Inform Land Management Research Articles

Determining the Usefulness of Land Information Management System (LIMS) in Ending Land Disputes in Zimbabwean A1 Farms

This study sought to determine the usefulness of the Land Information Management System (LIMS) for the resolution of Land Disputes in Marondera District A1 resettlement areas. The research was inspired by the continued occurrence of land disputes in Marondera A1 Farms. The main thrust of the research was to determine to assess the usefulness of the LIMS model in ending land disputes in Marondera District A1 farms. The study adopted a mixed research approach hinged on pragmatism research philosophy. A cross-sectional survey research design was used. The research used stratified random sampling for quantitative data whilst purposive sampling was used for the collection of qualitative data. Structured questionnaires and interview guides were the two major instruments that were used. A sample size of 373 participants was drawn from the Department of Lands Marondera, the Zimbabwe Lands Commission, Extension officers, and A1 farmers in areas of Wenimbi, Mushandira, and Ruware in Marondera. The sample size was arrived at using the Raosoft sample size calculator. The sample size for qualitative data was not predetermined but was arrived at using the saturation principle. In the analysis of quantitative data, tables, descriptive statistics, and inferential statistics were produced using Statistical Package for the Social Sciences (SPSS) version 23. The presentation of qualitative data followed a thematic approach in which responses were shown using word cloud analysis. The study revealed that the improved LIMS will enable land registration, land use planning, land dispute resolution, and data analysis and reporting. It was recommended in the study that the government encourage open communication and collaboration among local communities, farmers, and authorities to address grievances and prevent conflicts, fostering a sense of shared responsibility and ownership. Also with LIMS government conducts a thorough audit to identify and resolve issues related to land ownership, boundaries, and usage, helping to prevent future disputes.

Spatial distribution and transport characteristics of debris flow sediment using high resolution UAV images in the Ohya debris flow fan

Debris flows are significant geomorphic processes that can pose hazards to human settlements and infrastructure, making the understanding of their sediment transfer characteristics and impacts on the surrounding landscape crucial for effective land management and hazard mitigation strategies. This study investigates the distribution patterns of sandstone, vegetation, and shale classes within the Ohya debris flow fan, aiming to gain insights into the sediment characteristics, grain size variations, and vegetation cover trends along the flow path. Using a combination of field surveys and image processing we analyzed sediment characteristics and grain size variations a three study zones: upstream, transfer, and downstream. Statistical parameters such as mean, mode, skewness, and kurtosis were employed to quantify the grain size distribution and identify variations across the study zones. Results reveal distinct spatial variations in the distribution of sandstone, vegetation, and shale classes along the flow path. We observed a decrease in sandstone and vegetation cover from the upstream to the downstream sections, while the area covered by the shale class exhibited an increasing trend in the downstream direction. These findings suggest that debris flows selectively remove smaller particles downstream. The distribution of particle sizes within the sandstone class also exhibited variations, with a higher proportion of smaller pebbles downstream due to more effective removal of finer particles in the upstream zone. This study highlights the complex interplay between debris flow dynamics, sediment transport, and vegetation colonization. The findings contribute to the scientific knowledge of debris flow processes and can be used to inform land management decisions and mitigate the hazards associated with debris flows in similar environments.

Investigating Ecosystem Service Trade-Offs and Synergies: The Need for Correlations and Driving Factors in the Upper Fen River Basin of Shanxi Province, China

This research provides an overview of the trade-offs and synergies among ecosystem services (ESs) within the upper Fen River Basin (uFRB) that are crucial for informed land management and regional ecological protection. We utilized methodologies, including the dynamic equivalent factor method and spatial autocorrelation analysis, to track ES and driving factors from 1990 to 2020. This study revealed a 13.27% increase in overall ES value, with notable growth in forest land and water areas. Initially, synergies were dominant, but trade-offs became evident over time, particularly with food production. This study identified road proximity and the Normalized Difference Vegetation Index (NDVI) as primary drivers of ES values, with their impact evolving annually. The analysis also highlighted the importance of considering the temporal dynamics in ES relationships and the influence of driving factors on these services. We propose incorporating socio-ecological factors and ES bundles into spatial planning. This is crucial as it will allow us to optimize multi-ES objectives, thus balancing trade-offs and enhancing synergies for sustainable land use.

