Field measurements of the CO2 evolution rate under different crops during an irrigation cycle in a mountain oasis of Oman

For millennia oasis agriculture has been the backbone of rural livelihood in the desertic Sultanate of Oman. However, little is known about the functioning of these oasis systems, in particular with respect to the C turnover. The objective was to determine the effects of crop, i.e. alfalfa, wheat and bare fallow on the CO2 evolution rate during an irrigation cycle in relation to changes in soil water content and soil temperature. The gravimetric soil water content decreased from initially 24% to approximately 16% within 7 days after irrigation. The mean CO2 evolution rates increased significantly in the order fallow (27.4 mg C m^−2 h^−1) < wheat (45.5 mg C m^−2 h^−1) < alfalfa (97.5 mg C m^−2 h^−1). It can be calculated from these data that the CO2 evolution rate of the alfalfa root system was nearly four times higher than the corresponding rate in the wheat root system. The decline in CO2 evolution rate, especially during the first 4 days after irrigation, was significantly related to the decline in the gravimetric water content, with r = 0.70. CO2 evolution rate and soil temperature at 5 cm depth were negatively correlated (r = -0.56,n = 261) due to increasing soil temperature with decreasing gravimetric water content.

Evolving Distributed Algorithms with Genetic Programming

Distributed systems are one of the most vital components of the economy. The most prominent example is probably the internet, a constituent element of our knowledge society. During the recent years, the number of novel network types has steadily increased. Amongst others, sensor networks, distributed systems composed of tiny computational devices with scarce resources, have emerged. The further development and heterogeneous connection of such systems imposes new requirements on the software development process. Mobile and wireless networks, for instance, have to organize themselves autonomously and must be able to react to changes in the environment and to failing nodes alike. Researching new approaches for the design of distributed algorithms may lead to methods with which these requirements can be met efficiently. In this thesis, one such method is developed, tested, and discussed in respect of its practical utility. Our new design approach for distributed algorithms is based on Genetic Programming, a member of the family of evolutionary algorithms. Evolutionary algorithms are metaheuristic optimization methods which copy principles from natural evolution. They use a population of solution candidates which they try to refine step by step in order to attain optimal values for predefined objective functions. The synthesis of an algorithm with our approach starts with an analysis step in which the wanted global behavior of the distributed system is specified. From this specification, objective functions are derived which steer a Genetic Programming process where the solution candidates are distributed programs. The objective functions rate how close these programs approximate the goal behavior in multiple randomized network simulations. The evolutionary process step by step selects the most promising solution candidates and modifies and combines them with mutation and crossover operators. This way, a description of the global behavior of a distributed system is translated automatically to programs which, if executed locally on the nodes of the system, exhibit this behavior. In our work, we test six different ways for representing distributed programs, comprising adaptations and extensions of well-known Genetic Programming methods (SGP, eSGP, and LGP), one bio-inspired approach (Fraglets), and two new program representations called Rule-based Genetic Programming (RBGP, eRBGP) designed by us. We breed programs in these representations for three well-known example problems in distributed systems: election algorithms, the distributed mutual exclusion at a critical section, and the distributed computation of the greatest common divisor of a set of numbers. Synthesizing distributed programs the evolutionary way does not necessarily lead to the envisaged results. In a detailed analysis, we discuss the problematic features which make this form of Genetic Programming particularly hard. The two Rule-based Genetic Programming approaches have been developed especially in order to mitigate these difficulties. In our experiments, at least one of them (eRBGP) turned out to be a very efficient approach and in most cases, was superior to the other representations.

