Contagion Index Research Articles

Impact of landscape pattern changes on ecosystem service values in the Fenhe River Basin in China

The evolution of landscape patterns affects the supply of ecosystem services. It is important to explore the relationship between them to improve regional ecological stability and maintain ecological health. The Fenhe River is the second largest tributary of the Yellow River and it represents a fragile ecological environment. Our study aimed to analyze the impact of changes in landscape patterns on the value of ecosystem services (ESV) in the Fenhe River Basin (FRB). Land use data from 2000, 2010, and 2020 were used to extract landscape pattern indices. Methods such as ecosystem service value accounting, sensitivity analysis, correlation analysis, and geodetector modeling were employed to investigate changes in landscape patterns and ESV, and to identify the driving forces and impacts of these changes on ESV. The results showed that (1) from 2000 to 2020, the dominant landscape in the FRB was cultivated land, followed by forestland and grassland, which together covered 92% of the total area. (2) Over the past 20 years, the extent of landscape fragmentation had continued to increase and ecological function had deteriorated. (3) ESV had continued to decrease. The ESV provided by the regulating service function was the largest, accounting for over 49% of the total ESV. Support service function was second, accounting for over 34%. (4) The total ESV had a strong negative correlation with Shannon's diversity index (SHDI) and Shannon's evenness index(SHEI), a significant positive correlation with Contagion index (CONTAG). (5)The Human Activity Index (HAI) had a significant impact on changes in ESV, with an influence value of 0.6192, and its synergistic effect with NDVI further enhances this impact, achieving a synergy score of 0.71. Additionally, natural factors such as topography and climate also had significant effects on ESV changes.This study provides an evidence-based theoretical reference to guide the enhancement of the natural environment of the FRB and maintain highquality development of regional landscapes.

Evaluation and Optimization of Landscape Spatial Patterns and Ecosystem Services in the Northern Agro-Pastoral Ecotone, China

The alteration of landscape spatial patterns (LSPs) and ecosystem services (ESs) in watersheds can have detrimental effects on the local environment and community. However, a comprehensive understanding of the current state of LSPs and ESs in watersheds around Winter Olympic venues in China is limited. Here, we assessed current LSPs and ESs and developed optimization strategies for the Xigou watershed around Winter Olympic venues in the northern agro-pastoral ecotone of China. The results indicated that the main land use type was grassland in the Xigou watershed, and landscape types were relatively homogenous. All three ESs (water yield, sediment retention, and carbon storage) generally improved from 2004 to 2020. For ESs, there was the lowest total volume of water yield in 2004 (637.44 × 104 m3). But sediment retention (10.54 × 106 t, 18.13 × 106 t, 13.28 × 106 t, and 16.85 × 106 t) had an upward, then downward, then upward trend before and after ERP. Carbon storage grew steadily. Correlation analysis suggested that the three ESs were closely related to the landscape spatial indices of average patch area (AREA_MN), contagion index (CONTAG), and Shannon’s evenness index (SHEI). AREA_MN, CONTAG, and SHEI in the eastern part of the study area promoted sediment retention and carbon storage, while in the southwestern part of the study area, they inhibited water yield and sediment retention. The results suggest that improving sediment retention by optimizing land use and cover change (LUCC) and LSPs is the main approach to further enhance ESs in the study area. Our study suggests that the inclusion of multiple landscape pattern indices can provide a more comprehensive representation of regional ecosystem service.

Impact of landscape pattern on habitat quality in the Yangtze River Economic Belt from 2000 to 2030

Recently, rapid economic development of the Yangtze River Economic Belt region in China and the growing problem of regional habitat quality have seriously threatened the process of biodiversity conservation in the Yangtze River Basin. Studying the impact of changes in landscape pattern indexes on habitat quality in the Yangtze River Economic Belt can provide policy insights for biodiversity conservation in the Yangtze River Basin. However, existing studies are still lacking in exploring the effects of changing landscape pattern indices on habitat quality under future scenarios. Based on the land use data of the Yangtze River Economic Belt from 2000 to 2020, this study simulates the land use situation in 2030, and analyzes the landscape pattern indexes and habitat quality during the 30 years, to investigate the impact of landscape pattern indexes on habitat quality at global and local scales through various methods. The results show that landscape patterns were significantly affected by human activities and land use types, with the Yangtze River Economic Belt experiencing increased levels of land use and structural stabilization during the three decades (Shannon Diversity Index increased from 0.90 in 2000 to 0.94 in 2030), fragmentation of the landscape (Landscape fragmentation index increase from 0.094 in 2000 to 0.102 in 2030), and weakened connectivity (contagion index decrease from 48.213 in 2000 to 45.437 in 2030). The Habitat Quality has a large variation in spatial distribution at the county scale, with an average change in habitat quality of 1.04 % from 2000 to 2030, and an overall downward trend. There is a strong localized spatial autocorrelation between landscape pattern indices and habitat quality, with significant spatial heterogeneity and some form of variability at time scales. The results of this study help to further understand the eco-environmental problems of the Yangtze River Economic Belt, and provide theoretical references for the formulation of ecological environmental protection policies and ecological functional area planning.

