Dense Vegetation Research Articles

Enhancing the Capacity of Tourism Awareness Groups in Climate Change Adaptation and Mitigation at the Tanjung Batu Mangrove Ecotourism, Sekotong Tengah Village, West Lombok Regency

Mangrove Ecotourism in Tanjung Batu is one of the unique tourist attractions on Lombok Island, featuring a scenic 11-hectare mangrove area with dense vegetation coverage. The site is equipped with several facilities, including a 417-meter wooden bridge, several gazebos, selfie spots, a homestay, and a café. The ecotourism management is handled by the Tourism Awareness Group (Pokdarwis) of Sekotong Tengah Village. This destination is quite popular, with no fewer than 300 tourists visiting each month. However, this area is prone to climate-related disaster risks such as tidal floods, strong winds, high waves, floods, and droughts. Additionally, the ecotourism management has mainly focused on physical aspects and lacks sufficient managerial skills for implementing a sustainable governance system. The proposed solution is to strengthen the Pokdarwis management to improve ecotourism governance, optimizing its potential to deliver greater social, economic, and environmental value while contributing to climate change adaptation and mitigation efforts. The conclusion from the community service activity is that to address these challenges, the community is committed to preserving the mangrove ecosystem, preventing disturbances from both internal and external factors, and managing ecotourism in a way that benefits the surrounding community by reducing climate-related disaster risks. Priority activities include mangrove rehabilitation and enrichment, beach cleanup, monthly management meetings, semi-annual evaluations, and promptly developing plans to strengthen the fishermen's economy through involvement in marine tourism packages

Monitoring Türkiye’s Vegetation Cover with NDVI: Terrestrial and Temporal Perspectives

This study aims to monitor and analyze the temporal and spatial dynamics of Türkiye's vegetation cover from 2000 to 2023 using MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI (Normalized Difference Vegetation Index) data. The primary objective is to assess the changes in vegetation density across various geographical regions of Türkiye and determine how these changes are influenced by environmental factors such as land use and climate variability. NDVI data from July of each year were processed using ArcGIS to classify vegetation into six categories, ranging from water bodies to dense forests. The study reveals significant fluctuations in NDVI values, indicating both vegetation growth and degradation across different regions over time. Key findings include a positive correlation between NDVI values and forested areas, and a negative correlation in regions affected by drought or land use change. These results provide valuable insights into the long-term trends of vegetation dynamics in Türkiye and can help inform future conservation and land management strategies.

A UAV Thermal Imaging Format Conversion System and Its Application in Mosaic Surface Microthermal Environment Analysis.

UAV thermal infrared remote sensing technology, with its high flexibility and high temporal and spatial resolution, is crucial for understanding surface microthermal environments. Despite DJI Drones' industry-leading position, the JPG format of their thermal images limits direct image stitching and further analysis, hindering their broad application. To address this, a format conversion system, ThermoSwitcher, was developed for DJI thermal JPG images, and this system was applied to surface microthermal environment analysis, taking two regions with various local zones in Nanjing as the research area. The results showed that ThermoSwitcher can quickly and losslessly convert thermal JPG images to the Geotiff format, which is further convenient for producing image mosaics and for local temperature extraction. The results also indicated significant heterogeneity in the study area's temperature distribution, with high temperatures concentrated on sunlit artificial surfaces, and low temperatures corresponding to building shadows, dense vegetation, and water areas. The temperature distribution and change rates in different local zones were significantly influenced by surface cover type, material thermal properties, vegetation coverage, and building layout. Higher temperature change rates were observed in high-rise building and subway station areas, while lower rates were noted in water and vegetation-covered areas. Additionally, comparing the temperature distribution before and after image stitching revealed that the stitching process affected the temperature uniformity to some extent. The described format conversion system significantly enhances preprocessing efficiency, promoting advancements in drone remote sensing and refined surface microthermal environment research.

Quantitative assessment of interplay between urbanization dynamics and land surface temperature variations using generalized additive model coupled PDP for sustainable urban planning and management.

