No abstract

Tree biomass and the diversity relationship in mixed forest have an impact on forest ecosystem services provisions. Tree biomass yield is driven by several aspects such as species identity, site condition, stand density, tree age and tree diversity expressed as species mingling and structural diversity. By comparing diverse degrees of tree mixtures in natural forests, we can gain insight into the ecosystem services provision level and dynamic. Two monitoring sites in the Castilian Northern Plateau (Spain) have been analyzed to disentangle the relationships between biodiversity levels and tree biomass yield. Two permanent one hectare (ha) squared plots were established at Llano de San Marugán and Valdepoza. In each plot, all individual trees were measured (diameter and height), georeferenced and its species identity defined. Tree species in the two sites were Pinus sylvestris, Pinus nigra, Pinus pinea, Quercus pyrenaica, Quercus ilex, Quercus faginea and Juniperus thurifera. From these datasets, ten diversity indices that fall in three categories (species richness indices, species compositional/mingling indices and vertical structural indices) were used as predictor variables to fit several candidate models. By merging the trees by site (without considering the species identity) selected models include individual tree basal area as an explanatory variable combining by addition or interaction with diversity indices. When species are analyzed independently, structural diversity impacts on biomass yield in combination (additive or multiplicative) with tree size is negative for Pinus nigra and positive for the other species.

. Temporal variations in phenological events of forests, grasslands and desert steppe ecosystems in Mongolia: a remote sensing approach. Ann. For. Res. 59(2): 175-190.Abstract. The occurrences of phenological events are important variables in the evaluation of the influence of climate change on terrestrial ecosystems. Changes in climate can cause significant changes in the timing and duration of phenological events. Information related to large-scale phenology is therefore useful for exploring the seasonal and inter-annual variability in vegetation-climate interactions. This study aimed to obtain the timing and temporal pattern of the onset of green-up and dormancy (OG and OD) and length of growing season (LGS) using the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) for Forest, Grassland, and Desert steppe in Mongolia over the 10-year period from 2000 to 2009. Results demonstrated that phenological events can be differentiated by multi-temporal NDVI and EVI data and that the timing ascribed to OG and OD is slightly different between the two indices. In general, NDVI and EVI agreed that the OG of forest varied from late May to middle July. The OG of grassland and desert steppe suggested by NDVI were from late May to middle July and from middle May to middle July respectively, however EVI suggested an earlier timing of OG. NDVI and EVI also showed similar variation for the timing of OD from early September to early October. The derived LGS showed the least variation for forest, highest variation for desert steppe, and only moderate variation for grassland. Grassland and desert steppe experienced high positive and negative variations in the OG and LGS during the years from 2000 to 2009. These regions might be vulnerable to global change and are likely to be strongly affected by meteorological changes. Keywords phenological events; onset of green-up; onset of dormancy; length of growing season; peak time of vegetation maturity; vegetation indices; MODIS NDVI and EVI

Climate is one of the most important factors affecting the condition of vegetation. Plants are highly sensitive to climate change and display the most sensitive response to the effect of the climate change and environment, most particularly seen in the annual and seasonal alternations of vegetation productivity. Through the analysis of remotely sensed images, it is proved that vegetation indices can give signifi cant information regarding vegetation. The main purpose of this study was to estimate the infl uences of precipitation and temperature on spatio-temporal pattern of vegetation dynamics in Mongolia using MODIS sensor derived NDVI images over the course of 10 years. The correlation coeffi cient showed that mean growing season NDVI was correlated with both climatic factors, but more signifi cantly correlated with precipitation (r 2 =0.92, p=0.000) than temperature (r 2 =0.55, p=0.013). Growing season precipitation slightly decreased with an annual average decrement of 0.2 mm (r 2 =0.06). Meanwhile, the growing season mean temperature slightly increased over 10 years, with an annual average increment of 0.01°C per year (r 2 =0.003) from 2000 to 2009. However, the relationship between NDVI and climatic factors, and their change trends have been varied spatially and temporally.

Tree biomass and diversity relationship in mixed forest impacts on forest ecosystem services provisions. Tree biomass yield is driven by several aspects such as species identity, site condition, stand density, tree age as well as tree diversity expressed as species mingling and structural diversity. By comparing diverse degrees of tree mixture in natural forests we can insight on the ecosystem services provision level and dynamic. Two monitoring sites in the Castilian Northern Plateau (Spain) have been analyzed to disentangle the relationships between biodiversity levels and tree biomass yield. Two permanent one ha squared plots were established at Llano de San Marugan and Valdepoza. In each plot all individual trees were measured (diameter and height), georeferenced and its species identity defined. Tree species in the two sites were Pinus sylvestris, Pinus nigra, Pinus pinea, Quercus pyrenaica, Quercus ilex, Quercus faginea and Juniperus thurifera. From these datasets ten diversity indices that fall in three categories (species richness indices, species compositional/mingling indices and vertical structural indices) were used as predictor variables to fit several candidate models. By merging the trees by site (without considering the species identity) selected models include individual tree basal area as explanatory variable combining by addition or interaction with diversity indices. When species are analyzed independently structural diversity impacts on biomass yield in combination (additive or multiplicative) with tree size is negative Pinus nigra and positive for the other species.