Forest ecological benefit compensation plays a promoting role in improving the enthusiasm of forest ecological builders and maintainers, maintaining the legitimate economic interests of forest owners, and coordinating the fairness between the “clear water and green mountains” protectors and the “gold and silver mountains” beneficiaries. Comprehensive combed the domestic forest ecological benefit compensation mechanism, including the compensation scope, compensation subject, compensation object, the research progress of compensation standard, summarized the forest ecosystem benefits measurement, including physical appraisal method, the value evaluation method, energy analysis method and the characteristics and application research progress of ecological model method. This paper discusses the research status and existing problems of the calculation basis of compensation standard, the origin, research emphasis and progress of forest ecological service payment abroad in recent years, and the mechanism of forest ecological service payment in many countries. Finally, some suggestions are put forward to improve the compensation mechanism of forest ecological benefits in China. On the one hand, it is necessary to broaden the source of funds through various ways of marketization and scientifically evaluate the forest ecological benefits. On the other hand, the compensation standard should be established scientifically and reasonably to achieve different compensation levels or compensation intervals.

The wave effect and the shyness phenomenon in Alnus acuminata (Kunth) are crown parameters rarely studied, but important in the quality of the wood of standing trees, therefore, a morphometric modeling of the crowns of Alnus acuminata in homogeneous forests in the Sierra Norte de Puebla was carried out. In 20 rectangular sites of 1,000 m², the following were evaluated: total height (TA), normal diameter (ND), crown diameter (CD) and crown cover (CC). The Kruskal Wallis test was applied to data that did not meet the assumption of normality; for those that did, analysis of variance (ANOVA) was used, with Tukey mean comparison tests (α ≤ 0.05). The forest value index was 14.99, so its two-dimensional structure is normal based on DN, AT and CC. Its average slenderness index was 93.52, which makes the tree not very stable to mechanical damage. The life-space index was 38.92, which is high indicating that trees with low intraspecific competition developed better. At the canopy level, a pattern following an upward, oscillatory and constant wave effect was observed in groups of 10 trees. The shyness phenomenon showed an average crack opening of 27.39 cm between canopies, so this phenomenon is well defined for the species. It is concluded that in the crowns of Alnus acuminata, the wave effect is observed as a consequence of inequality in the acquisition of resources, and one way to minimize this inequality is through the phenomenon of botanical shyness.

Identify and diagnosis of homogenous units and separating them and eventually planning separately for each unit are considered the most principled way to manage units of forests and creating these trustable maps of forest’s types, plays important role in making optimum decisions for managing forest ecosystems in wide areas. Field method of circulation forest and Parcel explore to determine type of forest require to spend cost and much time. In recent years, providing these maps by using digital classification of remote sensing’s data has been noticed. The important tip to create these units is scale of map. To manage more accurate, it needs larger scale and more accurate maps. Purpose of this research is comparing observed classification of methods to recognize and determine type of forest by using data of Land Cover of Modis satellite with 1 kilometer resolution and on images of OLI sensor of LANDSAT satellite with 30 kilometers resolution by using vegetation indicators and also timely PCA and to create larger scale, better and more accurate resolution maps of homogenous units of forest. Eventually by using of verification, the best method was obtained to classify forest in Golestan province’s forest located on north-east of country.