Depósito y descomposición de hojarasca de Pinus cooperi C.E.Blanco en El Salto, Durango, México

López-Hernández, Juan; Corral-Rivas, José Javier; González‐Rodríguez, Humberto; Domínguez-Gómez, Tilo Gustavo; Meza, Marco Vinicio Gómez; Silva, Israel Cantú

doi:10.29298/rmcf.v9i50.249

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…In addition to the originally reported litter fall data, other data sets, including the confidence bounds, of the rate of litter fall [43][44][45][46]; other regional data, Mexico's commercial forest inventory data sets, and World litter data in forests [47] were added to the graph to test the strength of the relationship across these conifer forests. In addition to the originally reported litter fall data, other data sets, including the confidence bounds, of the rate of litter fall [43][44][45][46]; other regional data, Mexico's commercial forest inventory data sets, and World litter data in forests [47] were added to the graph to test the strength of the relationship across these conifer forests.…”

Section: Mass Balance Model Mbm Lsmentioning

confidence: 99%

Modeling Litter Stocks in Planted Forests of Northern Mexico

Rodríguez-Flores

Colín

Graciano-Luna

et al. 2022

Forests

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Litter, LS, 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 LS 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 LS, 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 (SMLS) and the mass balance budget model (MBMLS) tested and validated local and regional LS 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 SMLS model predicted and validated LS datasets (p = 0.0001; r2 = 0.82 and p = 0.0001; r2 = 0.79) better than the MBMLS model (p = 0.0001; r2 = 0.32 and p = 0.0001; r2 = 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 LS variance. SMLS predicted forest plantations growing in high productivity 40-year-old stands accumulate LS > 30 Mg ha−1 shifting to the new high-severity wildfire regime and intercepting ≈15% of the annual rainfall. SMLS is preliminarily recommended for LS assessments and predicts the need of LS 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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Section: Mass Balance Model Mbm Lsmentioning

confidence: 99%

Modeling Litter Stocks in Planted Forests of Northern Mexico

Rodríguez-Flores

Colín

Graciano-Luna

et al. 2022

Forests

View full text Add to dashboard Cite

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Modelos de descomposición del mantillo en ecosistemas templados del Noreste de México

Ramos Hernández,

López Hernández,

Gómez Meza

et al. 2023

RMCF

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La descomposición del mantillo es un proceso fundamental para mantener la productividad primaria neta y la fertilidad de los ecosistemas forestales. Por tal motivo, se realizó un estudio en el ejido Pablillo, municipio Galeana, Nuevo León, México durante un año para conocer el proceso de descomposición del mantillo en tres ecosistemas forestales de clima templado (pino, encino y pino-encino) que incluyó modelos para predecir la tasa de descomposición. En cada ecosistema se distribuyeron en cinco parcelas de 20 m×20 m 60 bolsas de polipropileno negro con 10 g de mantillo. Al comparar los tres tipos de vegetación, la pérdida de masa fue de 14 % para pino, 22 % en pino-encino y 23 % para encino. De acuerdo con el análisis de regresión, los modelos exponencial negativo simple (Olson) y lineal simple mostraron la mejor bondad de ajuste respecto a los modelos logarítmico y de potencia. El modelo lineal simple presentó un mejor ajuste con valores de R2=0.719 (encino), 0.626 (pino) y 0.620 (pino-encino); para el modelo de Olson, el Coeficiente R2 varió de 0.710 (encino) a 0.617 (pino-encino). La constante de descomposición del modelo de Olson fluctuó de 1.017 (encino) a 0.946 años (pino-encino), y en el modelo lineal simple de 1.009 (encino) a 0.944 años (pino-encino). El proceso de descomposición tuvo diferencias significativas entre ecosistemas atribuibles a la composición química del mantillo. En el ecosistema de pino se presentó el menor porcentaje de descomposición.

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Depósito y descomposición de hojarasca de Pinus cooperi C.E.Blanco en El Salto, Durango, México

Cited by 2 publications

References 11 publications

Modeling Litter Stocks in Planted Forests of Northern Mexico

Modeling Litter Stocks in Planted Forests of Northern Mexico

Modelos de descomposición del mantillo en ecosistemas templados del Noreste de México

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