Incentives for low-input land-use types and their influence on the attractiveness of landscapes

Changes in agricultural policy have traceable effects on landscape aesthetics. For the catchment area of Lake Greifensee, an economic land-use model predicted land-use changes caused by agricultural policy. Three scenarios implementing different direct payment schemes show that land-use intensity will decrease by 2011 compared with the ‘reference status’ 2000.The output of the economic land-use model is explicit in space. It was assessed by the ‘naturalness’ perception factor of the method proposed by Hoisl et al. [1989. Landschaftsästhetik in der Flurbereinigung. Materialien zur Flurbereinigung—Heft 17. Bayerisches Staatsministerium für Ernährung, Landwirtschaft und Forsten, München] with regard to landscape aesthetics. Even though lower land-use intensity is generally predicted by 2011, the values of the ‘naturalness’ perception factor do not significantly improve if the payment scheme remains unchanged, or if the payment scheme is amended by incentives for specific location of the ecological compensation areas (ECAs). A significant reduction in the values of the ‘naturalness’ perception factor was found when subsidies for ECA's were cancelled. This leads us to the conclusion that in order to keep Swiss landscapes as attractive as they are at present, policy must sustain incentives for low-intensity land-use types.     

Sampling effort needed to estimate condition and species richness in the Ohio river, USA

The level of sampling effort required to characterize fish assemblage condition in a river for the purposes of bioassessment may be estimated via different approaches. However, the goal with any approach is to determine the minimum level of effort necessary to reach some specific level of confidence in the assessment. In the Ohio River, condition is estimated and reported primarily at the level of pools defined by lock and dam structures. The goal of this study was to determine the minimum level of sampling effort required to adequately characterize pools in the Ohio River for the purpose of bioassessment. We followed two approaches to estimating required sampling effort using fish assemblage data from a long-term intensive survey across a number of Ohio River pools. First, we estimated the number of samples beyond which variation in the multimetric Ohio River Fish Index (ORFIn) leveled off. Then, we determined the number of samples necessary to collect approximately 90% of the fish species observed across all samples collected within the pool. For both approaches, approximately 15 samples were adequate to reduce variation in IBI scores to acceptable levels and to capture 90% of observed species in a pool. The results of this evaluation provide a basis not only for the Ohio River Valley Water Sanitation Commission (ORSANCO) but also states and other basin commissions to develop sampling designs for bioassessment that ensure adequate sampling of all assessment units.     

Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China

Land surface temperature （LST）, which is heavily influenced by urban surface structures, is a significant parameter in urban environmental analysis. This study examined the effect impervious surfaces （IS） spatial patterns have on LST in Beijing, China. A classification and regression tree model （CART） was adopted to estimate IS as a continuous variable using Landsat images from two seasons combined with QuickBird. LST was retrieved from the Landsat Thematic Mapper （TM） image to examine the relationships between IS and LST. The results revealed that CART was capable of consistently predicting LST with acceptable accuracy （correlation coefficient of 0.94 and the average error of 8.59%）. Spatial patterns of IS exhibited changing gradients across the various urban-rural transects, with LST values showing a concentric shape that increased as you moved from the outskirts towards the downtown areas. Transect analysis also indicated that the changes in both IS and LST patterns were similar at various resolution levels, which suggests a distinct linear relationship between them. Results of correlation analysis further showed that IS tended to be positively correlated with LST, and that the correlation coefficients increased from 0.807 to 0.925 with increases in IS pixel size. The findings identified in this study provide a theoretical basis for improving urban planning efforts to lessen urban temperatures and thus dampen urban heat island effects.     

Hydrologic Effects of Surface Coal Mining in Appalachia (U.S.)

Surface coal mining operations alter landscapes of the Appalachian Mountains, United States, by replacing bedrock with mine spoil, altering topography, removing native vegetation, and constructing mine soils with hydrologic properties that differ from those of native soils. Research has demonstrated hydrologic effects of mining and reclamation on Appalachian landscapes include increased peakflows at newly mined and reclaimed watersheds in response to strong storm events, increased subsurface void space, and increased base flows. We review these investigations with a focus on identifying changes to hydrologic flow paths caused by surface mining for coal in the Appalachian Mountains. We introduce two conceptual control points that govern hydrologic flow paths on mined lands, including the soil surface that partitions infiltration vs. surface runoff and a potential subsurface zone that partitions subsurface storm flow vs. deeper percolation. Investigations to improve knowledge of hydrologic pathways on reclaimed Appalachian mine sites are needed to identify effects of mining on hydrologic processes, aid development of reclamation methods to reduce hydrologic impacts, and direct environmental mitigation and public policy.