Search

The hemlock woolly adelgid (HWA) (Adelges tsugae Annand) is an invasive insect in the eastern United States. Since its initial detection in Richmond, Virginia, in 1951, HWA has spread to half of the eastern hemlock (Tsuga canadensis (L.) Carr.) natural range. Detection of early infestation symptoms via remote sensing requires the knowledge of the changes in reflectance resulting from physiological changes in the host as inflicted by the insect and the selection of equipment with the appropriate sensor characteristics. Laboratory-based reflectance measurements of infested and non-infested hemlock foliage collected from four sites in southern New Hampshire and Maine occurred biweekly over 6 months in 2012 and weekly over 5 weeks in 2013. Vegetation indices (red edge inflection point (REIP), normalized difference vegetation index (NDVI), moisture stress index (MSI), and near infrared (NIR) 3/1 ratio) were associated with concurrent chlorophyll and moisture content data. Infested first-year foliage contained greater concentrations of chlorophyll and moisture, resulting in reduced visible spectral reflectance, greater REIP and NDVI values, and lower MSI and NIR 3/1 values than non-infested foliage. Furthermore, fluorescence measurements indicated greater photosystem function during the early stages of infestation, suggesting a possible compensatory response by hemlock to infestation. Significant differences in reflectance between infested and non-infested foliage were observed in late June and July in the weeks immediately following HWA settlement on new growth. Implementing these observations during remote sensing mission planning may increase the likelihood of detecting early HWA infestation symptoms at landscape scales. Key words: Adelges tsugae, hemlock woolly adelgid, remote sensing, vegetation indices, fluorescence, chlorophyll. Le puceron lanigere de la pruche (PLP) (Adelges tsugae Annand) est un insecte invasif dans l'est des Etats-Unis. Depuis qu'il a ete detecte pour la premiere fois a Richmond en Virginie, en 1951, le PLP a envahi la moitie de l'aire de repartition naturelle de la pruche du Canada (Tsuga canadensis (L.) Carr.). Pour detecter les symptomes precoces d'infestation au moyen de la teledetection il faut connaitre les changements dans la reflectance dus aux modifications physiologiques chez l'hote causees par l'insecte et choisir l'equipement dont les capteurs ont les caracteristiques appropriees. Des mesures de reflectance ont ete effectuees en laboratoire sur du feuillage de pruche infeste ou non preleve a quatre endroits dans le sud du New Hampshire et du Maine a toutes les deux semaines durant six mois en 2012 et a toutes les semaines durant cinq semaines en 2013. Des indices de vegetation (REIP, NDVI, MSI et NIR 3/1) ont ete associes aux donnees simultanees de teneur en humidite et en chlorophylle. Le feuillage d'un an infeste contenait de plus fortes concentrations de chlorophylle et d'humidite qui se traduisaient par une diminution de la reflectance spectrale dans le visible, des valeurs plus elevees de REIP et NDVI et plus fables de MSI er NIR 3/1 que dans le feuillage non infeste. De plus, des mesures de fluorescence ont montre que le photosysteme fonctionnait davantage durant les premiers stades de l'infestation, ce qui suggere possiblement une reaction compensatoire de la pruche a l'infestation. Des differences significatives de reflectance entre le feuillage infeste et non infeste ont ete observees a la fin du mois de juin et en juillet durant les semaines qui ont immediatement suivi l'etablissement du PLP sur les nouvelles pousses. L'integration de ces observations durant la planification des missions de teledetection pourrait augmenter les chances de detecter les symptomes precoces d'infestation du PLP a l'echelle du paysage. [Traduit par la Redaction] Mots-cles: Adelges tsugae, puceron lanigere de la pruche, teledetection, indices de vegetation, fluorescence, chlorophylle., 1. Introduction Eastern hemlock (Tsuga canadensis (L.) Carr.) is a foundation tree species in the northeastern United States (Ellison et al. 2005). Often found on steep slopes and in riparian [...]

