Evaluating the impact of landscape configuration, patterns and composition on land surface temperature: an urban heat island study in the Megacity Lahore, Pakistan.

The urban heat island (UHI) phenomenon is negatively impacted by rapid urbanization, which significantly affects people's everyday lives, socioeconomic activities, and the urban thermal environment. This study focuses on the impact of composition, configuration, and landscape patterns on land surface temperature (LST) in Lahore, Pakistan. The study uses Landsat 5-TM and Landsat 8-OLI/TIRS data acquired over the years 2000, 2010 and 2020 to derive detailed information on land use, normalized difference vegetation index, LST, urban cooling islands (UCI), green cooling islands (GCI) and landscape metrics at the class and landscape level such as percentage of the landscape (PLAND), patch density (PD), class area (CA), largest patch index (LPI), number of patches (NP), aggregation index (AI), Landscape Shape Index (LSI), patch richness (PR), and mean patch shape index (SHAPE_MN). The study's results show that from the years 2000 to 2020, the built-up area increased by 17.57%, whereas vacant land, vegetation, and water bodies declined by 03.79%, 13.32% and 0.4% respectively. Furthermore, landscape metrics at the class level (PLAND, LSI, LPI, PD, AI, and NP) show that the landscape of Lahore is becoming increasingly heterogeneous and fragmented over time. The mean LST in the study area exhibited an increasing trend i.e. 18.87°C in 2000, 20.93°C in 2010, and 22.54°C in 2020. The significant contribution of green spaces is vital for reducing the effects of UHI and is highlighted by the fact that the mean LST of impervious surfaces is, on average, roughly 3°C higher than that of urban green spaces. The findings also demonstrate that there is a strong correlation between mean LST and both the amount of green space (which is negative) and impermeable surface (which is positive). The increasing trend of fragmentation and shape complexity highlighted a positive correlation with LST, while all area-related matrices including PLAND, CA and LPI displayed a negative correlation with LST. The mean LST was significantly correlated with the size, complexity of the shape, and aggregation of the patches of impervious surface and green space, although aggregation demonstrated the most constant and robust correlation. The results indicate that to create healthier and more comfortable environments in cities, the configuration and composition of urban impermeable surfaces and green spaces should be important considerations during the landscape planning and urban design processes.

Impacts of landscape patterns on plant species diversity at a global scale.

Landscape patterns are important drivers of biodiversity. Owing to differences in vegetation types, sampling methods, diversity measures, spatial scales, and landscape levels, the impact of landscape patterns on biodiversity remains widely debated. Using a global standardized plant community database and land use and land cover maps at 30-m resolution, for the period 1990-2017, we calculated plant species α- and ß-diversity, and landscape metrics at patch- and landscape-levels, and discerned the direct and indirect impacts of landscape patterns on plant species diversity based on environmental factors, namely climate, spatial features, and human disturbance. We found that landscape patterns exhibited the main indirect effects, whereas climate factors exhibited dominant direct effects on plant α-diversity via the direct effects of patch patterns and functional traits. With respect to ß-diversity, landscape-level patterns exerted more direct than indirect effects. These effects are strongly dependent on scale. Landscape- and patch-level patterns had opposite effects on plant diversity, depending on their composition and spatial structure, demonstrating that their effects could be mediated by one another. The adaptation of plants to landscape patterns is mainly through variations in leaf area, plant height, specific leaf area, stem density, seed biomass, and other seed-dispersal traits, which vary across vegetation types. Our findings highlight the importance of functional traits and diversity in understanding the mechanism by which landscape patterns influence plant species diversity; accordingly, we recommend balancing the spatial structure of patch- and landscape-level patterns to enhance variation in functional traits, and, ultimately, to maintain global plant diversity.

Understanding supply-demand mismatches in ecosystem services and interactive effects of drivers to support spatial planning in Tianjin metropolis, China.

