Highest Importance Value Research Articles

Investigating subtypes of lung adenocarcinoma by oxidative stress and immunotherapy related genes

Lung adenocarcinoma (LUAD) is one of the most widespread and fatal types of lung cancer. Oxidative stress, resulting from an imbalance in the production and accumulation of reactive oxygen species (ROS), is considered a promising therapeutic target for cancer treatment. Currently, immune checkpoint blockade (ICB) therapy is being explored as a potentially effective treatment for early-stage LUAD. In this research, we aim to identify distinct subtypes of LUAD patients by investigating genes associated with oxidative stress and immunotherapy. Additionally, we aim to propose subtype-specific therapeutic strategies. We conducted a thorough search of the Gene Expression Omnibus (GEO) datasets. From this search, we pinpointed datasets that contained both expression data and survival information. We selected genes associated with oxidative stress and immunotherapy using keyword searches on GeneCards. We then combined expression data of LUAD samples from both The Cancer Genome Atlas (TCGA) and 11 GEO datasets, forming a unified dataset. This dataset was subsequently divided into two subsets, Dataset_Training and Dataset_Testing, using a random bifurcation method, with each subset containing 50% of the data. We applied consensus clustering (CC) analysis to identify distinct LUAD subtypes within the Dataset_Training. Molecular variances associated with oxidative stress levels, the tumor microenvironment (TME), and immune checkpoint genes (ICGs) were then investigated among these subtypes. Employing feature selection combined with machine learning techniques, we constructed models that achieved the highest accuracy levels. We validated the identified subtypes and models from Dataset_Training using Dataset_Testing. A hub gene with the highest importance values in the machine learning model was identified. We then utilized virtual screening to discover potential compounds targeting this hub gene. In the unified dataset, we integrated 2,154 LUAD samples from TCGA-LUAD and 11 GEO datasets. We specifically selected 1,311 genes associated with immune and oxidative stress processes. The expression data of these genes were then employed for subtype identification through CC analysis. Within Dataset_Training, two distinct subtypes emerged, each marked by different levels of immune and oxidative stress pathway values. Consequently, we named these as the OX+ and IM+ subtypes. Notably, the OX+ subtype showed increased oxidative stress levels, correlating with a worse prognosis than the IM+ subtype. Conversely, the IM+ subtype demonstrated enhanced levels of immune pathways, immune cells, and ICGs compared to the OX+ subtype. We reconfirmed these findings in Dataset_Testing. Through gene selection, we identified an optimal combination of 12 genes for predicting LUAD subtypes: ACP1, AURKA, BIRC5, CYC1, GSTP1, HSPD1, HSPE1, MDH2, MRPL13, NDUFS1, SNRPD1, and SORD. Out of the four machine learning models we tested, the support vector machine (SVM) stood out, achieving the highest area under the curve (AUC) of 0.86 and an accuracy of 0.78 on Dataset_Testing. We focused on HSPE1, which was designated as the hub gene due to its paramount importance in the SVM model, and computed the docking structures for four compounds: ZINC3978005 (Dihydroergotamine), ZINC52955754 (Ergotamine), ZINC150588351 (Elbasvir), and ZINC242548690 (Digoxin). Our study identified two subtypes of LUAD patients based on oxidative stress and immunotherapy-related genes. Our findings provided subtype-specific therapeutic strategies.

