Charles A. Price , Todd A. Schroeder , Benjamin Branoff , Skip J. Van Bloem , Nicole Pillot-Torres , Morgan H. Chaudry , Monica Papeş , Humfredo Marcano-Vega
{"title":"波多黎各红树林线性维数与生物量的异速生长关系","authors":"Charles A. Price , Todd A. Schroeder , Benjamin Branoff , Skip J. Van Bloem , Nicole Pillot-Torres , Morgan H. Chaudry , Monica Papeş , Humfredo Marcano-Vega","doi":"10.1016/j.foreco.2025.122908","DOIUrl":null,"url":null,"abstract":"<div><div>Accurate biomass estimation is essential for carbon stock assessment and coastal ecosystem management. Despite decades of research and interest in Puerto Rican mangroves, we lack species specific allometric models with only 10 <em>Rhizophora mangle</em> individuals having been collected previously. To address this gap, we developed allometric equations for four mangrove species (<em>Avicennia germinans, Laguncularia racemosa, Rhizophora mangle, and Conocarpus erectus</em>) by harvesting and analyzing 152 individuals. Biomass estimation models were developed using standardized major axis (SMA) regression, incorporating DBH, tree height, crown diameter, and wet mass. Analysis of bivariate relationships between the linear dimensions and mass reveal common allometric slopes between species in 5 out of the 6 relationships. Local equations had a lower RMSE than global models, with DBH-based equations achieving the highest predictive accuracy (<em>R</em>² = 0.94), while crown diameter showed the weakest correlation (<em>R</em>² = 0.74). At the species level, DBH was the best predictor of both wet and dry mass in all cases examined. These results enhance biomass estimation accuracy for Puerto Rican mangroves, providing a critical tool for carbon stock assessments, conservation planning, and regional ecosystem management strategies.<ul><li><span>•</span><span><div>Future allometric harvesting efforts should focus on filling gaps in existing data by sampling new areas and by increasing sample sizes to capture more variability.</div></span></li><li><span>•</span><span><div>When collecting allometric data, researchers should collect trees across the entire range of available sizes.</div></span></li><li><span>•</span><span><div>Collecting allometric data from a broad range of forest types and environments will help to understand the extent of morphological and allometric variability.</div></span></li></ul></div></div>","PeriodicalId":12350,"journal":{"name":"Forest Ecology and Management","volume":"593 ","pages":"Article 122908"},"PeriodicalIF":3.7000,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Allometric relationships for the linear dimensions and biomass of Puerto Rican mangroves\",\"authors\":\"Charles A. Price , Todd A. Schroeder , Benjamin Branoff , Skip J. Van Bloem , Nicole Pillot-Torres , Morgan H. Chaudry , Monica Papeş , Humfredo Marcano-Vega\",\"doi\":\"10.1016/j.foreco.2025.122908\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Accurate biomass estimation is essential for carbon stock assessment and coastal ecosystem management. Despite decades of research and interest in Puerto Rican mangroves, we lack species specific allometric models with only 10 <em>Rhizophora mangle</em> individuals having been collected previously. To address this gap, we developed allometric equations for four mangrove species (<em>Avicennia germinans, Laguncularia racemosa, Rhizophora mangle, and Conocarpus erectus</em>) by harvesting and analyzing 152 individuals. Biomass estimation models were developed using standardized major axis (SMA) regression, incorporating DBH, tree height, crown diameter, and wet mass. Analysis of bivariate relationships between the linear dimensions and mass reveal common allometric slopes between species in 5 out of the 6 relationships. Local equations had a lower RMSE than global models, with DBH-based equations achieving the highest predictive accuracy (<em>R</em>² = 0.94), while crown diameter showed the weakest correlation (<em>R</em>² = 0.74). At the species level, DBH was the best predictor of both wet and dry mass in all cases examined. These results enhance biomass estimation accuracy for Puerto Rican mangroves, providing a critical tool for carbon stock assessments, conservation planning, and regional ecosystem management strategies.<ul><li><span>•</span><span><div>Future allometric harvesting efforts should focus on filling gaps in existing data by sampling new areas and by increasing sample sizes to capture more variability.</div></span></li><li><span>•</span><span><div>When collecting allometric data, researchers should collect trees across the entire range of available sizes.</div></span></li><li><span>•</span><span><div>Collecting allometric data from a broad range of forest types and environments will help to understand the extent of morphological and allometric variability.</div></span></li></ul></div></div>\",\"PeriodicalId\":12350,\"journal\":{\"name\":\"Forest Ecology and Management\",\"volume\":\"593 \",\"pages\":\"Article 122908\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2025-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Forest Ecology and Management\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0378112725004165\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"FORESTRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forest Ecology and Management","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378112725004165","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FORESTRY","Score":null,"Total":0}
Allometric relationships for the linear dimensions and biomass of Puerto Rican mangroves
Accurate biomass estimation is essential for carbon stock assessment and coastal ecosystem management. Despite decades of research and interest in Puerto Rican mangroves, we lack species specific allometric models with only 10 Rhizophora mangle individuals having been collected previously. To address this gap, we developed allometric equations for four mangrove species (Avicennia germinans, Laguncularia racemosa, Rhizophora mangle, and Conocarpus erectus) by harvesting and analyzing 152 individuals. Biomass estimation models were developed using standardized major axis (SMA) regression, incorporating DBH, tree height, crown diameter, and wet mass. Analysis of bivariate relationships between the linear dimensions and mass reveal common allometric slopes between species in 5 out of the 6 relationships. Local equations had a lower RMSE than global models, with DBH-based equations achieving the highest predictive accuracy (R² = 0.94), while crown diameter showed the weakest correlation (R² = 0.74). At the species level, DBH was the best predictor of both wet and dry mass in all cases examined. These results enhance biomass estimation accuracy for Puerto Rican mangroves, providing a critical tool for carbon stock assessments, conservation planning, and regional ecosystem management strategies.
•
Future allometric harvesting efforts should focus on filling gaps in existing data by sampling new areas and by increasing sample sizes to capture more variability.
•
When collecting allometric data, researchers should collect trees across the entire range of available sizes.
•
Collecting allometric data from a broad range of forest types and environments will help to understand the extent of morphological and allometric variability.
期刊介绍:
Forest Ecology and Management publishes scientific articles linking forest ecology with forest management, focusing on the application of biological, ecological and social knowledge to the management and conservation of plantations and natural forests. The scope of the journal includes all forest ecosystems of the world.
A peer-review process ensures the quality and international interest of the manuscripts accepted for publication. The journal encourages communication between scientists in disparate fields who share a common interest in ecology and forest management, bridging the gap between research workers and forest managers.
We encourage submission of papers that will have the strongest interest and value to the Journal''s international readership. Some key features of papers with strong interest include:
1. Clear connections between the ecology and management of forests;
2. Novel ideas or approaches to important challenges in forest ecology and management;
3. Studies that address a population of interest beyond the scale of single research sites, Three key points in the design of forest experiments, Forest Ecology and Management 255 (2008) 2022-2023);
4. Review Articles on timely, important topics. Authors are welcome to contact one of the editors to discuss the suitability of a potential review manuscript.
The Journal encourages proposals for special issues examining important areas of forest ecology and management. Potential guest editors should contact any of the Editors to begin discussions about topics, potential papers, and other details.