Assessing the dynamics and trigger factors of drought propagation in the China-Pakistan economic corridor: A three-dimensional perspective

Effectively managing drought in the China-Pakistan Economic Corridor (CPEC) region requires a precise understanding of the three-dimensional characteristics of meteorological drought (MD) and agricultural drought (AD), as well as the factors that trigger their propagation. This study employed non-stationary drought indices (NSPEI and SSMI) to develop a cutting-edge 3-dimensional drought identification model. This model was used to detect MD and AD patterns from 1981 to 2022 in the CPEC region and was integrated with binomial logistic regression to identify the critical factors that drive drought propagation. This study's key findings include: 1) Between 1981 and 2022, droughts in Xinjiang, China, exhibited a discernible southward migration trend, while in Pakistan, droughts showed a northward migration pattern. Drought frequency and extent have increased over time, with affected regions becoming more widespread in CPEC. Notably, drought events with higher preceding drought contagion indices (DCI) were more likely to evolve into extreme, long-term droughts. 2) Drought area emerged as a significant positive triggering factor for drought propagation in the CPEC region. Conversely, snowmelt in Xinjiang and the leaf area index for low vegetation in Pakistan acted as triggering elements affecting negatively. 3) Various factors played a pivotal role during drought propagation process, including geographical coordinates of drought centroids, DCI, and temperature variations. Additionally, snowmelt and snow evaporation significantly impacted drought propagation in Xinjiang, while vegetation cover in Pakistan played a crucial role during the drought propagation process. By utilizing four regression models and conducting comprehensive attribution analysis, this study sheds light on the characteristics of drought propagation and the factors influencing it. These findings are valuable for enhancing early warning systems and implementing effective drought mitigation strategies in the CPEC region.

Evaluation of Rice–Crayfish Field Fragmentation Based on Landscape Indices: A Case Study of Qianjiang City, China

Since the 21st century, rice–crayfish fields have been widely distributed in the Yangtze River Basin in China. However, the spontaneous construction of these fields by farmers has given rise to the issue of rice–crayfish field fragmentation (RCFF) in certain areas. This study introduced a novel method for evaluating RCFF using township-level administrative regions as the evaluation units. Three key evaluation elements, including five landscape indices, were employed: area and edge metrics (rice–crayfish area ratio), shape metrics (perimeter–area ratio distribution), and aggregation metrics (rice–crayfish patch density, percentage of like adjacencies, and rice–crayfish contagion index). The RCFF was quantified and its spatial distribution pattern was analyzed through the entropy method and GIS spatial analysis. Empirical studies conducted in Qianjiang city yielded insightful results: (1) The contribution of evaluation elements to the RCFF was ranked in descending order as follows: aggregation metrics > shape metrics > area and edge metrics. (2) The RCFF of Yunlianghu farm was the lowest at 0.06, while the RCFF of Yangshi subdistrict 2 was the highest at 0.94. The spatial distribution of the RCFF exhibited a distinct trend, showing a gradual decrease from the northeast to the southwest in Qianjiang, and a low-RCFF area in the southwest. This evaluation system enables local government decisionmakers to comprehend the current status of rice–crayfish field management and construction. It facilitates the scientific planning of rice–crayfish field layouts and provides guidance for farmers in their expansion strategies. This method can be promoted in counties (cities) where rice–crayfish fields are primarily distributed in the Yangtze River Basin, promoting the transition of traditional agriculture to environmentally friendly agriculture in China.

