Dense Cover Research Articles

Climate change ecological vulnerability and hotspot analysis of himalayan forests in North-Eastern region, India

The Himalayan forests are vulnerable to climate change leading to disturb the current flow of critical ecosystem services to the dependent population. Present study attempts to evaluate the current vulnerability status of major forest types in Nagaland, India due to climate change along with identifying the hot spots for mitigating the vulnerability of the forests. Vulnerability of mixed moist deciduous, pine, wet hill and wet temperate forests were evaluated using the IPCC framework. Local Moran's I analysis, hot spot analysis and a histogram analysis of the vulnerability were made in QGIS. Field data such as Shannon-Wiener Index and Importance Value Index along with secondary data such as edaphic factors, vegetation factors and climatic variables were used for vulnerability analysis. Analysis results that mixed moist deciduous forests had the highest area in under high-high clusters, hot spots and was highly vulnerable. The result suggests that very dense or moderately dense forest cover were less vulnerable than low density forests in the region. The study provides baseline information along with identification of vulnerable hot spot forests for future climate change policy and management of resources at the division level. The study suggests strengthening the less dense forests along with increasing the biodiversity through suitable strategy for mitigating the vulnerability.

Compost incorporation and wildflowers introduction for stormwater infiltration and erosion-control vegetation cover establishment in post-construction landscapes

Urban and suburban development frequently disturbs and compacts soils, reducing infiltration rates and fertility, posing challenges for post-development vegetation establishment, and contributing to soil erosion. This study investigated the effectiveness of compost incorporation in enhancing stormwater infiltration and vegetation establishment in urban landscapes. Experimental treatments comprised a split-split plot design of vegetation mix (grass, wildflowers, and grass-wildflowers) as main plot, ground cover (hydro-mulch and excelsior) as subplot, and compost (30% Compost and No-Compost) as sub-subplot factors. Wildflower inclusion was motivated by their recognized ecological benefits, including aesthetics, pollinator habitat, and deep root systems. Vegetation cover was assessed using RGB (Red-Green-Blue) imagery and ArcGIS-based supervised image classification. Over a 24-month period, bulk density, infiltration rate, soil penetration resistance, vegetation cover, and root mass density were assessed. Results highlighted that Compost treatments consistently reduced bulk density by 19–24%, lowered soil penetration resistance to under 2 MPa at both field-capacity and water-stressed conditions, and increased infiltration rate by 2–3 times compared to No-Compost treatments. Vegetation cover assessment revealed rapid establishment with 30% compost and 60:40 grass-wildflower mix, persisting for an initial 12 months. Subsequently, all treatments exhibited similar vegetation coverage from 13 to 24 months, reaching 95–100% cover. Compost treatments had significantly higher root mass density within the top 15 cm than No-Compost, but compost addition did not alter the root profile beyond the 15 cm depth incorporation depth. The findings suggest that incorporating 30% compost and including a wildflower or grass-wildflower mix appears to be effective in enhancing stormwater infiltration and provides rapid erosion control vegetation cover establishment in post-construction landscapes.

Outstanding Potential for Treating Wastewater from Office Buildings Using Fixed Activated Sludge with Attached Growth Process

The application of fixed activated sludge with an attached growth process (FASAG) with optimal operating conditions (hydraulic retention time (HRT) of 7 h, dissolved oxygen (DO) of 6 mg/L, and alkalinity dosage of 7.14 mgCaCO3/mgN-NH4+) treats wastewater generated from office buildings to meet discharge requirements (as per the regulation in the nation where the study was conducted) with typical parameters such as pH of 6.87–7.56, chemical oxygen demand (COD) of 32–64 mg/L, suspended solids (SS) of 8–11 mg/L, N-NH4+ of 1–7 mg/L, and denitrification efficiency reaches 53%. In addition, the FASAG is an outstanding integration that makes both economic and environmental sense when applied in local wastewater treatment systems. In particular, this process combines aerobic and anoxic processes in a creation tank. This explains why this approach can save investment and operating costs, energy, and land funds. In office building regions, where land area is frequently limited, saving land funds presents numerous options to enhance the density of green cover. Furthermore, as a new aspect, investing in reusing wastewater after treatment to irrigate plants or flush toilets in office buildings contributes to a decrease in the quantity of wastewater released into the environment, saving water resources and supporting sustainable development.

