Abstract: In 1998, tropical sea surface temperatures were the highest on record, topping off a 50-year trend for some tropical oceans. In the same year, coral reefs around the world suffered the most extensive and severe bleaching ( loss of symbiotic algae) and subsequent mortality on record. These events may not be attributable to local stressors or natural variability alone but were likely induced by an underlying global phenomenon. It is probable that anthropogenic global warming has contributed to the extensive coral bleaching that has occurred simultaneously throughout the reef regions of the world. The geographic extent, increasing frequency, and regional severity of mass bleaching events are an apparent result of a steadily rising baseline of marine temperatures, combined with regionally specific El Niño and La Niña events. The repercussions of the 1998 mass bleaching and mortality events will be far-reaching. Human populations dependent on reef services face losses of marine biodiversity, fisheries, and shoreline protection. Coral bleaching events may become more frequent and severe as the climate continues to warm, exposing coral reefs to an increasingly hostile environment. This global threat to corals compounds the effects of more localized anthropogenic factors that already place reefs at risk. Significant attention needs to be given to the monitoring of coral reef ecosystems, research on the projected and realized effects of global climate change, and measures to curtail greenhouse gas emissions. Even those reefs with well-enforced legal protection as marine sanctuaries, or those managed for sustainable use, are threatened by global climate change. 相似文献
Abstract: Despite growing concern, no consensus has emerged over the effects of habitat modification on species diversity in tropical forests. Even for comparatively well-studied taxa such as Lepidoptera, disturbance has been reported to increase and decrease diversity with approximately equal frequency. Species diversity within landscapes depends on the spatial scale at which communities are sampled, and the effects of disturbance in tropical forests have been studied at a wide range of spatial scales. Yet the question of how disturbance affects diversity at different spatial scales has not been addressed. We reanalyzed data from previous studies to examine the relationship between spatial scale and effects of disturbance on tropical-forest Lepidoptera. Disturbance had opposite effects on diversity at large and small scales: as scale decreased, the probability of a positive effect of disturbance on diversity increased. We also explicitly examined the relationship between spatial scale and the diversity of butterflies in selectively logged and unlogged forest in Maluku Province, Indonesia. Species richness increased with spatial scale in both logged and unlogged forest, but at a significantly faster rate in unlogged forest, whereas species evenness increased with scale in unlogged forest but did not increase with scale in logged forest. These data indicate that the effects of habitat modification on species diversity are heavily scale-dependent. As a result, recorded effects of disturbance were strongly influenced by the spatial scale at which species assemblages were sampled. Future studies need to account for this by explicitly examining the effects of disturbance at a number of different spatial scales. A further problem arises because the relationship between scale and diversity is likely to differ among taxa in relation to mobility. This may explain to some extent why the measured effects of disturbance have differed between relatively mobile and immobile taxa. 相似文献
Abstract: Genebank collection databases can be used for ecogeographical studies under the assumption that the accessions are a geographically unbiased sample. We evaluated the representativeness of a collection of wild potatoes from Bolivia and defined and assessed four types of bias: species, species-area, hotspot, and infrastructure. Species bias is the sampling of some species more often than others. Species-area bias is a sampling that is disproportionate to the total area in which a species is found. Hotspot bias is the disproportionate sampling of areas with high levels of diversity. Infrastructure bias is the disproportionate sampling of areas near roads and towns. Each of these biases is present in the Bolivian wild potato collection. The infrastructure bias was strong: 60% of all wild potato accessions were collected within 2 km of a road, as opposed to 22%, if collections had been made randomly. This analysis can serve as a guide for future collecting trips. It can also provide baseline information for the application of genebank data in studies based on geographic information systems. 相似文献
The use of quantitative data for constructing prognostic maps of the dynamics of ecosystem degradation and restoration by
nonlinear simulation methods is a topical field of landscape ecology. This method of dynamic cartography is based on fiberwise
comparison of data on the state of Chernye Zemli (the Kalmyk Republic, Russia) in different years and the detailed analysis
of the period on which the prognosis was based. For this purpose, materials of repeated aerial and satellite photography obtained
during a long period (1954–1993) were used. Comparison of maps characterizing the dynamics of Chernye Zemli between 1958 and
1993 allows prognostic electronic maps for the next 10–15 years (with a five-year interval) to be drawn and land prognosis
for the next 20–30 years (1998–2023) to be obtained.
Deceased 相似文献
The horizontal distribution and quantitative characteristics of macrozoobenthos were studied in small lakes of the Darwin Nature Reserve (southern Vologda oblast). The aggregation index varied in the open areas of acid lakes, which indicated that communities of small acid water bodies were unstable. The aggregation was the lowest in the open area of a neutral lake. In acid lakes, the number and biomass of macroinvertebrates were the highest near the coasts. In the neutral lake, conversely, these values were maximum in open areas and low near the coast due to a strong pressure of predatory invertebrates and fish. An aggregating effect of invertebrate predators was observed near the coasts of lakes of different types. 相似文献
Three-dimensional (3D) models are often utilised to assess the presence of sand and gravel deposits. Expanding these models to provide a better indication of the suitability of the deposit as aggregate for use in construction would be advantageous. This, however, leads to statistical challenges. To be effective, models must be able to reflect the interdependencies between different criteria (e.g. depth to deposit, thickness of deposit, ratio of mineral to waste, proportion of ‘fines’) as well as the inherent uncertainty introduced because models are derived from a limited set of boreholes in a study region. Using legacy borehole data collected during a systematic survey of sand and gravel deposits in the UK, we have developed a 3D model for a 2400 km2 region close to Reading, southern England. In developing the model, we have reassessed the borehole grading data to reflect modern extraction criteria and explored the most suitable statistical modelling technique. The additive log-ratio transform and the linear model of coregionalization have been applied, techniques that have been previously used to map soil texture classes in two dimensions, to assess the quality of sand and gravel deposits in the area. The application of these statistical techniques leads to a model which can be used to generate thousands of plausible realisations of the deposit which fully reflect the extent of model uncertainty. The approach offers potential to improve regional-scale mineral planning by providing an enhanced understanding of sand and gravel deposits and the extent to which they meet current extraction criteria.
Building a community that is resilient to disasters has become one of the main goals of disaster management. Communities that are more disaster resilient often experience less impact from the disaster and reduced recovery periods afterwards. This study develops a methodology for constructing a set of indicators measuring Community Disaster Resilience Index (CDRI) in terms of human, social, economic, environmental, and institutional factors. In this study, the degree of community resilience to natural disasters was measured for 229 local municipalities in Korea, followed by an examination of the relationship between the aggregated CDRI and disaster losses, using an ordinary least squares (OLS) regression method and a geographically weighted regression (GWR) method. Identifying the extent of community resilience to natural disasters would provide emergency managers and decision-makers with strategic directions for improving local communities' resilience to natural disasters while reducing the negative impacts of disasters. 相似文献