Topographic Position Research Articles

Consistent response to topographical variation in net assimilation rate across the central Himalayan broadleaved forests

In a mountainous landscape, vegetation patterns are influenced by the interaction of slope aspect and topographical positions. Here, we have examined the effect of two contrasting aspects (North and South) and three slope positions (Hill Base, Mid Slope and Hill Top) on net assimilation rate (NAR) of trees across four forest sites of the monsoonal Central Himalaya between 400 and 2300 m elevations. The study species, namely Shorea robusta, Quercus leucotrichophora, and Q. floribunda were broadleaved evergreen with concentrated summer leaf drop and simultaneous leafing. The NAR of these broadleaved species was measured in five seasons (pre-monsoon, monsoon, autumn, winter and spring) diurnally at their respective forest sites. In each of the forest site the dominant species was the same, on both aspects and the three slope positions. We also analyzed topographical associated effect of tree water relations on NAR, using the data of an earlier study on these species. The average NAR (μ mol m−2 s−1) across the four forest sites and five seasons, (measured diurnally) was higher on the north (5.08 ± 0.23) slope aspect than south aspect (4.61 ± 0.22; average of 120 NAR values for each aspect), and among the three slope positions, it was higher on hill base (5.13 ± 0.29), than on mid-slope (4.80 ± 0.27) and hill top (4.61 ± 0.26; average of 80 NAR values for each position). These patterns in NAR values in relation to slope aspects and slope positions were also found separately for each of the species, and each of the seasons. The NAR varied across the sites, seasons and day time from 2.84 to 11.99 μ mol m−2 s−1, largely because of the variation in tree water potential and leaf phenological changes. To conclude, the NAR shows a consistency in responses to differences in slope aspects and slope positions across the forests ranging from tropical to warm temperate type. The study would help generalizing topographical effects on tree growth.

Dynamic Plant–Herbivore Interactions between Bison Space Use and Vegetation Heterogeneity in a Tallgrass Prairie

Investigations into plant–herbivore interactions are of importance for understanding grassland ecosystem dynamics. Our research quantified the effects of vegetation heterogeneity at a patch scale of 30 m on bison space use in a tallgrass prairie through the analyses of the resource utilization function. In addition, we assessed the vegetation heterogeneity associated with bison locations by comparing the patch-scale vegetation characteristics between areas with high and low bison space use through Mann–Whitney U tests. Furthermore, we simulated the interactions between bison and vegetation patches (2 × 2 m) during the early growing season for the lowland topographic positions using agent-based modeling (ABM) as a preliminary study of linking bison foraging site selection with vegetation responses to bison grazing dynamically. The bison grazing strategy in the ABM of the grassland system was adjusted to ensure consistency in the vegetation pattern variations related to bison space use between the simulation and the empirical on-the-ground observations. The results indicated the following: (1) The effects of the patch-scale vegetation heterogeneity on the bison foraging site selection varied across the seasons, which were most evident in the middle of the growing season. (2) A relatively high level of bison space use generally resulted in diverse grassland canopies with high variability and interspersion. (3) From the ABM of the grassland system, it can be implied that bison select patches with high quality and quantity at the beginning of the growing season; as the vegetation quality and quantity improve overall, the bison graze randomly. This pattern was confirmed by observations of the bison foraging site selection in our study site. The ABM proved to be valuable in exploring and elucidating the underlying mechanisms of the grassland dynamics with a native North American grazer.

Topography drives tree–habitat association and functional and phylogenetic structure in the northernmost tropical dry forest of the Americas

ABSTRACT Background Plant species composition and structural attributes are related to physiographic factors such as slope orientation and topographic position. This relationship is accentuated with increasing seasonality in temperature and precipitation. Aims We quantified the relationship between topography and the taxonomic, functional and phylogenetic community composition of woody species at the northernmost distribution of seasonally dry tropical forests (STDF) in the Americas. Methods We related slope orientation (north-facing vs. south-facing) and position (upper slope vs. lower slope) to the distribution of species, assessed their habitat preference by life stage (juvenile vs. adult) and compared the observed phylogenetic distance of species against random species assemblages. Results Our results showed the segregation of two species groups in both life stages is related to slope orientation, but not to topographic position. We found a strong habitat association for 68% of the species with both juveniles and adults similarly associated with the same habitat. Slope orientation was related to taxonomic, functional and phylogenetic structure, but it differed in the two life stages. Conclusions The functional and evolutionary segregation of species between north-facing vs. south-facing habitats indicates that species are non-randomly distributed; suggesting that deterministic mechanisms (e.g. topographic habitat specialisation) are operating at a local scale.

