Statistics of extremes: Modeling ecological disturbances

The potential advantage of extreme value theory in modeling ecological disturbances is the central theme of this paper. The statistics of extremes have played only a very limited role in ecological modeling, despite the disproportionate influence of unusual disturbances on ecosystems. An overview of...

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Main Authors: Katz, R. W., Brush, G. S., Parlange, M. B.
Format: Text
Language:unknown
Published: 2005
Subjects:
Online Access:http://infoscience.epfl.ch/record/53944
http://www.jstor.org/stable/3450873
https://infoscience.epfl.ch/record/53944/files/2005_ecology_mp.pdf
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spelling ftinfoscience:oai:infoscience.tind.io:53944 2023-06-11T04:09:34+02:00 Statistics of extremes: Modeling ecological disturbances Katz, R. W. Brush, G. S. Parlange, M. B. 2005-09-08T12:42:48Z http://infoscience.epfl.ch/record/53944 http://www.jstor.org/stable/3450873 https://infoscience.epfl.ch/record/53944/files/2005_ecology_mp.pdf unknown http://infoscience.epfl.ch/record/53944 http://www.jstor.org/stable/3450873 https://infoscience.epfl.ch/record/53944/files/2005_ecology_mp.pdf http://infoscience.epfl.ch/record/53944 Text 2005 ftinfoscience 2023-05-07T23:50:24Z The potential advantage of extreme value theory in modeling ecological disturbances is the central theme of this paper. The statistics of extremes have played only a very limited role in ecological modeling, despite the disproportionate influence of unusual disturbances on ecosystems. An overview of this theory is provided, with emphasis on recent developments that both make more efficient use of the available data on extremes and enable applications that are more ecologically realistic. Consistent with the emphasis on scale in ecology, scaling properties of extremes are emphasized. It is argued that the existence of distributions whose extreme upper tail is ‘‘heavy’’ (i.e., decreases at a relatively slow rate) implies that ecological disturbances are sometimes regarded as more ‘‘surprising’’ than they ought to be. The application focuses on modeling disturbances in paleoecology. Two examples are considered: the first, a sediment yield time series for Nicolay Lake in the high Arctic, reflects only the influence of hydrologic disturbances; the second, a sediment rate time series in the Chesapeake Bay, includes both climatic and anthropogenic influences. Strong evidence supports a heavy-tailed distribution for the Nicolay Lake sediment yield, but not necessarily for the Chesapeake Bay sediment rates. For each example, it is demonstrated how the statistics of extremes can readily incorporate information about covariates, such as large-scale atmospheric–oceanic circulation patterns or land use. Text Arctic EPFL Infoscience (Ecole Polytechnique Fédérale Lausanne) Arctic
institution Open Polar
collection EPFL Infoscience (Ecole Polytechnique Fédérale Lausanne)
op_collection_id ftinfoscience
language unknown
description The potential advantage of extreme value theory in modeling ecological disturbances is the central theme of this paper. The statistics of extremes have played only a very limited role in ecological modeling, despite the disproportionate influence of unusual disturbances on ecosystems. An overview of this theory is provided, with emphasis on recent developments that both make more efficient use of the available data on extremes and enable applications that are more ecologically realistic. Consistent with the emphasis on scale in ecology, scaling properties of extremes are emphasized. It is argued that the existence of distributions whose extreme upper tail is ‘‘heavy’’ (i.e., decreases at a relatively slow rate) implies that ecological disturbances are sometimes regarded as more ‘‘surprising’’ than they ought to be. The application focuses on modeling disturbances in paleoecology. Two examples are considered: the first, a sediment yield time series for Nicolay Lake in the high Arctic, reflects only the influence of hydrologic disturbances; the second, a sediment rate time series in the Chesapeake Bay, includes both climatic and anthropogenic influences. Strong evidence supports a heavy-tailed distribution for the Nicolay Lake sediment yield, but not necessarily for the Chesapeake Bay sediment rates. For each example, it is demonstrated how the statistics of extremes can readily incorporate information about covariates, such as large-scale atmospheric–oceanic circulation patterns or land use.
format Text
author Katz, R. W.
Brush, G. S.
Parlange, M. B.
spellingShingle Katz, R. W.
Brush, G. S.
Parlange, M. B.
Statistics of extremes: Modeling ecological disturbances
author_facet Katz, R. W.
Brush, G. S.
Parlange, M. B.
author_sort Katz, R. W.
title Statistics of extremes: Modeling ecological disturbances
title_short Statistics of extremes: Modeling ecological disturbances
title_full Statistics of extremes: Modeling ecological disturbances
title_fullStr Statistics of extremes: Modeling ecological disturbances
title_full_unstemmed Statistics of extremes: Modeling ecological disturbances
title_sort statistics of extremes: modeling ecological disturbances
publishDate 2005
url http://infoscience.epfl.ch/record/53944
http://www.jstor.org/stable/3450873
https://infoscience.epfl.ch/record/53944/files/2005_ecology_mp.pdf
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source http://infoscience.epfl.ch/record/53944
op_relation http://infoscience.epfl.ch/record/53944
http://www.jstor.org/stable/3450873
https://infoscience.epfl.ch/record/53944/files/2005_ecology_mp.pdf
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