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  • community assembly  (2)
  • 05. General::05.01. Computational geophysics::05.01.04. Statistical analysis  (1)
  • Wiley  (3)
  • 1
    Publication Date: 2024-01-23
    Description: Understanding how community assembly processes drive biodiversity patterns is a \ncentral goal of community ecology. While it is generally accepted that ecological communities are assembled by both stochastic and deterministic processes, quantifying \ntheir relative importance remains challenging. Few studies have investigated how the \nrelative importance of stochastic and deterministic community assembly processes vary \namong taxa and along gradients of habitat degradation. Using data on 1645 arthropod species across seven taxonomic groups in Malaysian Borneo, we quantified the \nimportance of ecological stochasticity and of a suite of community assembly processes \nacross a gradient of logging intensity. The relationship between logging and community assembly varied depending on the specific combination of taxa and stochasticity \nmetric used, but, in general, the processes that govern invertebrate community assembly were remarkably robust to changes in land use intensity.
    Keywords: community assembly ; determinism ; habitat degradation ; logging ; stochasticity
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
    Format: application/pdf
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  • 2
    Publication Date: 2024-03-31
    Description: Aim: Amazonia hosts more tree species from numerous evolutionary lineages, both young and ancient, than any other biogeographic region. Previous studies have shown that tree lineages colonized multiple edaphic environments and dispersed widely across Amazonia, leading to a hypothesis, which we test, that lineages should not be strongly associated with either geographic regions or edaphic forest types. Location: Amazonia. Taxon: Angiosperms (Magnoliids; Monocots; Eudicots). Methods: Data for the abundance of 5082 tree species in 1989 plots were combined with a mega-phylogeny. We applied evolutionary ordination to assess how phylogenetic composition varies across Amazonia. We used variation partitioning and Moran's eigenvector maps (MEM) to test and quantify the separate and joint contributions of spatial and environmental variables to explain the phylogenetic composition of plots. We tested the indicator value of lineages for geographic regions and edaphic forest types and mapped associations onto the phylogeny. Results: In the terra firme and várzea forest types, the phylogenetic composition varies by geographic region, but the igapó and white-sand forest types retain a unique evolutionary signature regardless of region. Overall, we find that soil chemistry, climate and topography explain 24% of the variation in phylogenetic composition, with 79% of that variation being spatially structured (R2= 19% overall for combined spatial/environmental effects). The phylogenetic composition also shows substantial spatial patterns not related to the environmental variables we quantified (R2= 28%). A greater number of lineages were significant indicators of geographic regions than forest types. Main Conclusion: Numerous tree lineages, including some ancient ones (〉66 Ma), show strong associations with geographic regions and edaphic forest types of Amazonia. This shows that specialization in specific edaphic environments has played a long-standing role in the evolutionary assembly of Amazonian forests. Furthermore, many lineages, even those that have dispersed across Amazonia, dominate within a specific region, likely because of phylogenetically conserved niches for environmental conditions that are prevalent within regions.
    Keywords: community assembly ; dispersal limitation ; environmental selection ; evolutionary principal ; component analysis ; indicator lineage analysis ; Moran's eigenvector maps ; neotropics ; Niche ; conservatism ; tropical rain forests
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
    Format: application/pdf
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  • 3
    Publication Date: 2017-04-04
    Description: During volcanic crises, volcanologists estimate the impact of possible imminent eruptions usually through deterministic modeling of the effects of one or a few preestablished scenarios. Despite such an approach may bring an important information to the decision makers, the sole use of deterministic scenarios does not allow scientists to properly take into consideration all uncertainties, and it cannot be used to assess quantitatively the risk because the latter unavoidably requires a probabilistic approach. We present a model based on the concept of Bayesian event tree (hereinafter named BET_VH_ST, standing for Bayesian event tree for short-term volcanic hazard), for short-term near-real-time probabilistic volcanic hazard analysis formulated for any potential hazardous phenomenon accompanying an eruption. The specific goal of BET_VH_ST is to produce a quantitative assessment of the probability of exceedance of any potential level of intensity for a given volcanic hazard due to eruptions within restricted time windows (hours to days) in any area surrounding the volcano, accounting for all natural and epistemic uncertainties. BET_VH_ST properly assesses the conditional probability at each level of the event tree accounting for any relevant information derived from the monitoring system, theoretical models, and the past history of the volcano, propagating any relevant epistemic uncertainty underlying these assessments. As an application example of the model, we apply BET_VH_ST to assess short-term volcanic hazard related to tephra loading during Major Emergency Simulation Exercise, a major exercise at Mount Vesuvius that took place from 19 to 23 October 2006, consisting in a blind simulation of Vesuvius reactivation, from the early warning phase up to the final eruption, including the evacuation of a sample of about 2000 people from the area at risk. The results show that BET_VH_ST is able to produce short-term forecasts of the impact of tephra fall during a rapidly evolving crisis, accurately accounting for and propagating all uncertainties and enabling rational decision making under uncertainty.
    Description: Published
    Description: 8805–8826
    Description: 3V. Dinamiche e scenari eruttivi
    Description: JCR Journal
    Description: embargoed_20161231
    Keywords: short-term probabilistic volcanic hazard analysis ; bayesian event tree ; 05. General::05.01. Computational geophysics::05.01.04. Statistical analysis
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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