Land Suitability Assessment and Crop Water Requirements for Twenty Selected Crops in an Arid Land Environment

Expanding projects to reclaim marginal land is the most effective way to reduce land use pressures in densely populated areas, such as Egypt’s Nile Valley and Delta; however, this requires careful, sustainable land use planning. This study assessed the agricultural potential of the El-Dabaa area in the northern region of the Western Desert, Egypt. It focused on assessing land capability, evaluating crop suitability, mapping soil variability, and calculating crop water requirements for twenty different crops. In this work, we evaluated land capability using the modified Storie index model and assessed soil suitability using the land use suitability evaluation tool (LUSET). We also calculated crop water requirements (CWRs) utilizing the FAO-CROPWAT 8.0 model. Additionally, we employed ArcGIS 10.8 to create spatial variability maps of soil properties, land capability classes, and suitability classes. Using a systematic sampling grid, 100 soil profiles were excavated to represent the spatial variability of the soil in the study area, and the physicochemical parameters of the soil samples were analyzed. The results indicated that the study area is primarily characterized by flat to gently sloping surfaces with deep soils. Furthermore, there are no restrictions on soil salinity or alkalinity, no sodicity hazards, and low CaCO3 levels. On the other hand, the soils in the study area are coarse textured and have low levels of CEC and organic matter (OM), which are the major soil limiting factors. As a result, the land with fair capability (Grade 3) accounted for the vast majority of the study area (87.3%), covering 30599.4 ha. Land with poor capability (Grade 4) accounted for 6.5% of the total area, while non-agricultural land (Grade 5) accounted for less than 1%. These findings revealed that S2 and S3 are the dominant soil suitability classes for all the studied crops, indicating moderate and marginal soil suitabilities. Furthermore, there were only a few soil proportions classified as unsuitable (N class) for fruit crops, maize, and groundnuts. Among the crops studied, barley, wheat, sorghum, alfalfa, olives, citrus, potatoes, onions, tomatoes, sunflowers, safflowers, and soybeans are the most suitable for cultivation in the study area. The reference evapotranspiration (ETo) varied between 2.6 and 5.9 mm day−1, with higher rates observed in the summer months and lower rates in the winter months. Therefore, the increase in summer ETo rates and the decrease in winter ones result in higher CWRs during the summer season and lower ones during the winter season. The CWRs for the crops we studied ranged from 183.9 to 1644.8 mm season−1. These research findings suggest that the study area is suitable for cultivating a variety of crops. Crop production in the study area can be improved by adding organic matter to the soil, choosing drought-resistant crop varieties, employing effective irrigation systems, and implementing proper management practices. This study also provides valuable information for land managers to identify physical constraints and management needs for sustainable crop production. Furthermore, it offers valuable insights to aid investors, farmers, and governments in making informed decisions for agricultural development in the study region and similar arid and semiarid regions worldwide.

Understanding the effects of livestock grazing on dryland plant communities within the context of abiotic variability