Interconnectedness in the FOREX market during the high inflation regime: A network analysis

Our study employs network analysis to examine the interconnectedness in the Foreign Exchange market, focusing on 18 key currencies from both advanced and emerging markets from 2017 to 2023. This analysis includes a comparative look at the impact of two major recent crises: the COVID–19 pandemic and the Russia-Ukraine war. The latter is notably marked by increased inflation and uncertainty in economic policies. During the COVID–19 pandemic, we observed a significant level of interconnectedness among the EURO and 17 other currencies, indicating a dense network. In contrast, the period of the Russia-Ukraine war revealed a tendency for countries less engaged in international trade to become more isolated, as seen by their greater distance from the network's centroid. Additionally, we developed the Systemic Contagion Index, which shows a heightened susceptibility to contagion among developed economies during both the COVID–19 and Russia-Ukraine war crises, underscoring the vulnerability of developed countries' currency networks in times of turmoil. This study provides valuable insights for investors and global businesses, offering guidance on assessing currency vulnerability and enhancing their strategies for hedging and managing risks amidst fluctuating market conditions, especially during the high inflation regime.

Spatiotemporal evolution of landscape stability in World Heritage Karst Sites: a case study of Shibing Karst and Libo-Huanjiang Karst

Landscape stability is a paramount concern within the field of landscape ecology. Indices of landscape patterns not only facilitate an effective analysis of land use transformations but also delve into the mechanisms of landscape disturbances across various spatial and temporal dimensions. Utilizing land use data spanning from 2014 to 2022 for the Shibing and Libo-Huanjiang South China Karst (SCK) World Heritage Sites (WHSs), this study delves into the landscape dynamics of these areas over the past 8 years. This investigation employs landscape pattern indices and a moving window technique to construct a landscape stability evaluation model, incorporating indices such as the Contagion Index, Patch Density, and Total Edge Contrast. Moreover, the study employs Moran's I, a spatial autocorrelation index, to scrutinize the shifts in geographical heterogeneity of landscape stability within the said period. The findings reveal: (1) Between 2014 and 2022, the landscape patterns of the Shibing and Libo-Huanjiang WHSs have undergone significant transformations, with Woodland emerging as the predominant landscape type and its area exhibiting an upward trend in recent years. (2) The level of fragmentation within the research area has decreased, landscape diversity has diminished, and the aggregation index has risen, according to the landscape pattern indices from 2014 to 2022, indicating that conservation measures have significantly influenced the evolution of landscape patterns. (3) Throughout most of the study period, landscape stability predominantly remained at a relatively stable level, albeit with noticeable fluctuations in years heavily impacted by human activities. (4) The areas of high-high agglomeration and the hotspots of the heritage sites were primarily concentrated within the core zones of these sites, suggesting focused areas of conservation and landscape integrity.

Impact of touristification and landscape pattern on habitat quality in the Longji Rice Terrace Ecosystem, southern China, based on geographically weighted regression models

Although the roles of tourism development and landscape value in the conservation of rice terraces have become increasingly important in recent years, rice terraces still face abandonment and desertification. Habitat quality (HQ) assessments evaluate the biodiversity conservation status of rice terraces; however, the spatial and temporal evolution of rice terrace HQ and influencing factors remains poorly understood. Here, a case study was performed of the Longji Terraces, Longsheng, Guangxi, China. Land use and land cover (LULC) remote sensing data for 1985–2020 (every 5 years) were obtained, and the InVEST-HQ model was used to evaluate and map the spatial and temporal evolution patterns and characteristics of HQ. A landscape pattern index and tourism indicators were combined and used to construct geographically weighted regression (GWR) models to explore the impact of tourism and landscape pattern on HQ. Our findings indicated that: (1) forests and terraces are the dominant landscape patches in Longji because they are better protected. Forest area and HQ changes exhibited temporal consistency, meaning that as forest area increased, HQ improved. (2) Longji Terraces exhibited optimum HQ overall, with a multi-year average of 0.977 and insignificant inter-annual variations. Spatially, the geographical HQ distribution was characterised by ‘low local levels, high global level.’ However, the percentage of HQ degraded areas in the final period reached 68 %, which is significantly greater than that of the improved areas (28 %). Moreover, improved areas had more spatial overlap with administrative villages that present superior tourism development. (3) HQ was significantly negatively correlated with night-time light (NTL), showed periodic changes (first negative, then positive) with Shannon’s diversity index (SHDI), was positively correlated with the contagion index (CONTAG), and showed periodic transitions (initially positive, then negative) with the mean of patch area (AREA_MN), population (POP), and patch density (PD). (4) Over time, the study area HQ showed weaker clustering and increased dispersion. In addition, the influence of tourism and landscape patterns increased from 2000 to 2020, with R2 increasing from 0.42 to 0.95. The results establish a scientific foundation for the conservation of rice terraces and sustainable use of landscape resources.

