway and high-speed rail or destroying forest land,and it can increase farmers' income.( iii) It can increase the supply of domestic seeds,reduce seed import,save foreign exchange,and partly solve the problem of insufficient supply of forest and grass seeds.( iv) It is able to form a complete forest and grass seed industry economic cycle chain,increase employment,and provide new approaches for enriching and benefiting farmers.

Decreasing the error in the measurement of the ecosystem effective leaf area index of a Pinus massoniana forest

Decreasing the forest ecosystem leaf-area index error(LAIe)helps accurately estimate the growth and light energy utilization of aboveground foliage.Analyzing light transmission in forest ecosystems can effectively determine LAIe.The LAI-2200 plant canopy analyzer(PCA)is used extensively for rapid field-effective LAI(LAIe)measurements and primarily to measure forest canopy LAIe values.However,sometimes this parameter must also be measured in forests with small clearings.In this study,we used the LAI-2200 PCA to obtain one A-value and four B-values each for the canopy,herbaceous layer,and forest ecosystem LAIe.Field measurements showed that the three LAIe types were obviously different.In certain quadrats,the average herbaceous layer(Dicranopteris dichotoma Bernh.)LAIe apparently exceeded that of the Pinus massoniana forest ecosystem.The sources of this error were measuring and recording A-value readings for small canopies and underestimating the ecosystem LAIe.We obtained similar coefficients of determination for both the pre-recomputation and post-recomputation of the canopy and forest ecosystem LAIe(R^2C 0.96 and R^2C 0.99,respectively);thus,the error was decreased.Measuring field LAIe with the LAI-2200 PCA and recomputation should compensate for LAIe underestimation in complex forest ecosystems.

Occurrence, Damage and Control Measures of Main Forest Pests in Sanyuan District, Sanming City

From 2015 to 2017, a total of 1957 investigation sites were set up in Sanyuan District of Sanming City, to conduct a comprehensive investigation on the species, occurrence and distribution of forest pests in 200 species of plants. The results showed that there were 163 species of forest pests in Sanyuan District, including 122 species of pests and 41 species of diseases. Dendrolimus punctatus walker, Monochamus alternatus Hope, Pantana phyllostachysae Chao, Loudonta dispar(Kiriakoff), Rammeacris kiangsu(Tsai) and Schizotetranychus nanjingensis Ma et Yuan were common forest pests, and Bursaphelenchus xylophilus(Steiner et Burher) Nickle was an invasive forestry quarantine disease. The prevention and control measures and technical measures against B. xylophilus and common forest pests were put forward, in order to provide scientific basis for productive control.

Indicator Selection for Quality Measurement in Maternal Neonatal and Child Health Services: Application of Random Forest Classifier

Quality of Maternal, Neonatal and Child (MNCH) care is an important aspect in ensuring healthy outcomes and survival of mothers and children. To maintain quality in health services provided, organizations and other stakeholders in maternal and child health recommend regular quality measurement. Quality indicators are the key components in the quality measurement process. However, the literature shows neither an indicator selection process nor a set of quality indicators for quality measurement that is universally accepted. The lack of a universally accepted quality indicator selection process and set of quality indicators results in the establishment of a variety of quality indicator selection processes and several sets of quality indicators whenever the need for quality measurement arises. This adds extra processes that render quality measurement process. This study, therefore, aims to establish a set of quality indicators from a broad set of quality indicators recommended by the World Health Organization (WHO). The study deployed a machine learning technique, specifically a random forest classifier to select important indicators for quality measurement. Twenty-nine indicators were identified as important features and among those, eight indicators namely maternal mortality ratio, still-birth rate, delivery at a health facility, deliveries assisted by skilled attendants, proportional breach delivery, normal delivery rate, born before arrival rate and antenatal care visit coverage were identified to be the most important indicators for quality measurement.

A study on the measurement for forest ecological benefit

The indexes of dependent variables of the measurement on the forest ecological benefits were defined according to the analysis of the multiple ecological benefits of forest. This indexes system includes waterreserving, soil and water conservation, wind and sand suppression, microclimate improvement, carbon dioxide assimilation, atmosphere purification, flood and drought mitigation, tourism resource and wild creature protection benefits. The main factors from the numerous factors that affect dependent variables were chosen as independent variables. At last, a multivariate linear model was established for measurement of forest ecological benefit. With this multivariate linear model the forest ecological benefit of China was calculated. The forest ecological benefit of China is 723816 million yuan per year, which equals to 23.07% of the gross domestic product of China.