AbstractDrylands, which cover more than 40% of the Earth's terrestrial surface, face rising agricultural demand and the influence of climate change. Understanding how livestock grazing pressure and local climate affect these environments is pivotal for informed land management. We studied big sagebrush plant communities in southwestern Wyoming over grazing gradients created by artificial livestock watering points. To explore the role of abiotic factors in shaping plant community response to grazing, we assessed the response of plant functional groups to grazing while accounting for soil texture variability across a precipitation gradient. Our models estimated that sagebrush cover responded positively to grazing intensity, with a 6% increase in cover with intensity when comparing the heaviest grazing treatment with the lowest grazing intensity. Perennial bunchgrass cover, the primary forage component, had a small negative response, a 3% decrease in cover from the lowest grazing intensity to the highest. Grazing intensity had no effect on bunchgrass density, perennial forbs, or rhizomatous grasses. Compared with abiotic factors, grazing intensity had a small effect on perennial bunchgrass and bare ground. We found that precipitation explained a 13% increase in perennial bunchgrass cover and a 34% decrease in bare ground cover compared with a 6% increase with increasing intensity across our grazing gradients. Sand content also had a larger effect on perennial bunchgrass cover and density than grazing. Increased sand content was associated with increased bunchgrass cover and density, supporting the inverse texture hypothesis. Our results show that while livestock grazing impacts sagebrush plant communities, its effect is small when compared with the effects of climate and soil. Our study contributes to a growing body of research emphasizing the need to contextualize plant community responses to grazing within specific climatic and edaphic conditions, which will promote effective land management in dryland ecosystems.

An ecoregion-based approach to evaluate invasive plant species pools

Invasive alien species are an important component of global change, threatening biodiversity, ecosystem functioning, economy, and human health. The number of alien species that attain the invasive status has experienced an exponential increase in recent years, leading some government agencies and stakeholders to allocate substantial resources to early detection, control, mitigation, and eradication programs. To develop effective nature conservation strategies, it is crucial to understand the invasive status of alien species and to identify priority species for management at spatial scales with a biogeographical basis. Despite significant progress in producing lists of alien species at the country level, a standard methodology for species assessment within ecological regions (i.e., regions with similar environmental or biogeographical characteristics) is still lacking. Here, we develop a systematic approach to determine invasion status and to prioritize invasive alien plant species within an ecoregion. We apply this approach in the Cantabrian Mixed Forests ecoregion, which encompasses biogeographically related areas from N Portugal, NW Spain, and SW France, and is strongly affected by plant invasions. By combining scientific evidence with expert opinion on the ecological characteristics of alien plants, we identified 175 invasive plant species in the study ecoregion, of which 37 cause massive environmental and/or socio-economic impacts. For each species, we provide comprehensive information and recommendations for scientists, land managers, policy makers, and other stakeholders under a biogeographical basis. This information includes species characteristics, invasion status/level, population trends, geographic locations and range size, local abundance, environmental and socio-economic impacts, and invaded habitats. We also accounted for administrative divisions within the ecoregion to facilitate the use of such evaluations in local-scale management and conservation plans. Our framework may be applied to any ecoregion worldwide, enhancing the assessment and management of invasive species pools within biogeographically meaningful regions.

The LTAR Grazing Land Common Experiment at Walnut Gulch Experimental Watershed.

The Walnut Gulch Experimental Watershed (WGEW) Long-Term Agroecosystem Research (LTAR) network common experiment addresses the aspirational practice of brush management (BM) to reverse the prevailing condition of woody plant encroachment (WPE) and increase perennial native grass production. Across the western United States, the decision to implement BM includes consideration of management objectives, cost, and the expected impact on a diverse suite of ecosystem services. Maintaining or restoring grass cover will help meet the LTAR sustainable production, economic, and social goals, and averting degradation will meet environmental goals. This common experiment, focused on hydrologic and erosion impacts of BM, aims to inform land management decisions on three major plant communities in the Southwestern United States: creosote bush (Larrea tridentata), mesquite (Prosopis velutina), and pinyon-juniper (PJ, Pinus and Juniperus spp.). On the WGEW, applying tebuthiuron pellets to creosote bush increased grass cover and reduced runoff and erosion. The 2016BM experiment on the Santa Rita Experimental Range applied a commonly used liquid herbicide cocktail but achieved only 7% mortality on mesquite, probably because of the timing of the aerial application. Experiments manipulating rainfall amount and intensity on plots receiving fire, chemical, or mechanical BM treatments on PJ communities aim to improve process representation in simulation models. The deliverables of these BM experiments will be to (i) improve the performance of runoff and erosion models, (ii) enhance our ability to identify areas most at risk from reduced hydrologic function and soil erosion after shrub proliferation, and (iii) better predict how landscapes will respond to BM interventions. Ranchers, land management agencies, and watershed conservation organizations will benefit from training and availability of improved tools to focus treatments on areas where greatest net benefits might be realized.

