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Understanding Patterns (understanding + pattern)
Selected AbstractsIncreased gyrification in Williams syndrome: evidence using 3D MRI methodsDEVELOPMENTAL MEDICINE & CHILD NEUROLOGY, Issue 5 2002J Eric Schmitt BABS Understanding patterns of gyrification in neurogenetic disorders helps to uncover the neurodevelopmental etiology underlying behavioral phenotypes. This is particularly true in Williams syndrome (WS), a condition caused by de novo deletion of approximately 1 to 2Mb in the 7q11.23 region. Individuals with WS characteristically possess an unusual dissociation between deficits in visual-spatial ability and relative preservations in language, music, and social drive. A preliminary postmortem study reported anomalous gyri and sulci in individuals with WS. The present study examined gyrification patterns in 17 participants with WS (10 females, 7 males; mean age 28 years 11 months, SD 8 years 6 months) and 17 age- and sex-matched typically developing control participants (mean age 29 years 1 month, SD 8 years 1 month) using new automated techniques in MRI. Significantly increased cortical gyrification was found globally with abnormalities being more marked in the right parietal (p=0.0227), right occipital (p=0.0249), and left frontal (p=0.0086) regions. These results suggest that one or more genes in the 7q11.23 region are involved during the critical period when cortical folding occurs, and may be related to the hypothesized dorsal/ventral dissociation in this condition. [source] Evolutionary response of landraces to climate change in centers of crop diversityEVOLUTIONARY APPLICATIONS (ELECTRONIC), Issue 5-6 2010Kristin L. Mercer Abstract Landraces cultivated in centers of crop diversity result from past and contemporary patterns of natural and farmer-mediated evolutionary forces. Successful in situ conservation of crop genetic resources depends on continuity of these evolutionary processes. Climate change is projected to affect agricultural production, yet analyses of impacts on in situ conservation of crop genetic diversity and farmers who conserve it have been absent. How will crop landraces respond to alterations in climate? We review the roles that phenotypic plasticity, evolution, and gene flow might play in sustaining production, although we might expect erosion of genetic diversity if landrace populations or entire races lose productivity. For example, highland maize landraces in southern Mexico do not express the plasticity necessary to sustain productivity under climate change, but may evolve in response to altered conditions. The outcome for any given crop in a given region will depend on the distribution of genetic variation that affects fitness and patterns of climate change. Understanding patterns of neutral and adaptive diversity from the population to the landscape scale is essential to clarify how landraces conserved in situ will continue to evolve and how to minimize genetic erosion of this essential natural resource. [source] Forest landscape pattern in the KwaZulu,Natal midlands, South Africa: 50 years of change or stasis?AUSTRAL ECOLOGY, Issue 6 2004MICHAEL J. LAWES Abstract Understanding patterns and processes of habitat change is essential for managing and conserving forest fragments in anthropogenically altered landscapes. Digitized aerial photographs from 1944 and 1996 were examined for changes to the indigenous forest landscape in the Karkloof-Balgowan archipelago in KwaZulu,Natal, South Africa. Attributes relating to proximate land-use, patch shape, isolation and position in the landscape were used to determine putative causes of forest change. The total change in forest area was ,5.7% (forest covered 6739 ha in 1996). This is contrasted with previous reports for the period 1880,1940 that estimated change in total forest area of up to ,80%. Attrition was the predominant process of forest transformation between 1944 and 1996. Despite little overall change in forest area, 786 mostly small (<0.5 ha) forest patches were lost from the landscape, leaving 1277 forest patches in 1996. An increase in patch isolation, but no change in patch cohesion accompanied the changes in forest area. Ignoring patches that were eliminated, 514 patches decreased in area. This was partly a function of patch size, but the conversion of natural grassland to commercial plantation forestry in the matrix also influenced forest decline. Their small size and irregular shape caused forest patches in the region to be vulnerable to edge effects. Core area declined in a negative exponential way with increasing edge width and the total area of edge habitat exceeded that of core habitat at an edge width of only 50 m. Nevertheless, total core area decreased by only 2% (65 ha) between 1944 and 1996 because most of the eliminated patches were small and contained no core area. The large Karkloof forest (1649 ha) is a conservation priority for forest interior species, but the ecological role and biodiversity value of small forest patches should not be overlooked. [source] Evolution on oceanic islands: molecular