Number Of Patches Research Articles

Landscape configuration and storm characteristics drive spatial patterns of wind disturbance in boreal forest landscapes

ContextWind is an important disturbance in circumboreal forests, and its frequency and severity may change with climate change, highlighting the need to understand the drivers of wind disturbance. Currently, how landscape configuration drives wind disturbance is poorly understood.ObjectivesWe investigated whether and how landscape configuration is related to the extent and spatial pattern of wind disturbance, and how these relationships vary between windstorms and thunderstorms.MethodsWe used salvage logging data after 16 storms that occurred in Finland between 2011 and 2021. We placed a total of 301 landscapes, each encompassing an area of 8024 ha, within the storm tracks and used regression models to test how wind disturbance extent, disturbance patch size, number of disturbance patches, and disturbance patch clustering were related to landscape configuration and storm characteristics.ResultsIncreasing mean gap size and edge density, including permanent openings (e.g., lakes) and recent harvest gaps, increased disturbance extent, disturbance patch size, and number of disturbance patches. Conversely, increasing mean harvest gap size decreased disturbance patch clustering. Increasing wind speed had the largest contribution to increasing disturbance extent and number of disturbance patches, and decreasing disturbance patch clustering, with the magnitude of the effect varying between windstorms and thunderstorms.ConclusionsThe extent and spatial pattern of wind disturbances varied with landscape configuration and storm characteristics. Disturbance patches were larger in landscapes with large canopy gaps, resulting in a greater disturbance extent, exacerbated by increasing wind speed and thunderstorm development.

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

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

Soil nutrient heterogeneity affects community stability through changing asynchrony in an alpine meadow on the Qinghai-Tibetan Plateau

Soil nutrients are ubiquitously heterogeneously distributed and such heterogeneity can greatly influence plant and population growth, interspecific competition and community structure and productivity. Despite these impacts, it is still unknown how soil nutrient heterogeneity affects community stability. We conducted a three-year experiment in an alpine meadow on the Qinghai-Tibetan Plateau, involving one homogeneous and six heterogeneous treatments of N, P, and K addition. The heterogeneous treatments varied in patch size, patch contrast, and number of patch types. Community stability in the homogeneous treatment tended to be the highest, likely due to high asynchrony among functional groups. However, such effects varied with patch size, patch contrast and number of patch types. Also, the effects of patch contrast and number of patch types on community stability and asynchrony among functional groups depended on patch size. The grass proportion was significantly affected by soil nutrient heterogeneity, and greater number of patch types increased the grass proportion at the small patch size, but not at the large one. Additionally, species richness, Shannon-Weiner index and Simpson index were greater in high patch contrast compared to the homogeneous treatment, but community evenness was not. These results suggest that soil nutrient heterogeneity can influence community stability by modifying functional group asynchrony and community evenness, rather than biomass proportions or other plant diversity indices. Our findings highlight the importance of incorporating soil nutrient heterogeneity in modeling the responses of alpine ecosystems to continuous nitrogen deposition and climate warming.

A reaction-diffusion model for population dynamics in patchy landscapes

We address the linear eigenvalue problem associated with reaction-diffusion models for patchy linear domains with any finite number of unique patches. Interface conditions between adjacent patches may be chosen independently to accurately reflect organism behavior. We show that there exists a real principal eigenvalue with a corresponding non-negative eigenfunction that is non-zero interior to the domain. We demonstrate that our model is a generalization of several existing two-patch models. We consider simple three- and four-patch landscapes representing fragmented reserves to illustrate how our model can be used to analyze population persistence, spatial distribution, and migration dynamics. Fragmented landscapes with increased heterogeneity capture migration dynamics not found in landscapes with only two patch types, such as favorable habitat patches that experience net immigration. Conditions for the existence and non-existence of zero-flux conditions interior to three-patch systems are shown, which provide insight to the location of sources and direction(s) of migration.

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.