Spatiotemporal Dynamics of Constructed Wetland Landscape Patterns during Rapid Urbanization in Chengdu, China

The degradation of urban ecology, particularly in metropolitan areas distinguished by dense populations and impervious surfaces, presents a worldwide challenge linked to swift urban expansion. Despite extensive documentation of urbanization’s impact on broad regions or specific urban ecosystems over defined time periods, there remains a scarcity of studies investigating the spatiotemporal dynamics of landscape pattern (LP) changes in specific ecosystems at small-to-medium scales within inland megacities as a response to urbanization. Therefore, this work focused on the Bailuwan Wetland Park (BWP) in Chengdu, an inland megacity in southwestern China. Employing satellite imagery data from selected years spanning the previous decade (2010–2021, encompassing 2010, 2012, 2015, 2018, and 2021), this investigation delved into the influences of urbanization on the LP over various time-frames and across different land use/land cover (LULC) types. Our study revealed that urbanization has a significant impact on the patch-/landscape-level characteristics, including the class area (CA), number of patches (NP), patch density (PD), percentage of landscape (PLAND), aggregation index (AI), contagion index (CONTAG), largest patch index (LPI), landscape shape index (LSI), fractal dimension index (FRAC_MN), Shannon’s diversity (SHDI), and evenness index (SHEI). Over the period from 2010 to 2021, NP and PD experienced notable increases, while landscape shape (LSI/FRAC_MN) exhibited greater complexity and fragmentation (PLAND) intensified. Further, landscape heterogeneity (AI/CONTAG) and diversity (SHDI/SHEI) decreased. Particularly significant was the conversion of 52 ha of agricultural land to vegetation, resulting in heightened complexity and fragmentation in vegetation patterns. Additionally, the CA of lakes and rivers decreased following the establishment of the park, while the CA and NP of bare land presented significant increases. These findings suggest that rapid urbanization significantly influences the spatial–temporal dynamics of wetland landscape patterns. Consequently, it is imperative for society to prioritize the restoration and protection of urban constructed wetlands.

Spatial scale effects of landscape patterns on non-point source pollution: A case study of Taizi River Basin in Northeast China

River water quality is influenced by natural processes and human activities. Multi-scale landscape patterns can affect river water quality by altering the generation and transport processes of pollutants at different spatial scales. Taking Taizi River Basin in Northeast China as an example, we analyzed the relationship between landscape patterns and non-point source pollution in rivers based on water quality monitoring data and land use data by using correlation analysis and redundancy analysis methods. We aimed to determine the key spatial scales for the responses of landscape patterns to non-point source pollution and identify the key landscape indices influencing river non-point source pollution. The results showed that water quality of Taizi River Basin had seasonal differences, with better water quality during the flood season than non-flood season. Spatially, total nitrogen (TN) and total phosphorus (TP) were higher at the confluence points of tributaries and downstream areas. The impact of landscape patterns on non-point source pollution was stronger during the non-flood season than the flood season, while the influence on TN was stronger than on TP. At the spatial scale of within 500 m buffer zone during the flood season and at the sub-watershed scale during the non-flood season, landscape patterns showed the highest explanatory power for the variations of TN and TP. At the type level, built-up land, cropland, and bare land were positively correlated with TN and TP, while forest was negatively correlated with TN and TP, which were the key types influencing non-point source pollution. At the landscape level, patch density, percentage of like adjacencies, and contagion index were key indicators affecting watershed water quality. Lower patch density was associated with better connectivity and aggregation of "sink" landscapes, leading to better purification effects on TN, but more pronounced retention effects on TP. Conversely, higher landscape diversity and denser pattern of multiple types would cause the deterioration of water quality. Our results suggested that rational allocation of landscape types within the watershed and riparian buffer zones, appropriately enriching landscape diversity, and optimizing landscape aggregation and connectivity would be effective measures for improving water quality and achieving sustainable ecological management.

Coupling effect of key factors on ecosystem services in border areas: a study of the Pu'er region, Southwestern China.

