16 resultados para Landscape

em University of Queensland eSpace - Australia


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Sustainable forest restoration and management practices require a thorough understanding of the influence that habitat fragmentation has on the processes shaping genetic variation and its distribution in tree populations. We quantified genetic variation at isozyme markers and chloroplast DNA (cpDNA), analysed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) in severely fragmented populations of Sorbus aucuparia (Rosaceae) in a single catchment (Moffat) in southern Scotland. Remnants maintain surprisingly high levels of gene diversity (H-E) for isozymes (H-E = 0.195) and cpDNA markers (H-E = 0.490). Estimates are very similar to those from non-fragmented populations in continental Europe, even though the latter were sampled over a much larger spatial scale. Overall, no genetic bottleneck or departures from random mating were detected in the Moffat fragments. However, genetic differentiation among remnants was detected for both types of marker (isozymes Theta(n) = 0.043, cpDNA Theta(c) = 0.131; G-test, P-value < 0.001). In this self-incompatible, insect-pollinated, bird-dispersed tree species, the estimated ratio of pollen flow to seed flow between fragments is close to 1 (r = 1.36). Reduced pollen-mediated gene flow is a likely consequence of habitat fragmentation, but effective seed dispersal by birds is probably helping to maintain high levels of genetic diversity within remnants and reduce genetic differentiation between them.

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The late Early to early Middle Eocene Okanagan Highlands fossil sites, spanning -1000 km north-south (northeastern Washington State, southern British Columbia) provide an opportunity to reconstruct biotic communities across a broad upland landscape during the warmest part of the Cenozoic. Plant taxa from these fossil sites are characteristic of the modern eastern North American deciduous forest zone, principally the mixed mesophytic forest, but also include extinct taxa, taxa known only from eastern Asian mesothermal forests, and a small number of taxa restricted to the present-day North American west coast coniferous biome. In this preliminary report, paleoclimates and forest types are reconstructed using collections from Republic in Washington State, USA., and Princeton, Quilchena, Falkland, McAbee, Hat Creek, Horsefly, and Driftwood Canyon in British Columbia, Canada. Both leaf margin analysis (LMA) and quantitative bioclimatic analysis of identified nearest living relatives of megaflora indicated upper microthermal to lower mesothermal moist environments (MAT -10-15 degrees C, CMMT > 0 degrees C, MAP > 100 cm/year). Some taxa common to most sites suggest cool conditions (e.g., Abies, other Pinaceae; Alnus, other Betulaceae). However, all floras contain a substantive broadleaf deciduous element (e.g., Fagaceae, Juglandaceae) and conifers (e.g., Metasequoia) with the bioclimatic analysis yielding slightly higher MAT than LMA. Thermophilic (principally mesothermal) taxa include various insects, the aquatic fern Azolla, palms, the banana relative Ensete, taxodiaceous conifers, Eucommia and Gordonia, taxa which may have occurred near their climatic limits. The mixture of thermophilic and temperate insect and plant taxa indicates low-temperature seasonality (i.e., highly equable climate).

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The research literature on metalieuristic and evolutionary computation has proposed a large number of algorithms for the solution of challenging real-world optimization problems. It is often not possible to study theoretically the performance of these algorithms unless significant assumptions are made on either the algorithm itself or the problems to which it is applied, or both. As a consequence, metalieuristics are typically evaluated empirically using a set of test problems. Unfortunately, relatively little attention has been given to the development of methodologies and tools for the large-scale empirical evaluation and/or comparison of metaheuristics. In this paper, we propose a landscape (test-problem) generator that can be used to generate optimization problem instances for continuous, bound-constrained optimization problems. The landscape generator is parameterized by a small number of parameters, and the values of these parameters have a direct and intuitive interpretation in terms of the geometric features of the landscapes that they produce. An experimental space is defined over algorithms and problems, via a tuple of parameters for any specified algorithm and problem class (here determined by the landscape generator). An experiment is then clearly specified as a point in this space, in a way that is analogous to other areas of experimental algorithmics, and more generally in experimental design. Experimental results are presented, demonstrating the use of the landscape generator. In particular, we analyze some simple, continuous estimation of distribution algorithms, and gain new insights into the behavior of these algorithms using the landscape generator.

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Movements of wide-ranging top predators can now be studied effectively using satellite and archival telemetry. However, the motivations underlying movements remain difficult to determine because trajectories are seldom related to key biological gradients, such as changing prey distributions. Here, we use a dynamic prey landscape of zooplankton biomass in the north-east Atlantic Ocean to examine active habitat selection in the plankton-feeding basking shark Cetorhinus maximus. The relative success of shark searches across this landscape was examined by comparing prey biomass encountered by sharks with encounters by random-walk simulations of ‘model’ sharks. Movements of transmitter-tagged sharks monitored for 964 days (16754km estimated minimum distance) were concentrated on the European continental shelf in areas characterized by high seasonal productivity and complex prey distributions. We show movements by adult and sub-adult sharks yielded consistently higher prey encounter rates than 90% of random-walk simulations. Behavioural patterns were consistent with basking sharks using search tactics structured across multiple scales to exploit the richest prey areas available in preferred habitats. Simple behavioural rules based on learned responses to previously encountered prey distributions may explain the high performances. This study highlights how dynamic prey landscapes enable active habitat selection in large predators to be investigated from a trophic perspective, an approach that may inform conservation by identifying critical habitat of vulnerable species.

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Landscape change occurs through the interaction of a multitude of natural and human driving forces at a range of organisational levels, with humans playing an increasingly dominant role in many regions of the world. Building on the current knowledge of the underlying drivers of landscape change, a conceptual framework of regional landscape change was developed which integrated population, economic and cultural values, policy and science/technology. Using the Southern Brigalow Belt biogeographic region of Queensland as a case study, the role of natural and human drivers in landscape change was investigated in four phases of settlement since 1840. The Brigalow Belt has experienced comparable rates of vegetation clearance over the past 50 years to areas of tropical deforestation. Economic factors were important during all phases of development, but the five regional drivers often acted in synergy. Environmental constraints played a significant role in slowing rates of change. Temporal trends of deforestation followed a sigmoidal curve, with initial slow change accelerating though the middle phases then slowing in recent times. Future landscape management needs to take account of the influence of all the components of the conceptual framework, at a range of organisational levels, if more ecologically sustainable outcomes are to be achieved. (c) 2006 Elsevier B.V. All rights reserved.