通天河国家森林公园几种野生观赏草本经营利用对策分析

本文通过对柳兰、水金凤、大叶碎米荠、索骨丹、黄海棠等区域特色观赏植物形态特征、生态适应性及自然繁殖特点分析、论证了人工经营利用的可行性,提出＂修旧如旧＂的区域景观修复原则。

Responses of Vegetation and Primary Production in North-South Transect of Eastern China to Global Change Under Land Use Constraint

A regional model of vegetation dynamics was revised to include land use as a constraint to vegetation dynamics and primary production processes. The model was applied to a forest transect in eastern China (NSTEC, North-South transect of eastern China) to investigate the responses of the transect to possible future climatic change. The simulation result indicated that land use has profound effects on vegetation transition and primary production. In particular, land use reduced competition among vegetation classes and tended to result in less evergreen broadleaf forests but more shrubs and grasses in the transect area. The simulation runs with land use constraint also gave much more realistic estimation about net primary productivity as well as responses of the productivity to future climatic change along the transect. The simulations for future climate scenarios projected by general circulation models (GCM) with doubled atmospheric CO2 concentration predicted that deciduous broadleaf forests would increase, but conifer forests, shrubs and grasses would decrease. The overall effects of doubling CO2 and climatic changes on NSTEC were to produce an increased net primary productivity (NPP) at equilibrium for all seven GCM scenarios. The predicted range of NPP variation in the north is much larger than that in the south.

Effect of Different Vegetation Systems on Soil Erosion and Soil Nutrients in Red Soil Region of Southeastern China

The effect of different vegetation systems including bamboo plantation (BP), forest ecosystem (CF),citrus orchard (Ctr) and farmland (FL) on erosion and nutrients of red soil were investigated in hilly region of southeastern China to find effective control measures for soil erosion. The results showed that all the vegetation systems could significantly reduce soil erosion and nutrient losses compared to bare land (Br).The ability of different vegetation systems to conserve soil and water was in the order of Ctr ＞ BP ＞ CF ＞ FL ＞ Br. Vegetation could also improve soil fertility. The soil organic matter, total N and total P contents were much higher in all the vegetation systems than in bare land, especially for the top soils. Vegetation systems improved soil physical properties remarkably. Compared to the bare land, soil organic matter, TP,TK and available K, especially soil microbial biomass C, N and P, increased under all the vegetation covers.However, they were still much lower than expected, thus these biological measurements are still needed to be carried out continuously.

The Connection of Vegetation with Tourism Development and Economic Growth： A Case Study for Aruba

Vegetation is an important ecosystem on earth. It influences the earth system in many ways. Any influences on this fragile variable should be investigated, especially in a changing climate. Humans can have a positive or a negative influence on plants. This paper investigates the possible impact of tourism development and economic growth on vegetation health using cointegration and causality for Aruba. The proposed framework contributes to a better understanding on the use of remote sensing of vegetation response to tourism development and economic growth. Thereby, provide opportunities for improving the overall strategy for achieving sustainable development on a small island state. The calculations showed that there were relationships between the tourism demand and economic growth on the vegetation health on Aruba for the western part of the island. On the other hand, for the central part of the island, no relationships were found.

Probabilistic Classification of Tree and Shrub Vegetation on Phytogeographic System

The phytogeographical system for vegetation classification splits the vegetation in first level types： forest and grasslands. The forest type can be recognized in tropical rain forest and seasonal depending on the environmental conditions. This determines the occurrence of deciduous species in big or small quantity. And the grasslands are Savannah in majority. This work proposed probabilistic methods to classify these vegetation types based on priori occurrence of species. The test was carded out with forest inventory data using ten vegetation fragments in farm of Embrapa and Cascata＇s park in Sete Lagoas city, Minas Gerais, Brazil. The distribution of species with occurrence in different types was adapted to set theory and Bayes theorem. In this way, it is possible to calculate belonging of species on vegetation types. The results were compared with usual classification. The main contribution of probabilistic methods was to increase the information to classify tree and shrub vegetation inventoried. It is especially recommended for transition regions between vegetation types.

Influences of the interannual variability of vegetation LAI on surface temperature

The influences of interannual variability of vegetation LAI on surface temperature are investigated via two ensemble simulations, applying the Community Earth System Model. The interannual LAI, derived from Global Inventory Modeling and Mapping Studies NDVI for the period 1982-2011, and its associated climatological LAI, are used in the two ensemble simulations, respectively.The results show that the signals of the influences, represented as ensemble-mean differences, are generally weaker than the noises of the atmospheric variability, represented as one standard deviation of the ensemble differences. Spatially, the signals are stronger over the tropics compared with the mid-high latitudes. Such stronger signals are contributed by the significant linearity between LAI and surface temperature, which is mainly caused via the influences of LAI on evapotranspiration.The maximum amplitudes of the influences on the interannual variability of surface temperature are high and thus deserve full consideration. However, the mean magnitudes of influences are small because of the small changes in the amplitudes of LAI. This work only investigates the influences of the interannual variability of LAI and does not consider interannual changes in other vegetation characteristics, such as canopy height and fractional cover. Further work involving dynamic vegetation models may be needed to investigate the influences of vegetation variability.

