Pattern Index Research Articles

The Assessment of Biodiversity Changes and Sustainable Agricultural Development in The Beijing-Tianjin-Hebei Region of China

In the face of a series of challenges, such as climate change, population growth, and agricultural intensification, as well as the issue of how to promote sustainable development and guarantee food security, biodiversity, with its unique genetic, ecological, and traditional socio-cultural values, has become an important way to solve this dilemma. Urban biodiversity has continued to decline in recent decades due to rapid urbanization. The agroecosystem health of the Beijing-Tianjin-Hebei region, a typical urban agglomeration economic area, is facing a critical situation. Therefore, assessing the potential of ecosystem diversity in the Beijing-Tianjin-Hebei region and exploring the assessment mechanisms and methods of ecosystem health can provide theoretical support for biodiversity conservation and utilization. In this thesis, the overall ecosystem health of the Beijing-Tianjin-Hebei region was assessed based on the land cover data from 1992 to 2022 and the projected land cover data up to 2032, as well as using the habitat quality indicated by the Fragstats and InVEST models and the landscape pattern index, habitat quality, and mean species abundance (MSA) indicators of the GLOBIO module. The main results are as follows: Habitat quality and mean species abundance (MSA) in the Beijing-Tianjin-Hebei region were observed to show a continuous downward trend over 40 years from a landscape level perspective, and landscape fragmentation due to urbanization was the main reason. Habitat loss and habitat degradation caused by landscape fragmentation led to a decline in biodiversity. The spatial distribution of habitat quality in the Beijing-Tianjin-Hebei region is closely correlated with topography and landscape, being higher in the northwest and lower in the southeast, forming a clear spatial pattern that declined from 0.599 to 0.564 between 1992 and 2032. The mean species richness (MSA) value of the Beijing-Tianjin-Hebei region is significantly affected by infrastructure, especially road construction. With the continuous expansion of the road network, the MSA values in the region generally show a decreasing trend from 0.270 to 0.183 between 1992 and 2032. Based on the above results, it is recommended to carry out several aspects of agrobiodiversity conservation and ecosystem restoration.

The impact mechanism of human activities on the evolution of coastal wetlands in the Liaohe River Delta

IntroductionThis study aims to investigate the impact of human activities on the evolution of coastal wetlands in the Liaohe River Delta. Understanding these impacts is crucial for the management, protection, and sustainable development of the ecological environment in the region.MethodsQuantitative analysis of the evolution of coastal wetlands along the Liaohe River from 1995 to 2020 using Landsat series remote sensing images. This study examines the changes in different landscapes and explores the impact of human activities on wetlands through methods such as land transfer matrix, landscape pattern index, and human activity hotspots.ResultsThe results show that the area of coastal wetlands in the Liaohe River Delta exhibited a fluctuating downward trend from 1995 to 2020. The eastern and western parts of the delta experienced greater disturbance to wetland landscapes due to human activities, while the northern and southern parts were mostly waters and reed lands with a smaller degree of human disturbance. Human activities have led to significant changes in farmland, ponds, rice paddies, construction land, and reed fields, thereby promoting the evolution of coastal wetlands.DiscussionThis article discusses the characteristics of landscape pattern evolution in the study area, as well as the impact of human interference, economy, policies, and other factors on it, and compares it with the evolution patterns of other coastal wetlands in China. The changes in the landscape pattern of the study area are mainly reflected in the reduction and fragmentation of natural wetland areas, which are closely related to human activities, especially the development of construction and agriculture. The main economic manifestation is that the increase in land demand due to economic and urban development has led to the transformation of natural wetlands into construction land and other artificial landscapes. The implementation of regulations such as the Wetland Protection Law has contributed to the rational use and ecological restoration of wetlands, and also reflects the influence of policy factors. Compared with other studies, coastal wetlands in China generally face issues of degradation and loss, mainly caused by human activities, but also affected by natural factors such as rising sea levels, changes in coastlines, and climate change.