A novel two-way rebalancing strategy for identifying carbonylation sites

BackgroundAs an irreversible post-translational modification, protein carbonylation is closely related to many diseases and aging. Protein carbonylation prediction for related patients is significant, which can help clinicians make appropriate therapeutic schemes. Because carbonylation sites can be used to indicate change or loss of protein function, integrating these protein carbonylation site data has been a promising method in prediction. Based on these protein carbonylation site data, some protein carbonylation prediction methods have been proposed. However, most data is highly class imbalanced, and the number of un-carbonylation sites greatly exceeds that of carbonylation sites. Unfortunately, existing methods have not addressed this issue adequately.ResultsIn this work, we propose a novel two-way rebalancing strategy based on the attention technique and generative adversarial network (Carsite_AGan) for identifying protein carbonylation sites. Specifically, Carsite_AGan proposes a novel undersampling method based on attention technology that allows sites with high importance value to be selected from un-carbonylation sites. The attention technique can obtain the value of each sample’s importance. In the meanwhile, Carsite_AGan designs a generative adversarial network-based oversampling method to generate high-feasibility carbonylation sites. The generative adversarial network can generate high-feasibility samples through its generator and discriminator. Finally, we use a classifier like a nonlinear support vector machine to identify protein carbonylation sites.ConclusionsExperimental results demonstrate that our approach significantly outperforms other resampling methods. Using our approach to resampling carbonylation data can significantly improve the effect of identifying protein carbonylation sites.

Species Composition and Carbon Stock of Rehabilitated Mangrove Forest in Kupang District, East Nusa Tenggara, Indonesia

Since 1994, the community around the mangrove forest in Kupang district, East Nusa Tenggara Province, Indonesia, has rehabilitated the mangrove forest. Unfortunately, almost three decades of the success story of mangrove rehabilitation has not followed appropriate documentation on biodiversity and potential carbon stock. This research aimed to describe the species composition and estimate the carbon stock of rehabilitated mangrove forests. Forty-five sampling plots were distributed using purposive sampling based on mangrove zonation (distal, middle, proximal) and year of rehabilitation (2004, 2006, 2008). The findings revealed that there are ten mangrove species. Two species, namely Avicennia marina and Sonneratia alba, showed a high importance value index. The average aboveground carbon stock was 454.712 t/ha, distributed in seedlings, saplings, poles, and trees at 0.04%, 2.41%, 51.61%, and 45.94%, respectively. Mangrove rehabilitation in Kupang district, East Nusa Tenggara Province, has successfully increased the richness, heterogeneity, and carbon stock.

Current Status and Potential Invasiveness Evaluation of an Exotic Mangrove Species, Laguncularia racemosa (L.) C.F. Gaertn, on Hainan Island, China

Laguncularia racemosa is widely planted in coastal mudflats as a pioneer species of mangrove afforestation in China; however, whether it exhibits invasiveness as an exotic species has been a topic of debate. In this study, we investigated the distribution, community structure, and population characteristics of L. racemosa on Hainan Island, China, to discuss its potential invasiveness. The results showed that Hainan Island has become an important distribution area for L. racemosa in China, covering a total area of 64.90 ha. In this investigation, a total of 11 true mangrove species, belonging to six families and 11 genera, were discovered in the L. racemosa community throughout Hainan Island. Furthermore, L. racemosa exhibited a strong adaptive range to seawater salinity and demonstrated a high capacity for natural dispersion. L. racemosa exhibited high importance values in the tree, shrub, and seedling layers of this artificial community, indicating its dominance and potential exclusion of other mangrove species. Over time, the importance values of L. racemosa in the tree and shrub layers initially decreased and then increased, while the opposite trend was observed in the seedling layer. Overall, the diversity indexes, including the Simpson index, Shannon–Wiener index, and Pielou community evenness index, were low in the planted L. racemosa forest on Hainan Island, suggesting a relatively simple species composition within the L. racemosa community. Additionally, based on the height levels of the L. racemosa population, we found that it mainly belonged to the first level, characterized by a large number of seedlings on Hainan Island. The number of L. racemosa seedlings gradually decreased in subsequent levels, and higher height levels of L. racemosa appeared with longer planting times, indicating a growing trend of potential invasiveness of L. racemosa on Hainan Island over an extended period. We suggest that the government should be able to list L. racemosa as an invasive species that can be harvested in the future. Based on this, this study provides fundamental data and theoretical references for the sustainable prevention, control, and management of the exotic species L. racemosa on Hainan Island, and also in other mangrove wetlands in China.

