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Turning randomness into meaning at the molecular level using Muller's morphs.

ABSTRACT: While evolutionary theory follows from observable facts and logical inferences (Mayr, 1985), historically, the origin of novel inheritable variations was a major obstacle to acceptance of natural selection (Bowler, 1992; Bowler, 2005). While molecular mechanisms address this issue (Jablonka and Lamb, 2005), analysis of responses to the Biological Concept Inventory (BCI) (Klymkowsky et al., 2010), revealed that molecular biology majors rarely use molecular level ideas in their discourse, implying that they do not have an accessible framework within which to place evolutionary variation. We developed a "Socratic tutorial" focused on Muller's categorization of mutations' phenotypic effects (Muller, 1932). Using a novel vector-based method to analyzed students' essay responses, we found that a single interaction with this tutorial led to significant changes in thinking toward a clearer articulation of the effects of mutational change. We suggest that Muller's morphs provides an effective framework for facilitating student learning about mutational effects and evolutionary mechanisms.

SUBMITTER: Henson K

PROVIDER: S-EPMC3509460 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

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Turning randomness into meaning at the molecular level using Muller's morphs.

Henson Kathleen K Cooper Melanie M MM Klymkowsky Michael W MW

Biology open 20120227 4

While evolutionary theory follows from observable facts and logical inferences (Mayr, 1985), historically, the origin of novel inheritable variations was a major obstacle to acceptance of natural selection (Bowler, 1992; Bowler, 2005). While molecular mechanisms address this issue (Jablonka and Lamb, 2005), analysis of responses to the Biological Concept Inventory (BCI) (Klymkowsky et al., 2010), revealed that molecular biology majors rarely use molecular level ideas in their discourse, implying ...[more]

PMID: 23213431

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Project description:BackgroundWhen assessing connectivity, it is crucial to rely on accurate modeling frameworks that consider species movement preferences and patterns. One important aspect is the level of randomness or unpredictability in the route selection. In this respect, traditional approaches (based on least-cost path or circuit theory) consider species movements unrealistically as totally deterministic or as totally random. A recent approach (randomized shortest path) advocates for choosing intermediate levels of randomness through a single parameter. This parameter may be optimized by validating connectivity surfaces developed from different levels of randomness against observed movement data. However, connectivity models are seldom validated, and it is still unclear how to approach this task. To address this knowledge gap, this paper aims at comparing different validation methods to infer the optimal randomness level in connectivity studies. Additionally, we aimed to disentangle the practical consequences of applying traditional connectivity approaches versus using an optimized level of movement randomness when delineating corridors.MethodsThese objectives were accomplished through the study case of the Iberian lynx, an endangered species whose maintenance and recovery depend on the current connectivity among its population nuclei. We firstly determined a conductance surface based on point selection functions accounting for the behavioral state (territorial or exploratory) of individuals. Secondly, we identified the level of randomness that better fits lynxes' movements with independent GPS locations and different validation techniques. Lastly, we delineated corridors between lynx population nuclei through a) the randomized shortest path approach and the extreme and optimal levels of randomness of each validation method, and b) the traditional connectivity approaches.ResultsAccording to all used validation methodologies, models with intermediate levels of randomness outperformed those with extreme randomness levels representing totally deterministic or random movements. We found differences in the optimal randomness level among validation methods but similar results in the delineation of corridors. Our results also revealed that models with extreme randomness levels (deterministic and random walk) of the randomized path approach provided equivalent corridor networks to those from traditional approaches. Moreover, these corridor networks calculated with traditional approaches showed notable differences in patterns from the corridor network calculated with an optimized randomness level.ConclusionsHere we presented a connectivity model with a solid biological basis that calibrates the level of movement randomness and is supported by comprehensive validation methods. It is thus a step forward in the search and evaluation of connectivity approaches that lead to improved, efficient, and successful management actions.

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Turning randomness into meaning at the molecular level using Muller's morphs.

Publications

Turning randomness into meaning at the molecular level using Muller's morphs.

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