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D.C. Freeman

Publications and source records attributed to D.C. Freeman.

21 records · Page 2Linked to original sources

Nonlinear growth dynamics and the origin of fluctuating asymmetry

The nonlinear, complex nature of biosynthesis magnifies the impacts of small, random perturbations on organism growth, leading to distortions in adaptive allometries and, in particular, to fluctuating asymmetry. These distortions can be partly checked by cell-cell and inter-body part feedback during growth and development, though the latter mechanism also may lead to complex patterns in right-left asymmetry. Stress can be expected to increase the degree to which random growth perturbations are magnified and may also result in disruption of the check mechanisms, thus exaggerating fluctuating asymmetry. The processes described not only provide one explanation for the existence of fluctuating asymmetry and its augmentation under stress, but suggest additional effects of stress as well. Specifically, stress is predicted to lead to decreased fractal dimension of bone sutures and branching structures in animals, and in increased dimension of growth trace patterns such as those found in mollusc shells and fish otoliths and scales. A basic yet broad primer on fractals and chaos is provided as background for the theoretical development in this manuscript.

Genetica↗

Interaction assessment: Rationale and a test using plants

A non-manipulative method for deriving empirical expressions of population growth parameters from simple field data is presented. The derived expressions can be used to assess the intensity and form of density dependence and interspecies interactions, and have potential for parameterizing more mechanistic models of population dynamics and for use in applied ecology, e.g. land management or environmental risk assessment. The method is based on an assertion of invariant expected fitness across occupied microhabitats. Hence, its success depends upon the degree to which that assertion holds. The assertion, as used here, is broadly applicable. Thus, the method can be expected to yield reliable results even in nonequilibrium communities. Here, we apply the method to data on six desert plant species. Expressions generated from data in one stand, in one year, successfully predict plant cover values in other stands and years. The predicted patterns of plant species interactions are discussed in the light of current knowledge and theorics of desert succession.

Evolutionary Ecology↗