Factors and processes controlling hydrochemistry and evaporitic deposits in hypersaline wetland‐shallow lake systems

AbstractThree wetland‐shallow lakes were studied with the aim of analysing the processes and factors that control hydrochemistry and evaporite deposits in them in basins of the Pampean Plain, Argentina. In this sense, water balances and analysis of the water content of the lakes with normalized water difference index were made, and geologic‐geomorphological characteristics and groundwater flows were defined. Groundwater, surface water and evaporite samples were taken, along with sediment samples from wetland‐shallow lakes and surroundings. In situ pH, electrical conductivity and temperature, and laboratory chemical determinations of major ions of the water were measured. x‐ray diffraction (XRD) and scanning electron microscope (SEM)‐energy dispersive spectroscopy (EDS) analyses of evaporite and sediment samples were carried out. The results obtained allow the identification of two different systems. One of them is represented by Leubucó wetland‐lake basin, which is topographically higher and smaller than the other system, with Na‐HCO3 and Na‐Cl/SO4 groundwater inflows, with high concentrations of Ca2+ and Mg2+. In periods of high evaporation, the regional water table drops, and due to its topographic position, the lake dries. These determine the formation of thick layers of halite associated with magnesium salts on surface, and gypsum layers interbedded with clastic sediments. The other system involves de la Sal and Chasilauquen wetland‐lake basins, which have larger extensions. They receive Na‐HCO3 and Na‐Cl/SO4 groundwater inflow, but with low Mg2+ and Ca2+. Their lower topographic position determines that even during deficit periods, the water table intercepts the lakes surface and therefore, lakes have a shallow surface water level almost all the year, which is hypersaline, Na‐Cl type. These systems only have thin evaporite crusts, composed of halite and thenardite at the edges of the lakes, and the formation of Ca‐Mg sulfates is not observed. It is concluded that topographic position, basins size, geology, groundwater inflow and evaporation are the main processes and factors controlling hydrochemistry and evaporitic deposits.

Assessment of Groundwater Potential in a Mountainous Area Using Machine Learning and GIS, Rherhaya Basin, High Atlas, Morocco

Mountainous regions are vital for recharging aquifers in plain areas downstream, but understanding the geological, hydrogeological, and climatic factors is crucial to comprehend groundwater processes in these regions. Several parameters, including lithology, topography, secondary porosity, geological structures, and climatic conditions, affect the potential of groundwater in mountainous aquifers. Traditional groundwater modeling tools face several challenges in handling large amounts of real-time data, such as extracting useful features, quantifying uncertainty, and identifying links between different variables. Recent technological advances in artificial intelligence, particularly machine learning, provide solutions for hydrogeological research and applications. This paper focuses on modeling potential zones of groundwater sources using various methodologies based on GIS, spatial remote sensing, and machine learning. The study evaluated three models, Random Forest, Support Vector Machine, and Logistic Regression, in identifying potential groundwater zones in the Rherhaya watershed. More than 200 localized spring points were needed to ensure efficient model learning. The Support Vector Machine model demonstrated the highest performance during the 70/30% split, with a ROC-AUC of 84.4% for the test data. The study identified four critical conditioning factors of groundwater potentiality, including Topographic position index, River Distance, Valley Depth, and Plane Curvature. The models also highlighted the distance to rivers as a significant factor, particularly in the upstream portion of the watershed. The very low potentiality class occupied the largest area (over 32%), followed by low (between 24 and 29%), moderate (12–19%), high (10–14%), and very high (only 9–12%) classes. Only the Support Vector Machine model predicted that 12% of the catchment area had high potential for groundwater resources, indicating its superior performance in identifying high-potential zones. The results offer valuable insights that can aid decision-makers in effectively managing water resources in vulnerable areas.

