High Land Research Articles

Joint analysis of land, carbon and nitrogen reveals diverging trends in the sustainability of organic crops in Spain

The world's top ten Organic Farming (OF) countries by converted area include several Mediterranean countries, including Spain. Despite this, little is known about the consequences of OF on crop production and environmental sustainability in this country. In this article, we conduct an agronomic analysis of Spanish considerable conversion rate to OF, which tends to concentrate in certain provinces and crops. Indeed, in the case of various crops and in several provinces, the organic share of total agricultural land exceeds 20–30 %. This concentration makes it possible to compare information obtained from farmers through interviews and provincial statistical information. The study data consisted of information collected from interviews of a representative sample of organic farmers conducted in 2004 and 2020 as well as official statistical information. The results showed that no yield gap between OF and conventional farming was found for vegetables and fruit trees, while it showed an increasing trend in arable crops. Presumably, the reason is that fruit trees and vegetables generate and incorporate high levels of carbon (C) flows into the soil and have a low land cost per unit of incorporated nitrogen (N) (or can be paid for), allowing to meet crop needs and to increase soil organic matter (SOM). Conversely, in the case of rainfed arable crops, the soil C and N inputs are deficient due to the low crop residues and the high land cost of N. Consequently, SOM destruction and N deficit progressively broaden the yield gap, undermining the agroecosystem sustainability. To reverse the situation, among other measures, it is necessary to implement agricultural policies designed to make rotations with high legume ratios viable and to plant varieties presenting higher production of residues and roots, such as traditional varieties.

High dynamic range land wavefield reconstruction from randomized acquisition

Compressive sensing (CS) is an alternative to regular Shannon sampling that captures similar information from reduced measurements. It relies on randomized sampling patterns and a sparse data representation to reconstruct the regularly sampled object. CS is an important ingredient in afford- able seismic acquisition which can lead to improvements in the near surface mapping and in noise suppression for land data. However, the near surface traps the majority of the source-generated energy, resulting in data that are rich in high-wavenumber content and have amplitudes spanning several orders of magnitude. When dealing with such high dynamic range non-stationary data, the Fourier domain is not optimal for providing a sparse representation - a necessary condition for successful application of CS. In contrast, a discrete complex wavelet transform can localize high energy features, has good directional selectivity, and is near-shift invariant. Combined, these properties allow complex wavelets to represent detail-rich wavefields in a compact form. To leverage these features and achieve good CS reconstructions, we develop a scale- and orientation- dependent iterative soft thresholding scheme (IST) for reconstructing high dynamic range wavefields. Our approach requires little parametrization, is easy to implement, and robust to reconstructed wave- field sampling grid and dynamic range. We test IST on different wavefields with randomly missing traces, and compare the data reconstructions to the spectral projected gradient solver and projection onto convex sets. We quantify the reconstructions by a direct comparison of Fourier coefficients between fully sampled and reconstructed wavefields. Taking log10 of Fourier coefficients prior to computing the quality metric de-emphasizes the importance of magnitude match while highlighting Fourier coefficient support accuracy which usually translates into good structural fidelity of reconstructed data. We find that IST performs consistently among all examples, yielding a good phase match while performing gentle denoising.

Conversion of High Speed Landing Craft Boat for Passenger into High Speed Landing Craft Boat for Ambulance

Conversion of High Speed Landing Craft Boat for Passenger into High Speed Landing Craft Boat for Ambulance

Projecting hydrological response to climate change and urbanization using WEAP model: A case study for the main watersheds of Bicol River Basin, Philippines

Study regionBicol River Basin, Philippines Study focusThe study investigated the impact of climate change and urbanization on water resources in the Philippines. It used Water Evaluation and Planning (WEAP) software and climate forecasts from eight Global Circulation Models (GCMs) to assess the nation's water balance, focusing on two sensitive watersheds: Libmanan-Pulantuna (LPW) and Quinali (QW). The study projects water availability in these areas by creating climate-urbanization scenarios. Furthermore, our endeavor aims to provide insight into the complexities of hydrological processes within traditionally under-observed regions, serving as a blueprint for future environmental planning and sustainable water management in the Philippines and beyond. New hydrological insightsThe study's simulated streamflow matches observed data (R2: 0.70–0.85, NSE: 0.57–0.67) and indicates warming trends and variable precipitation in both watersheds. Rising water demand in domestic and industrial sectors contrasts with a decline in agriculture due to land conversion. QW faces increased water demands from urbanization, while LPW has lower unmet water demand. Low Land Decline scenarios indicate consistent water scarcity in agriculture, while High Land Decline scenarios predict a decrease by 2100. Urbanization significantly impacts future water stress more than climate change, with reduced agricultural land generally associated with lower water stress. Conversely, climate change exacerbates unmet demand issues in domestic and industrial development cases. Due to diminishing agricultural land, both watersheds are expected to transition from water-deficient to water-surplus regions by the end of the century. However, immediate action is crucial to address current water demands, particularly in the severely water-deficient Quinali Watershed.