phylogenetic approaches to understanding pattern and processMOLECULAR ECOLOGY, Issue 6 2002B. C. Emerson Abstract By their very nature oceanic island ecosystems offer great opportunities for the study of evolution and have for a long time been recognized as natural laboratories for studying evolution owing to their discrete geographical nature and diversity of species and habitats. The development of molecular genetic methods for phylogenetic reconstruction has been a significant advance for evolutionary biologists, providing a tool for answering questions about the diversity among the flora and fauna on such islands. These questions relate to both the origin and causes of species diversity both within an archipelago and on individual islands. Within a phylogenetic framework one can answer fundamental questions such as whether ecologically and/or morphologically similar species on different islands are the result of island colonization or convergent evolution. Testing hypotheses about ages of the individual species groups or entire community assemblages is also possible within a phylogenetic framework. Evolutionary biologists and ecologists are increasingly turning to molecular phylogenetics for studying oceanic island plant and animal communities and it is important to review what has been attempted and achieved so far, with some cautionary notes about interpreting phylogeographical pattern on oceanic islands. [source] Management strategies for plant invasions: manipulating productivity, disturbance, and competitionDIVERSITY AND DISTRIBUTIONS, Issue 3 2004Michael A. Huston ABSTRACT The traditional approach to understanding invasions has focused on properties of the invasive species and of the communities that are invaded. A well-established concept is that communities with higher species diversity should be more resistant to invaders. However, most recently published field data contradict this theory, finding instead that areas with high native plant diversity also have high exotic plant diversity. An alternative environment-based approach to understanding patterns of invasions assumes that native and exotic species respond similarly to environmental conditions, and thus predicts that they should have similar patterns of abundance and diversity. Establishment and growth of native and exotic species are predicted to vary in response to the interaction of plant growth rates with the frequency and intensity of mortality-causing disturbances. This theory distinguishes between the probability of establishment and the probability of dominance, predicting that establishment should be highest under unproductive and undisturbed conditions and also disturbed productive conditions. However, the probability of dominance by exotic species, and thus of potential negative impacts on diversity, is highest under productive conditions. The theory predicts that a change in disturbance regime can have opposite effects in environments with contrasting levels of productivity. Manipulation of productivity and disturbance provides opportunities for resource managers to influence the interactions among species, offering the potential to reduce or eliminate some types of invasive species. [source] Scales of association: hierarchical linear models and the measurement of ecological systemsECOLOGY LETTERS, Issue 6 2007Sean M. McMahon Abstract A fundamental challenge to understanding patterns in ecological systems lies in employing methods that can analyse, test and draw inference from measured associations between variables across scales. Hierarchical linear models (HLM) use advanced estimation algorithms to measure regression relationships and variance,covariance parameters in hierarchically structured data. Although hierarchical models have occasionally been used in the analysis of ecological data, their full potential to describe scales of association, diagnose variance explained, and to partition uncertainty has not been employed. In this paper we argue that the use of the HLM framework can enable significantly improved inference about ecological processes across levels of organization. After briefly describing the principals behind HLM, we give two examples that demonstrate a protocol for building hierarchical models and answering questions about the relationships between variables at multiple scales. The first example employs maximum likelihood methods to construct a two-level linear model predicting herbivore damage to a perennial plant at the individual- and patch-scale; the second example uses Bayesian estimation techniques to develop a three-level logistic model of plant flowering probability across individual plants, microsites and populations. HLM model development and diagnostics illustrate the importance of incorporating scale when modelling associations in ecological systems and offer a sophisticated yet accessible method for studies of populations, communities and ecosystems. We suggest that a greater coupling of hierarchical study designs and hierarchical analysis will yield significant insights on how ecological processes operate across scales. [source] | ||||||||||