229 research outputs found
The assessment of the relationship between information technology (IT) and airport performance
The evolution of the airport business is demonstrated by airports that are adopting
new business strategies and commercial models, which allow them to be, for
example, service providers instead of real-estate managers, with the focus on
cost reduction and increasing non-aeronautical (commercial) revenues.
Information technology (IT) can be used by airports to achieve their business
goals, such as enhancing performance by delivering cost reductions and
generating additional revenue streams.
Airports operate in an increasingly competitive and dynamic market, with the aim
of attracting a larger share of hub traffic from neighbouring airports. Therefore,
financial and operational performance will be key elements for airlines when
choosing a new airport destination.
The research shows that airports are more focused on passenger satisfaction,
resulting in airport performance indicators that have the passenger at its
operational core and performance targets (e.g. Airport Service Quality passenger
satisfaction survey). IT plays an important role in increasing airport performance
through the automation of processes such as the deployment of common-use
check-in desks and self-service check-in kiosks. Studies of other industries have
shown evidence that IT impacts firm performance, but there have been few
studies related to the airport industry.
Thus, the aim of this research is to assess the relationship between IT and airport
performance, and it proposes a conceptual framework to assess the relationship
between IT and airport performance by drawing from studies in other industries.
Two methodologies were used in this research, the first one was the case study,
and the second one was the online survey. The case studies consisted of 16 faceto-
face interviews with senior staff representing two airports in Asia, one airport
in Australia, and one airport in Europe. The case studies result show that there is
a relationship between IT and airport performance ... [cont.]
Considering external information to improve the phylogenetic comparison of microbial communities: A new approach based on constrained Double Principal Coordinates Analysis (cDPCoA)
© 2014 John Wiley & Sons Ltd. The use of next-generation sequencing technologies is revolutionizing microbial ecology by allowing a deep phylogenetic coverage of tens to thousands of samples simultaneously. Double Principal Coordinates Analysis (DPCoA) is a multivariate method, developed in community ecology, able to integrate a distance matrix describing differences among species (e.g. phylogenetic distances) in the analysis of a species abundance matrix. This ordination technique has been used recently to describe microbial communities taking into account phylogenetic relatedness. In this work, we extend DPCoA to integrate the information of external variables measured on communities. The constrained Double Principal Coordinates Analysis (cDPCoA) is able to enforce a priori classifications to retrieve subtle differences and (or) remove the effect of confounding factors. We describe the main principles of this new approach and demonstrate its usefulness by providing application examples based on published 16S rRNA gene data sets.Peer Reviewe
The ternary diagram of functional diversity
Among the many diversity indices in the ecologist toolbox, measures that can be partitioned into additive terms are particularly useful as the different components can be related to different ecological processes shaping community structure. In this paper, an additive diversity decomposition is proposed to partition the diversity structure of a given community into three complementary fractions: functional diversity, functional redundancy and species dominance. These three components sum up to one. Therefore, they can be used to portray the community structure in a ternary diagram. Since the identification of community-level patterns is an essential step to investigate the main drivers of species coexistence, the ternary diagram of functional diversity can be used to relate different facets of diversity to community assembly processes more exhaustively than looking only at one index at a time. The value of the proposed diversity decomposition is demonstrated by the analysis of actual abundance data on plant assemblages sampled in grazed and ungrazed grasslands in Tuscany (Central Italy)
Quantifying the extent of plant functional specialization using Grime's CSR strategies
Specialization refers to a species adaptation to a restricted range of environmental conditions. While generalist species are able to exploit a wide variety of resources in a broad range of habitats, specialist species tend to have narrower niche breadths. From an evolutionary perspective, specialization is the result of a functional syndrome in which a suite of traits covary to allow the effective exploitation of specific resources. Accordingly, the measurement of specialization should be based on a multi-trait approach. In plant ecology, a well-known classification of the adaptive strategies of plants is Grime's competitor, stress tolerator, ruderal (CSR) theory in which the three principal strategies represent relatively easily measurable trait combinations from the global spectrum of plant form and function arising under conditions of competition, abiotic restriction to growth or periodic disturbance, respectively. In this paper, we thus introduce a method to summarize the functional specialization of plant species and communities by applying inequality measures to Grime's CSR strategies. The general idea is that a plant species that can be exclusively assigned to one CSR strategy can be considered a specialist (as it adopts only one adaptive strategy to access resources), while species that share functional characteristics of multiple CSR strategies can be considered more generalist. The behavior of the proposed measures is shown with one case study on the functional changes of six Alpine vegetation types ordered along a gradient, from pioneer to more stable communities