The mountainous region of Asir is experiencing rapid and unsystematic urbanization leading to an increase in land surface temperatures (LST), which poses a challenge to human well-being and ecological balance. Therefore, it is necessary to study the interaction between land use and land cover (LULC)-induced urbanization and LST using advanced geostatistical techniques. In addition, understanding the urbanization process and urban density is essential for effective urban planning and management. The aim of this study was to investigate the interaction between the urbanization process, urban density and the associated LST. Using the Random Forest Algorithm, LULC mapping was conducted for the years 1990, 2000 and 2020. Metrics such as land cover change rate (LCCR), land cover index (LCI), landscape expansion index (LEI), mean landscape expansion index (MLEI) and area-weighted landscape expansion index (AWLEI) were used to understand urbanization processes and LULC changes. Convolutional kernels were used to model urban density, and the mono-window algorithm was applied to analyse LST in the selected years. In addition, the study assessed the Surface Urban Heat Island (SUHI) contribution index to LULC and used Generalized Additive Models (GAMs) in conjunction with Partial Dependence Plots (PDPs) to understand the relationship between urbanization processes, urban density and LST. In a detailed 30-year study, the application of the RF algorithm showed significant shifts in LULC with an overall validation accuracy of over 85%. Urban areas grew dramatically from 69.40 km2 in 1990 to 338.74 km2 in 2020, while water areas decreased from 1.51 to 0.54 km2. Dense vegetation increased from 43.36 to 52.22 km2, indicating positive ecological trends. The LST analysis showed a general warming, with the mean LST increasing from 40.51°C in 1990 to 46.73°C in 2020 and the highest temperature category (50-60°C) increasing from 0.78 to 33.35 km2. The built-up area of cities tripled between 1990 and 2020, with the Landscape Expansion Index reflecting significant growth in suburban areas. The modeling of urban density shows increasing urbanization in the centre, which will expand significantly to the east by 2020. The contribution of LULC to LST and the Urban Heat Island (SUHI) effect was evident, with built-up areas showing a constant temperature increase. GAMs confirmed a statistically significant relationship between urban density and LST, with different effects for different types of urban expansion. This comprehensive study quantitatively sheds light on the complicated dynamics of urbanization, land cover change and temperature variation and provides important insights for sustainable urban development.

Gastropods on the green roof of a high-rise building in a large European city

Understanding the distribution and diversity of terrestrial snails on green roofs (GR) can facilitate insights into the ecological functioning of these urban habitats. While green roofs have been shown to provide suitable habitat for mobile species such as birds and insects, there needs to be more research concerning the colonisation and persistence of less mobile animal groups, including terrestrial gastropods. The present study investigates the species richness of terrestrial gastropods on green roofs of high-rise buildings in Bratislava, Slovakia. The study examined four distinct types of green roofs: The green roofs were classified according to their management intensity, resulting in four categories: extensive, semi-intensive GR-A, semi-intensive GR-B, and intensive. The categories differed in terms of vegetation, substrate depth, irrigation, and sun exposure. The survey employed a variety of methods, including pitfall trapping, vegetation sweeping, soil sampling, and microhabitat investigations. The survey yielded evidence of 11 species of terrestrial gastropods (six snails and five slugs) inhabiting three GR types. The semi-intensive GR-A, which is characterised by dense vegetation and minimal management, supported all 11 species. No gastropods were observed on the extensive GR with shallow substrate and Sedum sp. vegetation. The presence of native and non-native species, including the non-native slug Ambigolimax valentianus, indicates that terrestrial gastropods can colonise GR. These findings emphasise the potential of GR to support urban biodiversity and highlight the need for further research on less mobile species in these habitats.

Impact of land cover changes on land surface temperature variations in Adama City, Ethiopia

ABSTRACT Land surface temperature (LST) is becoming a serious environmental issue, since it is an essential controller of city climate. Currently, addressing this challenge in urban planning has gained worldwide importance. The study aims to analyze the effect of land cover dynamics on LST using geographic information system and remote sensing techniques. In this study, Landsat 7 ETM+ (2002) and Landsat 8 TIRS (2022) data were used. The LST was retrieved from Landsat datasets. The correlation analyses were conducted on LST, normalized difference vegetation index (NDVI), and normalized difference built-up index (NDBI). The findings suggested that there was a negative correlation between LST and the NDVI, while a positive correlation existed with the NDBI. Moreover, NDBI was found to be a better predictor of LST than NDVI. Additionally, it was revealed that the proportion of dense and sparse vegetation cover was reduced from 24.14 km2 (17.47%) in 2002 to 18.17 km2 (13.15%) in 2022. Similarly, the average LST increased from 28.25 to 31.78°C. This indicated that the rapid growth of urban development was the primary factor behind the rise in LST. Therefore, it was deemed crucial to create a smart urban land use plan to mitigate the impacts of microclimate change.

