Deriving Biomass Models for Small-Diameter Loblolly Pine on the Crossett Experimental Forest

Foresters and landowners have a growing interest in carbon sequestration and cellulosic biofuels in southern pine forests, and hence need to be able to accurately predict them. To this end, we derived a set of aboveground biomass models using data from 62 small-diameter loblolly pines (Pinus taeda) sampled on the Crossett Experimental Forest in southeastern Arkansas. Of the 25 equations initially evaluated, we chose 17 that best fit our dataset and compared them using a suite of conventional test statistics, including pseudo-R2 , root mean squared error (RMSE), and bias. Because most of the 17 models varied little in pseudoR 2 (ranging between 0.96 and 0.99), bias (all were within ± 0.01), and RMSE, an additional comparison was done using Akaike’s Information Criterion corrected for small sample size (AICc). This test statistic produced considerably more discrimination between the biomass models. Of the 17 models evaluated, six produced ΔAICc scores that met or exceeded the threshold for substantial support. To recommend a single preferred model, we then extrapolated beyond our actual data and qualitatively compared model predictions with those from the National Biomass Estimator. Our “best” model did not have the minimum AICc score, but rather predicted logically consistent aboveground biomass values at both the upper and lower ends of our extrapolation

Serendipitous Data Following a Severe Windstorm in an Old-Growth Pine Stand

Reliable dimensional data for old-growth pine-dominated forests in the Gulf Coastal Plain of Arkansas are hard to find, but sometimes unfortunate circumstances provide good opportunities to acquire this information. On July 11, 2013, a severe thunderstorm with high winds struck the Levi Wilcoxon Demonstration Forest (LWDF) near Hamburg, Arkansas. This storm uprooted or snapped dozens of large pines and hardwoods and provided an opportunity to more closely inspect these rare specimens. For instance, the largest tree killed in this event, a loblolly pine (Pinus taeda), was 105 cm in diameter at breast height, 39.3 m tall, and if the tree had been sound would have yielded 3,803 board feet (Doyle log rule) of lumber. Gross board foot volume yield was also estimated from two other recently toppled large pines, an 85-cm-DBH loblolly and an 86-cm-DBH shortleaf pine (Pinus echinata), which tallied 2,430 and 2,312 board feet Doyle, respectively. A number of the other wind thrown pines on the LWDF were sound enough to count their rings for a reasonable (± 2-5 years) estimate of their ages. The stump of the fallen national champion shortleaf pine had 168 rings, and counts from other pines toppled by this storm had from 68 to 198 rings. We also searched for a new champion shortleaf pine using a LiDAR canopy height model of the LWDF to narrow our search. This preliminary assessment produced a number of targets that exceeded 40 m in height; further field checking of the tallest of these trees found that these were loblolly pines up to about 44 m. We eventually found shortleaf pines between 37 and 41 m tall, with diameters of up to 85 cm, indicating that the LWDF could still contain the Arkansas state champion

Comparing Aboveground Biomass Predictions for an Uneven-Aged Pine-Dominated Stand Using Local, Regional, and National Models

Sequestration by Arkansas forests removes carbon dioxide from the atmosphere, storing this carbon in biomass that fills a number of critical ecological and socioeconomic functions. We need a better understanding of the contribution of forests to the carbon cycle, including the accurate quantification of tree biomass. Models have long been developed to predict aboveground live tree biomass, but few of these have been derived from Arkansas forests. Since there is geographic variability in the growth and yield of pine as a function of genetics, site conditions, growth rate, stand stocking, and other factors, we decided to compare aboveground tree biomass estimates for a naturally regenerated, uneven-aged loblolly pine (Pinus taeda)-dominated stand on the Crossett Experimental Forest (CEF) in southeastern Arkansas. These predictions were made using a new locally derived biomass equation, five regional biomass equations, and the pine model from the National Biomass Estimators. With the local model as the baseline, considerable biomass variation appeared across a range of diameters—at the greatest diameter considered, the minimum value was only 69% of the maximum. Using a recent inventory from the CEF’s Good Farm Forty to compare each model, stand-level biomass estimates ranged from a low of 76.9 Mg/ha (a different Arkansas model) to as much as 96.1 Mg/ha (an Alabama model); the local CEF equation predicted 82.5 Mg/ha. A number of different factors contributed to this variability, including differences in model form and derivation procedures, geographic origins, and utilization standards. Regardless of the source of the departures, their magnitude suggests that care be used when making large-scale biomass estimates

Five Years of Change in an Old-Growth Pine-Hardwood Remnant in Ashley County, Arkansas