Maternal Periconceptional Adherence to a Mediterranean Diet Pattern and Child Body Mass Index Between Ages 3–10 Years by Sex, Age, and Race

Maternal Periconceptional Adherence to a Mediterranean Diet Pattern and Child Body Mass Index Between Ages 3–10 Years by Sex, Age, and Race

Chemical Composition and Therapeutic Potential of Syngonium podophyllum L. Leaves against Hypercholesterolemia in Rats: Liver, Kidney, and Heart Crosstalk

Background: One of the main risk factors for atherosclerosis is hypercholesterolemia Objective: This study aimed to assess hypercholesterolemia's effect on the liver, heart, and kidney and the impact of Syngonium podophyllum L. leaves methanolic extract as a treating agent in a rat model. Methods: Flavonoid components were isolated and identified from the methanolic extract of Syngonium podophyllum L. leaves. Total serum leptin, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), aspartate and alanine aminotransferases (AST and ALT), urea, and creatinine levels were all measured as part of the biochemical evaluation. The liver tissue was tested for levels of malondialdehyde (MDA), glutathione (GSH), superoxide dismutase (SOD), and DNA fragmentation. Results: Thirty-nine compounds were identified by GC/MS profiling of the n-hexane fraction of Syngonium podophyllum L leaves. The major volatile constituents were decane, 4-methyl, decane, N-acetyl 3-pentenyl, 1-amine, 2-methyl, 1-hexene, and 3-hydroxy, propanenitrile, while the major phenolic compounds isolated from methanolic extract were luteolin-7- α-L rhamnoside-4'- O-β-glucopyranoside (1), apigenin 6, 8-di-C-β-glucopyranoside (vicenin 2) (2), quercetin-3-Oα-L-rhamnoside (3), quercetin-7-O-β-glucoside compound (4), luteolin-7-O-β-glucoside (5), 5- hydroxy-6,7,8,4'-tetramethoxy flavone (6), gallic acid (7) and quercetin (8). Hypercholesterolemic rats revealed significant alterations (p ≤ 0.05) in the lipid profile, liver and kidney function, DNA fragmentation pattern and antioxidant indices. With oral cholesterol administration of 30 mg/0.3 mL, 0.7% tween/rats fed a high-fat diet for nine weeks, treatment with leaves extract (250 mg/kg body weight) was able to restore all biochemical parameters as well as the architectures of the liver and heart. Conclusion: Due to its abundance in physiologically active phenolic and flavonoid components, the methanolic extract of Syngonium podophyllum L. leaves successfully served as a hypolipidemic, anti-atherosclerotic, and antioxidant therapeutic agent.

A dataset of the ecological security patterns in the peripheral region of Poyang Lake from 2000 to 2020

With the continuous expansion of human activities, the habitats of many species are confronted with serious destruction and threats, leading to increasingly prominent ecological security issues. Therefore, it is crucial to establish an ecological security pattern that takes species habitats into consideration, so as to protect biodiversity and maintain ecological balance. Poyang Lake, as a paradise for wildlife, serves as the habitat and breeding ground for many bird species, fish, and other aquatic organisms. Taking the research scope of the peripheral region of Poyang Lake as an example, we produced the land use data for the years 2000, 2010, and 2020 on the basis of the Google Earth Engine platform and the random forest classification method. By integrating morphological spatial pattern analysis, landscape pattern indices, landscape connectivity indices, circuit theory, and long-term land use data, we developed a long-term ecological security pattern for the peripheral region of Poyang Lake from 2000 to 2020, which takes into accounts habitats for various species including fish and birds. This dataset contains various types of data, including innovative elements. In terms of data quality control and evaluation, strict quality control and evaluation processes were conducted on the data used and the predicted results, ensuring the accuracy and credibility of the data and providing effective data support and references for relevant research. The dataset not only comprises indicator data for constructing an ecological security pattern to protect species habitats but also includes historical and predicted ecological security pattern data for the peripheral region of Poyang Lake. It can provide important scientific data support and serve as references for future research on species protection and ecological security patterns in the peripheral region of the Poyang Lake.