Challenges and Opportunities of Sentinel-1 InSAR for Transport Infrastructure Monitoring

Monitoring displacement at transport infrastructure using Sentinel‑1 Interferometric Synthetic Aperture Radar (InSAR) faces challenges due to the sensor’s medium spatial resolution, which limits the pixel coverage over the infrastructure. Therefore, carefully selecting coherent pixels is crucial to achieve a high density of reliable measurement points and to minimize noisy observations. This study evaluates the effectiveness of various pixel selection methods for displacement monitoring within transport infrastructures. We employ a two-step InSAR time series processing approach. First, high-quality first-order pixels are selected using temporal phase coherence (TPC) to estimate and correct atmospheric contributions. Then, a combination of different pixel selection methods is applied to identify coherent second-order pixels for displacement analysis. These methods include amplitude dispersion index (ADI), TPC, phase linking coherence (PLC), and top eigenvalue percentage (TEP), targeting both point-like scatterer (PS) and distributed scatterer (DS) pixels. Experiments are conducted in two case studies: one in Germany, characterized by dense vegetation, and one in Spain, with sparse vegetation. In Germany, the density of measurement points was approximately 30 points/km², with the longest segment of the infrastructure without any coherent pixels being 2.8 km. In Spain, the density of measurement points exceeded 500 points/km², with the longest section without coherent pixels being 700 meters. The results indicate that despite the challenges posed by medium-resolution data, the sensor is capable of providing adequate measurement points when suitable pixel selection methods are employed. However, careful consideration is necessary to exclude noisy pixels from the analysis. The findings highlight the importance of choosing a proper method tailored to infrastructure characteristics. Specifically, combining TPC and PLC methods offers a complementary set of pixels suitable for displacement measurements, whereas ADI and TEP are less effective in this context. This study demonstrates the potential of Sentinel‑1 InSAR for capturing both regional-scale and localized displacements at transport infrastructure.

Field kinematics of intermittent swimming in bluegill sunfish (Lepomis macrochirus)—pelagic locomotion and littoral maneuverability

Abstract Objectives Locomotion is essential for the survival of animals. Fishes have evolved mechanisms to minimize the cost of transport. For example, Bluegill Sunfish (Lepomis macrochirus) employ intermittent swimming, which involves swimming at relatively slow speeds with short propulsive bursts alternating with gliding episodes. This typically involves axial undulation powered by slow-twitch muscle, either with or without pectoral fin usage. The propulsive bursts are at higher tailbeat frequencies than observed for a given average speed with constant propulsion, and muscle physiology experiments show that the propulsive bursts produce relatively high power, while the glide reduces fatigue relative to continuous activity. However, Bluegill encounter complex 3D in-shore habitats, in which an intermittent swimming gait may enable successful capture of habitat-specific prey. Methods Field observations of Bluegill Sunfish were made via underwater videography in Lake Waban, Massachusetts. Key Findings In both pelagic and littoral habitats, Bluegill employed intermittent swimming. This provided the maneuverability and muscle activity needed to capture prey items suspended in the water column and enabled effective prey detection and maneuverability for feeding on sessile invertebrates in dense vegetation. Radio telemetry studies demonstrated that bluegill moved regularly between the pelagic and the littoral. Conclusion In both zones, intermittent swimming may provide both energetic and foraging advantages.

Enhanced root zone soil moisture monitoring using multitemporal remote sensing data and machine learning techniques

