Plant Area Research Articles

The Use of High-Quality Watermelon Seedlings Is Prerequisite to Limit the Transplanting Shock and Achieve Yield Earliness

One of the most important crops of the Mediterranean, watermelon (Citrullus lanatus), is almost exclusively established through seedlings. For many years, agronomists, nurseries, and farmers have aimed to produce and use high-quality seedlings for better growth in the field. However, seedling quality has not been examined as to what defines the subsequent plant, flower, and fruit development, and to what extent. Our aim was to test whether different seedling qualities labeled as “Optimum”, “Acceptable”, or “Not Acceptable” for cultivation actually perform variably in terms of vegetative, flowering, and fruit development, as well as fruit quality after a full growing cycle in the field. Vegetative growth (stem diameter, plant area, and leaf number) was evaluated until flowering and was enhanced for Optimum plants. The flowering of Not Acceptable plants started two days later, while Optimum plants retained a greater number of female flowers throughout the two-week blooming evaluation. Most importantly, Optimum plants developed mature fruits four and six days faster than the Acceptable and Not Acceptable ones, respectively, showing considerable yield earliness. The photosynthetic mechanism, as well as fruit morphology and phytochemical content, were not affected by quality categories. Overall, indeed it is important to use high-quality seedlings to achieve yield earliness of watermelon fruits.

The assimilation surface of winter wheat under the effect of seed treatment with biological preparations

Purpose. To establish the peculiarities of the winter wheat assimilation apparatus development under the effect of seed treatment with biological preparations.
 Methods. Research was conducted using field, laboratory and mathematical methods in 2019–2022 in the stationary crop rotation of the Department of Crop Production of the National Academy of Sciences of Ukraine on typical podzolized chernozems in the Right Bank Forest Steppe of Ukraine. The peculiarities of the formation of the assimilation area of winter wheat under the application of biological preparations for seed treatment were studied with the use of the following preparations: Binok Zerno, Rizomax, Trichodermin, Planoriz, Urozhai Start. N32P32K32 fertilizer and complex granular fertilizer DuraSOP actibition were applied in seedbed preparation. The leaf area and glumes were calculated using the Petiole Pro program. The area of the stem was determined by the formula of the external area of the cylinder.
 Results. The flag leaf is quite important for the formation of a high yield of winter wheat, since its loss or damage significantly reduces the flow of photosynthetic assimilates into the plant. In particular, in the earing phase (BBCH 57), on average its area was 7.68 thousand m2/ha and good indicators of the formation of the area of the flag leaf were in the treatments with Binok Zerno and Harvest Start, both separately and in combination. In the next phase of development – flowering (BBCH 65) – the patterns were preserved, although the combination of Binok Zerno in a complex with fertilizer Harvest Start was better – 9.24 thousand m2/ha. A decrease in the total assimilation area was observed as a result of the gradual dying off of the leaves of the lower tiers, a reduction in the possibility of photosynthesis of the flag leaf and a decrease in the area of the ear involved in assimilation. In particular, on average according to the experiment, in the earing phase (BBCH 57), the total assimilation area of winter wheat was 51.9 thousand m2/ha; in the flowering phase (BBCH 65) 51.8 and in the phase of milk grain ripeness (BBCH 75) 29.3 thousand m2/ha. The total area of the assimilation surface in the earing phase (BBCH 57) was the largest for the combined seed treatment with the biological preparation Binok Zerno and the fertilizer Urozhai Start – 61.7 thousand m2/ha. In the future, in the phases of flowering (BBCH 65) and milk ripeness of grain (BBCH 75), the obtained patterns were preserved and the best treatment was the combined application of Binok Zerno and Harvest Start. By the end of the vegetation season, the concentration of the main photopigments in the leaves of winter wheat decreased In the phase of milk ripeness of the grain (BBCH 75), the content of chlorophyll a was 11.01 mg/g and chlorophyll b 3.93 mg/g. However, at earlier stages of wheat ontogenesis, the content of chlorophyll b in leaves increased, while chlorophyll a per gram of leaf dry matter decreased. It was established that the average content of chlorophyll a was 11.6 mg/g during the earing phase (BBCH 57), while the content of chlorophyll b was 4.09 mg/ha. In the flowering phase (BBCH 65), their content was 11,4 and 4.14 mg/ha, respectively. It was determined that the complex seed treatment with Binok Zerno + Harvest Start together with fertilizer N32P32K32 + Actibion ensured a higher content of chlorophylls – 16.3; 16.0 and 15.4 mg/g of dry matter, respectively.
 Conclusions. The application of the studied biological preparations for the seed treatment of winter wheat seeds contributes to a significant increase of the indicators of the total assimilation area of plants throughout the vegetation season, in particular its components, such as the area of flag leaves, blumes and stems, as well as the content of photosynthetic pigments. Established regularities of plant growth and development are important factors for optimizing crop cultivation technology in the conditions of the Right Bank Forest Steppe of Ukraine.