Spatial variability of clay minerals in a semi-arid region of Turkiye

Clay minerals are the source of many chemical and physical properties that influence the provision of soil-based ecosystem services. This study aimed to identify the most significant soil characteristics contributing to the spatial variability of clay minerals in a semi-arid region of Turkiye. Additionally, the study assessed the predictive capabilities of Classification and Regression Tree (CART), Random Forest Regression (RF) and eXtreme Gradient Boosting Regression (XGBoost) in estimating soil clay mineral content. Smectite+vermiculite (SMVR) was the most abundant clay mineral in the study area, followed by illite and kaolinite. Hyperparameter tuning significantly improved model accuracy, with root mean square error (RMSE) reductions ranging from 2.53% to 97.3%. The machine learning algorithms demonstrated varying performances in spatial prediction accuracy. The RF model achieved the lowest RMSE (8.587%) and the highest R2 values (0.796) for predicting SMVR. The XGBoost outperformed other models for kaolinite (RMSE: 4.814%, R2:0.713) and illite (RMSE:7.368%, R2:0.613). Exchangeable cations, particularly magnesium (Mg) and calcium (Ca), were identified as crucial factors influencing the spatial distribution of clay minerals. Among these, M concentration had the strongest influence on predicting both SMVR (38.1%) and illite (26.3%). Conversely, for kaolinite prediction, Ca concentration played the most significant role (38.7%), followed by Mg (19.93%). In conclusion, this study demonstrates the effectiveness of machine learning models, particularly XGBoost which achieved the lowest RMSE for all clay minerals investigated. These models offer a valuable tool for predicting clay mineral content in the Kazova Plain. The findings highlight the importance of parent material, weathering processes, and specific soil properties, such as exchangeable cations, in shaping clay mineral distribution. This knowledge not only contributes to a deeper understanding of soil formation in semi-arid environments but also practical applications. For instance, by predicting the abundance of SVMR, known for its high cation exchange capacity land managers can develop targeted strategies for optimizing fertilizer application in the Kazova Plain.

Genotype by environment interaction and stability study in bread wheat (Triticum aestivum L.) genotypes in Guji Zone, Southern Ethiopia

Genotype by environment interaction and stability study in bread wheat (Triticum aestivum L.) genotypes in Guji Zone, Southern Ethiopia

The Patrimonialization of Traditional Salinas in Europe, a Successful Transformation from a Productive to a Services-Based Activity

Traditional inland salinas in Spain and Portugal are often located in rural, isolated areas with low agricultural value, and very few have survived in coastal areas under high land use change pressure. Before the advent of efficient transportation networks, about 500 small inland and ca. 250 coastal saltworks existed there. During the 20th century, these sites were gradually abandoned in favor of industrial salt from mines or larger coastal salinas. Only a few were able to transform a productive activity into a multifunctional, services-oriented landscape. This contribution discusses the recovery and patrimonialization processes of nine inland salinas in Spain and Portugal protected as monuments, plus three other successful cases in Denmark, France, and Slovenia. With an indicator-based tool, the degree of patrimonialization of each site was quantified. In recent decades, these cultural landscapes have invested in gastronomy, wellness, tourism, and innovation, transforming a cultural landscape in decline into a living landscape for the future. The different stages in their patrimonialization process have been characterized, helping identify the hinges and tipping points at which a traditional productive activity in danger can evolve into a consolidated heritage-based successful initiative. Good practices have been detected and described. Potential pitfalls and challenges in patrimonialization were also identified, serving as early warning signs. Although focused on traditional salinas, the results of this study may help manage and preserve similar cultural landscapes in Europe. Some ideas for future management and research on productive cultural landscapes are provided.