Focusing on features with higher importance degree: A significance-wise mechanism for image restoration

With the aim of retrieving high-quality images from corrupted versions, image restoration meets the extensive demand of application scenarios. State-of-the-art methods solve this problem by means of designing convolution blocks in multistage architectures. However, the existing methods blindly extract and fuse features without considering which parts of the features are more effective for image restoration. In this paper, we propose a significance-wise mechanism with the goal of identifying the importance degree of each region in the feature representation and providing crucial feature information. Through the calculation of nonlinear function in the significance-wise mechanism, the region which is more conducive to image restoration will get higher importance values. Two important types of information are generated within the attention mechanism, including: (i) feature-sufficient maps with abundant feature representations, and (ii) significance-wise maps with the importance degree of patch information in the corrupted images. With the coordination of feature-sufficient maps and significance-wise maps, the network architecture can focus higher attention on crucial parts of feature information. Furthermore, we design a multistage feature fusion block with the significance-wise mechanism. Compared with existing attention mechanisms, our significance-wise mechanism has the ability to identify and generate crucial feature representation for multiple image restoration tasks. Due to the novel design of the network, we successfully implement multiple restoration tasks only by fine-tuning the number of channels once on a network. Abundant quantitative and qualitative experiments demonstrate that the effective image restoration network (EIRN) outperforms existing state-of-the-art algorithms on eleven datasets across a series of image restoration tasks, including image deblurring, denoising, super-resolution, and deraining. The source code and pretrained models will be available at https://github.com/XinyueZhangqdu/EIRN.

Spatio-Temporal Dynamic Characteristics and Landscape Connectivity of Heat Islands in Xiamen in the Face of Rapid Urbanization

With the acceleration of urbanization, urban heat waves have become a major problem affecting the lives of citizens. In this context, the accurate identification of the key patches and nodes of urban heat islands is important for improving the urban environment. This study examined the Landsat image data from Xiamen city in 2001, 2011, and 2021 to analyze the construction of the urban heat island (UHI) network. A morphological spatial pattern analysis (MSPA) and landscape connectivity model were utilized to identify the central thermal landscape patches and key nodes of UHI and their spatial and temporal evolution characteristics in the urban development process. The ultimate goal of this research is to provide valuable insights that can contribute to the enhancement of the urban environment. The results showed that (1) there was a significant increase in the heat island area (HIA) of Xiamen from 2001 to 2021, and the heat island patches show a concentrated trend. The temperature contrast between the urban area and the surrounding countryside was more distinct, indicating the urban construction land has a tendency to gather and spread. (2) The core area of the heat island accounted for the largest proportion of the thermal landscape area during the study period, and its proportion increased significantly. And the rate of increase was first rapid and then slow. The areas of the edge, branch, islet, bridge, loop, and perforation classes all showed different degrees of a decreasing trend. This indicates an increasing degree of aggregation between heat island patches. (3) The top 20 thermal landscape patches with high landscape connectivity importance values were identified. Among them, the importance value and area of the first four patches are relatively large, and belong to the three importance classes of extremely important, important, and generally important heat island core patches, which deserve focused attention and optimization. (4) Cooling measures can be prioritized for core areas of heat islands with high importance values. Connections between hot and cold islands can be interrupted or connected to mitigate the heat island effect throughout the region. The results of this study have important practical guidance for urban planning and sustainable development.

