511 research outputs found
Drought impacts on ecosystem functions of the U.S. National Forests and Grasslands: Part I evaluation of a water and carbon balance model
Understanding and quantitatively evaluating the regional impacts of climate change and variability (e.g., droughts) on forest ecosystem functions (i.e., water yield, evapotranspiration, and productivity) and services (e.g., fresh water supply and carbon sequestration) is of great importance for developing climate change adaptation strategies for National Forests and Grasslands (NFs) in the United States. However, few reliable continental-scale modeling tools are available to account for both water and carbon dynamics. The objective of this study was to test a monthly water and carbon balance model, the Water Supply Stress Index (WaSSI) model, for potential application in addressing the influences of drought on NFs ecosystem services across the conterminous United States (CONUS). The performance of the WaSSI model was comprehensively assessed with measured streamflow (Q) at 72 U.S. Geological Survey (USGS) gauging stations, and satellite-based estimates of watershed evapotranspiration (ET) and gross primary productivity (GPP) for 170 National Forest and Grassland (NFs). Across the 72 USGS watersheds, the WaSSI model generally captured the spatial variability of multi-year mean annual and monthly Q and annual ET as evaluated by Correlation Coefficient (R = 0.71–1.0), Nash–Sutcliffe Efficiency (NS = 0.31–1.00), and normalized Root Mean Squared Error (0.06–0.48). The modeled ET and GPP by WaSSI agreed well with the remote sensing-based estimates for multi-year annual and monthly means for all the NFs. However, there were systemic discrepancies in GPP between our simulations and the satellite-based estimates on a yearly and monthly scale, suggesting uncertainties in GPP estimates in all methods (i.e., remote sensing and modeling). Overall, our assessments suggested that the WaSSI model had the capability to reconstruct the long-term forest watershed water and carbon balances at a broad scale. This model evaluation study provides a foundation for model applications in understanding the impacts of climate change and variability (e.g., droughts) on NFs ecosystem service functions
Upscaling key ecosystem functions across the conterminous United States by a water-centric ecosystem model
We developed a water-centric monthly scale simulation model (WaSSI-C) by integrating empirical water and carbon flux measurements from the FLUXNET network and an existing water supply and demand accounting model (WaSSI). The WaSSI-C model was evaluated with basin-scale evapotranspiration (ET), gross ecosystem productivity (GEP), and net ecosystem exchange (NEE) estimates by multiple independent methods across 2103 eight-digit Hydrologic Unit Code watersheds in the conterminous United States from 2001 to 2006. Our results indicate that WaSSI-C captured the spatial and temporal variability and the effects of large droughts on key ecosystem fluxes. Our modeled mean (±standard deviation in space) ET (556 ± 228 mm yr−1) compared well to Moderate Resolution Imaging Spectroradiometer (MODIS) based (527 ± 251 mm yr−1) and watershed water balance based ET (571 ± 242 mm yr−1). Our mean annual GEP estimates (1362 ± 688 g C m−2 yr−1) compared well (R2 = 0.83) to estimates (1194 ± 649 g C m−2 yr−1) by eddy flux-based EC-MOD model, but both methods led significantly higher (25–30%) values than the standard MODIS product (904 ± 467 g C m−2 yr−1). Among the 18 water resource regions, the southeast ranked the highest in terms of its water yield and carbon sequestration capacity. When all ecosystems were considered, the mean NEE (−353 ± 298 g C m−2 yr−1) predicted by this study was 60% higher than EC-MOD\u27s estimate (−220 ± 225 g C m−2 yr−1) in absolute magnitude, suggesting overall high uncertainty in quantifying NEE at a large scale. Our water-centric model offers a new tool for examining the trade-offs between regional water and carbon resources under a changing environment
Limits on decaying dark energy density models from the CMB temperature-redshift relation
The nature of the dark energy is still a mystery and several models have been
proposed to explain it. Here we consider a phenomenological model for dark
energy decay into photons and particles as proposed by Lima (J. Lima, Phys.