Climate variability and change in Ecuador: dynamic downscaling of regional projections with RegCM4 and HadGEM2-ES for informed adaptation strategies

Ecuador, a country with distinct coastal (CO), highland (HL), and Amazon (AM) regions that are characterized by unique climatic, ecological, and socio-economic features is highly vulnerable to climate change. This study focuses on these three regions, highlighting their individual importance in the broader context of Ecuador's climate vulnerability. Utilizing dynamically downscaled data from the Regional Climate Model (RCM), we generated precipitation and air temperature projections for the period 2070–2099 under three different climate change scenarios. We indicate projected temperature increases across all three regions: mean temperature increases for the CO, HL and AM regions are of 1.35, 1.55, and 1.21°C, respectively. Each year, the largest temperature increases are predicted for the third quarter (June–August), with the smallest increases predicted for the last quarter (December–February). Precipitation patterns show varied changes, with CO exhibiting a positive mean daily change, in contrast to a mean negative change in the AM region. These region-specific projections underscore the differential impacts of climate change within Ecuador and highlight the necessity for tailored adaptation measures. The study's novel approach, focusing on distinct regional impacts within a single nation, offers valuable insights for policymakers, aiding in the development of effective, region-specific climate change mitigation and adaptation strategies. This targeted approach is crucial to address unique challenges faced by different regions, thereby supporting national resilience strategies.

Decreasing environmental footprints of dairy production systems through optimization of feed rations and origins

Environmental impacts of livestock production systems are a global concern, because of the large greenhouse gas (GHG) emissions and nitrogen (N) and phosphorus (P) losses associated with feed production and livestock rearing. These losses are in part related to the system of livestock production and their feed rations and feed origin. This study aims to investigate the economic and environmental impacts of optimizing feed configurations of dairy farms in Inner Mongolia (China), using data from farm surveys, life cycle assessments and linear optimization programming. The findings of our study reveal that feed optimization may lower carbon footprints by 36–44%, nitrogen footprints by 35–42%, and phosphorus footprints by 42–71%, compared to the baseline. The need for cropland decreased by 11–38% per kilogram of milk, feed costs decreased by 15–48%, and net profit increased by 39–129%. Further, we found a statistically significant negative correlation between environmental footprints and feed self-sufficiency of dairy farms. Notably, energy-rich feeds, silage maize, and grass should be grown on-farm. These findings underscore the potential of adjusting feed rations and origin to decrease environmental footprints and enhance net profits of dairy farms. However, we observed several barriers to widespread adoption of optimal feed rations and origin, which relate to land scarcity, high land rental costs, and lack of trust and cooperation with nearby arable farms. Our research provides a scientific foundation for optimizing feed rations and origins for diverse dairy systems to achieve improved environmental and economic performance.

Performance and egg quality traits of local chickens across different agroecologies in the Kewot district, North Shewa zone, Northern Ethiopia

This study was conducted to evaluate the performance (productive and reproductive) potential and egg quality traits of local chickens (LCs) across different agroecologies (AEs) in the Kewot district, North Shewa zone, northern Ethiopia. A multistage sampling technique was used to select the study sites and households (HHs). The data were collected through semi-structured questionnaires, monitoring and measurements. A total of 147 HHs were included in this study. Ninety brooding hens were monitored to determine hatchability and survivability percentages. A body weight of 120 LCs was measured at the market centres. Furthermore, the egg quality traits of 120 freshly laid eggs were evaluated. The data were analysed by a statistical package for social sciences (version 20). In the study area, the average flock size of the LC/HH populations was 9.90 ± 0.36. The most common flock type was chicks, followed by pullets, with significantly lower (p < 0.05) in the lowland (LL) AE. The mean age at first egg of females and the mean age at sexual maturity of males were 6.05 ± 0.06 and 5.68 ± 0.08 months, respectively. The numbers of eggs per clutch and per year were 14.29 ± 0.40 and 50.02 ± 1.51, respectively. There was no significant difference (p > 0.05) in the average number of clutches/hen/year across AEs, while significantly lower (p < 0.05) numbers of eggs per clutch and per year were recorded for highland (HL) AEs than for LL agro-ecology. The mean hatchability percentage was 80.94 ± 1.69%. The mean market body weights of the male and female LCs were 0.91 ± 0.05 and 0.82 ± 0.05 kg, respectively. There were significant differences (p < 0.05) in egg weight, egg width, shell thickness, shell ratio, albumen height, albumen and yolk weight, yolk colour, and Haugh unit (HU) between the AEs. The results revealed that the performance potential and egg quality traits of the LC in the study district were somewhat poor. Therefore, AE-specific development interventions should be designed and implemented to improve the performance potential and egg quality traits of LC in the study area.

