Modeling Tree Growth Responses to Climate Change: A Case Study in Natural Deciduous Mountain Forests
Climate change has significant effects on forest ecosystems around the world. Since tree diameter increment determines forest volume increment and ultimately forest production, an accurate estimate of this variable under future climate change is of great importance for sustainable forest management....
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-10-01
|
| Series: | Forests |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4907/13/11/1816 |
| _version_ | 1797468238986084352 |
|---|---|
| author | Mahmoud Bayat Thomas Knoke Sahar Heidari Seyedeh Kosar Hamidi Harold Burkhart Abolfazl Jaafari |
| author_facet | Mahmoud Bayat Thomas Knoke Sahar Heidari Seyedeh Kosar Hamidi Harold Burkhart Abolfazl Jaafari |
| author_sort | Mahmoud Bayat |
| collection | DOAJ |
| description | Climate change has significant effects on forest ecosystems around the world. Since tree diameter increment determines forest volume increment and ultimately forest production, an accurate estimate of this variable under future climate change is of great importance for sustainable forest management. In this study, we modeled tree diameter increment under the effects of current and expected future climate change, using multilayer perceptron (MLP) artificial neural networks and linear mixed-effect model in two sites of the Hyrcanian Forest, northern Iran. Using 573 monitoring fixed-area (0.1 ha) plots, we measured and calculated biotic and abiotic factors (i.e., diameter at breast height (DBH), basal area in the largest trees (BAL), basal area (BA), elevation, aspect, slope, precipitation, and temperature). We investigated the effect of climate change in the year 2070 under two reference scenarios; RCP 4.5 (an intermediate scenario) and RCP 8.5 (an extreme scenario) due to the uncertainty caused by the general circulation models. According to the scenarios of climate change, the amount of annual precipitation and temperature during the study period will increase by 12.18 mm and 1.77 °C, respectively. Further, the results showed that the impact of predicted climate change was not very noticeable and the growth at the end of the period decreased by only about 7% annually. The effect of precipitation and temperature on the growth rate, in fact, neutralize each other, and therefore, the growth rate does not change significantly at the end of the period compared to the beginning. Based on the models’ predictions, the MLP model performed better compared to the linear mixed-effect model in predicting tree diameter increment. |
| first_indexed | 2024-03-09T19:04:35Z |
| format | Article |
| id | doaj.art-7e0e75cf28f04b5e8205709a4c4c58be |
| institution | Directory Open Access Journal |
| issn | 1999-4907 |
| language | English |
| last_indexed | 2024-03-09T19:04:35Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Forests |
| spelling | doaj.art-7e0e75cf28f04b5e8205709a4c4c58be2023-11-24T04:43:40ZengMDPI AGForests1999-49072022-10-011311181610.3390/f13111816Modeling Tree Growth Responses to Climate Change: A Case Study in Natural Deciduous Mountain ForestsMahmoud Bayat0Thomas Knoke1Sahar Heidari2Seyedeh Kosar Hamidi3Harold Burkhart4Abolfazl Jaafari5Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran 1496813111, IranInstitute of Forest Management, TUM School of Life Sciences Weihenstephan, Technical University of Munich, Hans-Carl-von-Carlowitz-Platz 2, 85354 Freising, GermanyDepartment of Environment, Faculty of Natural Resources, University of Tehran, Tehran 3158777871, IranDepartment of Forestry, Faculty of Natural Resources, Sari Agriculture Sciences and Natural Resource University, Sari 4818166996, IranDepartment of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University, 319 Cheatham Hall, 310 West Campus Drive, Blacksburg, VA 24061, USAResearch Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran 1496813111, IranClimate change has significant effects on forest ecosystems around the world. Since tree diameter increment determines forest volume increment and ultimately forest production, an accurate estimate of this variable under future climate change is of great importance for sustainable forest management. In this study, we modeled tree diameter increment under the effects of current and expected future climate change, using multilayer perceptron (MLP) artificial neural networks and linear mixed-effect model in two sites of the Hyrcanian Forest, northern Iran. Using 573 monitoring fixed-area (0.1 ha) plots, we measured and calculated biotic and abiotic factors (i.e., diameter at breast height (DBH), basal area in the largest trees (BAL), basal area (BA), elevation, aspect, slope, precipitation, and temperature). We investigated the effect of climate change in the year 2070 under two reference scenarios; RCP 4.5 (an intermediate scenario) and RCP 8.5 (an extreme scenario) due to the uncertainty caused by the general circulation models. According to the scenarios of climate change, the amount of annual precipitation and temperature during the study period will increase by 12.18 mm and 1.77 °C, respectively. Further, the results showed that the impact of predicted climate change was not very noticeable and the growth at the end of the period decreased by only about 7% annually. The effect of precipitation and temperature on the growth rate, in fact, neutralize each other, and therefore, the growth rate does not change significantly at the end of the period compared to the beginning. Based on the models’ predictions, the MLP model performed better compared to the linear mixed-effect model in predicting tree diameter increment.https://www.mdpi.com/1999-4907/13/11/1816biotic and abiotic factorsclimate changeHyrcanian Forestmachine learningRCP scenarios |
| spellingShingle | Mahmoud Bayat Thomas Knoke Sahar Heidari Seyedeh Kosar Hamidi Harold Burkhart Abolfazl Jaafari Modeling Tree Growth Responses to Climate Change: A Case Study in Natural Deciduous Mountain Forests Forests biotic and abiotic factors climate change Hyrcanian Forest machine learning RCP scenarios |
| title | Modeling Tree Growth Responses to Climate Change: A Case Study in Natural Deciduous Mountain Forests |
| title_full | Modeling Tree Growth Responses to Climate Change: A Case Study in Natural Deciduous Mountain Forests |
| title_fullStr | Modeling Tree Growth Responses to Climate Change: A Case Study in Natural Deciduous Mountain Forests |
| title_full_unstemmed | Modeling Tree Growth Responses to Climate Change: A Case Study in Natural Deciduous Mountain Forests |
| title_short | Modeling Tree Growth Responses to Climate Change: A Case Study in Natural Deciduous Mountain Forests |
| title_sort | modeling tree growth responses to climate change a case study in natural deciduous mountain forests |
| topic | biotic and abiotic factors climate change Hyrcanian Forest machine learning RCP scenarios |
| url | https://www.mdpi.com/1999-4907/13/11/1816 |
| work_keys_str_mv | AT mahmoudbayat modelingtreegrowthresponsestoclimatechangeacasestudyinnaturaldeciduousmountainforests AT thomasknoke modelingtreegrowthresponsestoclimatechangeacasestudyinnaturaldeciduousmountainforests AT saharheidari modelingtreegrowthresponsestoclimatechangeacasestudyinnaturaldeciduousmountainforests AT seyedehkosarhamidi modelingtreegrowthresponsestoclimatechangeacasestudyinnaturaldeciduousmountainforests AT haroldburkhart modelingtreegrowthresponsestoclimatechangeacasestudyinnaturaldeciduousmountainforests AT abolfazljaafari modelingtreegrowthresponsestoclimatechangeacasestudyinnaturaldeciduousmountainforests |