Comparison of Potential Evapotranspiration (PET) using Three Methods for a Grass Reference and a Natural Forest in Coastal Plain of South Carolina

2014 S.C. Water Resources Conference - Informing Strategic Water Planning to Address Natural Resource, Community and Economic Challenge

Estimating mangrove aboveground biomass from airborne LiDAR data: a case study from the Zambezi River delta

Mangroves are ecologically and economically important forested wetlands with the highest carbon (C) density of all terrestrial ecosystems. Because of their exceptionally large C stocks and importance as a coastal buffer, their protection and restoration has been proposed as effective mitigation strategy for climate change. The inclusion of mangroves in mitigation strategies requires the quantification of C stocks (both above and belowground) and changes to accurately calculate emissions and sequestration. A growing number of countries are becoming interested in using mitigation initiatives, such as REDD+, in these unique coastal forests. However, it is not yet clear how methods to measure C traditionally used for other ecosystems can be modified to estimate biomass in mangroves with the precision and accuracy needed for these initiatives. Airborne lidar (ALS) data has often been proposed as the most accurate way for larger-scale assessments but, the application of ALS for coastal wetlands is scarce, primarily due to a lack of contemporaneous ALS and field measurements. Here, we evaluated the variability in field and lidar-based estimates of aboveground biomass (AGB) through the combination of different local and regional allometric models and standardized height metrics that are comparable across spatial resolutions and sensor types. The end result being a simplified approach for accurately estimating mangrove AGB at large-scales and determining the uncertainty by combining multiple allometric models. We then quantified wall-to-wall aboveground biomass stocks of a tall mangrove forest in the Zambezi Delta, Mozambique. Our results indicate that the Lidar H100 height metric correlates well with AGB estimates, with R2 between 0.80 and 0.88 and RMSE of 33% or less. When comparing lidar H100 AGB derived from three allometric models, mean AGB values range from 192 Mg. ha-1 up to 252 Mg. ha-1. We suggest the best model to predict AGB was based on the East Africa specific allometry and a power based regression that used Lidar H100 as the height input with a R2 of 0.85 and a RMSE of 122 Mg.ha-1 or 33%. The total AGB of the lidar inventoried mangrove area (6654 ha) was 1,350,902 Mg with a mean AGB 203 Mg. ha-1. Because the allometry suggested here was developed using standardized height metrics, it is recommended that the models can generate AGB estimates using other remote sensing instruments that are more readily accessible over other mangrove ecosystems on a large scale, and as part of future carbon monitoring efforts in mangroves

Hydrologic and Water Quality Monitoring on Turkey Creek Watershed, Francis Marion National Forest, SC

2008 S.C. Water Resources Conference - Addressing Water Challenges Facing the State and Regio

Wetland and Hydric Soils

Soil and the inherent biogeochemical processes in wetlands contrast starkly with those in upland forests and rangelands. The differences stem from extended periods of anoxia, or the lack of oxygen in the soil, that characterize wetland soils; in contrast, upland soils are nearly always oxic. As a result, wetland soil biogeochemistry is characterized by anaerobic processes, and wetland vegetation exhibits specific adaptations to grow under these conditions. However, many wetlands may also have periods during the year where the soils are unsaturated and aerated. This fluctuation between aerated and nonaerated soil conditions, along with the specialized vegetation, gives rise to a wide variety of highly valued ecosystem services

Selective Serotonin Reuptake Inhibitors and Associated Bleeding Risks: A Narrative and Clinical Review.

Major Depressive Disorder (MDD) is a major cause of disability worldwide and is associated with serious lasting impairment. A leading hypothesis of the pathophysiology of MDD is the monoamine deficiency hypothesis which suggests that depression is caused by depletion of serotonin, norepinephrine, or dopamine in the central nervous system. Serotonin is the most widely studied neurotransmitter in the pathophysiology of depression, with studies showing that reduced central serotonin synthesis leads to depressive symptoms in individuals at risk for depression. Selective Serotonin Reuptake Inhibitors (SSRI) inhibit serotonin reuptake and subsequently increase the amount of serotonin available in synapses. Common side effects of SSRIs include increased suicidality of patients under the age of 25, sexual dysfunction, anxiety, dizziness, weight gain, gastrointestinal distress, and headache. Other side effects include prolonging the QT interval, coagulopathy, and the risk of serotonin syndrome, as well as SSRI discontinuation syndrome. Sites of increased bleeding related to SSRI use have been reported to occur in the upper gastrointestinal tract, as well as intracranially. Based on the current literature, three studies have found that SSRIs are not associated with increased bleeding and/or increased perioperative risk, while others have demonstrated that SSRIs are associated with an increased risk in perioperative use. The inhibition of serotonin reuptake can affect platelet aggregation since platelets also express the serotonin transporter. SSRIs can result in decreased storage of serotonin in platelet dense granules. Increased serotonin can also increase gastric acid secretion, which increases the risk for ulceration. SSRIs in combination with NSAIDs also show a significantly increased risk of upper GI bleeding. Some studies show an increased bleeding risk from 30% to 70% when taking a combination of vitamin K antagonists and SSRIs in hospitalized patients. Related to the high prevalence of conditions that are treated with SSRIs, the bleeding risk associated with this class of medication merits further study