Modeling and spatialization of biomass and carbon stock using unmanned Aerial Vehicle Lidar (Lidar-UAV) metrics and forest inventory in cork oak forest of Maamora

Recently, the concerns about climate change have heightened the need for effective methods for estimating and mapping Biomass and Carbon stock at local, national, continental, and global scales. Reliable Biomass and Carbon stock quantification and spatialization is a challenge, especially in degraded Mediterranean Cork oak forest. To estimate and map Biomass (Btree−Total) and Carbon stock (Cst−total), we explored an improved approach using extracted metrics collected by Lidar-UAV (unmanned aerial vehicles Lidar), combined with forest inventory data. We approach three types of models for data analysis: Simple linear regression, multiple linear regressions, and stepwise multiple linear regression. The best Biomass and Carbon stock model fit is the Stepwise multiple linear regressions, involving the following metrics: maximum elevation, canopy cover and point cloud density and intensity. Our finding provides a quantification and spatialization Biomass and Carbon stock model based on Lidar-UAV metrics in Cork Oak Mediterranen forest and the results confirm the degraded state of Maamora Forest with a Biomass and Carbon stock relatively medium to low.

Levels of Land Cover Density on Carbon Reserves and Income in Dongo Baru Community Forest (HKm)

Community Forest (HKm) in Dongo Baru, Mount Rinjani forest area, in land management applies a mixed agroforestry pattern. The application of this pattern is the result of forest rehabilitation activities covering 138 ha in 2019. This HKm has a variety of different types of land management in one management area. This study aims to describe the condition of HKm using an environmental approach by estimating carbon stock data and economic value by looking at the value of arrive efficiency. The strategy utilized in this inquire about is graphic method by means of observation, Center Gather Discourse, and interviews, to 27 respondents / owners of land economic aspects by taking carbon stock data to 27 farmer-owned land. The environmental assessment to measure carbon stocks used a sample of 27 plots, measuring 50m x 20m for trees, 10m x 10m for poles, and 5m x 5m for saplings. The plots represent the density level of the forest area, i.e. dense, medium, not dense. Determination of forest density classification using Landsat-7 satellite image analysis in 2022. Based on the comes about within the ponder, it can be concluded that there are 3 density classifications that exist in the Dongo Baru HKm forest area, namely Meeting density, Moderately Meeting density and Not Meeting density. their respective incomes are meeting land density (Rp. 21,273,889), Moderately Meeting land density (Rp. 19,210,333) and Not Meeting land density (Rp. 22,431,556). Meeting land has carbon stock (256.86 tonnes/ha), Moderately Meeting land has carbon stock (95.34), and Not Meeting land has carbon stock (52.90 tonnes/ha). Land management with the density of Rapat land is considered to have fulfilled the principles of forest management from the economic and environmental aspects.

Organic Waste from the Management of the Invasive Oxalis pes-caprae as a Source of Nutrients for Small Horticultural Crops.

The management of invasive plants is a challenge when using traditional control methods, which are ineffective for large areas, leading to the abandonment of invaded areas and the subsequent worsening of the situation. Finding potential uses for waste resulting from invaders' management could motivate their control in the long-term, concurrently providing new bio-based resources with different applications. Oxalis pes-caprae is an invasive plant, widely distributed worldwide, which spreads aggressively through bulbils, creating a dense ground cover. This study was designed to assess the potential of Oxalis aboveground waste for use as fertilizer and in ameliorating deficit irrigation effects in growing crops. Diplotaxis tenuifolia (wild rocket) seedlings were planted in pots with soil mixed with Oxalis waste at 0, 2.2 and 4.3 kg m-2 or with commercial fertilizer, left to grow for 27 days and then irrigated at 100% or 50% field capacity for 14 days. The incorporation of the Oxalis waste improved the biomass, photosynthesis, sugars, total phenols and total antioxidant capacity in the crop, achieving commercial fertilization values, as well as increasing the phosphorus in soils. However, Oxalis waste seems not to directly affect plants' relative water contents. Our results support the use of Oxalis waste as fertilizer, which can encourage the long-term control of this invasive species.

