Pattern Index Research Articles

RIS-Based Opposite Phase Index Modulation and Its DNN-Assisted Joint Sequence Detection

Reconfigurable intelligent surface (RIS), a key technology for future wireless communications, allows intelligent reflection of signals and information transmission. The RIS-based modulation is considered a prospective information transmission mechanism. In this paper, a RIS-based opposite phase index modulation system is proposed, in which RIS can enhance the received power of user signals while transmitting additional data bits for near-end internet of things devices via opposite phase reflection pattern index without any additional radio frequency chain. To reduce the computational complexity of receiver detection, a deep neural network-assisted joint sequence detection method is proposed, in which the reflection pattern index and the symbol index are jointly detected. In addition, we derive the theoretical upper bound performance of the proposed modulation scheme in terms of the average bit error rate (BER) with the maximum likelihood detection. The theoretical and simulation results show that the proposed scheme has better BER performance and lower detection complexity than existing RIS-based modulation schemes.

Landscape Ecological Risk Assessment and Analysis of Influencing Factors in Selenga River Basin

Land degradation under the influence of global warming and ecological environmental destruction due to poor land management is the main challenge facing the Mongolian Plateau, and its future ecological risk change trends and drivers are also unclear. Therefore, to address the context relevant to this challenge, planning based on measured information from land use patterns is required. Based on land use and land cover (LULC), this study evaluates the landscape ecological risk (LER) of the Selenga River Basin by calculating the landscape pattern index. The spatiotemporal pattern and influencing factors of landscape ecological risk in the Selenga River Basin from 1990 to 2040 were analyzed. According to the results of LULC analysis, forest and grassland were the primary land use types in the Selenga River Basin. The built area, forest, and cropland showed an increasing trend, while the grassland area showed a fluctuating decreasing trend. From 1990 to 2010, the comprehensive land use dynamic degree showed a trend of rising first and then falling, specifically from 0.13% in 1990 to 0.29% in 2010, and will drop to 0.06% by 2040, indicating that the range of land use change is becoming more and more stable. The landscape ecological risk assessment shows a distribution pattern of “low at the edge and high in the middle”. The landscape ecological risk index (LER) first increases and then decreases, with the peak value in 2010 (0.085). By calculating the spatial aggregation of LER and the partial correlation with climate, we found that the Moran’s I index showed an “anti-V”-shaped change trend from 1990 to 2040, and the average landscape ecological risk presents positive spatial correlation, primarily with high-value aggregation, and peaked in 2010. Precipitation had a negative correlation with landscape ecological risk controlling for temperature, while there was a positive relationship between temperature and landscape ecological risk under the influence of controlling precipitation. This study provides a scientific basis for LULC planning in the Selenga River Basin, and is of great significance for maintaining the ecological security of the Mongolian Plateau.

Landscape Ecological Risk Assessment for the Tarim River Basin on the Basis of Land-Use Change

Land-use variation indicates the spatial differentiation of regional ecological risk. Landscape ecological risk assessment (LERA) has been used for the measurement and prediction of environmental quality. In the present study, the land-use dynamics of the Tarim River Basin from 2000 to 2020 were quantitatively analyzed using ENVI 5.6 software based on Landsat TM and ETM+ images (2000, 2010, and 2020). Moreover, the ecological risk level and its spatiotemporal differentiation features were explored using geostatistical methods based on landscape pattern indices. The results show that: (1) From 2000 to 2020, the arable land area increased the most (12,130.272 km2), and the woodland, wetland, water bodies, and building-land areas increased by 2416.541 km2, 4103.789 km2, 3331.230 km2, and 2330.860 km2, respectively. However, the bare-land area decreased the most (18,933.943 km2). (2) From 2000 to 2020, a decrease was detected in the landscape ecological risk index (LERI) of the basin, and the very low-, low-, and moderate-risk areas had the largest decrease. In addition, the area of the low- and moderate-risk areas gradually increased, while that of the high-risk areas was reduced. (3) The conversion rate of low-risk areas to very low-risk areas was the largest (5144.0907 km2/a), followed by that of high-risk areas to moderate-risk areas (4994.4765 km2/a). Therefore, the overall landscape ecological risk (LER) of the basin was reduced from 2000 to 2020, but the ecological risk of some areas, especially that of the glaciers and permanent snow-covered areas, still needs close attention.