Comparison of satellite images with different spatial resolutions to estimate stand structural diversity in urban forests

The structural diversity in urban forests is highly important to protect biodiversity. In particular, fruit trees and bush species, cavity-bearing trees and coarse, woody debris provide habitats for animals to feed, nest and hide. Improper silvicultural practices, intensive recreational use and illegal harvesting lead to a decline in the structural diversity in forests within larger metropolitan cities. It is important to monitor the structural diversity at definite time intervals using effective technologies with a view to instituting the necessary conservation measures. The use of satellite images seems to be appropriate to this end. Here we aimed to identify the associations between the textural features derived from the satellite images with different spatial resolutions and the structural diversity indices in urban forest stands (Shannon-Wiener index, complexity index, dominance index and density of wildlife trees). RapidEye images with a spatial resolution of 5 m × 5 m, ASTER images with a spatial resolution of 15 m × 15 m and Landsat-8 ETM satellite images with a spatial resolution of 30 m × 30 m were used in this study. The first-order (standard deviation of gray levels) and second order (GLCM entropy, GLCM contrast and GLCM correlation) textural features were calculated from the satellite images. When associations between textural features in the images and the structural diversity indices were assessed using the Pearson correlation coefficient, very high associations were found between the image textural features and the diversity indices. The highest association was found between the standard deviation of gray levels (SDGLRAP) derived from RVIRAP of RapidEye image and the Shannon-Wiener index (H h) calculated on the basis of tree height (R 2 = 0.64). The findings revealed that RapidEye satellite images with a spatial resolution of 5 m × 5 m are most suitable for estimating the structural diversity in urban forests.

Effect of cultivation measures on economic benefit of Larix olgesis pulp forest

According to the cultivating practice ofLarix olgensis pulp plantation, IRR (Internal revenue rate) and NPV (Net present value) were taken as two economic indices to study the effect of cultivation measurements on economic benefit ofLarix olgensis pulp forest. The results showed that the economic benefit of this type of forest is closely related to rotation and site class. Higher economic benefit could be obtained when the rotation is shorter and site class is higher. The planting density also had an obvious influence on economic benefit. On the base of assuring survival rate and conserving rate, the less the fee used in soil preparation and young growth tending is, the higher the economic benefit is. The influence of determined six cultivation measures on economic benefit in sequence was the rotation—site class—density—management fee level—young growth tending intensity—soil preparation methods.

Low net primary productivity of dominant tree species in a karst forest, southwestern China： first evidences from tree ring width and girth increment

Aboveground net primary productivity(ANPP)of two dominant species, one deciduous tree(Platycarya strobilacea) and one evergreen tree(Machilus cavaleriei),was estimated based on the tree-ring width and the girth increment as well as allometric functions in a karst evergreen and deciduous broadleaved mixed forest in central Guizhou Province, southwestern China. Results showed that the ANPP increased from 1961 to 2015, especially during the last 20–30 years, but with strong variations. The deciduous tree had higher ANPP than the evergreen tree according to two kinds of estimates by the tree ring and girth increment. The averaged ANPP for these two mature trees was 2.27 kg/individual/year, ca. 8 t/ha/year considering the normal stand density. Such karst forest productivity was lower than the natural subtropical forests in China and in the world.

A random forest algorithm based on similarity measure and dynamic weighted voting

The random forest model is universal and easy to understand, which is often used for classification and prediction. However, it uses non-selective integration and the majority rule to judge the final result, thus the difference between the decision trees in the model is ignored and the prediction accuracy of the model is reduced. Taking into consideration these defects, an improved random forest model based on confusion matrix (CM-RF)is proposed. The decision tree cluster is selectively constructed by the similarity measure in the process of constructing the model, and the result is output by using the dynamic weighted voting fusion method in the final voting session. Experiments show that the proposed CM-RF can reduce the impact of low-performance decision trees on the output result, thus improving the accuracy and generalization ability of random forest model.

