Highest Importance Value Research Articles

Modeling farmer behavior in adopting agroecological practices using AI tools in shea butter agroforestry systems

This study examines the performance of machine learning algorithms for identifying importance features for agroecological practices adoption in shea agroforestry systems. Primary data were collected from 272 representative and randomly selected farmers in two regions of northern Benin. Four machine learning algorithms (Naïve Bayes, Neural Network, Support Vector Machine and Bagging Decision Trees) were compared using four statistical performance metrics: accuracy, balanced accuracy, recall, and the area under the receiver operating characteristic curve (AUC), as well as calibration plots. The results indicated that the Naïve Bayes model performed best for predicting animal parking practices, and biopesticide while the Support Vector Machine outperformed other models in predicting cultural associations, improved seeds, and organic fertilizers adoption. Feature importance analysis revealed that the most significant feature influencing the adoption of animal parking and organic fertilizers practices was the farmers' region of origin, with the highest importance value (100%). When considering features with at least 50% importance, main occupation and means of transport for manure were also relevant for the adoption of animal parking practice. The farmers' ethnic group, village, and age class were the most influential characteristics for biopesticides, cultural association, and improved seeds practices, respectively, each with a 100% importance value. For improved seeds practice, farm assets and secondary occupation were also relevant when considering features with at least 50% importance. Therefore, providing comprehensive training on agroecological practices such as animal parking, crop diversification, biopesticide management, organic fertilization, and improved seeds use to farmers in Northern Benin, particularly those managing shea agrosystems, could contribute to the sustainable development of this vital resource and enhance food security.

Response of Species Diversity and Stability of Typical Steppe Plant Communities on the Mongolian Plateau to Different Grazing Patterns

ABSTRACTGrasslands represent a major biome on Earth and play a vital role in ecosystem functioning and dynamics. However, owing to the variations among grassland types, the impact of grazing on plant community diversity and stability remains unclear. This study is based on the typical steppe of the Mongolian Plateau. Field sampling and data analysis were combined to qualitatively and quantitatively investigate the structural characteristics, species diversity, and stability of plant communities under varying grazing intensities, that is, four‐season nomadic, two‐season rotational, and sedentary grazing (FSNG, TSRG, and SG, respectively). The results indicated that FSNG pastures exhibited the largest number of plant species while FSNG and TSRG pastures exhibited relatively high importance values for the primary dominant species. Carex duriuscula, Chenopodium glaucum, and Cleistogenes squarrosa were prominent in SG pastures, with C. duriuscula having the largest importance value. The mean height, cover, and aboveground biomass of plant communities in FSNG were significantly higher than those in SG (p < 0.05), with no significant difference observed between FSNG and TSRG. FSNG also demonstrated the highest Shannon–Wiener, Simpson, and Pielou indexes. The Shannon–Wiener and Simpson indexes between the FSNG, TSRG, and SG pastures showed significant differences (p < 0.05). Nomadic plant communities displayed positive loosely interspecific traits, suggesting independence and positive succession. Conversely, communities in TSRG and SG exhibited negative correlations and higher instability. The stability analysis ranked community stability as FSNG > TSRG > SG, suggesting that judicious grazing practices could enhance grassland stability. The findings reveal that grazing patterns influence plant community composition and function and that FSNG pastures promote higher species diversity, perennial dominance, and overall stability compared with TSRG and SG pastures.

Forest Management and Tree Species Diversity in a Temperate Forest of the Meseta Purhépecha, Michoacán

Objective: To evaluate how traditional forest management practices impact the diversity and structure of temperate forests in the Nuevo San Juan Parangaricutiro Indigenous Community (ICNSJP), with the goal of providing information on the sustainable management of these forests. Design/methodology/approach: Forest inventory data were collected and analyzed in stands treated with four thinning (A4) through the Silvicultural Development Method (SDM) and contrasted with stands that have not been intervened for more than 30 years (A0). Diversity indices and stand variables were used to statistically compare the effects of the treatments. Results: In total 20 species were recorded, 13 in A0 and 18 in A4. The true diversity (q1) recorded a value of 3.3±1.6 in A4 and 1.9±0.8 in A0, although this difference was not statistically significant. The species with highest importance value were Pinus douglasiana Martinez (30%) for A0 and P. pseudostrobus Lindl (27%) for A4. Limitations on study/implications: According to the SDM, the cutting cycle in A4 has not yet ended since the release and regeneration treatments are missing, therefore, monitoring is recommended to evaluate the effect of the SDM more comprehensively on diversity and structure in the forests of the ICNSJP. Findings/conclusions: Forest management in the ICNSJP has shown a positive effect in terms of species diversity and due to its commercial value, the development of P. pseudostrobus has been favored. In general, forest management has contributed to socioeconomic development by promoting species diversity, a key element for sustainable development.