Inventory of road arborization on the urban section of BR-153 Gurupi-TO

Roadside tree planting involves integrating the road into the landscape. Therefore, the objective of this study was to assess the tree vegetation in the urbanized, duplicated section of BR-153 highway in Gurupi, Tocantins. Permanent plots were systematically established along the central and lateral medians, each measuring 10x10m (100m²) in size, totaling 146 plots in the central median (CM), 54 in the right lateral median (RLM), and 49 in the left lateral median (LLM). Within these plots, all tree individuals with a minimum height of 4.0m from the ground and a diameter at breast height (DBH) ≥ 5cm were sampled.In the inventory, a total of 260 individuals were counted in the central median, distributed across 24 species and 7 families, with a Shannon diversity index (H') of 1.98 and Pielou's evenness index (J') of 0.62. In the right lateral median, 92 individuals were recorded, representing 13 species and 5 families, with (H') of 2.13 and (J') of 0.83. In the left lateral median, 68 individuals were registered, comprising 15 species and 6 families, with (H') of 2.06 and (J') of 0.76, which is consistent with studies conducted in the region. The average height of the vegetation was 6.6m, and the mean diameter along the stretch was 29.99 cm. The species with the highest importance values were Tabebuia roseo alba (Ridl.) Sandwith, Delonix regia (Bojer ex Hook.) Raf., and Syagrus harleyi Glassman. The families with the highest importance values were Bignoniaceae, Anacardiaceae, Fabaceae, and Arecaceae. Of the species found, 57.14% are recommended tree species for highway tree planting. However, it is worth noting that the high number of individuals of the exotic species Delonix regia (flamboyant) may be considered a negative aspect, as it may compromise the diversity of the Brazilian flora by outcompeting native species.

CARACTERIZACIÓN DE SISTEMAS AGROFORESTALES CON CACAO (Theobroma cacao L) EN TRES MUNICIPIOS DEL DEPARTAMENTO DE BOYACÁ, COLOMBIA

<p><strong>Background:</strong> In Colombia, most traditional cocoa crops are developed under agroforestry systems (SAF), associating shrubs and trees that provide shade for cocoa. They generate additional economic income and various ecosystem services. <strong>Objective:</strong> To characterize agroforestry systems with cocoa in three municipalities in eastern Boyacá (Miraflores, Berbeo, and Páez) belonging to the province of Lengupá. <strong>Methodology:</strong> A semi-structured interview was applied in 15 selected farms to learn about socioeconomic aspects, agronomic management of cocoa, and the use and management of trees. The botanical and structural composition and the Simpson (S), Shannon-Weaver (H´), and Jaccard (J) plant diversity indices were determined. <strong>Results:</strong> Cocoa producers in that region develop smallholder production under agroforestry systems with irregular tree species distribution, which are used for wood, firewood, shade, and food. At the regional level, 189 forest individuals accompanying cocoa were found, grouped into 18 families, 17 genera, and 28 species. The municipality of Berbeo presented the highest abundance (73 individuals), followed by Miraflores (67) and finally, Páez (49). In Berbeo, the species with a high importance value index (IVI) were <em>Ceiba pentandra</em> and <em>Cedrela odorata</em> (35 and 33, respectively), in Miraflores <em>Trichant<strong>h</strong>era gigantea </em>and <em>Persea americana</em> (44 and 42) and, in Páez <em>Cedrela odorata</em> (104). <strong>Implications:</strong> The selective felling of forests in SAF with cocoa, which intensifies the production of wood, has favored the loss of diversity; Therefore, the floristic composition studies serve as a basis to identify other potential forest species for the establishment of SAF to promote the diversification of the productive system and contribute to its resilience and sustainability. <strong>Conclusion:</strong> The agroforestry systems with cocoa in three municipalities in eastern Boyacá presented a differential composition and diversity, marked by a lower diversity in the municipality of Páez, where the species <em>C. odorata</em> had greater representation, related to the affinity of farmers for timber species of commercial interest.</p>

Niche and Interspecific Association of Dominant Tree Species in Spruce–Fir Mixed Forests in Northeast China

