Conventional Survey Techniques Research Articles

A COMPUTATIONAL ANALYSIS OF IDEOLOGICAL POSITIONS, EMOTIONAL STANCE, AND SUPPORT FOR PRESIDENTIAL CANDIDATES IN TURKEY

Using artificial intelligence, this article explores the intricate dynamics between ideologies, emotions, and political preferences of the electorate in Turkey. Utilizing a dataset of one billion posts from X (formerly Twitter), the study maps out political opinions, focusing on support for presidential candidates, ideological stances, and collective emotions around the pivotal 2023 Turkish presidential elections. We discuss the limitations of conventional survey techniques and introduce an ERC‐funded Politus project that processes digital trace data to offer timely insights into social and political trends. The study's findings, particularly around the “prayer rug (seccade) crisis,” underscore the complexity of electoral politics and the potential of digital trace data in capturing the evolving sentiments and ideological orientations of voters. Through this computational approach, the research provides a granular depiction of Turkey's ideological map and electoral behavior, contributing significantly to the discourse on political analysis in the digital era.

Label-free and highly sensitive detection of aflatoxin B1 by Ag IANPs via surface-enhanced Raman spectroscopy

Aflatoxin B1 (AFB1), a pernicious constituent of the aflatoxin family, predominantly contaminates cereals, oils, and their derivatives. Acknowledged as a Class I carcinogen by the World Health Organization (WHO), the expeditious and quantitative discernment of AFB1 remains imperative. This investigation delineates that aluminum ions can precipitate the coalescence of iodine-modified silver nanoparticles, thereby engendering hot spots conducive for label-free AFB1 identification via Surface-Enhanced Raman Spectroscopy (SERS). This methodology manifests a remarkable limit of detection (LOD) at 0.47 fg/mL, surpassing the sensitivity thresholds of conventional survey techniques. Moreover, this method has good anti-interference ability, with a relative error of less than 10% and a relative standard deviation of less than 6% in quantitative results. Collectively, these findings illuminate the substantial application potential and viability of this approach in the quantitative analysis of AFB1, underpinning a significant advancement in food safety diagnostics.

Land use Change Detection Methodologies and Techniques for Remotely Sensed Images

The increasing land use changes leading to urban expansion have attracted the researches. Urbanization has become a recent growing trend in many cities around the world. In most cases to estimate the urban expansion with the conventional survey and mapping techniques is expensive and time consuming. Remote sensing is increasingly used for detection and analysis of urban expansion since it is cost effective and technologically efficient. This paper aims to give the taxonomy of various methods and techniques to analyze the land use change detection through remote sensing images in an effective manner. One of the most important functions of remote sensing data is Land Use and Land Cover maps managed through image classification. This describes the various classifiers, software and image digitization techniques that are used in estimating the urban changes. Wide database of images has been used to test the algorithms. Hence, an in-depth study of existing work related to land use change detection will help to accelerate research in the field of urban change. This paper presents a systematic analysis of work done in land use change detection area. We also present a Comparison of existing methods and techniques used for land use change detection. Based on this analysis, we finally presented a few future research directions related to land use change detection through remote sensing images, which will be reduce uncertainties in the image-processing chain to improve classification accuracy.

An Advanced Software Platform and Algorithmic Framework for Mobile DBH Data Acquisition

Rapid and precise tree Diameter at Breast Height (DBH) measurement is pivotal in forest inventories. While the recent advancements in LiDAR and Structure from Motion (SFM) technologies have paved the way for automated DBH measurements, the significant equipment costs and the complexity of operational procedures continue to constrain the ubiquitous adoption of these technologies for real-time DBH assessments. In this research, we introduce KAN-Forest, a real-time DBH measurement and key point localization algorithm utilizing RGB-D (Red, Green, Blue-Depth) imaging technology. Firstly, we improved the YOLOv5-seg segmentation module with a Channel and Spatial Attention (CBAM) module, augmenting its efficiency in extracting the tree’s edge features in intricate forest scenarios. Subsequently, we devised an image processing algorithm for real-time key point localization and DBH measurement, leveraging historical data to fine-tune current frame assessments. This system facilitates real-time image data upload via wireless LAN for immediate host computer processing. We validated our approach on seven sample plots, achieving bbAP50 and segAP50 scores of: 90.0%(+3.0%), 90.9%(+0.9%), respectively with the improved YOLOv5-seg model. The method exhibited a DBH estimation RMSE of 17.61∼54.96 mm (R2=0.937), and secured 78% valid DBH samples at a 59 FPS. Our system stands as a cost-effective, portable, and user-friendly alternative to conventional forest survey techniques, maintaining accuracy in real-time measurements compared to SFM- and LiDAR-based algorithms. The integration of WLAN and its inherent scalability facilitates deployment on Unmanned Ground Vehicles (UGVs) to improve the efficiency of forest inventory. We have shared the algorithms and datasets on Github for peer evaluations.