Organic food has lower environmental impacts per area unit and similar climate impacts per mass unit compared to conventional

In recent years, interest in studying the climate and environmental impact of organic food has grown. Here, we compared the environmental impacts of organic and conventional food using data from 100 life cycle assessment studies. Most studies focused on climate impacts, with fewer addressing biodiversity loss and ecotoxicity. Findings revealed no significant differences in global warming, eutrophication potential, and energy use per mass unit. However, organic food showed lower global warming, eutrophication potential, and energy use per area unit, with higher land use. Additionally, organic farming showed lower potential for biodiversity loss and ecotoxicity. Challenges in life cycle assessment include evaluating biodiversity, toxicity, soil quality, and carbon changes. The choice of functional units influences results, highlighting the importance of considering multiple units in assessing organic food’s environmental footprint. This study emphasizes the necessity for comprehensive assessments at both product and diet levels to support informed decisions.

Land Cover Classification Based on Multimodal Remote Sensing Fusion

Abstract. Global high-precision and high timeliness land cover data is a fundamental and strategic resource for global strategic interest maintenance, global environmental change research, and sustainable development planning. However, due to difficulties in obtaining control and reference information from overseas, a single data source cannot effectively cover, and surface coverage classification faces significant challenges in information extraction. Based on this, this article proposes an intelligent interpretation method for typical elements based on multimodal fusion, starting from the characteristics of domestic remote sensing images. It also develops an optical SAR data conversion and complementarity strategy based on convolutional translation networks, as well as a typical element extraction algorithm. This solves the problems of sparse remote sensing images, limited effective observations, and difficult information recognition, thereby achieving automation of typical element information under dense observation time series High precision extraction and analysis.

Pengaruh Kombinasi Populasi Tumpangsari Kedelai-Singkong pada Pertumbuhan dan Hasil Benih Tanaman Kedelai dan Hasil Umbi Singkong

Intercropping soybeans with cassava can become one solution to increase the production of soybean in Indonesia. This research aimed to determine the most optimal population combination of soybean-cassava intercropping for the growth and yield of soybean seeds, cassava tuber yield, and land use efficiency (LUE).. The research was carried out on the farm land of the Main Seed Center in Sekincau District, West Lampung Regency, Lampung Province, Indonesia at -5°02’27” South and 104°18’16” East at elevation of 1173.1 meter from sea level and at the Seed and Plant Breeding Laboratory Faculty of Agriculture University of Lampung during June 2022 - February 2023. The four treatments of population combination of soybean-cassava intercropping were applied in a completely randomized block design (CRBD) and replicated five times in five blocks. The four population combination treatments of soybean-cassava intercropping were a) 100% soybean and 0% cassava (monoculture) (p₁), b) 67% soybean and 97% cassava (p₂), c) 67% soybean and 89% cassava (p₃), and d) 50% soybeans and 97% cassava (p₄). The growth and the seed yield per soybean stem of monoculture did not differ to those of the soybean-cassava intercropping, but the soybean seed yield per plot area of the intercropping was lower than those of monoculture. Its mainly due to the soybean population of the intercropping was lower compared to monoculture. All population combinations in soybean-cassava intercropping were effective in supporting the growth and yield of soybean seeds, but the population combination of 50% soybean and 97% cassava (p₄) was also effective in supporting cassava tuber yield, and had the highest land use efficiency among other population combinations. Key words: flowering age, plant height, seed weight, tuber weight of cassava

The suitability assessment for land territorial spatial planning based on ANN-CA model and the Internet of Things