The coupling effects created by transboundary and local factors on ecosystem services are often difficult to determine. This poses great challenges for ecosystem protection and management in border areas. To decrease uncertainty, it is crucial to quantify and spatialize the impact multiple factors have on ecosystem services within different scenarios. In this study, we identified key transboundary and local factors from a set of 15 sorted factors related to four main ecosystem services. We employed a Bayesian Network-Geographic Information System (BN-GIS) model to simulate 90 scenarios with multiple factors combinations, quantifying and spatializing the coupling effects on the main ecosystem services. These simulations were conducted in the Pu'er region, which is situated alongside three countries, and serves as a representative border area in southwest China. The results showed that: (1) The coupling effects of multiple factors yield significant variations when combined in different scenarios. Managers can optimize ecosystem services by strategically regulating factors within specific areas through the acquisition of various probabilistic distributions and combinations of key factors in positive coupling effect scenarios. The outcome is a positive coupling effect. (2) Among the four main ecosystem services in the Pu'er region, food availability and biodiversity were affected by key transboundary and local factors. This suggests that the coupling of transboundary and local factors is more likely to have a significant impact on these two ecosystem services. Of the 45 combination scenarios on food availability, the majority exhibit a negative coupling effect. In contrast, among the 45 combination scenarios on biodiversity, most scenarios have a positive coupling effect. This indicates that food availability is at a higher risk of being influenced by the coupling effects of multiple factors, while biodiversity faces a lower risk. (3) Transboundary pests & diseases, application of pesticides, fertilizer & filming , population density, and land use were the key factors affecting food availability. Bio-invasion, the normalized differential vegetation index, precipitation, and the landscape contagion index were the key factors affecting biodiversity. In this case, focusing on preventing transboundary factors such as transboundary pests & disease and bio-invasion should be the goal. (4) Attention should also be paid to the conditions under which these transboundary factors combine with local factors. In the areas where these negative coupling effects occur, enhanced monitoring of both transboundary and local factors is essential to prevent adverse effects.

The landscape altered the interaction between vegetation and climate in the desert oasis of Hotan River Basin, Xinjiang, China

In the arid region, the oasis is characterized by a desert substance and a mosaic of vegetation. The biophysical processes and interactions between vegetation and the local climate in this kind of region are determined by the macroscopic structure of the ecosystems, i.e. landscape patterns. To understand how these landscape patterns impact regional hydro-heat coupling across space and evolve over time, we utilized remote sensing observational data and methods to examine the relationships among these factors. In this case, we focused on the oasis along the upstream of the Hotan River Basin in the Taklamakan Desert in Xinjiang of western China and employed the satellite imagery datasets of Landsat from 1993 to 2019 to investigate the dynamics of vegetation–climate factors. Based on the land use and cover change datasets, the landscape pattern metrics, including patch density (PD), contagion index (CONTAG), fractal dimension (FRAC), were calculated to measure the landscape features on the different aspects, i.e. the fragmentation, the connectivity, and the complexity. With the algorithm of land surface energy balance, the land surface indicators, including the soil-adjusted vegetation index (SAVI), albedo, surface irradiance temperature (Ts), and evapotranspiration (ET), were calculated to represent the key process in the interaction of vegetation–climate. The temporal-spatial dynamics of the landscape patterns and the vegetation–climate metrics were mapped and demonstrated in a quantitative manner. The statistical results revealed that during the past decades, the agricultural land in the study area had significantly increased by 17 %. Grassland and shrubs had also expanded, while the desert area decreased from 82.57 % to 78.82 % of the total area, with an overall reduction rate of 1.4 %/10a. It was found the study area was getting warmer and dryer based on the general trends of Ts and ET observed during the period of 1993–2019. The agricultural land had the highest PD and CONTAG, and the lowest FRAC. The agricultural land had the lowest Ts and the highest ET. The results of structural equation model identified the decoupling effects of PD and CONTAG on the regional hydro-heat environment, while confirmed that FRAC had positive impact on the coupling between Ts and ET. Our study bridged the landscape pattern with the regional vegetation–climate interaction and provided the suggestions for the landscape planning and management for a more sustainable arid region.

Identifying the effects of landscape pattern on soil conservation services on the Qinghai-Tibet Plateau

