516 research outputs found
Inside Money, Procyclical Leverage, and Banking Catastrophes
We explore a model of the interaction between banks and outside investors in
which the ability of banks to issue inside money (short-term liabilities
believed to be convertible into currency at par) can generate a collapse in
asset prices and widespread bank insolvency. The banks and investors share a
common belief about the future value of certain long-term assets, but they have
different objective functions; changes to this common belief result in
portfolio adjustments and trade. Positive belief shocks induce banks to buy
risky assets from investors, and the banks finance those purchases by issuing
new short-term liabilities. Negative belief shocks induce banks to sell assets
in order to reduce their chance of insolvency to a tolerably low level, and
they supply more assets at lower prices, which can result in multiple
market-clearing prices. A sufficiently severe negative shock causes the set of
equilibrium prices to contract (in a manner given by a cusp catastrophe),
causing prices to plummet discontinuously and banks to become insolvent.
Successive positive and negative shocks of equal magnitude do not cancel;
rather, a banking catastrophe can occur even if beliefs simply return to their
initial state. Capital requirements can prevent crises by curtailing the
expansion of balance sheets when beliefs become more optimistic, but they can
also force larger price declines. Emergency asset price supports can be
understood as attempts by a central bank to coordinate expectations on an
equilibrium with solvency.Comment: 31 pages, 10 figure
Epidemics in partially overlapped multiplex networks
Many real networks exhibit a layered structure in which links in each layer
reflect the function of nodes on different environments. These multiple types
of links are usually represented by a multiplex network in which each layer has
a different topology. In real-world networks, however, not all nodes are
present on every layer. To generate a more realistic scenario, we use a
generalized multiplex network and assume that only a fraction of the nodes
are shared by the layers. We develop a theoretical framework for a branching
process to describe the spread of an epidemic on these partially overlapped
multiplex networks. This allows us to obtain the fraction of infected
individuals as a function of the effective probability that the disease will be
transmitted . We also theoretically determine the dependence of the epidemic
threshold on the fraction of shared nodes in a system composed of two
layers. We find that in the limit of the threshold is dominated by
the layer with the smaller isolated threshold. Although a system of two
completely isolated networks is nearly indistinguishable from a system of two
networks that share just a few nodes, we find that the presence of these few
shared nodes causes the epidemic threshold of the isolated network with the
lower propagating capacity to change discontinuously and to acquire the
threshold of the other network.Comment: 13 pages, 4 figure
Madagascar's grasses and grasslands:anthropogenic or natural?
Grasses, by their high productivity even under very low pCO2, their ability to survive repeated burning and to tolerate long dry seasons, have transformed the terrestrial biomes in the Neogene and Quaternary. The expansion of grasslands at the cost of biodiverse forest biomes in Madagascar is often postulated as a consequence of the Holocene settlement of the island by humans. However, we show that the Malagasy grass flora has many indications of being ancient with a long local evolutionary history, much predating the Holocene arrival of humans. First, the level of endemism in the Madagascar grass flora is well above the global average for large islands. Second, a survey of many of the more diverse areas indicates that there is a very high spatial and ecological turnover in the grass flora, indicating a high degree of niche specialization. We also find some evidence that there are both recently disturbed and natural stable grasslands: phylogenetic community assembly indicates that recently severely disturbed grasslands are phylogenetically clustered, whereas more undisturbed grasslands tend to be phylogenetically more evenly distributed. From this evidence, it is likely that grass communities existed in Madagascar long before human arrival and so were determined by climate, natural grazing and other natural factors. Humans introduced zebu cattle farming and increased fire frequency, and may have triggered an expansion of the grasslands. Grasses probably played the same role in the modification of the Malagasy environments as elsewhere in the tropics
The extreme vulnerability of interdependent spatially embedded networks
Recent studies show that in interdependent networks a very small failure in
one network may lead to catastrophic consequences. Above a critical fraction of
interdependent nodes, even a single node failure can invoke cascading failures
that may abruptly fragment the system, while below this "critical dependency"
(CD) a failure of few nodes leads only to small damage to the system. So far,
the research has been focused on interdependent random networks without space
limitations. However, many real systems, such as power grids and the Internet,
are not random but are spatially embedded. Here we analytically and numerically
analyze the stability of systems consisting of interdependent spatially
embedded networks modeled as lattice networks. Surprisingly, we find that in
lattice systems, in contrast to non-embedded systems, there is no CD and
\textit{any} small fraction of interdependent nodes leads to an abrupt
collapse. We show that this extreme vulnerability of very weakly coupled
lattices is a consequence of the critical exponent describing the percolation
transition of a single lattice. Our results are important for understanding the
vulnerabilities and for designing robust interdependent spatial embedded
networks.Comment: 13 pages, 5 figure
Towards designing robust coupled networks
Natural and technological interdependent systems have been shown to be highly
vulnerable due to cascading failures and an abrupt collapse of global
connectivity under initial failure. Mitigating the risk by partial
disconnection endangers their functionality. Here we propose a systematic
strategy of selecting a minimum number of autonomous nodes that guarantee a
smooth transition in robustness. Our method which is based on betweenness is
tested on various examples including the famous 2003 electrical blackout of
Italy. We show that, with this strategy, the necessary number of autonomous
nodes can be reduced by a factor of five compared to a random choice. We also
find that the transition to abrupt collapse follows tricritical scaling
characterized by a set of exponents which is independent on the protection
strategy
Avoiding catastrophic failure in correlated networks of networks
Networks in nature do not act in isolation but instead exchange information,
and depend on each other to function properly. An incipient theory of Networks
of Networks have shown that connected random networks may very easily result in
abrupt failures. This theoretical finding bares an intrinsic paradox: If
natural systems organize in interconnected networks, how can they be so stable?