Design of higher gain linearly polarized 2×2 microstrip patch array antenna for wireless communication

The fifth-generation technology is popular and best as far as data rates are concerned for wireless applications. To meet the increased demand of the modern world for faithful communication, this research work is carried out. In this approach, a single patch, 1×2 array, and 2×2 array are designed using a low-cost FR4 dielectric substrate ( =4.4) covering the 3.3–3.8 GHz frequency band. Due to the lack of gain from arrays in the present research, an attempt is made to achieve excellent gain from arrays with a minimum number of patches. First, the gain of a single inset-fed antenna is compared with another normal single patch of the same thickness but with an additional air dielectric medium. Next, the second single patch is extended to obtain a rectangular 1×2 array and a 2×2 array antenna. A second single patch measuring 50×32.5×0.8 mm is designed assuming an infinite ground plane. It has 3mm air gap between the patch strip and the ground. Air acts as a second dielectric layer that reduces power loss. This allows a maximum gain of 15.2 dB with a return loss of -22 dB. Also, antenna efficiency and bandwidth are 91% and 267.69 MHz, respectively.

Landscape metrics of the Brusy Commune before and after wind-storm: an assessment of the extent of changes based on Landsat-8 data

Monitoring the change in land cover in disaster-affected areas, such as forests, has become a conventional forest management practice, particularly in protected areas. Most change detection and fragmentation studies rely on single-dated satellite images even while investigating changes over a long temporal span. This study aims to move a step further to compare fragmentation before and after a derecho event that occurred in August 2017 using 23 Landsat-8 images of Brusy Commune within the Tuchola Forest Biosphere Reserve. The supervised classification was carried out in the Google Earth Engine using the machine learning algorithm of random forests within the summer months of 2017 and 2018. The high overall accuracy of 0.92 was obtained for the two images which were then analysed with landscape metrics such as mean patch size, number of patches, total edge and edge density using Patch Analyst. These landscape metrics facilitated the characterisation of landscape fragmentation at both the class and landscape levels. Shannon’s Diversity Index was employed to assess heterogeneity across the landscape. The findings indicate significant fragmentation, particularly in the forest and pasture classes, with overall low diversity. This study underscores the potential for future research to employ advanced machine learning techniques and non-parametric classifiers, such as neural networks, to enhance the prediction of fragmentation across various spatial scales.

MMGPL: Multimodal Medical Data Analysis with Graph Prompt Learning

Prompt learning has demonstrated impressive efficacy in the fine-tuning of multimodal large models to a wide range of downstream tasks. Nonetheless, applying existing prompt learning methods for the diagnosis of neurological disorder still suffers from two issues: (i) existing methods typically treat all patches equally, despite the fact that only a small number of patches in neuroimaging are relevant to the disease, and (ii) they ignore the structural information inherent in the brain connection network which is crucial for understanding and diagnosing neurological disorders. To tackle these issues, we introduce a novel prompt learning model by learning graph prompts during the fine-tuning process of multimodal models for diagnosing neurological disorders. Specifically, we first leverage GPT-4 to obtain relevant disease concepts and compute semantic similarity between these concepts and all patches. Secondly, we reduce the weight of irrelevant patches according to the semantic similarity between each patch and disease-related concepts. Moreover, we construct a graph among tokens based on these concepts and employ a graph convolutional network layer to extract the structural information of the graph, which is used to prompt the pre-trained multimodal models for diagnosing neurological disorders. Extensive experiments demonstrate that our method achieves superior performance for neurological disorder diagnosis compared with state-of-the-art methods and validated by clinicians.

Coverless Image Steganography Using Content-Based Image Patch Retrieval

Abstract Image steganography is the process of concealing secret information within a cover image. The main challenge of steganography is to ensure that the embedding process does not significantly alter the cover file. In this paper, instead of modifying a cover image to carry information, steganography is performed using a set of images. These images are selected from a dataset of natural images. Each image in the dataset is divided into a number of non-overlapping patches. Then, indexing of the patches is performed based on their features. The secret image is also divided into a set of non-overlapping patches. Similar versions of the patches in the secret image are searched in the dataset to identify candidate patches. The final candidate is selected by calculating the minimum distance between the feature vector of the patches in the secret image and the patches in the dataset. Finally, the receiver retrieves the secret image using the pieces of selected images. Since, instead of embedding information in a cover image, a set of patches from natural images are selected without any changes, this approach can resist change-tracking tools, as demonstrated by experimental results, and also offers the advantage of high embedding capacity.

