18,366 research outputs found
Simulating acculturation dynamics between migrants and locals in relation to network formation
International migration implies the coexistence of different ethnic and
cultural groups in the receiving country. The refugee crisis of 2015 has
resulted in critical levels of opinion polarization on the question of whether
to welcome migrants, causing clashes in receiving countries. This scenario
emphasizes the need to better understand the dynamics of mutual adaptation
between locals and migrants, and the conditions that favor successful
integration. Agent-based simulations can help achieve this goal. In this work,
we introduce our model MigrAgent and our preliminary results. The model
synthesizes the dynamics of migration intake and post-migration adaptation. It
explores the different acculturation outcomes that can emerge from the mutual
adaptation of a migrant population and a local population depending on their
degree of tolerance. With parameter sweeping, we detect how different
acculturation strategies can coexist in a society and in different degrees
among various subgroups. The results show higher polarization effects between a
local population and a migrant population for fast intake conditions. When
migrant intake is slow, transitory conditions between acculturation outcomes
emerge for subgroups, e.g., from assimilation to integration for liberal
migrants and from marginalization to separation for conservative migrants.
Relative group sizes due to speed of intake cause counterintuitive scenarios,
such as the separation of liberal locals. We qualitatively compare the
processes of our model with the German portion sample of the survey Causes and
Consequences of Socio-Cultural Integration Processes among New Immigrants in
Europe (SCIP), finding preliminary confirmation of our assumptions and results.Comment: 24 pages, plus supplemental material, 11 figure
An acoustic view of ocean mixing
Knowledge of the parameter K (turbulent diffusivity/"mixing intensity") is a key to understand transport processes of matter and energy in the ocean. Especially the almost vertical component of K across the ocean stratification
(diapycnal diffusivity) is vital for research on biogeochemical cycles or greenhouse gas budgets.
Recent boost in precision of water velocity data that can be obtained from vessel-mounted acoustic instruments (vmADCP) allows identifying ocean regions of elevated diapycnal diffusivity during research cruises - in high horizontal resolution and without extra ship time needed.
This contribution relates acoustic data from two cruises
in the Tropical North East Atlantic Oxygen Minimum Zone
to simultaneous field observations of diapycnal diffusivity:
pointwise measurements by a microstructure profiler
as well as one integrative value from a large scale Tracer Release Experiment
Evolution of Threats in the Global Risk Network
With a steadily growing population and rapid advancements in technology, the
global economy is increasing in size and complexity. This growth exacerbates
global vulnerabilities and may lead to unforeseen consequences such as global
pandemics fueled by air travel, cyberspace attacks, and cascading failures
caused by the weakest link in a supply chain. Hence, a quantitative
understanding of the mechanisms driving global network vulnerabilities is
urgently needed. Developing methods for efficiently monitoring evolution of the
global economy is essential to such understanding. Each year the World Economic
Forum publishes an authoritative report on the state of the global economy and
identifies risks that are likely to be active, impactful or contagious. Using a
Cascading Alternating Renewal Process approach to model the dynamics of the
global risk network, we are able to answer critical questions regarding the
evolution of this network. To fully trace the evolution of the network we
analyze the asymptotic state of risks (risk levels which would be reached in
the long term if the risks were left unabated) given a snapshot in time, this
elucidates the various challenges faced by the world community at each point in
time. We also investigate the influence exerted by each risk on others. Results
presented here are obtained through either quantitative analysis or
computational simulations.Comment: 27 pages, 15 figure
From Social Simulation to Integrative System Design
As the recent financial crisis showed, today there is a strong need to gain
"ecological perspective" of all relevant interactions in
socio-economic-techno-environmental systems. For this, we suggested to set-up a
network of Centers for integrative systems design, which shall be able to run
all potentially relevant scenarios, identify causality chains, explore feedback
and cascading effects for a number of model variants, and determine the
reliability of their implications (given the validity of the underlying
models). They will be able to detect possible negative side effect of policy