A Novel Integrated Spatiotemporal-Variable Model of Landscape Changes in Traditional Villages in the Jinshaan Gorge, Yellow River Basin

Spatiotemporal studies of landscape pattern evolution in traditional villages are beneficial for addressing complex urbanization and global climate change. Using the traditional villages of Jiaxian and Linxian in the Jinshaan Gorge of the Yellow River Basin, this study employed a three-dimensional (3D) analysis involving three spatial scales (macro, meso, and micro), temporal scales (past, present, and future), and variables (humanity, society, and nature) based on the methods of spatiotemporal data analysis (SDA), geographic information system, remote sensing, and landscape pattern index (LPI) by Fragstats. On the macro scale, a significant turning point in ecological conservation awareness was indicated by LPI and SDA. Urban and rural construction land continuously increased because of urbanization. Plowland, grassland, and woodland were the main influencing factors in the evolution of rural settlements, with a 0.42% cumulative transformation rate. On the meso scale, the interactions and mutual promotion of mountain and aquatic environments, aquatic facilities, agricultural production, and cultural heritage have shaped the socioeconomic dimensions of evolution. On the micro scale, with urbanization, some traditional humanistic spaces have lost their original functions. A novel spatiotemporal-variable quantitative model explored the spatiotemporal evolution characteristics of human–land coupling, which can be used for the sustainable development of river basins worldwide.

Analysis of Land Use Change Characteristics and Its Driving Forces in the Loess Plateau: A Case Study in the Yan River Basin

Land resources are closely intertwined with human survival, making it crucial to explore the spatiotemporal changes and driving forces of land use. In this study, the Yan River Basin in the Loess Plateau was selected as the study area. The Mann–Kendall trend test, Pettitt’s test, landscape pattern indices, and other methods were employed to explore characteristics and driving factors of land use change from 1990 to 2020. The results indicate that: (1) The areas of forest and impervious showed a significant increasing trend and suddenly changed in 2004. Change-point years for the area of cropland and grassland were 2005 and 1999, respectively. The main transition of land use types was from cropland to grassland and from grassland to forest. (2) Patches showed a trend towards regularization and simplification, indicating the strengthening of human activities’ impact on spatial patterns. (3) Both social and natural factors jointly influenced land use change in the Yan River Basin. The Grain for Green (GfG) project was the main driving factor in accelerating land use transformation. This study aims to provide a basis for the scientific management of land resources and serve as an example for related research on land use change in the Loess Plateau.

Agricultural wetland utilization based on land cover restoration and water–ecosystem nexus

Abstract Wetlands, as a special ecological environment, are not only important biodiversity conservation areas but also one of the important agricultural resources. Agriculture plays an irreplaceable role in human society. It is directly related to human survival and development, and is also a part of people's environmental awareness and cultural inheritance. Based on the principles of sustainable development and strengthening environmental protection, people should pay more attention to the development and improvement of agriculture. However, with the advancement of urbanization, the area of wetlands continues to decrease, causing damage to ecosystems and posing a threat to some agricultural production. This article combined the transfer matrix of agricultural wetland utilization, landscape change rate, and landscape pattern index, used RS (Remote Sensing) and GIS (Geographic Information System) technologies to analyze the dynamic changes in agricultural wetland utilization and landscape of Honghu Lake in the Four Lakes region, and explored its changing factors. The results indicated that the construction land area showed an increasing trend in 2016, 2019, and 2022, while the wetland area of rice fields showed a first decreasing and then increasing trend.

A Critical Assessment of Master Development Plan and Landscape Pattern of Jaipur City

There are various factors that influence the land use/land cover changes and spatial pattern of the landscape. The land use/land cover categories of existing land use map-2009 and master development plan-2025 are reorganized into 8 land use/land cover categories to measure the changes if everything goes according to the Master Development Plan-2025. The ArcGIS 10.3 and Erdas 14 software have been used to generate statistics and maps. The Fragstats 4.2 software has been used to analyse the indices of the landscape pattern. The urban area (i.e. Jaipur city region, satellite towns, and transport corridors) was 19.94% in MDP-2011 that is expected to increase to 54.3% in MDP-2025. During 2009-2025 the JDA aims to increase built-up from 48.79% to 72.95% in JMC. The ecological area is also expected to increase from 24.55% (MDP-2011) to 30.4% (MDP-2025). The rural area is expected to decrease significantly from 55.51% (MDP-2011) to 15.31% (MDP-2025). Thematic change dynamics reveal that in the JMC most of the agricultural land and vacant land will be converted into built-up, urban greenery, and institutional land. The landscape metrics analysis reveals that land use conversion is reducing the diversity of land use/land cover patches but patches are being more spatially aggregated. The diversity and heterogeneity of patches will reduce but the aggregation of patches will cause an increase in the patch size.