Phenological growth stages of Gleditsia sinensis Lam. (Fabaceae) using the extended BBCH scale

AbstractGleditsia sinensis is a species endemic to China, an ecologically economic multipurpose tree with great development potential, which could be used as medicine, food, industrial materials and wood. It is well known that the standardized description of plant development stages according to their phenological characteristics not only is crucial for conduct of various agronomic practices, but also facilitates the exchange of new findings based on the same understanding of the plant. However, a uniform phenology scale of G. sinensis has rarely been reported, despite its expanding plant area and rapid development of this industry over the past few years. Thus, phenological events of G. sinensis were monitored based on the BBCH scale during two consecutive years in this study. Eight of the 10 BBCH stages described in detail by combining numbers and letters based on its species characteristic were accurately recorded, including bud development (0), leaf development (1), shoot development (3), inflorescence emergence (5), flowering (6), pod development (7), maturity of pod (8) and senescence (9). As far as we know, it is the first time that a special phenological rhythm for G. sinensis has been developed using an extended BBCH scale, which not only provides the basis for other basic research, but also assists growers in conducting planting management practices.

Advancing terrestrial biodiversity monitoring with satellite remote sensing in the context of the Kunming-Montreal global biodiversity framework

Satellite remote sensing (SRS) provides huge potential for tracking progress towards conservation targets and goals, but SRS products need to be tailored towards the requirements of ecological users and policymakers. In this viewpoint article, we propose to advance SRS products with a terrestrial biodiversity focus for tracking the goals and targets of the Kunming-Montreal global biodiversity framework (GBF). Of 371 GBF biodiversity indicators, we identified 58 unique indicators for tracking the state of terrestrial biodiversity, spanning 2 goals and 8 targets. Thirty-six shared enough information to analyse their underlying workflows and spatial information products. We used the concept of Essential Biodiversity Variables (EBV) to connect spatial information products to different dimensions of biodiversity (e.g. species populations, species traits, and ecosystem structure), and then counted EBV usage across GBF goals and targets. Combined with published scores on feasibility, accuracy, and immaturity of SRS products, we identified a priority list of terrestrial SRS products representing opportunities for scientific development in the next decade. From this list, we suggest two key directions for advancing SRS products and workflows in the GBF context using current instruments and technologies. First, existing terrestrial ecosystem distributions and live cover fraction SRS products (of above-ground biomass, ecosystem fragmentation, ecosystem structural variance, fraction of vegetation cover, plant area index profile, and land cover) need to be refined using a co-design approach to achieve harmonized ecosystem taxonomies, reference states and improved thematic detail. Second, new SRS products related to plant physiology and primary productivity (e.g. leaf area index, chlorophyll content & flux, foliar N/P/K content, and carbon cycle) need to be developed to better estimate plant functional traits, especially with deep learning techniques, radiative transfer models and multi-sensor frameworks. Advancements along these two routes could greatly improve the tracking of GBF target 2 (‘improve connectivity of priority terrestrial ecosystems), target 3 (‘ensure management of protected areas’), target 6 (‘control the introduction and impact of invasive alien species’), target 8 (‘minimize impact of climate change on biodiversity’), target 10 (‘increase sustainable productivity of agricultural and forested ecosystems’) and target 12 (‘increase public urban green/blue spaces’). Such improvements can have secondary benefits for other EBVs, e.g. as predictor variables for modelling species distributions and population abundances (i.e. data that are required in several GBF indicators). We hope that our viewpoint stimulates the advancement of biodiversity monitoring from space and a stronger collaboration among ecologists, SRS scientists and policy experts.