Some traits of ecology and demography in settlements of the common hamster (<i>cricetus cricetus</i>, cricetidae, rodentia) under different levels of environmental comfort in a Simferopol city park

The spatial and demographic structure of two common hamster settlements was studied in two adjacent areas in a park of Simferopol City, Crimea, one differing in a lower vegetation storey (protective factor) while the other in the frequency of human visits (disturbance factor). We counted environmental comfort as the sum of scores (on a ten-point scale) of safe conditions (positive value) and disturbance factors (negative value). A strong positive relation was found between environmental comfort and the following characteristics of the settlements: (a) the number of burrows per area unit; (b) a nonrandom number of aggregative burrows; and (c) the percentage of juveniles in the population. The seldom visited places with a dense cover of grass and bushes appear to be the most favorable habitats, yet these are not typical of an urban landscape. However, it is those places that seem to serve as the sources that support the existence of hamster populations in less favorable city territories. Preservation of such places is one of the essential factors determining the survival of urban populations of the hamster.

The Effect of Land Cover Change on Soil Erosion in Awach Kibuon Sub-basin, Kenya

Land cover change is a significant driver of soil erosion. While soil erosion is a natural process, human activities can significantly alter the landscape, making soil more vulnerable to erosion. This erosion reduces a watershed's capacity to sustain vital natural resources and ecosystem services. This study investigated the impact of these changes on soil erosion within four hydrological units (Awach Kibuon, Awach Owade, Awach Kasipul, and Awach Kabondo) of the Awach Kibuon sub-basin between 2018 and 2023. The specific objective of the study was to quantify the effect of land cover change on soil erosion rate and determine how specific land cover types affect soil erosion in the study area. This study employed a quasi-longitudinal design to assess the influence of land cover changes on soil erosion. Sentinel-2 NDVI satellite imagery provided land cover data. The land cover maps, soil data, rainfall data and the Digital Elevation Model were used in the Revised Universal Soil Loss Equation Model within a GIS environment to estimate soil erosion rates. The study revealed a consistent decline in vegetation cover across all hydrological units, as indicated by a decrease in NDVI. The mean NDVI decreased by 12.88%, 10.92%, 4.78%, and 11.92% in Awach Kibuon, Awach Owade, Awach Kasipul and Awach Kabondo respectively. Conversely, the mean soil erosion rate increased by 23.9% in Awach Kibuon, 17.85% in Awach Owade, 24.43% in Awach Kasipul, and 20.54% in Awach Kabondo. Sediment yield increased by 33% in Awach Kibuon, 18% in Awach Owade, 17% in Awach Kasipul, and 23% in Awach Kabondo. These findings suggest a direct relationship between reduced vegetation and elevated soil erosion. The relationship between land cover and erosion varies depending on the density of vegetation. Areas with dense vegetation cover have an inverse relationship, highlighting the protective role of vegetation cover. However, the study also observed that very dense vegetation areas which were also found in high-sloped areas experienced high soil erosion rates. The erosion rate increases even in areas that have experienced an increase in vegetation cover. This is because these areas are also found in high-sloped areas. The slope factor superseded the ability of vegetation cover to protect against soil loss. In conclusion, the change in land cover has significantly increased soil erosion in the Awach Kibuon Sub-basin, however, the slope factor also accelerated soil loss in the basin. Therefore, a holistic approach that combines promoting vegetation cover with land management techniques like terracing and drainage channels is crucial for mitigating soil degradation and water sedimentation in sub-basin.

Livestock Detection and Counting in Kenyan Rangelands Using Aerial Imagery and Deep Learning Techniques

Accurate livestock counts are essential for effective pastureland management. High spatial resolution remote sensing, coupled with deep learning, has shown promising results in livestock detection. However, challenges persist, particularly when the targets are small and in a heterogeneous environment, such as those in African rangelands. This study evaluated nine state-of-the-art object detection models, four variants each from YOLOv5 and YOLOv8, and Faster R-CNN, for detecting cattle in 10 cm resolution aerial RGB imagery in Kenya. The experiment involved 1039 images with 9641 labels for training from sites with varying land cover characteristics. The trained models were evaluated on 277 images and 2642 labels in the test dataset, and their performance was compared using Precision, Recall, and Average Precision (AP0.5–0.95). The results indicated that reduced spatial resolution, dense shrub cover, and shadows diminish the model’s ability to distinguish cattle from the background. The YOLOv8m architecture achieved the best AP0.5–0.95 accuracy of 39.6% with Precision and Recall of 91.0% and 83.4%, respectively. Despite its superior performance, YOLOv8m had the highest counting error of −8%. By contrast, YOLOv5m with AP0.5–0.95 of 39.3% attained the most accurate cattle count with RMSE of 1.3 and R2 of 0.98 for variable cattle herd densities. These results highlight that a model with high AP0.5–0.95 detection accuracy may struggle with counting cattle accurately. Nevertheless, these findings suggest the potential to upscale aerial-imagery-trained object detection models to satellite imagery for conducting cattle censuses over large areas. In addition, accurate cattle counts will support sustainable pastureland management by ensuring stock numbers do not exceed the forage available for grazing, thereby mitigating overgrazing.