The association between dietary pattern and visceral adiposity index, triglyceride-glucose index, inflammation, and body composition among Iranian overweight and obese women

The aim of the present study was to investigate the association between dietary patterns, derived through latent class analysis (LCA), with visceral adiposity index (VAI), Triglyceride-Glucose Index (TyG), inflammation biomarkers, and body composition in overweight and obese Iranian women. For this cross-sectional study, dietary exposure was assessed using a validated 147-item semi-quantitative food frequency questionnaire (FFQ). Dietary patterns were derived through LCA. Binary logistic was performed to test the associations of dietary patterns with VAI, TyG, inflammation biomarkers, and body composition. Health centers in Tehran, Iran. 376 obese and overweight women, aged > 18 years. Two dietary patterns were identified using LCA modeling: healthy and unhealthy. Women in the unhealthy class were characterized by higher consumption of fast food, sweetened beverages, grains, unhealthy oils, butter and margarine, and snacks. Compared with the healthy class, the unhealthy class was associated with an increased risk of higher fasting blood sugar (FBS) (OR = 6.07; 95% CI: 1.33–27.74, P value = 0.02), c-reactive protein (CRP) (OR = 1.72; 95% CI: 1.05–2.80; P value = 0.02), and lower fat free mass index (FFMI) (OR = 0.56; 95% CI: 0.35–0.88, P value = 0.01), after adjusting for confounders. We found that adherence to an unhealthy dietary pattern was associated with decreased FFMI and increased FBS and CRP using LCA, but not with the rest of the variables. Further studies should be conducted to confirm the veracity of these findings.

Landscape Dynamics and Ecological Risk Assessment of Cold Temperate Forest Moose Habitat in the Great Khingan Mountains, China.

The change in habitat pattern is one of the key factors affecting the survival of the moose population. The study of the habitat landscape pattern is the key to protecting the Chinese cold-temperate forest moose population and monitoring the global distribution of moose. Through the ecological risk assessment of the moose habitat landscape pattern in a cold-temperate forest, we hope to assess the strength of habitat resistance under stress factors. This study provides a theoretical basis for the protection of the moose population in the cold-temperate forest in China and the establishment of the cold-temperate forest national park. In the study, the MaxEnt model, landscape index calculation and ecological risk assessment model construction were used to analyze the field survey and infrared camera monitoring data from April 2014 to January 2023. The habitat suitability layer of the moose population in the Nanwenghe National Nature Reserve of the Great Khingan Mountains was calculated, and the range of the moose habitat was divided based on the logical threshold of the model. The landscape pattern index of the moose habitat was calculated by Fragstats software and a landscape ecological risk assessment model was established to analyze the landscape pattern and ecological risk dynamic changes of the moose habitat in 2015 and 2020. The results showed that under the premise of global warming, the habitat landscape contagion index decreased by 4.53 and the split index increased by 4.86 from 2015 to 2020. In terms of ecological risk: the area of low ecological risk areas increased by 0.88%; the area of medium ecological risk areas decreased by 1.11%; and the area of high ecological risk areas increased by 0.23%. The fragmentation risk of the landscape pattern of the moose habitat tends to increase, the preferred patch type is dispersed, the degree of aggregation is low, and the risk of patch type transformation increases. The middle and high ecological risk areas are mainly concentrated in the river area and its nearby forests, showing a fine and scattered distribution. Under the interference of global warming and human activities, the fragmentation trend of the moose habitat in the study area is increasing, and the habitat quality is declining, which is likely to cause moose population migration. For this reason, the author believes that the whole cold temperate forest is likely to face the risk of increasing the transformation trend of dominant patch types in the cold-temperate coniferous forest region mainly caused by global warming, resulting in an increase in the risk of habitat fragmentation. While the distribution range of moose is reduced, it has a significant impact on the diversity and ecological integrity of the whole cold-temperate forest ecosystem. This study provides theoretical references for further research on the impact of climate warming on global species distribution and related studies. It is also helpful for humans to strengthen their protection awareness of forest and river areas and formulate reasonable protection and sustainable development planning of cold-temperate forests. Finally, it provides theoretical references for effective monitoring and protection of cold-temperate forests and moose population dynamics.

