6 resultados para TOP PREDATORS

em National Center for Biotechnology Information - NCBI


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Although most ecologists agree that both top-down and bottom-up forces (predation and resource limitation, respectively) act in concert to influence populations of herbivores, it has proven difficult to estimate the relative contributions of such forces in terrestrial systems. Using a combination of time–series analysis of population counts recorded over 16 years and experimental data, we present the first estimates of the relative roles of top-down and bottom-up forces on the population dynamics of two terrestrial insect herbivores on the English oak (Quercus robur). Data suggest that temporal variation in winter moth, Operophtera brumata, density is dominated by time-lagged effects of pupal predators. By comparison, spatial variation in O. brumata density is dominated by host–plant quality. Overall, top-down forces explain 34.2% of population variance, bottom-up forces explain 17.2% of population variance, and 48.6% remains unexplained. In contrast, populations of the green oak tortrix, Tortrix viridana, appear dominated by bottom-up forces. Resource limitation, expressed as intraspecific competition among larvae for oak leaves, explains 29.4% of population variance. Host quality effects explain an additional 5.7% of population variance. We detected no major top-down effects on T. viridana populations. An unknown factor causing a linear decline in T. viridana populations over the 16-year study period accounts for most of the remaining unexplained variance. We discuss the observed differences between the insect species and the utility of time–series analysis as a tool in assessing the relative importance of top-down and bottom-up forces on herbivore populations.

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Insight into the dependence of benthic communities on biological and physical processes in nearshore pelagic environments, long considered a “black box,” has eluded ecologists. In rocky intertidal communities at Oregon coastal sites 80 km apart, differences in abundance of sessile invertebrates, herbivores, carnivores, and macrophytes in the low zone were not readily explained by local scale differences in hydrodynamic or physical conditions (wave forces, surge flow, or air temperature during low tide). Field experiments employing predator and herbivore manipulations and prey transplants suggested top-down (predation, grazing) processes varied positively with bottom-up processes (growth of filter-feeders, prey recruitment), but the basis for these differences was unknown. Shore-based sampling revealed that between-site differences were associated with nearshore oceanographic conditions, including phytoplankton concentration and productivity, particulates, and water temperature during upwelling. Further, samples taken at 19 sites along 380 km of coastline suggested that the differences documented between two sites reflect broader scale gradients of phytoplankton concentration. Among several alternative explanations, a coastal hydrodynamics hypothesis, reflecting mesoscale (tens to hundreds of kilometers) variation in the interaction between offshore currents and winds and continental shelf bathymetry, was inferred to be the primary underlying cause. Satellite imagery and offshore chlorophyll-a samples are consistent with the postulated mechanism. Our results suggest that benthic community dynamics can be coupled to pelagic ecosystems by both trophic and transport linkages.

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In a recent article, Hunter uses the late George Varley and George Gradwell’s long-term data on the winter moth (Operophtera brumata) and green tortrix (Tortrix viridana) populations to propose a method of quantifying the relative importance of top-down effects (because of natural enemies) and bottom-up effects (because of resource competition) in influencing population dynamics. We believe this approach is deeply flawed. Using Varley and Gradwell’s winter moth study, we show that the problems with Hunter’s analysis lie in his misinterpretation of the population dynamics and his inappropriate use of statistical techniques. We also emphasize the importance of distinguishing clearly between two quite different things: firstly, top-down and bottom-up regulation of populations and secondly, the much simpler task of categorizing factors affecting changes in population density as either top-down or bottom-up processes.

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One of the fundamental tenets of oncology is that tumors arise from stem cells. In the colon, stem cells are thought to reside at the base of crypts. In the early stages of tumorigenesis, however, dysplastic cells are routinely found at the luminal surface of the crypts whereas the cells at the bases of these same crypts appear morphologically normal. To understand this discrepancy, we evaluated the molecular characteristics of cells isolated from the bases and orifices of the same crypts in small colorectal adenomas. We found that the dysplastic cells at the tops of the crypts often exhibited genetic alterations of adenomatous polyposis coli (APC) and neoplasia-associated patterns of gene expression. In contrast, cells located at the base of these same crypts did not contain such alterations and were not clonally related to the contiguous transformed cells above them. These results imply that development of adenomatous polyps proceeds through a top-down mechanism. Genetically altered cells in the superficial portions of the mucosae spread laterally and downward to form new crypts that first connect to preexisting normal crypts and eventually replace them.

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The hierarchical properties of potential energy landscapes have been used to gain insight into thermodynamic and kinetic properties of protein ensembles. It also may be possible to use them to direct computational searches for thermodynamically stable macroscopic states, i.e., computational protein folding. To this end, we have developed a top-down search procedure in which conformation space is recursively dissected according to the intrinsic hierarchical structure of a landscape's effective-energy barriers. This procedure generates an inverted tree similar to the disconnectivity graphs generated by local minima-clustering methods, but it fundamentally differs in the manner in which the portion of the tree that is to be computationally explored is selected. A key ingredient is a branch-selection algorithm that takes advantage of statistically predictive properties of the landscape to guide searches down the tree branches that are most likely to lead to the physically relevant macroscopic states. Using the computational folding of a β-hairpin-forming peptide as an example, we show that such predictive properties indeed exist and can be used for structure prediction by free-energy global minimization.