A detection scheme that uses classical and spatial statistics has been developed to identify roadways with the most severe safety needs. It is based on the null hypothesis that all roadways have the same crash risk, that is, all have the same nonfatal and fatal crash rates throughout the entire study region. Fatal and nonfatal crash rates, which are assumed to be randomly distributed as Poisson processes, are modeled with a marked homogeneous Poisson process model. Since the traffic exposures are typically unknown at the crash sites, they are predicted with a geostatistical model. Locations, where the null hypothesis is rejected, are safety treatment candidates. P-value risk rankings are used to identify locations with the most severe safety needs. The results from alternative analyses--one using vehicle miles traveled and another using population as measures of traffic exposure--are conducted and compared. The state of New Hampshire is used in a case study. The effects of analyzing areas with small traffic exposures, the so-called 'small-area estimation' problem, and the aim to develop a data-driven detection scheme that meets the requirements as an objective decision-making tool are discussed. DOI: 10.1061/(ASCE)TE.1943-5436.0000048 CE Database subject headings: Traffic safety; Traffic models; Spatial analysis; Spatial data; Spatial distribution; Statistics; Stochastic processes. Author keywords: Traffic safety; Traffic models; Spatial analysis; Spatial data; Spatial distribution; Statistics; Stochastic processes.

A characteristic feature of the eastern Bering Sea (EBS) is a subsurface layer linked to seasonal sea ice (SSI) and defined by bottom temperatures less than 2 °C, which is termed the cold pool. Cold pool variability is directly tied to regional zooplankton and fish dynamics. Multifrequency (200 and 460 kHz) acoustic backscatter data were collected remotely using upward looking echosounders along the EBS shelf from 2008 and 2018 and used as a proxy of biological abundance. Acoustic data were coupled with bottom temperature and regional SSI data from the cold (2006–2013) and warm (2014–2018) regimes to assess the relationship between biological scattering communities and cold pool variation. Acoustic backscatter was 2 orders of magnitude greater during the cold regime than during the warm regime, with multifrequency analysis indicating a shift in the warm regime frequency-dependent scattering communities. Cold pool proxy SSI was a stronger predictor for biological scattering than bottom temperature in the cold regime, while warm regime bottom temperature and SSI were equal in predictive power and resulted in improved predictive model performance. Results suggest coupled cold pool and frequency-dependent scattering dynamics are a potential regime shift indicator and may be useful for management practices in surrounding Arctic ecosystems. [ABSTRACT FROM AUTHOR]

A physical and chemical heterogeneity study of glaciofluvial deposit in Deerfield, New Hampshire, was conducted in order to understand the processes controlling the spatial variation of sediment properties. The findings suggest that lithofacies and color information could aid the characterization and modeling of heterogeneity at similar carbon-poor glaciofluvial sites.

The impact of multibeam echosounder (MBES) operations on marine mammals has been less studied compared to military sonars. To contribute to the growing body of MBES knowledge, echolocation clicks of foraging Cuvier's beaked whales were detected on the Southern California Antisubmarine Warfare Range (SOAR) hydrophones during two MBES surveys and assembled into foraging events called group vocal periods (GVPs). Four GVP characteristics were analyzed Before, During, and After 12 kHz MBES surveys at the SOAR in 2017 and 2019 to assess differences in foraging behavior with respect to the mapping activity. The number of GVP per hour increased During and After MBES surveys compared with Before. There were no other differences between non-MBES and MBES periods for the three other characteristics: the number of clicks per GVP, GVP duration, and click rate. These results indicate that there was not a consistent change in foraging behavior during the MBES surveys that would suggest a clear response. The animals did not leave the range nor stop foraging during MBES activity. These results are in stark contrast to those of analogous studies assessing the effect of Naval mid-frequency active sonar on beaked whale foraging, where beaked whales stopped echolocating and left the area. [ABSTRACT FROM AUTHOR]

Reoccurring seasonal cyanobacterial harmful algal blooms (CHABs) persist in many waters, and recent work has shown links between CHAB and elevated risk of amyotrophic lateral sclerosis (ALS). Quantifying the exposure levels of CHAB as a potential risk factor for ALS is complicated by human mobility, potential pathways, and data availability. In this work, we develop phycocyanin concentration (i.e., CHAB exposure) maps using satellite remote sensing across northern New England to assess relationships with ALS cases using a spatial epidemiological approach. Strategic semi-analytical regression models integrated Landsat and in situ observations to map phycocyanin concentration (PC) for all lakes greater than 8 ha ( n = 4117) across the region. Then, systematic versions of a Bayesian Poisson Log-linear model were fit to assess the mapped PC as a risk factor for ALS while accounting for model uncertainty and modifiable area unit problems. The satellite remote sensing of PC had strong overall ability to map conditions (adj. R2, 0.86; RMSE, 11.92) and spatial variability across the region. PC tended to be positively associated with ALS risk with the level of significance depending on fixed model components. Meta-analysis shows that when average PC exposure is 100 μg/L, an all model average odds ratio is 1.48, meaning there is about a 48% increase in average ALS risk. This research generated the first regionally comprehensive map of PC for thousands of lakes and integrated robust spatial uncertainty. The outcomes support the hypothesis that cyanotoxins increase the risk of ALS, which helps our understanding of the etiology of ALS. [ABSTRACT FROM AUTHOR]