Street network patterns for mitigating urban heat islands in arid climates

ABSTRACT This study explores the impact of street pattern measurements on urban heat islands (UHI) in the arid climate of Mashhad, Iran. The Landsat-8 top-of-the-atmosphere (TOA) brightness images from 2013 to 2021, average values of normalized difference vegetation index (NDVI) and land surface temperature (LST) were calculated. Street pattern measurements, including closeness-centrality, straightness, and street orientation, were employed to analyse the patterns in each district. The results indicated that districts with higher straightness and lower closeness-centrality exhibit cooler surface temperatures. Strong correlations were observed between LST and NDVI, straightness, and local closeness-centrality. The research highlighted the importance of considering street network measurements in long-term urban planning and design to mitigate the UHI effect in arid regions. A moderate grid street pattern with a reasonable distribution of green spaces throughout the region is suggested to reduce surface temperatures sustainably. Street pattern indexes, such as straightness and local closeness-centrality, are identified as significant factors in urban design to mitigate UHI. These findings have implications for urban planners, who can use this information to create street network patterns with lower UHI effects by reducing local closeness-centrality and increasing straightness.

Pneumatic Defoliation Enhances Fruit Skin Color and Anthocyanin Pigments in ‘Picnic’ Apples

Apple skin color is essential for market value. Therefore, this study evaluated the efficiency of pneumatic defoliation (PD) on the enhancement of red skin color and anthocyanin pigments in ‘Picnic’ apples. Three weeks before harvesting, apple trees were treated with PD with low- (0.7 bar) and high- (0.9 bar) air pressure at a tractor driving speed of 2 km/h. Undefoliated trees served as controls. Higher leaf defoliation and leaf damage rates were observed in the high-PD treatment than those in the low-PD treatment. Photosynthetically active radiation inside the canopies was the highest in trees subjected to high-pressure PD than in those that underwent low-pressure PD and the controls. At harvest, the fruit color (a*) value, red-colored area, and anthocyanin content in the fruit skin were the highest in the high-PD treatment, intermediate in the low-PD treatment, and the lowest in the control treatments. Additionally, a higher expression of anthocyanin biosynthetic genes was observed in both defoliation treatments, especially under high PD. However, except for higher flesh firmness under low PD, the L* and b* values and fruit quality indices (fruit weight, starch pattern index, titratable acidity, soluble solids content, and sunburn occurrence) were not significantly affected by either PD treatment. In conclusion, PD can be used to enhance skin coloration and anthocyanin pigments in apples; further PD with high air pressure achieved optimum red skin coloration in ‘Picnic’ apples.

Factors impacting ecological network in Changsha-Zhuzhou-Xiangtan urban agglomeration, China—Based on the perspective of functional performance

Research on ecological network of highly urbanised areas still suffers from a lack of species specificity in the identification of sources and corridors, solidified identification range with errors, and neglect of stepping stones. This study examined the evolution of ecological network components (habitats and corridors) of the active urban birds, with factors that impact them, from the perspective of functional performance, with the aim of evaluating ecological networks using a flexible identification approach. Habitat function performance (level of ecological source function performance, SFP; level of ecological stepping-stone function performance, SsFP) and corridor function performance (CFP) per grid were constructed using a flexible identification strategy to ensure that the ecological network function of each grid was not overlooked. Additionally, nonlinear relationships between bird habitats in ecological network components and three driving factor types such as topography, resistance, and landscape pattern were explored at the global scale using the Moran’s I, geographical detector, and regression equations. Local regressions were used to determine the impact of regional landscape patterns on CFP for management recommendations. The following results were observed: (1) Of the 238 grids with significant continuous changes in SFP and SsFP, scenario 16 (S16: SFP continuously decreasing with SsFP continuously increasing) accounted for 33.40%, indicating more grids had a transfer in primary function performance from source to stepping stones, mainly in the central part of Changsha-Zhuzhou-Xiangtan urban agglomeration (CZXUA). The amount of change in the continuous change scenario was concentrated within the range 0.2–0.6. (2) Spatial correlation analysis showed that the positive indicators, percentage of construction land (CLP) and nighttime lighting data (NLD), and the negative indicator, normalised difference vegetation index (NDVI), in resistance had consistently increasing negative and positive correlations with SFP, whereas the correlations with the landscape pattern indices remained stable. Topography and resistance factors contributed more to the spatial heterogeneity of SFP, whereas their contribution to SsFP demonstrated the opposite trend. The regression relationship between habitat function performance and explanatory variables showed a high R2 value for nonlinear fitting. (3) Multiscale CFP was identified based on habitat function and the contribution of resistance factors. Geographically weighted regression analysis showed significant positive and negative impacts on CFP at the local scale, with landscape diversity and patchy irregularities providing more spaces for potential ecological corridor functions, and that regional landscape regulation strategies need to be weighed from multiple perspectives. Overall, this study proposes a flexible method for identifying ecological networks and multi-scale urban ecological management strategies.