Kinetic Analysis of Rainfall-Induced Landslides in May 2022 in Wuping, Fujian, SE China

In the context of global climate change, shallow landslides induced by strong typhoons and the ensuing rainstorms have increased significantly in China’s eastern coastal areas. On 27 May 2022, more than 700 liquefied landslides were induced by the rain gush in Wuping County, Longyan City, Fujian Province, SE China. In light of their widespread occurrence and the severe damage caused, detailed field investigations, UAV surveys, trench observations, in situ tests, and numerical simulation are conducted in this work. The cascading landslides are classified as channelized landslides and hillslope landslides. Long-term rainfall, the influence of vegetation roots under wind load, and differences in the strength and structure of surficial soil are the dominant controlling factors. The sliding surface is localized to be the interface at a depth of 1–1.5 m between the fully weathered granite and the strongly weathered granite. Kinetic analysis of a channelized landslide shows that it is characterized by short runout, rapid velocity, and strong impact energy. The maximum velocity, impact energy, and impact force of the Laifu landslide are 29 m/s, 4221.35 J, and 2110 kPa. Effective excavation is usually impossible in this context. This work highlights the escalating issue of shallow landslides in eastern China’s coastal areas, exacerbated by climate change and extreme weather events like typhoons. By conducting comprehensive investigations and analyses, the research identifies key factors influencing landslide occurrence, such as rainfall patterns and soil characteristics. Understanding the dynamics and impact of these landslides is vital for improving risk assessment, developing effective early warning systems, and informing land management policies in this region. Further exploration concerning hydro-meteorological hazard early warning should be encouraged in this region.

Pan Trapping and Malaise Trapping: A Comparison of Bee Collection Techniques in Subalpine Meadows

Public lands, managed for multiple uses such as logging, mining, grazing, and recreation, also support vital environmental services like wild bee pollination. A trending decline in wild bees has heightened interest in documenting these key pollinators in their native habitats. Accurate assessment of pollinator community diversity is crucial for population monitoring and informing land management practices. In this study, we evaluate the efficiency of Malaise traps and pan traps in sampling wild bees over three growing seasons in subalpine meadow communities in central Utah. Sixteen trapping sites were established, each with a Malaise trap and an array of blue, white, and yellow pan traps, nine at each site. Weekly collections were made through summer months and a comparison of their effectiveness in capturing bee abundance and species richness was made. Malaise traps captured significantly greater abundance of bees on average, though this was species-dependent. Malaise traps were especially effective at capturing Bombus spp. and larger species. Pan traps were generally more effective with smaller species such as Hylaeus spp. White pan traps outperformed yellow and blue pan traps in terms of abundance and only yellow pan traps in terms of richness. Both methods contributed unique species to the overall collection effort, suggesting that a combination of trapping methods provides a more comprehensive understanding of bee communities. Species accumulation curves indicate that species existing within the community went unencountered in our samples and that more time or perhaps additional methods could aid in best describing the entire community.

On the effectiveness of multi-scale landscape metrics in soil organic carbon mapping

