Effects of spatially structured vegetation patterns on hillslope erosion in a semiarid Mediterranean environment: a simulation study

A general trend of decreasing soil loss rates with increasing vegetation cover fraction is widely accepted. Field observations and experimental work, however, show that the form of the cover‐erosion function can vary considerably, in particular for low cover conditions that prevail on arid and semiarid hillslopes. In this paper the structured spatial distribution of the vegetation cover and associated soil attributes is proposed as one of the possible causes of variation in cover–erosion relationships, in particular in dryland environments where patchy vegetation covers are common. A simulation approach was used to test the hypothesis that hillslope discharge and soil loss could be affected by variation in the spatial correlation structure of coupled vegetation cover and soil patterns alone. The Limburg Soil Erosion Model (LISEM) was parameterized and verified for a small catchment with discontinuous vegetation cover at Rambla Honda, SE Spain. Using the same parameter sets LISEM was subsequently used to simulate water and sediment fluxes on 1 ha hypothetical hillslopes with simulated spatial distributions of vegetation and soil parameters. Storms of constant rainfall intensity in the range of 30–70 mm h^?1 and 10–30 min duration were applied. To quantify the effect of the spatial correlation structure of the vegetation and soil patterns, predicted discharge and soil loss rates from hillslopes with spatially structured distributions of vegetation and soil parameters were compared with those from hillslopes with spatially uniform distributions. The results showed that the spatial organization of bare and vegetated surfaces alone can have a substantial impact on predicted storm discharge and erosion. In general, water and sediment yields from hillslopes with spatially structured distributions of vegetation and soil parameters were greater than from identical hillslopes with spatially uniform distributions. Within a storm the effect of spatially structured vegetation and soil patterns was observed to be highly dynamic, and to depend on rainfall intensity and slope gradient. Copyright © 2005 John Wiley & Sons, Ltd.     

The role of vegetation patterns in structuring runoff and sediment fluxes in drylands

The dynamics of vegetation‐driven spatial heterogeneity (VDSH) and its function in structuring runoff and sediment fluxes have received increased attention from both geomorphological and ecological perspectives, particularly in arid regions with sparse vegetation cover. This paper reviews the recent findings in this area obtained from field evidence and numerical simulation experiments, and outlines their implications for soil erosion assessment. VDSH is often observed at two scales, individual plant clumps and stands of clumps. At the patch scale, the local outcomes of vegetated patches on soil erodibility and hydraulic soil properties are well established. They involve greater water storage capacity as well as increased organic carbon and nutrient inputs. These effects operate together with an enhanced capacity for the interception of water and windborne resources, and an increased biological activity that accelerates breakdown of plant litter and nutrient turnover rates. This suite of relationships, which often involve positive feedback mechanisms, creates vegetated patches that are increasingly different from nearby bare ground areas. By this way a mosaic builds up with bare ground and vegetated patches coupled together, respectively, as sources and sinks of water, sediments and nutrients. At the stand scale within‐storm temporal variability of rainfall intensity controls reinfiltration of overland flow and its decay with slope length. At moderate rainfall intensity, this factor interacts with the spatial structure of VDSH and the mechanism of overland flow generation. Reinfiltration is greater in small‐grained VDSH and topsoil saturation excess overland flow. Available information shows that VDSH structures of sources and sinks of water and sediments evolve dynamically with hillslope fluxes and tune their spatial configurations to them. Rainfall simulation experiments in large plots show that coarsening VDSH leads to significantly greater erosion rates even under heavy rainfall intensity because of the flow concentration and its velocity increase. Copyright © 2005 John Wiley & Sons, Ltd.     