Response of the Desertification Landscape Patterns to Spatial–Temporal Changes of Land Use: A Case Study of Salaxi in South China Karst

Land use change and karst desertification (KD) are interdependent. It is crucial to investigate the relationship between the KD landscape and spatial–temporal changes in land use for effective and sustainable KD management practices in karst plateau mountains. In this study, we analyzed the spatial and temporal characteristics, evolution in the pattern of land use, and KD in the Salaxi study area from 2009 to 2019, using the landscape pattern index and KD evolution trajectories, and discussed their response relationships. The results revealed the following: (1) In Salaxi, cultivated land predominantly transformed into shrubland, grassland, and woodland. The area of grassland, construction land, and garden land significantly increased, with respective increments of 379.85%, 157.14%, and 1847.81%. Conversely, the area of unutilized land decreased from 53.56 hm2 to 8.55 hm2, with the proportion declining from 0.62% to 0.10%. KD primarily occurs in shrubland, cultivated land, and woodland. (2) The areas of non-KD and potential KD have increased. There was a noticeable conversion of light and medium KD into potential KD, with areas of 1206.84 hm2 and 459.47 hm2, respectively. The KD landscape is dominated by stable and weakening ecological restoration. The comprehensive ranking of the incidence of soil KD in the study area is as follows: yellow soil > yellow-brown soil > coarse bone soil > limestone soil > purple soil. (3) The land use landscape index, the evenness index, and the fragmentation index in the demonstration area increased by 0.263, 0.120, and 0.534, respectively, while the KD landscape index, evenness index, and fragmentation index decreased by 0.360, 0.123, and 1.098, respectively. Additionally, the spreading index and aggregation index of the land use landscape decreased by 9.247 and 3.086, respectively, while the KD landscape’s spreading index and aggregation index increased by 6.688 and 0.430, respectively. Both the sub-dimension indexes of the land use landscape and the KD landscape increased by 0.009. Overall, the landscape pattern of KD changes in response to land use variations and different land types exhibited varying responses to KD. The study of KD and land use landscape patterns can provide references for national strategies on KD control and the development of ecological industries.

Association of blood donor characteristics and in vitro haemolysis of packed red blood cell concentrates during storage.

Blood donor variability can affect the storage properties of packed red blood cells (PRBCs). This study aimed to determine the association of donor characteristics with in vitro storage haemolysis of PRBCs. In the prospective observational study, a total of 109 whole blood donors were enrolled using the purposive sampling method. A pre-donation sample was collected for haemoglobin (Hb) and serum uric acid (UA) levels. PRBC aliquots were tested for potassium, lactate dehydrogenase (LDH), Hb, haematocrit, plasma Hb and haemolysis on days 1, 21 and 35 of storage. The association of these parameters with donor age, sex, donation status, dietary pattern and body mass index was determined. Mean haemolysis was significantly higher in PRBCs from donors with UA levels ≤6 mg/dL than donors with UA levels >6 mg/dL on day 35 of storage (0.22 ± 0.11 vs. 0.18 ± 0.07, p = 0.03). Median plasma Hb (mg/L) was significantly higher in PRBCs from first-time donors on day 21 (586 vs. 509, p = 0.05) and day 35 (1507 vs. 1358, p = 0.02) of storage in comparison to frequent donors. Significantly higher mean potassium (p = 0.04 day 1; p = 0.02 day 21) and median LDH values (p = 0.02 day 1, p = 0.05 day 21) were observed in PRBCs from male donors. A statistically significant positive association was observed between donor UA and LDH levels of PRBCs on day 35 of storage (β coefficient: 715.52, p-value: 0.003) on multiple regression analysis. In vitro haemolysis of PRBCs is affected by blood donor characteristics.