Soil organic carbon (SOC) mapping delivers invaluable information to the global carbon budget and climate change mitigation endeavour. Environmental variables at sample locations are frequently used as explanatory variables for simulating the spatial distribution of soil properties. However, these may not fully capture the spatial information generated by soil-forming processes. We applied multi-scale landscape metrics that can comprehensively characterize the surrounding landscape information of sample points. The metrics were extracted at two levels (landscape level and class level) and include the diversity, shape and area, fragmentation and connectivity with a buffer distance from 500 m to 5,000 m. We then investigated its effectiveness as environmental variables via recursive feature elimination, random forests, and quantile regression forests. The Jianghan Plain, China, was selected as the study area, where over 19,000 topsoil samples were collected. Results indicated that multi-scale landscape metrics enhanced the predictability of SOC mapping, with R2 increased by 43 %. Specifically, Shannon’s diversity index, the percentage of landscape index, interspersion and juxtaposition index, and patch cohesion index outperformed environmental variables that were extracted at the sample location. In addition, the relationships between SOC and landscape metrics were found to be scale-dependent. Landscape metrics demonstrated significant explanatory capacity for SOC across various spatial scales. Notably, as the scale surpassed 3,000 m, there was a discernible improvement in the explanatory effectiveness of the landscape metrics for SOC. Our findings highlight that landscape metrics are effective in characterising the soil-landscape relationship that is generated by multi-scale natural and anthropogenic soil-forming processes. Meanwhile, knowledge of the intricate relationship between landscape characteristics and SOC is crucial for informing land management decisions aimed at enhancing carbon sequestration, mitigating climate change, and maintaining soil fertility.

Oued Lakhdar watershed (Morocco), monitoring land use/cover changes: remote sensing and GIS approach

ABSTRACT Landsat is a series of Earth-observation satellites jointly managed by NASA and the United States Geological Survey (USGS) that capture multispectral images of the Earth’s surface dating back to the 1970s, providing a valuable tool for tracking changes in land cover over time. In this study, Landsat satellite data were combined with remote sensing and Geographic Information System (GIS) technologies to monitor land cover changes in the Oued Lakhdar watershed, which covers an area of 1,638 km2. Landsat satellite data for the years 1987, 1994, 2004, 2014, and 2021 were used, and the maximum likelihood method was applied in ArcGIS software version 10.4.1 to classify land components. The classification was validated using total accuracy, the kappa index, Google Earth, and terrain knowledge. The results show remarkable changes in land cover, with an increase in bare soil and irrigated crops between 1987 and 2021, especially in the last six years, totaling 0.672 km2/yr and 15.028 km2/yr of the study area, respectively, and a decrease in water bodies and dense forests, totaling −0.941 km2/yr and −30.046 km2/yr, respectively. Water retention coefficient analysis indicates that the watershed is anthropized and has a low retention capacity. This study provides valuable information for land use planning and management in the Oued Lakhdar watershed (Morocco).

Integration of bare soil and crop growth remote sensing data to improve the accuracy of soil organic matter mapping in black soil areas

Accurately mapping the spatial distribution of soil organic matter (SOM) content is critical for informed land management decisions and comprehensive climate change analyses. Remote sensing-based SOM mapping models during periods of bare soil exposure have demonstrated efficacy in various regional studies. However, integrating bare soil imagery with growing season imagery for SOM content mapping remains a complex process. We conducted a study in Youyi Farm, a representative area of black soil in Northeast China. We collected 574 soil samples (0–20 cm) with SOM content through field sampling and laboratory analysis. Additionally, cloud-free Sentinel-2 images were obtained from the Google Earth Engine (GEE) platform for both the bare soil period (April-June, October) and crop growth period (July-September) from 2019 to 2021. To assess the influence of crop growth information on SOM mapping, we incorporated remote sensing imagery during the crop growth period, considering different crop type zones (maize (Zea mays L.), soybean (Glycine max L.), and rice (Oryza sativa L.)). We conducted overall and zonal regressions using the random forest (RF) model to validate the prediction results through cross-validation. Our findings indicate that: (1) adding crop growth period images to the bare soil period images in different years can improve the accuracy of SOM mapping. For example, in the overall regression model of 2020, the highest accuracy was achieved by using the combination of May-July images, with an R2 value of 0.70 and an RMSE value of 0.71 %; (2) zonal regression by differentiating crop types can effectively improve the SOM mapping accuracy. In 2019, using zonal regression, the R2 of SOM mapping accuracy was improved by 0.02 and the RMSE was reduced by 0.03 % compared with the overall regression; (3) precipitation is an important factor affecting the accuracy of SOM prediction, and the lower the precipitation, the higher the accuracy of SOM prediction. In summary, the results of this study show that in the SOM remote sensing mapping of the black soil area, the growing period remote sensing information of different crop types should be comprehensively considered and combined with the image data of the years of lower precipitation, the accuracy of the SOM mapping can be effectively improved, which provides a new technological path and an application basis for the enhancement of the accuracy in remote sensing mapping with soil attributes.

