Topographic Position Research Articles

Assessment of Albariño (<i>Vitis vinifera</i> sp.) plasticity to local climate in the Atlantic eastern coastal terroir of Uruguay

Plasticity is typically used in biology to describe the ability of an organism to adapt to changes in its environment. Within a viticulture production system under similar management practices, studying the plasticity of a specific cultivar under different local climatic conditions can enhance our understanding of the grape typicity and, consequently, the wine style of a region. This work aims to assess the performance of Albariño vines grown in different mesoclimates within the emerging wine region along Uruguay’s Atlantic coast. The study was conducted in a commercial vineyard in Garzón, Maldonado Department, a key location in this developing wine region. Temperature sensors were installed in each of the four Albariño plots, situated in two contrasting topographic positions relative to Atlantic Ocean exposure, to assess mesoclimate and the ocean’s influences on grapevine plasticity. Agronomic measurements were taken to assess the performance of Albariño under the local climatic conditions. The multivariate analysis of yield and berry composition variables with ocean exposure and seasonal climate has identified three key findings: 1) the Albariño cultivar has shown strong potential for cultivation in eastern Uruguay due to its favourable agronomic and oenological performance, 2) vineyard ocean exposure has a greater effect on berry composition at harvest than on yield, contributing 70.7 % and 63.4 % of the total variability, respectively as observed from the Principal Component Analysis, 3) the correlations between berry composition and ocean exposure are stronger under warmer and drier conditions. Understanding the plasticity of Albariño under different local climatic conditions is valuable for sustainable production systems, provided both production and high quality are maintained. This study highlights the importance of selecting appropriate cultivars and understanding the local climate for the future success of vineyards.

Investigation of Lineament Extraction: Analysis and Comparison of Digital Elevation Models in the Ait Semgane Region, Morocco

An automated lineament extraction model was successfully applied in the mountainous region of Ait Semgane, Morocco, enabling the identification of geological and tectonic linear features. Our research implemented several approaches including Topographic Position Index (TPI), shading, and Digital Elevation Models (DEMs), as input for the lineament extraction algorithm and applied to various Dems. We aimed to compare all of these strategies to determine the optimal method and the most favorable input DEM. Results revealed variable performance among methods, emphasizing the importance of choosing the optimum method based on specific objectives. TPI and Hillshade methods showed high sensitivity in detecting lineaments, while ALOS PALSAR and Sentinel 1 InSAR datasets were effective for subtle features. Lineament density exhibited specific orientations for highly-dissected zones, with TPI highlighting NE-SW and E-W orientations. Lineament orientations demonstrated consistency with established geology, confirming pre-existing tectonic knowledge. Cartographic analysis of faults emphasized the success of the SRTM DEM model with the TPI method, highlighting significant faults. Results also revealed a concentration of faults in the NW and southern sectors, corroborating bibliographic references and the well-documented tectonic setting of the study area. This automated methodology facilitated lineament extraction in unmapped areas, reinforcing the validity of the undertaken cartographic analysis.

Multi-Approaches for Flash Flooding Hazard Assessment of Rabigh Area, Makkah Province, Saudi Arabia: Insights from Geospatial Analysis

Flash flood hazard assessment is a critical component of disaster risk management, particularly in regions vulnerable to extreme rainfall and climatic events. This study focuses on evaluating the flash flood susceptibility of the Rabigh area, located along the Red Sea coast in Makkah province, Saudi Arabia. Using advanced GIS tools and a spatial multi-criteria analysis approach, the research integrates a variety of datasets, including remotely sensed satellite data, the SRTM Digital Elevation Model (DEM), and topographic indices. The main goal was to produce detailed flood susceptibility maps based on the morphometric characteristics of the region’s drainage basins. These basins were delineated and assessed for their flood vulnerability using three distinct modeling techniques, each highlighting different aspects of flood behavior. The results show that the northern basin (Dulaidila) and the central basins (Rabigh, Algud, and Al Nuaibeaa) exhibit the highest flood risk, with significant susceptibility also observed in the southern basins (Ofoq and Saabar). Other basins in the region display moderate susceptibility levels. A key aspect of this analysis was the overlay of the integrated flood susceptibility map with the Topographic Position Index (TPI), a crucial topographic indicator, which helped refine the understanding of flood-prone areas by linking basin morphometry with in-situ topographic features. This study’s comprehensive approach offers valuable insights that can be applied to other coastal regions where hydrological and climatic data are scarce, contributing to more effective flood risk mitigation and strategic planning.