Protein Folding Simulations: Confinement, External Fields and Sequence Design

The present Thesis looks at the problem of protein folding using Monte Carlo and Langevin simulations, three topics in protein folding have been studied: 1) the effect of confining potential barriers, 2) the effect of a static external field and 3) the design of amino acid sequences which fold in a short time and which have a stable native state (global minimum). Regarding the first topic, we studied the confinement of a small protein of 16 amino acids known as 1NJ0 (PDB code) which has a beta-sheet structure as a native state. The confinement of proteins occurs frequently in the cell environment. Some molecules called Chaperones, present in the cytoplasm, capture the unfolded proteins in their interior and avoid the formation of aggregates and misfolded proteins. This mechanism of confinement mediated by Chaperones is not yet well understood. In the present work we considered two kinds of potential barriers which try to mimic the confinement induced by a Chaperon molecule. The first kind of potential was a purely repulsive barrier whose only effect is to create a cavity where the protein folds up correctly. The second kind of potential was a barrier which includes both attractive and repulsive effects. We performed Wang-Landau simulations to calculate the thermodynamical properties of 1NJ0. From the free energy landscape plot we found that 1NJ0 has two intermediate states in the bulk (without confinement) which are clearly separated from the native and the unfolded states. For the case of the purely repulsive barrier we found that the intermediate states get closer to each other in the free energy landscape plot and eventually they collapse into a single intermediate state. The unfolded state is more compact, compared to that in the bulk, as the size of the barrier decreases. For an attractive barrier modifications of the states (native, unfolded and intermediates) are observed depending on the degree of attraction between the protein and the walls of the barrier. The strength of the attraction is measured by the parameter $\epsilon$. A purely repulsive barrier is obtained for $\epsilon=0$ and a purely attractive barrier for $\epsilon=1$. The states are changed slightly for magnitudes of the attraction up to $\epsilon=0.4$. The disappearance of the intermediate states of 1NJ0 is already observed for $\epsilon =0.6$. A very high attractive barrier ($\epsilon \sim 1.0$) produces a completely denatured state. In the second topic of this Thesis we dealt with the interaction of a protein with an external electric field. We demonstrated by means of computer simulations, specifically by using the Wang-Landau algorithm, that the folded, unfolded, and intermediate states can be modified by means of a field. We have found that an external field can induce several modifications in the thermodynamics of these states: for relatively low magnitudes of the field ($<2.06 \times 10^8$ V/m) no major changes in the states are observed. However, for higher magnitudes than ($6.19 \times 10^8$ V/m) one observes the appearance of a new native state which exhibits a helix-like structure. In contrast, the original native state is a $\beta$-sheet structure. In the new native state all the dipoles in the backbone structure are aligned parallel to the field. The design of amino acid sequences constitutes the third topic of the present work. We have tested the Rate of Convergence criterion proposed by D. Gridnev and M. Garcia ({\it work unpublished}). We applied it to the study of off-lattice models. The Rate of Convergence criterion is used to decide if a certain sequence will fold up correctly within a relatively short time. Before the present work, the common way to decide if a certain sequence was a good/bad folder was by performing the whole dynamics until the sequence got its native state (if it existed), or by studying the curvature of the potential energy surface. There are some difficulties in the last two approaches. In the first approach, performing the complete dynamics for hundreds of sequences is a rather challenging task because of the CPU time needed. In the second approach, calculating the curvature of the potential energy surface is possible only for very smooth surfaces. The Rate of Convergence criterion seems to avoid the previous difficulties. With this criterion one does not need to perform the complete dynamics to find the good and bad sequences. Also, the criterion does not depend on the kind of force field used and therefore it can be used even for very rugged energy surfaces.