Metropolitan areas are being challenged by the disparity between growing societal needs and dwindling natural resource provision. Understanding the supply-demand mismatches of ecosystem services (ES) and their drivers is essential for landscape planning and decision-making. However, integrating such information into spatial planning remains challenging due to the complex nature of urban ecosystems and their intrinsic interactions. In this study, we first assessed and mapped the supply, demand, and mismatches of six typical ES in Tianjin, China. We then clustered numerous townships based on their corresponding spatial characteristic of ES supply-demand mismatches. We also used Random Forest regression to examine the relative importance of drivers and applied Partial Least Squares structural equation modelling to decouple their interactions. The results showed that, the distribution of ES supply and demand showed obvious spatial heterogeneity, with a common surplus of ES supply in highly natural mountainous region and an excess of demand in urban centre. Additionally, all towns were classified into four spatial clusters with homogeneous states of supply-demand mismatches, serving as basic units for spatial optimization. Moreover, the interactions between drivers affected ES supply-demand mismatches in a coupled manner, including the direct effects of the socioeconomic factor (-0.821) and landscape composition (0.234), as well as the indirect effects of the biophysical factor (0.151) and landscape configuration (0.082). Finally, we discussed the utility of analysing the spatial mismatches between ES supply and demand for integrated territorial planning and coordinated decision-making.

Investigating relationships between landscape patterns and surface runoff from a spatial distribution and intensity perspective.

Rapid urbanization changes landscape patterns and results in frequent urban waterlogging issues, which affect citizens' daily lives and cause economic loss. Understanding the spatial patterns and impact factors associated with urban waterlogging under different rainfall intensities has significant implications for mitigating this hazard. In this study, the runoff depth calculated according to the Storm Water Management Model (SWMM) simulation results was used to investigate the spatial characteristics of urban waterlogging. Multiple scenario-based designs, a correlation analysis, and a stepwise regression model were employed to detect the relationship between surface runoff depth and landscape patterns under different rainfall intensities. The results show that when the rainfall intensity reached 12.5 mm/12 h, the conversion rate of rainfall to runoff increased significantly, indicating an increased waterlogging risk. Areas with impervious surface proportions of 25-50% and 75-100% were shown to require more attention due to the strong sensitivity of the surface runoff depth to an increase in the impervious surface. It is most cost-effective to maintain the original high-density vegetation or increase the vegetation density from 0-25% to 25-50% for urban green space. Additionally, the landscape configuration also affects the surface runoff depth. The fragmented, scattered, or regular shape of impervious surface patches can reduce surface runoff effectively; larger and less fragmented green space was also shown to have a surface runoff controlling. The adjusted R2 values were greater than 0.6 for all stepwise regression models, indicating that the landscape variables selected in the study can effectively predict the surface runoff depth. These models also showed that the landscape composition had a more profound contribution than the landscape configuration on runoff depth. These findings provide meaningful insights and perspectives for urban waterlogging hazard mitigation, quantitative landscape planning, and risk management. The method proposed by this study provides a referable framework for future studies on urban waterlogging and its response to the landscape in the context of global climate change.

Dynamic of land use, landscape, and their impact on ecological quality in the northern sand-prevention belt of China.

Changes in land use and landscapes have a direct impact on the regional eco-environment. It is of great importance to understand the change pattern of land use, landscapes, and their mechanism on the ecological quality, especially ecologically fragile areas. The northern sand-prevention belt (NSPB) is an important ecologically fragile area in China, which has a large influence on the ecological security of the entire country. Based on the land use data of the NSPB in 2000, 2010, and 2018, we studied the spatio-temporal characteristics of land-use change and change in landscape patterns. The ecological quality represented by the remote sensing-based desertification index (RSDI) was calculated using satellite images. The effects of land use and landscape patterns on RSDI were analyzed by geographic detector and geographically weighted regression. Important results include the following: (1) Land-use change in the study area was high during 2000-2010 but slower in 2010-2018. Grassland was the largest land-use type in the NSPB, and varied greatly in terms of total change and spatial location. The major change was the conversion between dense and moderate grass, with 64,860 km2 of dense grass turning into moderate grass, and 48,505 km2 changing the other way. (2) Among the four landscape metrics, patch density, area-weighted mean fractal dimension, and edge density increased, whereas the aggregation index decreased, which indicated that the landscape was developing towards heterogeneity, fragmentation, complexity, and aggregation. Spatially, the landscape metrics presented a strip distribution in the east of the NSPB. (3) The effects of various land-use types on ecological quality, from high to low, were unused land, woodland, dense grass, cropland, moderate grass, built-up land, sparse grass, and waterbody. The areas where the ecological quality was greatly affected by the landscape patterns were concentrated in the agro-pastoral ecotone and the forest-steppe ecotone. The results of this study reveal the trends of land use and landscape patterns in the NSPB over 18 years and can help to understand their mechanism on ecological quality, which is of significance for the management of this area.