Evaluation of soil erosion from chestnut forests: A case study in the Yanshan Mountains, China

Soil erosion from chestnut forests has many types and intensities. However, less attention has been paid to the increasing soil erosion in the chestnut forests of Yanshan Mountains region, North China. The objective of this study was to discuss forest ages(<5, 5~<10, 10~<20, and 20~ yr), slopes(5°~<15°, 15°~<25°, 25°~<35°, and 35°~), slope positions(upslope, midslope, downslope, and whole slope), and slope aspects(sunny, half-sunny, shade, and half-shade) effects on soil erosion types and intensities in chestnut forests. A field survey was applied to investigate in detail the contiguous chestnut forests near Changfu village of Hebei Province, China on October 9-30, 2016. Results showed that chestnut forests are dominated by moderate erosion in this region, and the soil erosionfrom chestnut forests tended to deteriorate gradually. The average land degradation index was 0.31. The erosion intensity from chestnut forests will gradually increase with the year of planting. Most of the slopes are greater than 15°, accounting for 86.7% of the total chestnut forests. Most of the chestnut forests occupy the whole slope, accounting for 47.5% of the total area. Moderate erosion occurs most commonly for different slope aspects. In conclusion, improving the preparation efficiency of chestnut forests and enhancing the construction standards of soil and water conservation measures would be useful measures to avoid soil erosion from chestnut forests reaching a more severe level.

Rate of timber production in a tropical rainforest ecosystem of Southwestern Nigeria and its implications on sustainable forest management

Timber harvesting data are very essential for sustainable management of forest resources.These data are very scarce in developing countries.Therefore,we collected and analyzed data on the rate of timber production of the free areas and the forest reserves in Ondo State,Nigeria.The data collected from the State Department of Forestry＇s official records,annual reports and files were on the species,volume and number of different economic timbers exploited on monthly basis between 2003 and 2005.Analyses were done with the student t-test and one-way analysis of variance.Results reveal that the highest numbers of species,families and stems were exploited in the free areas when compared with what was exploited from the reserves for the three-year period.However,the total volume of trees removed from the reserves was significantly higher（p〈0.05） than what was removed from the free areas.A total 60 different indigenous hardwood species in 25 families were exploited from the free areas,and 57 in 23 families from the reserves.The total number of stems exploited from the forest ecosystem of Ondo state during the three-year period stood at 111377 with an estimated volume of 295089.67 m^3.While the mean number of stems and volume exploited per annum is 37125 and 98363.22 m^3,respectively.The monthly average number of stems and volume is 3094 and 8196 m^3,respectively.The t-test results show that there were significant differences（p〈0.05） in number of stems and volume removed from the free areas and the reserves.The ANOVA results reveal a significant increase（p〈0.05） in logging activities between the years of 2003 and 2004 but there was a decline in year 2005.This trend reveals that economic timber species were disappearing from the forests and the ecosystem was seriously disturbed during logging activities.Principles for achieving the goals of sustainable forest management（SFM） and urgent conservation measures to mitigate the consequences of forest degradation were suggested.

Variable Importance Measure System Based on Advanced Random Forest

The variable importance measure(VIM)can be implemented to rank or select important variables,which can effectively reduce the variable dimension and shorten the computational time.Random forest(RF)is an ensemble learning method by constructing multiple decision trees.In order to improve the prediction accuracy of random forest,advanced random forest is presented by using Kriging models as the models of leaf nodes in all the decision trees.Referring to the Mean Decrease Accuracy(MDA)index based on Out-of-Bag(OOB)data,the single variable,group variables and correlated variables importance measures are proposed to establish a complete VIM system on the basis of advanced random forest.The link of MDA and variance-based sensitivity total index is explored,and then the corresponding relationship of proposed VIM indices and variance-based global sensitivity indices are constructed,which gives a novel way to solve variance-based global sensitivity.Finally,several numerical and engineering examples are given to verify the effectiveness of proposed VIM system and the validity of the established relationship.

