Scale Effects on the Calculation of Ecosystem Service Values: A Comparison among Results from Different LULC Datasets

Land use/land cover (LULC) has an important impact on the ecological environment and is crucial for calculating ecosystem service values (ESVs). However, whether and to what extent the ESVs vary when calculated by LULC product data at different spatial scales remain unclear. Data from two LULC products were used in this study, and two datasets with different spatial scales were obtained by resampling. Then, the ESVs were calculated by the equivalent factor method. Finally, the impacts of LULC on ESVs at different scales were studied, revealing the following: (1) The ESVs calculated by LULC products and by the same products at different scales are different. (2) The difference in the ESVs calculated by the two LULC datasets is approximately 28%, and the difference tends to decrease with increasing scale. (3) With an increase in the LULC scale, the overall change trend of ESVs also increases, and the increasing trend gradually moderates. In addition, the ESVs and LULC scale conform to a logarithmic relationship, and the coefficient of determination (R2) is greater than 0.7. These results have important reference value for obtaining reliable ESVs.

Temporal variation of patch connectivity determines biodiversity recovery from recurrent disturbances

Understanding the capacity of ecological systems to withstand and recover from disturbances is a major challenge for ecological research in the context of environmental change. Disturbances have multi-scale effects: they can cause species extinctions locally and alter connectivity between habitat patches at the metacommunity level. Yet, our understanding of how disturbances influence landscape connectivity remains limited. To fill this gap, we develop a novel connectivity index that integrates the temporal variation of patch connectivity induced by disturbances, which can be applied to any spatially-structured habitat. We then combine this index with a metacommunity model to specifically investigate biodiversity recovery from drying events in river network metacommunities. We demonstrate that patch connectivity explains variations of species richness between groups of organisms with contrasting dispersal modes and captures the effect of drying intensity (i.e., fraction of patches that dry-up) and drying location on community recovery. As a general rule, loss of patch connectivity decreases community recovery, regardless of patch location in the river network, dispersal mode, or drying intensity. Local communities of flying organisms maintained higher patch connectivity in drying river networks compared to organisms with strictly aquatic dispersal, which explained the higher recovery capacity of this group from drying events. The general relationship between patch connectivity and community recovery we found can be applied to any spatial network subject to temporal variation of connectivity, thus providing a powerful tool for biodiversity management in dynamic landscapes.

Analysis of the spatial differentiation and scale effects of the three-dimensional architectural landscape in Xi’an, China

Three-dimensional landscape patterns are an effective means to study the relationship between landscape pattern evolution and eco-environmental effects. This paper selects six districts in Xi’an as the study area to examine the spatial distribution characteristics of the three-dimensional architectural landscape in the city’s main urban area using three-dimensional information on the buildings in 2020 with the support of GIS. In this study, two new architectural landscape indices—landscape height variable coefficient and building rugosity index—were employed in landscape pattern analysis, whilst a system of rigorous and comprehensive three-dimensional architectural landscape metrics was established using principal component analysis. A mathematical model of weighted change of landscape metrics based on the objective weighting method was applied to carry out scale analysis of the landscape patterns. Spatial statistical analysis and spatial autocorrelation analysis were conducted to comprehensively study the differentiation of three-dimensional architectural landscape spatial patterns. The results show that the characteristic scale of the three-dimensional landscape pattern in Xi’an’s main urban area is around 8 km. Moreover, the three-dimensional landscape of the buildings in this area is spatially positively correlated, exhibiting a high degree of spatial autocorrelation whilst only showing small spatial differences. The layout of the architectural landscape pattern is disorderly and chaotic within the second ring, whilst the clustering of patch types occurs near the third ring. Moreover, the building density in the Beilin, Lianhu, and Xincheng districts is large, the building height types are rich, and the roughness of the underlying surface is high, such that these are key areas to be improved through urban renewal. The height, volume, density, morphological heterogeneity, and vertical roughness of the architectural landscape vary amongst functional areas within the study area. This paper is the first to apply the study of spatial heterogeneity of three-dimensional landscape patterns to Xi’an. It does so in order to provide a quantitative basis for urban landscape ecological design for urban renewal and the rational planning of built-up areas, which will promote the sustainable development of the city’s urban environment.

Spurious Correlation Due to Scaling

Scaling is common in empirical accounting research. It is often done to mitigate heteroscedasticity or the influence of firm size on parameter estimates. However, Barth and Clinch conclude that common diagnostic tools are ineffective in detecting various scale effects. Using analytic results and Monte Carlo simulations, we show that common forms of scaling, when misapplied, induce substantial spurious correlation via biased parameter estimates. Researchers, when uncertain about the exact functional form of scale effect, are typically better off dealing with both heteroscedasticity and the influence of larger firms using techniques other than scaling.

CRITICAL REVIEW OF MODERN NUMERICAL MODELLING OF SNOW ACCUMULATION ON ROOFS WITH ARBITRARY GEOMETRY

The calculation of snow loads on roofs of buildings and structures with arbitrary geometry is a complex problem, solving which requires simulating snow accumulation with acceptable engineering accuracy. Experiments in wind tunnels, although widely used in recent years, do not allow to reproduce the real full-scale effects of all snow transport subprocesses, since it is impossible to satisfy all the similarity conditions. This situation, coupled with the continuous improvement of mathematical models, numerical methods, computer technologies and related software, makes the development and future implementation of numerical modelling in real construction practice and regulatory documents inevitable. This paper reviews currently existing mathematical models and numerical methods used to calculate the forms of snow deposits. And, although the lack of significant progress in the field of modelling snow accumulation still remains one of the major problems in CFD, use of existing models, supported by field observations and experimental data, allows to reproduce reasonably accurate snow distributions. The importance of the “symbiosis” between classical experimental methods and modern numerical models is specifically emphasized in the paper, as well as the fact that only the joint use of approaches can comprehensively describe modelling of snow accumulation and snow transport and provide better solutions to a wider range of problems.