Accurate root zone soil moisture (RZSM) estimation using remote sensing (RS) in areas with dense vegetation is essential for real-time field monitoring and precise irrigation scheduling. Traditional methods often face challenges due to the dense crop cover and the complexity of soil and climate interactions. These challenges include the coarse spatial resolution of available soil moisture products, the influence of vegetation and surface roughness, and the difficulty of estimating RZSM from surface data. Aiming to overcome these limitations, two RZSM estimation methods were developed by combining synthetic aperture radar (SAR) data from Sentinel-1 (VV and VH polarizations) and optical and thermal RS data from Landsat-8. These data sources were used in conjunction with various machine learning (ML) models such as M5-pruned (M5P), support vector regression (SVR), extreme gradient boosting (XGBoost), and random forest regression (RFR) to improve the accuracy of soil moisture estimation. In addition to RS data, soil physical and hydraulic properties, meteorological variables, and topographical parameters were selected as inputs to the ML models for estimating the RZSM of sugarcane crops in Khuzestan, Iran. This study identified the temperature vegetation dryness index (TVDI) as a critical parameter for estimating RZSM in combination with the Sentinel-1 SAR data under high vegetation conditions. In both methods, the RFR algorithm outperformed, with similar performance, the XGBoost, SVR, and M5P algorithms in estimating soil surface moisture (R2 = 0.89, RMSE = 0.04 cm3cm−3). However, the accuracy of the RFR algorithm decreased with increasing depth for both the optical-thermal and combined SAR and optical-thermal RS data. This decrease was more pronounced in the combined approach, particularly for the root zone, where the RMSE reached approximately 0.073 cm3cm−3. Accordingly, the key findings demonstrated that the optical-thermal RS data outperformed the SAR RS data for retrieving RZSM in high-vegetated areas. However, combining TVDI with SAR data is a substantial improvement that opens a new path in radar-based RZSM estimation methods under high vegetation conditions.

A singular, broadly-applicable model for estimating on- and off-path walking travel rates using airborne lidar data

Accurate prediction of walking travel rates is central to wide-ranging applications, including modeling historical travel networks, simulating evacuation from hazards, evaluating military ground troop movements, and assessing risk to wildland firefighters. Most of the existing functions for estimating travel rates have focused on slope as the sole landscape impediment, while some have gone a step further in applying a limited set of multiplicative factors to account for broadly defined surface types (e.g., “on-path” vs. “off-path”). In this study, we introduce the Simulating Travel Rates In Diverse Environments (STRIDE) model, which accurately predicts travel rates using a suite of airborne lidar-derived metrics (slope, vegetation density, and surface roughness) that encompass a continuous spectrum of landscape structure. STRIDE enables the accurate prediction of both on- and off-path travel rates using a single function that can be applied across wide-ranging environmental settings. The model explained more than 80% of the variance in the mean travel rates from three separate field experiments, with an average predictive error less than 16%. We demonstrate the use of STRIDE to map least-cost paths, highlighting its propensity for selecting logically consistent routes and producing more accurate yet considerably greater total travel time estimates than a slope-only model.

Greenness Exposure and Mortality Risk in a Cardio-Oncologic Population.

Knowledge is lacking on the relationship between greenness and mortality in cancer survivors who experience coronary artery disease (CAD), a cardio-oncologic population. We aimed to investigate the association between residential greenness exposure and all-cause mortality in a cardio-oncologic population. Cancer survivors undergoing percutaneous coronary intervention at the Rabin Medical Center in Israel between 2004 and 2014 were included in the study. Clinical data were collected from medical records during index hospitalization and from the Israeli National Cancer Registry. Residential greenness was estimated by the normalized difference vegetation index (NDVI), a satellite-based index derived from Landsat imagery at a 30-meter spatial resolution, with larger values indicating higher levels of vegetative density (ranging between -1 to 1). Mortality follow-up data were obtained through the end of 2021. Cox models were used to assess the hazard ratios (HRs) for all-cause mortality per 1SD increase in NDVI. Among 1,331 patients analyzed [mean (SD) age, 75.6 (10.2) years, 373 (28%) females], the mean (SD) NDVI within a 300-meter radius was 0.12 (0.03). During a median follow-up period of 12.0 (IQR 9.2-14.7) years, 883 (66%) participants died. After adjustment for potential confounding factors, including residential socioeconomic status, air pollution, and smoking, NDVI was inversely associated with mortality hazard [HR (95% CI) = 0.93 (0.86, 0.99); p=.042]. The association was stronger among individuals with more recently (<10 years) diagnosed cancer [HR (95% CI) = 0.89 (0.81, 0.98); p=.019]. In a cohort of cardio-oncologic patients, greenness was independently associated with lower mortality.