decisions, before they occur. The Centers belonging to this network of
Integrative Systems Design Centers would be focused on a particular field, but
they would be part of an attempt to eventually cover all relevant areas of
society and economy and integrate them within a "Living Earth Simulator". The
results of all research activities of such Centers would be turned into
informative input for political Decision Arenas. For example, Crisis
Observatories (for financial instabilities, shortages of resources,
environmental change, conflict, spreading of diseases, etc.) would be connected
with such Decision Arenas for the purpose of visualization, in order to make
complex interdependencies understandable to scientists, decision-makers, and
the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c
Robust identification of local adaptation from allele frequencies
Comparing allele frequencies among populations that differ in environment has
long been a tool for detecting loci involved in local adaptation. However, such
analyses are complicated by an imperfect knowledge of population allele
frequencies and neutral correlations of allele frequencies among populations
due to shared population history and gene flow. Here we develop a set of
methods to robustly test for unusual allele frequency patterns, and
correlations between environmental variables and allele frequencies while
accounting for these complications based on a Bayesian model previously
implemented in the software Bayenv. Using this model, we calculate a set of
`standardized allele frequencies' that allows investigators to apply tests of
their choice to multiple populations, while accounting for sampling and
covariance due to population history. We illustrate this first by showing that
these standardized frequencies can be used to calculate powerful tests to
detect non-parametric correlations with environmental variables, which are also
less prone to spurious results due to outlier populations. We then demonstrate
how these standardized allele frequencies can be used to construct a test to
detect SNPs that deviate strongly from neutral population structure. This test
is conceptually related to FST but should be more powerful as we account for
population history. We also extend the model to next-generation sequencing of
population pools, which is a cost-efficient way to estimate population allele
frequencies, but it implies an additional level of sampling noise. The utility
of these methods is demonstrated in simulations and by re-analyzing human SNP
data from the HGDP populations. An implementation of our method will be
available from http://gcbias.org.Comment: 27 pages, 7 figure
Mechanisms and Models of Agropastoral Spread During the Neolithic in the West Mediterranean: The Cardial Spread Model
abstract: This dissertation examines the various factors and processes that have been proposed as explanations for the spread of agriculture in the west Mediterranean. The expansion of the Neolithic in the west Mediterranean (the Impresso-Cardial Neolithic) is characterized by a rapid spread of agricultural subsistence and material culture from the southern portion of the Italian peninsula to the western coast of the Iberian peninsula. To address this unique case, four conceptual models of Neolithic spread have been proposed: the Wave of Advance, the Capillary Spread Model, the Maritime Pioneer Colonization Model and the Dual Model. An agent-based model, the Cardial Spread Model, was built to simulate each conceptual spread model in a spatially explicit environment for comparison with evidence from the archaeological record. Chronological information detailing the arrival of the Neolithic was used to create a map of the initial arrival of the Neolithic (a chronosurface) throughout the study area. The results of each conceptual spread model were then compared to the chronosurface in order to evaluate the relative performance of each conceptual model of spread. These experiments suggest that both the Dual and Maritime Pioneer Colonization models best fit the available chronological and spatial distribution of the Impresso-Cardial Neolithic.
For the purpose of informing agent movement and improving the fit of the conceptual spread models, a variety of paleoenvironmental maps were tested within the Cardial Spread Model. The outcome of these experiments suggests that topographic slope was an important factor in settlement location and that rivers were important vectors of transportation for early Neolithic migration. This research demonstrates the application of techniques rare to archaeological analysis, agent-based modeling and the inclusion of paleoenvironmental information, and provides a valuable tool that future researchers can utilize to further evaluate and fabricate new models of Neolithic expansion.Dissertation/ThesisDoctoral Dissertation Anthropology 201
The speed of range shifts in fragmented landscapes
Peer reviewedPublisher PD
- …