A hierarchical modelling framework for estimating individual‐ and population‐level reproductive success from movement data

Abstract Rapidly advancing animal telemetry technologies paired with new statistical models can provide insight into the behaviour of otherwise unobservable free‐living animals. Changes in behaviour apparent from pairing telemetry with statistical models often occur as animals undertake key life‐history activities, such as reproduction. For many species that are secretive or occupy remote areas, these life‐history events are difficult to detect with conventional survey techniques, and consequently, vital rates are difficult to estimate. We present a hierarchical modelling framework, which integrates movement data observed via animal‐borne telemetry and optional, infrequent survey data, to estimate individual‐ and population‐level reproductive success. The approach combines a mechanistic movement model and survival model, and allows for assessing the effects of hypothesized individual and environmental covariates on reproductive success. We first tested our approach with simulated data, and then applied it to movement data from migratory golden eagles (Aquila chrysaetos) breeding in southcentral Alaska across four breeding seasons. We show that results supported our biological hypotheses that changes in movement coincided with the timing of reproductive failures, and that changes in movement could be used to assess breeding success (and failure) at the individual and population levels. The analysis also provided evidence of inter‐annual variation in population‐level nest success and the timing of nesting failures. This new approach is adaptable to many species that care for young and can be tracked with telemetry devices, and can provide not only individual‐level information useful for testing ecological hypotheses, but estimates of demographic parameters that can directly inform conservation and management if tagged animals are representative of the population.

EDNA metabarcoding of avocado flowers: 'Hass' it got potential to survey arthropods in food production systems?

In the face of global biodiversity declines, surveys of beneficial and antagonistic arthropod diversity as well as the ecological services that they provide are increasingly important in both natural and agro-ecosystems. Conventional survey methods used to monitor these communities often require extensive taxonomic expertise and are time-intensive, potentially limiting their application in industries such as agriculture, where arthropods often play a critical role in productivity (e.g. pollinators, pests and predators). Environmental DNA (eDNA) metabarcoding of a novel substrate, crop flowers, may offer an accurate and high throughput alternative to aid in the detection of these managed and unmanaged taxa. Here, we compared the arthropod communities detected with eDNA metabarcoding of flowers, from an agricultural species (Persea americana-'Hass' avocado), with two conventional survey techniques: digital video recording (DVR) devices and pan traps. In total, 80 eDNA flower samples, 96 h of DVRs and 48 pan trap samples were collected. Across the three methods, 49 arthropod families were identified, of which 12 were unique to the eDNA dataset. Environmental DNA metabarcoding from flowers revealed potential arthropod pollinators, as well as plant pests and parasites. Alpha diversity levels did not differ across the three survey methods although taxonomic composition varied significantly, with only 12% of arthropod families found to be common across all three methods. eDNA metabarcoding of flowers has the potential to revolutionize the way arthropod communities are monitored in natural and agro-ecosystems, potentially detecting the response of pollinators and pests to climate change, diseases, habitat loss and other disturbances.

Taking eDNA underground: Factors affecting eDNA detection of subterranean fauna in groundwater.