Land use patterns affect soil erosion processes and soil conservation services. Identifying key landscape pattern affecting soil conservation services is critical for improving soil conservation services and optimizing land use patterns. In this study, the Qinghai-Tibet Plateau (QTP), where ecosystem services are important, was selected as research area. Based on land use, meteorological, soil and vegetation data, the RUSLE model was used to estimate soil conservation quantitatively from 2000 to 2020. The temporal changes in landscape metrics were analyzed using Fragstats, and the response of soil conservation services to landscape metrics was analyzed by correlation analysis. The landscape pattern showed an obvious temporal change trend. In general, the overall landscape of the QTP became more diversified and fragmented, and the landscape shape tended to become more complicated. Patch density (PD), edge density (ED), landscape shape index (LSI), splitting index (SPLIT), Shannon's diversity index (SHDI), and Shannon's evenness index (SHEI) showed increasing trends, while largest patch index (LPI), mean patch area (AREA_MN), aggregation index (AI), and contagion index (CONTAG) showed decreasing trends. At the class level, the variations of landscape pattern metrics of different land use types were big difference. In the 20-year period, soil conservation services were generally on the rise. The spatial heterogeneity of soil conservation services decreased from the south-east to the north-west. PD and ED were positively correlated with soil conservation function, while AREA_MN and AI had a negative correlation with soil conservation function. The effect of landscape pattern metric variation on soil conservation capacity significantly differed among different land use types. Results of the research offer reasonable evidence for landscape management, water and soil retention function improvement and regional ecological protection on the QTP.

Commonality in systemic risk from green and conventional energy

Our study is a novel attempt to examine the sub-industry sectors of conventional energy (i.e., oil & gas, crude production, oil refinery & marketing, and oil equipment and services) and the sub-industry sector of green energy (i.e., renewable energy) to analyse the systemic risk and commonality. The results show that the systemic risk for green energy has decreased since 2006, indicating a shift towards net-zero emissions. Further, we develop a systemic contagion index (SCI) for green and conventional energy. The SCI shows that green energy has lower contagion than conventional energy. However, conventional energy appears to create lower contagion during crises, indicating its herding characteristics and investors' preference for conventional energy during crises. A mild systemic risk commonality between green and conventional energy provides an opportunity to shift towards green energy, thus enhancing the possibility of achieving net-zero emissions. These findings provide guidance to policymakers to build the global green and conventional energy policy to achieve net-zero emissions in 2050.

Habitat suitability and crop damage risk caused by wild boar in Guizhou Plateau, China

AbstractCrop damage caused by wild boar (Sus scrofa) in many agroforestry regions of the world has affected agricultural development and farmers' livelihoods. Understanding the patterns of wild boar crop damage is important for properly managing these conflicts, and can improve the effectiveness of existing prevention strategies. We collected a comprehensive dataset from Guizhou Province, China, from 2017 to 2020, obtained from motion‐sensitive camera monitoring, transect surveys, interview surveys, and wildlife management administrations. These data include 3,156 records of wild boar activity in natural areas and 576 records of crop damage. We applied a multi‐scale MaxEnt model to map the regional distribution of wild boar habitat suitability and crop damage risk in Guizhou Province and focused on the role of habitat suitability in wild boar crop damage from a regional perspective. Wild boar habitat suitability exhibits a divergent pattern, expanding from the central area of Guizhou Province to the eastern, northern, southern, and northwestern regions, with a gradually increasing trend. Suitability of habitat for wild boar was associated with composite topographic index, mean coldest season temperature, isothermality, Shannon diversity index, edge density, and distance to village roads. Similarly, crop damage caused by wild boars in agroforestry areas is mainly concentrated in the northeast, with the risk increasing from west to east. The risk of damage was associated with temperature seasonality, roughness, distance to village roads, precipitation in the warmest quarter, edge density, and contagion index. Furthermore, in agroforestry areas, there is a positive correlation between wild boar habitat suitability and crop damage risk, with Spearman rank correlation coefficients ranging from 0.5759 to 0.5932. This correlation is not perfectly synchronized on a regional scale. This study indicates that the relationship between habitat suitability and crop damage caused by wild boar in Guizhou Province is primarily influenced by changes in population size rather than the habitat. Consequently, we emphasize the importance of controlling wild boar populations through hunting as a way to effectively reduce the risk of crop damage in agroforestry areas, without neglecting the need for proper habitat management.

Spatial-temporal changes of landscape and habitat quality in typical ecologically fragile areas of western China over the past 40 years: A case study of the Ningxia Hui Autonomous Region.