Effects of microtopography on within-field spatial variation of inherent soil properties in Andosols of Tokachi district, Hokkaido

ABSTRACT In large-scale upland cropping systems, understanding the magnitude of soil property variations and mapping the distribution are essential to improve soil nutrient management. The Tokachi district of Hokkaido has large-scale upland fields, and the soils are dominated by Andosols that inherently have characteristic clay minerals and high soil organic carbon content. In the region, microtopography is known to exist that can affect soil formation and within-field variation of the inherent soil properties. However, limited information exists about the relationship between microtopography and the spatial variation of inherent soil properties that are important for nutrient dynamics. Therefore, this study aimed to assess the effect of microtopography on the within-field variation of inherent soil properties in Andosols of Tokachi district, Hokkaido. Within a 6.6-ha field with an elevation difference of 3.2 m, four soil profiles were surveyed at different topographical positions, and 530 surface soil samples were collected at 12-m intervals. Samples were analyzed for total carbon (TC), acid-oxalate extractable Al, Fe, and Si (Alo, Feo, and Sio), pyrophosphate extractable Al and Fe (Alp and Fep), cation exchange capacity (CEC), and phosphate absorption coefficient (PAC). Geostatistical analysis was applied to understand the spatial structure of the surface soil properties. All soil profiles were dominated by volcanic parent materials, and they were classified into different types of Andosols. An exceptional variation of inherent soil properties was found in the surface soil, with TC content ranging from 35.2 to 124 g kg−1 and CEC from 20.3 to 55.7 cmolc kg−1. Geostatistical analysis showed that TC content varied over a large distance (range: 226 m) while allophane content varied at a shorter distance (range: 118 m). Our findings revealed that microtopography affected the soil water dynamics and erosion of the surface soil particles which caused the variation of TC, CEC, and allophane. Further studies must be conducted to understand the effects of the variation of these inherent soil properties on soil nutrient availability and crop productivity.

Spatial prediction of groundwater potential by various novel boosting-based ensemble learning models in mountainous areas

This study makes a significant contribution to the field of groundwater potential mapping (GWPM) by exploring the application of ensemble learning models (ELMs), specifically boosting ensemble models (BEMs), which have not been fully utilized in GWPM. By employing six ELMs (random forest, AdaBoost, XGBoost, CatBoost, GBDT and LightGBM), along with Tree-structured Parzen Estimator in Luoning County, China, this study identifies key indicators (topographic position index, distance to rivers and topographic wetness index) and demonstrates the superior model performance of XGBoost compared to other ELMs. Additionally, correlation analysis confirms the accuracy of XGBoost in predicting relationships between important indicators and groundwater potentials. Finally, the findings provide valuable insights for sustainable groundwater management strategies in Luoning County and emphasize the need for further exploration of ELMs, development of comprehensive performance evaluation and indicator systems, reduction of the inconsistencies between indicators and predication results and practical research to support future sustainable groundwater management.

Rainfall and topographic position determine tree embolism resistance in Amazônia and Cerrado sites

Droughts are predicted to increase in both frequency and intensity by the end of the 21st century, but ecosystem response is not expected to be uniform across landscapes. Here we assess the importance of the hill-to-valley hydrologic gradient in shaping vegetation embolism resistance under different rainfall regimes using hydraulic functional traits. We demonstrate that rainfall and hydrology modulate together the embolism resistance of tree species in different sites and topographic positions. Although buffered by stable access to groundwater, valley plants are intrinsically more vulnerable to drought-induced embolism than those on hills. In all study sites, the variability in resistance to embolism is higher on hills than on valleys, suggesting that the diversity of strategies to cope with drought is more important for tree communities on hills. When comparing our results with previously published data across the tropics, we show greater variability at the local scale than previously reported. Our results reinforce the urgent need to extend sampling efforts across rainfall regimes and topographic positions to improve the characterization of ecosystem resistance to drought at finer spatial scales.