Urban conservation and tree diversity: a case study in Parque Xokleng, Nova Veneza, Southern Santa Catarina

Urban forests can be defined as sets comprising vegetation fragments and isolated or grouped trees inserted in urban or peri-urban areas. Within this mosaic, urban fragments are important for biodiversity conservation. The aim of this study is to contribute to the knowledge about the structure of vegetation in an urban forest in the town of Nova Veneza, Santa Catarina, Brazil. The study was conducted in the Parque Natural Municipal Xokleng (PNMX). A phytosociological survey was conducted in the forest, using the plot method, in which 30 continuous plots of 10 m x 10 m were established. We considered a tree every individual that had a diameter at breast height greater than or equal to 5 cm. In this study, 497 individuals belonging to 75 species and 32 families were sampled, along with 14 dead individuals, three individuals identified only at genus level, and one unidentified individual. The species with the highest importance values were Tetrorchidium rubrivenium, Machaerium stipitatum, Ficus adhatodifolia, Cabralea canjerana, Mollinedia triflora. The vegetation structure is similar to the structure observed in other secondary forest fragments in the southern region of Santa Catarina. The presence of secondary species in the canopy and with high dominance values reflects the regeneration process the forest is undergoing.

PHYTOSOCIOLOGICAL CHARACTERIZATION OF AN URBAN FRAGMENT OF INTERIOR ATLANTIC FOREST - PARANÁ, BRAZIL

The Parque Natural Municipal Paulo Gorski, located in western Paraná, comprises an urban remnant of Mixed Ombrophilous Forest. This study aimed to identify tree species and conduct the phytosociological characterization of this fragment of the Atlantic Forest. Monthly visits were made in ten plots (20 x 5 m) to collect fertile samples. A rarefaction curve was generated, and phytosociological parameters, diversity, and the distribution of individuals in diameter classes were calculated. A total of 158 tree individuals were sampled, distributed across 23 families and 47 species (including six exotic ones). Among the species found, 74.4% exhibited zoochoric dispersion syndrome, 19.1% anemochoric, and 6.5% autocoric. Concerning successional category, 63.8% were early successional species. Alchornea triplinervia (Spreng.) Müll.Arg. and Prunus myrtifolia (L.) Urb. had the highest importance values due to their high number of individuals, greater frequency, and basal area. Araucaria angustifolia (Bertol.) Kuntz, an endangered species, also had a high importance value. The Shannon diversity index was 3.43, and evenness was 0.89. Approximately 70% of the individuals were distributed in smaller diameter classes (< 15 cm), forming an inverted J-shape, an expected pattern indicating a regenerative capacity and structure of preserved forest remnants, despite being in an urban area and facing significant human pressures. This urban forest fragment should be preserved, as it contains native and endangered tree species from the region, serving as an ecological corridor, and maintains important ecological and social functions for the region.

Plants associated with water towers in the Saharan environment: Floristic diversity and therapeutic virtues

Water in arid regions plays a vital role in the existence and development of living beings. The main aim of this work is to study the diversity and therapeutic properties of plant species that grow in the vicinity of water towers (constructions used to store and distribute drinking water) in the Saharan environment (south-western Algeria). Twenty-two floristic surveys were carried out in five representative sites to study the floristic diversity. The biological and phytogeographical spectra were established, and the therapeutic properties were determined for each plant species inventoried. The results show that the floristic richness is of the order of 41 species belonging to 39 genera and 16 botanical families, the most represented of which are the Asteraceae (19.51%) and Poaceae (17.07%). The biological spectrum showed the existence of 20 species of therophytes, and the phytogeographic spectrum indicated that most of the inventoried plant species belonged to the Saharo-Arabian biogeographic element (31.7%). The leaves (51.22%) are the most used for therapeutic aspects, while decoction is the most commonly used preparation method (60.98%). The plants with the highest importance values are Calotropis procera (27.78%), Phoenix dactylifera (16.67%), Cynodon dactylon and Tamarix gallica (15.56% each). This study shows that the various plant species inventoried offer important therapeutic properties for treating various pathologies.