Quantitative analysis and prediction of urban heat island intensity on urban-rural gradient: A case study of Shanghai.

Urbanization causes enormous land use/land cover (LULC) changes, which have become significant drivers of land surface temperature (LST) change in rapidly urbanizing city, and the changes in LULC subsequently increase the LST to form urban heat island (UHI). This paper first identified the spatial distribution pattern of the LULC changes and surface urban heat island intensity (SUHII) in the study area in recent 20 years based on Landsat TM/OLI data. And later, the relationship between the distribution of impervious surface (IS) and vegetable coverage (VC) and SUHII was analyzed quantitatively. Then, the land cover and land surface temperature (LST) in Shanghai in 2027 under three development modes were simulated and predicted based on FLUS model and geospatial analysis. The results showed that (1) Regional land cover and LST had obvious differences in gradient distribution from urban to rural areas, and the outer ring road (Ring3) was an obvious dividing line; (2) the proportion of IS and VC were significantly positively (|R| > 0.695) and negatively (|R| > 0.328) correlated with LST; (3) under the three different scenario development models, the ecological space protection model effectively regulated the SUHII, which was 15.91% less than the SUHII in 2017 (34% inside Ring3 and 14% outside Ring3). The results could provide a reference for the rational allocation of urban land and landscape optimization in reducing SUHII` in typical urbanized areas.

Monitoring the Landscape Pattern and Characteristics of Non-Point Source Pollution in a Mountainous River Basin.

This study aimed to assess the relationship between the landscape patterns and non-point source (NPS) pollution distribution in Qixia County, China. The sub-basin classification was conducted based on a digital elevation model and Landsat8 satellite images. Water samples were collected from each sub-basin, andtheir water quality during the wet and dry seasons was estimated. The correlation between the landscape indices and water pollution indicators was determined by Pearson analysis. The location-weighted landscape contrast index (LWLCI) was calculated based on the "source-sink" theory. Qixia was further divided into five sections based on the LWLCI score to illustrate the potential risk of NPS pollution. The results showed that the water quality in Qixia County was generally good. Cultivated land, orchards, construction areas, and unused land were positively correlated with the water pollution index and weredesignated as the "source" landscape categories, while forests, grasslands, and water bodies, which were negatively correlated with water pollution, were the "sink" landscapes; the LWCI was high in 36.94% of the study area. In these areas, measures such as increasing vegetation buffer zones are necessary to decrease the sediment and nutrient loads carried by precipitation.

Dynamic landscapes and the driving forces in the Yellow River Delta wetland region in the past four decades.

Wetlands provide a broad range of ecosystem services, such as flood control, groundwater replenishment, and water purification. These services are particularly important in the Yellow River Delta, one of four estuarine deltas in China. The aim of this study was to examine the patterns and drivers forces of wetland landscape in the Yellow River Delta. We analyzed the spatio-temporal characteristics of land use change and dynamic landscape patterns changes between 1980 and 2018, divided into eight periods, from land use and remote sensing data. We also analyzed data for annual precipitation, annual temperature, annual evapotranspiration, digital elevation, slope, distance from the main river, built-up land, GDP, and population with principal component analysis, to identify the main drivers behind the changes in the wetland landscape. The results showed that, from 1980 to 2018, the total area of wetland decreased first and then increased the total area of wetland increased and was 1172.73 km2 greater in 2018 than it was in 1980, and the types of wetland in the Yellow River Delta changed frequently. From 1980 to 2005, the area of wetland decreased and the landscape dominance and degree of fragmentation were relatively high. From 2006 to 2018, as environmental policies were implemented and wetland protection became more important, the rate of development of wetland areas increased in a north-south direction, the proportion of landscape types became more balanced, and the spatial distribution homogenized. The main drivers of change in the wetland landscapes were GDP, population, precipitation, and temperature which were included 81.852% of the original information. The findings from this study provide us with an improved understanding of how land use and wetland landscapes changed from 1980 and 2018 and may have implications for the protection of wetland ecosystems, species diversity, and sustainable development.