Stygofauna are aquatic fauna that have evolved to live underground. The impacts of anthropogenic climate change, extraction and pollution on groundwater pose major threats to groundwater health, prompting the need for efficient and reliable means to detect and monitor stygofaunal communities. Conventional survey techniques for these species rely on morphological identification and can be biased, labour-intensive and often indeterminate to lower taxonomic levels. By contrast, environmentalDNA (eDNA)-based methods have the potential to dramatically improve on existing stygofaunal survey methods in a large range of habitats and for all life stages, reducing the need for the destructive manual collection of often critically endangered species or for specialized taxonomic expertise. We compared eDNA and haul-net samples collected in 2020 and 2021 from 19 groundwater bores and a cave on Barrow Island, northwest Western Australia, and assessed how sampling factors influenced the quality of eDNA detection of stygofauna. The two detection methods were complementary; eDNA metabarcoding was able to detect soft-bodied taxa and fish often missed by nets, but only detected seven of the nine stygofaunal crustacean orders identified from haul-net specimens. Our results also indicated that eDNA metabarcoding could detect 54%-100% of stygofauna from shallow-water samples and 82%-90% from sediment samples. However, there was significant variation in stygofaunal diversity between sample years and sampling types. The findings of this study demonstrate that haul-net sampling has a tendency to underestimate stygofaunal diversity and that eDNA metabarcoding of groundwater can substantially improve the efficiency of stygofaunal surveys.

Use of UAV Monitoring to Identify Factors Limiting the Sustainability of Stream Restoration Projects

The detection and mapping of riverscapes with Unmanned Aerial Vehicles (UAVs, drones) provide detailed, reliable, and operable spatial information in hydrological sciences, enhancing conventional field survey techniques. In this study, we present the results of long-term, optical RGB (red, green, blue) UAV monitoring of stream restoration projects to identify the positive and negative features that affect their sustainability. We determined quantitative and qualitative aspects of restoration, such as the restoration effect, the dynamics of fluvial processes, hydrological connectivity, and riparian vegetation. The study was based on six years of UAV monitoring in three restored streams in Prague, Czech Republic. The multitemporal riverscape models from the photogrammetric reconstruction served as a basis for the visual assessment, compliant with the standard hydromorphological assessment. Such a combined approach extends the potential of UAV monitoring by allowing for the use of existing classification schemes and data and the objective detection of critical features. The study pointed to the significant discrepancies in channel geometry between the planned restorations and realized restorations in all assessed projects as a general phenomenon. Multitemporal, optical RGB UAV monitoring then detected issues in qualitative aspects that limit restoration quality, such as water overuse, extensive eutrophication, or inefficient riparian shading.

INTEGRATING GEOSPATIAL TECHNIQUES AND UAS TECHNOLOGY TO UPDATE LIDAR DTM FOR FLOOD MODELING IN LAS NIEVES, AGUSAN DEL NORTE, PHILIPPINES

Abstract. The Digital Terrain Model (DTM) is essential in generating the topographic structure of an area by eliminating its external features. Conventional survey techniques are still employed to obtain accurate geographic data on the earth's surface. However, accurate land surveys are now achievable because of the development of Unmanned Aerial Vehicles (UAVs). This study aims to update the LiDAR DTM for Flood Modeling in Las Nieves, Agusan del Norte, using GNSS and UAS integration. The Static GNSS survey was carried out to collect precise points for the direct georeferencing of the DJI Phantom 4 GNSS-RTK UAV. There is a continuous investigation of the influence of flight parameters in creating DTM. Hence, this study also evaluates the effects of overlap percentage and flight altitude on the quality of the generated DTM. There were 16 flight plans prepared using various combinations of flight parameters. The UAS data collected was processed using the Structure from Motion. The quality of the DTM was assessed based on its accuracy and level of completeness to identify the optimal parameters for generating the data model. Based on the results of the accuracy and completeness of the DTMs, the optimal parameters for generating are 90% and 120 meters. Subsequently, the UAS-based DTM generated using this combination of flight parameters was utilized in updating the existing DTM of Las Nieves to create the flood model of the area. The flood model was generated using the hydrologic and hydraulic modeling of the HEC RAS Mapper.

