Mendelian Executive

A “Mendelian” executive is proposed as an image of strategy-making that lies intermediate between the grand strategist suggested by rational choice approaches and a Darwinian process of random variation and market-based differential selection. The Mendelian executive is capable of intentional design efforts in order to explore possible adjacent strategic spaces. Furthermore, the argument developed here highlights the role of intentionality with respect to selection processes within the organization, and the culling and amplification of strategic initiatives. The firm is viewed as operating an “artificial selection” environment in contrast to selection as the direct consequence of the outcome of competitive processes. Examining the nature of the processes generating these experimental variants and the bases of internal selection, and how these selection criteria may themselves change, is argued to be central to the formation of strategy in dynamic environments.

Environmental changes dictate selection and nonspecific epistasis in an empirical phenotype-environment-fitness landscape

SummaryThe fitness landscape, a function that maps genotypic and phenotypic changes to their effects on fitness, is an invaluable concept in evolutionary biochemistry. Though widely discussed, measurements of phenotype-fitness landscapes in proteins remain scarce. Here, we quantify all single mutational effects on fitness and phenotype (antibiotic resistance level) of VIM-2 β-lactamase (5600 variants) across a 64-fold range of ampicillin concentrations by deep mutational scanning. We then construct a phenotype-fitness landscape that takes variations in environmental selection pressure into account (a phenotype-environment-fitness landscape). We found that a simple, empirical landscape accurately models the ~39,000 mutational data points, which suggests the evolution of VIM-2 can be predicted based on the selection environment. Our landscape provides new quantitative knowledge on the evolution of the β-lactamases and proteins in general, particularly their evolutionary dynamics under sub-inhibitory antibiotic concentrations, as well as the mechanisms and environmental dependence of nonspecific epistasis.

Evolutionäärinen tulkinta sektoritutkimuksen rakenteellisesta kehittämisestä ympäristö- ja luonnonvara- alalla

The evolutionary approach to the long-term change in Finnish public research system The article examines long-term structural change in Finland’s public research institutes system within the framework of evolutionary organization theory, focusing on evolutionary features, selection environment and key mechanisms. Empirical data is gathered by thematic interviews. Observation is that the mission to support evolutionary over revolutionary change has been gradually accomplished but opposing forces in selection environment have complicated the process. The aim to promote horizontal cooperation between sectorial institutes has formed new collaborative variants to system, but these have not been able to compete with institute fusion strategy.

Selection Criteria and Selection Environment for Drought Tolerance of Egyptian Wheat (Triticum aestivum L.) Landraces

Strong correlations between wheat traits and drought tolerance (DT) associated with high heritability and high genetic advance from selection would allow plant breeder to use such traits as selection criteria. The objective of the present investigation was to determine the optimum selection criteria and selection environment for drought tolerance via estimation of correlation coefficients (r) among 13 agronomic, grain yield and quality traits and DT of 20 wheat landraces, broad-sense heritability (h2b) and genetic advance (GA) from selection for such traits under well-watered (WW) and water stressed (WS) environments. A two-year experiment was carried out using a split-plot design with four replications. Results concluded that the best selection criterion for drought tolerance in our study was grain yield/plant (GYPP), followed by a number of grains/spike (GPS), grain filling period (GFP), grain starch (GSC) and protein (GPC) content, plant height (PH) and days to maturity (DTM), since they showed high (r), high h2b and high GA estimates. The best selection environment was WW for days to anthesis, PH, spikes/plant, GPS, spikelets/spike, GYPP, GPC and WS for DTM, GFP, GSC and thousand-grain weight traits. This information could help future breeding programs in selection for improving drought tolerance of wheat.

THE TOLERANCE AND YIELD COMPONENTS OF RICE BREEDING LINES SELECTED UNDER LOW AND OPTIMUM NITROGEN CONDITIONS

<p class="abstrakinggris">One of the important issues on rice breeding is to develop new rice lines suitable for nitrogen efficiency in the suboptimum environment. The study aimed to evaluate the tolerance and yield components of rice breeding lines selected under low and high nitrogen conditions. The F6 generation from two cross-combinations of Gampai/IR77674 and Progol/Asahan, were evaluated in the dry season of 2014 under N suboptimum and N optimum conditions. A total of 172 lines plus six check varieties derived from the low and high N environment selection were evaluated under low N rate (34.5 kg N ha^-1) and high N rate (138 kg N ha^-1), arranged in an augmented design. Six check varieties were relocated three times in each block. Plot size was 5.5 m² and plant spacing 20 cm x 20 cm. Data were collected for grain yield and major yield components. Results showed that the <span class="tlid-translation">different status of nitrogen fertilizer affected the number of productive fillers, number of filled grains, 100-grain weight, and grain yield.</span> Different cross combinations exhibited different results in the progeny performance. Ten lines have a higher yield also tolerant to low N condition, i.e. B14250F-6-9, B14250F-1-4, B14250F-9-9, B14250F-6-4, B14250F-5-2, B14262F-15-6, B14250F-2-6, B14262F-12-4, B14250F-5-1, and B14250F-11-4. Thus, to obtain the N tolerant lines, selection at a low N environment was more effective compared with the optimum selection environment.</p>