5,852 research outputs found

    Climate Variability and Human Migration in the Netherlands, 1865-1937

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    Human migration is frequently cited as a potential social outcome of climate change and variability, and these effects are often assumed to be stronger in the past when economies were less developed and markets more localized. Yet, few studies have used historical data to test the relationship between climate and migration directly. In addition, the results of recent studies that link demographic and climate data are not consistent with conventional narratives of displacement responses. Using longitudinal individual-level demographic data from the Historical Sample of the Netherlands (HSN) and climate data that cover the same period, we examine the effects of climate variability on migration using event history models. Only internal moves in the later period and for certain social groups are associated with negative climate conditions, and the strength and direction of the observed effects change over time. International moves decrease with extreme rainfall, suggesting that the complex relationships between climate and migration that have been observed for contemporary populations extend into the nineteenth century

    Oil Extraction and Indigenous Livelihoods in the Northern Ecuadorian Amazon

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    Globally, the extraction of minerals and fossil fuels is increasingly penetrating into isolated regions inhabited by indigenous peoples, potentially undermining their livelihoods and well-being. To provide new insight to this issue, we draw on a unique longitudinal dataset collected in the Ecuadorian Amazon over an 11-year period from 484 indigenous households with varying degrees of exposure to oil extraction. Fixed and random effects regression models of the consequences of oil activities for livelihood outcomes reveal mixed and multidimensional effects. These results challenge common assumptions about these processes and are only partly consistent with hypotheses drawn from the Dutch disease literature

    Soil quality and human migration in Kenya and Uganda

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    Soil degradation is widely considered to be a key factor undermining agricultural livelihoods in the developing world and contributing to rural out-migration. To date, however, few quantitative studies have examined the effects of soil characteristics on human migration or other social outcomes for potentially vulnerable households. This study takes advantage of a unique longitudinal survey dataset from Kenya and Uganda containing information on household-level soil properties to investigate the effects of soil quality on population mobility. Random effects multinomial logit models are used to test for effects of soil quality on both temporary and permanent migration while accounting for a variety of potential confounders. The analysis reveals that soil quality significantly reduces migration in Kenya, particularly for temporary labor migration, but marginally increases migration in Uganda. These findings are consistent with several previous studies in showing that adverse environmental conditions tend to increase migration but not universally, contrary to common assumptions about environmentally-induced migration

    Consequences of out-migration for land use in rural Ecuador

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    In rural Ecuador and elsewhere in Latin America, the departure of migrants and the receipt of migrant remittances have led to declining rural populations and increasing cash incomes. It is commonly assumed that these processes will lead to agricultural abandonment and the regrowth of native vegetation, thus undermining traditional livelihoods and providing a boon for biodiversity conservation. However, an increasing number of household-level studies have found mixed and complex effects of out-migration and remittances on agriculture. We advance this literature by using household survey data and satellite imagery from three study areas in rural Ecuador to investigate the effects of migration and remittances on agricultural land use. Multivariate methods are used to disaggregate the effects of migration and remittances, to account for other influences on land use and to correct for the potential endogeneity of migration and remittances. Contrary to common assumptions but consistent with previous studies, we find that migrant departure has a positive effect on agricultural activities that is offset by migrant remittances. These results suggest that rural out-migration alone is not likely to lead to a forest transition in the study areas

    Numerical simulations of stellar SiO maser variability. Investigation of the effect of shocks

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    A stellar hydrodynamic pulsation model has been combined with a SiO maser model in an attempt to calculate the temporal variability of SiO maser emission in the circumstellar envelope (CE) of a model AGB star. This study investigates whether the variations in local physical conditions brought about by shocks are the predominant contributing factor to SiO maser variability because, in this work, the radiative part of the pump is constant. We find that some aspects of the variability are not consistent with a pump provided by shock-enhanced collisions alone. In these simulations, gas parcels of relatively enhanced SiO abundance are distributed in a model CE by a Monte Carlo method, at a single epoch of the stellar cycle. From this epoch on, Lagrangian motions of individual parcels are calculated according to the velocity fields encountered in the model CE during the stellar pulsation cycle. The potentially masing gas parcels therefore experience different densities and temperatures, and have varying line-of-sight velocity gradients throughout the stellar cycle, which may or may not be suitable to produce maser emission. At each epoch (separated by 16.6 days), emission lines from the parcels are combined to produce synthetic spectra and VLBI-type images. We report here the results for v=1, J=1-0 (43-GHz) and J=2-1 (86-GHz) masers.Comment: 16 pages, 8 figures, accepted by A&

    A Blind Search for Magnetospheric Emissions from Planetary Companions to Nearby Solar-type Stars

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    This paper reports a blind search for magnetospheric emissions from planets around nearby stars. Young stars are likely to have much stronger stellar winds than the Sun, and because planetary magnetospheric emissions are powered by stellar winds, stronger stellar winds may enhance the radio luminosity of any orbiting planets. Using various stellar catalogs, we selected nearby stars (<~ 30 pc) with relatively young age estimates (< 3 Gyr). We constructed different samples from the stellar catalogs, finding between 100 and several hundred stars. We stacked images from the 74-MHz (4-m wavelength) VLA Low-frequency Sky Survey (VLSS), obtaining 3\sigma limits on planetary emission in the stacked images of between 10 and 33 mJy. These flux density limits correspond to average planetary luminosities less than 5--10 x 10^{23} erg/s. Using recent models for the scaling of stellar wind velocity, density, and magnetic field with stellar age, we estimate scaling factors for the strength of stellar winds, relative to the Sun, in our samples. The typical kinetic energy carried by the stellar winds in our samples is 15--50 times larger than that of the Sun, and the typical magnetic energy is 5--10 times larger. If we assume that every star is orbited by a Jupiter-like planet with a luminosity larger than that of the Jovian decametric radiation by the above factors, our limits on planetary luminosities from the stacking analysis are likely to be a factor of 10--100 above what would be required to detect the planets in a statistical sense. Similar statistical analyses with observations by future instruments, such as the Low Frequency Array (LOFAR) and the Long Wavelength Array (LWA), offer the promise of improvements by factors of 10--100.Comment: 11 pages; AASTeX; accepted for publication in A
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