HemiPy: A Python module for automated estimation of forest biophysical variables and uncertainties from digital hemispherical photographs

Abstract Digital hemispherical photography (DHP) is widely used to derive forest biophysical variables including leaf, plant, and green area index (LAI, PAI and GAI), the fraction of intercepted photosynthetically active radiation (FIPAR), and the fraction of vegetation cover (FCOVER). However, the majority of software packages for processing DHP data are based on a graphical user interface, making programmatic analysis difficult. Meanwhile, few natively support analysis of RAW image formats, while none incorporate the propagation or provision of uncertainties. To address these limitations, we present HemiPy, an open‐source Python module for deriving forest biophysical variables and uncertainties from DHP images in an automated manner. We assess HemiPy using simulated hemispherical images, in addition to multiannual time‐series and litterfall data from several forested National Ecological Observatory Network (NEON) sites, as well as comparison against the CAN‐EYE software package. Multiannual time‐series of PAI, FIPAR and FCOVER demonstrate HemiPy's outputs realistically represent expected temporal patterns. Comparison against litterfall data reveals reasonable accuracies are achievable, with RMSE values close to the error of ~1 unit typically attributed to optical LAI measurement approaches. HemiPy's PAI, FIPAR and FCOVER outputs demonstrate good agreement with CAN‐EYE. Consistent with previous studies, when compared to simulated hemispherical images, better agreement is observed for PAI derived using gap fraction near the hinge angle of 57.5° only, as opposed to values derived using gap fraction over a wider range of zenith angles. HemiPy should prove a useful tool for processing DHP images, and its open‐source nature means that it can be adopted, extended and further refined by the user community.

Genetic Variances, Heritability and Traits Association of Early Maturing Maize Hybrids under Induced Drought at Seedling and Flowering Stages

Aims: Information on traits association and inheritance are crucial to designing appropriate breeding strategies for improving maize production and productivity in drought-prone ecologies. The objectives of this study were to investigate inter-trait relationships among maize hybrids and estimate genetic variances and heritability of drought tolerance parameters under seedling and flowering drought conditions.
 Methodology: Sixty-six single cross hybrids generated using diallel mating design plus nine hybrid checks were evaluated using a 5 x 15 alpha lattice and randomized complete block designs in three replicates on the field and in the screenhouse respectively, during 2015 cropping season. Data were collected on grain yield, ears per plant, anthesis-silking interval, seedling aspect, chlorophyll content and leaf area and these data were subjected to analysis of variance as well as correlation and path coefficient analyses.
 Results: Significant mean squares (P = .05) were observed for all measured traits except leaf area and shoot fresh weight. Narrow-sense heritability estimate for grain yield was moderate (33.4%) on the field and low (0 – 25%) for all the seedling traits. The low narrow-sense heritability estimates observed for most seedling traits implied that the scope for improvement of these traits in the genotypes is limited. Seedling traits under drought stress were not directly correlated with grain yield on the field except number of dead leaves relative to the total number of leaves. Results of the path analysis revealed that number of leaves, number of dead leaves and chlorophyll content under the screenhouse conditions had significant direct effects on grain yield on the field.
 Conclusion: Number of leaves, and chlorophyll content under drought at seedling stage could therefore be used as indicator traits for grain yield improvement in maize exposed to drought stress at flowering stage.

The NWRD Dataset: An Open-Source Annotated Segmentation Dataset of Diseased Wheat Crop.

Wheat stripe rust disease (WRD) is extremely detrimental to wheat crop health, and it severely affects the crop yield, increasing the risk of food insecurity. Manual inspection by trained personnel is carried out to inspect the disease spread and extent of damage to wheat fields. However, this is quite inefficient, time-consuming, and laborious, owing to the large area of wheat plantations. Artificial intelligence (AI) and deep learning (DL) offer efficient and accurate solutions to such real-world problems. By analyzing large amounts of data, AI algorithms can identify patterns that are difficult for humans to detect, enabling early disease detection and prevention. However, deep learning models are data-driven, and scarcity of data related to specific crop diseases is one major hindrance in developing models. To overcome this limitation, in this work, we introduce an annotated real-world semantic segmentation dataset named the NUST Wheat Rust Disease (NWRD) dataset. Multileaf images from wheat fields under various illumination conditions with complex backgrounds were collected, preprocessed, and manually annotated to construct a segmentation dataset specific to wheat stripe rust disease. Classification of WRD into different types and categories is a task that has been solved in the literature; however, semantic segmentation of wheat crops to identify the specific areas of plants and leaves affected by the disease remains a challenge. For this reason, in this work, we target semantic segmentation of WRD to estimate the extent of disease spread in wheat fields. Sections of fields where the disease is prevalent need to be segmented to ensure that the sick plants are quarantined and remedial actions are taken. This will consequently limit the use of harmful fungicides only on the targeted disease area instead of the majority of wheat fields, promoting environmentally friendly and sustainable farming solutions. Owing to the complexity of the proposed NWRD segmentation dataset, in our experiments, promising results were obtained using the UNet semantic segmentation model and the proposed adaptive patching with feedback (APF) technique, which produced a precision of 0.506, recall of 0.624, and F1 score of 0.557 for the rust class.