Exploring a GIS-based analytic hierarchy process for spatial flood risk assessment in Egypt: a case study of the Damietta branch

Floods are the most common and costly disasters worldwide, while spatial flood risk assessment is still challenging due to fewer observations and method limitations. In this study, the flood risk zonation in the Nile districts of the Damietta branch, Egypt, is delineated and assessed by integrating remote sensing with a geographic information system, and an analytical hierarchy process (AHP). Twelve thematic layers (elevation, slope, normalized difference vegetation index, topographic wetness index, modified normalized difference water index, topographic positioning index, stream power index, modified Fournier index, drainage density, distance to the river, sediment transport index, and lithology) are used for producing flood susceptibility zonation (FSZ) and six parameters (total population, distance to hospital, land use/land cover, population density, road density, and distance to road) are utilized for producing flood vulnerability zonation. Multicollinearity analysis is applied to identify highly correlated independent variables. Sensitivity studies have been used to assess the effectiveness of the AHP model. The results indicate that the high and very high flood risk classes cover 21.40% and 8.26% of the area, respectively. In 14.07%, 27.01%, and 29.26% of the research area, respectively, flood risk zones classified as very low, low, and moderate are found. Finally, FSZ is validated using the receiver operating characteristics curve and area under curve (AUC) analysis. A higher AUC value (0.741) in the validation findings demonstrated the validity of this AHP approach. The results of this study will help planners, hydrologists, and managers of water resources manage areas that are susceptible to flooding and reduce potential harm.

Potential phosphorus mobilization from riparian vegetation following freezing

Phosphorus (P) rich runoff from agricultural landscapes is a major contributor to freshwater eutrophication. Vegetated riparian zones are often employed to retain P from field runoff before it enters streams. In cold regions, vegetation has the potential to release P to runoff following freezing; however, it is unclear if this differs with winter frost severity, riparian zone local topography, vegetation type, and/or exposure to flooding/inundation. To explore the vulnerability of riparian vegetation to winter P losses, this study quantified soil and vegetation P concentrations from 8 riparian zones in Canada at different topographic positions within each riparian site (upper/field edge, lower/water edge) in both the fall and spring seasons and related this to observed surface temperatures and water levels throughout the non-growing season. This was complemented by two laboratory mesocosm experiments in which (1) plant samples were subjected to moderate (−40C) and severe (−250C) simulated winter frost treatments to quantify changes in their water extractable P (WEP) content, and (2) mesocosms were inundated with water to determine if dissolved P concentrations in flood water differed when plants were left intact, clipped but left on the soil surface, or harvested. Greater soil and vegetation P concentrations were observed at upper locations (field edge), and this remained consistent following freezing; however, vegetation WEP concentrations increased with greater simulated frost severity. In the field, temperatures were moderated by snow cover and although differences with riparian zone position were apparent between fall and spring collected samples, changes in P pools did not appear to be related to frost severity or inundation in the field. The mesocosm experiment revealed that harvesting vegetation considerably reduced dissolved P concentrations in flood water. This study shows that vegetated riparian zones can act as a source of P to streams during the winter non-growing season, and highlights the potential for riparian vegetation management in reducing P losses from riparian zones in cold climates.

Repeatability of Scheimpflug-Placido camera in mild dry eye versus normal eyes according to the topographical position of the cornea.

We aimed to investigate the repeatability of various corneal measurements according to topographical location in the entire cornea measured by dual rotating Scheimpflug-Placido camera and to explore the differences in repeatability between patients with mild dry eye and those with normal eyes. In both the normal and dry eye groups, divided based on BUT or the height of the tear film, there were no statistically significant differences in the ratio of unacceptable variation (RUV) and ICC. The consistency of the examination of the anterior and posterior refractive values and corneal thickness according to the corneal location, measured three times repeatedly using the Galilei anterior segment camera, was high. There was no difference based on the height of the tear film or the tear film break-up time. However, caution is needed when interpreting the values of the anterior corneal refractive values, as there can be changes of more than 0.5D within 3mm of the central area.