On Landscape Patterns in Typical Mountainous Counties Middle Reaches of the Yangtze River in China.

The landscape patterns of plantations (PT) are the results of human disturbances on local vegetation, and in turn, differ greatly from natural forests (NF), since the patterns strongly influence the natural circulation of material and energy. There is a need to understand the differences of landscape patterns between PT and NF, to establish a near natural afforestation strategy. This study chose three typical silvicultural counties in the middle reaches of the Yangtze River as the research areas and compared the landscape patterns of NF and PT, with other land use types (grassland, GL; cropland, CL; shrubland, SL; orchard, OR; built-up land, BUL; bare land, BL; and water bodies, WB). The results revealed that the areas of PT accounted for 7.67%, 12.05%, and 18.97% of three counties, bigger than GL, OC, BUL, BL, and WB, as one of main land use types. The landscape patterns of PT (mean patch size between 2.06 to 6.05 ha) were more fragmented than NF (mean patch size between 5.83 to 53.91 ha). NF areas increased along the relative altitude gradient, from 0 to 2500 m, while PT areas peaked from 100-1000 m. The higher the altitude, the more typical the zonal distribution of PT, the more aggregated the NF. NF had significant negative correlations with BL, BUL, CL, PT, GL, and OC, which suggest that human activities had seriously interfered with NF. Although PT as an ecological protection strategy was increasing, the landscape patterns of PT were obviously different from NF. This may affect the material energy flow in the ecological environment. The results in the present study have great implications in the other regions in China and the relevant parts of the world where natural forests were heavily disturbed.

Temporal invariance of social-ecological catchments.

Natural resources such as waterbodies, public parks, and wildlife refuges attract people from varying distances on the landscape, creating "social-ecological catchments." Catchments have provided great utility for understanding physical and social relationships within specific disciplines. Yet, catchments are rarely used across disciplines, such as its application to understand complex spatiotemporal dynamics between mobile human users and patchily distributed natural resources. We collected residence ZIP codes from 19,983 angler parties during 2014-2017 to construct seven angler-waterbody catchments in Nebraska, USA. We predicted that sizes of dense (10% utilization distribution) and dispersed (95% utilization distribution) angler-waterbody catchments would change across seasons and years as a function of diverse resource selection among mobile anglers. Contrary to expectations, we revealed that catchment size was invariant. We discuss how social (conservation actions) and ecological (low water quality, reduction in species diversity) conditions are expected to impact landscape patterns in resource use. We highlight how this simple concept and user-friendly technique can inform timely landscape-level conservation decisions within coupled social-ecological systems that are currently difficult to study and understand.

belg: A Tool for Calculating Boltzmann Entropy of Landscape Gradients.

Entropy is a fundamental concept in thermodynamics that is important in many fields, including image processing, neurobiology, urban planning, and sustainability. As of recently, the application of Boltzmann entropy for landscape patterns was mostly limited to the conceptual discussion. However, in the last several years, a number of methods for calculating Boltzmann entropy for landscape mosaics and gradients were proposed. We developed an R package belg as an open source tool for calculating Boltzmann entropy of landscape gradients. The package contains functions to calculate relative and absolute Boltzmann entropy using the hierarchy-based and the aggregation-based methods. It also supports input raster with missing (NA) values, allowing for calculations on real data. In this study, we explain ideas behind implemented methods, describe the core functionality of the software, and present three examples of its use. The examples show the basic functions in this package, how to adjust Boltzmann entropy values for data with missing values, and how to use the belg package in larger workflows. We expect that the belg package will be a useful tool in the discussion of using entropy for a description of landscape patterns and facilitate a thermodynamic understanding of landscape dynamics.