Plants lacking OST1 show conditional stomatal closure and wildtype-like growth sensitivity at high VPD.

Climate change-associated rise in VPD (atmospheric vapor pressure deficit) results in increased plant transpiration and reduced stomatal conductance, photosynthesis, biomass, and yield. High VPD-induced stomatal closure of Arabidopsis is an active process regulated via the kinase SnRK2.6 (OPEN STOMATA 1, OST1). Here, we performed gas exchange, leaf water potential and rosette growth measurements to study, whether (1) high VPD-induced stomatal closure is detected in plants carrying loss-of-function mutations in OST1 (ost1-3) when they are grown at reduced soil water content or measured at increased air temperature; (2) ost1-3 plants expressing OST1 construct with no ABA-activation domain, but intact ABA-independent activation, show stronger stomatal VPD response compared with ost1-3 plants; and (3) rosette area and biomass of ost1-3 are more affected by growth at high VPD compared with Col-0. The stomata of well-watered ost1-3 plants were insensitive to high VPD regardless of air temperature, but in deficit-irrigated ost1-3, leaf water potential decreased the most and stomata closed at high VPD. Differences between VPD-induced stomatal closures of ost1-3 plants and ost1-3 plants expressing OST1 with no ABA-activation domain point at gradual VPD-induced ABA-independent activation of OST1. High VPD conditions led to similar reductions in rosette area and specific leaf area of well-watered Col-0 and ost1-3 plants. Rosette dry mass was unaffected by high VPD. Our results show that OST1 loss-of-function plants display conditional stomatal closure and no extra sensitivity of rosette area growth compared with Col-0 wildtype under high VPD conditions.

Landscape structure of the territory of the district Pustynsky of the projected National Park Nizhegorodskoe Zavolzh’e

The paper presents the results of landscape differentiation of the territory of the district Pustynsky of the projected National Park Nizhegorodskoe Zavolzh’e, performed at the hierarchical level of landscape types. The researched territory is located in the broad-leaved forest subzone of the forest-steppe zone, indigenous vegetation has been preserved on its territory - broad-leaved spruce, pine, pine-spruce forests. Currently, is being completed work on the creation of the Nizhny Novgorod Region’s first national park Nizhegorodskoe Zavolzh’e, which is designed as a cluster, including five sites. The specifics of the national park’s operating mode require functional zoning of the territory, taking into account the vulnerability of natural complexes, permissible recreational loads and distribution areas of rare plant and animal species, which determines the high demand for landscape zoning schemes necessary for the effective organization of environmental and recreational activities. The article presents a scheme of landscape zoning of the territory of one of the five districts of the projected national Park – Pustynsky.

Improved Prediction of Aquatic Beetle Diversity in a Stagnant Pool by a One-Dimensional Convolutional Neural Network Using Variational Autoencoder Generative Adversarial Network-Generated Data

Building a reasonable model for predicting biodiversity using limited data is challenging. Expanding limited experimental data using a variational autoencoder generative adversarial network (VAEGAN) to improve biodiversity predictions for a region is a new strategy. Aquatic beetle diversity in a large >30-year-old artificial pool that had not had human interference in Nanshe Village (Dapeng Peninsula, Shenzhen City, Guangdong Province, China) was investigated. Eight ecological factors were considered. These were water temperature, salinity, pH, water depth, proportional area of aquatic plants, proportional area of submerged plants, water area, and water level. Field sampling was performed for 1 or 2 days in the middle or late part of each month for a year. A type D net was swept 10 times in the same direction in each ~1 m × ~1 m sample square, generating 132 datasets (experimental data). In total, 39 aquatic beetle species were collected, 19 of which were assigned to Hydrophilidae, 16 to Dytiscidae, 3 to Noteridae, and 1 to Gyrinidae. A one-dimensional convolutional neural network (1-D CNN) was used to assess and predict the grade of the number of individuals and the number of aquatic beetle species. The Bayesian-optimized 1-D CNN established using 112 experimental datasets as the training set and the other 20 datasets as validation and testing sets gave a 74.0% prediction accuracy for the grade of the number of individuals and a 70.0% prediction accuracy for the number of species. The impact of insufficient sample data on the model was assessed using a VAEGAN to expand the training set from 112 to 512 samples, and then the Bayesian-optimized 1-D CNN-based VAEGAN prediction model was re-established. This improved prediction accuracy for the grade of the number of individuals to 86.0% and for the number of species to 85.0%. The grade of the number of individuals’ prediction accuracy was 88.0% and the number of species’ prediction accuracy was 85.0% when the random effects of only obtaining a single individual of a species were excluded. The results indicated that the accuracy of the 1-D CNN in predicting the aquatic beetle species number and abundance from relevant environmental factors can be improved using a VAEGAN to expand the experimental data.