Evaluating pasture cover density mapping: a comparative analysis of Sentinel-2 and Spot-5 multispectral sensor images

Vegetation density extraction is influenced by the characteristics of satellite images, vegetation type, classification algorithm, and region, but there is little information about multispectral imaging (MSI). Studying the compatibility of the information content of sensors to replace sensors in areas where there is no easy access to their data is necessary for remote sensing (RS) studies. This study aims to assess the suitability of MSI from Sentinel-2 and Spot-5 satellites for generating pasture density maps. The Middle Kashkan watershed in the Lorestan Province of Iran was the study area. Geometric correction of the images was performed using ground control points (GCP) and the area's digital elevation model, achieving an accuracy of 0.21 pixels or better. Supervised classification techniques including parallelogram, minimal distance, maximum likelihood, and artificial neural network (ANN) algorithms were applied to the primary MSI of each satellite, as well as the integrated image of Spot-5 and the resulting pasture density map. Three density categories were considered: 5–25%, 25–50%, and over 50%. To validate the accuracy of the classification, a ground truth map of the region was created by interpreting a referenced official digital orthophotomosaic image at a scale of 1:40,000. Comparative analysis of the classified images revealed that the Sentinel-2 image with PCA-2-8 band composition and ANN classification algorithm yielded superior results, with an overall accuracy of 65.72% and a kappa coefficient of 0.08, compared to the Spot-5 image with PCA-3-1 band composition and the ANN classification algorithm. Spot-5 satellite images demonstrated greater effectiveness in generating pasture cover maps across the three density categories. These findings suggest that satellite images with suitable spatial and spectral resolution can be effectively utilized for generating accurate pasture density maps and monitoring long-term pasture preservation, particularly in regions characterized by high aerial photography altitudes in pasture areas. This approach holds the potential for effective pasture management and conservation efforts on a global scale.

Scarification under the canopy of Japanese oak: should pre-harvest treatment coincide with the masting year of acorns?

ABSTRACT The regeneration of Japanese oak (Quercus crispula Blume) has turned even more pressing in recent years. The pre-harvest treatment, which accumulates advanced seedlings, is essential for its natural regeneration in stands with a dense dwarf bamboo cover. Such pre-harvest treatment is considered particularly effective when done in conjunction with a mast year of acorns, but it is difficult to adjust the operation to specific timing. If there is no mast year for several years after the pre-harvest treatment, there is concern that the “priority effect” from other plant species may inhibit Japanese oak regeneration. The objective of this study was to determine whether scarification under the canopy of Japanese oaks, treated several years before the masting of acorns, is effective for its regeneration. Seedlings and vegetation were surveyed at sites scarified four years before (PRE) and just before masting (MAST) to compare the effects of treatments, i.e. differences in scarification years on the number and/or size of tall trees and other plant species. PRE could limit the predominance of dwarf bamboos and birches, and sufficient number of seedlings (>10 stems m−2) for future development was observed in the fifth year after masting. Since Japanese oak generally has a masting cycle of less than 5 years at most, we can conclude that the timing of pre-harvest treatment is not constrained by the masting year. Further studies are required to determine the details of priority effects of competitive plants on oak seedlings to establish a natural forest management for Japanese oak.

