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The Missisquoi River originates in a densely forested, hilly, and lightly populated region in northern Vermont, USA, flowing north until it crosses the Canadian border. The upper American stretches of the river are federally designated as "Wild and Scenic" in recognition of its outstanding natural, cultural, and recreational values. This paper reports on the place-based and river-focused perspectives of rural residents who live and work along the Missisquoi River and its tributaries and who are the recipients of Vermont's shifting river management strategies. The mixed methods research drew on participant observation, interviews, and interpretations of photovisualizations (PVZs). The PVZ method identified the different geographical imaginaries held by residents and conservation professionals, demonstrating that PVZs can be used as a method to foster dialogue about sense of place and conservation initiatives. Visual aids can help unveil the complex, temporal relationships between landowners and the adjacent waterways, which in turn influence participation in river restoration efforts. [ABSTRACT FROM AUTHOR]

Soil process models such as RothC typically assume soil organic carbon (SOC) is in equilibrium at the beginning of each simulation run. This is not likely to be true in the real world, since recalcitrant SOC pools (notably, humified material) take many decades to re-stabilize after a land use change. The equilibrium assumption stems from a spinup method in which the model is run under a single land use until all SOC pools stabilize. To overcome this, we demonstrate an alternative spinup procedure that accounts for historical land use changes. The "steady-state" and "historical" spinup methods both impute unknown C inputs such that the modeled SOC matches empirical measurements at the beginning of the simulation and set initial SOC fractions. Holding all other parameters equal, we evaluated how each spinup affects SOC projections in simulations of agricultural land use change in the U.S. state of Vermont. We found that projected SOC trajectories for all land use scenarios are sensitive to the spinup procedure. These differences are due to disparities in imputed below-ground plant-derived carbon between the two procedures. Compared to the steady-state, imputed C in the historical spinup is higher for land uses that increase SOC (e.g., adoption of regenerative practices) and lower for land uses that decrease SOC (e.g., a transition from pasture to crops), due to the time window within which land use changes are assumed to have occurred. The novel historical spinup procedure captures important dynamics commonly missing in previous studies, representing an advancement in soil process modeling. [ABSTRACT FROM AUTHOR]

High-resolution digital elevation models (HR-DEMs) originating from airborne laser scanning (ALS) point clouds must be transformed into Culvert-modified DEMs for hydrological and geomorphological analysis. To produce a culvert-modified DEM, information on the locations of drainage structures (DSs) (e.g., bridges and culverts) is essential. Nevertheless, DS mapping techniques, whether in connection with the development of new methods or an application setting of existing methods, have always been complicated. Consequently, wide area DS data are rare, making it challenging to produce a culvert-modified DEM in a wide area capacity. Alternatively, the breach algorithm (BA) method is a standard procedure to obtain culvert-modified DEMs in the absence of DS data, solving the problem to some extent. This paper addresses this shortcoming using a newly developed drainage structure mapping algorithm (DSMA) for obtaining a culvert-modified DEM for an area of 36 km2 in Vermont, USA. Benchmark DS data are used as a standard reference to assess the performance of the DSMA method compared to the BA method. A consistent methodological framework is formulated to obtain a culvert-modified DEM using DS data, mapped using the DSMA and resultant culvert-modified DEM is then compared with BA method respectively. The DSs found from the culvert-modified DEMs were reported as true positive (TP), false positive (FP), and false negative (FN). Based on TP, FP, and FN originating from the culvert-modified DEMs of both methods, the evaluation metrics of the false positive rate (FPR) (i.e., the commission error) and false negative rate (FNR) (i.e., the omission error) were computed. Our evaluation showed that the newly developed DSMA-based DS data resulted in an FPR of 0.05 with federal highway authorities (FHWA) roads and 0.12 with non-FHWA roads. The FNR with FHWA roads was 0.07, and with non-FHWA roads, it was 0.38. The BA method showed an FPR of 0.28 with FHWA roads and 0.62 with non-FHWA roads. Similarly, the FNR for the BA method was 0.32 with FHWA roads and 0.61 with non-FHWA roads. The statistics based on the FPR and FNR showed that the DSMA-based culvert-modified DEM was more accurate compared with the BA method, and the formulated framework for producing culvert-modified DEMs using DSMA-based DS data was robust. [ABSTRACT FROM AUTHOR]

Visitation to parks and protected areas (PPAs) has become increasingly widespread in the United States. This increased visitation is especially concerning within congressionally designated wilderness areas where federal agencies are tasked with the dual mandate of preserving wilderness character while simultaneously providing high-quality outdoor recreation experiences. This study investigated the influence of social, situational, and ecological factors on outdoor recreation visitor behaviors and decision making within the Lye Brook Congressionally Designated Wilderness (LBW) area in Vermont, USA. An on-site intercept survey (n = 576) was employed to collect data from LBW visitors in the summer of 2021. Descriptive and multi-variate statistics (e.g., binary logistic regression, structural equation modeling) indicated that visitor behaviors (e.g., coping, substitution) and decision-making (e.g., intention-to-return) were significantly influenced by social (e.g., conflict), situational (e.g., litter, access), and ecological (e.g., trail conditions, weather) impacts. Moreover, the presence of various weather conditions was found to significantly influence the severity of perceived social, situational, and ecological impacts. Study results indicated that outdoor recreation experiences are multifaceted, necessitating a suite of social, situational, and ecological considerations, especially when examining the relationship between visitor coping behaviors and intention-to-return. This research advances the coping framework, provides empirical support for future examination of social–ecological system (SES) theory, and emphasizes the utility of employing an adaptive systems approach for sustainable PPA management. [ABSTRACT FROM AUTHOR]