Customer Preferences for Using the Gojek Application: A Conjoint Analysis Study

This research aimed to understand and determine customers’ preferences for the first ride-hailing application named Gojek. Product attributes were used as independent variables, and categorized into three indicators: product quality, product features, and product design attributes. Preferences were determined by measuring utilities and importance values using the conjoint analysis method. The population of this research comprised Gojek application users in Batam, with 160 respondents determined by using a rule of thumb specified for conjoint analysis. Data were collected through an online questionnaire and processed using SPSS 22. The research results indicated that among the three indicators of product attributes, product features dominated the respondents' preferences, as evidenced by having the highest importance value, with the GoPay payment feature level being the most preferred. In second place was product quality, with data security and privacy as the preferred attributes at that level. Product design was consequently ranked last with the lowest importance value, and ease of use was the most preferred attribute.

Parcel-Based Sugarcane Mapping Using Smoothed Sentinel-1 Time Series Data

The timely and accurate mapping of sugarcane cultivation is significant to ensure the sustainability of the sugarcane industry, including sugarcane production, rural society, sugar futures, and crop insurance. Synthetic aperture radar (SAR), due to its all-weather and all-time imaging capability, plays an important role in mapping sugarcane cultivation in cloudy areas. However, the inherent speckle noise of SAR data worsens the “salt and pepper” effect in the sugarcane map. Therefore, in previous studies, an additional land cover map or optical image was still required. This study proposes a new application paradigm of time series SAR data for sugarcane mapping to tackle this limitation. First, the locally estimated scatterplot smoothing (LOESS) smoothing technique was exploited to reconstruct time series SAR data and reduce SAR noise in the time domain. Second, temporal importance was evaluated using RF MDA ranking, and basic parcel units were obtained only based on multi-temporal SAR images with high importance values. Lastly, the parcel-based classification method, combining time series smoothing SAR data, RF classifier, and basic parcel units, was used to generate a sugarcane extent map without unreasonable sugarcane spots. The proposed paradigm was applied to map sugarcane cultivation in Suixi County, China. Results showed that the proposed paradigm was able to produce an accurate sugarcane cultivation map with an overall accuracy of 96.09% and a Kappa coefficient of 0.91. Compared with the pixel-based classification result with original time series SAR data, the new paradigm performed much better in reducing the “salt and pepper” spots and improving the completeness of the sugarcane plots. In particular, the unreasonable non-vegetation spots in the sugarcane map were eliminated. The results demonstrated the efficacy of the new paradigm for mapping sugarcane cultivation. Unlike traditional methods that rely on optical remote sensing data, the new paradigm offers a high level of practicality for mapping sugarcane in large regions. This is particularly beneficial in cloudy areas where optical remote sensing data is frequently unavailable.

Neighborhood Competition and Understory-Associated Vegetation Are Important Factors Influencing the Natural Regeneration of Subtropical Mountain Forests

Natural regeneration is deemed essential for maintaining biodiversity and ecosystem stability. Previous studies, however, have primarily concentrated on regions exhibiting limited environmental and climatic variability, overlooking the classification of natural regeneration based on age and source. Research conducted at the mesoscale, characterized by increased environmental variability and the incorporation of neighborhood competition and understory-associated vegetation, enhances our comprehension of the multifaceted influences on natural regeneration. To comprehend this issue, this study implemented 60 plots, each measuring 20 m × 20 m, across five distinct areas of Chongqing, China. Twenty explanatory variables were chosen from five diverse categories: understory vegetation, neighborhood competition, stand structure, climatic factors, and environmental factors. And the naturally regenerated species were classified into seedlings and saplings, as well as endogenous and exogenous species, based on their age and origin. We examined the response of the different categories of natural regeneration to various factors and constructed a structural equation model (SEM) for significant factors to investigate their direct and indirect effects on natural regeneration. A total of 61 regenerated tree species belonging to 29 families and 42 genera were found in the study area, and the naturally regenerating species with high importance values were Quercus fabri, Robinia pseudoacacia, Alangium chinense, Cunninghamia lanceolata, and Ligustrum lucidum. It was found that neighborhood competition and understory-associated vegetation explained the largest proportion (more than 50%) of the variation in the different categories of natural regeneration, and forests with clumped distribution (W), a high mingling index (M) and strong competition (H) had a reduced natural regeneration capacity. Understory-associated herbs significantly reduced natural regeneration and the crowdedness index (C) significantly inhibited the understory-associated herbs, thus indirectly promoting natural regeneration. The shrub cover is significantly and positively correlated with the number of naturally regenerated plants and can be used as an indicator of a forest community’s regeneration potential. Understanding the differences in the importance of various factors at the mesoscale, as well as their direct and indirect impacts, can help us further comprehend the mechanisms of natural regeneration and provide a foundation for the sustainable development of forests.