Effects of fertilizer type and rate on partitioning of soil organic matter into pools of different stability

Type and rate of fertilizers influence the level of soil organic carbon (Corg) and total nitrogen (Nt) markedly, but the effect on C and N partitioning into different pools is open to question. The objectives of the present work were to: (i) quantify the impact of fertilizer type and rate on labile, intermediate and passive C and N pools by using a combination of biological, chemical and mathematical methods; (ii) explain previously reported differences in the soil organic matter (SOM) levels between soils receiving farmyard manure with or without biodynamic preparations by using Corg time series and information on SOM partitioning; and (iii) quantify the long-term and short-term dynamics of SOM in density fractions and microbial biomass as affected by fertilizer type and rate and determine the incorporation of crop residues into labile SOM fractions. Samples were taken from a sandy Cambisol from the long-term fertilization trial in Darmstadt, Germany, founded in 1980. The nine treatments (four field replicates) were: straw incorporation plus application of mineral fertilizer (MSI) and application of rotted farmyard manure with (DYN) or without (FYM) addition of biodynamic preparations, each at high (140 – 150 kg N ha-1 year-1; MSIH, DYNH, FYMH), medium (100 kg N ha-1 year-1; MSIM, DYNM, FYMM) and low (50 – 60 kg N ha-1 year-1; MSIL, DYNL, FYML) rates. The main findings were: (i) The stocks of Corg (t ha-1) were affected by fertilizer type and rate and increased in the order MSIL (23.6), MSIM (23.7), MSIH (24.2) < FYML (25.3) < FYMM (28.1), FYMH (28.1). Stocks of Nt were affected in the same way (C/N ratio: 11). Storage of C and N in the modelled labile pools (turnover times: 462 and 153 days for C and N, respectively) were not influenced by the type of fertilizer (FYM and MSI) but depended significantly (p ≤ 0.05) on the application rate and ranged from 1.8 to 3.2 t C ha 1 (7 – 13% of Corg) and from 90 to 140 kg N ha-1 (4-5% of Nt). In the calculated intermediate pool (C/N ratio 7), stocks of C were markedly higher in FYM treatments (15-18 t ha-1) compared to MSI treatments (12-14 t ha-1). This showed that differences in SOM stocks in the sandy Cambisol induced by fertilizer rate may be short-lived in case of changing management, but differences induced by fertilizer type may persist for decades. (ii) Crop yields, estimated C inputs (1.5 t ha-1 year-1) with crop residue, microbial bio¬mass C (Cmic, 118 – 150 mg kg-1), microbial biomass N (17 – 20 mg kg-1) and labile C and N pools did not differ significantly between FYM and DYN treatments. However, labile C increased linearly with application rate (R2 = 0.53) from 7 to 11% of Corg. This also applied for labile N (3.5 to 4.9% of Nt). The higher contents of Corg in DYN treatments existed since 1982, when the first sampling was conducted for all individual treatments. Contents of Corg between DYN and FYM treatments con-verged slightly since then. Furthermore, at least 30% of the difference in Corg was located in the passive pool where a treatment effect could be excluded. Therefore, the reported differences in Corg contents existed most likely since the beginning of the experiment and, as a single factor of biodynamic agriculture, application of bio-dynamic preparations had no effect on SOM stocks. (iii) Stocks of SOM, light fraction organic C (LFOC, ρ ≤ 2.0 g cm-3), light fraction organic N and Cmic decreased in the order FYMH > FYML > MSIH, MSIL for all sampling dates in 2008 (March, May, September, December). However, statistical significance of treatment effects differed between the dates, probably due to dif-ferences in the spatial variation throughout the year. The high proportion of LFOC on total Corg stocks (45 – 55%) highlighted the importance of selective preservation of OM as a stabilization mechanism in this sandy Cambisol. The apparent turnover time of LFOC was between 21 and 32 years, which agreed very well with studies with substantially longer vegetation change compared to our study. Overall, both approaches; (I) the combination of incubation, chemical fractionation and simple modelling and (II) the density fractionation; provided complementary information on the partitioning of SOM into pools of different stability. The density fractionation showed that differences in Corg stocks between FYM and MSI treatments were mainly located in the light fraction, i.e. induced by higher recalcitrance of the organic input in the FYM treatments. Moreover, the use of the combination of biological, chemical and mathematical methods indicated that effects of fertilizer rate on total Corg and Nt stocks may be short-lived, but that the effect of fertilizer type may persist for longer time spans in the sandy Cambisol.