This work aims to utilize Internet of Things (IoT) technology and the Artificial Neural Network - Cellular Automaton (ANN-CA) model to analyze the construction of indicators for territorial spatial planning and urban development suitability assessment. Firstly, the IoT technology is introduced, and its application potential in land planning is explored. Using the IoT technology, various data related to land use are collected, and these data are transmitted and summarized through IoT equipment to form a data base. Based on the collected data, the ANN-CA model and the “dual assessment” concept are employed to establish an indicator system for urban development suitability assessment, encompassing permanent basic farmland, ecological redlines, and current built-up areas. Through the combination of these two models, the future land use situation can be predicted more accurately. The trained model is evaluated, including simulation accuracy, error analysis, Kappa coefficient and other indicators. Compared with the actual data, the accuracy and credibility of the model are verified. Finally, according to the prediction results of the model, the land use situation is analyzed and interpreted to provide decision support for urban planning and development. The research results show that the combination of IoT technology and ANN-CA model can effectively analyze the evolution law of land use and the suitability of urban development. Through the reasonable setting and processing of model parameters and data, people can get high accuracy land use prediction results, which provides important reference and support for urban planning and sustainable development. The suitability for urban development within County M exhibits noticeable spatial disparities, with the central region being more suitable for development while the peripheral regions are relatively less favorable. This work provides valuable guidance for decision-makers and researchers in the field of territorial planning, and promotes orderly urban development and sustainable prosperity.

Effects of Fluid Viscous Damper on Reinforced Concrete Tall Building under Lateral Loading in Lagos, Nigeria

The rapid construction of tall buildings in unconventional areas of Lagos, driven by high land cost necessitates meticulous analysis and design to withstand lateral loads such as wind and seismic forces. Typically, enhancing structural rigidity is the conventional approach to counteracting horizontal loads. This study examines the effectiveness of fluid viscous damping (FVD) in reducing gravity, wind and seismic loads in a 24 – story suspended floor frame structure. Using ETABS 2019 software, the building’s modeling and analysis demonstrate that integrating FVDs at each floor level significantly reduces displacement, drift and overturning moments by 20%, 24%, and 29%, respectively, thus enhancing structural stability. Analyzing structural response in Nigeria, despite low seismic intensity, is crucial for risk management and resilience. It informs building practices, improves building codes, and prepares for potential seismic events, ensuring safer infrastructure. This research provides a computational framework for dampening vibrations in tall buildings through FVD technology.

Changes in Runoff Coefficient Index as a Result of Land Use Change (Case Study: Malang City)

The result of this research is to present observations about changes in the value of the conveyance coefficient in an area or region caused by changes in land use as a basis for decision making for water resources management in urban areas, by considering field data and satellite image classification to observe changes. As well as the consequences of the development of an area as seen from population growth, economy and housing needs. Malang City continues to experience land use change as evidenced by the decrease in agricultural land area. The method used is supervised classification with the help of geographic information systems and analyzing land use change over the past 20 years through map overlay. The data used are Landsat and Terrasar-X satellite images with the land use classes used are open land, settlements, agriculture, and shrubs. Satellite images were classified to analyze the extent of land use change and to see the rate of change in the conveyance coefficient of each class over the past 20 years. The results show that the study area has a change in the value of the conveyance coefficient caused by a fairly high land use change from agricultural land to built-up land such as settlements or housing. Malang City has a tendency to increase the population significantly because it is an educational city that continues to need a place to live and allows the rotation of various economic needs. The results of the analysis showed that there were changes in the value of the conveyance coefficient from 2002 to 2022, with an upward trend. In 2002 the C value was 0.2468; in 2007 it was 0.2899; in 2012 it was 0.3457; in 2017 it was 0.3895; in 2022 it was 0.4119. With an average value of change every year is about 13.78%.

An Ellipsoidal Plate Motion Model of the Indo‐Australian Tectonic Plate

AbstractWe present a class of “ellipsoidal rotation matrices” which can be used to characterize tectonic plate motion; where geocentric Cartesian coordinates travel along paths tangential to the ellipsoid. We contrast them with conventional Euler pole plate motion models which are more closely aligned with spherical coordinate systems and inherently induce a change in geodetic ellipsoidal height. We demonstrate the use of each in the Indo‐Australian tectonic plate setting, which is known to move approximately 7 cm/year in a north‐northeast direction. Geocentric Datum of Australia 2020 (GDA2020) coordinates are “plate‐fixed” static coordinates obtained using a conventional Euler pole plate motion model to align time dependent coordinates with the 2014 realization of the International Terrestrial Reference Frame at the epoch 2020.0. We show that this Euler pole plate motion model can introduce ellipsoidal height velocities of up to −0.2 mm/year. This is small but systematic, so pertinent for consideration with high accuracy vertical land motion studies using GDA2020 coordinates and velocities. We further investigate the comparative statistical accuracy of conventional Euler pole and the ellipsoidal models with respect to characterizing plate motion captured in high quality Global Navigation Satellite System data.