Research on survey line arrangement of a multibeam bathymetric system in ocean mapping

Submarine topography measurement technology is an important technology for exploring marine resources. Multi-beam bathymetry systems have high efficiency and important application value in underwater resource surveys, marine delimitation, and other fields. They are currently one of the most widely used measurement technologies. This study aims to optimize multi-beam bathymetry technology and apply it to seabed topography measurement, achieving a transition from point measurement to line measurement and minimizing measurement paths. A mathematical model was established for the coverage width and overlap rate between adjacent bands of multi-beam bathymetry at a given water depth based on planar geometric modeling and three-dimensional geometric modeling. The model was applied to a rectangular sea area with a length of 2 nautical miles (3704 meters) from north to south and a width of 4 nautical miles (7408 meters) from east to west. The optimal survey line planning was obtained as follows: all survey lines are in the north-south direction, with a total of 34 survey lines and a total length of 68 nautical miles. This model has good solution results for optimizing the layout of survey lines under different seabed conditions and can adjust important parameters of the system according to different conditions. The model has broad practical significance and can provide a reference for ocean-sounding work and other fields with high accuracy.

A novel transformer-based neural network under model interpretability for improving wheat yield estimation using remotely sensed multi-variables

Timely and accurate yield prediction before wheat harvest is of great significance for food policy formulation and national economic development. Deep learning method gains importance on crop yield estimation and growth monitoring with the rapid development of deep learning models combined with remotely sensed data. However, the problems of nonlinear parameter optimization and long-term dependence in time series data have restricted the improvement of yield estimation accuracy. Transformer model completely abandons the traditional deep learning architecture and is gradually applied to time series tasks due to the advantage in modeling long-term dependence. This study introduced a novel transformer-based deep learning framework to estimate winter wheat yield in the Guanzhong Plain utilizing remotely sensed multi-variables, namely leaf area index (LAI), fraction of photosynthetically active radiation (FPAR) and vegetation temperature condition index (VTCI). The proposed model, called SSA-LSTM-transformer (SLTF), was developed for dealing with above problems under the automatic optimization capability of the sparrow search algorithm (SSA) and the long-term memory advantage of the long short-term memory (LSTM) structure. The findings demonstrated that the SLTF model achieved better estimation accuracy at the county level (R2 = 0.72, RMSE = 488.68 kg/ha) compared with the single transformer model (R2 = 0.61, RMSE = 573.99 kg/ha). The analysis on SLTF model’s performance at sampling sites over different disasters suggested that the model can effectively learn the effects of diseases, lodge and pests on crop yield estimation, which had good generalization ability at all sampling sites (R2 = 0.45, RMSE = 738.63 kg/ha). The Shapley Additive exPlanations (SHAP) approach was employed to evaluate the relative importance of remotely sensed multi-variables to yield and to understand how each input variable influences the estimated yield for global interpretability and local interpretability of the SLTF model. It was found that FPAR played the largest roles in yield estimation with the highest importance value, and FPAR and LAI from late April to late May and VTCI from late March to mid-April were regarded as important features for the estimated yield with high importance value. In conclusion, our findings indicated the potential of SLTF model for winter wheat yield estimation, which contributes to promoting further application of remotely sensed technology for agricultural production.