Urban Green Infrastructure Connectivity: The Role of Private Semi-Natural Areas

Green spaces and blue spaces in cities provide a wealth of benefits to the urban social–ecological system. Unfortunately, urban development fragments natural habitats, reducing connectivity and biodiversity. Urban green–blue infrastructure (UGI) networks can mitigate these effects by providing ecological corridors that enhance habitat connectivity. This study examined UGI connectivity for two indicator species in a rapidly developing city in the southern United States. We mapped and analyzed UGI at a high resolution (0.6 m) across the entire city, with a focus on semi-natural areas in private land and residential neighborhoods. Integrating graph theory and a gravity model, we assessed structural UGI networks and ranked them based on their ability to support functional connectivity. Most of the potential habitat corridors we mapped in this project traversed private lands, including 58% of the priority habitat for the Golden-cheeked Warbler and 69% of the priority habitat for the Rio Grande Wild Turkey. Riparian zones and other areas with dense tree cover were critical linkages in these habitat corridors. Our findings illustrate the important role that private semi-natural areas play in UGI, habitat connectivity, and essential ecosystem services.

Big Disaster from Small Watershed: Insights into the Failure and Disaster-Causing Mechanism of a Debris Flow on 25 September 2021 in Tianquan, China

The occurrence of debris flow events in small-scale watersheds with dense vegetation in mountainous areas that result in significant loss of life and missing individuals challenges our understanding and expertise in investigating and preventing these disasters. This has raised concerns about the occurrence of large debris flow disasters from small watersheds. This study focused on a catastrophic debris flow that took place in Longtou Gully (0.45 km2) in Tianquan County, Ya’an City on 25 September 2021, which resulted in 14 deaths and missing individuals. Through comprehensive field investigations, high-precision remote sensing data analyses, and numerical simulations, we analyzed the triggering mechanisms and dynamic processes of this event. Our results indicate that the convergence hollow at the channel head exhibited higher hydraulic conditions during rainfall compared to gentle slopes and convex terrains, leading to the instability of colluvial soil due to the expansion of the saturated zone near the soil–bedrock interface. The entrainment of material eroded from the channel resulted in an approximately 4.7 times increase in volume, and the channel scarp with a height of about 200 m amplified the destructive power of the debris flow. We emphasize the need to take seriously the possibility of catastrophic debris flows in small-scale watersheds, with colluvial deposits in hollows at the channel head under vegetation cover that serve as precursor material sources, and the presence of channel scarps formed by changes in the incision rate of the main river, which is common in the small watershed on both sides. This study provides insights for risk assessment of debris flows in small-scale catchments with dense vegetation cover in mountainous areas, highlighting the importance of vigilance in addressing disasters in small-scale catchments, particularly in regions with increasing human–environment conflicts.

Geospatial AI solution to monitor and mitigate increasing adverse ecological and hydrological impacts of climate change in Uttarakhand Himalaya (India).

Though climate change and its adverse ecological and geohydrological impacts are being experienced across the world in all types of ecosystems but as far as the Himalaya mountain ecosystem is concerned, the rate of climate change and subsequent impacts have reached an alarming stage due to anthropogenic and technogenic intervention on natural process and now need most effective and less time taking management strategy. Addressing this burning environmental problem, a geospatial artificial intelligence (GeoAI) technique-based case study is presented here from one of the most densely populated and urbanized regions of Himalaya mountain, viz Uttarakhand Himalaya, which is also called central Himalaya. The results of the study suggest that due to quite a high rate of climate change, the climatic zones shifting towards higher altitudes at the average rate of 5.6 2m/year, causing several adverse ecological impacts in terms of decreasing quality dense temperate forest cover (0.05%/year), snow cover (0.02%/year), water bodies (0.01%/year), agricultural land (0.31%/year), and horticultural land (0.01%/year). Conversion of these eco-friendly land use land cover into barren land, fallow land, and built-up land causes geohydrological consequences of climate change in terms of decreasing rainy days (1%/year), drying perennial springs (0.20%/year), perennial streams (0.11%/year), decreasing spring and stream discharge during non-monsoon season, increased extreme rainfall events (6-8%/year), and subsequent surface runoff during monsoon season. Further, the study advocates that the degraded geohydrological process has resulted in an increased frequency of disaster events (floods, cloudbursts, landslides. etc.) with a 3% (12 events) annual rate, causing great loss of environment, infrastructure, lives, and economy each year. Therefore, it has been very urgent to mitigate climate change and increase geohydrological disaster events through an integrated approach. Keep in view this, the present study proposed an integrated watershed management plan which is equally useful to be implemented across the Himalaya region and other similar ecosystems across the world.