Analysis of Landscape Pattern Evolution and Impact Factors in the Mainstream Basin of the Tarim River from 1980 to 2020

The mainstream basin of the Tarim River serves as a vital ecological security barrier that prevents the merging and expansion of deserts and an important strategic corridor directly linking Qinghai and Xinjiang. With society’s development and climate change, ecological issues such as river interruption, vegetation degradation, and land desertification in the basin have notably intensified, and the ecological security is facing a critical test. Exploring the characteristics of landscape changes and their driving factors within the basin is crucial in improving the ecological environment system’s management. Based on land use data from 1980 to 2020, this study analyzed the characteristics of the spatiotemporal changes and pattern evolution of the landscape through a landscape transfer matrix and landscape pattern indices. It further revealed the impact factors of the landscape pattern through canonical correspondence analysis. The results showed that (1) in 1980–2020, the areas of desert, forest, farmland, and settlement landscapes increased, while the area of grassland landscape decreased, and the water landscape showed an “increasing–decreasing–recovery” pattern. The landscape transition types mainly included the transition from grassland to desert; mutual transitions among farmland, grassland, and forests; mutual transitions between water and grassland; and the transition from farmland to settlements. (2) The overall landscape pattern demonstrated increased fragmentation, shape complexity, and evenness with decreased aggregation. Furthermore, different landscapes exhibited distinct characteristics of landscape pattern changes; for instance, grassland landscape showed severe fragmentation, while desert landscape displayed the strongest dominance. (3) The landscape pattern was a result of the combined impact of natural and human factors, with the soil thickness (SOT), road density (ROD), annual actual evapotranspiration (AAE), population density (POD), and mean annual temperature (MAT) exhibiting significant influences. Specifically, the settlement and farmland landscapes were mainly influenced by the mean annual relative humidity (MAH), POD, GDP density (GDP), and distance to artificial water (DAW); the forest, grassland, and water landscapes were mainly influenced by the SOT, soil organic matter content (SOM), AAE, ROD, elevation (ELE), MAT, slope (SLP), and distance to natural water (DNW); and the desert landscape was mainly influenced by the DAW, DNW, SLP, AAE, SOT, SOM, and ROD. These findings can provide a scientific reference for landscape management and restoration, as well as sustainable social and economic development, in the mainstream basin of the Tarim River.

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.

Landscape Ecological Risk and Drivers of Land-Use Transition under the Perspective of Differences in Topographic Gradient

Human activities have caused different degrees of land-use change on different topographic gradients, with impacts on the landscape and ecosystem. Effectively preventing and addressing ecological risk (ER) and achieving harmonious coexistence between humans and nature are important aspects of sustainable development. In this study, we used Gansu Province as an example, adopted five periods of land-use data in 1980, 1990, 2000, 2010 and 2020, and used the geoinformatic Tupu method and the terrain distribution index to study land-use changes under different topographic gradients, and then constructed the landscape ecological risk assessment (LERA) model based on the landscape pattern index to analyze landscape ecological risk (LER) spatiotemporal changes under different topographic gradients, and finally explored the LER driving factors using the geodetector model. The results showed that (1) the dominant land-use types were unused land and grassland, accounting for approximately 74% of the land. The situation of transferring and changing each type was more drastic. The distribution and changes in cropland and built-up land were easily found in low topographic gradient areas with low elevations and small slopes; the distribution and changes in woodland, grassland and water areas were easily found in high topographic gradient areas with high elevations and large slopes. (2) The landscape ecological risk index (LERI) was 0.018, 0.019, 0.019, 0.019 and 0.020, respectively, with spatial expressions of high in the northwest and low in the southeast. Low LER was concentrated in high topographic gradient ecological reserves; high LER was concentrated in low topographic gradient human interference areas and high topographic gradient natural environmental complex areas. (3) Natural factors mainly acted on the LER on moderate and high topographic position gradients; socioeconomic factors mainly acted on the LER on low topographic position gradients. Human interference interacted with natural factors more than human interference alone on LER. This study can provide a scientific basis for ensuring ecological security and sustainable development in areas with complex topography and geomorphology.