Trends in the future evolution of rural settlements in oasis-desert areas under water use simulation scenarios: Take the Hexi Corridor region of China as an example

The uncontrolled expansion of rural settlements caused by the imbalance in the matching of land and water resources has hindered the realization of the goal of sustainable rural development in the oasis-desert area. In this study, “water resources-land resources-oasis rural settlements” are integrated into the same framework of symbiosis development, and the evolution of rural settlements in the context of water and land resources constraints is predicted. We used the coupled “SD-SOS-FLUS” (“system dynamics-suitable oasis structure-future land use simulation”) model to predict the differences in rural settlement sizes and their spatial distribution under the inertial development water use scenario (ID) and sustainable development water use scenario (SD) in the northeast part of the Hexi Corridor in China. In addition, we explored differences in oasis circle structure and land use structure under different water allocation scenarios. Compared with a single model, the coupled model “SD-SOS-FLUS” can better simulate the symbiosis relationship between “water resources-land resources- oasis rural settlements”. Through the prediction, the proportion of water used for production in the ID scenario is still as high as 86.30 %, while the proportion of ecological water use is only 11.50 %, and the continuous imbalance of the water use structure results in the area of arable land and rural settlements will be increased to 7,473.21 km2 and 487.16 km2. It increased by 115.63 km2 and 41.28 km2 respectively compared to 2020, which in turn made the oasis area expanding outward, and the radius R of the oasis also increased from 53.65 km in 2020 to 54.79 km in 2030. The area of arable land and rural settlements under water and land resource constraints in the SD scenario decreased to 5223.56 km2 and 105.04 km2. The contraction of the oasis increases the transition zone circle width B2 from 19.88 km in 2020 to 24.58 km in 2030, an increase of 5 km compared to the ID scenario. As a result of the spatial reconfiguration, the number of rural settlement patches decreased from 1.04 × 104 to 0.15 × 104 in 2020, saving 3.41 × 104 ha of land after optimization.

Spatio−Temporal Changes and Key Driving Factors of Urban Green Space Configuration on Land Surface Temperature

Changes in land cover by rapid urbanization have diminished the cooling effect of urban green spaces (UGS), exacerbating the upward trend of land surface temperature (LST). A thorough and precise understanding of the spatio-temporal characteristics of UGS and LST is essential for mitigating localized high temperatures in cities. This study identified the spatio-temporal changes in UGS configuration and LST in Shanghai from 2003 to 2022. The correlation between UGS configuration and LST was explored using spatial autocorrelation analysis and causal inference. The results show that (1) the high-temperature space had grown from 721 km2 in 2003 to 3059 km2 in 2022; (2) in suburbs, the largest area of UGS tended to decrease, while the number of patches tended to increase, indicating a distinct feature of suburbanization; (3) changes in the largest area of UGS had more significant spatial correlation, indicating that urban sprawl primarily impacts large UGSs; and (4) compared to the number and shape of UGS, changes in the largest area are the key factor influencing regional LST. These findings enrich the knowledge of the spatio−temporal relationship between the UGS configuration and its cooling effect in urbanization, offering valuable insights for building cooler cities.

Landscape metrics for land use/cover change and green space pattern in Can Tho city in 1998-2020 based on remote sensing and GIS

Changes in land cover/green space in Can Tho city in the period 1998-2020 were analyzed based on remote sensing data and the perspective of landscape ecology. The data collected from JAXA on land cover/land use classification entire Can Tho city in the period 1998-2020 was used to extract landscape metrics and to analyze the changes by a conversion matrix. The result shows a complex change in the urban green space in the period 1998 - 2020 in Can Tho. Research results show that Can Tho city had rice paddies and other croplands accounting for the majority of the land use structure. In the period 1998-2020, the city experienced a major shrinkage in croplands. Although other land use/cover types fluctuated differently, the fragmentation process still prevailed with fragments having discrete connections in space. The process of urbanization occurred with the expansion of built-up, but the concentration level was not high, with small fragments appearing sporadically distributed. However, comparing the landscape indices in the period 1998 – 2020 showed the aggregation process was increasingly taking place, and the level of fragmentation had tended to decrease. This trend was evidenced by the sharp increase in the number of patches, effective mesh size, and splitting index simultaneously with the gradual decline of the LPI index. The research results show high potential in expanding green space in Can Tho as well as application in planning urban green space development.