Species Diversity and Composition of Macrophytes in Shallabugh Wetland, Ganderbal, Jammu, and Kashmir, India

Macrophyte diversity, richness, and composition of the Shallabugh wetland Reserve, one of the Important Bird and Biodiversity Area in India. The wetland shows the presence of 39 plant species of 27 families and three tree species belonging to three families and a diversity index of H = 3.12 and Evenness e^H/S = 0.5836. The high Importance Value Index (IVI=22.8) was recorded for Typha latifolia, followed by Ceratophyllum demersum (IVI=19.2). The shift in macrophyte community structure is evidenced by the local extinction of Nelumbo nucifera from the Shallabugh wetland area and the near-disappearance of some economically important plants such as Trapa natans (IVI= 0.24). The investigation of various aspects of the wetland ecology of Shallabugh reveals that species composition has witnessed great changes over the years. The conversion of the 141 hectares of wetland into grassland gave way for terrestrial species to flourish. The study serves as the baseline study of the macrophyte community composition and structure of the Shallabugh wetland.

Online application for the diagnosis of atherosclerosis by six genes.

Atherosclerosis (AS) is a primary contributor to cardiovascular disease, leading to significant global mortality rates. Developing effective diagnostic indicators and models for AS holds the potential to substantially reduce the fatalities and disabilities associated with cardiovascular disease. Blood sample analysis has emerged as a promising avenue for facilitating diagnosis and assessing disease prognosis. Nonetheless, it lacks an accurate model or tool for AS diagnosis. Hence, the principal objective of this study is to develop a convenient, simple, and accurate model for the early detection of AS. We downloaded the expression data of blood samples from GEO databases. By dividing the mean values of housekeeping genes (meanHGs) and applying the comBat function, we aimed to reduce the batch effect. After separating the datasets into training, evaluation, and testing sets, we applied differential expression analyses (DEA) between AS and control samples from the training dataset. Then, a gradient-boosting model was used to evaluate the importance of genes and identify the hub genes. Using different machine learning algorithms, we constructed a prediction model with the highest accuracy in the testing dataset. Finally, we make the machine learning models publicly accessible by shiny app construction. Seven datasets (GSE9874, GSE12288, GSE20129, GSE23746, GSE27034, GSE90074, and GSE202625), including 403 samples with AS and 325 healthy subjects, were obtained by comprehensive searching and filtering by specific requirements. The batch effect was successfully removed by dividing the meanHGs and applying the comBat function. 331 genes were found to be related to atherosclerosis by the DEA analysis between AS and health samples. The top 6 genes with the highest importance values from the gradient boosting model were identified. Out of the seven machine learning algorithms tested, the random forest model exhibited the most impressive performance in the testing datasets, achieving an accuracy exceeding 0.8. While the batch effect reduction analysis in our study could have contributed to the increased accuracy values, our comparison results further highlight the superiority of our model over the genes provided in published studies. This underscores the effectiveness of our approach in delivering superior predictive performance. The machine-learning models were then uploaded to the Shiny app's server, making it easy for users to distinguish AS samples from normal samples. A prognostic Shiny application, built upon six potential atherosclerosis-associated genes, has been developed, offering an accurate diagnosis of atherosclerosis.

Management implications of habitat selection by whooping cranes (Grus americana) on the Texas coast

AbstractEffective habitat management for rare and endangered species requires a thorough understanding of their specific habitat requirements. Although machine learning models have been increasingly used in the analyses of habitat use by wildlife, the primary focus of these models has been on generating spatial predictions. In this study, we used machine learning models in combination with simulated management actions to guide planning and inform managers. We used data from 61 whooping cranes (Grus americana) tagged with GPS telemetry collars between 2009 and 2018 near Aransas National Wildlife Refuge in coastal Texas. We included variables based on topography, land use classification, vegetation height, plant phenology, drought, storm surge events, and both wild and prescribed fires. We then built models at multiple scales: population level, home range level, and roosting and daytime within home range level. We simulated responses to the two primary management actions used to enhance whooping crane habitat on Aransas National Wildlife Refuge: prescribed fire and removal of woody vegetation. At the population and home range scales, land use classification variables had the highest importance values, whereas the combined elevation and bathymetry layer was the most important predictor at both roosting and daytime within home range scales. Our findings revealed that the effects of fire, although generally modest, varied spatially. Areas dominated by estuarine wetlands exhibited higher predicted use within the first months after a fire, whereas those dominated by palustrine wetlands were more likely to be avoided in the immediate postfire years. Our simulation of vegetation removal identified the areas on Aransas National Wildlife Refuge where whooping cranes were predicted to benefit the most if vegetation were removed. These techniques can be used by other researchers wanting to examine and predict the effects of potential management actions on target species habitat.