Detection of archaeological structure on the slope ground using geophysical methods: The case of the Castle of Canossa

Canossa Castle is located in the municipality of Canossa 18 km South of Reggio Emilia (North Italy). It was constructed in 940 by Adalberto Atto, son of Sigifredo of Lucca. Lombard chieftains needed this strategic hill to defend their lands against intrusions of other barbarian tribes. Subsequent improvements made the stronghold one of the best-defended castles in the country. Canossa Castle became particularly famous as a site of reconciliation between King Henry IV and Roman Pope Gregory VII during the Investiture Controversy in 1077.To redevelop the area and create an easy tourist route, the Superintendence of Archaeology, Fine Arts and Landscape for the Metropolitan City of Bologna and the Provinces of Modena, Reggio Emilia and Ferrara planned excavations in the area close to the Castle. To get precise information on where to carry out excavations geophysical surveys were undertaken in the spring of 2021. The castle stands on a rock with a steep slope and dense vegetation and this makes it very difficult to carry out geophysical prospecting. This guided the choice of geophysical methodologies to be used. For this reason, electrical resistivity tomography was used along the steep slope, while in the narrow flatter area, the ground penetrating radar methodology was used. The results demonstrate the effectiveness of the chosen geophysical methodologies.

The loss of riparian vegetation along streams causes morphological divergences in functional traits of semiaquatic insects (Heteropteran: Gerromorpha) in the eastern Amazon.

Understanding the effects of mining activities on Amazonian streams and their impact on aquatic communities is of paramount importance in the current context of resource overexploitation in society. In this study, we assessed the significance of the environment and interspecific interactions on the organization patterns of semiaquatic insect species in a mineral extraction region in the eastern Amazon. We utilized the morpho functional characteristics of 22 species from the suborder Gerromorpha (Heteropteran), considering both the abundance and sexual dimorphism of these species. Additionally, we quantified the density of riparian vegetation surrounding each stream to categorize sampling points and evaluate whether there are differences in species distribution patterns among categories. We sampled 16 sites, categorized into two treatments based on the percentage of riparian vegetation in forested and deforested areas located in the Capim River Basin. We did not find the action of environmental filters on the total assembly; however, we found significant morphological divergence for all the traits analyzed. On the other hand, the separation of streams into treatments with different portions of riparian vegetation showed that there are significant differences between them regarding species distribution patterns. Forested streams within a 500-m radius have species distributed over a larger area, indicating that these streams have greater resource availability or that species can use these resources more efficiently. Our results demonstrate the importance of riparian vegetation for the studied communities, as well as for mitigating the impacts caused by mining activities.

FOCOS DE CALOR E QUEIMADAS EM UNIDADES DE CONSERVAÇÃO FEDERAIS DO PANTANAL MATO-GROSSENSE NO PERÍODO DE 2016 – 2021

The Pantanal is one of the biomes that has suffered the most from burning, mainly due to its environmental characteristics. In view of this situation, this research sought to analyze the temporal space distribution of the sources of heat and recurrent fires in the Conservation Units Federal at the pantanal mato-grossense in the period 2016 to 2021 through Normalized Burn Ratio (NBR) and by the Forest Fires and Burns Program, made available by the National Institute for Space Research (INPE). Satellite images and analyzes of the NBR index were processed in a virtual platform (GEE) and a database was created, which were treated and generated two types of maps, the NBRs and the distribution of hotspots. The results showed that 2020 was the year with the highest occurrence of hotspots in the studied period, totaling 54,140 thousand hotspots inside of UCs. The UCs Mato-grossense Pantanal National Park, SESC-Pantanal Private Reserve of Natural Heritage Ecological Resort and the Taiamã Ecological Station, showed the highest area burned in the year 2021 throughout the study period. Compared to 2020, there was an increase in burned area in 2021 in the UCs, Taiamã Ecological Station, RPPN Reserve Jubran, RPPN Ecological Resort SESC-Pantanal, Mato-grossense Pantanal National Park. It has been shown that in UCs, RPPN Resort Farm Dorochê, RPPN Ecological Resort SESC-Pantanal, Mato-grossense Pantanal National Park the Low Severity, Low Moderate Severity and High Moderate Severity classes, which represent less dense vegetation, increased considerably from 2016 to 2021. The UCs that showed the highest burn were: RPPN Resort Farm Dorochê and Mato-grossense Pantanal National Park. The NBR in this study presented results that disagree with what actually happened in the UCs, showing that the period used in the study from July to October is not recommended, because the fires may not have occurred yet, however, it shows that for the following year when hot spots occurred, the NBR detects scars from the fires of the previous year.