Temporal-spatial evolution of the integrated landscape patterns in the Zhengzhou Metropolitan Area based on nighttime light data

Metropolitan integration development refers to the interconnection between cities and the coordinated development of various aspects such as economy, society, culture, and nature, which is the goal of metropolitan area development. With the Zhengzhou metropolitan area as the research area and based on nighttime light data from 2012 to 2021, we comprehensively used landscape index and landscape morphology spatial pattern analysis methods, systematically evaluated the integration process of the metropolitan area from the perspective of spatial expansion and spatial connection, analyzed the spatiotemporal variations of the landscape pattern of the metropolitan area, and revealed the spatiotemporal expansion and connection patterns of the metropolitan area. The results showed that the area of the Zhengzhou metropolitan area expanded year by year from 2012 to 2021, with the number of landscape patches continuously increasing, showing an agglomeration phenomenon. In the metropolitan area, there was a trend towards stability and multi-directional coordinated growth. The contribution of non-central cities to expansion increased annually, while the expansion patterns of various constituent cities gradually shifted from internal filling to external expansion. The connection scale within the metropolitan area had been expanding annually, with enhanced intercity connections. Intercity connection belts and channels for material and information exchange were emerging, and the integrated network of urban agglomeration connections was gradually forming. Metropolitan integration planning provided positive guidance for the development of metropolitan areas. We should fully leverage the driving effects of metropolitan areas, pay attention to the integration of Zhengzhou-Kaifeng and Zhengzhou-Xuchang, promote the formation of emerging growth poles in Xinxiang and Jiaozuo, as well as regional coordinated development, strengthen the network of policies, economy, transportation, information, etc., and form a diversified and integrated development situation.

Review of lidocaine plaster prescribing and monitoring in primary care

Abstract Introduction Lidocaine medicated plasters (LMPs) are accepted by the Scottish Medicines Consortium (SMC) for restricted use in post-herpetic neuralgia where first-line therapies are ineffective or intolerable.[1] Subsequently, LMPs are restricted for use in post-herpetic neuralgia within a large NHS board with Ralvo as formulary brand due to cost-effectiveness. Despite this, the spend on LMPs is increasing with the cost per 1000 list size above the national average.[2] Aim To review and improve LMP prescribing and monitoring in a general practice. Methods An audit within a GP practice was undertaken by conducting an EMIS search to extract all patients prescribed LMPs within the previous 6 months from December 2022. A baseline audit was completed to determine compliance against the criteria (standards set as 100%), shown in Table 1. Data were analysed using Microsoft Excel. In the interest of improving audit results, a pharmacist then conducted telephone reviews with a view to stopping LMP if appropriate, reducing prescription quantities and/or switching to Ralvo. Post review, criteria were re-audited to determine the impact. Following this, an education session was conducted. Results The results against the standards are shown in Table 1. The LMP reviews resulted in: therapy stopped (n=2; 8%), therapy reduced (n=7; 26%), therapy continued (n=11; 40%), and therapy removed from repeat (n=7; 26%). Reductions were achieved by reducing the number of patches, cutting patches or increasing the patch-free interval. Some patients continued therapy despite off-license indication due to a significant reduction in pain score and benefit in physical function. Following the audit and review of LMP, an informal general practitioner education session was conducted to promote adherence to formulary and SMC recommendations, aiming to prevent LMP initiation for off-license indications. Impact was not studied. Conclusion There is a lack of compliance with SMC and formulary recommendations with all patients in this study being prescribed LMPs for off-licensed indications. Pharmacy involvement in regular reviews could ensure patients are prescribed the most cost-effective brand and ongoing treatment appropriateness assessed, particularly for off-license indications. The study was implemented in one general practice; therefore, there is scope for extrapolation across the National Health Service board with aims to reduce LMP prescription costs and medication burden. Further work is also required to achieve a change in prescribing habits.