A Neural Network Method for Monitoring Snowstorm: A Case Study in Southern China

It has been observed that low temperature, rainfall, snowfall, frost have never occurred over the past 50 years in the southern China, and weather in this area is very complex, so the monitoring equipments are few. Optical and thermal infrared remote sensing is influenced much by clouds, so the passive microwave Advanced Microwave Scanning Radiometer-Earth Observing System （AMSR-E） data are the best choice to monitor and analyze the development of disaster. In order to improve estimation accuracy, the dynamic learn- ing neural network was used to retrieve snow depth. The difference of brightness temperatures of TB18.7v and TB36.sv, TBI8.7H and TB36.sH, TB23,sv and TB89v, TBz3.8H and TB89H are made as four main input nodes and the snow depth is the only one output node of neural network. The mean and the standard deviation of retrieval errors are about 4.8 cm and 6.7 cm relative to the test data of ground measurements. The application analysis indicated that the neural network can be utilized to monitor the change of snow intensity distribution through passive microwave data in the complex weather of the southern China.

Land-Cover Change Monitoring in Obuasi, Ghana： An Integration of Earth Observation, Geoinformation Systems and Stochastic Modelling

For over twenty years, Obuasi Municipality, Ghana, has experienced land-cover change arising from gold mining and urbanisation. This project quantified the land-cover changes that have taken place and projected likely future land-cover. An integration of EO （earth observation）, GIS （geographical information science） and Stochastic Modelling was examined. Post-classification Change Detection employed Landsat TM or ETM＋ images in 1986, 2002 and 2008. Subsequently, Markov Chain Analysis projected the land-cover distribution for 2020. Seven broad land-use and land-cover classes were identified and mapped, namely： built-up areas, mine sites tailing ponds barren land forestland farmland and rangeland. The results obtained for the 2008 to 2020 projection revealed a continuous expansion of built-up areas （1.63%）, mine sites （0.89%） and farmland （3.4%）, and a reduction of forestland （4.17%） and rangeland （2.59%）. Despite the advent of very high resolution satellite imagery, this use of EO and GIS technology focussed on low-cost and lower resolution satellite imagery, coupled with Markov Modelling and was found to be beneficial in describing and analysing land-cover change processes in the study area, and was hence potentially useful for strategic planning purposes.

Remote sensing based monitoring of interannual variations in vegetation activity in China from 1982 to 2009

Terrestrial vegetation is one of the most important components of the Earth's land surface. Variations in terrestrial vegetation directly impact the Earth system's balance of material and energy. This paper describes detected variations in vegetation activity at a national scale for China based on nearly 30 years of remote sensing data derived from NOAA/AVHRR(1982–2006) and MODIS(2001–2009). Vegetation activity is analyzed for four regions covering agriculture, forests, grasslands, and China's Northwest region with sparse vegetation cover(including regions without vegetation). Relationships between variations in vegetation activity and climate change as well as agricultural production are also explored. The results show that vegetation activity has generally increased across large areas, especially during the most recent decade. The variations in vegetation activity have been driven primarily by human factors, especially in the southern forest region and the Northwest region with sparse vegetation cover. The results further show that the variations in vegetation activity have influenced agricultural production, but with a certain time lag.

Assessment of Changes in the Value of Ecosystem Services in the Koshi River Basin,Central High Himalayas Based on Land Cover Changes and the CA-Markov Model

Climate warming and economic developments have created pressures on the ecological systems that human populations rely on,and this process has contributed to the degradation of ecosystems and the loss of ecosystem services.In this study,Landsat satellite data were chosen as the data source and the Koshi River Basin（KB） in the central high Himalayas as the study area.Changes in land cover and changes in the value of ecosystem services between 1990 and 2010 were analyzed and the land cover pattern of the KB in 2030 and 2050 was modeled using the CA-Markov model.Changes in land cover and in the value of ecosystem services in the KB for the period 2010–2050 were then analyzed.The value of ecosystem services in the KB was found to decrease by 2.05×10~8 USD y^（-1） between 1990 and 2010.Among these results,the services value of forest,snow/glacier and barren area decreased,while that of cropland increased.From 1990 to 2050,forest showed the largest reduction in ecosystem services value,as much as 11.87×10~8 USD y^（-1）,while cropland showed the greatest increase,by 3.05×10~8 USD y^（-1）.Deforestation and reclamation in Nepal contributed to a reduction in the value of ecosystem services in the KB.Barren areas that were transformed into water bodies brought about an increase in ecosystem services value in the lower reaches of the Koshi River.In general,this process is likely to be related to increasing human activity in the KB.

