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A Hierarchical Threshold Modeling Ap...

Nummer, Stephanie A.,

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A Hierarchical Threshold Modeling Approach for Understanding Biological and Physical System Responses to Climate Change /

Record Type:	Electronic resources : Monograph/item
Title/Author:	A Hierarchical Threshold Modeling Approach for Understanding Biological and Physical System Responses to Climate Change // Stephanie A Nummer.
Author:	Nummer, Stephanie A.,
Description:	1 electronic resource (115 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 83-09, Section: B.
Contained By:	Dissertations Abstracts International83-09B.
Subject:	Ecology. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29133698
ISBN:	9798209890645

A Hierarchical Threshold Modeling Approach for Understanding Biological and Physical System Responses to Climate Change /
Nummer, Stephanie A.,

A Hierarchical Threshold Modeling Approach for Understanding Biological and Physical System Responses to Climate Change /Stephanie A Nummer. - 1 electronic resource (115 pages)

Source: Dissertations Abstracts International, Volume: 83-09, Section: B.

Prior to the recent upward climb, global average temperatures were relatively stable and was described by Mann et al. 1999 using a hockey-stick model. The hockey-stick model consists of two line segments (with the x-axis as time and temperature as the y-axis) meeting at a single changepoint. The hockey-stick model also describes North American average temperatures. The line segment prior to the changepoint is flat (indicating a stable average temperature), and the line after the changepoint has a positive slope (indicating increasing average temperatures). Because the long-term average temperature change is a defining characteristic of climate change, researchers have shown that changes in many phenological variables over time can also be described by a hockey-stick model. For phenological variables, the changepoint and the slope of the line after the changepoint represent the timing of the onset and the effect the change in phenological signal in response of climate change. However, large annual variation often obscures the pattern when analyzed using data from a single location/species, whereas regional differences due to spatial variability of climate and weather patterns render pooling data from different locations impractical. The Bayesian hierarchical modeling approach is effective in separating these two sources of variability by partially pooling data from multiple location/species. As such, I develop a Bayesian hierarchical hockey-stick model and apply it to different biological and physical systems that respond to temperature. Our systems of interest are 1) North American lilac first bloom dates, 2) Great Lakes ice coverage duration, and 3) spring and fall migratory bird migration season at Powdermill Nature Reserve - Avian Research Center (PNR - ARC). After applying the hockey-stick model to the systems of interest, North American lilac first bloom dates generally began to response to the long-term change in temperature in 1973 and are shifting roughly one day earlier every three years subsequently. The duration of Great Lakes ice coverage has been decreasing by approximately three days every four years since mid-1979 in response to the change in temperature. Finally, spring migration through PNR - ARC presents with 20 species advancing their passage and 17 species not responding to climate change with a shift in migration through PNR - ARC. Fall migration at PNR - ARC is slightly more complicated with some species shifting passage time to earlier in the season, some shifting to later passage time, and many of the species studied not responding to climate change via migratory timing in the fall. It is important to understand and accurately estimate the rate of change of phenological signals because different systems and trophic levels can shift at different rates - leading to increased risk to the population size of different species and thus community structure.

English

ISBN: 9798209890645Subjects--Topical Terms:

516476
Ecology.
Subjects--Index Terms:

Climate Change

A Hierarchical Threshold Modeling Approach for Understanding Biological and Physical System Responses to Climate Change /
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300 $a 1 electronic resource (115 pages)
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500 $a Source: Dissertations Abstracts International, Volume: 83-09, Section: B.
500 $a Advisors: Qian, Song S. Committee members: Gronewold, Andrew; Refsnider, Jeanine M.; Shao, Qin; Streby, Henry M.
502 $b Ph.D. $c The University of Toledo $d 2021.
520 $a Prior to the recent upward climb, global average temperatures were relatively stable and was described by Mann et al. 1999 using a hockey-stick model. The hockey-stick model consists of two line segments (with the x-axis as time and temperature as the y-axis) meeting at a single changepoint. The hockey-stick model also describes North American average temperatures. The line segment prior to the changepoint is flat (indicating a stable average temperature), and the line after the changepoint has a positive slope (indicating increasing average temperatures). Because the long-term average temperature change is a defining characteristic of climate change, researchers have shown that changes in many phenological variables over time can also be described by a hockey-stick model. For phenological variables, the changepoint and the slope of the line after the changepoint represent the timing of the onset and the effect the change in phenological signal in response of climate change. However, large annual variation often obscures the pattern when analyzed using data from a single location/species, whereas regional differences due to spatial variability of climate and weather patterns render pooling data from different locations impractical. The Bayesian hierarchical modeling approach is effective in separating these two sources of variability by partially pooling data from multiple location/species. As such, I develop a Bayesian hierarchical hockey-stick model and apply it to different biological and physical systems that respond to temperature. Our systems of interest are 1) North American lilac first bloom dates, 2) Great Lakes ice coverage duration, and 3) spring and fall migratory bird migration season at Powdermill Nature Reserve - Avian Research Center (PNR - ARC). After applying the hockey-stick model to the systems of interest, North American lilac first bloom dates generally began to response to the long-term change in temperature in 1973 and are shifting roughly one day earlier every three years subsequently. The duration of Great Lakes ice coverage has been decreasing by approximately three days every four years since mid-1979 in response to the change in temperature. Finally, spring migration through PNR - ARC presents with 20 species advancing their passage and 17 species not responding to climate change with a shift in migration through PNR - ARC. Fall migration at PNR - ARC is slightly more complicated with some species shifting passage time to earlier in the season, some shifting to later passage time, and many of the species studied not responding to climate change via migratory timing in the fall. It is important to understand and accurately estimate the rate of change of phenological signals because different systems and trophic levels can shift at different rates - leading to increased risk to the population size of different species and thus community structure.
546 $a English
590 $a School code: 0232
650 4 $a Ecology. $3 516476
650 4 $a Atmospheric sciences. $3 3168354
650 4 $a Meteorology. $3 542822
650 4 $a Climate change. $2 bicssc $3 2079509
653 $a Climate Change
653 $a Phenology
653 $a Bayesian
653 $a Hierarchical model
690 $a 0404
690 $a 0557
690 $a 0725
690 $a 0329
710 2 $a The University of Toledo. $b Biology (Ecology). $e degree granting institution. $3 3823289
720 1 $a Qian, Song S. $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 83-09B.
790 $a 0232
791 $a Ph.D.
792 $a 2021
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29133698