Reconstructing social mixing patterns via weighted contact matrices from online and representative surveys

The unprecedented behavioural responses of societies have been evidently shaping the COVID-19 pandemic, yet it is a significant challenge to accurately monitor the continuously changing social mixing patterns in real-time. Contact matrices, usually stratified by age, summarise interaction motifs efficiently, but their collection relies on conventional representative survey techniques, which are expensive and slow to obtain. Here we report a data collection effort involving over 2.3% of the Hungarian population to simultaneously record contact matrices through a longitudinal online and sequence of representative phone surveys. To correct non-representative biases characterising the online data, by using census data and the representative samples we develop a reconstruction method to provide a scalable, cheap, and flexible way to dynamically obtain closer-to-representative contact matrices. Our results demonstrate that although some conventional socio-demographic characters correlate significantly with the change of contact numbers, the strongest predictors can be collected only via surveys techniques and combined with census data for the best reconstruction performance. We demonstrate the potential of combined online-offline data collections to understand the changing behavioural responses determining the future evolution of the outbreak, and to inform epidemic models with crucial data.

Evaluating the effectiveness of drones for quantifying invasive upside-down jellyfish (Cassiopea sp.) in Lake Macquarie, Australia.

Upside-down jellyfish (Cassiopea sp.) are mostly sedentary, benthic jellyfish that have invaded estuarine ecosystems around the world. Monitoring the spread of this invasive jellyfish must contend with high spatial and temporal variability in abundance of individuals, especially around their invasion front. Here, we evaluated the utility of drones to survey invasive Cassiopea in a coastal lake on the east coast of Australia. To assess the efficacy of a drone-based methodology, we compared the densities and counts of Cassiopea from drone observations to conventional boat-based observations and evaluated cost and time efficiency of these methods. We showed that there was no significant difference in Cassiopea density measured by drones compared to boat-based methods along the same transects. However, abundance estimates of Cassiopea derived from scaling-up transect densities were over-inflated by 319% for drones and 178% for boats, compared to drone-based counts of the whole site. Although conventional boat-based survey techniques were cost-efficient in the short-term, we recommend doing whole-of-site counts using drones. This is because it provides a time-saving and precise technique for long-term monitoring of the spatio-temporally dynamic invasion front of Cassiopea in coastal lakes and other sheltered marine habitats with relatively clear water.

High-Resolution Vertical Habitat Mapping of a Deep-Sea Cliff Offshore Greenland

Recent advances in deep-sea exploration with underwater vehicles have led to the discovery of vertical environments inhabited by a diverse sessile fauna. However, despite their ecological importance, vertical habitats remain poorly characterized by conventional downward-looking survey techniques. Here we present a high-resolution 3-dimensional habitat map of a vertical cliff hosting a suspension-feeding community at the flank of an underwater glacial trough in the Greenland waters of the Labrador Sea. Using a forward-looking set-up on a Remotely Operated Vehicle (ROV), a high-resolution multibeam echosounder was used to map out the topography of the deep-sea terrain, including, for the first time, the backscatter intensity. Navigational accuracy was improved through a combination of the USBL and the DVL navigation of the ROV. Multi-scale terrain descriptors were derived and assigned to the 3D point cloud of the terrain. Following an unsupervised habitat mapping approach, the application of a K-means clustering revealed four potential habitat types, driven by geomorphology, backscatter and fine-scale features. Using groundtruthing seabed images, the ecological significance of the four habitat clusters was assessed in order to evaluate the benefit of unsupervised habitat mapping for further fine-scale ecological studies of vertical environments. This study demonstrates the importance of a priori knowledge of the terrain around habitats that are rarely explored for ecological investigations. It also emphasizes the importance of remote characterization of habitat distribution for assessing the representativeness of benthic faunal studies often constrained by time-limited sampling activities. This case study further identifies current limitations (e.g., navigation accuracy, irregular terrain acquisition difficulties) that can potentially limit the use of deep-sea terrain models for fine-scale investigations.

