Coupling Human and Natural Systems for Sustainability: Experiences from China’s Loess Plateau

Addressing the sustainability challenges facing humanity in the Anthropocene requires the coupling of human and natural systems, rather than their separate treatment. To understand the dynamics of a coupled human and natural system (CHANS) and promote its sustainability, we proposed a conceptual cascade framework of “Pattern-Process-Service-Sustainability”. The use of this framework was systematically illustrated by a review of CHANS research experiences in China’s Loess Plateau (LP) in terms of coupling landscape patterns and ecological processes, linking ecological processes to services, and promoting social-ecological sustainability. The LP is well-known for its historically notorious soil erosion and successful vegetation restoration achieved in recent decades. Vegetation coverage in the LP has increased since 2000 due to ecological restoration. Soil erosion has been well controlled and the sediment deriving from the LP, and flowing into the Yellow River, has greatly decreased; however, overplanting, the introduction of exotic plant species, and the mismanagement of planted vegetation have also led to soil drying in some areas. Ecosystem services, especially for soil conservation and carbon sequestration, have significantly improved, although a trade-off between carbon sequestration and water supply has been identified at multiple scales. Based on the comprehensive understanding of CHANS dynamics, targeted policy and management suggestions are here proposed to support the social-ecological sustainability of the LP. The research experience accumulated on the LP offers examples of the application of the “Pattern-Process-Service-Sustainability” framework. Future research using this framework should especially examine the integrated research of multiple processes, the cascades of ecosystem structure, function, services, and human-wellbeing, the feedback mechanisms of human and natural systems, and the data and models for sustainability.

Response of Variation of Water and Sediment to Landscape Pattern in the Dapoling Watershed

The relationship between water-sediment processes and landscape pattern changes has currently become a research hotspot in low-carbon water and land resource optimization research. The SWAT-VRR model is a distributed hydrological model which better shows the effect of land use landscape change on hydrological processes in the watershed. In this paper, the hydrological models of the Dapoling watershed were built, the runoff and sediment yield from 2006 to 2011 were simulated, and the relationship between landscape patterns and water-sediment yield was analyzed. The results show that the SWAT-VRR model is more accurate and reasonable in describing runoff and sediment yield than the SWAT model. The sub-basins whose soil erosion is relatively light are mostly concentrated in the middle reaches with a slope mainly between 0–5°. The NP, PD, ED, SPIIT, SHEI, and SHDI of the watershed increased slightly, and the COHESION, AI, CONTAG, and LPI showed a certain decrease. The landscape pattern is further fragmented, with the degree of landscape heterogeneity increasing and the connection reducing. The runoff, sediment yield and surface runoff are all extremely significantly negatively correlated with forest, which implies that for more complicated patch shapes of forest which have longer boundaries connecting with the patches of other landscape types, the water and sediment processes are regulated more effectively. Therefore, it can be more productive to carry out research on the optimization of water and soil resources under the constraint of carbon emission based on the SWAT-VRR model.

On the Scale Effect of Relationship Identification between Land Surface Temperature and 3D Landscape Pattern: The Application of Random Forest

Urbanization processes greatly change urban landscape patterns and the urban thermal environment. Significant multi-scale correlation exists between the land surface temperature (LST) and landscape pattern. Compared with traditional linear regression methods, the regression model based on random forest has the advantages of higher accuracy and better learning ability, and can remove the linear correlation between regression features. Taking Beijing’s metropolitan area as an example, this paper conducted multi-scale relationship analysis between 3D landscape patterns and LST using Pearson Correlation Coefficient (PCC), Multiple Linear Regression and Random Forest Regression (RFR). The results indicated that LST was relatively high in the central area of Beijing, and decreased from the center to the surrounding areas. The interpretation effect of 3D landscape metrics on LST was more obvious than that of the 2D landscape metrics, and 3D landscape diversity and evenness played more important roles than the other metrics in the change of LST. The multi-scale relationship between LST and the landscape pattern was discovered in the fourth ring road of Beijing, the effect of the extent of change on the landscape pattern is greater than that of the grain size change, and the interpretation effect and correlation of landscape metrics on LST increase with the increase in the rectangle size. Impervious surfaces significantly increased the LST, while the impervious surfaces located at low building areas were more likely to increase LST than those located at tall building areas. It seems that increasing the distance between buildings to improve the rate of energy exchange between urban and rural areas can effectively decrease LST. Vegetation and water can effectively reduce LST, but large, clustered and irregularly shaped patches have a better effect on land surface cooling than small and discrete patches. The Coefficients of Rectangle Variation (CORV) power function fitting results of landscape metrics showed that the optimal rectangle size for studying the relationship between the 3D landscape pattern and LST is about 700 m. Our study is useful for future urban planning and provides references to mitigate the daytime urban heat island (UHI) effect.

Agriculturally Intensified Landscapes Are Associated With Reduced Body Condition of Lady Beetles

Context: Agricultural intensification is contributing to a global species decline. Underlying mechanisms include toxic effects of pesticides on non-target organisms and reductions in habitat and food availability. However, the effects of agricultural intensification on body condition, particularly of ecosystem service providing arthropods, are poorly understood.Objectives: Here, we investigated whether variations in the body condition of common lady beetle species (Coleoptera: Coccinellidae) can be explained by the composition and configuration of the surrounding landscape. Assuming strong seasonal variation in food availability in intensively farmed regions, we included the entire period of lady beetle activity in our study.Methods: Lady beetles were collected from April to September 2011 in 30 landscapes in southern Wisconsin, USA. We examined how body size, body density, and lipid content of the beetles responded to the percentage of intensive cropland, habitat diversity, and edge density in the surrounding landscape.Results: The strongest predictor of body condition was the percentage of intensive cropland. For every 10% increase in cropland, body density decreased by about 3.9% and fat content by 6.4%. Landscape diversity and edge density correlated with body condition of individual species.Conclusions: In agriculturally intensified landscapes, lady beetles with reduced body condition may produce fewer offspring, have lower survival rates, and exert less effective pest control. Thus, our results suggest a mechanistic link between landscape patterns and observed declines in lady beetle populations. Our results also show that the expansion of monocultures affects even common cropland-associated species such as Harmonia axyridis, suggesting a long-term decline in biocontrol services in simplified agricultural landscapes.

Study of the Landscape Pattern of Shuiyu Village in Beijing, China: A Comprehensive Analysis of Adaptation to Local Microclimate

The paper used technical parameters to investigate optimized solutions to protect the ecological environment and improve the microclimate adaptability among the traditional villages in Beijing. Shuiyu Village was used as a case study to analyze the coupling relationship between landscape patterns and the microclimate of traditional villages, with a focus on the ecological relationship between residents and the microclimate. This study also developed a climate index system, which includes computer numerical simulation and microclimate comprehensive analysis methods. The distinct types of landscape patterns were studied using the system. In addition, this paper studied the adaptive design mechanism in-depth, the form parameters of comfort evaluation controllability, and map expression technology of morphological parameters. The findings of this study include the optimized value of the environment based on landscape pattern and the map through the Rhino modeling platform. An interactive platform was developed, and a parametric-assisted optimization design process for traditional villages in the northern part of China was proposed. Moreover, this study concluded optimized strategies and technical guidelines for future planning of the rural areas in northern China with a goal to protect traditional villages and transform them into smart villages with microclimate adaptability.

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.