Modeling Litter Stocks in Planted Forests of Northern Mexico
Litter, <i>LS</i>, is the organic material in which locates in the top A soil horizon, playing key ecological roles in forests. Models, in contrast to common allocation factors, must be used in <i>LS</i> assessments as they are currently absent in the scientific literature. I...
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MDPI AG
2022-07-01
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| Series: | Forests |
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| Online Access: | https://www.mdpi.com/1999-4907/13/7/1049 |
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| author | Felipa de Jesús Rodríguez-Flores José-Guadalupe Colín José de Jesús Graciano-Luna José Návar |
| author_facet | Felipa de Jesús Rodríguez-Flores José-Guadalupe Colín José de Jesús Graciano-Luna José Návar |
| author_sort | Felipa de Jesús Rodríguez-Flores |
| collection | DOAJ |
| description | Litter, <i>LS</i>, is the organic material in which locates in the top A soil horizon, playing key ecological roles in forests. Models, in contrast to common allocation factors, must be used in <i>LS</i> assessments as they are currently absent in the scientific literature. Its evaluation assess the mass, input and flux of several bio-geo-chemicals, rainfall interception as one component of the local hydrology, and wildfire regimes, among others, hence its importance in forestry. The aim of this study was to: (i) develop models to assess <i>LS</i>, accumulation, and loss rates; and (ii) assess rainfall interception and fire regimes in 133 northern forest plantations of Mexico. Two developed techniques: the statistical model (SM<sub>LS</sub>) and the mass balance budget model (MBM<sub>LS</sub>) tested and validated local and regional <i>LS</i> datasets. Models use basal area, timber, aboveground tree biomass, litter fall, accumulation, and loss sub-models. The best fitting model was used to predict rainfall interception and fire behavior in forest plantations. Results showed the SM<sub>LS</sub> model predicted and validated <i>LS</i> datasets (<i>p</i> = 0.0001; <i>r</i><sup>2</sup> = 0.82 and <i>p</i> = 0.0001; <i>r</i><sup>2</sup> = 0.79) better than the MBM<sub>LS</sub> model (<i>p</i> = 0.0001; <i>r</i><sup>2</sup> = 0.32 and <i>p</i> = 0.0001; <i>r</i><sup>2</sup> = 0.66) but the later followed well tendencies of Mexican and World datasets; counts for inputs, stocks, and losses from all processes and revealed decomposition loss may explain ≈40% of the total <i>LS</i> variance. SM<sub>LS</sub> predicted forest plantations growing in high productivity 40-year-old stands accumulate <i>LS</i> > 30 Mg ha<sup>−1</sup> shifting to the new high-severity wildfire regime and intercepting ≈15% of the annual rainfall. SM<sub>LS</sub> is preliminarily recommended for <i>LS</i> assessments and predicts the need of <i>LS</i> management in forest plantations (>40-year-old) to reduce rainfall interception as well as the risk of high-severity wildfires. The novel, flexible, simple, contrasting and consistent modeling approaches is a piece of scientific information required in forest management. |
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| id | doaj.art-23f27e29ad8e4f5bb02e20d26f29f1a8 |
| institution | Directory Open Access Journal |
| issn | 1999-4907 |
| language | English |
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| publishDate | 2022-07-01 |
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| series | Forests |