In this paper, we use the InVEST model and five periods of land use data from 1980 to 2020 to assess the habitat quality of the Ningxia Hui Autonomous Region in Western China, which has characteristics of a typical fragile ecosystem. We further analyse the spatial and temporal characteristics of habitat quality evolution and its relationship with land use and landscape pattern indices to explore the close relationship between regional habitat quality changes and human natural resource conservation and utilization. The research results show that the overall habitat quality of Ningxia Hui Autonomous Region was stable and at a moderate level (0.57-0.60) during the 40 years from 1980 to 2020; Habitat patches (2020) with low (24.89%), high (22.45%) and very high (29.81%) quality occupy a larger proportion of the area, followed by very low (13.31%) and moderate levels (9.54%). Over the past 40 years, there have been 275 sample sites in Ningxia where habitat quality has deteriorated, 1593 sample sites where the habitat quality has remained stable, and 184 sample sites where the habitat quality has increased. From 1980 to 2020, the Mean Patch Area of landscape types in Ningxia decreased by 25.9 hm2. The Patch Density increased by 0.06 /hm2. The Largest Patch Index decreased by 15.69%. The Edge Density increased by 2.5 m/hm2. The Contagion Index decreased by 2.99%. The Area-Weighted Mean Patch Fractal Dimension remained basically unchanged (0.01). The Landscape Shape Index showed a trend of first increasing and then decreasing, increasing by 13.94. The Area-Weighted Mean Shape Index has been reduced by 9.45. The Shannon Diversity Index and Shannon Evenness Index both show an increasing trend, but the amplitude is relatively small, with 0.09 and 0.04, respectively. There was a significant spatial aggregation of high and low habitat quality in Ningxia, with high values usually distributed in the northern and southern areas with good natural conditions and low values distributed in areas with frequent human activities and poor natural conditions. The decrease in habitat quality in Ningxia was mainly due to the expansion of cultivated land and construction land, the increase in landscape fragmentation and the resulting decrease in connectivity. On the other hand, due to the implementation of ecological protection measures, such as the project of returning farmland to pasture and grass to forest, the quality of habitats in Ningxia increased. The conclusions of this study support the idea that the conservation of habitat quality in ecologically fragile areas should fully preserve the original natural habitats and reduce the interference of human activities to increase the habitat suitability of the landscape and the habitat connectivity between patches. At the same time, targeted ecological protection policies should be developed to restore the areas where the habitat quality has been damaged and ultimately maintain the stability of biodiversity and ecosystems in ecologically fragile areas. Meanwhile, for ecologically fragile areas with similar ecological characteristics to those of Ningxia, our research supports the idea of increasing the protection of the stability of the original habitats, increasing the proportion of ecological restoration projects, financial investment and seeking cooperation with local community managers and residents will help to improve the quality of the regional habitats and the enrichment of the biodiversity, and ultimately promote the harmonious coexistence of human beings and nature in the modernized sense of the word.

Identifying the Relationships between Landscape Pattern and Ecosystem Service Value from a Spatiotemporal Variation Perspective in a Mountain–Hill–Plain Region

Identifying the changes in landscape pattern and ecosystem service value (ESV) and clarifying their relationship in temporal changes and spatial variations can provide insight into regional landscape features and scientific support for regional landscape planning. Leveraging land use data from the Yihe River Basin, we quantitatively assessed the landscape pattern and ESV shifts spanning from 2000 to 2018 using the landscape pattern indexes and the equivalence factor method. We employed Pearson correlation metrics and the geographically weighted regression model to explore the interrelation of their spatiotemporal variations. Our results show the following: (1) Forestland represents the most expansive land cover category. Apart from construction land, all other types experienced a decline in area. The most notable change occurred in the area of construction land. (2) The aggregation of the overall landscape shows a downward trend. The levels of fragmentation, landscape diversity, and richness increased. (3) Throughout the entire study period, the overall ESV gradually decreased, and the land cover type with the greatest contribution to the ESV was forestland. (4) In terms of temporal changes, the patch density and edge density of the overall area are significantly negatively correlated with total ESVs. The largest values for the patch index, perimeter–area fractal dimension (PAFRAC), and aggregation are significantly positively correlated with total ESVs. (5) In terms of spatial variation, the contagion index (CONTAG), PAFRAC, and the Shannon diversity index (SHDI) were noticeably correlated with ESVs. The CONTAG is positively correlated with ESVs upstream, but negatively midstream and downstream. The SHDI is negatively correlated with ESVs upstream, but positively midstream and downstream. The PAFRAC exhibits a positive correlation with ESVs for the most part. The association between the landscape pattern indexes and ESVs exhibits temporal and spatial inconsistencies in most instances, suggesting a spatiotemporal scale effect in their relationship. This study recommends that the local government devises a long-term strategy for urban development and exercises stringent control over the unregulated expansion of construction land. Through reasonable territorial spatial planning, government departments could enhance the connectivity of the overall landscape pattern of the Yihe River Basin to achieve the reasonable allocation and sustainable development of regional resources.