Investigating the Electrochemical Properties of Alkaloids Compound Derived from Catharanthus Roseus Extract

The Catharanthus roseus plant was extracted and converted to nanoparticles in this work. The Soxhlet method was used to extract alkaloid compounds from the Catharanthus roseus plant and converted them to the nanoscale. Chitosan polymer was used as a linking material and converted to Chitosan nanoparticles (CSNPs). The extracted alkaloids were linked with Chitosan nanoparticles by maleic anhydride to get the final product (CSNPs-Linker-alkaloids). The pure Chitosan, Chitosan nanoparticles, and CSNPs-Linker-alkaloids were characterized by X-ray diffractometer, and Fourier Transform Infrared spectroscopy. X-ray results show that all samples have an orthorhombic structure with crystallite size in nanodimensions. FTIR spectra prove that the P=O is the cross-linkage between chitosan and phosphate groups by ionic bond, which indicate that the Chitosan nanoparticle has been formed in the solution. FTIR spectrum for CSNPs - Linker - alkaloids appear a new distinct band at 1708.93 cm-1 which demonstrates the presence of C = O esterification. Atomic Force Microscope images of the Chitosan nanoparticles and CSNPs-Linker-alkaloids show that they have almost spherical shapes with average sizes of 90 and 92.6 nm respectively. The electroactive surface area of glassy carbon electrodes (GCE), extract plant, and Linker-alkaloids were calculated in KCl solution containing K3[Fe (CN)6]. The presence of CSNPs-Linker-alkaloids in modified glassy carbon electrodes about 3 times. The successful synthesis of organic nanoparticles from the Catharanthus roseus plant can be used safely in biosensors, environmental monitoring, and biomedical applications.

Microbial–Plant Collaborative Remediation of Cd-Contaminated Wastewater and Soil in the Surrounding Area of Nuclear Power Plants and Risk Assessment

The continuous development of China’s nuclear industry has caused an increasingly serious problem of heavy metal pollution in the ecological environment. A survey of the current situation shows that the quality of China’s groundwater bodies and their surrounding ecological environment has been severely affected. China has started to devote more attention to the issue of nuclear emissions and pollution. In view of this, this study takes an area contaminated by nuclear power plant emissions as the object of research and uses plant–microbe synergy to remediate the cadmium-contaminated environment. Cadmium-tolerant strains were isolated from the soil and identified as Serratia marcescens. The morphological characteristics of the cadmium-tolerant strains were observed with electron microscopy in the presence or absence of cadmium ions. The removal of Cd2+ from wastewater was analyzed in four experimental groups: Cd2+ removal from Cd2+-contaminated wastewater by combining a Cd-tolerant strain with Cd-flower, Cd-tolerant strain with Cd-flower, Cd-flower with alkali treatment, and Cd-tolerant strain with alkali treatment. This study innovatively treated Cd ion concentrations of 50 mg/L, 100 mg/L, 200 mg/L, and 300 mg/L. The results showed that the cadmium-tolerant strains were more densely concentrated in the treated Phyllostachys than in the untreated condition. This indicates that the Cd-tolerant strains were effectively enhanced by the alkali treatment of Phyllostachys spp. and that the adsorption of Cd ions to the Cd-tolerant strains was improved. In the presence of Cd2+ flowers only, the best removal of Cd2+ was achieved at a concentration of 50 mg/L, with a removal rate of 74.10%; the addition of Cd-tolerant strains resulted in a removal rate of 91.21%. When the alkali treatment was applied to the flat bamboo flowers, the removal rate was 84.36% when the concentration of Cd2+ was 100 mg/L. Then, when the cadmium-tolerant strain was added to the treated flat bamboo flower group, the maximum removal rate was 89.74% when the concentration of Cd2+ was 100 mg/L. The cadmium ion content of Cd2+ increased positively with increasing experimental time. In addition, the quasi-secondary correlation coefficients for cadmium ions in Lobelia were all greater than 0.9905, indicating that the adsorption kinetics were significantly correlated with the quasi-secondary kinetics. The analysis of heavy metal enrichment in Lobelia was divided into four groups, with Lobelia showing the best tolerance and cadmium adsorption capacity at a cadmium concentration of 20 mg/L. The results of super-enrichment coefficients showed that the enrichment coefficients of Lobelia ranged from 1.03 to 1.97, with values greater than 1. All these results indicate that the combination of cadmium-tolerant strains and plants can effectively remediate nuclear-contaminated soil and wastewater, thus improving soil availability and water regeneration, and improving the human living environment.