Research on a New Soundscape Evaluation Method Suitable for Scenic Areas

Existing studies have focused mainly on the environmental quality of scenic spots, such as sufficient oxygen content in the air and a high concentration of negative oxygen ions. The perceptions of soundscape in scenic areas are generally good, but there are few reports on the quantitative evaluation of soundscape quality in scenic areas. In this study, we analysed existing methods for evaluating the soundscape of a landscape, evaluated the soundscape comfort of scenic spots, analysed and refined the natural environmental factors affecting the soundscape, and proposed for the first time to use physical environmental indicators such as the air temperature difference, relative humidity, natural illuminance ratio and wind speed as environmental evaluation variables. A quantitative method was used to calculate the soundscape comfort index (SSI) of the landscape. The physical environmental indicators related to famous scenic spots in China, namely, Qingcheng mountain field testing and a subjective soundscape of tourist satisfaction survey, were used to calculate the corresponding soundscape comfort index values, and a quantitative analysis of soundscape comfort and differences in temperature, relative humidity, the illumination ratio, and the correlation between the equivalent sound level A was performed. The measured values of the temperature difference and light ratio were significantly correlated with the soundscape comfort index. The distribution of sound landscape comfort was given by a GIS map, and soundscape comfort was evaluated scientifically. The correlations between soundscape comfort and landscape patch number (PN), landscape patch density (PD), diversity index (Shannon), and landscape shape index (LSI) were quantitatively analysed, which confirmed that the perception of soundscape comfort was affected by landscape space to different degrees. This study has scientific significance and application value for the soundscape evaluation of scenic areas and has significance for soundscape evaluation and design strategies for urban landscapes.

Measuring canopy morphology of saltmarsh plant patches using UAV-based LiDAR data

Plant patches play a crucial role in understanding the biogeomorphology of saltmarshes. Although two-dimensional optical remote sensing has long been applied to the study of saltmarsh plant patches, studies focusing on the canopy features at a patch-scale remain limited. Therefore, a simple and efficient method is needed to capture three-dimensional patch features and their relationship to habitat. This study utilized UAV-based LiDAR to obtain three-dimensional patch features of the native species S. mariqueter and the invasive species S. alterniflora in Andong Shoal, Hangzhou Bay, and examine the relationship between patch distribution and geomorphological characteristics. A workflow was established to overcome the inability of low-cost LiDAR sensor to penetrate dense vegetation, resulting in no ground return. Results showed that S. alterniflora patches were smaller in size but taller in canopy height than S. mariqueter patches. Regarding morphological patterns of patch canopy, S. alterniflora exhibited single-arch patterns (29%) and double-arch patterns (16%), whereas S. mariqueter exhibited only single-arch patterns (83%). The presence of double-arch patches suggested the development of fairy circles, indicating that the invasive S. alterniflora exhibits greater ecological resilience compared to the native S. mariqueter. Furthermore, this study explored the ecological niches of the two species in the pioneer zone of Andong Shoal. The ecological niches for S. alterniflora were 2.00-2.25 m, whereas that for S. mariqueter were 1.85-2.00 m and 2.25-2.40 m. Distance from the tidal creeks significantly moderated the number and area of patches for both species. This study demonstrated that UAV-based LiDAR technology can provide high-quality three-dimensional information about the pioneer zone of saltmarsh, thus helping to understand biogeomorphological processes in this region.

Slow passage through the Busse balloon – predicting steps on the Eckhaus staircase

Abstract Motivated by the impact of worsening climate conditions on vegetation patches, we study dynamic instabilities in an idealised Ginzburg–Landau model. Our main results predict time instances of sudden drops in wavenumber and the resulting target states. The changes in wavenumber correspond to the annihilation of individual vegetation patches when resources are scarce and cannot support the original number of patches. Drops happen well after the primary pattern has destabilised at the Eckhaus boundary and key to distinguishing between the disappearance of 1,2 or more patches during the drop are complex spatio-temporal resonances in the linearisation at the unstable pattern. We support our results with numerical simulations and expect our results to be conceptually applicable universally near the Eckhaus boundary, in particular in more realistic models.