This study focuses on the natural coniferous and broad-leaved mixed forest dominated by Picea asperata and Abies fabri in the Jingouling Forest Farm of Northeast China. Specifically, we place emphasis on examining the effects of different thinning intensities. By comparing the niche characteristics and interspecific associations of dominant tree species under various thinning intensity conditions, our aim is to gain deeper insights into the patterns of resource utilization by species and the interplay of tree species in the forest canopy. Based on plot survey data, analysis methods such as niche breadth, niche overlap index, Pearson correlation coefficient, and Spearman’s rank correlation coefficient were used to analyze the niche and interspecific relationship characteristics of the dominant tree species in the community. The results indicate that among the four selective cutting intensities, the tree species with the highest importance value in all cases is Abies fabri, with an average importance value of 30.29%. Additionally, Picea asperata exhibits the widest niche breadth among the tree species, with a value of 4.59. The selective thinning in this study resulted in a reduction of average species niche overlap in the community compared to the control plots. There were both positive and negative interspecies associations observed, but they were statistically insignificant. Few pairs showed significant correlations, with the positive-to-negative ratio of Pearson coefficients decreasing as the selective cutting intensity increased. The Spearman rank correlation analysis revealed a positive-to-negative ratio exceeding one for species pairs in the community under both light and heavy-cutting conditions, with no significant negative correlations observed. In summary, selective cutting disturbance can effectively increase the importance value of the dominant tree species, Abies fabri, in the community. However, it leads to a reduction in the niche breadth of all tree species present in the forest. Moderate selective cutting is considered a more suitable intensity, as it promotes the maintenance of biodiversity and yields higher forest management benefits in the mixed forest of Picea asperata and Abies fabri in Northeast China.

Stress mitigation by riparian flora in industrial contaminated area of River Chenab Punjab, Pakistan.

Faisalabad is a major industrial area in Pakistan's Punjab province that discharges wastewater into the Chenab River. Industrial effluents in Faisalabad are predicted to pose a significant threat to the riparian vegetation of the Chenab River and nearby vegetation. Heavy metal pollution of plants, water, and soils is one of the biggest problems worldwide that needs to be addressed because heavy metals above normal levels are extremely dangerous to both riparian vegetation and wildlife. The results indicated high levels of pollution in the industrial effluents as well as in the river in terms of salinity, metal toxicity, TSS, TDS, SAR, the acidic and alkaline nature of the industrial effluents, and the spread of industrial effluents up to 15 square kilometres in the Chenab River. Despite the higher pollution, four plants were found at all sites: Calotropis procera, Phyla nodiflora, Eclipta alba and Ranunculus sceleratus. It was found that most of the selected plants were phytoaccumulators, making them best suited to survive in harsh environments such as those with industrial pollution. The Fe concentration in the plant constituents was the highest, along with Zn, Pb, Cd, and Cu, all of which were above the permissible limits of the WHO. The metal transfer factor (MTF) was higher in most of the plants studied, and even exceeded 10 at some severely affected sites. Calotropis procera proved to be the most suitable plant for growth on drainage systems and also at river sites, as it had the highest importance value across all sites and seasons.

Study of the Mullusca Community in the Reclamation Beach of Manado Beach

Purpose: This study aims to inventory the types of molluscs and community structure and to know their activities on the reclamation beach of Manado Bay. The types of molluscs encountered in the first phase of the study totaled 15 species from 7 families while in the second phase there were 21 species from 10 families. Method: Based on the methods observations were made using the observation method or direct observation of mollusc species that were affected by environmental factors. The research was conducted from July to August on the reclamation beach of Manado Bay, North Sulawesi. Method of this study is based on the Preliminary Research, Mollusca Sampling, Data analysis. Results and conclusion: Based on the results of data analysis in phase I research in the intertidal zone showed that the mollusk density value was 58.30 Ind/m2. The damage index obtained from the analysis results is low, namely H' = 1.684. The dominance value obtained from the results of data analysis is low, namely C = 0.27-0.44. The highest species frequency value was found in the Cellana radiata species with a value of 0.60 and the lowest in the species Menathais tuberosa, Drupa rubusidae, Drupa ricinus, Nerita polita, with a value of 0.03. The domination value obtained from the results of data analysis is C = 0.06, which means that the value is classified as low. The activity of molluscs in terms of their ability to respond and adapt to the molluscs in the intertidal zone varies according to the species observed based on the size of the species and their preferred adaptability. Research implications: The relatively high importance value index was found in the species Saccostrea cucullata with a value of 106.28% while the lowest value was in the species Menathais tuberosa and Drupa ricinus with a value of 1.24%. In phase II research in the subtidal zone showed that the mollusk density value was 1.86 Ind/m2. The damage index obtained from the analysis results is classified as moderate, namely H' = 2.950. Originality/value: Molluscs are one of the many potential biological resources found in an ecosystem, and have an important role for the balance of the ecosystem.

