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PubMed2004

[Water conservation functions of several artificial forest ecosystems in semiarid region of western Liaoning Province].

Five artificial forest ecosystems in semiarid region of western Liaoning Province were selected to test their water conservation capacity. The average interception rate of different artificial forest ecosystems varied from 14.58% to 37.19%, and the order was H. rhamnoides forest ecosystem > P. tabulaeformis-H. rhamnoides mixed forest ecosystem > P. simonii-H. rhamnoides mixed forest ecosystem > P. tabulaeformis forest ecosystem > P. simonii forest ecosystem. The thickness of the litter layer in different forest ecosystems varied from 1.6 to 4.1 cm, and the biomass of the litter varied from 1890.4 to 6425.2 kg x hm(-2). The order of the thickness and the biomass of the litter in different forest ecosystems was H. rhamnoides forest ecosystem > P. tabulaeformis-H. rhamnoides mixed forest ecosystem > P. simonii-H. rhamnoides mixed forest ecosystem > P. tabulaeformis forest ecosystem > P. simonii forest ecosystem. The maximum water holding capacity of the litter in different forest ecosystems varied form 5957.7 to 19332.9 kg x hm(-2), and the order was H. rhamnoides forest ecosystem > P. tabulaeformis-H. rhamnoides mixed forest ecosystem > P. simonii-H. rhamnoides mixed forest ecosystem > P. tabulaeformis forest ecosystem > P. simonii forest ecosystem. The water holding capacity of non-capillary porosity of 0-40 cm soil layer in different forest ecosystems varied from 23.70 to 37.85 mm, and the order was H. rhamnoides forest ecosystem > P. simonii-H. rhamnoides mixed forest ecosystem > P. tabulaeformis-H. rhamnoides mixed forest ecosystem > P. simonii forest ecosystem > P. tabulaeformis forest ecosystem. Among the five artificial forest ecosystems, H. rhamnoides forest ecosystem had the best water conservation capacity, and the mixed forest ecosystems had a better water conservation capacity than P. tabulaeformis and P. simonii forest ecosystem.

China↗
PubMed2002

Regional estimation of current and future forest biomass.

The 90,674 wildland fires that burned 2.9 million ha at an estimated suppression cost of $1.6 billion in the United States during the 2000 fire season demonstrated that forest fuel loading has become a hazard to life, property, and ecosystem health as a result of past fire exclusion policies and practices. The fire regime at any given location in these regions is a result of complex interactions between forest biomass, topography, ignitions, and weather. Forest structure and biomass are important aspects in determining current and future fire regimes. Efforts to quantify live and dead forest biomass at the local to regional scale has been hindered by the uncertainty surrounding the measurement and modeling of forest ecosystem processes and fluxes. The interaction of elevated CO2 with climate, soil nutrients, and other forest management factors that affect forest growth and fuel loading will play a major role in determining future forest stand growth and the distribution of species across the southern United States. The use of satellite image analysis has been tested for timely and accurate measurement of spatially explicit land use change and is well suited for use in inventory and monitoring of forest carbon. The incorporation of Landsat Thematic Mapper data coupled with a physiologically based productivity model (PnET), soil water holding capacity, and historic and projected climatic data provides an opportunity to enhance field plot based forest inventory and monitoring methodologies. We use periodic forest inventory data from the USDA Forest Service's Forest Inventory and Analysis (FIA) project to obtain estimates of forest area and type to generate estimates of carbon storage for evergreen, deciduous, and mixed forest classes for use in an assessment of remotely sensed forest cover at the regional scale for the southern United States. The displays of net primary productivity (NPP) generated from the PnET model show areas of high and low forest carbon storage potential and their spatial relationship to other landscape features for the southern United States. At the regional scale, predicted annual NPP in 1992 ranged from 836 to 2181 g/m2/year for evergreen forests and 769-2634 g/m2/year for deciduous forests with a regional mean for all forest land of 1448 g/m2/year. Prediction of annual NPP in 2050 ranged from 913 to 2076 g/m2/year for evergreen forest types to 1214-2376 g/m2/year for deciduous forest types with a regional mean for all forest land of 1659 g/m2/year. The changes in forest productivity from 1992 to 2050 are shown to display potential areas of increased or decreased forest biomass. This methodology addresses the need for spatially quantifying forest carbon in the terrestrial biosphere to assess forest productivity and wildland fire fuels.

Biomass↗
PubMed2005

Climatic controls of vegetation vigor in four contrasting forest types of India--evaluation from National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer datasets (1990-2000).

