Controlled ecological life support system - biological problems

The general processes and controls associated with two distinct experimental paradigms are examined. Specific areas for research related to biotic production (food production) and biotic decomposition (waste management) are explored. The workshop discussions were directed toward Elemental cycles and the biological factors that affect the transformations of nutrients into food, of food material into waste, and of waste into nutrients were discussed. To focus on biological issues, the discussion assumed that (1) food production would be by biological means (thus excluding chemical synthesis), (2) energy would not be a limiting factor, and (3) engineering capacity for composition and leak rate would be adequate

Atmosphere Behavior in Gas-Closed Mouse-Algal Systems: An Experimental and Modelling Study

A dual approach of mathematical modelling and laboratory experimentation aimed at examining the gas exchange characteristics of artificial animal/plant systems closed to the ambient atmosphere was initiated. The development of control techniques and management strategies for maintaining the atmospheric levels of carbon dioxide and oxygen at physiological levels is examined. A mathematical model simulating the atmospheric behavior in these systems was developed and an experimental gas closed system was constructed. These systems are described and preliminary results are presented

Controlled Ecological Life Support System. First Principal Investigators Meeting

Control problems in autonomous life support systems, CELSS candidate species, maximum grain yield, plant growth, waste management, air pollution, and mineral separation are discussed

The Interaction of Global Biochemical Cycles

The global biosphere in an exceedingly complex system. To gain an understanding of its structure and dynamic features, it is necessary not only to increase the knowledge about the detailed processes but also to develop models of how global interactions take place. Attempts to analyze the detailed physical, chemical and biological processes in this context need to be guided by an advancement of understanding of the latter. It is necessary to develop a strategy of data gathering that severs both these purposes simultaneously. The following papers deal with critical aspects in the global cycles of carbon, nitrogen, phosphorus and sulfur in details as well as the cycle of water and the flow of energy in the Earth's environment. The objective is to set partly the foundation for the development of mathematical models that allow exploration of the coupled dynamics of the global cycles of carbon, nitrogen, phosphorus, sulfur, as well as energy and water flux

Potential net primary productivity in South America: application of a global model

We use a mechanistically based ecosystem simulation model to describe and analyze the spatial and temporal patterns of terrestrial net primary productivity (NPP) in South America. The Terrestrial Ecosystem Model (TEM) is designed to predict major carbon and nitrogen fluxes and pool sizes in terrestrial ecosystems at continental to global scales. Information from intensively studies field sites is used in combination with continental—scale information on climate, soils, and vegetation to estimate NPP in each of 5888 non—wetland, 0.5° latitude °0.5° longitude grid cells in South America, at monthly time steps. Preliminary analyses are presented for the scenario of natural vegetation throughout the continent, as a prelude to evaluating human impacts on terrestrial NPP. The potential annual NPP of South America is estimated to be 12.5 Pg/yr of carbon (26.3 Pg/yr of organic matter) in a non—wetland area of 17.0 ° 106 km2. More than 50% of this production occurs in the tropical and subtropical evergreen forest region. Six independent model runs, each based on an independently derived set of model parameters, generated mean annual NPP estimates for the tropical evergreen forest region ranging from 900 to 1510 g°m—2°yr—1 of carbon, with an overall mean of 1170 g°m—2°yr—1. Coefficients of variation in estimated annual NPP averaged 20% for any specific location in the evergreen forests, which is probably within the confidence limits of extant NPP measurements. Predicted rates of mean annual NPP in other types of vegetation ranged from 95 g°m—2°yr—1 in arid shrublands to 930 g°m@?yr—1 in savannas, and were within the ranges measured in empirical studies. The spatial distribution of predicted NPP was directly compared with estimates made using the Miami mode of Lieth (1975). Overall, TEM predictions were °10% lower than those of the Miami model, but the two models agreed closely on the spatial patterns of NPP in south America. Unlike previous models, however, TEM estimates NPP monthly, allowing for the evaluation of seasonal phenomena. This is an important step toward integration of ecosystem models with remotely sensed information, global climate models, and atmospheric transport models, all of which are evaluated at comparable spatial and temporal scales. Seasonal patterns of NPP in South America are correlated with moisture availability in most vegetation types, but are strongly influenced by seasonal differences in cloudiness in the tropical evergreen forests. On an annual basis, moisture availability was the factor that was correlated most strongly with annual NPP in South America, but differences were again observed among vegetation types. These results allow for the investigation and analysis of climatic controls over NPP at continental scales, within and among vegetation types, and within years. Further model validation is needed. Nevertheless, the ability to investigate NPP—environment interactions with a high spatial and temporal resolution at continental scales should prove useful if not essential for rigorous analysis of the potential effects of global climate changes on terrestrial ecosystems