Residents’ perceptions of tourism development: A case study of the Issyk-Kul Lake region, Kyrgyzstan

The main aim of this study is to examine residents" perceptions of tourism development and its impact in the Issyk-Kul Lake region, as this is the most visited region of Kyrgyzstan. Accordingly, importance-performance analysis (IPA) was used to evaluate socio-economic, socio-cultural, and environmental attributes to better understand locals" perspectives on tourism development. Among the 38 items measuring the tourism development impact in the region, there are no items identified for the "Possible overkill" quadrant. Fifteen items fall in the "Keep up the good work" quadrant, which shows high performance and importance values. Another fifteen items fall in the "Concentrate here" quadrant, meaning that local residents perceive the attributes as important, but the perception of performance levels is below average. The gap analysis further supports the general finding from this study that there is no discernible difference between performance and importance attributes. The study showed that overall respondents gave importance a higher rating than performance. In general, when importance values exceed performance values, tourism development can be deemed positive. Unlike previous studies, this study addresses an understanding of the socio-economic, socio-cultural, and environmental impacts of tourism in the region from the local residents" perspective.

Deep Learning Model Based on Contrast-Enhanced Computed Tomography Imaging to Predict Postoperative Early Recurrence after the Curative Resection of a Solitary Hepatocellular Carcinoma

We aimed to develop the deep learning (DL) predictive model for postoperative early recurrence (within 2 years) of hepatocellular carcinoma (HCC) based on contrast-enhanced computed tomography (CECT) imaging. This study included 543 patients who underwent initial hepatectomy for HCC and were randomly classified into training, validation, and test datasets at a ratio of 8:1:1. Several clinical variables and arterial CECT images were used to create predictive models for early recurrence. Artificial intelligence models were implemented using convolutional neural networks and multilayer perceptron as a classifier. Furthermore, the Youden index was used to discriminate between high- and low-risk groups. The importance values of each explanatory variable for early recurrence were calculated using permutation importance. The DL predictive model for postoperative early recurrence was developed with the area under the curve values of 0.71 (test datasets) and 0.73 (validation datasets). Postoperative early recurrence incidences in the high- and low-risk groups were 73% and 30%, respectively (p = 0.0057). Permutation importance demonstrated that among the explanatory variables, the variable with the highest importance value was CECT imaging analysis. We developed a DL model to predict postoperative early HCC recurrence. DL-based analysis is effective for determining the treatment strategies in patients with HCC.

Influential Community Search over Large Heterogeneous Information Networks

Recently, the topic of influential community search has gained much attention. Given a graph, it aims to find communities of vertices with high importance values from it. Existing works mainly focus on conventional homogeneous networks, where vertices are of the same type. Thus, they cannot be applied to heterogeneous information networks (HINs) like bibliographic networks and knowledge graphs, where vertices are of multiple types and their importance values are of heterogeneity (i.e., for vertices of different types, their importance meanings are also different). In this paper, we study the problem of influential community search over large HINs. We introduce a novel community model, called heterogeneous influential community (HIC), or a set of closely connected vertices that are of the same type and high importance values, using the meta-path-based core model. An HIC not only captures the importance of vertices in a community, but also considers the influence on meta-paths connecting them. To search the HICs, we mainly consider meta-paths with two and three vertex types. Then, we develop basic algorithms by iteratively peeling vertices with low importance values, and further propose advanced algorithms by identifying the key vertices and designing pruning strategies that allow us to quickly eliminate vertices with low importance values. Extensive experiments on four real large HINs show that our solutions are effective for searching HICs, and the advanced algorithms significantly outperform baselines.