Compound Planting of Bletilla striata under Forest in the Three Gorges Dam Area

[Objectives] The aim was to study the artificial cultivation of Bletilla striata to realize large scale and standardization planting. [Methods] The comparison tests were conducted on B. striata with different canopy densities of the Magnolia officinalis forests,different compound planting densities and different tending measures and management. [Results] When the stand canopy density was 0. 4-0. 6,the per unit yield of B. striata was 5. 4%,6. 8% higher than that at the canopy density of less than 0. 4 and more than 0. 6,respectively. When the planting density was 30 cm × 30 cm,the per unit yield increased by 16. 1%,12. 0%,13. 1% respectively compared with the planting density of 20 cm × 20 cm,25 cm × 25 cm,35 cm × 35 cm. When B. striata was planted from October to November,the per unit yield was 5. 6% higher than that planted from December to January of the following year,and 21. 3% higher than that from February to March of the second year. When farmyard manure was applied during the cultivation,the per unit yield was 31. 7% and 18. 4% higher than the application of chemical fertilizer and compound fertilizer. When weeding 4 times per year,the per unit yield increased by 240. 1%,137. 0% and 43. 9% respectively from that weeding 1 times,2 times,3 times per year. [Conclusions]When planting B. striata,the stand canopy density of 0. 4-0. 6 could make it receive absolutely shelters and the lighting conditions required for the growth,thereby bringing in high emergence rate,good growth potential and high yield. The best planting effect of B. striata could achieve by planting from October to November with the planting density of 30 cm × 30 cm,which can play the maximum benefit of individual plants. Moreover,weeding 4 times per year combined with the use of farmyard manure can promote the development and growth of tubers,which can greatly improve the yield of B. striata.

Suggestions on management measures of pine forest ecosystems invaded by Bursaphelenchus xylophilus

Pine wood nematode （PWN）, Bursaphelenchus xylophilus （Steiner et Buhrer） Nickle is an important invasive alien species in forests of China and has become one of the most destructive forest diseases. In order to improve the resistance and resilience of pine forest ecosystems against B. xylophilus invasion and make the pine forest ecosystem more timely responsive to PWN invasion, we made some recommendations based on five years of intensive observations. We advocate a set of management measures with the theme “Prevention is priority, but integrated with curative techniques and ecological resilience” on the pine forest ecosystem invaded by B. xylophilus; details of accurate measures are proposed. The aim is to discover the underlying problems of present pine forest ecosys-tems and to take, correspondingly, administrative measures and strategies, which will encourage the pine forest ecosystem to develop in a benign way.

Eco-environment Restoration and Regional Differentiation Characteristics Based on “Building Terrace and Returning Slope Farmland to Forests and Grass”

Based on the scientific and technological achievements in the past decade in the Loess Hilly-gully Region and the successful demonstration experience in Yan'an Yangou watershed, we summarize the characteristics of eco-environment restoration pattern based on "building terrace and returning slope farmland to forests and grass". According to the data on land use, slope farmland and the agricultural population in 1999, we calculate the area of new terrace that needs to be built, the area of garden plot that needs to be extended, vegetation restoration area and investment demand in counties (cities, districts). Establishing and using some indicators, such as basic farmland extension indicator, garden plot extension indicator, vegetation restoration index and investment demand density, we conduct type classification and analysis of regional differentiation characteristics in 55 counties (cities, districts). The results show that in the Loess Hilly-gully Region, 691 600 hm2 of new terrace needs to be built, 792 000 hm2 of economic forests and orchards need to be extended, 5 410 200 hm2 of vegetation needs to be restored, and the total investment demand is 15.82 billion yuan; in terms of geographical distribution, obviously there are two key areas for eco-environment restoration (one is located in the border area between northern Shaanxi and northwestern Shanxi, and the other is located in the eastern Gansu and southern Ningxia area); the classified regional guidance policies should be formulated as soon as possible, and the limited funds should be concentrated in the key areas.

How do machine learning techniques help in increasing accuracy of landslide susceptibility maps?

Landslides are abundant in mountainous regions.They are responsible for substantial damages and losses in those areas.The A1 Highway,which is an important road in Algeria,was sometimes constructed in mountainous and/or semi-mountainous areas.Previous studies of landslide susceptibility mapping conducted near this road using statistical and expert methods have yielded ordinary results.In this research,we are interested in how do machine learning techniques help in increasing accuracy of landslide susceptibility maps in the vicinity of the A1 Highway corridor.To do this,an important section at Ain Bouziane(NE,Algeria) is chosen as a case study to evaluate the landslide susceptibility using three different machine learning methods,namely,random forest(RF),support vector machine(SVM),and boosted regression tree(BRT).First,an inventory map and nine input factors were prepared for landslide susceptibility mapping(LSM) analyses.The three models were constructed to find the most susceptible areas to this phenomenon.The results were assessed by calculating the receiver operating characteristic(ROC) curve,the standard error(Std.error),and the confidence interval(CI) at 95%.The RF model reached the highest predictive accuracy(AUC=97.2%) comparatively to the other models.The outcomes of this research proved that the obtained machine learning models had the ability to predict future landslide locations in this important road section.In addition,their application gives an improvement of the accuracy of LSMs near the road corridor.The machine learning models may become an important prediction tool that will identify landslide alleviation actions.