Local Topography Has Significant Impact on Dendroclimatic Response of Picea jezoensis and Determines Variation of Factors Limiting Its Radial Growth in the Southern Sikhote-Alin

Climate change significantly influences forest communities, even leading to their complete transformation. In the case of boreal and temperate forests, it is particularly important to understand how dominant tree species respond to climate changes, as they largely determine the structure of forest communities. In this study, we focus on the Jezo spruce (Picea jezoensis (Siebold & Zucc.) Carriere), which is widespread in Northeast Asia. We investigated the climate parameters affecting the radial growth of Jezo spruce and how their influence changes along environmental gradients. For the research, 500 tree cores were collected from 10 sites located at elevations ranging from 460 to 1060 m. We found a negative response of Jezo spruce radial growth to precipitation in July–August and SPEI in July of the current year, maximum temperatures in July–August and November of the previous year. On the other hand, we observed a positive response to the maximum temperatures in January of the current year. Furthermore, we established that the influence of these climatic parameters depends on local topography, with 74.3% of the variance in response values being explained by elevation, slope, and the Topographic Position Index. The results obtained demonstrate that the reaction of Jezo spruce radial growth to climate change will be complex, and the balance between negative and positive effects will depend significantly on local topography.

Spatial Prediction of Landslide Susceptibility Using Logistic Regression (LR), Functional Trees (FTs), and Random Subspace Functional Trees (RSFTs) for Pengyang County, China

Landslides pose significant and serious geological threat disasters worldwide, threatening human lives and property; China is particularly susceptible to these disasters. This paper focuses on Pengyang County, which is situated in the Ningxia Hui Autonomous Region of China, an area prone to landslides. This study investigated the application of machine learning techniques for analyzing landslide susceptibility. To construct and validate the model, we initially compiled a landslide inventory comprising 972 historical landslides and an equivalent number of non-landslide sites (Data sourced from the Pengyang County Department of Natural Resources). To ensure an impartial evaluation, both the landslide and non-landslide datasets were randomly divided into two sets using a 70/30 ratio. Next, we extracted 15 landslide conditioning factors, including the slope angle, elevation, profile curvature, plan curvature, slope aspect, TWI (topographic wetness index), TPI (topographic position index), distance to roads and rivers, NDVI (normalized difference vegetation index), rainfall, land use, lithology, SPI (stream power index), and STI (sediment transport index), from the spatial database. Subsequently, a correlation analysis between the conditioning factors and landslide occurrences was conducted using the certainty factor (CF) method. Three landslide models were established by employing logistic regression (LR), functional trees (FTs), and random subspace functional trees (RSFTs) algorithms. The landslide susceptibility map was categorized into five levels: very low, low, medium, high, and very high susceptibility. Finally, the predictive capability of the three algorithms was assessed using the area under the receiver operating characteristic curve (AUC). The better the prediction, the higher the AUC value. The results indicate that all three models are predictive and practical, with only minor discrepancies in accuracy. The integrated model (RSFT) displayed the highest predictive performance, achieving an AUC value of 0.844 for the training dataset and 0.837 for the validation dataset. This was followed by the LR model (0.811 for the training dataset and 0.814 for the validation dataset) and the FT model (0.776 for the training dataset and 0.760 for the validation dataset). The proposed methods and resulting landslide susceptibility map can assist researchers and local authorities in making informed decisions for future geohazard prevention and mitigation. Furthermore, they will prove valuable and be useful for other regions with similar geological characteristics features.