Using Weights of Evidence in the Spatial Relation Between Infected Snails and Geographic Factors

Schistosomiasis is a serious public health problem in the middle-lower Yangtze River Basin in China. Study of spatial variation of snail distribution that is related to microgeographic factors can help to choose pertinent measures for snail extinguishment and environment rebuilding. This paper studied the theoretical architecture of weights-of-evidence approach. The case study was made for spatial relation between the occurrence of infected snails and geographic factor combinations in Waijiazhou marshland of Poyang Lake region in China. The multievidence data came from the geographical factor combinations by crossing operation of vegetation coverage grade layer, cattle route distance grade layer, and special environment layer (181 combinations in total) in GIS. The calculation of weight contrast index shows that high vegetation coverage, cattle route distance of <45 meters, and special geographic factor "ground depression" had direct spatial relation with the occurrence of infected snails. The verification by crossing operation in GIS indicated 72.45% of the infected snails concentrated on the areas of positive weight contrast index (sequenced in an order of weight contrast index from high to low), demonstrating the high efficiency of the model established in finding infected snails according to the geographic factor combinations that can be explicitly discerned in the study area.

Recent leveling off of vegetation greenness and primary production reveals the increasing soil water limitations on the greening Earth

Global vegetation photosynthesis and productivity have increased substantially since the 1980s,but this trend is heterogeneous in both time and space.Here,we categorize the secular trend in global vegetation greenness into sustained greening,sustained browning and greening-to-browning.We found that by 2016,increased global vegetation greenness had begun to level off,with the area of browning increasing in the last decade,reaching 39.0 million km^(2)(35.9%of the world’s vegetated area).This area is larger than the area with sustained increasing growth(27.8 million km^(2),26.4%);thus,12.0%±3.1%(0.019±0.004 NDVI a^(-1))of the previous earlier increase has been offset since 2010(2010–2016,P<0.05).Global gross primary production also leveled off,following the trend in vegetation greenness in time and space.This leveling off was caused by increasing soil water limitations due to the spatial expansion of drought,whose impact dominated over the impacts of temperature and solar radiation.This response of global gross primary production to soil water limitation was not identified by land submodels within Earth system models.Our results provide empirical evidence that global vegetation greenness and primary production are offset by water stress and suggest that as global warming continues,land submodels may overestimate the world’s capacity to take up carbon with global vegetation greening.

Risk Assessment of Vegetation Degradation Using Geographic Information System: A Case Study of Qareh Aghaj Basin,Iran

The entire land of Southern Iran faces problems arising out of various types of land degradation of which vegetation degradation forms one of the major types. The Qareh Aghaj basin（1 265 000 ha）,which covers the upper reaches of Mond River,has been chosen for a test risk assessment of this type. The different kinds of data for indicators of vegetation degradation were gathered from the records and published reports of the governmental offices of Iran. A new model has been developed for assessing the risk of vegetation degradation. Taking into consideration nine indicators of vegetation degradation the model identifies areas with ＂Potential Risk＂（risky zones） and areas of ＂Actual Risk＂ as well as projects the probability of the worse degradation in future. The preparation of risk maps based on the GIS analysis of these indicators will be helpful for prioritizing the areas to initiate remedial measures. By fixing the thresholds of severity classes of the nine indicators a hazard map for each indicator was first prepared in GIS. The risk classes were defined on the basis of risk scores arrived at by assigning the appropriate attributes to the indicators and the risk map was prepared by overlaying nine hazard maps in the GIS. Areas under actual risk have been found to be widespread（78%） in the basin and when the risk map classified into subclasses of potential risk with different probability levels the model projects a statistical picture of the risk of vegetation degradation.

Reconsidering the efficiency of grazing exclusion using fences on the Tibetan Plateau

Grazing exclusion using fences is a key policy being applied by the Chinese government to rehabilitate degraded grasslands on the Tibetan Plateau(TP)and elsewhere.However,there is a limited understanding of the effects of grazing exclusion on alpine ecosystem functions and services and its impacts on herders’livelihoods.Our meta-analyses and questionnaire-based surveys revealed that grazing exclusion with fences was effective in promoting aboveground vegetation growth for up to four years in degraded alpine meadows and for up to eight years in the alpine steppes of the TP.Longer-term fencing did not bring any ecological and economic benefits.We also found that fencing hindered wildlife movement,increased grazing pressure in unfenced areas,lowered the satisfaction of herders,and rendered substantial financial costs to both regional and national governments.We recommend that traditional free grazing should be encouraged if applicable,short-term fencing(for 4-8 years)should be adopted in severely degraded grasslands,and fencing should be avoided in key wildlife habitat areas,especially the protected large mammal species.