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...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-11-01
|
| Series: | Forests |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4907/12/11/1560 |
| _version_ | 1797510207083905024 |
|---|---|
| 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 |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T05:28:19Z |
| format | Article |
| id | doaj.art-2ad2c4b6328b4d7c97a276c11e4c0ba0 |
| institution | Directory Open Access Journal |
| issn | 1999-4907 |
| language | English |
| last_indexed | 2024-03-10T05:28:19Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Forests |
| spelling | doaj.art-2ad2c4b6328b4d7c97a276c11e4c0ba02023-11-22T23:25:31ZengMDPI AGForests1999-49072021-11-011211156010.3390/f12111560The Significance of Aggregation Methods in Functional Group ModelingHuan Zhang0Herman H. Shugart1Bin Wang2Manuel Lerdau3School of Landscape and Ecological Engineering, Hebei University of Engineering, Handan 056038, ChinaDepartment of Environmental Sciences, University of Virginia, Charlottesville, VA 22901, USAEnvironmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 38730, USADepartment of Environmental Sciences, University of Virginia, Charlottesville, VA 22901, USAThe 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.https://www.mdpi.com/1999-4907/12/11/1560individual-based modelgap modelIBMfunctional typesUVAFME modelmixed-species model |
| spellingShingle | Huan Zhang Herman H. Shugart Bin Wang Manuel Lerdau The Significance of Aggregation Methods in Functional Group Modeling Forests individual-based model gap model IBM functional types UVAFME model mixed-species model |
| title | 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_short | The Significance of Aggregation Methods in Functional Group Modeling |
| title_sort | significance of aggregation methods in functional group modeling |
| topic | individual-based model gap model IBM functional types UVAFME model mixed-species model |
| url | https://www.mdpi.com/1999-4907/12/11/1560 |
| 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 |