Relationship Between Lightning Activity and Terrain in High-Altitude Mountainous Areas

In China, the average elevation of Yunnan Province exceeds 2000 m, with a greatly fluctuating terrain. Most areas have a high-altitude mountainous terrain and relatively high ground lightning activity. Topography is one of the most critical factors affecting regional lightning characteristics. Therefore, clarifying the quantitative relationship between cloud-to-ground lightning activity and topography can help evaluate the risk of hazard-pregnant environments and adopt active protective measures. In this study, we used a mathematical statistical method to analyze the correlation between cloud-to-ground lightning density and altitude, slope, slope aspect, topographic position index, and land-cover type in Yunnan for the past 10 years. We also used the Apriori algorithm to study the coupling effects of different topographic factors and mine the topographic attribute sets that strongly correlate with high-level lightning activity. We used the entropy weight method to construct a comprehensive index of hazard-pregnant environments and quantitatively evaluate the impact weights of different factors on cloud-to-ground lightning activity. Correlation analysis of lightning density and sensitivity indicated a correlation coefficient of 0.473 between both factors, highlighting the effectiveness of evaluating regional lightning risk with the sensitivity of a hazard-pregnant environment

Типология и генезис циркульных знаков петроглифов Кайракколь и Аксу

Петроглифы Кайракколь и Аксу входят в группу памятников археологического комплекса Таусамалы, расположенного в Аксуском районе Жетысуской области. В составе комплекса зафиксированы три могильника и поселение раннего железного века, одиночные и небольшие группы курганов, которые предварительно датированы эпохой Средневековья, и скопления разновременных петроглифов. Памятники занимают территорию от окраин поселка Таусамалы и восточных склонов гор Каракунгей довосточной оконечности плато Суук в горах Кайракколь. Исследование комплекса началось в 2019 году с аварийных раскопок сотрудниками ТОО «Археологическая экспедиция» на кургане, содержащем погребение пазырыкского типа, впоследствии включенном в состав крупного могильника Таусамалы. Уникальные материалы, полученные в ходе этой работы, позволили продолжить изучение памятника.С 2020 года ТОО «Археологическая экспедиция» и Жетысуское областное управление по охране и использованию историко-культурного наследия проводят совместные и планомерные исследования на вновь обнаруженном могильнике и в его окрестностях. В 2022 году на археологическом комплексе приступил к работе таусамальский отряд Института археологии им. А.Х. Маргулана. В результате проведенной археологической разведки выявлены новые памятники, скопления петроглифов, среди которых отмечается коллекция циркульных знаков. Полученные в 2022 году данные позволили успешно выполнить первоначальную попытку их систематизации. Публикуемая коллекция включает 25 циркульных знаков с пяти крупных скоплений петроглифов. В работе учтены характеристики как самих изображений, так и их пространственное и топографическое положение. На основе выделенных параметров построена первичная типология и осуществлена попытка анализа генезиса циркульных изображений. Составлены визуализированные комбинации исходных и производных групп изображений. В результате проведенного исследования знаки разделены на два основных вида — собственно циркульные и очковидные наскальные изображения. Каждый вид изображений с учетом фиксируемых характеристик разбит на три группы. В список выделенных циркульных знаков входят изображения зам

Spatiotemporal Variation of Anticyclonic Eddies in the South China Sea during 1993–2019

Based on the absolute dynamic topography data from the Copernicus Marine Environment Monitoring Service, this paper applies the Topographic Position Index to develop a new approach for mapping the anticyclonic eddies in the South China Sea (SCS). The results show that anticyclonic eddies are active in the deep basin of SCS, and the five selected parameters (number or frequency, lifetime, kinetic energy, amplitude, and area or radius) of anticyclonic eddies have a similar temporal variation and a similar spatial distribution pattern. (1) As for monthly variations, anticyclonic eddies are active in late spring and most active in summer. (2) The El Niño–Southern Oscillation had a stronger impact on the inter-annual variations of anticyclonic eddies in the SCS before 2013, resulting in a significant transition of inter-annual variations of these five parameters in around 2004. After 2013, most of these five parameters had a minimum in 2015 and a maximum in 2017. (3) Analyses show that the eddy activities in the SCS are significantly influenced by the monsoon wind and the western boundary current like Kuroshio. Therefore, the areas southwest of Taiwan Island and east of Vietnam are the two areas where the anticyclonic eddies are most active, with much larger eddy kinetic energy and much higher eddy amplitude.