The Stability of Competitive Metacommunities Is Insensitive to Dispersal Connectivity in a Fluctuating Environment.

AbstractMaintaining the stability of ecological communities is critical for conservation, yet we lack a clear understanding of what attributes of metacommunity structure control stability. Some theories suggest that greater dispersal promotes metacommunity stability by stabilizing local populations, while others suggest that dispersal synchronizes fluctuations across patches and leads to global instability. These effects of dispersal on stability may be mediated by metacommunity structure: the number of patches, the pattern of connections across patches, and levels of spatiotemporal correlation in the environment. Thus, we need theory to investigate metacommunity dynamics under different spatial structures and ecological scenarios. Here, we use simulations to investigate whether stability is primarily affected by connectivity, including dispersal rate and topology of connectivity network, or by mechanisms related to the number of patches. We find that in competitive metacommunities with environmental stochasticity, network topology has little effect on stability on the metacommunity scale even while it could change spatial diversity patterns. In contrast, the number of connected patches is the dominant factor promoting stability through averaging stochastic fluctuations across more patches, rather than due to more habitat heterogeneity per se. These results broaden our understanding of how metacommunity structure changes metacommunity stability, which is relevant for designing effective conservation strategies.

Enhancing urban blue-green landscape quality assessment through hybrid genetic algorithm-back propagation (GA-BP) neural network approach: a case study in Fucheng, China

This study employs an artificial neural network optimization algorithm, enhanced with a Genetic Algorithm-Back Propagation (GA-BP) network, to assess the service quality of urban water bodies and green spaces, aiming to promote healthy urban environments. From an initial set of 95 variables, 29 key variables were selected, including 17 input variables, such as water and green space area, population size, and urbanization rate, six hidden layer neurons, such as patch number, patch density, and average patch size, and one output variable for the comprehensive value of blue-green landscape quality. The results indicate that the GA-BP network achieves an average relative error of 0.94772%, which is superior to the 1.5988% of the traditional BP network. Moreover, it boasts a prediction accuracy of 90% for the comprehensive value of landscape quality from 2015 to 2022, significantly outperforming the BP network’s approximate 70% accuracy. This method enhances the accuracy of landscape quality assessment but also aids in identifying crucial factors influencing quality. It provides scientific and objective guidance for future urban landscape structure and layout, contributing to high-quality urban development and the creation of exemplary living areas.

Spatiotemporal assessment of the nexus between urban sprawl and land surface temperature as microclimatic effect: implications for urban planning.

Rapid urbanisation has led to significant environmental and climatic changes worldwide, especially in urban heat islands where increased land surface temperature (LST) poses a major challenge to sustainable urban living. In the city of Abha in southwestern Saudi Arabia, a region experiencing rapid urban growth, the impact of such expansion on LST and the resulting microclimatic changes are still poorly understood. This study aims to explore the dynamics of urban sprawl and its direct impact on LST to provide important insights for urban planning and climate change mitigation strategies. Using the random forest (RF) algorithm optimised for land use and land cover (LULC) mapping, LULC models were derived that had an overall accuracy of 87.70%, 86.27% and 93.53% for 1990, 2000 and 2020, respectively. The mono-window algorithm facilitated the derivation of LST, while Markovian transition matrices and spatial linear regression models assessed LULC dynamics and LST trends. Notably, built-up areas grew from 69.40 km2 in 1990 to 338.74 km2 in 2020, while LST in urban areas showed a pronounced warming trend, with temperatures increasing from an average of 43.71°C in 1990 to 50.46°C in 2020. Six landscape fragmentation indices were then calculated for urban areas over three decades. The results show that the Largest Patch Index (LPI) increases from 22.78 in 1990 to 65.24 in 2020, and the number of patches (NP) escalates from 2,531 in 1990 to an impressive 10,710 in 2020. Further regression analyses highlighted the morphological changes in the cities and attributed almost 97% of the LST variability to these urban patch dynamics. In addition, water bodies showed a cooling trend with a temperature decrease from 33.76°C in 2000 to 29.69°C in 2020, suggesting an anthropogenic influence. The conclusion emphasises the urgent need for sustainable urban planning to counteract the warming trends associated with urban sprawl and promote climate resilience.