Evidence of mesophication following selective cutting and shelterwood in Virginia’s eastern deciduous forest, USA

The replacement of oaks (Quercus) with mesic tree species in the eastern deciduous forests of North America involves a positive feedback loop being driven by fire suppression and climate change. In this study, we explored the impact of timber harvesting as a potential facilitator of mesophication. Young stands resulting from shelterwoods (on federal lands) and selective cutting (on private lands) were sampled to compare the composition and density of seedlings, saplings, and trees in western Virginia, USA. Oak overstory trees had lower importance values and densities at selective cutting sites compared to shelterwood sites. Among saplings, mesic species had higher importance values and densities than oaks at both selective cutting and shelterwood sites. Evidence of mesophication was found at both selective cutting and shelterwood sites; but a higher level of mesophication appeared to be occurring at the selective cutting sites than at shelterwood sites. At selective cutting sites scarlet oak (Quercus coccinea) was absent from all sampled plots and a dense midstory of subcanopy trees, especially eastern redbud (Cercis canadensis), appeared to be hindering successful oak regeneration. Our results indicate timber harvesting, without regard for the composition of the regeneration layer, may facilitate mesophication in the eastern deciduous forest, with selective cutting resulting in more successful establishment of mesic species compared to shelterwoods. These findings have implications for mesophication on private forest lands, where selective cutting is a very common method of timber harvesting.

Teak (Tectona grandis Linn. f) and Edaphic Factors Affecting the Regeneration of Woody Species and Their Functional Traits in Economic Forest Plantation, Northern Thailand

Improved understanding of relationships among plant traits, stand characteristics, and soil properties can provide insights into the regenerating tree communities of commercial teak plantations. We investigated whether plant traits could be used to predict the natural regeneration of woody species in teak plantations with different soil and stand conditions. Data were collected in fifty 20 m × 20 m plots that were established in teak plantations of varying ages in northern Thailand. We analyzed differences in stand characteristics, soil properties, and community-level functional traits among sites. The RLQ analysis was performed to explore the associations among species abundances, plant traits, and a combined set of soil variables and stand characteristics. Our results showed that tree species with high leaf dry matter contents and high wood density dominated communities in an older teak plantation and were associated with high OM and N concentrations. Trees with larger leaves are increased in plantations that had experienced their first teak thinning, and were rich in organic matter. Species with high specific leaf areas increased in sites with high teak basal areas and which had experienced more intense thinning on fertile soils. Thick-leaved species had high importance values on sites with high densities of teak and infertile soils. Our results indicated that tree communities with similar conspecific traits were associated with specific soil and stand conditions in teak plantations. A knowledge of these regeneration dynamics may allow forest managers to encourage increased natural regeneration and enhanced diversity in commercial teak plantations.

Conjoint Analysis: Consumer Preferences of Kampong Chicken in Bukittinggi City

When purchasing, consumers will prioritize the attributes attached to the product. Research needs to be done to increase consumer buying interest through consumer preference. Especially if it is done in an area with potential but little interest in Kampong chicken meat, this study aims to look at the preferences of Kampong chicken consumers in Bukittinggi City, West Sumatra, Indonesia. The research implementation time was in August 2023. This study's population is Kampong chicken consumers in several wholesale markets in Bukittinggi. For the sample size, 200 respondents had been taken. The variables in this study are a set of attributes of Kampong chicken: price, color, texture, age, gender, chicken meat parts, and chicken skin. The results showed that the highest importance value was at the age attribute of the chicken, which was 19.069, while the lowest value was the price. Based on calculations, it was found that consumers prefer affordable prices to price stabilization. The preferred meat color was meat with a pink color, chewy skin texture, medium size, 4-5 months old, male sex; the most preferred part was the breast, and the chicken was consumed without the skin.