Remote Sensing Monitoring and Spatial Pattern Analysis of Non-Grain Production of Cultivated Land in Anhui Province, China

In recent years, non-grain production of cultivated land (NGPCL) has become increasingly prominent in China, seriously affecting food production and threatening the country’s food security. However, there is a lack of large-scale and high-precision methods for remote sensing identification of NGPCL. From the perspective of effective management of cultivated land resources, the characteristics of the spatial patterns of NGPCL, both on a large scale and at a patch scale, need to be further studied. For solving this problem, this paper uses the Google Earth engine (GEE) cloud computing platform and multi-source remote sensing data with a machine learning algorithm to determine the occurrence of NGPCL in Anhui province in 2019, and then uses nine selected landscape pattern indexes to analyze the spatial patterns of NGPCL from two aspects, specifically, economic development level and topography. The results show that: (1) terrain features, radar features, and texture features are beneficial to the extraction of NGPCL; (2) the degree of separation obtained by using an importance evaluation approach shows that spectral features have the highest importance, followed by index features with red edges, texture features, index features without red edges, radar features, and terrain features; and (3) the cultivated land in Anhui province in 2019 is mainly planted with food crops, and the phenomenon of NGPCL is more likely to occur in areas with high economic development levels and flat terrain. Aided by the GEE cloud platform, multi-source remote sensing data, and machine learning algorithm, the remote sensing monitoring approach utilized in this study could accurately, quickly, and efficiently determine NGPCL on a regional scale.

Spatial Patterns of Urban Green-Blue Spaces and Residents’ Well-Being: The Mediating Effect of Neighborhood Social Cohesion

Urban green-blue spaces (UGBS) can benefit residents’ well-being through multiple pathways. Previous studies have confirmed that the quantity and composition of UGBS can promote neighborhood social cohesion, which subsequently contributes to residents’ physical and mental health. However, there has been little attention paid to the spatial patterns of UGBS in such relationships. This study adopted landscape pattern indexes to characterize the spatial patterns of UGBS and explored the mediation effect of neighborhood social cohesion between the spatial patterns of UGBS and residents’ well-being, measured by self-rated health (SRH) and happiness. Partial Least Squares Structural Equation Model (PLS-SEM) was used for analyses with data obtained from the 2018 Shandong Provincial Social Survey Questionnaire (SGSS), which included 773 selected residents in urban areas. The results indicated that (1) there was a mediation effect of neighborhood social cohesion between the spatial patterns of UGBS and residents’ SRH and happiness; (2) the aggregation and diversity of UGBS had greater impacts on enhancing neighborhood social cohesion than the size, complexity, and fragmentation; (3) the aggregation and diversity of UGBS had indirect effects on improving happiness and SRH, and the aggregation of UGBS had a direct positive effect on SRH. By focusing on the spatial patterns of UGBS and neighborhood social cohesion, this study extends current debates on the pathways among UGBS, social cohesion, and public health. Urban planning strategies were proposed to increase the benefits of UGBS in urban areas.

Identifying key landscape pattern indices influencing the NPP: A case study of the upper and middle reaches of the Yellow River

Human activities and climate change directly affect the composition, structure, and function of ecosystems and, consequently, their net primary productivity (NPP). In this study, we explored the response relationships between landscape pattern indices and NPP changes in three major vegetation types (forest, grassland, and shrubland) in the upper and middle reaches of the Yellow River Basin using a random forest model. The results showed that landscape fragmentation increased, leading to higher landscape heterogeneity and edge effects. Patch shapes became more irregular, and spatial distribution became more dispersed. From 2000 to 2015, both vegetation types and NPP showed significant spatial heterogeneity in the study area. The number of patches (NP), largest patch index (LPI), and percent-like adjacency (PLADJ) metrics were used to determine the core landscape characteristics to assess the NPP changes in forest, shrubland, and grassland, respectively. This study provides a basis for understanding the relationships among landscape patterns, vegetation types, and NPP and serves as a reference for developing NPP predictive models in the Loess Plateau region.