Assessment of Keratitis Damage in an Age Dependent Mouse Model Using Analytical Software

Background: Streptococcus pneumoniae (pneumococcus) is a grampositive bacterium that is responsible for diseases such as, otitis media, conjunctivitis, bacterial keratitis, pneumonia, and meningitis. Bacterial keratitis is one of the most common after-effects of trauma to the eye. Some reports have shown the S. pneumoniae spreads through enzymes that are produced to digest the cornea, which in turn can causes blindness. There is a need for more improved measures that can reverse the detrimental effects of the bacteria. The long-term goal of this research is to better understand the complete role of S. pneumoniae and its components in bacterial keratitis to develop next generation therapies to prevent blindness. The purpose of this study is to develop alternative measures to evaluate damage associated with keratitis infection by use of computer applications. Methods: This study analyzed images of the established Keratitis pneumococcal mouse model. The eye images of mice 7-8-week-old and 9-month-old were collected. Additional images were taken on post-infection days one, three, five, and nine, revealing the progression of the infection. Results: The ImageJ Application provided more in depth review to determine the detrimental effects of S. pneumoniae. Through the software, a “Color Threshold” was created on every image to emphasize the area of damage caused by the bacteria. A scatter plot of every image created a map of the particles, and the diameter created a scale demonstrating the impact of keratitis. Data revealed that the most significant increase in infection occurs between Day 1 and 3 post-infection. Conclusions: The study has created a computer model to establish a baseline for the infection process of S. pneumoniae in the traditional mouse model. ImageJ has proven to be a useful tool to analyze the impact of disease on the murine model. Results from this study also provide evidence of the importance of early intervention in ocular disease

Two-Dimensional Topology of the 2dF Galaxy Redshift Survey

We study the topology of the publicly available data released by the 2dFGRS. The 2dFGRS data contains over 100,000 galaxy redshifts with a magnitude limit of b_J=19.45 and is the largest such survey to date. The data lie over a wide range of right ascension (75 degree strips) but only within a narrow range of declination (10 degree and 15 degree strips). This allows measurements of the two-dimensional genus to be made. The NGP displays a slight meatball shift topology, whereas the SGP displays a bubble like topology. The current SGP data also have a slightly higher genus amplitude. In both cases, a slight excess of overdense regions are found over underdense regions. We assess the significance of these features using mock catalogs drawn from the Virgo Consortium's Hubble Volume LCDM z=0 simulation. We find that differences between the NGP and SGP genus curves are only significant at the 1 sigma level. The average genus curve of the 2dFGRS agrees well with that extracted from the LCDM mock catalogs. We compare the amplitude of the 2dFGRS genus curve to the amplitude of a Gaussian random field with the same power spectrum as the 2dFGRS and find, contradictory to results for the 3D genus of other samples, that the amplitude of the GRF genus curve is slightly lower than that of the 2dFGRS. This could be due to a a feature in the current data set or the 2D genus may not be as sensitive as the 3D genus to non-linear clustering due to the averaging over the thickness of the slice in 2D. (Abridged)Comment: Submitted to ApJ A version with Figure 1 in higher resolution can be obtained from http://www.physics.drexel.edu/~hoyle

The Topology of Cosmological Reionization

Using the largest cosmological reionization simulation to-date (~24 billion particles), we use the genus curve to quantify the topology of neutral hydrogen distribution on scales > 1 Mpc as it evolves during cosmological reionization. We find that the reionization process proceeds primarily in an inside-out fashion, where higher density regions become ionized earlier than lower density regions. There are four distinct topological phases: (1) Pre-reionization at z ~ 15, when the genus curve is consistent with a Gaussian density distribution. (2) Pre-overlap at 10 < z < 15, during which the number of HII bubbles increases gradually with time, until percolation of HII bubbles starts to take effect, characterized by a very flat genus curve at high volume fractions. (3) Overlap at 8 < z < 10, when large HII bubbles rapidly merge, manifested by a precipitous drop in the amplitude of the genus curve. (4) Post-overlap at 6 < z < 8, when HII bubbles have mostly overlapped and the genus curve is consistent with a diminishing number of isolated neutral islands. After the end of reionization (z < 6), the genus of neutral hydrogen is consistent with Gaussian random phase, in agreement with observations.Comment: 9 pages, 6 figures, accepted by Ap

Extracting ecological and biophysical information from AVHRR optical data: An integrated algorithm based on inverse modeling

Satellite remote sensing provides the only means of directly observing the entire surface of the Earth at regular spatial and temporal intervals