Accurate Profiling of Microbial Communities from Massively Parallel Sequencing using Convex Optimization
We describe the Microbial Community Reconstruction ({\bf MCR}) Problem, which
is fundamental for microbiome analysis. In this problem, the goal is to
reconstruct the identity and frequency of species comprising a microbial
community, using short sequence reads from Massively Parallel Sequencing (MPS)
data obtained for specified genomic regions. We formulate the problem
mathematically as a convex optimization problem and provide sufficient
conditions for identifiability, namely the ability to reconstruct species
identity and frequency correctly when the data size (number of reads) grows to
infinity. We discuss different metrics for assessing the quality of the
reconstructed solution, including a novel phylogenetically-aware metric based
on the Mahalanobis distance, and give upper-bounds on the reconstruction error
for a finite number of reads under different metrics. We propose a scalable
divide-and-conquer algorithm for the problem using convex optimization, which
enables us to handle large problems (with species). We show using
numerical simulations that for realistic scenarios, where the microbial
communities are sparse, our algorithm gives solutions with high accuracy, both
in terms of obtaining accurate frequency, and in terms of species phylogenetic
resolution.Comment: To appear in SPIRE 1
Positive definite metric spaces
Magnitude is a numerical invariant of finite metric spaces, recently
introduced by T. Leinster, which is analogous in precise senses to the
cardinality of finite sets or the Euler characteristic of topological spaces.
It has been extended to infinite metric spaces in several a priori distinct
ways. This paper develops the theory of a class of metric spaces, positive
definite metric spaces, for which magnitude is more tractable than in general.
Positive definiteness is a generalization of the classical property of negative
type for a metric space, which is known to hold for many interesting classes of
spaces. It is proved that all the proposed definitions of magnitude coincide
for compact positive definite metric spaces and further results are proved
about the behavior of magnitude as a function of such spaces. Finally, some
facts about the magnitude of compact subsets of l_p^n for p \le 2 are proved,
generalizing results of Leinster for p=1,2, using properties of these spaces
which are somewhat stronger than positive definiteness.Comment: v5: Corrected some misstatements in the last few paragraphs. Updated
reference
Variation within and between Closely Related Species Uncovers High Intra-Specific Variability in Dispersal
Mounting evidence shows that contrasting selection pressures generate variability in dispersal patterns among individuals or populations of the same species, with potential impacts on both species dynamics and evolution. However, this variability is hardly considered in empirical works, where a single dispersal function is considered to adequately reflect the species-specific dispersal ability, suggesting thereby that within-species variation is negligible as regard to inter-specific differences in dispersal abilities. We propose here an original method to make the comparison of intra- and inter-specific variability in dispersal, by decomposing the diversity of that trait along a phylogeny of closely related species. We used as test group European butterflies that are classic study organisms in spatial ecology. We apply the analysis separately to eight metrics that reflect the dispersal propensity, the dispersal ability or the dispersal efficiency of populations and species. At the inter-specific level, only the dispersal ability showed the signature of a phylogenetic signal while neither the dispersal propensity nor the dispersal efficiency did. At the within-species level, the partitioning of dispersal diversity showed that dispersal was variable or highly variable among populations: intra-specific variability represented from 11% to 133% of inter-specific variability in dispersal metrics. This finding shows that dispersal variation is far from negligible in the wild. Understanding the processes behind this high within-species variation should allow us to properly account for dispersal in demographic models. Accordingly, to encompass the within species variability in life histories the use of more than one value per trait per species should be encouraged in the construction of databases aiming at being sources for modelling purposes
Functional differentiation between fish assemblages from forested and deforested streams
Author correction : a global database for metacommunity ecology, integrating species, traits, environment and space
Correction to: Scientific Data https://doi.org/10.1038/s41597-019-0344-7, published online 08 January 202
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