Shell Dimension-Weight Relationship and Condition Index of the Invasive Mussel Mytella strigata in Sasmuan, Pampanga, Philippines

A total of 300 Mytella strigata were collected at three sampling points in the mussel coastal demonstration farm in Sasmuan, Pampanga, and subjected to morphometric and gravimetric measurements for the evaluation of its growth pattern and condition index. Designated sampling sites were based on the distances to the river mouth (200 m, 400 m, and 600 m) with varying water quality parameters (temperature, salinity, pH, water velocity, and chlorophyll-a). Mussels in Site 2 had significantly larger shell dimensions (SL = 2.862 cm, SW = 1.458 cm, SH = 0.926 cm), shell weight (0.640 g), and total live weight (1.150 g). Significantly higher (p < 0.05) soft-tissue dry weight (0.083 g), however, was obtained in Site 3, while comparable (p >0.05) soft tissue weight was observed in Site 2 (0.364 g) and Site 3 (0.413 g). Nevertheless, mussels in all sites demonstrated negative allometric growth (b < 3). The length-weight relationship revealed a weak to moderate, positive correlation. A significantly higher (p < 0.05) condition index was obtained in Site 3, which could have been influenced by higher chlorophyll-a and substantially lower water velocity. As such, this signifies its potential to have a well-established population in this spatial distance (600 m) from the river mouth. Hence, regular harvest and product development is recommended as strategic options to control its proliferation.

Analysis of Supply–Demand Relationship of Cooling Capacity of Blue–Green Landscape under the Direction of Mitigating Urban Heat Island

Urban blue–green landscapes (UBGLs) have an important impact on the mitigation of UHIs. Clarifying the supply/demand relationship of the UBGLs’ cooling effect can serve as an indicator for high-quality urban development. We established the cooling capacity supply–demand evaluation systems of UBGLs by using multi-source data and a suitable landscape mesh size. Furthermore, we utilized the coupling coordination degree (CCD) model and the linear regression equation method to explore the spatial distribution of and variation in UBGLs’ cooling efficiency. The results showed the following: (1) according to the UBGL/SUHI landscape pattern index and the Pearson correlation coefficient of the land surface temperature (LST), the optimal mesh size was found to be 1200 m. (2) According to the unitary linear regression calculation, the matching of the cooling capacity supply and demand in the context of Qunli New Town showed obvious polarization; furthermore, Hanan new town and old town are more balanced than Qunli new town. (3) According to the spatiotemporal dynamic evolution of CCD, the proportion of moderate coordination- advancing cooling efficiency is the highest, reaching 35.3%. Second are moderate imbalance–hysteretic cooling efficiency (18.4%) and moderate imbalance–systematic balanced development (13.7%), with the old city highly coordinated area as the center and the coupling coordination type (gradually outward) turning into a state of serious imbalance, and then back into a state of high coordination. The findings of the investigations enriched a new viewpoint and practical scientific basis for UBGL system planning and cooling efficiency equity realizations.

Responses of the Siberian crane population to temporal and spatial hydrological variations in stopover sites in northeast China

The Siberian crane (Grus leucogeranus), a critically endangered species, is used as an indicator species for ecosystem stability because of its sensitivity to the environment. The distribution of Siberian cranes has shown dramatic fluctuations on an order of magnitude at the main stopover site (Jilin Momoge National Nature Reserve) since the present century, which poses a great challenge to the conservation of endangered species. Research on the threshold values of key factors of the Siberian crane in stopover habitats and the relationship between the Siberian crane and hydrological temporal and spatial fluctuations can promote endangered species conservation. The response of population changes and distribution patterns of Siberian cranes to hydrological temporal and spatial patterns of wetlands was analyzed from 1984 to 2020. The results showed that population changes and distribution patterns of Siberian cranes were highly correlated with hydrological temporal and spatial patterns in the study area, and their variation trend was the same. However, there were obvious stage migration changes in the core activity area of the Siberian crane (1984–2000, 2001–2010 and 2010–2020). The habitat characteristics of fragmentation, dispersion and complex shape of water bodies changed from steady to dramatic fluctuations and then leveled off in the core activity area of Siberian cranes during the 37 years of migration transit. This was closely related to the early agricultural reclamation and the later ecological water replenishment project in the study area. In addition, the trend of the water pattern index of the spatial distribution of Siberian crane active habitat was also closely related to their habitat selection preference. When the perimeter area fractal dimension of water (1.27–1.40), landscape division index (0.73–0.95) and aggregation index (80.97–91.36) are within a certain stable threshold, the stopover habitat of the Siberian crane is suitable. This study will provide scientific guidance for the conservation of the Siberian crane population and the development of wetland restoration projects.