ANALYSIS OF THE HORIZONTAL STRUCTURE OF THE YOUNG REGENERANT BANK IN A DEGRADED RIVERSIDE ECOSYSTEM IN THE SEMIARID OF PARAIBA

The objective was to evaluate the structure of the young regenerating stratum in a degraded riverside area of caatinga in the Serra Branca-PB, the semiarid region of Paraíba. Two inventories were performed, one in the dry season (September/2019) and the other in the rainy season (March/2020). In the riparian area, 50 contiguous plots of 10 X 20 m were allocated. In the center of each plot, subplots of 1 X 1 m were plotted, totaling 50 m2, for the evaluation of the regenerating stratum. The density, frequency, dominance, and importance value parameters were calculated. The heterogeneity of the floristic community was determined by the Shannon diversity index (H') and Pielou's evenness index (J'). In both inventories, 39 species distributed in 31 genera and 14 families were recorded. In the dry period, the species with the highest importance value were respectively Alternanthera tenella Colla, Sida galheirensis Ulbr. and Fabaceae 1. Related to the rainy season, the species with the highest importance value were Urochloa decumbens (Stapf), R.D.Webster, Blainvillea acmella (L.), Philipson, and Boerhavia diffusa L. The diversity and evenness values were 1.22 nats.ind.-1 and 0.49 (dry season) and 2.59 nats.ind.-1 and 0.71 (rainy season), respectively. The results obtained in the two inventories were similar to other studies in these same conditions of degraded caatinga. The study also demonstrated that this area is in an initial stage of ecological succession, with a predominance of exotic species in both inventories (dry and rainy).

The relationship between canopy microclimate, fruit and seed yield, and quality in Xanthoceras sorbifolium

Xanthoceras sorbifolium has high oil content and important biomass energy value, but its development is limited by the problem of low yield. This study investigated the relationship between the canopy microclimate, fruit yield, and fruit quality of Xanthoceras sorbifolium. Difference between the distributions of canopy microclimate factors as well as fruit and seed parameters in the inner and outer canopies of the lower layer, as well as between the inner and outer canopies of the upper layer, were investigated for a period of one year. Canopy structure induced significant differences between canopy microclimate factors during various periods of the year. Light intensity and temperature of the outer and upper canopies were higher than those of inner and lower canopies. However, relative humidity showed an opposing trend. Light intensity was significantly and positively correlated with fruit set percentage, fruit yield, and seed yield. Temperature was significantly and positively correlated with fruit yield and seed yield, but significantly negatively correlated with the oil concentration of seed kernels. Fruit and seed yields significantly decreased from the outer to the inner canopy and from the upper to the lower canopy. Fruit set percentage in the outer canopy was also significantly higher than that in the inner canopy. However, oil concentrations in the seed kernels of the lower layer were significantly higher than those of the upper layer. Additionally, regression analysis was used to construct evaluation models for microclimate, fruit, and seed parameters. Regression equations corresponding to the association between single microclimatic factors during different periods and the fruit and seed parameters may provide a reference for canopy pruning and help develop an optimal regression model that may be used to predict and estimate fruit and seed parameters.

Species niche and interspecific associations alter flora structure along a fertilization gradient in an alpine meadow of Tianshan Mountain, Xinjiang

The niche breadth, niche overlap, and interspecific associations of species in Bayinbuluke alpine meadow were investigated using ecology statistics to explore the competitive connection between the species and restricted resources in the community and the stable coexistence relationships among populations under different nitrogen addition gradients in the short term. The findings demonstrate the following. (1) The importance value of species shifted, with the fertilization samples Festuca ovina and Poa annua becoming the species with the highest importance value. Species richness fell gradually as fertilization gradient progressed, while the number of species grew initially and subsequently decreased. (2) Under different fertilization methods, the niche width and niche overlap values of the principal species changed. A positive link was found between niche width values and critical values under fertilization treatment compared with the controls. (3) By using the variance ratio approach, Pearson’s correlation, and the association coefficient test, a positive correlation was discovered among species under low fertilization gradient treatment. However, a negative correlation was found under other gradients.