Soil respiration in tropical seasonal rain forest in Xishuangbanna, SW China

With the static opaque chamber and gas chromatography technique, from January 2003 to January 2004 soil respiration was investigated in a tropical seasonal rain forest in Xishuangbanna, SW China. In this study three treatments were applied, each with three replicates: A (bare soil), B (soil+litter), and C (soil+litter+seedling). The results showed that soil respiration varied seasonally, low from December 2003 to February 2004, and high from June to July 2004. The annual average values of CO2 efflux from soil respiration differed among the treatments at 1% level, with the rank of C (14642 mgCO2· m-2. h-1)＞B (12807 mgCO2· m-2. h-1)＞A (9532 mgCO2· m-2. h-1). Diurnal variation in soil respiration was not apparent due to little diurnal temperate change in Xishuangbanna. There was a parabola relationship between soil respiration and soil moisture at 1% level. Soil respiration rates were higher when soil moisture ranged from 35% to 45%. There was an exponential relationship between soil respiration and soil temperature (at a depth of 5cm in mineral soil) at 1% level. The calculated Q1o values in this study,ranging from 2.03 to 2.36, were very near to those of tropical soil reported. The CO2 efflux in 2003was 5.34 kgCO2· m-2. a-1 from soil plus litter plus seedling, of them 3.48 kgCO2· m-2. a-1 from soil (accounting for 62.5%), 1.19 kgCO2· m-2. a-1 from litter (22.3%) and 0.67 kgCO2·m-2. a-1 from seedling (12.5%).     

The diurnal and seasonal characteristics of urban heat island variation in Beijing city and surrounding areas and impact factors based on remote sensing satellite data

Based on the land surface temperature (LST), the land cover classification map,vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains,especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃ between Beijing city and suburb areas, comparatively is 8- 10℃ between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative.The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481).The results demonstrate that the vegetation greenness is an important factor for reducing the UHI,and large-scale construction of greenbelts can considerably reduce the UHI effect.     

Effect of the Mahanadi River on the Development of Storm Surge Along the Orissa Coast of India: A Numerical Study

River-ocean coupled models are described for the evaluation of the interaction between river discharge and surge development along the Orissa coast of India. The models are used to study the effect of fresh water discharge from the Mahanadi River on the surge response along the Orissa coast due to the October 1999 super cyclone which led to severe flooding of the coastal and delta regions of Orissa. The so-called 1999 Paradip cyclone was one of the most severe cyclones; causing extensive damage to property and loss of lives. The present study emphasizes the impact of the Mahanadi River on overall surge development along the Orissa coast. Therefore, we have developed a location specific fine resolution model for the Orissa coast and coupled it with a one–dimensional river model. The numerical experiments are carried out, both with and without inclusion of fresh water discharge from the river. The bathymetry for the model has been taken from the naval hydrographic charts extending from the south of Orissa to the south of west Bengal. A simple drying scheme has also been included in the model in order to avoid the exposure of land near the coast due to strong negative sea-surface elevations. The simulations with river-ocean coupled models show that the discharge of fresh water carried by the river may modify the surge height in the Bay, especially in the western Bay of Bengal where one of the largest river systems of the east coast of India, the Mahanadi River, joins with the Bay of Bengal. Another dynamic effect of this inlet is the potentially deep inland penetration of the surge originating in the Bay. The model results are in good agreement with the available observations/estimates.     

森林沼泽景观区中大比例尺化探找矿工作方法的研究--记大梁金矿的发现

大梁金矿是通过森林沼泽景观区开展1：50000和1：25000地球化学测量及综合地质工作而发现的,证明采用的森林沼泽景观中大比例尺化探方法是行之有效的.     