Cadmium contamination in cacao farms of Piura, North Peru: A comprehensive assessment of geogenic and anthropogenic sources and implications for future production

Cadmium (Cd) is a heavy metal that poses a threat to food safety via the ingestion of food products with Cd. The uptake of Cd by the cacao tree (Theobroma cacao) has gained attention after the European Union set limits for Cd in chocolate products, the main commodity produced from cacao beans. In this study, we analyzed levels of Cd in soils and plant tissues across five cacao farms in the Piura region of Peru to identify the origins of Cd accumulation, and the natural and human factors controlling its concentration. Our results show that Cd levels varied in the order: leaves (1.25 mg kg−1) > beans (0.78 mg kg−1) > soils at 5 cm (0.68 mg kg−1) > soils at 20 cm (0.6 mg kg−1). Our findings suggest that the higher concentration of Cd in plant tissues and surface soils can be explained by readily available Cd from fertilizers and a litter layer being absorbed, cycled, and accumulated by the plant. Moreover, even when fertilizers are within regulatory limits, their continuous application, combined with the biocycling of Cd, may lead to high Cd concentrations in beans and leaves. Conversely, farms on alluvial soils and more stable topographic positions display higher soil and plant Cd concentrations. Likewise, farms located at lower altitudes, with higher contributing areas are more likely to receive Cd transported through sediments and water in the river network. Our results also suggest that variations in the underlying geology and soil mineralogy may be a source of potentially Cd bearing sediments. Overall, this study indicates that the high levels of Cd in plants in the study area are the result of a combined mechanism involving plant bioaccumulation and high Cd in fertilizers for the most part, with a minor contribution from potential Cd bearing minerals in sediments of alluvial soils.

Multiscale influences on Elk (Cervus canadensis) calving site selection across a fragmented Appalachian landscape

Abstract Due to the vulnerability of neonatal ungulates, selection of a birth site can have important implications for offspring survival and thus fitness of the mother. We studied parturition site selection in cow Elk in southeastern Kentucky, United States, using a use–availability framework to evaluate the effects of landscape variables sampled at multiple spatial grains on the relative probability of use of parturition sites. We identified 81 Elk parturition sites during May–Aug 2020–2022 and fit several candidate resource selection function models using a sample of 24,314 random locations to characterize habitat availability. Using an information-theoretic approach to rank candidate models, we identified two top-performing models (cumulative ωi = 0.97), which indicated that at fine spatial grains (~10- and 30-m pixels) parturient cow Elk selected for intermediate canopy cover and lower terrain ruggedness compared to available locations. At coarse grains (250–1,000-m buffers/neighborhoods), Elk selected against vegetation greenness/biomass, for higher topographic positions, for closer proximity to major roads, and with higher solar radiation potential. We also found evidence that Elk responded positively to forest/open edge densities at coarse grains, demonstrating that calving habitat throughout the Kentucky Elk Restoration Zone is associated with heterogeneous landscapes resulting from surface mine reclamation. As a result, habitat management actions should aim to increase patchy, early successional shrub cover on gentle topography.

Land Use Change and Landscape Ecological Risk Assessment Based on Terrain Gradients in Yuanmou Basin

Investigating the distribution characteristics of landscape ecological risk (LER) on terrain gradients is of great significance for optimizing the landscape pattern of ecologically vulnerable areas in mountainous regions and maintaining the sustainable development of the ecological environment. The Yuanmou Basin is a typical ecologically vulnerable area in the southwestern mountainous region of China, where issues such as soil erosion are pronounced, becoming one of the main factors restricting regional economic development. This study selected the Yuanmou Basin as the study area, and, using land use data from 2000, 2010, and 2020, constructed an LER assessment model based on disturbance and vulnerability. By integrating elevation and topographic position index data, we examined the spatiotemporal evolution characteristics of LER under different terrain gradients. The LER assessment results are summarized as follows: (1) From 2000 to 2020, the land use types of the Yuanmou Basin were mainly grassland, forest land and cropland. The land use showed a sharp increase in the cropland area and a simultaneous decrease in the grassland area, indicating a main land use evolution direction from grassland to cropland. (2) Over the span of 20 years, the average landscape ecological risk in the Yuanmou Basin slightly increased, specifically manifesting as a significant reduction in low ecological risk areas, while areas of medium and slightly lower ecological risks saw an increase. (3) The spatial distribution of LER in the Yuanmou Basin presents a pattern of being low on the periphery and high in the center, with significant positive spatial correlation, obvious spatial aggregation, as well as “high-high” and “low-low” clustering. (4) Low- and lower-risk areas in the Yuanmou Basin are distributed in the non-arid thermal zone and the medium–high terrain zone, while areas of medium, higher and high risk levels are mainly distributed in the arid thermal zone and the low terrain zone. The research results provide a scientific basis for optimizing and developing the land resources of the Yuanmou Basin.