Geospatial Intelligence for Landslide Susceptibility and Risk Analysis: Insights from NH31A and East Sikkim Himalaya Settlements

Slope instability is a serious concern in the Sikkim Himalayas. The town and numerous road segments along National Highway 31A were ravaged by multiple landslides that occurred in the nearby region. A bivariate statistical method known as frequency ratio (FR), information value (IV), and certainty factor (CF) analysis was employed in this work to examine landslide risk assessment (LRA) and landslide susceptibility zonation (LSZ) maps in the Rorachu watershed. This study represents the first comprehensive analysis of landslide risk in the populated areas of East Sikkim and along NH31A, offering a deeper understanding of the risks involved and contributing to the enhancement of local resilience against landslide hazards. A total of 153 different landslide locations were mapped using Google Earth and GIS software; 30% (46) of these locations were used to validate the models, and 70% of these (107) served as training data for the FR, IV, and CF models. The thirteen landslide causative factors (geology, soil, elevations, slope, curvature, drainage density (DD), road density (RD), rainfall, normalized difference vegetation index (NDVI), land use land cover (LULC), topographic position index (TPI), stream power index (SPI), and topographic wetness index (TWI)) were extracted from a spatial database for LSZ mapping. Landslides were most prevalent on slopes (35° to 50°), heights (2,500–4,100 m), and rainfall (2000–2,500 mm and 3,000–3,300 mm). The area under the curves (AUC) for the FR, IV, and CF models are 0.925 (92.50%), 0.846 (84.60%), and 0.868 (86.20%), respectively. The prediction rates are shown by the AUCs for the FR, IV, and CF models, which are 0.828 (82.8%), 0.750 (%), and 0.836 (83.60%), respectively. According to the landslide risk assessment (LRA), the FR (20.75%), IV (40.91%) and CF (18.78%) models showed high risk on Highway 31A, while the FR (9.05%), IV (38.59%) and CF (20.90%) models showed high risk in densely populated areas. These landslide risk and vulnerability maps can be used to develop land use planning strategies that can save lives and are useful for planners and mitigation measures. Special attention should be paid to urbanization, highway construction, and deforestation.

Physico-chemical Characterization and Taxonomic Classification of Soil Profiles in a Toposequence Located in RRTTS and KVK Farm, Keonjhar, Odisha, India

The study investigates the physico-chemical characteristics and taxonomic classification of soil profiles along a toposequence at the RRTTS and KVK farm, Keonjhar, Odisha. Three distinct land types - upland, medium land, and lowland - were selected for the study, representing varying topographic positions. The investigation focused on soil properties such as bulk density, particle density, pH, organic carbon content, electrical conductivity, cation exchange capacity (CEC), base saturation, and available macro and micronutrients. Results indicated that bulk and particle densities were lower in upper horizons and increased with depth, while soil pH exhibited an increasing trend with increasing depth, likely due to the movement of basic cations during intensive rainfall. Organic carbon content was higher in surface horizons and declined with depth, whereas available potassium increased with depth, attributed to parent material and clay content. The exchangeable cations, primarily calcium and magnesium, dominated the soil profiles. The soils were classified into Loamy-skeletal, mixed, hyperthermic Typic Ustorthents (Pedon 1), Fine-loamy, mixed, hyperthermic Udic Haplustalfs (Pedon 2), and Fine-loamy, mixed, hyperthermic Udic Paleustalfs (Pedon 3). The study concluded that different landforms within the toposequence require specific land-use planning and conservation measures to enhance soil productivity and sustainability. Upland areas are recommended for plantation and agroforestry, medium land for crop production, and low land for paddy cultivation and pisciculture. Tailored conservation strategies, including contour cultivation and water harvesting, are essential to mitigate soil erosion and optimize land use in the region.

Depth Wise Distribution of Soil Physico-Chemical Properties and Nutrients Across a Toposequence Located at KVK Farm, Sakhigopal, Odisha, India

This study aims to identify soil-related constraints for crop production and provide insights for soil management by analyzing soil profiles across different topographic positions (upland, medium land, and lowland) at KVK farm, Sakhigopal, Puri located in the East and Southeastern Coastal Plain Agro-Climatic Zone of Odisha. The profiles were evaluated for key physico-chemical properties and nutrient contents, revealing significant variations influenced by topography. The results showed that the soil's physical and chemical properties and available nutrient status showed distinct variations among the pedons. Among soil physical properties, the sand percentage, bulk density, and particle density increased with soil depth. Whereas, the clay percentage, total porosity, and water-holding capacity decreased with soil depth. Soil pH ranged from 6.32 to 7.50 and the electrical conductivity was recorded below 1 dSm-1. The organic carbon content ranged from 8.6 to 10.3 g kg-1. In general, soil pH, base saturation, and exchangeable cations increased with soil depth. On the other hand, soil organic carbon content and exchangeable acidity decreased with soil depth. Available nitrogen, phosphorus, potassium, and sulphur contents decreased with soil depth. However, in general, their concentrations increased along the slope (towards low land), which may be attributed to increased levels of organic carbon and clay contents in the lower topographic positions owing to high moisture content and higher cropping intensity. The findings of this study provide valuable insights regarding soil property characterisation across a transect for sustainable land use planning.