Computation of drag coefficient for real vegetation in wetlands

The flow characteristics in wetlands and vegetated channels are depend on the physical structure, density, and pattern of vegetation. Estimating average velocity in vegetated wetlands requires an accurate determination of the drag coefficient. The innovation of this research lies in calculating the drag coefficient while considering the pattern shape, plant flexural rigidity, and vegetation structure. Laboratory experiments were conducted in a rectangular flume using a parallel pattern of Eleocharis plants at three densities: low, medium, and high, with discharge rates of 18.2, 23.7, and 28.8 L/s, respectively. Comparative analysis revealed that the equation proposed by Kothyari et al. (2009) [23] is just suitable for determining the drag coefficient on rigid cylinders with a staggered pattern and it should be improved for real vegetation with different pattern. A comprehensive equation was developed for real wetland vegetation, incorporating a new pattern coefficient for pattern shape (ζpp) and correction factor (η) to consider plant flexural rigidity and vegetation structure. The results demonstrate that this equation accurately predicts the drag coefficient (RMSE = 0.127, MAE = 0.107, and R2 = 0.9059) in channels with real vegetation with parallel and staggered patterns.

The urban air quality nexus: Assessing the interplay of land cover change and air pollution in emerging South Asian cities

Air quality degradation presents a significant public health challenge, particularly in rapidly urbanizing regions where changes in land use/land cover (LULC) can dramatically influence pollution levels. This study investigates the association between LULC changes and air pollution (AP) in the five fastest-growing cities of Bangladesh from 1998 to 2021. Leveraging satellite data from Landsat and Sentinel-5P, the analysis reveals a substantial increase in urban areas and sparse vegetation, with declines in dense vegetation and water bodies over this period. Urban expansion was most pronounced in Sylhet (22–254%), while Khulna experienced the largest increase in sparse vegetation (2–124%). Dense vegetation loss was highest in Dhaka (20–77%) and water bodies (9–59%) over this period. Concentrations of six major air pollutants (APTs) - aerosol index, CO, HCHO, NO2, O3, and SO2 - were quantified, showing alarmingly high levels in densely populated industrial and commercial zones. Pearson's correlation indicates strong positive associations between APTs and urban land indices (R > 0.8), while negative correlations exist with vegetation indices. Geographically weighted regression modeling identifies city centers with dense urban built-up as pollution hotspots, where APTs exhibited stronger impacts on land cover changes (R2 > 0.8) compared to other land classes. The highest daily emissions were observed for O3 (1031 tons) and CO (356 tons) at Chittagong in 2021. In contrast, areas with substantial green cover displayed weaker pollutant-land cover associations. These findings underscore how unplanned urbanization drives AP by replacing natural land cover with emission sources, providing crucial insights to guide sustainable urban planning strategies integrating pollution mitigation and environmental resilience.

Prescribed fire and natural habitat characteristics affect crawfish frog (Rana areolata) advertisement call transmission

ABSTRACT For acoustically signalling animals, the rate of signal degradation is critical for successful communication. Degradation is heavily influenced by habitat characteristics, with sound degrading more rapidly in the presence of environmental obstacles (e.g. vegetation). Land management strategies such as prescribed burns eliminate obstacles and should therefore lead to more efficient sound transmission. Crawfish frogs (Rana areolata) produce long-distance advertisement calls for breeding. Habitats surrounding crawfish frog breeding ponds vary in vegetative density, and prairies surrounding breeding habitat often undergo controlled burns prior to the breeding season. We hypothesised that R. areolata advertisement calls would transmit more efficiently in post-burned prairies compared to other more vegetated habitats. To test this hypothesis, we conducted a sound transmission playback experiment, broadcasting crawfish frog calls in three habitats: forest, prairie, and post-burned prairie. We compared sound degradation measures between habitat types and across distances. We found that crawfish frog calls experienced up to 6.8 dB less excess attenuation in post-burned habitats relative to other habitat types, and that in general, prairie habitats had better sound transmission than forest. These results indicate that land management and habitat structure have consequences for acoustic communication, and may also influence the findings of frog call detection surveys.

