Ecology - Is coral bleaching really adaptive?

From an experiment in which corals are transplanted between two depths on a Panamanian coral reef, Baker1 infers that bleaching may sometimes help reef corals to survive environmental change. Although Baker's results hint at further mechanisms by which reef-building corals may acclimatize to changing light conditions, we do not consider that the evidence supports his inference.

PETAL LOSS, a trihelix transcription factor gene, regulates perianth architecture in the Arabidopsis flower

Perianth development is specifically disrupted in mutants of the PETAL LOSS (PTL) gene, particularly petal initiation and orientation. We have cloned PTL and show that it encodes a plant-specific trihelix transcription factor, one of a family previously known only as regulators of light-controlled genes. PTL transcripts were detected in the early-developing flower, in four zones between the initiating sepals and in their developing margins. Strong misexpression of PTL in a range of tissues universally results in inhibition of growth, indicating that its normal role is to suppress growth between initiating sepals, ensuring that they remain separate. Consistent with this, sepals are sometimes fused in ptl single mutants, but much more frequently in double mutants with either of the organ boundary genes cup-shaped cotyledon1 or 2. Expression of PTL within the newly arising sepals is apparently prevented by the PINOID auxin-response gene. Surprisingly, PTL expression could not be detected in petals during the early stages of their development, so petal defects associated with PTL loss of function may be indirect, perhaps involving disruption to signalling processes caused by overgrowth in the region. PTL-driven reporter gene expression was also detected at later stages in the margins of expanding sepals, petals and stamens, and in the leaf margins; thus, PTL may redundantly dampen lateral outgrowth of these organs, helping define their final shape.

Modeling the optical constants of solids using acceptance-probability-controlled simulated annealing with an adaptive move generation procedure

The acceptance-probability-controlled simulated annealing with an adaptive move generation procedure, an optimization technique derived from the simulated annealing algorithm, is presented. The adaptive move generation procedure was compared against the random move generation procedure on seven multiminima test functions, as well as on the synthetic data, resembling the optical constants of a metal. In all cases the algorithm proved to have faster convergence and superior escaping from local minima. This algorithm was then applied to fit the model dielectric function to data for platinum and aluminum.

The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

Aspects of adaptive management of coastal wetlands: Case studies of processes, conservation, restoration, impacts and assessment

Coastal wetlands are dynamic and include the freshwater-intertidal interface. In many parts of the world such wetlands are under pressure from increasing human populations and from predicted sea-level rise. Their complexity and the limited knowledge of processes operating in these systems combine to make them a management challenge.Adaptive management is advocated for complex ecosystem management (Hackney 2000; Meretsky et al. 2000; Thom 2000;National Research Council 2003).Adaptive management identifies management aims,makes an inventory/environmental assessment,plans management actions, implements these, assesses outcomes, and provides feedback to iterate the process (Holling 1978;Walters and Holling 1990). This allows for a dynamic management system that is responsive to change. In the area of wetland management recent adaptive approaches are exemplified by Natuhara et al. (2004) for wild bird management, Bunch and Dudycha (2004) for a river system, Thom (2000) for restoration, and Quinn and Hanna (2003) for seasonal wetlands in California. There are many wetland habitats for which we currently have only rudimentary knowledge (Hackney 2000), emphasizing the need for good information as a prerequisite for effective management. The management framework must also provide a way to incorporate the best available science into management decisions and to use management outcomes as opportunities to improve scientific understanding and provide feedback to the decision system. Figure 9.1 shows a model developed by Anorov (2004) based on the process-response model of Maltby et al. (1994) that forms a framework for the science that underlies an adaptive management system in the wetland context.