The Spatiotemporal Variability of Soil Available Phosphorus and Potassium in Karst Region: The Crucial Role of Socio-Geographical Factors

The contents of soil available phosphorus (AVP) and potassium (AVK) in karstic mountainous agricultural areas have changed rapidly in recent decades. This temporal variation displays strong spatial heterogeneity due to these areas’ complex topography and anthropogenic activities. Socio-geographical factors can reflect the changes in the natural environment caused by human beings, and our objective is to enhance understanding of their role in explaining the changes of AVP and AVK. In a typical karst region (611.5 km2) with uniform soil parent material and low climatic variability, 255 topsoil samples (138 in 2012 and 117 in 2021) were collected to quantify the temporal AVP and AVK changes. Random forest (RF) and partial dependence plot analyses were conducted to investigate the responses of these changes to socio-geographical factors (distance from the nearest town center [DFT] and village density [VD]), topography, biology, and landscape pattern indexes. The mean values of AVP (48.25 mg kg−1) and AVK (357.67 mg kg−1) in 2021 were significantly (p < 0.01) higher than those in 2012 (28.84 mg kg−1 and 131.67 mg kg−1, respectively). Semi-variance analysis showed strong spatial autocorrelation for AVP and AVK, ranging from 7.29% to 10.95% and 13.31% to 10.33% from 2012 to 2021, respectively. Adding socio-geographical factors can greatly improve the explanatory power of RF modeling for AVP and AVK changes by 19% and 27%, respectively. DFT and VD emerged as the two most important variables affecting these changes, followed by elevation. These three variables all demonstrated clear nonlinear threshold effects on AVP and AVK changes. A strong accumulation of AVP and AVK was observed at DFT < 5 km and VD > 20. The AVP changes increased dramatically when the elevation ranged between 1298 m and 1390 m, while the AVK changes decreased rapidly when the elevation ranged between 1350 m and 1466 m. The interaction effects of DFT and VD with elevation on these changes were also demonstrated. Overall, this study examined the important role of socio-geographical factors and their nonlinear threshold and interaction effects on AVP and AVK changes. The findings help unravel the complex causes of these changes and thus contribute to the design of optimal soil phosphorus and potassium management strategies.

A landscape pattern gradient analysis method coupling wavelet algorithm for balancing development and protection activities of the coastal zone: A case study

Due to the economic importance and ecological vulnerability of coastal areas, the optimization of spatial patterns is important for the sustainable development of coastal zones. In this study, a new landscape pattern index gradient analysis method coupled with wavelet algorithm (GA-WA) was explored to balance the development and protection activities in the coastal zone. First, based on the classification results of remote sensing images, the gradient detection of the coastal zone was carried out using the cumulative moving window method, and the calculation of the landscape pattern index was carried out using Fragstats software to obtain the gradient change curve of the landscape pattern index. Secondly, the wavelet algorithm was applied to micro-analyze the above gradient change curves, and the results of multiscale analysis of the landscape pattern index in the study area were obtained. Finally, it is demonstrated how this method can help in practical decision making. It was found that:(1) The landscape pattern index gradient analysis method coupled with wavelet algorithms offers a new approach to balance the development and protection of coastal zones. This approach presents an innovative method for optimizing the ecological pattern of coastal zone landscapes from the perspective of macro–micro combination, which is not only applicable to coastal zones but also can be extended to other strip corridor landscapes.(2) The gradient analysis of the coastal zone landscape pattern index provides results at multiple spatial scales, which is superior to the analysis at a single spatial scale. The results of the gradient analysis method are finer and more stable, which solves the uncertainty problem of traditional landscape pattern index analysis. There is a significant difference between the landscape indices of the overall landscape and the gradient landscape, in which the AREA_MN index of the ecological land has the largest difference, reaching 110.18%.(3) Wavelet coefficient variance diagrams, real component contour diagrams, and modulus squared diagrams reveal the characteristics, cycles, and patterns of landscape dynamics changes, as well as the distribution at different gradient window scales. These tools help to identify the driving factors and development trends of landscape dynamics changes and solve problems of functional positioning in undeveloped areas, as well as the transformation of microscopic small parcels within developed areas. By analyzing regular cycles of landscape index changes, it is possible to determine the functional positioning of land and to position human intervention through peaks to guard against risky gradient windows.