Development of nuclear power in Belarus: a sociological analysis of the elasticity of public opinion

The article discusses the results of sociological monitoring of public opinion on the use of nuclear energy in Belarus. The main part presents an analysis of the data obtained from the results of a sociological study conducted by the Institute of Sociology of the National Academy of Sciences of Belarus in 2022 on the assignment “Conduct sociological monitoring of public opinion of the population of the Republic of Belarus in order to form a positive attitude towards nuclear energy” of event 8 “Information and analytical support for the development of nuclear Energy in the Republic of Belarus” of subprogram 3 “Scientific support for the efficient and safe operation of the Belarusian nuclear power plant and promising areas for the development of nuclear energy” of the State Program “Science-intensive technologies and equipment” for 2021– 2025. The time intervals within which important events had a direct or indirect impact on public opinion about nuclear energy are characterized. A sociological method of calculation has been developed that makes it possible to trace the vector of public opinion’s response to nuclear energy (increase or decrease in the level of loyalty) to various internal or external factors. An assessment of the elasticity of public opinion about nuclear power is carried out with the construction of a typology of this elasticity. Also, self-assessments of the respondents’ formation and stability of their position regarding the implementation of the project “Belarusian NPP” were revealed. The need for systematic information and explanatory work among the population on all the main aspects of the practical use of nuclear energy is shown.

Influence of non-urban reference delineation on trend estimate of surface urban heat island intensity: A comparison of seven methods

Increasing concern over urban heat mitigation creates an emerging necessity to track the evolution of urban heat island intensity (UHII) to assess the effectiveness of existing plans in combating urban heat. However, complex human-environment interactions make it difficult to accurately isolate urban effects in UHII evolutions due to unstable non-urban references. This study provided the first test on the sensitivity of surface UHII (SUHII) trend estimate to seven methods of non-urban reference delineation across 281 Chinese cities. The corresponding seven non-urban references include administrative non-urban areas, administrative non-urban areas excluding extreme elevations, administrative low plant areas, suburb, outer suburb, outer suburbs progressively excluding unstable areas interfered by evident greening/desertification trends and the SUHI footprint of neighboring cities, respectively. Results revealed that the selection of different non-urban references significantly altered SUHII and the nature of observed surface thermal island (heat or cold) in 74% and 8% of cities, respectively. Besides, due to diverse and inconsistent land use and land cover changes across and nearby non-urban areas, the way of non-urban reference delineation also affected the amplitude and even direction of statistically significant SUHII trends in 41% and 21% of cities, respectively. Among the seven methods, the use of suburb which was collectively interfered by urban and non-urban changing factors, produced a large number of misestimated significant downtrends (2.7-4.5 times more cities than other methods) and was therefore in general not recommended. Administrative non-urban areas were not suitable to cities with evident greening/desertification trends, yet the applicability can be largely enhanced by removing areas with extreme elevations. Low plant areas were in general feasible, except for the cities with suburban low plants additionally warmed up by urban areas. Outer suburb was relatively the optimal, particularly the areas with all concerned interferences excluded. Overall, this study provided empirical evidence supporting the need to use stable non-urban references for reliable trend estimate of urban-induced SUHII variations. The results may benefit more accurate assessments of the causes, progress, and consequences of SUHI evolution, thereby minimizing the chances of policy failure in SUHI mitigation.