Toposequent Effect on Soil Morphology and Classification of Ultisol Soil in the Ayer Hitam Forest Reserve, Peninsular Malaysia

Morphology in forest soils has developed over a long time due to the non-intensive management of forest soils. Damage to forest soil occurs when there is logging activity, fire, or land use change. Some forest was used as productive land for example agroforestry and forest production. As with landuse in agriculture, intensive management of forests can also reduce soil productivity. Inaccuracy forest land use would cause environmental or economic damage, so basic soil management data in forest areas is needed. However, the soil morphology of the Ayer Hitam Forest Reserve (AHFR) in Malaysiahas never been observed. The objective of this study is to assess the soil characteristic and soil morphological properties of theAHFR. Studying the characteristics of soil morphology in toposequent conditions is necessary to find out the differences in soil from different heights and the effects of erosion, transportation, and deposition on the soil. This study was conducted in the AHFR, Puchong, Selangor Darul Ehsan, Peninsular Malaysia. Mapping of the area under investigation was carried out by conventional soil survey techniques with a physiographic approach using maps with a scale of 1:30,000. The results showed that AHFRhas some different soil morphological characteristics and classification in subgroupamong five different slope positions with similar soil order, which is a Ultisol soil. The soil in the AHFRis formed from highly weathered soil due to high rainfall in this location.The results of this study are important for soil development, identification management, and land use priority such as erosion control on steep-slope forest areas, regeneration and reforestation, and it can also be used for forest education, practice, research, and training activities.Keywords: Ayer Hitam Forest Reserve, forest soil, soil morphology, toposequent, Ultisol soil

The applicability of eDNA metabarcoding approaches for sessile benthic surveying in the Kimberley region, north‐western Australia

AbstractThe application of environmental DNA technologies is a promising new approach to rapidly audit biodiversity across large‐scale, remote regions. Here, we examine the efficacy of a dual‐assay eDNA metabarcoding approach for sessile benthic bioassessments in the turbid waters of the Lalang‐garram marine parks, Kimberley, north‐western Australia. We ask three principal questions: (1) “Is the eDNA released by sessile benthic taxa (i.e., hard and soft corals, sponges and tunicates) locally detectable?”, (2) “What level of taxonomic resolution is afforded by eDNA metabarcoding using the ITS2 region?”, and (3) “How well does eDNA metabarcoding compare to conventional benthic survey techniques?”. We report that a dual‐assay eDNA metabarcoding approach can detect approximately 70% of the local benthic taxa (i.e., at a species, genus level). It is, however, not as effective at the individual/population level, detecting only approximately 40% of unique amplicon sequence variant (ASV) signals released by an array of individual benthic organisms at the surveyed locations. In examining the efficacy and resolution of the applied ITS2 metabarcoding markers for bioassessments, we report large gaps in the variety of publicly available benthic ITS2 reference sequence data, limiting our ability to provide robust taxonomic assignments. These findings highlight the need to extend ITS2 databases for greater regional representation. Until this is adequately addressed, we recommend that investigating taxonomic assignments to a genus level is the most robust approach for benthic monitoring using eDNA. Lastly, we found eDNA metabarcoding and conventional belt transect surveys each detected numerous unique hard coral genera, indicating that a combined approach provides the most effective way to audit benthic biodiversity. This point notwithstanding, eDNA metabarcoding had the power to distinguish similar diversity trends between sites to that determined by the belt transect methodology, validating the application of eDNA metabarcoding as either a stand‐alone, or complementary technique for assessing sessile benthic taxa.

Applied gamma-ray spectrometry for evaluating tropical soil processes and attributes

Geophysical methods, such as gamma-ray spectrometry, have great potential to enhance knowledge of the pedosphere (pedogenesis, pedogeochemistry and pedogeomorphology), helping to predict tropical soil attributes. We applied proximal gamma-ray spectrometry to evaluate tropical landscape dynamics, pedogenesis and spatial distribution of radionuclides and selected soil attributes. This study was carried out in southeast Brazil, where 79 soil samples (0–20 cm) along transects were collected to perform physical-chemical analysis coupled with collection of surface gamma-ray spectrometric data, allowing the detection of the radionuclides uranium (U238), thorium (Th232), and potassium (K40). Additionally, we analyzed soils in four toposequences, with varying lithology, relief, and hydrology. The radionuclide concentrations in soils showed a direct relationship with the parent material composition, either rocks or sediments. Weathering degree and the geochemical behavior of each radionuclide determines its permanence or removal in soils. Denudation processes along the toposequences also influence the distribution of radionuclides. On one hand, the radionuclide contents of mature, weathered soils are closely associated with advanced pedogenesis, with a higher clay contents and argic horizon formation, whereas in younger, less weathered soils the parent material exerts a greater influence than pedogenesis. Uranium decreased with altitude, and showed greater mobility compared with thorium. Thorium presented a higher correlation with clay content, and the opposite with sand content. Potassium detection increased with soil cation exchange capacity (CEC) and clay content. Gamma-spectrometry detected significant variations in some segments along the toposequences, undetectable by conventional soil survey techniques. This may indicate changes from one soil class to another or the continuity of a particular soil class, demonstrating the potential of this tool in digital soil mapping, pedogeochemical, pedogeomorphological and pedogenesis processes studies.