Risdiplam for the Use of Spinal Muscular Atrophy

Spinal muscular atrophy (SMA) is one of the leading causes of death in infants related to the degeneration of neurons. Currently, there are no curative treatment options for SMA, and many options available may not be feasible. This review presents the background, clinical studies, and indications for the use of Risdiplam in treating SMA. SMA causes a decrease in the production of survival motor neuron proteins (SMN) and current treatments target to increase the expression of SMN. Risdiplam is the first and only oral medication to be approved to treat SMA. As an SMN2 splicing modifier, it has provided stronger systemic therapies than previous intrathecal and gene replacement therapies. There have been many efforts to treat SMA with multidisciplinary approaches. These include intrathecal injections to gene replacement therapies. However, these have been faced with limitations such as reaching a good therapeutic dose in systemic tissues, route of administration, and price. Risdiplam is currently the only orally administered drug approved by the FDA for the treatment of SMA. It not only provides a good therapeutic window to systemic tissues but allows for a non-invasive approach in infants. Further investigation and comparison on the safety profile of Risdiplam due to its broader systemic effect should be considered with other available therapies

Restoration of a Severely Impacted Riparian Wetland System - The Pen Branch Project

The Savannah River Swamp is a 3020 ha forested wetland on the floodplain of the Savannah River and is located on the Department of Energy’s Savannah River Site (SRS) near Aiken, SC (Fig. 1). Historically the swamp consisted ofapproximately 50% baldcypress-water tupelo stands, 40% mixed bottomland hardwood stands, and 10% shrub, marsh, and open water. Tributeries of the river were typical of Southeastern bottomland hardwood forests. The hydrology was controlled by flow from four creeks that drain into the swamp and by flooding of the Savannah River. Upstream dams on the Savannah River have caused some alteration of the water levels and timing of flooding within the floodplain(Schneider et al., 1989)

Variation in carbon and nitrogen concentrations among peatland categories at the global scale

Publisher Copyright: © 2022 This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.Peatlands account for 15 to 30% of the world's soil carbon (C) stock and are important controls over global nitrogen (N) cycles. However, C and N concentrations are known to vary among peatlands contributing to the uncertainty of global C inventories, but there are few global studies that relate peatland classification to peat chemistry. We analyzed 436 peat cores sampled in 24 countries across six continents and measured C, N, and organic matter (OM) content at three depths down to 70 cm. Sites were distinguished between northern (387) and tropical (49) peatlands and assigned to one of six distinct broadly recognized peatland categories that vary primarily along a pH gradient. Peat C and N concentrations, OM content, and C:N ratios differed significantly among peatland categories, but few differences in chemistry with depth were found within each category. Across all peatlands C and N concentrations in the 10-20 cm layer, were 440 ± 85.1 g kg-1 and 13.9 ± 7.4 g kg-1, with an average C:N ratio of 30.1 ± 20.8. Among peatland categories, median C concentrations were highest in bogs, poor fens and tropical swamps (446-532 g kg-1) and lowest in intermediate and extremely rich fens (375-414 g kg-1). The C:OM ratio in peat was similar across most peatland categories, except in deeper samples from ombrotrophic tropical peat swamps that were higher than other peatlands categories. Peat N concentrations and C:N ratios varied approximately two-fold among peatland categories and N concentrations tended to be higher (and C:N lower) in intermediate fens compared with other peatland types. This study reports on a unique data set and demonstrates that differences in peat C and OM concentrations among broadly classified peatland categories are predictable, which can aid future studies that use land cover assessments to refine global peatland C and N stocks.Peer reviewe

A muon-track reconstruction exploiting stochastic losses for large-scale Cherenkov detectors

IceCube is a cubic-kilometer Cherenkov telescope operating at the South Pole. The main goal of IceCube is the detection of astrophysical neutrinos and the identification of their sources. High-energy muon neutrinos are observed via the secondary muons produced in charge current interactions with nuclei in the ice. Currently, the best performing muon track directional reconstruction is based on a maximum likelihood method using the arrival time distribution of Cherenkov photons registered by the experiment's photomultipliers. A known systematic shortcoming of the prevailing method is to assume a continuous energy loss along the muon track. However at energies $>1$ TeV the light yield from muons is dominated by stochastic showers. This paper discusses a generalized ansatz where the expected arrival time distribution is parametrized by a stochastic muon energy loss pattern. This more realistic parametrization of the loss profile leads to an improvement of the muon angular resolution of up to $20\%$ for through-going tracks and up to a factor 2 for starting tracks over existing algorithms. Additionally, the procedure to estimate the directional reconstruction uncertainty has been improved to be more robust against numerical errors

LeptonInjector and LeptonWeighter: A neutrino event generator and weighter for neutrino observatories

We present a high-energy neutrino event generator, called LeptonInjector, alongside an event weighter, called LeptonWeighter. Both are designed for large-volume Cherenkov neutrino telescopes such as IceCube. The neutrino event generator allows for quick and flexible simulation of neutrino events within and around the detector volume, and implements the leading Standard Model neutrino interaction processes relevant for neutrino observatories: neutrino-nucleon deep-inelastic scattering and neutrino-electron annihilation. In this paper, we discuss the event generation algorithm, the weighting algorithm, and the main functions of the publicly available code, with examples.Comment: 28 pages, 10 figures, 3 table