Integrated remote sensing and geographic information system overlay analysis for groundwater potential evaluation using AHP and fuzzy AHP: Southern sections of the western Afar rift margin and associated rift floor

A persistent drought commonly affects the southern sections of the western Afar rift margin and the associated rift floor, leaving the populace concerned about their access to food. A comprehensive assessment and usage of the local groundwater resource is therefore essential to overcoming the ongoing drought and meeting the area's increasing demand for sustainable water. With the aid of RS, GIS, AHP, and Fuzzy AHP methods, this study aims to assess the area's groundwater potential. Lineament density, Geology,Topographic Wetness Index (TWI), Recharge, Slope, Land Use and Land Cover, Soil, and Drainage Density were created using GIS and RS techniques and are the thematic layers taken into consideration for this purpose. The weight of these themes for their relative significance to groundwater occurrence was determined using AHP and Fuzzy AHP (FAHP). Lineament density is the primary factor influencing the presence of groundwater, followed by geology, TWI, and recharge. The Very low (221.48 km2), Low (9084.46 km2), Moderate (8281.96 km2), High (1441.65 km2), and Very High (102.45 km2) groundwater potential zones (GWPZs) were delineated using the GIS-overlay analysis technique. The validation of the groundwater potential zone map was completed using the well discharge, transmissivity, and specific capacity, and the scatter plot demonstrated a strong connection with R2 values of 0.81, 0.79, and 0.80, respectively. The sensitivity index (SI) shows that lineament density and geology, which have SI values of 2.08% and 1.74%, respectively, have the greatest influence on the distributions of groundwater potentiality in the catchment, while drainage density has the least influence, with a SI value of −0.89%. By ensuring sustainable management and development, the study's findings will help with decision-making for the long-term supply of groundwater. Additionally, the approach utilized in the study can be applied to other comparable arid to semiarid regions.

Karakteristik Indeks Air Menggunakan Normalized Difference Water Index (NDWI) Pada DAS Negeri Rutong Kota Ambon

The objectives of this study are analyzing the transformation of the water content of the NDWI index and the spatial pattern of its mapping in the Rutong State Watershed of Ambon City and analyzing the influence of environmental attributes on spatial patterns of NDWI index water content. The results of the transformation of the NDWI index water content and the distribution pattern of the NDWI water content for the 2010-2022 period show that changes in the distribution of NDWI water content have shifted ways that extend to coastal areas towards the mainland. The difference between the watery area and the dry area around it is visible. High water content dominates with the water content of tree vegetation begins to experience decreasing changes. In contrast, low and moderate water content increases and spreads along the coast, moving towards land areas. The spatial distribution pattern of low and moderate NDWI water content extends from coastal and inland areas to hills and mountains. The results of the analysis of the influence of environmental attributes on the spatial pattern of the NDWI index water content showed that the results of the ANOVA F-count (36,051) were more significant than the F-table (2,479), indicating that the parameters of temperature, humidity, vegetation density and type of vegetation cover had a considerable influence simultaneously on the water content of the NDWI index at a significance level (0.000) smaller than α 0.05. The results of the partial test (t-test) show that the parameters of temperature, humidity, and vegetation density have a partially significant influence on the water content of the NDWI index. While the variable type of vegetation cover has an insignificant impact on water content, the NDWI index is at a significance level of α 0.05.

Assessing receptivity to malaria using case surveillance and forest data in a near-elimination setting in northeast Thailand

BackgroundThailand aimed to eliminate malaria by 2024, and as such is planning for future prevention of re-establishment in malaria free provinces. Understanding the receptivity of local areas to malaria allows the appropriate targeting of interventions. Current approaches to assessing receptivity involve collecting entomological data. Forest coverage is known to be associated with malaria risk, as an environment conducive to both vector breeding and high-risk human behaviours.MethodsGeolocated, anonymized, individual-level surveillance data from 2011 to 2021 from the Thai Division of Vector-Borne Disease (DVBD) was used to calculate incidence and estimated Rc at village level. Forest cover was calculated using raster maps of tree crown cover density and year of forest loss from the publicly available Hansen dataset. Incidence and forest cover were compared graphically and using Spearman’s rho. The current foci classification system was applied to data from the last 5 years (2017–2021) and forest cover for 2021 compared between the classifications. A simple risk score was developed to identify villages with high receptivity.ResultsThere was a non-linear decrease in annual cases by 96.6% (1061 to 36) across the two provinces from 2011 to 2021. Indigenous Annual Parasite Index (API) and approximated Rc were higher in villages in highly forested subdistricts, and with higher forest cover within 5 km. Forest cover was also higher in malaria foci which consistently reported malaria cases each year than those which did not. An Rc > 1 was only reported in villages in subdistricts with > 25% forest cover. When applying a simple risk score using forest cover and recent case history, the classifications were comparable to those of the risk stratification system currently used by the DVBD.ConclusionsThere was a positive association between forest coverage around a village and indigenous malaria cases. Most local transmission was observed in the heavily forested subdistricts on the international borders with Laos and Cambodia, which are where the most receptive villages are located. These areas are at greater risk of importation of malaria due to population mobility and forest-going activities. Combining forest cover and recent case surveillance data with measures of vulnerability may be useful for prediction of malaria recurrence risk.