Geophysical Mapping of Cemented Subsoils for Agricultural Development in Southern Peru

Cemented subsoils, commonly referred to as caliche, pose a regular challenge for agricultural development in arid and semi-arid regions like coastal southern Peru. These subsurface features restrict root penetration, limit water infiltration and hinder essential soil processes, ultimately reducing crop yields and agricultural productivity. Accurate and efficient mapping of caliche is important for optimizing land-use planning and implementing sustainable agricultural practices. This study presents the application of near-surface geophysical techniques for mapping caliche deposits in the context of agricultural development at the future Majes II site in the Arequipa region of southern Peru. Specifically, we employed high-frequency ground-penetrating radar (GPR) and frequency-domain electromagnetics (FDEM) at a testbed on the Majes II site to evaluate their ability to delineate the extent, thickness, and depth of caliche within the local geology. GPR offers high-resolution imaging, effectively capturing sharp contrasts between caliche and surrounding materials, providing detailed information on the thickness (approximately 0.4 m) and the depth (up to 1.5 m) of the caliche layers. FDEM provides valuable insights into the presence of caliche at a faster rate of data acquisition and processing, enabling rapid assessment of the extent of caliche deposits, although with the tradeoff of lower resolution and depth information. We demonstrate that these two geophysical methods can be used separately or in an integrated manner for collaborative interpretation at the Majes II site to inform land management decisions, including identifying areas with favorable conditions for crop production and implementing targeted interventions to mitigate the adverse effects of caliche on agricultural productivity.

Soil quality assessment in the Araban plain across various land use types

BackgroundSoil is an important resource for improving the quality of human well-being and creating sustainable environmental awareness. Therefore, it is imperative to protect the soil health. This study determined quality of the soils in the Araban plain, Türkiye using three different methods, i.e., principal component analysis (PCA), analytic hierarchy process (AHP), and expert opinion (EO). The major aim was to determine the most appropriate method for determining soil quality and recommending soil protection practices for improving quality. MethodsThis study was conducted on an area of approximately 25,000 ha. A total of 230 soil samples (7 pasture areas, 56 orchards, and 167 arable crops) were analyzed to determine key soil quality indicators. A minimum dataset consisting of parameters that best represent the soils of the region was created. Subsequently, PCA was used to predict soil quality with the optimal accuracy using the least amount of data. The EO was incorporated to validate the PCA results. The AHP was used to assign weights to the parameters. Indicators at all sampling points were converted to unitless scorers. These scores were then formulated as soil quality index (SQI) using the weighted summation method. ResultsOrganic matter (OM) exerted the highest impact on soil quality. Significant variations in SQI values were observed among arable land, orchards land and pastureland (P < 0.01). Significant variations were recorded in SQI values of the assessment methods employed in this study. The lowest (0.552) and highest (0.829) SQI values were recorded for AHP and EO, respectively. Overall, streamlining indicators through PCA gave the most accurate result for SQI value. Subsequently, SQI determination should involve weighing with AHP, particularly towards EO. ConclusionThe AHP was found to be the most appropriate method for evaluating soil quality in Araban. This integrated approach ensures a robust evaluation of soil quality, facilitating more accurate and nuanced insights for informed land management decisions. Overall, 92.61 % of the region’s soil had poor and medium soil quality. Therefore, increasing OM content and aggregate stability are suggested to improve soil quality in the study region.