An Improved Assessment Method to Estimate (Poly)phenol Intake in Adults with Chronic Pancreatitis

BackgroundInsights into (poly)phenol exposure represent a modifiable factor that may modulate inflammation in chronic pancreatitis (CP), yet intake is poorly characterized and methods for assessment are underdeveloped.AimsThe aims are to develop and test a method for estimating (poly)phenol intake from a 90-day food frequency questionnaire (FFQ) using the Phenol-Explorer database and determine associations with dietary patterns in CP patients versus controls via analysis of previously collected cross-sectional data.MethodsFifty-two CP patients and 48 controls were recruited from an ambulatory clinic at a large, academic institution. To assess the feasibility of the proposed methodology for estimating dietary (poly)phenol exposure, a retrospective analysis of FFQ data was completed. Mann–Whitney U tests were used to compare (poly)phenol intake by group; Spearman correlations and multivariable-adjusted log-linear associations were used to compare (poly)phenol intakes with dietary scores within the sample.ResultsEstimation of (poly)phenol intake from FFQs was feasible and produced estimates within a range of intake previously reported. Total (poly)phenol intake was significantly lower in CP vs controls (463 vs. 567mg/1000kcal; p = 0.041). In adjusted analyses, higher total (poly)phenol intake was associated with higher HEI-2015 (r = 0.34, p < 0.001), aMED (r = 0.22, p = 0.007), EDIH (r = 0.29, p < 0.001), and EDIP scores (r = 0.35, p < 0.001), representing higher overall diet quality and lower insulinemic and anti-inflammatory dietary potentials, respectively. ConclusionsUsing enhanced methods to derive total (poly)phenol intake from an FFQ is feasible. Those with CP have lower total (poly)phenol intake and less favorable dietary pattern indices, thus supporting future tailored dietary intervention studies in this population.Graphical

Coupled InVEST–MGWR modeling to analyze the impacts of changing landscape patterns on habitat quality in the Fen River basin

The present study employed remote sensing images of the Fen River Basin from 2005, 2010, 2015, and 2020 as the primary data source. The software ENVI, ArcGIS, and Fragstats 4.2 were utilized to measure the landscape pattern index of the Fen River Basin. A collinearity test was conducted to remove any redundant landscape pattern indices. Based on the selected landscape indices, the landscape pattern index values were ascertained as follows. Using the shifting window method, the landscape pattern index of the Fen River Basin was obtained. Second, the habitat quality in the Fen River Basin was assessed using the InVEST model, and the spatial autocorrelation approach was employed to confirm that the habitat quality was spatially autocorrelated. Finally, the spatial impacts of landscape pattern indices on habitat quality were examined using the MGWR model. The results show that (1) the Fen River Basin's overall habitat quality declined between 2005 and 2020; however, the deterioration slowed with time and had a typical "poor in the middle and high around the margins" spatial distribution. The habitat quality of the low-value area continued to increase, the habitat quality of the lower-value area decreased annually, the habitat quality of the middle-value area decreased and then increased, the habitat quality of the higher-quality area tended to increase, decrease, and then increase again, and the habitat quality of the high-quality area decreased annually. (2) The fit of the MGWR model was greater than those of the OLS and traditional GWR models, and it was able to more clearly illustrate the various roles that landscape pattern indices and habitat quality play in one another. (3) Changes in landscape patterns had a major impact on habitat quality; habitat quality was positively impacted by PD and AI, negatively impacted by MESH, and had positive and negative bidirectional effects from CONTAG and AI.

Digital image analysis-based assessment of starch pattern index in commercial apple cultivars: reliability and applicability

Digital image analysis-based assessment of starch pattern index in commercial apple cultivars: reliability and applicability

Analysis of the evolution and influencing factors of ecological environment quality after the transformation of resource-exhausted cities based on GEE and RSEI: a case study of Xuzhou City, China

ABSTRACT This study used Google Earth Engine (GEE) to get and process Landsat images of Xuzhou from 2008 to 2020, and built remote sensing ecological indices (RSEI). This study analyzed the spatiotemporal features and drivers of ecological environment quality after Xuzhou’s transformation using landscape pattern index, spatial autocorrelation, and geographic detector methods. The results showed that: (1) The ecological environment quality of Xuzhou improved steadily but unevenly from 2008 to 2020; the west and central urban areas had poor but improving quality, while the east had the opposite trend; (2) The landscape pattern indices of ecological environment quality in different regions of Xuzhou did not change consistently from 2008 to 2020; (3) The spatial distribution of ecological environment quality had significant autocorrelation, with high-high clusters in the east and low-low clusters in the center and the urban areas of each district and county; (4) NDVI is the component index that has the greatest impact on the changes in the RSEI. Among the single factors, land use conditions have the strongest influence on ecological environmental quality. After the interaction of dual factors, the explanatory power is stronger than that of any single factor. The research results can support urban planning and design, ecological environment protection, etc. in Xuzhou, and offer insights for monitoring and evaluation of ecological environment quality after the transformation of resource-exhausted cities.