Do protected areas enhance surface water quality across the Brazilian Amazon?

Protected Areas (PAs) are pivotal instruments in natural resource conservation and maintaining or enhancing ecosystem services, including hydrological functions. In the Amazon, the impact of PAs on the quality of river waters remains largely overlooked. Therefore, this study aims to evaluate whether Environmental Protected Areas (EPAs) and Indigenous Lands (ILs) efficiently protect the quality of surface waters in the Brazilian Amazon. Water quality variables from river gauge stations distributed across the lowlands Amazon are analyzed according to baseline river hydrogeochemistry classification, both inside and outside PAs. This study found that whitewater and clearwater rivers coursing within EPAs and ILs show lower turbidity and electrical conductivity compared to those outside PAs, likely due to the buffering effect of dense forest cover within protected landscapes. Moreover, data indicate that protected areas enhance the water quality from upstream unprotected landscapes in the Brazilian Amazon. These results highlight the need to further invest on effective mechanisms of water resource conservation across lowland tropical regions, and particularly in the Earth’s largest watershed.

Efficacy of invasive plant control depends on timing of herbicide application and invader soil seedbank density

Understanding the underlying temporal dynamics influencing invasive plant control outcomes is essential to achieve restoration and land management goals. Within grasslands, herbicides are commonly used as the main method for invasive plant control, but the efficacy of management may be dependent on seasonal dynamics, as well as the number of applications. Additionally, assessments to quantify invasive plant control are often limited to aboveground plant composition, overlooking the potential repository of propagules stored in the soil seedbank, and additional impacts on nontarget species. To ensure that an herbicide method is effectively controlling invader populations, while limiting impacts on the resident plant communities, both above‐ and belowground species responses must be assessed. We established an herbicide field experiment across different sites and years in Riverside, CA, U.S.A., to assess the control of a global annual invasive forb, Oncosiphon pilulifer. We investigated how seasonal herbicide management (early‐season vs. late‐season) and repeated annual herbicide applications (1 vs. 2 years) influenced cover and seedbank density of our focal invader and the resident plant community 1 year after treatment. We found that although late‐ and early‐season‐applied herbicides reduced invader cover, early‐season applications were the only strategy to reduce invader seedbank density, indicating potential longer term management control. Lastly, native cover was limited in post‐treated areas, suggesting that additional management strategies may be needed to overcome native establishment limitations in invaded grasslands.

Modelling of Granular Sediment Transport in Steady Flow over a Mobile Sloped Bed

This paper introduces a three-layer system, proposing a comprehensive model of granular mixture transport over a mobile sloped bed in a steady flow. This system, consisting of the bottom, contact, and upper zones, provides complete, continuous sediment velocity and concentration vertical profiles. The aim of this study is to develop and experimentally verify this model for sediment transport over a bottom locally sloping in line with or opposite the direction of sediment flow. The model considers gravity’s effect on sediment transport in the bottom (dense) layer when the component of gravity parallel to the bottom acts together with shear stresses associated with water flow. This is a crucial factor often overlooked in previous studies. This effect causes an increase in velocity in the mobile sublayer of the dense layer and significantly affects the vertical distributions of velocity and concentration above this layer. The proposed shear variation due to the interaction between fractions and an intensive sediment mixing and sorting process over a mobile sloped bed adds to the novelty of our approach. The data sets used for the model’s validation cover various conditions, including slopes, grain diameters, densities, and grain mobility conditions, from incipient motion to a fully mobilized bed. This extensive validation process instils confidence in the theoretical description and its applicability to real-world scenarios in the design of hydraulic infrastructure, such as dams, barrages, bridges, and irrigation, and flood control systems.