Modelling aboveground biomass of a multistage managed forest through synergistic use of Landsat-OLI, ALOS-2 L-band SAR and GEDI metrics

To better understand forest carbon budgets and design forest-based climate change mitigation solutions, reliable biomass estimation is critical. Integrating multi-sensor remote sensing data can improve forest monitoring and evaluation. This study adopted a one-hectare plot size sampling design to improve the integration of GEDI footprints with in-situ, optical, and SAR data for the estimation of forest above-ground biomass (AGB). The study was carried out for a managed tropical forest in the Himalayan foothills of India. The space-borne GEDI retrieved the canopy height of the study area with an RMSE of 3.36 m and Adj. R2 of 0.70. Extrapolating GEDI footprint heights (RH95) with Landsat 8 indices using Random Forest (RF) yielded a spatial canopy height of the study area with an R2 of 0.97 and RMSE of 2.32 m. Using the GEDI canopy height, foliage density, and plant area index, the AGB at GEDI footprints level was estimated using RF, with an R2 of 0.91 and an RMSE of 20.10 Mg ha−1. The spatial AGB model that only considered ALOS-2 SAR variables had an R2 of 0.61 and an RMSE of 18.27 Mg ha−1, whereas the RF model that considered both SAR variables and canopy height had a superior R2 of 0.77 and a lower RMSE of 13.86 Mg ha−1. The addition of canopy height data reduced the RMSE of the AGB model by 4.41 Mg ha−1 and also predicted a higher range of AGB. The study demonstrates the effectiveness of combining GEDI data with other sensors (optical and SAR data) to provide precise AGB of multistage managed forests using a one-hectare plot size sampling design.

Ecophysiology of Growth and Yield of Several Local Rice Varieties (Oryza Sativa L.) withVarious Kinds of Irrigation

A research aims to examine the physiology, growth and yield of rice in several varieties of rice plants with System of Rice Intensification and conventional irrigation methods. The study was conducted using 3x4 factorial strip plot design arranged in a Completely Randomized Block Design with 3 blocks as replications. The first factor was the type of irrigation that had 3 treatments, i.e., irrigation, intermittent irrigation: 10 days inundated, 5 days drained and intermittent irrigation: 7 days flooding, 3 days drying. The second factor was the rice varieties consisting of 4 varieties, i.e., Rojolele Genjah, Mentik Wangi, Mentik Susu and Cempo Hitam.The results showed that the plant height of the Rojolele Genjah variety was higher than other varieties. The grain yield per hectare of Mentik Wangi, Mentik Susu and Cempo Hitam varieties were higher than the Rojolele Genjah Variety. The treatment of irrigation for 7 days of flooding and 3 days of drying was greater than other irrigation for panicle length, and harvest index. CGR of conventional irrigation treatment was greater than intermittent irrigation. There was interaction between varieties and irrigation on the leaf area of rice plants, which in Cempon Hitam Variety with irrigation intermittently 10 days of flooding 5 days drying had the broadest leave area.

Tropical forests are mainly unstratified especially in Amazonia and regions with lower fertility or higher temperatures

The stratified nature of tropical forest structure had been noted by early explorers, but until recent use of satellite-based LiDAR (GEDI, or Global Ecosystems Dynamics Investigation LiDAR), it was not possible to quantify stratification across all tropical forests. Understanding stratification is important because by some estimates, a majority of the world’s species inhabit tropical forest canopies. Stratification can modify vertical microenvironment, and thus can affect a species’ susceptibility to anthropogenic climate change. Here we find that, based on analyzing each GEDI 25 m diameter footprint in tropical forests (after screening for human impact), most footprints (60%–90%) do not have multiple layers of vegetation. The most common forest structure has a minimum plant area index (PAI) at ∼40 m followed by an increase in PAI until ∼15 m followed by a decline in PAI to the ground layer (described hereafter as a one peak footprint). There are large geographic patterns to forest structure within the Amazon basin (ranging between 60% and 90% one peak) and between the Amazon (79 ± 9% sd) and SE Asia or Africa (72 ± 14% v 73 ± 11%). The number of canopy layers is significantly correlated with tree height (r 2 = 0.12) and forest biomass (r 2 = 0.14). Environmental variables such as maximum temperature (T max) (r 2 = 0.05), vapor pressure deficit (VPD) (r 2 = 0.03) and soil fertility proxies (e.g. total cation exchange capacity −r 2 = 0.01) were also statistically significant but less strongly correlated given the complex and heterogeneous local structural to regional climatic interactions. Certain boundaries, like the Pebas Formation and Ecoregions, clearly delineate continental scale structural changes. More broadly, deviation from more ideal conditions (e.g. lower fertility or higher temperatures) leads to shorter, less stratified forests with lower biomass.