Effect of agricultural landscape pattern on the qualitative food web of epigaeic arthropods in low hilly areas of northern China

Under the macro background of global change and sustainable development, the sustainable and healthy development of agricultural landscapes is crucial for human well-being. Formulating targeted protection measures based on biodiversity conservation is currently a hot topic and challenge. Our study focused on Jianping County, a typical hilly area in northern China, to understand the impact of regional agricultural landscape patterns on qualitative food webs. We calculated food web parameters by constructing predator-pest qualitative food web matrices and compared the differences in food web structure characteristics under different agricultural landscape patterns. By using function regression method, we established landscape indices and food web parameter models. The results showed that the average number and community structure of predatory natural enemies and pests varied across different agricultural landscape patterns, but the common groups were similar. Maintaining a proportion of 30–40 % non-crop habitats is optimal for the stability of qualitative food webs. Different landscape elements have varying regulatory effects on the structure of qualitative food webs, and the food web parameter model can explain these effects more directly. Specifically, the Landscape Shape Index (LSI) is significantly positively correlated with Generality (G), while the Contagion Index (CONTAG) is significantly negatively correlated with vulnerability (V). We propose that in low hilly areas, where non-crop diversity is the primary source of heterogeneity, promoting measures for non-crop habitats through landscape planning will help maintain the richness of epigaeic arthropods and the stability of qualitative food webs. This research is of great significance in promoting ecological control and sustainable development of agroecosystems in low hilly areas.

Evaluating the Influence of Land Use and Landscape Pattern on the Spatial Pattern of Water Quality in the Pearl River Basin

Differences in land use and landscape patterns have become crucial factors affecting regional water quality. In order to investigate the effects of different land use and landscape patterns on water quality, this study used dissolved oxygen (DO), ammonia nitrogen (NH4+-N), and potassium permanganate index (CODMn) from 147 conventional water quality monitoring stations in the Pearl River basin of China from January to December 2021 as representative water quality parameters. The quantitative relationship between land use, landscape pattern, and water quality in the Pearl River basin was investigated using geographic information system technology (GIS) and partial least squares (PLS). The results showed that the overall water quality of the Pearl River basin was relatively positive and mainly threatened by organic pollution. The water quality of the Pearl River basin was affected by the spatial characteristics of land use and landscape pattern, showing a poorer spatial pattern on the eastern and western ends and a better one in the central part of the basin. The developed PLS regression model could better explain the quantitative relationship between water quality, land use, and landscape pattern, concluding that unused urban land has the greatest impact on water quality, with an impact coefficient of more than 0.10. The interspersion juxtaposition index (IJI) for representing landscape patterns had the greatest impact on water quality indicators, with an impact coefficient of −0.15 on DO, 0.13 on NH4+-N, and 0.15 on CODMn, respectively. Meanwhile, land use types such as unused land and water and landscape patterns indicated by the Shannon diversity index (SHDI) and the contagion index (CONTAG) had significant effects on watershed water quality. The results of the study provide a reference value for the optimal adjustment of land use structure and water quality improvement in the basin.

The Impact of Land—Use Composition and Landscape Pattern on Water Quality at Different Spatial Scales in the Dan River Basin, Qin Ling Mountains

To study the impact of land—use structure and landscape pattern on water quality at different spatial scales in the Dan River Basin (Qin Ling Mountains, China), water samples from 21 sites along the Dan River were collected in 2022 during the dry and wet seasons, and nine water quality indices were tested. Land—use composition and landscape pattern indices at riverine reach, riparian, and sub—basin were obtained, and correlation analysis and redundancy analysis (RDA) were used to determine the relationship with water quality. The results are as follows. (1) Water quality in the Dan River is better in the wet season than in the dry season; the main pollutants are total nitrogen (TN) and total phosphorus (TP). (2) The impact of land—use composition and landscape pattern on water quality has a scale effect; riverine reach can best explain the water quality. (3) Agricultural land and forest have the greatest impacts on water quality; agricultural land and construction land aggravate the deterioration of water quality, while forest, grassland, and water area have positive effects on water quality. The largest patch index (LPI) and contagion index (CONTAG) were positively correlated with pollutants, while Patch richness density (PRD), Patch shape (PD), Shannon’s diversity index (SHDI), and landscape shape index (LSI) were negatively correlated with pollutants, indicating that with an increase in the impact of human activities on landscapes, the degree of fragmentation decreases patch richness, landscape shape tends to be simplified, and water pollution is eventually aggravated. Land planners should focus on optimizing the land—use structure and landscape pattern to increase the diversity of the landscape. Therefore, strict environmental regulations must be established.