Ten-day advanced very high resolution radiometer images from 1990 to 2000 were used to examine spatial patterns in the normalized difference vegetation index (NDVI) and their relationships with climatic variables for four contrasting forest types in India. The NDVI signal has been extracted from homogeneous vegetation patches and has been found to be distinct for deciduous and evergreen forest types, although the mixed-deciduous signal was close to the deciduous ones. To examine the decadal response of the satellite-measured vegetation phenology to climate variability, seven different NDVI metrics were calculated using the 11-year NDVI data. Results suggested strong spatial variability in forest NDVI metrics. Among the forest types studied, wet evergreen forests of north-east India had highest mean NDVI (0.692) followed by evergreen forests of the Western Ghats (0.529), mixed deciduous forests (0.519) and finally dry deciduous forests (0.421). The sum of NDVI (SNDVI) and the time-integrated NDVI followed a similar pattern, although the values for mixed deciduous forests were closer to those for evergreen forests of the Western Ghats. Dry deciduous forests had higher values of inter-annual range (RNDVI) and low mean NDVI, also coinciding with a high SD and thus a high coefficient of variation (CV) in NDVI (CVNDVI). SNDVI has been found to be high for wet evergreen forests of north-east India, followed by evergreen forests of the Western Ghats, mixed deciduous forests and dry deciduous forests. Further, the maximum NDVI values of wet evergreen forests of north-east India (0.624) coincided with relatively high annual total precipitation (2,238.9 mm). The time lags had a strong influence in the correlation coefficients between annual total rainfall and NDVI. The correlation coefficients were found to be comparatively high (R2=0.635) for dry deciduous forests than for evergreen forests and mixed deciduous forests, when the precipitation data with a lag of 30 days was correlated against NDVI. Using multiple regression approach models were developed for individual forest types using 16 different climatic indices. A high proportion of the temporal variance (>90%) has been accounted for by three of the precipitation parameters (maximum precipitation, precipitation of the wettest quarter and driest quarter) and two of the temperature parameters (annual mean temperature and temperature of the coldest quarter) for mixed deciduous forests. Similarly, in the case of deciduous forests, four precipitation parameters and three temperature parameters explained nearly 83.6% of the variance. These results suggest differences in the relationship between NDVI and climatic variables based upon the time of growing season, time interval and climatic indices over which they were summed. These results have implications for forest cover mapping and monitoring in tropical regions of India.

Climate↗
PubMed2002

[A review on fundamental studies of secondary forest management].

Secondary forest is also called as natural secondary forest, which regenerates on native forest that has been disturbed by severe natural or anthropogenic disturbances. The structural and dynamic organizations, growth, productivity and stand environment of secondary forests are significantly different from those of natural and artificial forests. Such significant differences make secondary forests have their own special characteristics in forestry. Secondary forests are the main body of forests in China. Therefore, their management plays a very important role in the projects of natural forest conservation and the construction of ecological environment in China or in the world. Based on a wide range of literature collection on secondary forest research, the fundamental studies of secondary forest management were discussed. The major topics are as follows: 1) basic characteristics of secondary forest, 2) principles of secondary forest management, 3) types of secondary forest, 4) community structure and succession dynamics of secondary forest, including niches, biodiversity, succession and so on, 5) main ecological processes of secondary forest, including regeneration, forest soil and forest environment. Additionally, the research needs and tendency related to secondary forest in the future were also given, based on the analyses of the main results and the problems in current management of secondary forest. The review may be helpful to the research of secondary forest management, and to the projects of natural forest conservation in China.

China↗
PubMed2003

Fragmented forest in tropical landscape--the case of the state of Selangor, Malaysia.

This paper presents the pattern and changes of fragmented forest in relation with changes of total forest cover in the state of Selangor in three decades. In this study, inventoried forest cover maps of Selangor in 1971/1972, 1981/1982 and 1991/1992 produced by the Forestry Department of Peninsular Malaysia were digitized to examine the changes in area and number of fragmented forest. Results showed that in 1971/1972, 16 fragmented forests were identified in Selangor. All fragmented forests were identified as dipterocarp forest. A decade later the number of fragmented forests increased by approximately 44% (23). Of the 23 fragmented forests, two were peat swamp forests whereas the remaining were dipterocarp forests. In 1991/1992 the number of fragmented forests (12) was reduced by 47.8%. Two of the fragmented forests were identified as peat swamp forest, seven dipterocarp forest and the other three was mixed of dipterocarp forests and plantation forests. Fragmentation of both dipterocarp and peat swamp forests occurred profoundly during the period between 1971/1972 and 1981/1982, which consequently increased the number of fragmented forests compared with before the period of 1971/1972 where fragmentation happened only at dipterocarp forests. However, many fragmented forests vanished between the 1981/1982 and 1991/1992 periods.

Conservation of Natural Resources↗