A theory of forest dynamics: Spatially explicit models and issues of scale

Good progress has been made in the first year of DOE grant (number sign) FG02-90ER60933. The purpose of the project is to develop and investigate models of forest dynamics that apply across a range of spatial scales. The grant is one third of a three-part project. The second third was funded by the NSF this year and is intended to provide the empirical data necessary to calibrate and test small-scale (less than or equal to 1000 ha) models. The final third was also funded this year (NASA), and will provide data to calibrate and test the large-scale features of the models

Mirror-grating tuning arrangement for high resolution lasers

A tuning arrangement (10) for a tunable laser comprises a single holographic grating (12) and two flat surface reflective mirrors (13 and 14). The beam (15) from the laser cavity is incident on the grating at a grazing angle for optimum beam expansion. The diffracted beam propogates from the grating to the first mirror (13), therefrom to the second mirror (14) and is reflected at the Littrow angle to the grating, whereat it is diffracted a second time and returned to the second mirror (14) for reflection to the first mirror (13). Therefrom it is reflected back to the grating. After undergoing a third diffraction it is directed back into the cavity for further amplification

Divergent drivers of leaf trait variation within species, among species, and among functional groups.

Understanding variation in leaf functional traits-including rates of photosynthesis and respiration and concentrations of nitrogen and phosphorus-is a fundamental challenge in plant ecophysiology. When expressed per unit leaf area, these traits typically increase with leaf mass per area (LMA) within species but are roughly independent of LMA across the global flora. LMA is determined by mass components with different biological functions, including photosynthetic mass that largely determines metabolic rates and contains most nitrogen and phosphorus, and structural mass that affects toughness and leaf lifespan (LL). A possible explanation for the contrasting trait relationships is that most LMA variation within species is associated with variation in photosynthetic mass, whereas most LMA variation across the global flora is associated with variation in structural mass. This hypothesis leads to the predictions that (i) gas exchange rates and nutrient concentrations per unit leaf area should increase strongly with LMA across species assemblages with low LL variance but should increase weakly with LMA across species assemblages with high LL variance and that (ii) controlling for LL variation should increase the strength of the above LMA relationships. We present analyses of intra- and interspecific trait variation from three tropical forest sites and interspecific analyses within functional groups in a global dataset that are consistent with the above predictions. Our analysis suggests that the qualitatively different trait relationships exhibited by different leaf assemblages can be understood by considering the degree to which photosynthetic and structural mass components contribute to LMA variation in a given assemblage

Connecting to smart cities : analyzing energy times series to visualize monthly electricity peak load in residential buildings

Rapidly growing energy consumption rate is considered an alarming threat to economic stability and environmental sustainability. There is an urgent need of proposing novel solutions to mitigate the drastic impact of increased energy demand in urban cities to improve energy efficiency in smart buildings. It is commonly agreed that exploring, analyzing and visualizing energy consumption patterns in residential buildings can help to estimate their energy demands. Moreover, visualizing energy consumption patterns of residential buildings can also help to diagnose if there is any unpredictable increase in energy demand at a certain time period. However, visualizing and inferring energy consumption patterns from typical line graphs, bar charts, scatter plots is obsolete, less informative and do not provide deep and significant insight of the daily domestic demand of energy utilization. Moreover, these methods become less significant when high temporal resolution is required. In this research work, advanced data exploratory and data analytics techniques are applied on energy time series. Data exploration results are presented in the form of heatmap. Heatmap provides a significant insight of energy utilization behavior during different times of the day. Heatmap results are articulated from three analytical perspectives; descriptive analysis, diagnostic analysis and contextual analysis

Reaching peak emissions

Rapid growth in global CO2 emissions from fossil fuels and industry ceased in the past two years, despite continued economic growth. Decreased coal use in China was largely responsible, coupled with slower global growth in petroleum and faster growth in renewables

Land Use Sector Involvement in Mitigation Policies Across Carbon Markets

Different local and international experiences show that the agroforestry sector can be fully included in the global warming mitigation strategies and in the market mechanisms that may have environmental and socioeconomic benefits. At present, however, the primary sector plays only a minor role in mitigation policies within the UNFCCC and under Kyoto’s Protocol, due to problems and difficulties related to emission/absorption accounting models andmonitoring and standardisation systems. If, on one hand, the progress in science has enabled to overcome accountingrelated problems, on the other, there are no adequate mechanisms to encourage and remunerate the primary sector’s efforts. More specifically, if the primary sector is considered as a source of emissions, it should also be recognised that it has beneficial impacts, notably in economic terms, as carbon sink. Therefore, the definition of clear and internationally shared rules might increase the carbon friendly initiatives and help reduce greenhouse gas emissions. This article is focused on the international experiences that have concerned the primary sector and is intended to supply researchers and policymakers with suggestions and recommendations for implementing local market practices related to carbon credits

Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits: The elders risk assessment index