Resistivity anomalies in the shallow and deep crust beneath West Tasmania from a broadband magnetotelluric 2D transect

West Tasmania has a complex geological history, including a Cambrian tectonic collision and related orogenesis, which formed ore deposits in a volcanic hosted massive sulfide (VHMS) setting. While the topography and dense vegetation covering the area presents challenges for on-ground investigations, the area is relatively well-studied such that 3D geological models are available. This contribution presents results of a broadband magnetotelluric (MT) 2D transect across the area (∼30 stations over a ∼ 80 km line, deployed in early 2016) that enables a combined interpretation of regional-scale geoelectric and geological structures. After accounting for noise, distortion and geoelectric strike; we produce 2D resistivity models using OCCAM2D inversion. We infer low resistivity anomalies in the shallow ( < 3 km ), mid (3–8 km) and deeper crust. Along this MT transect the shallow and mid crust low resistivity zones correspond to major crustal faults. Deep low resistivity features in the east of the transect suggest fluid pathways associated with metamorphism along the western boundary of the Tyennan block during the Cambrian Tyennan Orogeny, while others potentially represent the metasomatism of lower crustal rocks and fluid pathways converging into the mid crust.

Exploring environmental condition of silvofishery pond to support the sustainability of mangrove management in Berau Regency, Indonesia

The integration of mangrove management with aquaculture, termed the silvofishery pond system, has been implemented in Berau Regency, East Kalimantan Province, Indonesia. A detailed survey was conducted to assess the features of mangrove terrain surrounding silvofishery ponds, aiming to enhance the productive and sustainable management of these mangrove areas in Berau Regency. This survey focused on various land characteristics such as topography, tidal patterns, water quality, soil properties, climate, and the state of mangrove vegetation. The health of mangrove vegetation was assessed by calculating the Important Value Index (IVI) across different growth stages: trees, saplings, and seedlings. The findings reveal that the mangrove adjacent to the silvofishery ponds in Berau Regency are home to 14 species from 13 genera and 10 families. Rhizophora mucronata displayed the highest IVI scores across all growth stages: 75.17% for trees, 93.14% for saplings, and 66.98% for seedlings, the latter shared with Rhizophora apiculata. Soil quality emerged as a critical limiting factor for land use in silvofishery ponds, particularly due to high potential acidity (low pH) and low nitrogen (N) content. To enhance soil quality, it is recommended that soil management practices such as remediation (via drying, submerging, flushing, or liming) and N supplementation through fertilization be employed. Furthermore, given the sparse mangrove vegetation density at the tree level (1,012 trees/ha), efforts to promote natural mangrove regeneration and prevent deforestation and degradation are advised. Considering the unique characteristics of the mangroves, the implementation of the komplangan model—a silvofishery approach that segregates mangroves restoration pond from grow-out ponds—is recommended to boost productivity and ensure sustainability in the coastal region of Berau.

Rootstock selection for ‘Swatow’ Mandarin trees grown at different locations throughout the Brazilian subtropics

Evaluating citrus rootstocks is of paramount importance in determining their suitability for a certain region and promoting resilience in orchards by increasing the genetic pool, thereby potentially contributing to a more strategic establishment of new plantings. This long-term field study (2000–2013) aimed to evaluate different rootstocks for ‘Swatow’ mandarin grown at two locations (Paranavaí and Londrina) in the Brazilian subtropics. Nine rootstocks were evaluated, including ‘Rangpur’ lime, ‘Swingle’ citrumelo, ‘Volkamer’ lemon, ‘Caipira DAC’ sweet orange, ‘Cleopatra’ and ‘Sunki’ mandarins, ‘Trifoliate’ orange, ‘Carrizo’, and ‘Fepagro C-13’ citranges. Trees were assessed for vegetative growth, yield, fruit quality, density, and yield estimates. The experimental design was a randomized block arranged in a 9 × 2 setting (rootstock × location) with 6 replicates and 4 trees per plot. ‘Swatow’ trees grew more vigorously in Londrina than Paranavaí, particularly for ‘Cleopatra’ and ‘Sunki’ pairings. Tree vigor was reduced with ‘Trifoliate’, resulting in higher tree density estimates and yield efficiency. This rootstock, along with ‘Rangpur’, ‘Swingle’, and ‘Carrizo’ provided superior yield to the scion. All tested rootstocks conferred good fruit quality. Fruits were larger and heavier in ‘Sunki’ pairings, showing higher soluble solids (SS) content, along with ‘Caipira DAC’, ‘Trifoliate’, ‘Swingle’, and ‘Carrizo’ at both locations. Our findings confirm the suitability of ‘Trifoliate’ orange, ‘Carrizo’ citrange, or ‘Caipira DAC’ orange rootstocks as promising candidates for ‘Swatow’ mandarin cultivation in humid subtropical and analogous regions. Further investigations are invoked to improve the horticultural performance of ‘Swatow’ mandarin trees grafted onto these rootstocks.