| spelling | doaj.art-23f27e29ad8e4f5bb02e20d26f29f1a82023-12-03T15:03:12ZengMDPI AGForests1999-49072022-07-01137104910.3390/f13071049Modeling Litter Stocks in Planted Forests of Northern MexicoFelipa de Jesús Rodríguez-Flores0José-Guadalupe Colín1José de Jesús Graciano-Luna2José Návar3Ingeniería en Tecnología Ambiental, Universidad Politécnica de Durango, Carretera Durango-México Km 9.5, Localidad Dolores Hidalgo, Durango C.P. 34300, MexicoTecnológico Nacional de México/Instituto Tecnológico de El Salto, Calle Tecnológico No 101, Colonia La Forestal, El Salto, Durango C.P. 34942, MexicoTecnológico Nacional de México/Instituto Tecnológico de El Salto, Calle Tecnológico No 101, Colonia La Forestal, El Salto, Durango C.P. 34942, MexicoTecnológico Nacional de México/Instituto Tecnológico de Ciudad Victoria, Blvd Emilio Portes Gil No 1301 Pte., Cd Victoria C.P. 87010, Tamaulipas, MexicoLitter, <i>LS</i>, is the organic material in which locates in the top A soil horizon, playing key ecological roles in forests. Models, in contrast to common allocation factors, must be used in <i>LS</i> assessments as they are currently absent in the scientific literature. Its evaluation assess the mass, input and flux of several bio-geo-chemicals, rainfall interception as one component of the local hydrology, and wildfire regimes, among others, hence its importance in forestry. The aim of this study was to: (i) develop models to assess <i>LS</i>, accumulation, and loss rates; and (ii) assess rainfall interception and fire regimes in 133 northern forest plantations of Mexico. Two developed techniques: the statistical model (SM<sub>LS</sub>) and the mass balance budget model (MBM<sub>LS</sub>) tested and validated local and regional <i>LS</i> datasets. Models use basal area, timber, aboveground tree biomass, litter fall, accumulation, and loss sub-models. The best fitting model was used to predict rainfall interception and fire behavior in forest plantations. Results showed the SM<sub>LS</sub> model predicted and validated <i>LS</i> datasets (<i>p</i> = 0.0001; <i>r</i><sup>2</sup> = 0.82 and <i>p</i> = 0.0001; <i>r</i><sup>2</sup> = 0.79) better than the MBM<sub>LS</sub> model (<i>p</i> = 0.0001; <i>r</i><sup>2</sup> = 0.32 and <i>p</i> = 0.0001; <i>r</i><sup>2</sup> = 0.66) but the later followed well tendencies of Mexican and World datasets; counts for inputs, stocks, and losses from all processes and revealed decomposition loss may explain ≈40% of the total <i>LS</i> variance. SM<sub>LS</sub> predicted forest plantations growing in high productivity 40-year-old stands accumulate <i>LS</i> > 30 Mg ha<sup>−1</sup> shifting to the new high-severity wildfire regime and intercepting ≈15% of the annual rainfall. SM<sub>LS</sub> is preliminarily recommended for <i>LS</i> assessments and predicts the need of <i>LS</i> management in forest plantations (>40-year-old) to reduce rainfall interception as well as the risk of high-severity wildfires. The novel, flexible, simple, contrasting and consistent modeling approaches is a piece of scientific information required in forest management.https://www.mdpi.com/1999-4907/13/7/1049litter stock & accumulation rateslitter lossesmodel predictionsmass balance budget modelforest wildfires |
| spellingShingle | Felipa de Jesús Rodríguez-Flores José-Guadalupe Colín José de Jesús Graciano-Luna José Návar Modeling Litter Stocks in Planted Forests of Northern Mexico Forests litter stock & accumulation rates litter losses model predictions mass balance budget model forest wildfires |
| title | Modeling Litter Stocks in Planted Forests of Northern Mexico |
| title_full | Modeling Litter Stocks in Planted Forests of Northern Mexico |
| title_fullStr | Modeling Litter Stocks in Planted Forests of Northern Mexico |
| title_full_unstemmed | Modeling Litter Stocks in Planted Forests of Northern Mexico |
| title_short | Modeling Litter Stocks in Planted Forests of Northern Mexico |
| title_sort | modeling litter stocks in planted forests of northern mexico |
| topic | litter stock & accumulation rates litter losses model predictions mass balance budget model forest wildfires |
| url | https://www.mdpi.com/1999-4907/13/7/1049 |
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