A novel ‘triple drawdown’ method highlights deficiencies in invasive alien crayfish survey and control techniques

Abstract Freshwater crayfish can be successful invaders that threaten native biota and aquatic ecosystems in numerous countries worldwide. Nonetheless, the inability of conventional crayfish survey techniques like trapping and handsearching to yield quantitative population data has limited the understanding of crayfish invasion biology and associated ecological impacts. Here, we employed a novel ‘triple drawdown’ (TDD) method to sample invasive populations of signal crayfish Pacifastacus leniusculus in a headwater stream in Northern England. The method was compared with conventional techniques of trapping and handsearching. The TDD method proved to be an effective technique with high capture efficiency, reporting signal crayfish densities from 20.5 to 110.4 animals/m2 at our study sites. These numbers exceed any previous estimates for similar streams. The TDD showed the vast majority of individuals across all sites were juvenile or sub‐adult (<26 mm CL), with only 2.3% of the population large enough (≥35 mm CL) to be caught in standard traps. Synthesis and applications. The triple drawdown (TDD) method demonstrates strong inefficiencies and biases in conventional crayfish survey and management techniques. Trapping is not recommended for representative sampling or control of juvenile dominated populations. TDDs, which can be adapted and modified to operate in multiple habitat types and freshwater systems, generate robust quantitative data on invasive crayfish population demographics in situ. This can advance our understanding of the biology of an important invader of freshwater systems around the world. Obtaining this data prior and post‐intervention is fundamental to evaluate invasive crayfish management, and we recommend the TDD method to assess the effectiveness of future control measures.

Broadcasting Regional Call Dialects Has Little Influence on the Effectiveness of Call-Broadcast Surveys for Marsh Birds

Emergent wetlands have declined in North America and, in response, many wetland-dependent animals have declined in abundance. For example, many species of secretive marsh birds in North America have declined during the last century. However, estimates of population decline and efforts to assess the effects of management actions are hampered because marsh birds are difficult to detect using conventional survey techniques. Call-broadcast surveys can improve detection probability of marsh birds; however, the effectiveness of call-broadcast varies regionally for some marsh birds, which might reflect differential responsiveness to call dialects. Here, we evaluated differential responses by least bitterns (Ixobrychus exilis) and clapper rails (Rallus crepitans) to different call dialects by using 679 paired call-broadcast surveys in Florida and South Carolina. We detected similar numbers of least bitterns and clapper rails responding to the different call dialects, except in Florida, where least bitterns responded more frequently to a more-distant (Louisiana) dialect than a more-local (Florida) dialect. Our results suggest that, at least for clapper rails and least bitterns, it may not be necessary to incorporate regional call dialects into standardized surveys. However, additional research is needed in more regions of North America and with other species.

Investigation of Highway Stormwater Management Pond Capacity for Flood Detention and Water Quality Treatment Retention via Remote Sensing Data and Conventional Topographic Survey

