The adaptive value of carry-over effects, the persistence of induced phenotypes for several generations despite the change in the conditions that first induced these phenotypes, is studied in the framework of a simple model. Three different organismal strategies-non-inducible (genetic), completely inducible (plastic), and intermediate (carry-over)-are compared in fitness terms within three different environments. Analytical results and numerical simulations show that carry-over effects can have an advantage in stochastic environments even over organisms with high adaptive plasticity. We argue that carry-over effects represent an adaptive mechanism on the ecological timescale that fills the gap between short-term individual adaptations and long-term evolutionary adaptations. An extension of the concept of plasticity to incorporate the time dimension and include the stability of induced phenotypes through both clonal and sexual generations, is suggested.
JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. abstract: A change in the environmental conditions across spacefor example, altitude or latitude-can cause significant changes in the density of a vegetation type and, consequently, in spatial connectivity. We use spatially explicit simulations to study the transition from connected to fragmented vegetation. A static (gradient percolation) model is compared to dynamic (gradient contact process) models. Connectivity is characterized from the perspective of various species that use this vegetation type for habitat and differ in dispersal or migration range, that is, "step length" across the landscape. The boundary of connected vegetation delineated by a particular step length is termed the " hull edge." We found that for every step length and for every gradient, the hull edge is a fractal with dimension 7/ 4. The result is the same for different spatial models, suggesting that there are universal laws in ecotone geometry. To demonstrate that the model is applicable to real data, a hull edge of fractal dimension 7/4 is shown on a satellite image of a piñon-juniper woodland on a hillside. We propose to use the hull edge to define the boundary of a vegetation type unambiguously. This offers a new tool for detecting a shift of the boundary due to a climate change.
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