The Association Between Overall, Healthy, and Unhealthy Plant-Based Diet Index and Risk of Prediabetes and Type 2 Diabetes Mellitus: A Systematic Review and Dose-Response Meta-Analysis of Prospective Studies.

The global incidence of prediabetes and type 2 diabetes mellitus (T2DM) has increased substantially in recent years. Among the established, modifiable lifestyle factors associated with favorable prediabetes and T2DM risk, healthy dietary patterns have attracted considerable attention. The association between adherence to plant-based dietary pattern indices (PDIs), including the overall PDI (O-PDI), healthy PDI (H-PDI), and unhealthy PDI (U-PDI), and the risk of prediabetes and T2DM was investigated in this study. A literature search was conducted of the PubMed/Medline, Scopus, and Web of Sciences databases from their inception to February 2024. A systematic review and meta-analysis were conducted using random effects models and dose-response analyses. The Cochran Q test and the I2 statistic were used to evaluate heterogeneity between studies. A total of 16 publications, with data on a total of 721 012 participants, were identified for the meta-analysis. According to a pooled analysis, compared with the lowest category of O-PDI and H-PDI adherence, the highest category was associated with a 14% and 19% reduction in T2DM risk, respectively, for O-PDI (effect size [ES] = 0.86; 95%CI, 0.82-0.90; I2 = 57.7) and H-PDI (ES = 0.81; 95%CI, 0.75-0.88; I2 = 82.6). Greater adherence to U-PDI was significantly associated with an 10% increase in the risk of T2DM (ES = 1.10; 95%CI, 1.04-1.16). Consistent associations were found within the predetermined subgroups. As well, there was a nonlinear inverse association between O-PDI, H-PDI, and T2DM risk. No significant association was found between adherence to O-PDI (ES = 0.87; 95%CI, 0.75-1.01; I2 = 68%), H-PDI (ES = 0.99; 95%CI, 0.87-1.13; I2 = 0.0%), and U-PDI (ES = 1.09; 95%CI, 0.94-1.21; I2 = 22.9%) and risk of prediabetes. These findings underscore the importance of dietary selections within the framework of a plant-based dietary pattern, particularly when incorporating healthful, plant-based foods, which may have potential benefits in reducing the T2DM risk. PROSPERO registration no. CRD42023459851.

Regular widespread aggregations of the oceanic jellyfish Pelagia noctiluca in the northeast Atlantic over 11 years

The jellyfish Pelagia noctiluca form extensive aggregations in the Mediterranean Sea that can exert top-down control on prey and cause mass-mortalities in fish farms. The description of extensive aggregations of P. noctiluca in the northeast Atlantic in 2007 coupled with a subsequent mortality event of farmed salmon in Northern Ireland prompted further investigation of the species in this region. We collected standardised P. noctiluca biomass from 1938 fisheries trawls over 11 years (2008–2018) covering ∼200,000 km2 of northeast Atlantic shelf seas. While a linear trend in P. noctiluca was not identified, the mean annual biomass exhibited significant fluctuations, with particularly elevated levels in 2009, 2013, 2014 and 2016 (0.05, 0.02, 0.01 and 0.02 kg ha−1, respectively). Mean biomass was higher in the northern (0.028 kg ha−1) and western portions (0.005 kg ha−1) of the study area compared to the southwestern (0.003 kg ha−1) and southeastern portions (0.001 kg ha−1). A binomial generalised linear mixed model of P. noctiluca biomass data indicated that higher P. noctiluca occurrence was driven by a positive Eastern Atlantic Pattern index (strongest effect), south-easterly winds, a negative North Atlantic Oscillation index and lower sea-surface temperatures (weakest effect). The fixed effects accounted for 36.81% of the variance in P. noctiluca occurrence data, while a random year effect further explained an additional 24.06% of the variance. These conditions may destabilise the European Slope Current in autumn-winter which promotes the transport of P. noctiluca from oceanic sources onto the northeast Atlantic shelf. Our findings represent a dramatic shift in our understanding of this species in the northeast Atlantic which may have significant ecological impacts, from predation on fish eggs and larvae to providing food for oceanic sunfish.

