The Significance of Aggregation Methods in Functional Group Modeling

The growth of forests and the feedbacks between forests and environmental changes are central issues in the planetary carbon cycle, global climate change, and basic plant ecology. A challenge to understanding both growth and feedbacks from local to global scales is that many critical metabolic proce...

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Autores principales:	Huan Zhang, Herman H. Shugart, Bin Wang, Manuel Lerdau
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	individual-based model gap model IBM functional types UVAFME model mixed-species model Plant ecology QK900-989
Acceso en línea:	https://doaj.org/article/2ad2c4b6328b4d7c97a276c11e4c0ba0
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spelling	oai:doaj.org-article:2ad2c4b6328b4d7c97a276c11e4c0ba02021-11-25T17:38:46ZThe Significance of Aggregation Methods in Functional Group Modeling10.3390/f121115601999-4907https://doaj.org/article/2ad2c4b6328b4d7c97a276c11e4c0ba02021-11-01T00:00:00Zhttps://www.mdpi.com/1999-4907/12/11/1560https://doaj.org/toc/1999-4907The growth of forests and the feedbacks between forests and environmental changes are central issues in the planetary carbon cycle, global climate change, and basic plant ecology. A challenge to understanding both growth and feedbacks from local to global scales is that many critical metabolic processes vary among species. An innovation in solving this challenge is the recognition that species can be lumped into “functional groups” based on metabolic similarity, and these functional groups can then be studied in computational models that simulate ecosystem function. Despite the vast resources devoted to functional group studies and the progress made by them, an important logical and biological question has not been formally addressed, “How do the groupings alter the results of modeling studies?” To what extent do modeling results depend on the choices made in aggregating taxa into functional groups. Here, we consider the effects of using different aggregation strategies in simulating the carbon dynamics of a deciduous forest. Understanding the impacts that aggregation strategy has on efforts to simulate regional-to-global-scale forest dynamics offers insights into both ecosystem regulation and model function and addresses this central problem in the study of carbon dynamics.Huan ZhangHerman H. ShugartBin WangManuel LerdauMDPI AGarticleindividual-based modelgap modelIBMfunctional typesUVAFME modelmixed-species modelPlant ecologyQK900-989ENForests, Vol 12, Iss 1560, p 1560 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	individual-based model gap model IBM functional types UVAFME model mixed-species model Plant ecology QK900-989
spellingShingle	individual-based model gap model IBM functional types UVAFME model mixed-species model Plant ecology QK900-989 Huan Zhang Herman H. Shugart Bin Wang Manuel Lerdau The Significance of Aggregation Methods in Functional Group Modeling
description	The growth of forests and the feedbacks between forests and environmental changes are central issues in the planetary carbon cycle, global climate change, and basic plant ecology. A challenge to understanding both growth and feedbacks from local to global scales is that many critical metabolic processes vary among species. An innovation in solving this challenge is the recognition that species can be lumped into “functional groups” based on metabolic similarity, and these functional groups can then be studied in computational models that simulate ecosystem function. Despite the vast resources devoted to functional group studies and the progress made by them, an important logical and biological question has not been formally addressed, “How do the groupings alter the results of modeling studies?” To what extent do modeling results depend on the choices made in aggregating taxa into functional groups. Here, we consider the effects of using different aggregation strategies in simulating the carbon dynamics of a deciduous forest. Understanding the impacts that aggregation strategy has on efforts to simulate regional-to-global-scale forest dynamics offers insights into both ecosystem regulation and model function and addresses this central problem in the study of carbon dynamics.
format	article
author	Huan Zhang Herman H. Shugart Bin Wang Manuel Lerdau
author_facet	Huan Zhang Herman H. Shugart Bin Wang Manuel Lerdau
author_sort	Huan Zhang
title	The Significance of Aggregation Methods in Functional Group Modeling
title_short	The Significance of Aggregation Methods in Functional Group Modeling
title_full	The Significance of Aggregation Methods in Functional Group Modeling
title_fullStr	The Significance of Aggregation Methods in Functional Group Modeling
title_full_unstemmed	The Significance of Aggregation Methods in Functional Group Modeling
title_sort	significance of aggregation methods in functional group modeling
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/2ad2c4b6328b4d7c97a276c11e4c0ba0
work_keys_str_mv	AT huanzhang thesignificanceofaggregationmethodsinfunctionalgroupmodeling AT hermanhshugart thesignificanceofaggregationmethodsinfunctionalgroupmodeling AT binwang thesignificanceofaggregationmethodsinfunctionalgroupmodeling AT manuellerdau thesignificanceofaggregationmethodsinfunctionalgroupmodeling AT huanzhang significanceofaggregationmethodsinfunctionalgroupmodeling AT hermanhshugart significanceofaggregationmethodsinfunctionalgroupmodeling AT binwang significanceofaggregationmethodsinfunctionalgroupmodeling AT manuellerdau significanceofaggregationmethodsinfunctionalgroupmodeling
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The Significance of Aggregation Methods in Functional Group Modeling

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