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Climate, Fascism, and Ibex: Experiments in Using Population Dynamics Modeling as a Historiographical Tool

In the interwar years the Gran Paradiso ibex population followed two subsequent, contrasting trends: a steady rise once the national park was established in 1922, followed by a precipitous fall after the Fascist regime took direct control of conservation in 1934, which almost led to the colony’s ext...

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Detalles Bibliográficos
Autor principal: Graf von Hardenberg, Wilko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7110951/
https://www.ncbi.nlm.nih.gov/pubmed/31321590
http://dx.doi.org/10.1007/s10739-019-09579-0
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author Graf von Hardenberg, Wilko
author_facet Graf von Hardenberg, Wilko
author_sort Graf von Hardenberg, Wilko
collection PubMed
description In the interwar years the Gran Paradiso ibex population followed two subsequent, contrasting trends: a steady rise once the national park was established in 1922, followed by a precipitous fall after the Fascist regime took direct control of conservation in 1934, which almost led to the colony’s extinction. This paper addresses the issue of how models taken from population ecology may inform historical narratives. The data for the interwar years were analyzed using a statistical model based on climate and population density, which has proved reliable for most of the post-World War II period. The article highlights the pivotal role of anthropic variables in determining the inter-war trends and how these are best analyzed using historical scholarship.
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spelling pubmed-71109512020-04-06 Climate, Fascism, and Ibex: Experiments in Using Population Dynamics Modeling as a Historiographical Tool Graf von Hardenberg, Wilko J Hist Biol Original Research In the interwar years the Gran Paradiso ibex population followed two subsequent, contrasting trends: a steady rise once the national park was established in 1922, followed by a precipitous fall after the Fascist regime took direct control of conservation in 1934, which almost led to the colony’s extinction. This paper addresses the issue of how models taken from population ecology may inform historical narratives. The data for the interwar years were analyzed using a statistical model based on climate and population density, which has proved reliable for most of the post-World War II period. The article highlights the pivotal role of anthropic variables in determining the inter-war trends and how these are best analyzed using historical scholarship. Springer Netherlands 2019-07-18 2019 /pmc/articles/PMC7110951/ /pubmed/31321590 http://dx.doi.org/10.1007/s10739-019-09579-0 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Research
Graf von Hardenberg, Wilko
Climate, Fascism, and Ibex: Experiments in Using Population Dynamics Modeling as a Historiographical Tool
title Climate, Fascism, and Ibex: Experiments in Using Population Dynamics Modeling as a Historiographical Tool
title_full Climate, Fascism, and Ibex: Experiments in Using Population Dynamics Modeling as a Historiographical Tool
title_fullStr Climate, Fascism, and Ibex: Experiments in Using Population Dynamics Modeling as a Historiographical Tool
title_full_unstemmed Climate, Fascism, and Ibex: Experiments in Using Population Dynamics Modeling as a Historiographical Tool
title_short Climate, Fascism, and Ibex: Experiments in Using Population Dynamics Modeling as a Historiographical Tool
title_sort climate, fascism, and ibex: experiments in using population dynamics modeling as a historiographical tool
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7110951/
https://www.ncbi.nlm.nih.gov/pubmed/31321590
http://dx.doi.org/10.1007/s10739-019-09579-0
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