A spatially explicit model of litter accumulation in fire maintained longleaf pine forest ecosystems of the Southeastern USA

Abstract

The continuity and depth of the surface fuel layer (i.e., litter and duff) are major drivers of fire spread and fuel consumption. Nevertheless, its spatial explicit quantification over relatively large areas remains unresolved: local fuel heterogeneity introduces large uncertainties in estimates derived from field-based models and sparse data samples. Besides that, the sensitivity of remote sensors to surface litter loads is limited, particularly under canopy cover. In fire-maintained pine forests of the Southeastern US, surface fuel accumulation and its distribution over the forest floor are mainly driven by vegetation productivity, decomposition, and time since fire (TSF). Traditional ecological and stand-level models provide a means to equilibrate between opposing rates of deposition and decomposition as a function of TSF at the landscape level but don’t account for spatial heterogeneity. We developed a top-down, object-based approach for wall-to-wall estimation of surface litter loads using TSF records, the ecological-based Olson model, and tree crown objects derived from airborne laser scanning (ALS) data. The approach involves, first, the spatially explicit estimation of litter production through a tree crown production model, driven by tree crown attributes extracted from the ALS point clouds, and informed by tree inventory data and allometric equations, including vegetation leaf turnover rates. Second, litter accumulation is estimated using the fire-driven Olson equation, which models accumulation progressively with time until decomposition balances deposition and a steady state of accumulation is reached. The methodology is demonstrated at several fire-maintained longleaf pine forest locations in southeastern USA, where tree inventory data, surface litter loads, prescribed fire records, and ALS data are available for testing and validation of the methodology. Comparison between preliminary modeled estimates and observed litter loads shows a relatively good agreement (RMSE=0.21 [kg m-2]; BIAS 0.07 [kg m-2]). This suggests that the proposed approach to indirectly map patterns of litter production and litter accumulation can provide a realistic means to map the continuity of the litter layer, thus overcoming the limitation of traditional ecological landscape models to account for spatial heterogeneity. This high-resolution map of litter loads will be further valuable as input to physics-based fire behavior and spread models and to improve the spatially explicit characterization of the duff layer.

Pine trees structure plant biodiversity patterns in savannas

“…Although previous research at these sites did not detect differences in some fire-related characteristics of basal and open locations after one fire (Kreye et al, 2020), the occurrence of certain species close to and away from pines could reflect the longterm fire history at each point (Brewer, 2023). In addition, they could result from spatial patterns of pine litter deposition, which has been shown to vary with time since fire, decomposition rate, stand structure, and direction of prevailing winds (Blaydes et al, 2023;Sánchez-López et al, 2023). Fine-scale fuel heterogeneity results in spatial variation in plant survival and establishment through aboveground fire intensity or soil heating (Platt et al, 2016;Kennard & Outcalt 2006), which ultimately manifests in differential community assembly over time (Mugnani et al, 2019;Robertson et al, 2019).…”

Fuel buildup shapes post-fire fuel decomposition through soil heating effects on plants, fungi, and soil chemistry

“…As in most savannas, pyrophilic plants form a continuous layer of surface vegetation and fire-resistant trees (here longleaf pines) form an incomplete canopy (Peet et al, 2018). The spatial heterogeneity of the pine canopy creates variation in fire severity through differences in pine needle and grass fuel loads (Ellair and Platt, 2013; Platt et al, 2016b; Sánchez-López et al, 2023). Previous work in this system has linked variation in fire severity and frequency to changes in fungal (SemenovaLJNelsen et al, 2019) and bacterial communities (Dao et al 2022), as well as reduced decomposition (Hopkins et al, 2020).…”

Application of Multivariate Principal Component Analysis for Characterization of Leaf Litters in Northern Nigeria

“…Many researchers have used the independent factor scores derived from multivariate technique of principal component factor analysis to soil and leaf litter properties [3,11,12]. The modelling component of leaf litter decomposition is widely reported in scientific literatures [13,14]. In Sub-Saharan Africa, there is dearth of information on the interrelationships among mass loss and litter chemistry traits of leaf litters using a multivariate approach.…”