Environmental, economic, and social of <em>Colletotrichum gloeosporioides</em> in the cultivation of the Creole yam.

Maintaining some productivity of the Creole yam (Dioscorea alata L.), affected by anthracnose (Colletotrichum gloeosporioides), from agrochemicals, generates changes in soil fertility, water quality and in the agricultural ecosystem of peasant agri-food production, but the proportion in which the management of an endemic fungus impacts and therefore persistent over time is unknown. This situation leads to investigate the environmental, economic, and social impact caused by the management of anthracnose in the cultivation of yam in the municipality of Colosó, department of Sucre, Colombia. A descriptive quantitative methodology was followed; A sample of 135 producers participated from techniques such as direct observation, interviews, surveys, focus groups and for the trade-off analysis of environmental, economic and social impacts the Leopold matrix. The results show a peasant production composed mainly of men (96%), of mestizo origin (91.6%), aged 41 to 60 years (55%); level of education in primary (56.5%) and baccalaureate (20.6%); They plant areas of 1.0 to 1.75 hectares (60.1%) and little technical assistance. Soil (47.3%) was impacted by accumulation of agrochemicals and water when contaminated (71.7%). Leopold's matrix considered the transformation of the territory around tutoring, soil loss, contamination of water bodies and burning of crop residues. In conclusion, maintaining the productivity of the Creole yam cultivar involves establishing the trade-off of the relationship between the planned solutions and the impacts on ecosystems in terms of environmental costs.

Drivers of Species Distribution and Niche Dynamics for Ornamental Plants Originating at Different Latitudes

Human activities provide migration opportunities for many ornamental plants and make them become a new potential invasion risk, threatening the local ecosystem. However, ornamental plants come from a wide range of sources, and there is still a lack of understanding on the distribution driving factors, ecological niche dynamics and invasion ability of ornamental plants based on the origin of different latitudes to evaluate their potential invasion risks. In this study, an ensemble of ecological niche model and a niche dynamic model were used to analyze the invasion potential of herbaceous and woody ornamental plants originating from different latitudes. The results showed that there were significant differences in environmental factors driving the distribution of plants originating from different latitudes, and climate-related factors were the primary driving force for each plant in the native and introduced regions. Urban land was the most influential factor in the introduced areas of most plants, potentially reflecting the importance of human activities in the distribution of ornamental plants. Additionally, only woody plants originating from mid-latitudes showed greater diffusivity than those originating in high latitudes and low latitudes, and the niche widths of all the herbaceous plants in the introduced regions nearly exceeded those in the native regions. This phenomenon was observed only in woody plants with mid-latitude origins. The niche similarity of all plant species between the introduced and native regions was high, indicating that all species in the introduced regions inherited niche characteristics from plants in the native regions.

HUBUNGAN ANTARA BEBERAPA KARAKTERISTIK FISIKA TANAH DENGAN PRODUKSI NILAM DI KECAMATAN WOLASI KABUPATEN KONAWE SELATAN

Based on Regional Statistical Data for South Konawe Regency (2021) the harvested area of patchouli plants reached 427 ha with a total production of 924 tons or an average production of 2.16 tons ha-1 in 2019, but patchouli production has decreased sharply, where in 2020 production Patchouli only achieves an average production of 0.34 tons ha-1. This also happened in Wolasi Sub-District as one of the patchouli cultivation centers for South Konawe Regency. The average production is still far below the national average. It is suspected that the soil fertility factor is one of the causes of the decreased productivity of patchouli plants in Wolasi District. This research was carried out on patchouli plantations in Wolasi District, South Konawe Regency. The research objectives were: 1) to determine the relationship between soil physical characteristics and patchouli production in Wolasi District. The research was carried out from September to November 2022. The research method used a survey method which was based on field observations and soil analysis at the Soil Science Laboratory, Halu Oleo University. Determining the location of sampling of soil and patchouli production at the location of patchouli plantations in Wolasi District uses a composite sampling technique. There are 12 soil sampling locations. The results of the soil analysis were then statistically analyzed using Microsoft Excel software. Analysis was conducted to reveal the relationship between soil physical characteristics (porosity, bulk density and soil depth) with patchouli production. The results showed that content weight had a positive correlation and affected patchouli productivity by 23.23%. Porosity has a positive correlation and affects patchouli productivity by 16.68%. Effective depth has a positive correlation and affects patchouli productivity by 36.3%.Keywords: regression analysis, patchouli productivity, soil physical properties