Characterizing the heterogeneous correlations between the landscape patterns and seasonal variations of total nitrogen and total phosphorus in a peri-urban watershed.

Landscape patterns in a watershed potentially have significant influence on the occurrence, migration, and transformation of pollutants, such as nitrogen (N) and phosphorus (P) in rivers. Human activities can accelerate the pollution and complicate the problem especially in a peri-urban watershed with different types of land use. To characterize the heterogeneous correlations between landscape patterns and seasonal variations of N and P in a peri-urban watershed located upstream of Tianjin metropolis, China, observations of total nitrogen (TN) and total phosphorus (TP) at 33 locations were performed in the wet and dry seasons from 2013 to 2016. The data from individual locations were averaged for the wet and dry seasons and analyzed with geographical detector to identify influential landscape indices on seasonal water quality variations. The geographically weighted regression method, capable of analyzing heterogeneous correlations, was used to evaluate the integrated effects from different landscape indices. The results demonstrated that the location-weighted landscape contrast index (LWLI), the ratio of urban areas, and the ratio of forest areas were major influential indicators that affected TN and TP in river water. These indices also had integrated effects on variations of TN and TP together with other indices such as Shannon diversity index, landscape shape index, largest patch index, and contagion index. The integrated effects were different in the wet and dry seasons because of different effects of flushing and dilution by rainwater and the heterogeneity in landscape patterns. The LWLI had a positive relationship to water quality in the areas with high ratio of urban areas, indicating that domestic wastewater can be a major source of N and P pollution. The approaches and findings of this study may provide a reference for characterizing the major factors and integrated effects that control nonpoint source pollution in a watershed.

Monitoring land surface thermal environments under the background of landscape patterns in arid regions: A case study in Aksu river basin.

Land surface temperature (LST) is defined as an important indicator in the formation and evolution of climate. In some cases, changes in landscape patterns affect LST, even more than the contribution of greenhouse gases. Although much work has been done with respect to the correlations between urban development and thermal environment dynamics, the related questions regarding relationships between LST and landscape patterns in arid regions are not thoroughly considered. Understanding these questions is important in climate change and land planning. The objective of this study was to explore the spatiotemporal variations of LST by distribution index (DI) and Mann-Kendall mutation analysis method and to quantify the relationships between landscape patterns, climatic factors, topographic factors, and the land surface thermal environment (LSTE) by the ordinary linear regressions (OLS) model. The landscape patterns dataset, which was validated by a field trip, was extracted from the Land satellite (Landsat) TM/OLI images by the Random Forest methodology in ArcGIS software. The MODIS/LST product was validated by the "Monthly dataset of China's surface climate" and a field trip. Annual LST increased by 0.54 °C (23.15 °C in 2000 and 23.79 °C in 2015). In different landscape patterns, the percentage of areas with a high level of LST showed a significant difference. In barren land, the highest area proportion for the high LST level was larger than in other landscape patterns. Meanwhile, the area of low LST was mainly concentrated in water bodies. Considerable changes have occurred in landscape patterns, in which the most noteworthy was cultivated land encroaching on grass land (3708.44 km2). The composition of landscape patterns was more important than distribution in determining the region's LST. These findings provide valuable information for land planners dealing with climate change and ecosystem conservation in arid regions.

Landscape Characteristics Affecting Spatial Patterns of Water Quality Variation in a Highly Disturbed Region.