Lakes have been suggested as an indicator of climate change; however, long-term, systematic records of lake temperature are limited. Satellite remote sensing is capable of supporting lake temperature mapping with the advantage of large-area and systematic observations. The goal of this research application was to assess spatiotemporal trends in lake skin temperature for all lakes over 8 ha across northern New England for the past three decades. Nearly 10 000 Landsat scenes for July, August, and September from 1984 to 2014 were processed using MODTRAN and MERRA parameterizations to generate atmospherically corrected lake skin temperature records. Results show, on average, lakes warmed at a rate of 0.8°C decade-1, with smaller lakes warming at a faster rate. Complementing regression and space--time analyses showed similar results (R² = 0.63) for lake temperature trends and found lakes, on average, are warming faster than daily maximumorminimum air temperature. Nomajor hot spots were found as lake temperature changes were heterogeneous on a local scale and evenly distributed across the region. Maximum and minimum daily temperature, lake size, and elevation were found as significant drivers of lake temperature. This effort provides the first regionally focused and comprehensive spatiotemporal assessment of thousands (n = 3955) of lakes concentrated in one geographic region. The approach is scalable and adaptable to any region for assessing lake temperature trends and potential drivers. [ABSTRACT FROM AUTHOR]

Background:The dynamics of gaps plays a role in the regimes of tree mortality, production of coarse woody debris (CWD) and the variability of light in the forest understory. Aims:To quantify the area affected by, and the carbon fluxes associated with, natural gap-phase disturbances in a tropical lowland evergreen rain forest by use of ground measurements and high-resolution satellite images. Methods:We surveyed two large forest inventory plots of 114 and 53 ha of the Tapajós National Forest (TNF) in the Brazilian Amazon during 2008 and 2009, respectively. We mapped all gaps and collected data on light availability, CWD stocks and tree mortality in the field. Gap location, canopy openness (CO) and leaf area index (LAI) estimated in the field were compared with two IKONOS–2 high-resolution satellite images acquired at approximately the time of the field measurements. Results:In the two large plots (167 ha total area) we found 96 gaps. The gaps represented 1.42% of the total area and gaps <1-year-old accounted for 0.81% of the plot area. In TNF, the production of CWD in recent gaps was 0.76 Mg C ha−1year−1and the mean tree mortality was 2.38 stems ha−1year−1. The area of gaps estimated using thresholds of light intensity measured by remote sensing optical instruments was twice as large as the gap areas measured on the ground. We found no significant correlation between spectral remote sensing images and CO or LAI, probably due to the high degree of shadow in the high-resolution satellite images. Conclusions:We present the first statistics of CWD production based on gap size in the tropical forest literature. Tree mortality and CWD flux and the forest floor light environment were closely related to gap area. However, less than 30% of the annual tree mortality and CWD flux was associated with gaps, and gaps were difficult to detect using remote sensing methods because of the high proportion of shadow in the images. These results highlight the need for permanent plots in long-term carbon studies. [ABSTRACT FROM PUBLISHER]

A Bayesian statistical approach for determining the parameter uncertainty of a storm-water treatment model is reported. The storm-water treatment technologies included a sand filter and a subsurface gravel wetland. The two field systems were loaded and monitored in a side-by-side fashion over a two-year period. The loading to each system was storm-water runoff generated by ambient rainfall on a commuter parking lot. Contaminant transport is simulated by using a one-dimensional advection-dispersion model. The unknown parameters of the model are the contaminant deposition rate and the hydrodynamic dispersion. The following contaminants are considered in the study: total suspended solids, total petroleum hydrocarbons-diesel range hydrocarbons, and zinc. Parameter uncertainties are addressed by estimating the posterior probability distributions through a conventional Metropolis-Hastings algorithm. Results indicate that the posterior distributions are unimodal and, in some instances, exhibit some level of skewness. The Bayesian approach allowed the estimation of the 10th, 25th, 50th, 75th, and 95th percentiles of the posterior probability distributions. The prediction capabilities of the model were explored by performing a Monte Carlo simulation using the calculated posterior distributions and two rainfall-runoff events not considered during the calibration phase. The objective is to estimate effluent concentrations from the treatment systems under different scenarios of flow and contaminant loads. In general, estimated effluent concentrations and the total estimated mass fell within the defined uncertainty limits. [ABSTRACT FROM AUTHOR]