Community structure and regeneration capacity of mangrove forest

Mangrove forests play a vital role in the environment. They provide a number of ecosystem services for supporting marine biodiversity, humans, and other living organisms inhabiting the area. This study aimed to determine the community structure and regeneration capacity of mangrove forests in Lebak, Sultan Kudarat, Philippines. Community structure was determined through relative density, relative frequency, relative dominance, and importance value. Using the center point circular plot method, 13 plots with 40 m diameter were established in two sampling sites: natural stand and reforested. Shannon-Weiner diversity and evenness indexes were used to determine species diversity and distribution, respectively. This study recorded a total of 14 462 individuals within the 1256 m² sampling plots, having Rhizophoraceae as the most abundant family with seven species that cover about 71% of both mangrove ecosystems. The vegetation analysis revealed that Ceriops tagal (70.35%) and Rhizophora mucronata (96.51%) had the highest importance value in the natural stand and reforested mangrove forests, respectively. Furthermore, these two species were also accounted for having the highest regeneration contribution among all species in each site. Shannon-Weiner diversity index revealed that the natural stand was more diverse compared to the reforested mangrove forest. However, the Shannon-Weiner evenness index showed that species in the reforested mangrove forest are more evenly distributed than species in the natural stand. Natural mangrove stands in Lebak have complex community structure and have higher regeneration capacity than the reforested mangrove forest. With this, the study suggested continuing the best practices employed for mangrove conservation in the area and crafting a strategic plan for sustainable mangrove resource utilization.

Plant communities and potential phytoremediation species for resource utilization of abandoned drilling mud

Oil and gas development produces a large amount of abandoned drilling mud, which may be a source of pollution but may also be a potential resource. A quadrat sampling method was used in the Changqing Oilfield to investigate the plant community characteristics inside and outside abandoned drilling mud pits at different completion times. The importance value of plant showed that the natural succession of plant communities in the abandoned drilling mud pool could be divided into three stages: (1) 4–8 years after the completion of the well, Leymus secalinus, Calamagrostis epigeios with the importance values of more than 100, were dominant species in the initial construction stage; (2) 9–13 years after the succession, the intense competition stage of the plant community, although the importance value of plant inside the mud pit had decreased, it was still higher than the importance value of plant outside the mud pool. The importance values of L. secalinus and Artemisia scoparia outside the mud pool were 62.5 and 52.5, while those in the mud pool were 95 and 75, respectively; (3) 23–28 years after the succession, the gradual stabilization stage of the plant community, the importance value of plant was lower than that in the mud pool. Leymus secalinus, C. epigeios and A. scoparia could be used for phytoremediation of abandoned drilling soil for their higher importance values. Changes of Shannon–Wiener index, Pielou index, Community ecological dominance and vegetation biomass showed that the mud pit was suitable for the recovery and growth of the dominant species, improved the diversity of plant communities inside the mud pit compared with the stable plant community outside the mud pit. Abandoned drilling mud increased the content of nitrogen, potassium and trace elements in plants. While the variation coefficient of heavy metal content in plants inside and outside the mud pit was large, but the content of heavy metals in plants was within the normal range. Abandoned drilling mud has the potential for resource utilization on the premise of ensuring soil quality and safety. This study provides information on the comprehensive treatment, resource utilization, disposal economics and environmental safety of abandoned drilling mud.

The Composition, Structure, and Standing Carbon Stock of Teak Based Agroforestry Systems in Gundih, Grobogan Regency, Central Java

The teak-based agroforestry system in Gundih, Grobogan Regency, Central Java Province is potentially equivalent to a secondary forest, based on the biodiversity, carbon stock, and utility. This study is prompted by the lack of research on tree vegetation analysis in teak-based agroforestry systems. The aim of this study is to determine the composition and structure of tree vegetation in agroforestry systems within the Gundih area. The research method used plots measuring 20 x 20 m2, in a sampling area of 1 ha and with plot placement using the Purposive Sampling method. The results show that there are 12 tree species from 9 families with a total population of 341 trees/ha. The two tree species with the highest Important Value (IV) are Tectona grandis L.f (93,48) and Swietenia mahagoni (L.) Jacq (66,78). The tree diversity of teak-based agroforestry systems is classified as moderate with an H’ value of 1,81. The carbon stock of tree stands in the agroforestry system is 64,43 MgC/ha. It can be concluded that teak-based agroforestry has the potential to be an option for environmental conservation.