Stormwater management ponds are common best management practice (BMP) and green infrastructure (GI) for flood attenuation and water quality treatment in highway projects. Originally designed to provide storage volume for flood detention, stormwater ponds today often employ additional retention volume at pond bottom in a hope to improve water quality via sedimentation and other pollutant-removal mechanisms. It is commonly assumed that sediment accumulation and topographic variations (such as erosion, channelization, and in-pond plant growth and decay) over time often decrease the capacity of stormwater ponds. However, differences between design capacities and field capacities over time have never been verified and quantitatively analyzed before. This study presents such analysis using conventional topographic survey techniques and remote sensing data (topographic light detection and ranging digital elevation model [LIDAR DEM]) for 10 highway stormwater ponds along Interstate Highway-95 (I-95) systems in Baltimore City, Cecil County, and Harford County, Maryland, United States, with facility service life ranging from 14 to 26 years (1990–2015). Data derived from LIDAR DEM were compared with those from topographic survey; the LIDAR DEM data appear to be effective in measuring flood detention capacities and identifying silted ponds, but not in estimating the remaining retention volume for water quality treatment. Data from topographic survey indicate that the total volume in the ponds was relatively unchanged compared with the design, with increases in some instances. The increase typically occurred at the pond’s upper stages. Nonetheless, the water quality treatment capacity at pond bottom (wet pool volume) was drastically less (up to 100% of the design). As current maintenance practice of stormwater ponds relies heavily on visual inspection, the storage volume variations are often overlooked. As such, the findings prompt uncertainty on the long-term effectiveness of watershed implementation plan and models in the Chesapeake Bay watersheds, as many of them depend on wet pool volume design in BMP and GI.

Detection of freshwater mussels (Unionidae) using environmental DNA in riverine systems

AbstractEnvironmental DNA (eDNA) methods are being developed for use in conservation biology to improve upon conventional species survey techniques. Validation of eDNA methods in different environmental contexts is required if they are to be widely adopted. One potential application of eDNA methods is for the detection of freshwater mussels (Bivalvia: Unionidae), which are among the most imperiled species in North America. Conventional unionid survey methods are highly invasive and can be difficult to conduct due to issues with morphological identification and their cryptic use of habitat. eDNA methods can potentially provide a non‐invasive, extremely specific, and highly sensitive alternative. Here, we examine the effectiveness of eDNA methods at detecting an imperiled unionid, the wavy‐rayed lampmussel (Lampsilis fasciola), in lotic systems with moderate discharge. We developed a novel qPCR assay for the detection of L. fasciola eDNA, which included a custom internal positive control to check for PCR inhibition. We used different experimental densities of caged L. fasciola specimens as a point source of eDNA within two rivers of the Grand River watershed in Southern Ontario. Sampling occurred at set distances downstream of the cage using purpose‐built sampling equipment. Detection was obtained at the cage (i.e., point of eDNA shedding) but not downstream at distances ≥10 m during stream discharges of approximately 1,632–2,332 L/s. The results indicate that eDNA is diluted rapidly in rivers with moderate discharge and that high‐resolution spatial sampling efforts may be necessary to obtain meaningful eDNA‐based distribution data of unionids, and other sessile organisms, present at low density in lotic systems.

Stocking and over-the-counter sale of misoprostol for medical abortion in Ghana's community pharmacies: comparison of questionnaire and mystery client survey.

In many sub-Saharan African countries with restricted safe abortion services, community pharmacies are important sources of abortifacients. However, data on stocking and over-the-counter sale of abortifacients in community pharmacies are often limited. The main objective of this study was to compare stocking and over-the-counter sale of misoprostol at community pharmacies using questionnaire and mystery client surveys in Ghana. A cross-sectional questionnaire-based survey, complemented with a mystery client survey, was conducted at 165 randomly selected community pharmacies in Accra, Ghana. Structured questionnaires were administered to pharmacists/pharmacy workers. A mystery client survey to each of these pharmacies was also undertaken. Descriptive statistical techniques (frequencies and proportions) were used to estimate and compare stocking and over-the-counter sale of misoprostolat community pharmacies from the two data collection methods. Some 50.3% (83) of community pharmacists/pharmacy workers reported stocking misoprostol and selling it over-the-counter for medical abortion in the questionnaire-based survey. However, in the mystery client survey, 122 (74%) pharmacists/pharmacy workers reported stocking misoprostol and actually selling it over-the-counter to the mystery clients. Thus approximately 39 (24%) more pharmacies stocked misoprostol and sold it over-the-counter even though they originally denied stocking the drug in the questionnaire survey. Also, the drug was often sold without a prescription, and many did so without asking for a confirmatory pregnancy test or gestational age. In contexts where access to safe abortion services is restricted, mystery client surveys, rather than conventional questionnaire-based survey techniques, may better illuminate stocking and over-the-counter sale of abortifacients at community pharmacies.