We explored the role of aquatic systems in the global N cycle using a spatially distributed, within-basin, aquatic nitrogen (N) removal model, implemented within the Framework for Aquatic Modeling in the Earth System (FrAMES-N). The model predicts mean annual total N (TN) removal by small rivers (with drainage areas from 2.6-1000 km²), large rivers, lakes, and reservoirs, using a 30′ latitude x longitude river network to route and process material from continental source areas to the coastal zone. Mean annual aquatic TN removal (for the mid-1990s time period) is determined by the distributions of aquatic TN inputs, mean annual hydrological characteristics, and biological activity. Model-predicted TN concentrations at basin mouths corresponded well with observations (median relative error = -12%, interquartile range of relative error = 85%), an improvement over assumptions of uniform aquatic removal across basins. Removal by aquatic systems globally accounted for 14% of total N inputs to continental surfaces, but represented 53% of inputs to aquatic systems. Integrated aquatic removal was similar in small rivers (16.5% of inputs), large rivers (13.6%), and lakes (15.2%), while large reservoirs were less important (5.2%). Bias related to runoff suggests improvements are needed in nonpoint N input estimates and/or aquatic biological activity. The within-basin approach represented by FrAMES-N will improve understanding of the freshwater nutrient flux response to anthropogenic change at global scales. [ABSTRACT FROM AUTHOR]

Predictive methods for contaminant release from virgin and secondary road construction materials are important for evaluating potential long-term soil and groundwater contamination from highways. The objective of this research was to describe the field hydrology in a highway embankment and to investigate leaching under unsaturated conditions by use of a contaminant fate and transport model. The HYDRUS2D code was used to solve the Richards equation and the advection–dispersion equation with retardation. Water flow in a Minnesota highway embankment was successfully modeled in one dimension for several rain events after Bayesian calibration of the hydraulic parameters against water content data at a point 0.32 m from the surface of the embankment. The hypothetical leaching of Cadmium from coal fly ash was probabilistically simulated in a scenario where the top 0.50 m of the embankment was replaced by coal fly ash. Simulation results were compared to the percolation equation method where the solubility is multiplied by the liquid-to-solid ratio to estimate total release. If a low solubility value is used for Cadmium, the release estimates obtained using the percolation/equilibrium model are close to those predicted from HYDRUS2D simulations (∼10–4–10–2 mg Cd/kg ash). If high solubility is used, the percolation equation over predicts the actual release (0.1–1.0 mg Cd/kg ash). At the 90th percentile of uncertainty, the 10-year liquid-to-solid ratio for the coal fly ash embankment was 9.48 L/kg, and the fraction of precipitation that infiltrated the coal fly ash embankment was 92%. Probabilistic modeling with HYDRUS2D appears to be a promising realistic approach to predicting field hydrology and subsequent leaching in embankments. [ABSTRACT FROM AUTHOR]

We performed a synthetic analysis of Harvard Forest net ecosystem exchange of CO2 (NEE) time series and a simple ecosystem carbon flux model, the simplified Photosynthesis and Evapo-Transpiration model (SIPNET). SIPNET runs at a half-daily time step, and has two vegetation carbon pools, a single aggregated soil carbon pool, and a simple soil moisture sub-model. We used a stochastic Bayesian parameter estimation technique that provided posterior distributions of the model parameters, conditioned on the observed fluxes and the model equations. In this analysis, we estimated the values of all quantities that govern model behavior, including both rate constants and initial conditions for carbon pools. The purpose of this analysis was not to calibrate the model to make predictions about future fluxes but rather to understand how much information about process controls can be derived directly from the NEE observations. A wavelet decomposition enabled us to assess model performance at multiple time scales from diurnal to decadal. The model parameters are most highly constrained by eddy flux data at daily to seasonal time scales, suggesting that this approach is not useful for calculating annual integrals. However, the ability of the model to fit both the diurnal and seasonal variability patterns in the data simultaneously, using the same parameter set, indicates the effectiveness of this parameter estimation method. Our results quantify the extent to which the eddy covariance data contain information about the ecosystem process parameters represented in the model, and suggest several next steps in model development and observations for improved synthesis of models with flux observations. [ABSTRACT FROM AUTHOR]