Flooding Hazard Vulnerability Assessment Using Remote Sensing Data and Geospatial Techniques: A Case Study from Mekkah Province, Saudi Arabia

Flash floods are catastrophic phenomena that pose a serious risk to coastal infrastructures, towns, villages, and cities. This study assesses the risk of flash floods in the ungauged Mekkah province region based on specific and effective morphometric and topographic features characterizing the study region. Shuttle Radar Topography Mission (SRTM) data were employed to construct a digital elevation model (DEM) for a detailed analysis, and the geographical information systems software 10.4 (GIS) was utilized to assess the linear, area, and relief aspects of the morphometric parameters. The ArcHydro tool was used to prepare the primary parameters, including the watershed border, flow accumulation, flow direction, flow length, and stream ordering. The study region’s flash flood hazard degrees were assessed using several morphometric characteristics that were measured, computed, and connected. Two different and effective methods were used to independently develop two models of flood vulnerability behaviors. The integrated method analysis revealed that most of the eastern and western parts of the studied province provide high levels of flood vulnerability. Due to it being one of the most helpful topographic indices, the integrated flood vulnerability final map was overlayed with the topographic position index (TPI). The integrated results aided in understanding the link between the general basins’ morphometric characteristics and their topographical features for mapping the different flood susceptibility locations over the entire studied province. Thus, this can be applied to investigate a surface-specific reduction plan against the impacts of flood hazards in the studied landscape.

Mitigating the extinction risk of globally threatened and endemic mountainous Orthoptera species: Parnassiana parnassica and Oropodisma parnassica

Abstract Orthoptera species are vulnerable to extinction on a global scale. Greece hosts 35% (380 species) of the European Orthoptera fauna with a high degree of endemic (37%) and threatened species (37%). We sampled 46 plots (100 m2) to investigate the distribution and ecological requirement of two Greek mountain endemic and red‐listed species: Parnassiana parnassica (Ramme, 1926; Orthoptera: Tettigoniidae; Critically Endangered [CR]) and Oropodisma parnassica (Scudder, 1897; Orthoptera: Caelifera; Endangered [EN]). Species had a restricted geographical range, with two isolated populations confined to high altitudes (1527–2320 m) of Mts. Parnassos and Elikonas. Species distribution models showed that slope affected their suitable habitat, together with the topographic position index and the annual temperature range (P. parnassica), and the amount of green vegetation and evapotranspiration (O. parnassica). Connectivity analysis showed that P. parnassica‐suitable habitat consisted of few larger and well‐connected patches (26 patches: effective mesh size of 1.57 km2) and that O. parnassica‐suitable habitat consisted of more but smaller and less connected patches (56 patches: effective mesh size of 0.3 km2). Generalised linear models showed that the population density of P. parnassica was negatively influenced by the height of herbaceous vegetation and that of O. parnassica was positively influenced by altitude. The species face three main imminent threats: land take, wildfires and global warming, whereas livestock grazing seems to have a positive impact and skiing a neutral impact on their populations. We assessed both species as EN after International Union for Conservation of Nature (IUCN) criteria and a suite of conservation measures are suggested for their status improvement.

Картографирование почв на основе аэрофотосъемки с БПЛА

The article presents the results of research on the creation of a detailed soil map (scale 1:2500) using the example of a land plot of the Federal State Budgetary Educational Institution of Higher Education Perm State Agrarian University. The purpose of the research is to improve the methodology of detailed soil mapping using an unmanned aerial vehicle (UAV) and methods of geoinformation analysis of aerial photographs. The total area of the plot is 13.4 hectares, on which a UAV survey was carried out on September 12, 2023, and a soil survey was carried out on a detailed scale from June 1 to 24, 2024. Soil mapping was carried out on the basis of field data and a digital elevation model created by photogrammetry methods based on UAV survey materials. The map creation process is automated by creating geoprocessing models in QGIS model builder. Based on the results of creating a detailed soil map, a conclusion was made about the close relationship of soils with characteristic relief elements, which are reflected in classes according to the topographic position index TPI. Keywords: UAV, GEOINFORMATIONAL MAPPING, SOIL MAP