Mine soil properties as influenced by tree species and topography of the re-vegetated coal mine overburden dump

Re-vegetation or natural succession of plant species is an important factor of soil development in postmining overburden dumps. As the parent material (sedimentary rocks and regolith) is more or less uniform in the dump, the topographic position and vegetation are the major factors that affects the mine soil quality. Accordingly, this study was designed for a relative evaluation of the influence of dump topographical position (crest, backslope, toeslope) and tree species (Azadirachta indica, Cassia siamea, and Leucaena leucocephala) on soil quality. Trees growing on the toeslope of the dump were significantly taller with larger diameter at breast height than those at backslope or crest. Soil moisture, pH, total S, available P, and Fe content were significantly (P < 0.05) affected by topographical position of the dump. All these properties were higher in the toeslope, except S in the crest. Tree species affected all the soil properties, except electrical conductivity and Mn. Organic carbon content was significantly lower for the nitrogen fixer L. leucocephala (2.03 %) than A. indica (3.30 %) or C. siamea (3.39 %). Soil dehydrogenase activity (39.79 mg TPF/24hr/kg) and microbial biomass carbon (286 µg/g) was higher under L. leucocephala, and C. siamea, respectively. Based on redundancy analysis (RDA), 87.5 % of the data variation is explained by the tree species, whereas, only 12.5 % by the topography. Principal component analysis revealed that C. siamea contributes significantly for the variation in soil properties of the dump. Re-vegetated plant species are a dominant factor of soil development in post mining dump than the topographical position. C siamea and the toeslope are closely associated with soil microbial biomass carbon. It is recommended to plant C. siamea with relatively higher planting density in crest and backslope than toeslope of the dump.

THE EXPLAINABILITY OF GRADIENT-BOOSTED DECISION TREES FOR DIGITAL ELEVATION MODEL (DEM) ERROR PREDICTION

Abstract. Gradient boosted decision trees (GBDTs) have repeatedly outperformed several machine learning and deep learning algorithms in competitive data science. However, the explainability of GBDT predictions especially with earth observation data is still an open issue requiring more focus by researchers. In this study, we investigate the explainability of Bayesian-optimised GBDT algorithms for modelling and prediction of the vertical error in Copernicus GLO-30 digital elevation model (DEM). Three GBDT algorithms are investigated (extreme gradient boosting - XGBoost, light boosting machine – LightGBM, and categorical boosting – CatBoost), and SHapley Additive exPlanations (SHAP) are adopted for the explainability analysis. The assessment sites are selected from urban/industrial and mountainous landscapes in Cape Town, South Africa. Training datasets are comprised of eleven predictor variables which are known influencers of elevation error: elevation, slope, aspect, surface roughness, topographic position index, terrain ruggedness index, terrain surface texture, vector roughness measure, forest cover, bare ground cover, and urban footprints. The target variable (elevation error) was calculated with respect to accurate airborne LiDAR. After model training and testing, the GBDTs were applied for predicting the elevation error at model implementation sites. The SHAP plots showed varying levels of emphasis on the parameters depending on the land cover and terrain. For example, in the urban area, the influence of vector ruggedness measure surpassed that of first-order derivatives such as slope and aspect. Thus, it is recommended that machine learning modelling procedures and workflows incorporate model explainability to ensure robust interpretation and understanding of model predictions by both technical and non-technical users.