Management of bushrocks in agricultural landscapes for reptile conservation

ABSTRACT Bushrocks provide critical habitat for reptiles and are a common feature in agricultural landscapes. Recent advances in soil amelioration practices have triggered a resurgence in the large-scale removal of bushrock from commodity production regions. Rock removal practices have substantial impacts on biodiversity, particularly for range-restricted and rock-dependent reptile species. We discuss findings from several observational studies and natural experiments on the ecological role of bushrocks in agricultural landscapes to inform land management and restoration practices. We found that bushrocks were critical as overwintering retreats, and reptiles preferred higher elevation areas with minimal canopy cover. We found reptiles rapidly responded to bushrock restoration, with increases in abundance and richness of reptiles in rock addition plots compared to controls. Our research highlights the importance of bushrock habitat, and the removal of such habitat may have far-reaching consequences. Conservation of reptiles in agricultural landscapes requires appropriate management and retention of bushrock. We urge for greater protection of existing bushrock habitats and consideration of rock as a restoration tool to improve conservation outcomes for reptiles in agricultural landscapes.

Impact of Environmental Conditions on Soil Geochemistry in Southern Kazakhstan

This study investigated the elemental composition of soils in Kyzylorda and Turkestan (southern Kazakhstan), an area rich in natural resources but facing potential environmental threats from industry and agriculture. The goal was to establish baseline geochemical values and assess soil contamination risks. Soil samples were collected from across the region and analyzed using ICP-MS and INAA techniques, providing a comprehensive profile of 72 elements. Statistical analysis revealed significant variations in elemental concentrations, with enrichments observed for specific elements when compared with reference values. Notably, both regions shared a core set of elements including rare earth elements (yttrium series: holmium, erbium, thulium), noble metals (gold, platinum, ruthenium, palladium), and tungsten. Enrichment patterns, however, provided distinct insights. Rare earth element enrichments likely reflect the region’s geology, while elevated radioactive elements necessitate further investigation to understand potential environmental and health risks. Enrichment of iron group elements might be linked to a combination of geological factors and anthropogenic activities like mining or industrial processes. A significantly higher number of elements exceeded background levels in Kyzylorda compared with Turkestan, suggesting greater element accumulation in Kyzylorda’s soil. This difference could be attributed to variations in regional geology or historical anthropogenic activities. The established geochemical baseline for 72 elements and the identified areas of potential contamination will inform land management practices, guide future environmental monitoring efforts, and ultimately contribute to the safeguarding of public health in southern Kazakhstan.

The new millennium so far: analysing land cover change in Ogun State Nigeria

ABSTRACT Land cover change research is salient in providing information for land use planning and management in urban areas. This study therefore analysed land cover change in four local government areas in Ogun State, Nigeria. Using remote sensing and geographic information system, Landsat images were analysed between 2001, 2013 and 2020 with both unsupervised and supervised image classifications. Results showed that between 2002 and 2013, there was a 41.14% decrease in forest area which further reduced by 41.92% by 2020. Agricultural land increased by 66.47% between 2002 and 2013 but reduced by 43.24% by 2020. Urban areas increased by 108.66% between 2002 and 2013 while by 2020 they had gained 42.19% additional land. It is concluded that the 2005–2025 Ogun State regional planning policy has so far been less than effective due to massive ecological change caused by urban expansion in the region.

Sustaining ex-mining lake-converted constructed wetlands as nature-based solutions: A comprehensive assessment of the carbon-water nexus in Paya Indah Wetlands, Malaysia

