Rainfall-runoff modelling is widely used for runoff estimation at the catchment scale. However, its simulation capability is sometimes influenced because of rapid land cover changes occurring in catchments. This paper investigates whether modification of a rainfall-runoff model, Xinanjiang, by the incorporation of dynamic remote sensing data (MODIS leaf area index (LAI) and albedo) can improve runoff estimates for four south-east Australian catchments which experienced severe bushfire impacts.

Land surface topography is one of the most important terrain properties which impact hydrological, geomorphological, and ecological processes active on a landscape. In our previous efforts to develop a soil depth model based upon topographic and land cover variables, we derived a set of hydrological proximity measures (HPMs) from a Digital Elevation Model (DEM) as potential explanatory variables for soil depth.

Traditionally, management of rangelands is based on the successional theory for vegetation developed by Clements. This approach, which came to be known as “the range succession model”, assumes a progressive change of vegetation towards the final (climax) stage and considers grazing as a primary driver of its dynamics. This model cannot be applied in Mediterranean rangelands, however, because they are largely modified plant communities and their final stage is usually a forest or dense woodland.

Land‐cover change and ecosystem degradation may lead to biotic homogenization, yet our understanding of this phenomenon over large spatial scales and different biotic groups remains weak. We used a multi‐taxa dataset from 335 sites and 36 heterogeneous landscapes in the Brazilian Amazon to examine the potential for landscape‐scale processes to modulate the cumulative effects of local disturbances.

This work addresses the estimation of net surface longwave radiation (NSLR) from net surface shortwave radiation (NSSR) by analysing the Surface Radiation Budget Network (SURFRAD) radiation data under cloudy conditions. A general model is developed to estimate NSLR from the NSSR for cloudy skies with a root mean square error (RMSE) of 23.16 W m⁻² compared with in situ data. The model is applied to AmeriFlux data. The results show that the mean error and RMSE are –2.31 W m⁻² and 29.25 W m⁻², respectively, compared with the measurement of AmeriFlux.

Human activities influence the biodiversity of Mediterranean ecosystems and are involved in the transformation of natural habitats into farmland. We surveyed birds using the point count method on 288 plots at a 50-m radius in three altitudinal landscapes with different rural character in spring and autumn. The results showed that bird species richness in the study area was high (74 species). High total species richness was found in the upland rural landscape characterized by mixed land use and high landscape diversity.

In order to identify sustainable management solutions for small-scale farmer agroecosystems, a better understanding of these dynamic forest–farmland systems, existing farming and forestry strategies, and farmer perspectives is important. We examined the relationship between agricultural land use patterns and farmers’ practices and identified existing and potential characteristics of healthy agroecosystems at local scale in the context of village communities in Zanzibar, Tanzania.

We report estimates of the amount, distribution, and uncertainty of aboveground biomass (AGB) of the different ecoregions and forest land cover classes within the North American boreal forest, analyze the factors driving the error estimates, and compare our estimates with other reported values. A three-phase sampling strategy was used (i) to tie ground plot AGB to airborne profiling lidar metrics and (ii) to link the airborne estimates of AGB to ICESat-GLAS lidar measurements such that (iii) GLAS could be used as a regional sampling tool.

Land surface change caused by fires and succession is confounded by many site-specific factors and requires further study. The objective of this study was to reveal the spatially explicit land surface change by minimizing the confounding factors of weather variability, seasonal offset, topography, land cover, and drainage. In a pilot study of the Yukon River Basin of interior Alaska, we retrieved Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) from a postfire Landsat image acquired on August 5th, 2004.

The ecological integrity of lotic ecosystems is intimately linked to the quality of their catchments. Environmental protection efforts should therefore be implemented at the relevant catchment-scale in order to support river biodiversity and associated ecosystem services. Therefore, freshwater management can greatly benefit from tools that enable spatially-explicit predictions of water quality across heterogeneous landscapes.

The Huajiang and Hongfenghu demonstration areas represent typical karst landforms and rocky desertification landscapes in Guizhou, China. These were selected for a comparison of rocky desertification and land use cover. Based mainly on 5� m resolution Spot 5, remote sensing images, topographic maps (1:10,000) and land use maps, the intensity and extent of rocky desertification, and slope characteristics of the two areas were interpreted. Spatial overlay analysis was used to compare the land use/land cover (LULC) and rocky desertification within each.

The aquatic vegetation of Číčov Lake in the Danube floodplain, which is listed in the Ramsar Convention, was investigated to address three main questions: (1) how have landscape composition and the structures of the lake and its buffer zone changed from the mid-20th century; (2) how have species richness and the abundance of the aquatic macrophyte assemblage in this lake ecosystem changed over the last 34 years; and (3) which landscape metrics can best explain these temporal changes for floating-leaved macrophytes?