Intermittency of Gravity Wave Potential Energy Generated by Mountains Revealed from COSMIC-2 Observations

The intermittency of gravity wave potential energy (GWPE) in the upper troposphere and stratosphere was investigated using the Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) temperature data over three typical mountains (Tibetan Plateau, Rocky Mountains, and Andes). These typical mountains have high sea level elevations but different land–sea contrast. The probability density function (PDF) of GWPE has the independent variable of GWPE and dependent variable of occurrence probability of GWPE over a region. Our analysis showed that the PDFs of GWPE over these three mountains roughly followed lognormal distributions in all heights and months. But, the key parameters (mean value and standard deviation) of lognormal distribution varied with heights and months. Above each mountain, the two key parameters exhibited similar temporal and spatial distributions. They had the largest values around the tropopause region, smaller values in the lower stratosphere (~20–30 km), and larger values in the upper stratosphere (~35–45 km). The intermittency of GWs is represented as the ratio of the GWPE at 50th percentile to the GWPE at 90th percentile. The weakest intermittency was at ~20–30 km (above the zonal mean winds of zero) over the Tibetan Plateau and Rocky Mountains in all months and over the Andes from November to March, respectively. Generally, the weakest intermittency (~0.4) occurred in the region where the key parameters were the smallest around summer. The key parameters of lognormal distribution were dominated by annual variation over the Andes throughout the height range, 8–50 km. However, the semiannual variations are also significant in the lower stratosphere over the Tibetan Plateau and Rocky Mountains. The seasonal variations in the intermittency were not as obvious as those of the key parameters. The lognormal distributions and the intermittencies derived here provide an observational constraint on the tunable parameters in GW parameterization schemes.

SPATIOTEMPORAL ANALYSIS OF VIOLENT CONFLICT AND LAND COVER CHANGE IN LANAO DEL SUR FROM 2011 TO 2020

Abstract. With Lanao del Sur historically being a setting for numerous violent conflict events, its land use and land cover (LULC) manifest the direct and indirect effects of conflict such as destruction and forced displacement that influences land cover change (LCC). Tracking LULC changes can determine the extent of damage induced by conflicts and support the crafting of policies toward sustainable development. To see how conflict has affected the land systems, Landsat-7, and -8 imagery from 2011 to 2020 were used to examine Lanao del Sur's periodic land covers and their trajectories. Barangay-level conflict incidence was also used to identify areas with both high conflict incidence and high rates of LCC. Trajectory analysis revealed patterns in land processes: afforestation coinciding with abandonment, and cultivation being bordered by deforestation as the connecting grassland cover decreases. Decreases in grassland cover were simultaneous with an increase in agricultural lands. Generally coinciding with conflict hotspots, areas with high conflict incidence and land cover change were typically found in urban centers, near water bodies, and provincial boundaries where there was a high volume of human activities. Meanwhile, areas with low conflict incidence and LCC were found in forested areas. Overall, there is a significant positive correlation between conflict occurrences and LCC (r = 0.388), with abandonment (r = 0.533) and cultivation (r = 0.546) having moderate strengths of association.

Mercury Bioconcentration and Translocation in Rooted Macrophytes (Paspalum repens Berg.) from Floodplain Lakes in the Araguaia River Watershed, Brazilian Savanna

Macrophytes are fundamental photosynthetic organisms for functioning freshwater ecosystems, identified as potential bioindicators of mercury (Hg) in the environment. We quantified the concentrations of total Hg (THg) in water and macrophytes (Paspalum repens Berg.) from 17 lakes on the Araguaia River floodplain, aiming to compare the bioconcentration factor (BCF) in the aerial tissues and roots; evaluate the translocation factor (TF) between plant tissues; and assess the influence of environmental factors and land use on THg concentrations in water and macrophytes. The BCF was significantly higher in roots (1.29 ± 0.32) than in aerial tissues (0.41 ± 0.34), with low TF between plant tissues (0.14 ± 0.06). The highest concentrations of THg in water were determined in lakes with higher land use intensity and a pH close to neutral, indicating the transport of particulate-bound Hg and the immobilization in the water column. In contrast, wetlands were priority areas for the bioconcentration of THg in macrophytes, associated with sulfate, dissolved oxygen, and oxidation–reduction potential in the water. Thus, although P. repens is not a suitable bioindicator of Hg mobilization by anthropogenic land use in our study area, our results suggest the potential of macrophytes as bioindicators of sites that are favorable to Hg methylation.