Water and carbon, essential for Earth's well-being, face imminent threats from human activities that fuel climate change. This study investigates nature-based solutions, focusing on the carbon-water nexus of ex-mining lake-converted constructed wetlands, specifically in Malaysia's Paya Indah Wetlands (PIW). Addressing research gaps, it assesses the ecosystem services of these wetlands, emphasising integrated evaluations for informed land management and employing a top-down conservation approach. Methodologically, spatial assessments, soil and water sampling, carbon quantification, water quality index calculations, land cover classification and stakeholder surveys were conducted. Results underscore the significant carbon sequestration and water quality improvement potential of constructed wetlands, with soil and sediment carbon accumulation reaching 1553.11 Mg C ha−1 (equivalent to 5700 Mg CO2 ha−1), translating to an annual sequestration capacity of 67.5 Mg C ha−1 year−1. Water quality index values ranged from 58 to 81 (Classes II to III). PIW's establishment led to a reduction of over 90% in barren land, with increases in water bodies (36%) and vegetation-covered land (38%), boosting wildlife populations by 30%. Spatial variations in organic carbon density and water quality underscore the complexity of the carbon-water nexus and its impacts on ecosystem health and water security. Despite land use changes, PIW demonstrates resilience, contributing to climate change mitigation. Stakeholder perceptions vary, emphasising the need for adaptive strategies. The study proposes transdisciplinary conservation initiatives and adaptive plans, stressing the pivotal role of ex-mining lake-converted constructed wetlands in enhancing climate resilience.

Investigating the impact of temperature on growth rate of the root rot fungus, Gymnopus fusipes.

Gymnopus fusipes is an understudied root rot pathogen associated with multiple tree species and is linked to episodes of oak decline across the United Kingdom and Europe. Although the reported distribution of G. fusipes is broad, many observations rely solely on visual identification of fruiting bodies, which can be unreliable, and lack confirmation by molecular and/or isolation data to verify this broad ecological range. Given the paucity of information regarding the true ecological distribution of G. fusipes, it is difficult to predict and model the potential distribution of the species under both current and future climate scenarios. In this study, to determine the growth capabilities of G. fusipes across a range of ecologically relevant temperatures, five geographically diverse isolates of G. fusipes were grown at five different temperatures ranging from 4-37°C, to determine the optimal temperature for G. fusipes growth, and to establish whether geographically diverse isolates exhibit local adaptation to temperature tolerance. Incubation temperature had a significant effect on G. fusipes growth rate, with 25°C representing the optimum (P<0.001). Isolates had differing growth rates at each of the temperatures, with an isolate from the UK having the highest overall growth rate across all five temperatures tested (P<0.001), and at the optimum, increased by a mean value of over 4915 mm2. Local adaptation to temperature tolerance was not found in the isolates tested. These data demonstrate the optimal incubation temperature for future laboratory studies on G. fusipes and provide the first data on the growth rate of this pathogen across ecologically relevant climate ranges that may inform land managers, modellers, and policy makers in predicting the current and potentially future geographical limits of this widespread root rot pathogen.

Influence of Morphometric Relief Parameters on Soil Depth Changes and Humus Horizon Thickness in Relation to Erosion-Accumulation Processes: A Study in the Ipeľská Pahorkatina Hills, Slovakia

Abstract This study examines the spatial distribution of soil types and their susceptibility to erosion and accumulation processes in a study area in Slovakia. Field research involving 71 probes identified various soil types, with Regosols and Cutanic Luvisols being predominant. The study found that erosion-accumulation processes were detected in 69.97% of the probes, with changes observed in soil horizons. Soil analysis revealed different relations between soil depth, humus thickness, and terrain characteristics such as slope, slope length, and slope length and steepness factor (LS factor). Specifically, we confirmed a moderately strong positive correlation between soil depth and humus thickness (r = 0.597, n = 71, p &lt; 0.001). Shallow soils (0–30 cm) exhibited a very strong positive correlation between soil depth and humus horizon thickness (r = 0.978, n = 33, p &lt; 0.001). Conversely, no relationship was found in moderately deep soils (30–60 cm) (r = 0.018, n = 14, p &lt; 0.948). For deep soils, we identified a moderately strong positive correlation (r = 0.345, n = 24, p = 0.098). While slope and slope length showed relationships with soil depth and humus thickness, the LS factor did not exhibit a clear correlation. These findings underscore the importance of understanding soil dynamics in informing land management practices, especially in areas susceptible to erosion. Recommendations include continued monitoring of eroded soils and implementing erosion control measures to maintain soil health and sustainability in agricultural production amidst climate change challenges.