Rev. D 54, 2571 (1996)). He studied the thermodynamic aspects of decaying dark
energy models in particular in the case of a continuous photon creation and/or
disruption. Following his approach, we derive a temperature redshift relation
for the CMB which depends on the effective equation of state and on
the "adiabatic index" . Comparing our relation with the data on the CMB
temperature as a function of the redshift obtained from Sunyaev-Zel'dovich
observations and at higher redshift from quasar absorption line spectra, we
find , adopting for the adiabatic index ,
in good agreement with current estimates and still compatible with
, implying that the dark energy content being constant in time.Comment: 8 pages, 1 figur
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A model to predict stream water temperature across the conterminous USA
Stream water temperature (tₛ) is a critical water quality parameter for aquatic ecosystems. However, tₛ records are sparse or nonexistent in many river systems. In this work, we present an empirical model to predict tₛ at the site scale across the USA. The model, derived using data from 171 reference sites selected from the Geospatial Attributes of Gages for Evaluating Streamflow database, describes the linear relationship between monthly mean air temperature (tₐ) and tₛ. Multiple linear regression models are used to predict the slope (m) and intercept (b) of the tₐ–tₛ linear relation as a function of climatic, hydrologic and land cover characteristics. Model performance to predict ts resulted in a mean Nash–Sutcliffe efficiency coefficient of 0.78 across all sites. Application of the model to predict tₛ at additional 89 nonreference sites with a higher human alteration yielded a mean Nash– Sutcliffe value of 0.45. We also analysed seasonal thermal sensitivity (m) and found strong hysteresis in the tₐ–tₛ relation. Drainage area exerts a strong control on m in all seasons, whereas the cooling effect of groundwater was only evident for the spring and fall seasons. However, groundwater contributions are negatively related to mean tₛ in all seasons. Finally, we found that elevation and mean basin slope are negatively related to mean tₛ in all seasons, indicating that steep basins tend to stay cooler because of shorter residence times to gain heat from their surroundings. This model can potentially be used to predict climate change impacts on ts across the USA
Monthly land cover-specific evapotranspiration models derived from global eddy flux measurements and remote sensing data
Evapotranspiration (ET) is arguably the most uncertain ecohydrologic variable for quantifying watershed water budgets. Although numerous ET and hydrological models exist, accurately predicting the effects of global change on water use and availability remains challenging because of model deficiency and/or a lack of input parameters. The objective of this study was to create a new set of monthly ET models that can better quantify landscape-level ET with readily available meteorological and biophysical information. We integrated eddy covariance flux measurements from over 200 sites, multiple year remote sensing products from the Moderate Resolution Imaging Spectroradiometer (MODIS), and statistical modelling. Through examining the key biophysical controls on ET by land cover type (i.e. shrubland, cropland, deciduous forest, evergreen forest, mixed forest, grassland, and savannas), we created unique ET regression models for each land cover type using different combinations of biophysical independent factors. Leaf area index and net radiation explained most of the variability of observed ET for shrubland, cropland, grassland, savannas, and evergreen forest ecosystems. In contrast, potential ET (PET) as estimated by the temperaturebased Hamon method was most useful for estimating monthly ET for deciduous and mixed forests. The more data-demanding PET method, FAO reference ET model, had similar power as the simpler Hamon PET method for estimating actual ET. We developed three sets of monthly ET models by land cover type for different practical applications with different data availability. Our models may be used to improve water balance estimates for large basins or regions with mixed land cover types
The relationship between cadence, pedalling technique and gross efficiency in cycling