Geospatial Modelling of Flood Susceptibility of the Calabar City, Cross River State, Nigeria

Flooding remains a major environmental problem in many parts of the world including Nigeria, causing untold losses. This study modelled the flood susceptibility of Calabar Metropolis using frequency ratio and geographical information system (GIS). Direct field observation and key informant approaches were used to obtain 127 previous and current flood locations in the study area from which a database of historical flood occurrence was developed. Using the geostatistical analyst tool within a geographical information environment the flood locations were split into two parts in the ratio of 70:30 percent for the training and testing processes, respectively. Eight flood conditioning factors (elevation, slope, aspect, curvature topographic position index, topographic wetness index, land cover and normalized difference vegetation index) were extracted from SRTM-30m DEM and Landsat 8 data accordingly and used in the geospatial analysis of flood occurrence within the GIS. The frequency ratio model was then developed using the training dataset. The final product was the flood susceptibility map of the study area. The results revealed that 9.3 percent of the study area was considered to have very high flood susceptibility, 19.97 percent was classified as high flood susceptibility while 31.79 percent was under moderate risk area. About 39 percent of the study area was classified at least under low flood susceptibility. The order of contribution of the conditioning factors to the model were topographic position index (TPI), elevation, normalized difference vegetation index (NDVI), land cover, curvature, aspect, slope, and topographic wetness index (TWI). The validation of the model using the receiver operating characteristics (ROC) curve returned an AUC value of 74.81 percent. Hence, the result was acceptable for the prediction of flood locations in the study area. The findings would assist urban planners, environmental managers, risk reduction and management agencies, land developers, policy makers, and indeed the general public.

Mining, farming, and diplomacy. Understanding the human landscape of Bronze Age Sardinia (Italy) through geospatial analysis

Human agency on landscape modification and land use is often seen in terms of socio-economic opportunities vs. natural constraints. In the study of prehistoric cultures this is both a strong source of information about sustenance strategies and community behaviours, and a subject potentially easy to analyse within a limited set of physical and social parameters. The recent advancements in the use of spatial analysis tools in landscape archaeology allow to obtain ever more precise models. However, studies that compare at the same time the geological landscape and social elements are very scarce. We used Point Pattern Analysis and Modelling to investigate megalithic structures (nuraghes) in Bronze Age southwestern Sardinia (Italy) and identify correlations between their spatial patterns and a set of covariates encompassing both environmental (i.e. topography and geological resources) and cultural factors. The models which best represent pattern distribution come from the combination of covariates from both groups.The models highlight a close distance from known ore deposits and show a clear dependence of Nuragic populations to ore extraction and metallurgy. The availability of fertile soils with moderate permeability and moderately low pH is also significant, as well as a preference to prominent locations with a positive correlation with the Topographic Position Index and the Convexity Index. From a cultural standpoint, we observed a consistent aggregation of simple nuraghes around complex nuraghes at mid-short distances. The occurrence of polycentric patterns can be explained either by the former emerging from the presence of the latter or vice versa, and is typically associated with a loosely stratified social structure devoid of strong hierarchies. These results underscore the efficacy of spatial analysis in disentangling and juxtaposing the physical and social factors influencing the distribution of past culture, and offer new insight on the development of Bronze Age societies in their geographical context.

Accuracy assessment of the geomorphon approach to detect ecological sites in the Dry Chaco region of Argentina