Abstract: Spatio-temporal correlation analyses were performed on time series of daily freshwater discharge, wind fields, and SeaWiFS-derived surface particle concentrations in the northern Gulf of Mexico. The influences of discharge and winds on surface particle concentrations were investigated by mapping temporal correlation coefficients at each pixel for the whole time series (1997–2000) and for each season during 1999 and 2000. Maps of the correlation between suspended particulate matter concentration (SPM) and river discharge suggest regions that are fluvially influenced. The particulate matter may be sediments carried by the river plume or biogenic particles (e.g., detritus) stimulated by the river discharge. The algorithm used to estimate SPM concentrations does not differentiate between sediment and detritus. Maps of the correlation between wind stress and SPM suggest regions where wind mixing accounts for particulate resuspension and subsequent transport. Regions of significant positive wind-SPM correlation were independent, and often spatially separated, from regions of strong positive discharge-SPM correlation. Thus, the influences of winds and discharge on particle distributions can be investigated independently. Regions of high wind-SPM correlation were associated with shallow shelf areas, as correlation contours generally followed the bathymetric contours, and expanded in size under offshore wind regimes. These areas exhibited less spatial and temporal variability than the regions of high discharge-SPM correlation associated with the Mississippi-Atchafalaya river system. There was no apparent relationship between the magnitude of Mississippi- Atchafalaya discharge and the spatial extent of the region of high discharge-SPM correlation during seasonal analyses. Instead, the spatial extent and orientation of the discharge-SPM correlation field appeared to be a function of winds (both their direction and speed) and the buoyancy of the plume. [Copyright &y& Elsevier]

Abstract: In this paper, we present an improved procedure for collecting no or little atmosphere- and snow-contaminated observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The resultant time series of daily MODIS data of a temperate deciduous broadleaf forest (the Bartlett Experimental Forest) in 2004 show strong seasonal dynamics of surface reflectance of green, near infrared and shortwave infrared bands, and clearly delineate leaf phenology and length of plant growing season. We also estimate the fractions of photosynthetically active radiation (PAR) absorbed by vegetation canopy (FAPARcanopy), leaf (FAPARleaf), and chlorophyll (FAPARchl), respectively, using a coupled leaf-canopy radiative transfer model (PROSAIL-2) and daily MODIS data. The Markov Chain Monte Carlo (MCMC) method (the Metropolis algorithm) is used for model inversion, which provides probability distributions of the retrieved variables. A two-step procedure is used to estimate the fractions of absorbed PAR: (1) to retrieve biophysical and biochemical variables from MODIS images using the PROSAIL-2 model; and (2) to calculate the fractions with the estimated model variables from the first step. Inversion and forward simulations of the PROSAIL-2 model are carried out for the temperate deciduous broadleaf forest during day of year (DOY) 184 to 201 in 2005. The reproduced reflectance values from the PROSAIL-2 model agree well with the observed MODIS reflectance for the five spectral bands (green, red, NIR1, NIR2, and SWIR1). The estimated leaf area index, leaf dry matter, leaf chlorophyll content and FAPARcanopy values are close to field measurements at the site. The results also showed significant differences between FAPARcanopy and FAPARchl at the site. Our results show that MODIS imagery provides important information on biophysical and biochemical variables at both leaf and canopy levels. [Copyright &y& Elsevier]

Abstract: In this paper, we present a theoretical and modeling framework to estimate the fractions of photosynthetically active radiation (PAR) absorbed by vegetation canopy (FAPARcanopy), leaf (FAPARleaf ), and chlorophyll (FAPARchl), respectively. FAPARcanopy is an important biophysical variable and has been used to estimate gross and net primary production. However, only PAR absorbed by chlorophyll is used for photosynthesis, and therefore there is a need to quantify FAPARchl. We modified and coupled a leaf radiative transfer model (PROSPECT) and a canopy radiative transfer model (SAIL-2), and incorporated a Markov Chain Monte Carlo (MCMC) method (the Metropolis algorithm) for model inversion, which provides probability distributions of the retrieved variables. Our two-step procedure is: (1) to retrieve biophysical and biochemical variables using coupled PROSPECT+SAIL-2 model (PROSAIL-2), combined with multiple daily images (five spectral bands) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor; and (2) to calculate FAPARcanopy, FAPARleaf and FAPARchl with the estimated model variables from the first step. We evaluated our approach for a temperate forest area in the Northeastern US, using MODIS data from 2001 to 2003. The inverted PROSAIL-2 fit the observed MODIS reflectance data well for the five MODIS spectral bands. The estimated leaf area index (LAI) values are within the range of field measured data. Significant differences between FAPARcanopy and FAPARchl are found for this test case. Our study demonstrates the potential for using a model such as PROSAIL-2, combined with an inverse approach, for quantifying FAPARchl, FAPARleaf, FAPARcanopy, biophysical variables, and biochemical variables for deciduous broadleaf forests at leaf- and canopy-levels over time. [Copyright &y& Elsevier]