Potential of important vegetation in Vatulemo Green Open Space

Green Open Space is a space that is fully arranged with various plants. The expansion of green open space in Palu City is designed to meet the minimum minimum area of greeneries at 30% of the city area. Landscape areas with different types of vegetation have different abilities to provide thermal comfort. This research aims to analyze the vegetation structure and the ability of vegetation to reduce air temperature in Vatulemo's green open space. This research method are analysis of the vegetation structure in Vatulemo City Park's green open space based on the types of vegetation components that comprise the green open space and exploratory analysis of the ability of vegetation with the highest importance value (IVI) to reduce air temperatures that provide thermal comfort for various living things. The results showed a codominance between the vegetation was found, for instance, Cuphea sp, Samanea saman, Cynodon dactylon, Terminalia mantaly and Tabernaemontana divaricata. The average temperature under and outside the canopy of the vegetation was quite different. The temperature under the canopy is lower than outside the canopy. The difference in surface temperature under and outside the canopy is influenced by the primary factor of shading arising from the thickness of each vegetation's canopy. As a result, according to SNI 03-6572-2001, temperature under canopy vegetation with the highest importance are classified as comfortable warm standard temperature. In Vatulemo Park, planting canopy trees remains extremely scarce. Each vegetation has a different ability to create thermal comfort.

Distância da margem como fator modulante da assembleia de macrófitas em um reservatório tropical

Abstract: Aim Evaluate the structure of the aquatic macrophytes assembly of the Jacarecica II Dam, Areia Branca, Sergipe, and verify if distance from the margin is a driver for species richness, and composition in this environment. Methods We settled transects where we plotted quadrats and subplots. The transects were perpendicular in relation to the reservoir margin, and the first quadrat was placed on the margin with the four following ones completely over the water surface. We estimated cover area for each macrophyte species in each quadrat. Each species was also classified according to its life form. We calculated community indexes and tested the influence of the distance from the margin on the structure of macrophyte assemblies. Results We sampled 10 emergent and four free-floating species, resulting in a richness of 14 species. The species with higher importance value were weedy and ruderal species (Salvinia auriculata and Eichhornia crassipes). The distance to the margin caused changes in macrophyte assembly and presented negative relation with species richness. Conclusions The studied assembly presents few species, with some presenting great dominance. This dominance reflects the anthropization of these habitats. Besides, the species composition and richness are modified in the sense that emergent and free-floating species co-occur in marginal quadrats, but only free-floating species occur in quadrats that are in areas that are more distant from the reservoir margin.

SHORT COMMUNICATION: Survey of Grasses (Poaceae and Cyperaceae) Within Caraga State University- Main Campus, Philippines

Campus landscapes provide aesthetic appreciation and promote recreational activities, and ecological protection. Grasses are vital in providing major campus greenery, but their distribution, functional significance, and inventory are scarcely reported. This study focused on identifying grass species from the family Poaceae and Cyperaceae by determining their importance value, percentage cover, and economic uses within five sampling stations inside Caraga State University (CSU)-Main campus. Seventeen species of Poaceae and three species of Cyperaceae were documented inside the campus. Across the stations, Station 3 (Oval grounds) accounted for most of the grass species. The species belonging to the Family Poaceae have the highest percentage cover. The Cyperus brevifolius (Cyperaceae) showed a high relative frequency and importance value. However, this species is the most dominant across the sampling stations. The findings of this study are an excellent basis to assess further by looking at the various diversity indices to understand better ecological behavior and the importance of these species of grasses. The findings have implications for the ongoing infrastructure development of CSU by specializing in the design to expand landscapes, converting concrete areas into grass landscapes, and maintenance and conservation to allow various species to grow and establish.