DEFORESTATION IN NORTHEAST THAILAND, 1975–91: RESULTS OF A GENERAL STATISTICAL MODEL

Using a general statistical model, this study attempts to characterise the trend of deforestation in the northeast region (Isan) of Thailand between 1975 and 1991, a period when the kingdom had sustained high rates of economic growth and steady increases in population. Using data obtained directly from government bodies on the 17 provinces comprising this heavily deforested region, the study examines the correlations between forest area and a set of six variables: population density, agricultural area, real per capita income, accumulated irrigated area, agricultural credit levels, and distance from Bangkok, the national political and economic centre. It also considers the effect of the two logging bans instituted in 1979 and since 1989. The study found a negative correlation between forest area and population density in particular, followed in ranking by agricultural credit, per capita income, the logging bans and distance from Bangkok. Viewed together with more recent data showing that rates of deforestation in the kingdom as a whole have slowed and appear to be stabilising, these results also suggest the beginnings in the 1990s of a forest transition – from an industrial to a post‐industrial stage in forest utilisation – in Thailand.     

Leaf area index retrieval based on canopy reflectance and vegetation index in eastern China

The aim of this paper is to investigate the feasibility of using Landsat TM data to retrieve leaf area index (LAI). To get a LAI retrieval model based ground reflectance and vegetation index, detailed field data were collected in the study area of eastern China, dominated by bamboo, tea plant and greengage. Plant canopy reflectance of Landsat TM wavelength bands has been inversed using software of 6S. LAI is an important ecological parameter. In this paper, atmospheric corrected Landsat TM imagery was utilized to calculate different vegetation indices (VI), such as simple ratio vegetation index (SR), shortwave infrared modified simple ratio (MSR), and normalized difference vegetation index (NDVI). Data of 53 samples of LAI were measured by LAI-2000 (LI-COR) in the study area. LAI was modeled based on different reflectances of bands and different vegetation indices from Landsat TM and LAI samples data. There are certainly correlations between LAI and the reflectance of Tm3, TM4, TM5 and TM7. The best model through analyzing the results is LAI = 1.2097*MSR + 0.4741 using the method of regression analysis. The result shows that the correlation coefficient R2 is 0.5157, and average accuracy is 85.75%. However, whether the model of this paper is suitable for application in subtropics needs to be verified in the future.     

Incorporating Spatial Dependence in Predictive Vegetation Models: Residual Interpolation Methods*

Predictive vegetation modeling can be used statistically to relate the distribution of vegetation across a landscape as a function of important environmental variables. Often these models are developed without considering the spatial pattern that is inherent in biogeographical data, resulting from either biotic processes or missing or misspecified environmental variables. Including spatial dependence explicitly in a predictive model can be an efficient way to improve model accuracy with the available data. In this study, model residuals were interpolated and added to model predictions, and the resulting prediction accuracies were assessed. Adding kriged residuals improved model accuracy more often than adding simulated residuals, although some alliances showed no improvement or worse accuracy when residuals were added. In general, the prediction accuracies that were not increased by adding kriged residuals were either rare in the sample or had high nonspatial model accuracy. Regression interpolation methods can be an important addition to current tools used in predictive vegetation models as they allow observations that are predicted well by environmental variables to be left alone, while adjusting over‐ and underpredicted observations based on local factors.     

Local provenance in rehabilitation of degraded landscapes: a case study from the Hawkesbury–Nepean catchment, Australia

Throughout Australia thousands of volunteers are engaged in Landcare projects that should help rehabilitate degraded landscapes. Many of these projects involve tree planting, but their seed is not necessarily of local provenance. Based on a survey of 85 Landcare groups working in the Hawkesbury–Nepean catchment, data were collected about Landcare groups' knowledge of their seed source, understanding of local provenance and the ecosystem in which they were planting trees and the source of funding for their projects. The findings from the study indicate that about one in five (21%) of the groups surveyed that introduced plant material were not aware of local provenance issues. Indirect indications were that a large number of Landcare groups state-wide may be doing more harm than good to the landscape while trying to rehabilitate it. The data also showed that one in seven (13%) of the groups funded by the Australian Government through the Natural Heritage Trust (NHT) had limited awareness of local provenance issues. With millions of dollars being spent on 'works on the ground', it would be prudent to allocate some funds to document and monitor current Landcare activities, so that the environmental outcomes can be quantified and more effective Landcare policies can be developed in the future.