Technique and energy saving are two variables often considered as important for performance in cycling and related to each other. Theoretically, excellent pedalling technique should give high gross efficiency (GE). The purpose of the present study was to examine the relationship between pedalling technique and GE. 10 well-trained cyclists were measured for GE, force effectiveness (FE) and dead centre size (DC) at a work rate corresponding to ~75% of VO2max during level and inclined cycling, seat adjusted forward and backward, at three different cadences around their own freely chosen cadence (FCC) on an ergometer. Within subjects, FE, DC and GE decreased as cadence increased (p < 0.001). A strong relationship between FE and GE was found, which was to great extent explained by FCC. The relationship between cadence and both FE and GE, within and between subjects, was very similar, irrespective of FCC. There was no difference between level and inclined cycling position. The seat adjustments did not affect FE, DC and GE or the relationship between them. Energy expenditure is strongly coupled to cadence, but force effectiveness, as a measure for pedalling technique, is not likely the cause of this relationship. FE, DC and GE are not affected by body orientation or seat adjustments, indicating that these parameters and the relationship between them are robust to coordinative challenges within a range of cadence, body orientation and seat position that is used in regular cycling
Enteric Neurospheres Are Not Specific to Neural Crest Cultures: Implications for Neural Stem Cell Therapies
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited
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Short-term stream water temperature observations permit rapid assessment of potential climate change impacts
Assessment of potential climate change impacts on stream water temperature (Tₛ) across large scales remains challenging for resource managers because energy exchange processes between the atmosphere and the stream environment are complex and uncertain, and few long-term datasets are available to evaluate changes over time. In this study, we demonstrate how simple monthly linear regression models based on short-term historical Tₛ observations and readily available interpolated air temperature (Tₐ) estimates can be used for rapid assessment of historical and future changes in Tₛ. Models were developed for 61 sites in the southeastern USA using ≥18 months of observations and were validated at sites with longer periods of record. The Tₛ models were then used to estimate temporal changes in Tₛ at each site using both historical estimates and future Tₐ projections. Results suggested that the linear regression models adequately explained the variability in Tₛ across sites, and the relationships between Tₛ and Tₐ remained consistent over 37 years. We estimated that most sites had increases in historical annual mean Tₛ between 1961 and 2010 (mean of +0.11 °C decade⁻¹). All 61 sites were projected to experience increases in Tₛ from 2011 to 2060 under the three climate projections evaluated (mean of +0.41 °Cdecade⁻¹). Several of the sites with the largest historical and future Tₛ changes were located in ecoregions home to temperature-sensitive fish species. This methodology can be used by resource managers for rapid assessment of potential climate change impacts on stream water temperature
Deflationary cosmology: observational expressions
We discuss the classical cosmological tests for a large class of FRW type
models driven by a decaying vacuum energy density. Analytic expressions for the
lookback time, age of the universe, luminosity distance, angular diameter, and
galaxy number counts versus redshift are derived and their meaning discussed in
detail. It is found that the standard FRW results are significantly altered,
showing that such tests may constrain the physical parameters of these models
which are also in agreement to the accelerated expansion suggested by the
latest SNe type Ia observations.Comment: 8 pages, 8 figures, LaTe
Clinical outcome of endonasal KTP laser assisted dacryocystorhinostomy
BACKGROUND: To evaluate the clinical outcome of primary endonasal laser assisted dacryocystorhinostomy (ENL-DCR) using the potassium-titanyl-phosphate laser. METHODS: We retrospectively reviewed all primary ENL-DCRs performed within a period of twelve months by the same combined Ophthalmology and Otorhinolaringology team in Freeman Hospital, Newcastle upon Tyne, UK. The main outcome measure for success was resolution or significant improvement of epiphora. Details of surgery, intraoperative and postoperative complications, as well as pathology associated with failure were also studied. Patients were followed up for at least 12 months. RESULTS: A total of 41 consecutive ENL-DCRs on 29 patients (22 females, 7 males, mean age 75 years) were analysed. All patients had bicanalicular silicone intubation for at least 4 months. The success rate at 12 months postoperatively was 78.1%. Pathology associated with failure included: intranasal pathology (12.2%), mucocele (7.3%), and systemic sarcoidosis (2.4%). No significant intra-operative complications were recorded. CONCLUSION: The ENL-DCR with potassium-titanyl-phosphate laser can be considered as a safe and efficient primary procedure for the treatment of nasolacrimal duct obstruction
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