Spatial patterns of water quality trends for 45 stations in control units of the Shandong Province, China during 2009-2017 were examined by a non-parametric seasonal Mann-Kendall's test (SMK) for dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), permanganate index (CODMn), total phosphorus (TP) and ammonia nitrogen (NH3-N). The DO concentration showed significant upward trends at approximately half of the stations, while other parameters showed significant downward trends at more than 40% of stations. The stations with downward trends presented significant spatial autocorrelation, and were mainly concentrated in the northwest and southwest regions. The relationship between the landscape characteristics and water quality was explored using stepwise multiple regression models, which indicated the water quality was better explained using landscape pattern metrics compared to the percentage of land use types. Decreased mean patch area and connectedness of farmland will promote the control of BOD, COD and CODMn, whereas the increased landscape percentage of urban areas were not conducive to the water quality improvement, which suggested the sprawling of farmland and urban land was not beneficial to pollution control. Increasing the grassland area was conducive to the reduction of pollutants, while the effect of grassland fragmentation was reversed.

Evolution of Landscape Ecological Risk at the Optimal Scale: A Case Study of the Open Coastal Wetlands in Jiangsu, China.

Detailed analysis of the evolution characteristics of landscape ecological risk is crucial for coastal sustainable management and for understanding the potential environmental impacts of a man-made landform landscapes (MMLL). As a typical open coastal wetland, large-scale human activities (e.g., tidal reclamation, fishery activities, wind farm construction, and port construction) have substantially affected the evolution of the coastal ecological environment. Previous landscape ecological risk assessment studies have documented the effectiveness of assessing the quality of ecological environment processes. However, these studies have either focused on the noncoastal zone, or they have not considered the evolution of the spatial characteristics and ecological risk evolution of the landscape at an optimal scale. Here, we present a landscape ecological risk pattern (LERP) evolution model, based on two successive steps: first, we constructed an optimal scale method with an appropriate extent and grain using multi⁻temporal Landsat TM/OLI images acquired in the years 2000, 2004, 2008, 2013 and 2017, and then we calculated landscape ecological risk indices. Based on this model, the entire process of the spatiotemporal evolution of ecological risk patterns of the open coastal wetlands in Jiangsu, China, was determined. The principal findings are as follows: (1) The main landscape types in the study area are tidal flats and farmland, and the main features of the landscape evolution are a significant increase in aquafarming and a substantial decrease in the tidal flat area, while the landscape heterogeneity increased; (2) In the past 20 years, the areas of low and relatively low ecological risk in the study region were greatly reduced, while the areas of medium, relatively high, and high ecological risk greatly increased; the areas of high-grade ecological risk areas are mainly around Dongtai and Dafeng; (3) The area of ecological risk from low-grade to high-grade occupied 71.75% of the study area during 2000⁻2017. During the previous periods (2000⁻2004 and 2004⁻2008), the areas of low-grade ecological risk were transformed to areas of middle-grade ecological risk area, while during the later periods (2008⁻2013 and 2013⁻2017) there was a substantial increase in the proportion of areas of high-grade ecological risk. Our results complement the official database of coastal landscape planning, and provide important information for assessing the potential effects of MMLL processes on coastal environments.

Connectivity in riparian plants: influence of vegetation type and habitat fragmentation overrides water flow.

Spatial genetic patterns can be influenced by a broad range of factors across a landscape. The hypothesis that heterogeneous vegetation and habitat fragmentation rather than water flow influence genetic patterns in two riparian plant species with different niches was tested. Genotyping by sequencing was used to assess the genetic diversity and structure of each species at 12 sites across a river catchment. Generalized dissimilarity modelling examined the relative influence that vegetation type and habitat fragmentation had on patterns of genetic differentiation across the landscape. Restricted gene flow in the widespread species, Callistachys lanceolata, resulted in lower genetic differentiation than that exhibited by Astartea leptophylla, a restricted riparian species with high gene flow. Geographic distance and vegetation type explained the patterns of genetic differentiation in the widespread species, whereas habitat fragmentation and, to a lesser extent, vegetation type explained patterns in the restricted species. Water flow was not found to have significant impacts on patterns of genetic diversity in riparian plant species with restricted and widespread distribution. Impacts of vegetation type on genetic differentiation were most likely due to change in canopy density and associated pollinator communities in the vegetation types across the catchment. Reduced connectivity caused by habitat fragmentation was evident in the restricted riparian species, while reduced connectivity in the widespread species was related to the change of vegetation type between sites. Natural causes of reduced connectivity as well as anthropogenic causes need to be considered in future work to predict persistence and resilience under a changing climate.