<p>Abstract</p> <p>Background</p> <p>The prevention of recurrent hospitalizations in the frail elderly requires the implementation of high-intensity interventions such as case management. In order to be practically and financially sustainable, these programs require a method of identifying those patients most at risk for hospitalization, and therefore most likely to benefit from an intervention. The goal of this study is to demonstrate the use of an electronic medical record to create an administrative index which is able to risk-stratify this heterogeneous population.</p> <p>Methods</p> <p>We conducted a retrospective cohort study at a single tertiary care facility in Rochester, Minnesota. Patients included all 12,650 community-dwelling adults age 60 and older assigned to a primary care internal medicine provider on January 1, 2005. Patient risk factors over the previous two years, including demographic characteristics, comorbid diseases, and hospitalizations, were evaluated for significance in a logistic regression model. The primary outcome was the total number of emergency room visits and hospitalizations in the subsequent two years. Risk factors were assigned a score based on their regression coefficient estimate and a total risk score created. This score was evaluated for sensitivity and specificity.</p> <p>Results</p> <p>The final model had an AUC of 0.678 for the primary outcome. Patients in the highest 10% of the risk group had a relative risk of 9.5 for either hospitalization or emergency room visits, and a relative risk of 13.3 for hospitalization in the subsequent two year period.</p> <p>Conclusions</p> <p>It is possible to create a screening tool which identifies an elderly population at high risk for hospital and emergency room admission using clinical and administrative data readily available within an electronic medical record.</p

Constraining Fossil Fuel CO2 Emissions From Urban Area Using OCO‐2 Observations of Total Column CO2

Satellite observations of the total column dry‐air CO2 (XCO2) are expected to support the quantification and monitoring of fossil fuel CO2 (ffCO2) emissions from urban areas. We evaluate the utility of the Orbiting Carbon Observatory 2 (OCO‐2) XCO2 retrievals to optimize whole‐city emissions, using a Bayesian inversion system and high‐resolution transport modeling. The uncertainties of constrained emissions related to transport model, satellite measurements, and local biospheric fluxes are quantified. For the first two uncertainty sources, we examine cities of different landscapes: “plume city” located in relatively flat terrain, represented by Riyadh and Cairo; and “basin city” located in basin terrain, represented by Los Angeles (LA). The retrieved scaling factors of emissions and their uncertainties show prominent variabilities from track to track, due to the varying meteorological conditions and relative locations of the tracks transecting plumes. To explore the performance of multiple tracks in retrieving emissions, pseudo data experiments are carried out. The estimated least numbers of tracks required to constrain the total emissions for Riyadh (<10% uncertainty), Cairo (<10%), and LA (<5%) are 8, 5, and 7, respectively. Additionally, to evaluate the impact of biospheric fluxes on derivation of the ffXCO2 enhancements, we conduct simulations for Pearl River Delta metropolitan area. Significant fractions of local XCO2 enhancements associated with local biospheric XCO2 variations are shown, which potentially lead to biased estimates of ffCO2 emissions. We demonstrate that satellite measurements can be used to improve urban ffCO2 emissions with a sufficient amount of measurements and appropriate representations of the uncertainty components.Key PointsInversion method is utilized to constrain whole‐city fossil fuel emissions with measurement and transport model errors consideredPotential of incorporating multiple tracks to obtain regular emission estimates is evaluated by pseudo data experimentsSignificant contribution of the biospheric fluxes variability to local XCO2 variation is demonstratedPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154979/1/jgrd56150_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154979/2/jgrd56150.pd

Convergence of bark investment according to fire and climate structures ecosystem vulnerability to future change

Fire regimes in savannas and forests are changing over much of the world. Anticipating the impact of these changes requires understanding how plants are adapted to fire. Here we test whether fire imposes a broad selective force on a key fire-tolerance trait, bark thickness, across 572 tree species distributed worldwide. We show that investment in thick bark is a pervasive adaptation in frequently burned areas across savannas and forests in both temperate and tropical regions where surface fires occur. Geographic variability in bark thickness is largely explained by annual burned area and precipitation seasonality. Combining environmental and species distribution data allowed us to assess the vulnerability to future climate and fire conditions: tropical rainforests are especially vulnerable, whereas seasonal forests and savannas are more robust. The strong link between fire and bark thickness provides an avenue for assessing the vulnerability of tree communities to fire and demands inclusion in global models

Tropical tree height and crown allometries for the Barro Colorado Nature Monument, Panama: a comparison of alternative hierarchical models incorporating interspecific variation in relation to life history traits

Tree allometric relationships are widely employed for estimating forest biomass and production and are basic building blocks of dynamic vegetation models. In tropical forests, allometric relationships are often modeled by fitting scale-invariant power functions to pooled data from multiple species, an approach that fails to capture changes in scaling during ontogeny and physical limits to maximum tree size and that ignores interspecific differences in allometry. Here, we analyzed allometric relationships of tree height (9884 individuals) and crown area (2425) with trunk diameter for 162 species from the Barro Colorado Nature Monument, Panama. We fit nonlinear, hierarchical models informed by species traits – wood density, mean sapling growth, or sapling mortality – and assessed the performance of three alternative functional forms: the scale-invariant power function and the saturating Weibull and generalized Michaelis–Menten (gMM) functions. The relationship of tree height with trunk diameter was best fit by a saturating gMM model in which variation in allometric parameters was related to interspecific differences in sapling growth rates, a measure of regeneration light demand. Light-demanding species attained taller heights at comparatively smaller diameters as juveniles and had shorter asymptotic heights at larger diameters as adults. The relationship of crown area with trunk diameter was best fit by a power function model incorporating a weak positive relationship between crown area and species-specific wood density. The use of saturating functional forms and the incorporation of functional traits in tree allometric models is a promising approach for improving estimates of forest biomass and productivity. Our results provide an improved basis for parameterizing tropical plant functional types in vegetation models.</p