In this article we address the problem of efficient and secure monitoring of computer network traffic. We proposed, implemented, and tested a hardware-accelerated implementation of a network probe, using the DE5-Net FPGA development platform. We showed that even when using a cryptographic SHA-3 hash function, the probe uses less than 17% of the available FPGA resources, offering a throughput of over 20 Gbit/s. We have also researched the problem of choosing an optimal hash function to be used in a network probe for addressing network flows in a flow cache. In our work we compared five 32-bit hash functions, including two cryptographic ones: SHA-1 and SHA-3. We ran a series of experiments with various hash functions, using traffic replayed from the CICIDS 2017 dataset. We showed that SHA-1 and SHA-3 provide flow distributions as uniform as the ones offered by the modified Vermont hash function proposed in 2008 (i.e., with low means and standard deviations of the bucket occupation), yet assuring higher security against potential attacks on a network probe. [ABSTRACT FROM AUTHOR]

Wide-area drainage structure (DS) mapping is of great concern, as many DSs are reaching the end of their design life and information on their location is usually absent. Recently, airborne laser scanning (ALS) has been proven useful for DS mapping through manual methods using ALS-derived digital elevation models (DEMs) and hillshade images. However, manual methods are slow and labor-intensive. To overcome these limitations, this paper proposes an automated DS mapping algorithm (DSMA) using classified ALS point clouds and road centerline information. The DSMA begins with removing ALS ground points within the buffer of the road centerlines; the size of the buffer varies according to different road classes. An ALS-modified DEM (ALS-mDEM) is then generated from the remaining ground points. A drainage network (DN) is derived from the ALS-mDEM. Candidate DSs are then obtained by intersecting the DN with the road centerlines. Finally, a refinement buffer of 15 m is placed around each candidate DS to prevent duplicate DS from being generated in close proximity. A total area of 50 km2, including an urban site and a rural site, in Vermont, USA, was used to assess the DSMA. Based on the road functional classification scheme of the Federal Highway Administration (FHWA), the centerline information regarding FHWA roads was obtained from a public data portal. The centerline information on non-FHWA roads, i.e., private roads and streets, was derived from the impervious surface data of a land cover dataset. A benchmark DS dataset was gathered from the transport agency of Vermont and was further augmented using Google Earth Street View images by the authors. The one-to-one correspondence between the benchmark DS and mapped DS for these two sites was then established. The positional accuracy was assessed by computing the Euclidian distance between the benchmark DS and mapped DS. The mean positional accuracy for the urban site and rural site were 13.5 m and 15.8 m, respectively. F1-scores were calculated to assess the prediction accuracy. For FHWA roads, the F1-scores were 0.87 and 0.94 for the urban site and rural site, respectively. For non-FHWA roads, the F1-scores were 0.72 and 0.74 for the urban site and rural site, respectively. [ABSTRACT FROM AUTHOR]

Many state and national geological surveys produce map products from surficial and bedrock geologic maps as a value-added deliverable for a variety of stakeholders. Improvements in powerful geostatistical exploratory tools and robust three-dimensional capabilities within geographic information systems (GIS) can facilitate the production of derivative products. In addition to providing access to geostatistical functions, many software packages are also capable of rendering three-dimensional visualizations using spatially distributed point data. A GIS-based approach using ESRI's® Geostatistical Analyst® was used to create derivative maps depicting surficial overburden, bedrock topography, and potentiometric surface using well data and bedrock exposures. This methodology describes the importance and relevance of creating three-dimensional visualizations in tandem with traditional two-dimensional map products. These 3D products are especially useful for town managers and planners--often unfamiliar with interpreting two-dimensional geologic map products--so they can better visualize and understand the relationships between surficial overburden and potential groundwater resources. [ABSTRACT FROM AUTHOR]

Many U.S. dairy farms, especially small farms, are struggling to stay in business due to difficult economic conditions. While switching to organic milk production has been identified as one way to improve farm profitability, there are very limited economic data available on organic dairy profitability and the key factors contributing to its variation among organic dairy farms. This study analyzes a 10-year longitudinal dataset of Vermont organic dairy farms (2006–2016), collected by the University of Vermont Extension, to identify key factors influencing farm profitability and quantify their impact on farm return on assets (ROA) through a multivariate fixed-effects regression model. Results suggest that significant factors for organic farm profitability measured by ROA include feeding management, farm management, farm size, milk price and input costs. Such findings may help many organic dairy farms identify potential areas for improving their profitability and conventional farms evaluate the potential financial benefits of switching to organic operation. [ABSTRACT FROM AUTHOR]

Information on public support and willingness to pay (WTP) for renewable energy from alternative sources is critically important for the development and evaluation of renewable energy policies and programs. This study assesses consumer support and WTP for electricity from solar panels, wind turbines, and on-farm anaerobic digester systems (ADS) in the United States, using data collected from a household survey in the state of Vermont. Empirical results suggest that solar power was the respondents' top choice for public investment, and cow power (electricity generated from ADS) was the least-favored choice. Also, the variations in the likelihood of being willing to pay a premium for each renewable electricity across respondents were closely associated with factors such as education, political affiliation, homeownership, and local agricultural engagement. The relatively low level of public support and WTP for cow power is likely the result of unfamiliarity with this renewable source of electricity, and more educational efforts are highly needed to promote this renewable energy with many environmental benefits for a dairy state. [ABSTRACT FROM AUTHOR]