Impacts of urbanization and landscape patterns on the earthworm communities in residential areas in Beijing.

Earthworms play an important role in soil processes and functions. However, few studies have focused on their community patterns in perturbed systems, especially in an urban environment with a high turnover rate of land cover. In this study, we collected and identified the earthworms in the residential areas in metropolitan Beijing. We further investigated the effects of urban soil properties, urbanization and landscape patterns on the earthworm communities. The results showed that both the abundance and biomass of earthworms in residential areas in metropolitan was relatively low. The abundance of earthworms was negatively correlated with soil organic carbon (SOC) in this study. Soil moisture and pH could be considered as the most important edaphic variables that affected earthworm communities. The construction age of residential areas significantly influenced the earthworm abundance. Moreover, the earthworm community composition responded differently to urban landscape features at different scales. The percentage of impervious and green space surface, the amount of landscape cover types, patch density and landscape fragment significantly affected the earthworm assemblages. Our result discovered that the edaphic properties, urbanization as well as landscape patterns might be the potential factors that influenced the earthworm community patterns.

A modeling framework for the establishment and spread of invasive species in heterogeneous environments.

Natural and human-induced events are continuously altering the structure of our landscapes and as a result impacting the spatial relationships between individual landscape elements and the species living in the area. Yet, only recently has the influence of the surrounding landscape on invasive species spread started to be considered. The scientific community increasingly recognizes the need for broader modeling framework that focuses on cross-study comparisons at different spatiotemporal scales. Using two illustrative examples, we introduce a general modeling framework that allows for a systematic investigation of the effect of habitat change on invasive species establishment and spread. The essential parts of the framework are (i) a mechanistic spatially explicit model (a modular dispersal framework-MDIG) that allows population dynamics and dispersal to be modeled in a geographical information system (GIS), (ii) a landscape generator that allows replicated landscape patterns with partially controllable spatial properties to be generated, and (iii) landscape metrics that depict the essential aspects of landscape with which dispersal and demographic processes interact. The modeling framework provides functionality for a wide variety of applications ranging from predictions of the spatiotemporal spread of real species and comparison of potential management strategies, to theoretical investigation of the effect of habitat change on population dynamics. Such a framework allows to quantify how small-grain landscape characteristics, such as habitat size and habitat connectivity, interact with life-history traits to determine the dynamics of invasive species spread in fragmented landscape. As such, it will give deeper insights into species traits and landscape features that lead to establishment and spread success and may be key to preventing new incursions and the development of efficient monitoring, surveillance, control or eradication programs.

Assessing public aesthetic preferences towards some urban landscape patterns: the case study of two different geographic groups.

Landscape aesthetics is closely linked to people's daily life, and a large body of studies has been conducted to understand the public's landscape preferences. These studies commonly focused on comprehensive landscape configuration, yet limited emphasis was placed on the patterns of individual landscape features. This research explored people's preferences towards the composition and patterns of some specific urban features. Questionnaire-based survey was conducted in two cities: Cambridge, UK and Nanjing, China and more than 180 responses were collected, respectively. Respondents from both sites showed similar preferences towards freely growing trees, individual houses, gable roofs and mixed design of green spaces. On the other hand, respondents from Cambridge and Nanjing have different preferences towards the height of trees, the size of green spaces, and the height diversity of buildings. This survey also proved that the factors of age, education, status and length of living have larger influences on landscape preferences than the factors of gender, and major. Furthermore, strong correlations were found between people's aesthetic preferences towards comparative landscape patterns, building types, tree shapes and roof structures. The existence of generally shared landscape preferences makes it feasible to conduct international and standardized projects for acquiring comparable and transferable criteria. The methodology and findings of this research provides landscape planners and decision makers with useful reference to compare, evaluate and improve urban landscape configurations to meet people's needs.