Water-dispersible colloids distribution along an alluvial fan transect in hyper-arid Atacama Desert

As located in one of the oldest and driest deserts on Earth, soils in the Atacama Desert are greatly affected by atmospheric dust deposited on soil surface and the related fate of water-dispersible colloids (WDCs, <300 nm). We hypothesize that formation and content of these WDCs change with topography and age of natural soils. To highlight the processes involved, we investigated a mid-sized and gently (∼5°) sloping alluvial fan system of multi-phase evolution at 1480 m a.s.l. in the Paposo region of the hyper-arid Atacama Desert, which is considered typical for this part of the Coastal Cordillera. Sampling was done along a topographic transect in 11 pits, and assessed the distribution and composition of WDCs by means of asymmetric flow field-flow fractionation (AF4). The younger fan section (optically stimulated luminescence (OSL)-age of ∼13.6 ka) exhibited a pronounced surface roughness and steep slopes. Here, WDCs from the top soils (0–1 cm) free of plants contained nearly 54 ± 7% of medium-sized colloids (MCs, 210–300 nm) with a dominance of Si and Al. The elevated concentrations of fine colloids (FC, 24–210 nm) and particularly nanocolloids (NCs, 0.6–24 nm) was shown in levelled surface soils near shrubs with predominance of organic carbon (OC) and Ca. With higher collodial OC and Ca content in soils near shrubs, more WDC-P was formed concomitantly through increased OC-Ca-P associations. Larger variations in total WDC content were detected in the surface soils of the older fan section, which was dated to ∼56.4 ka. Here, the peaking NC had almost disappeared and thus MC dominated, probably reflecting re-aggregation and wind erosion over longer periods of time across a relatively smooth land surface. The WDCs and WDC-P peaked at 5–10 cm depth in the older fan section, as here a solid mineral/salt layer was present, while in the younger fan section the WDCs were more likely to be translocated from ‘permeable’ surface into deeper layers, likely reflecting leaching with occasional heavy rainfall. Overall, forms and distribution of WDCs depended on both topographic position and sediment age, thus making colloids as unique tracers of soil development processes during myriad or more years.

Predictive spatial analysis for a critical assessment of the preservation potential of Palaeolithic record in the Leiria region (central Portugal)

Predictive spatial analysis in archaeology refers to the use of geostatistical and computational techniques to assess the relationships between the distribution of archaeological sites and the environmental context. It is increasingly becoming an essential tool in scientific-academic research and rescue archaeology. In the interconnection between these two working contexts, this study aims to explore the advantages of applying an inductive approach, combining Geographical Information Systems (GIS) and geostatistical methods, to identify areas with different degrees of probability for the preservation of the Palaeolithic record in the lower valley of the Lis River (Leiria region, central Portugal). Topographic, hydrographic, geological, and geomorphological data were collected, processed, and integrated into a spatial database, using a GIS, to define the environmental conditioning factors. After applying a spatial multicollinearity procedure, slope, topographical position index, cost-weighted distance to access the watercourses, heat load index and lithology were chosen as input variables for the predictive modelling. Archaeological data, corresponding to the location of known Palaeolithic sites, were also retrieved from the official records. Three models were implemented using regression and multi-criteria methods; for Model 1 a Generalised Additive Model (GAM) was applied, while for Model 2 and Model 3 two distinct combinations of Probabilistic Frequency Ratio (PFR) and Analytic Hierarchy Process (AHP) were used. The spatial cross-tabulation between the obtained predictive maps and the location of the known Palaeolithic sites shows that all the models are acceptable. However, the combinations of PFR + AHP seem to evidence greater efficacy compared to the GAM. Model 3 offers the best performance (90%), followed by Model 2 (87%) and Model 1 (68%). Possible sources of inaccuracies in the input data and the spatial modelling results were critically discussed. Model 3 generated the most robust and reliable predictive prototype map. The maps produced can serve local and regional agencies as a complement and aid decision-making in public policies for spatial planning, and in the conservation/management of cultural heritage. These cartographic representations can provide quicker identification of areas of interest, for example, in the context of rescue archaeology, along with a substantial reduction in time and costs for project promoters, as well as helping in the environmental impact assessments.