Ecological sites are a classification of local-land types based on differences in important environmental factors including soil properties, slope and landscape position within a geomorphologic and climatic zone. The concept is pivotal to conduct adaptative management in arid rangelands because it defines homogeneous areas over which specific soil-vegetation-disturbance dynamic occurs. Geomorphon is a computationally efficient method that uses Digital Elevation Models (DEMs) for the classification of landforms at multiple scales. The objective of this study was to evaluate the accuracy of the geomorphon approach to map ecological sites in a 11,259-ha study area within the Dry Chaco region of Argentina, utilizing local topographic positions along soil catena as a predictor of broader ecological sites classes. We used two DEM pixel resolutions (12.5 m and 30 m) and optimized the flatness threshold (t) and search radius (L) geomorphon parameters. As “ground truth” we used legacy data of 62 soil profiles descriptions. The geomorphon elements detected were reclassified into the three main ecological sites of the study area: highlands, midlands and lowlands. We used the overall disagreement (D) as the main metric for evaluating the accuracy of ecological site classifications. We found that: i) the lowest t value (0.05°) captured subtle topographical changes and thus more effectively reflected the soil-landscape relationship, and ii) larger L values paired with the lower pixel resolution (30 m) diminished the impact of minor landforms, improving the accuracy of ecological site detections. We determined that the geomorphon model with the pixel resolution of 30 m, t-value of 0.05°, and L-value of 12 produced the ecological site classification map with the highest accuracy, achieving a moderate-high accuracy (D of 33.9 %). Our study suggests that the geomorphon approach shows potential for consistent, reproducible and easily updatable ecological site mapping over larger areas.

Landscape positioning of Neolithic mustatil stone structures along the margins of the Nefud Desert, Saudi Arabia

Monumental rectangular stone structures called mustatils are an important emerging feature of the Holocene archaeological record of northwestern Arabia. To date, few have been excavated, with available radiocarbon dates suggesting an age range of ca. 5400–4200 BC. Here we present a rigorous spatial analysis to identify the patterning and landscape context of 169 mustatils in the southern and western margins of the Nefud Desert. This included: (1) a systematic survey of satellite imagery to identify mustatils; (2) viewshed analysis to examine location and landscape visibility; (3) a point process model to understand how diverse environmental and landscape variables affect mustatil locations; (4) mark correlation function to assess spatial patterning of mustatils based on their size. Results indicate that mustatil locations are determined most by proximity to water (likely locations of enhanced surface water occurrence under the enhanced humidity of the Mid-Holocene), on east facing slopes, close to rocky areas, at elevations between 880 and 950 masl, and on or near topographic ridges (positive topographic position index). Viewshed analysis showed that mustatils are preferentially located in areas that have good views, but not the best that are available, indicating complex landscape positioning that balances a range of topographic and behavioural factors. Using a rank permutation method with size (length) of mustatils as a proxy for labour mobilization we show that mustatils within clusters are not arranged hierarchically based on size, and were likely built by non-stratified groups of people. Our analyses show that people were choosing multiple factors when deciding where to build mustatils, and that the distribution of mustatils may relate to different groups of people resulting in the construction of complex ritual landscapes. As one of the earliest examples of large-scale monumental stone structure construction in global prehistory, understanding mustatils can enlighten us on human-environment interaction during the Neolithic.

Morphometry of the Mt Manengouba volcano: Insights into tephrostratigraphy of Eboga maars (South West Cameroon)

The GIS-based geomorphological and morphometric approaches were combined with field- and tephrostratigraphic analyses to reconstruct the history of the Mt Manengouba volcano including the Eboga maars in the southwestern part of the Cameroon Volcanic Line (CVL). The elevation, slope, relative relief, topographic position and terrain ruggedness indexes from the Digital Elevation Model (DEM, 12.5 m) were determined to constrain two main geomorphic units corresponding to the Elengoum and Eboga nested stratovolcanoes which were affected by differential erosional processes. The studied grain size, shape, vesicularity, structure, degree of lithification, sorting, thickness, grading patterns, sedimentary features, spatial distribution revealed three tephrostratigraphic units: U1 (U1-1, lithic and juvenile; U1-2 dominantly juvenile), U2 (U2-1 ash- and juvenile rich-deposits; U2-2, juvenile-scoria with few lithic) and U3 (scoria cone deposits). The total volume of ∼0.199 km3 of tephra deposits ranges the Eboga maars volcanoes within the small-volume monogenetic types. These results revealed dry/wet phreatomagmatism and strombolian activity as a contribution to the seven phases-eruptive history of the Mt Manengouba volcano: the pre-Manengouba; emplacement of Elengoum stratovolcano; collapse of Elengoum summit and formation of Elengoum caldera; emplacement of Eboga stratovolcano; the collapse of Eboga summit and formation of Eboga caldera; a phreatomagmatic phase and emplacement of Female and Male maars ending with an explosive stage associated with the formation of scoria and parasitic cones.