Persistent trends and inefficiencies in the Greek housing market: a sentiment based approach

PurposeWe examine the aggregate price trend of the Greek housing market from a behavioral perspective.Design/methodology/approachWe construct a behavioral real estate sentiment index, based on relevant real estate search terms from Google Trends and websites, and examine its association with real estate price distributions and trends. By employing EGARCH(1,1) on the New Apartments Index data from the Bank of Greece, we capture real estate price volatility and asymmetric effects resulting from changes in the real estate search index. Enhancing robustness, macroeconomic variables are added to the mean equation. Additionally, a run test assesses the efficiency of the Greek housing market.FindingsThe results show a significant relationship between the Greek housing market and our real estate sentiment index; an increase (decrease) in search activity, indicating a growing interest in the real estate market, is strongly linked to potential increases (decreases) in real estate prices. These results remain robust across various estimation procedures and control variables. These findings underscore the influential role of real estate sentiment on the Greek housing market and highlight the importance of considering behavioral factors when analyzing and predicting trends in the housing market.Originality/valueTo investigate the behavioral effect on the Greek housing market, we construct our behavioral pattern indexes using Google search-based sentiment data from Google Trends. Additionally, we incorporate the Google Trend index as an explanatory variable in the EGARCH mean equation to evaluate the influence of online search behavior on the dynamics and prices of the Greek housing market.

Diversity and Distribution Patterns of Dragonflies in The Region Bagek Kembar Ecotourism, Sekotong

Dragonflies have an important role as environmental bioindicators, especially as indicators of the success of mangrove ecosystem restoration projects and their distinctive color has becomes an ecotourism attraction, so this research is important to do. This research aims to determine the diversity and distribution patterns of dragonflies in the Bagek Kembar Sekotong Mangrove Ecotourism area. This is an explorative descriptive study and was carried out between December 2023-January 2024. The research method used was catching dragonflies with insect nets following three transect paths along the river flow in the Bagek Kembar Sekotong Mangrove Ecotourism area. Analysis of species diversity data using the Shannon Wiener diversity index and calculation of the dragonfly distribution pattern index using the variance test. Based on the research results, 9 species of dragonflies were obtained, including 8 species of dragonflies (Anisoptera) and 1 species of dragonflies (Zygoptera). The diversity index (H') of dragonflies at the observation location is 1,866. The conclusion is that diversity of dragonflies at the research location is in the medium category. The distribution pattern of dragonflies at the research location shows that one Potamarcha congener species has a regular distribution pattern and the other 8 species that had groups distribution pattern.

Nanoscale Phase and Orientation Mapping in Multiphase Polycrystalline Hafnium Zirconium Oxide Thin Films Using 4D-STEM and Automated Diffraction Indexing.

Ferroelectric hafnium zirconium oxide (HZO) holds promise for nextgeneration memory and transistors due to its superior scalability and seamless integration with complementary metal-oxide-semiconductor processing. A major challenge in developing this emerging ferroelectric material is the metastable nature of the non-centrosymmetric polar phase responsible for ferroelectricity, resulting in a coexistence of both polar and non-polar phases with uneven grain sizes and random orientations. Due to the structural similarity between the multiple phases and the nanoscale dimensions of the thin film devices, accurate measurement of phase-specific information remains challenging. Here, the application of 4D scanning transmission electron microscopy is demonstrated with automated electron diffraction pattern indexing to analyze multiphase polycrystalline HZO thin films, enabling the characterization of crystallographic phase and orientation across large working areas on the order of hundreds of nanometers. This approach offers a powerful characterization framework to produce a quantitative and statistically robust analysis of the intricate structure of HZO films by uncovering phase composition, polarization axis alignment, and unique phase distribution within the HZO film. This study introduces a novel approach for analyzing ferroelectric HZO, facilitating reliable characterization of process-structure-property relationships imperative to accelerating the growth optimization, performance, and successful implementation of ferroelectric HZO in devices.