Here we provide a solution to this conundrum, showing that the stability of a
system of networks relies on the relation between the internal structure of a
network and its pattern of connections to other networks. Specifically, we
demonstrate that if network inter-connections are provided by hubs of the
network and if there is a moderate degree of convergence of inter-network
connection the systems of network are stable and robust to failure. We test
this theoretical prediction in two independent experiments of functional brain
networks (in task- and resting states) which show that brain networks are
connected with a topology that maximizes stability according to the theory.Comment: 40 pages, 7 figure
Global biodiversity monitoring: From data sources to Essential Biodiversity Variables
Essential Biodiversity Variables (EBVs) consolidate information from varied biodiversity observation sources. Here we demonstrate the links between data sources, EBVs and indicators and discuss how different sources of biodiversity observations can be harnessed to inform EBVs. We classify sources of primary observations into four types: extensive and intensive monitoring schemes, ecological field studies and satellite remote sensing. We characterize their geographic, taxonomic and temporal coverage. Ecological field studies and intensive monitoring schemes inform a wide range of EBVs, but the former tend to deliver short-term data, while the geographic coverage of the latter is limited. In contrast, extensive monitoring schemes mostly inform the population abundance EBV, but deliver long-term data across an extensive network of sites. Satellite remote sensing is particularly suited to providing information on ecosystem function and structure EBVs. Biases behind data sources may affect the representativeness of global biodiversity datasets. To improve them, researchers must assess data sources and then develop strategies to compensate for identified gaps. We draw on the population abundance dataset informing the Living Planet Index (LPI) to illustrate the effects of data sources on EBV representativeness. We find that long-term monitoring schemes informing the LPI are still scarce outside of Europe and North America and that ecological field studies play a key role in covering that gap. Achieving representative EBV datasets will depend both on the ability to integrate available data, through data harmonization and modeling efforts, and on the establishment of new monitoring programs to address critical data gaps
Long-distance dispersal explains the bipolar disjunction in Carex macloviana
PREMISE OF THE STUDY: The sedge Carex macloviana d’Urv presents a bipolar distribution. To clarify the origin of its distribution, we consider the four main hypotheses: long-distance dispersal (either by mountain hopping or by direct dispersal), vicariance, parallel evolution, and human introduction. METHODS: Phylogenetic, phylogeographic, and divergence time estimation analyses were carried out based on two nuclear ribosomal (ETS and ITS) regions, one nuclear single copy gene (CATP), and three plastid DNA regions (rps 16 and 5′ trn K introns, and psb A-trn H spacer), using Bayesian inference, maximum likelihood, and statistical parsimony. Bioclimatic data were used to characterize the climatic niche of C. macloviana. KEY RESULTS: C arex macloviana constitutes a paraphyletic species, dating back to the Pleistocene (0.62 Mya, 95% highest posterior density: 0.29–1.00 Mya). This species displays strong genetic structure between hemispheres, wiThtwo different lineages in the Southern Hemisphere and limited genetic differentiation in Northern Hemisphere populations. Also, populations from the Southern Hemisphere show a narrower climatic niche wiThregards to the Northern Hemisphere populations. CONCLUSIONS: C arex macloviana reached its bipolar distribution by long-distance dispersal, although it was not possible to determine whether it was caused by mountain hopping or by direct dispersal. While there is some support that Carex macloviana might have colonized the Northern Hemisphere by south-to-norThtranshemisphere dispersal during the Pleistocene, unlike the southwards dispersal pattern inferred for other bipolar Carex L. species, we cannot entirely rule out north-to-souThdispersion.Ministerio de EconomĂa y Competitividad CGL2016-77401-
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