Investigation of the Relationship between Topographic and Forest Stand Characteristics Using Aerial Laser Scanning and Field Survey Data

The article thoroughly investigates the relationships between terrain features and tree measurements derived from aerial laser scanning (ALS) data and field surveys in a 1067-hectare forested area. A digital elevation model (DEM) was generated from ALS data, which was then used to derive additional layers such as slope, aspect, topographic position index (TPI), and landforms. The authors developed a mathematical procedure to determine the radii for the topographic position index. The canopy height model was created, and individual trees were segmented using a novel voxel aggregation method, allowing for the calculation of tree height and crown size. Accuracy assessments were conducted between ALS-derived data and field-collected data. Terrain variability within each forest unit was evaluated using characteristics such as standard deviation, entropy, and frequency. The relationships between tree height and the derived topographic features within forest subcompartments, as well as the correlation between the height yield map for the entire area and the TPI layer, were analysed. The authors found strong correlation between the topographic position index and tree heights in both cases. The presented remote-sensing-based methodology and the results can be effectively used in digital forest site mapping, complemented by field sampling and laboratory soil analyses, and, as final goal, in carbon stock assessment.

Control of landscape position on organic matter decomposition via soil moisture during a wet summer

Sustainable cropland management requires preservation of soil organic matter (SOM). In spite of in depth understanding gained from ample field and laboratory studies, we have a poor understanding of landscape scale spatial variation of fresh organic matter (OM) decomposition and its conversion into soil organic carbon (SOC). Particularly, local topographic position may be expected to co-control these processes via soil hydrology. In this study, we sought to identify if such control is significant by setting up a field experiment with two contrasting positions across 10 gently sloping cropland fields covering three different soil texture groups, i.e. loamy sand, (sandy) loam and silt loam. We wanted to link OM decomposition to within-field differences in soil moisture, whilst keeping variation in other soil and management factors minimal. Specifically, mesocosms with 13C enriched ryegrass (the OM source) were incorporated in the fields for ten weeks and afterwards, soil was separated into > 500 µm, 53 – 500 µm and < 53 µm sized fractions. Overall, we found that lower located positions were wetter than higher positions with average differences of 11 %, 20 % and 16 % in water-filled pore space for the loamy sand, (sandy) loam and silt loam soil, respectively. Mineralization of added OM was surprisingly independent of landscape position, even though moisture conditions appeared wetter than optimal at the low but not at the high landscape positions. Remaining ryegrass residues > 500 µm did follow local topography-driven gradients in soil moisture with higher amounts in low landscape positions. In other words, drier conditions at high landscape positions improved coarse OM decomposition, with consequently more ryegrass-carbon (C) ending up in finer soil fractions (< 500 µm). Additionally, soil texture affected decomposition of the smallest fraction (< 53 µm) with a stabilizing effect for finer-textured (silt loam) soils. We conclude that, despite significant contrasts in moisture conditions between landscape positions, within-field spatial variability of OM mineralization was overall limited during the observed wet summer period. Nevertheless, landscape position affected the quality of remnant unmineralized C, with relatively more conversion of freshly added OM into OM associated with silt and clay at the drier higher positions, potentially improving the long-term stability of SOM. Likewise observations under different weather conditions are needed to evaluate the necessity of precise modelling of local soil hydrology for predicting SOC stock evolution on the landscape scale.

Unveiling Wheat’s Future Amidst Climate Change in the Central Ethiopia Region

Quantifying how climatic change affects wheat production, and accurately predicting its potential distributions in the face of future climate, are highly important for ensuring food security in Ethiopia. This study leverages advanced machine learning algorithms including Random Forest, Maxent, Boosted Regression Tree, and Generalised Linear Model alongside an ensemble approach to accurately predict shifts in wheat habitat suitability in the Central Ethiopia Region over the upcoming decades. An extensive dataset consisting of 19 bioclimatic variables (Bio1–Bio19), elevation, solar radiation, and topographic positioning index was refined by excluding collinear predictors to increase model accuracy. The analysis revealed that the precipitation of the wettest month, minimum temperature of the coldest month, temperature seasonality, and precipitation of the coldest quarter are the most influential factors, which collectively account for a significant proportion of habitat suitability changes. The future projections revealed that up to 100% of the regions currently classified as moderately or highly suitable for wheat could become unsuitable by 2050, 2070, and 2090, illustrating a dramatic potential decline in wheat production. Generally, the future of wheat cultivation will depend heavily on developing varieties that can thrive under altered conditions; thus, immediate and informed action is needed to safeguard the food security of the region.