The Levi Wilcoxon Demonstration Forest near Hamburg, Arkansas is an industrially-owned remnant of old-growth pine and hardwoods. Some of the loblolly (Pinus taeda L.)and shortleaf (Pinus echinata Mill.)pine in this stand are over 200 years old, and numerous individuals exceed 90 cm in diameter and 30 m in height. A2000 survey of a portion of this tract found that 27 tree species contributed an average of387.5 live stems/ha and 31.8 m2 /ha of basal area. An inventory of the same plots in2006 yielded noticeable declines in density (now down to 342.5 stems/ha) and basal area (now 28.2 m2 /ha). Much of this loss came in the aftermath of a windstorm in May 2003, which felled a number of overstory pines. Loblolly pine decreased from 49.6 stems/ha and 13.2 m2 /ha in2000 to 42.1 trees/ha and 11.2 m 2 /ha in2006, while shortleaf pine declined from 21.7 trees/ha and 5.0 m2 /ha to 14.6 trees/ha and 3.5 m 2 /ha. Further pine mortality came from smaller-scale windthrow, lightning, and bark beetle infestations. Some hardwoods were also toppled by storms or crushed by falling trees, but most appear to have succumbed to drought, competition, and salvage logging. However, hardwood basal area remained virtually unchanged over this period, signifying adequate diameter growth and midstory recruitment. In particular, shade-tolerant hardwood species showed notable gains. Even though most overstory pines currently appear healthy, natural catastrophes and the lack of new canopy recruits may eradicate virtually all pines from this stand within 30 to 50 years

Checklist of Major Plant Species in Ashley County, Arkansas Noted by General Land Office Surveyors

The original General Land Office (GLO) survey notes for the Ashley County, Arkansas, area were examined to determine the plant taxa mentioned during the 1818 to 1855 surveys. While some challenges in identifying species were encountered, at least 39 families and approximately 100 species were identified with reasonable certainty. Most references were for trees used to witness corners or lines. Prominent arboreal genera recorded in these early survey records included Quercus, Pinus, Carya, Liquidambar, Nyssa, Ulmus, Acer, Fraxinus, and Taxodium. A number of shrubs, vines, graminoids, and herbaceous species were also reported, including notable genera like Vaccinium, Lindera, Crataegus, Myrica, Rubus, Smilax, Vitis, Arundinaria, and Bidens. Even though very few GLO surveyors had formal training in plant identification, their familiarity with local and regional floras (undoubtedly supplemented by their field crew\u27s knowledge) contributed to the relative accuracy of the effort. Taxonomic discrepancies (e.g., shifting species names, delineation of new taxa since the survey was completed, obscure common names) have obscured a number of identifications in this study. Nevertheless, the GLO records are a valuable and systematic (statewide) source of information from a period of time that predates most formal botanical investigations

Comparison of Pine Height Models for the Crossett Experimental Forest

Many models to predict tree height from diameter have been developed, but not all are equally useful. This study compared a set of height-diameter models for loblolly (Pinus taeda) and shortleaf (Pinus echinata) pines from Ashley County, Arkansas. Almost 560 trees ranging in diameter at breast height (DBH) from 0.3 cm (both species) to 91.9 cm (for shortleaf) or 108.2 cm (for loblolly) were chosen for measurement. Height equations were then fit to four different functions (Chapman-Richards, modified logistic, exponential, and Curtis-Arney) with weighted nonlinear least squares regression using DBH as the only predictor. Models were evaluated using a series of goodness-of-fit measures, including fit index (R 2 ), root mean square error (RMSE), bias, and corrected Akaike information criterion (AICc). All of the models fit the data very well, with 96 to 98% of the variation explained for loblolly pine, and 96 to 97% explained for shortleaf pine. Similarly, few differences were apparent in RMSE, bias, and AICc, although it was clear that the Curtis-Arney function fit both pine species slightly less well across the upper range of the diameters. Only subtle differences appeared in curve shape for small- to moderate-sized pines, with increasing departures predicted above 75 cm DBH. Given their overall similarity in performance, the modified logistic function was the preferred height diameter model because of its more intuitive allometry at the upper extreme of pine size, especially when compared to the original FVS height dubbing equation. A unified height-diameter model capable of predicting total tree height for either pine taxa was also developed with a modified logistic function

Stand Conditions Immediately following a Restoration Harvest in an Old-growth Pine-hardwood Remnant

Portions of the Levi Wilcoxon Demonstration Forest (LWDF), a privately owned parcel of old growth pine and hardwoods in Ashley County, Arkansas, were recently treated to restore conditions similar to some historic accounts of the virgin forest. Following a hardwood-only cut, a post-harvest inventory showed that the number of tree species in the sample area declined from 24 in 2006 (the most recent pre-harvest inventory) to 12 in 2009. Loblolly (Pinus taeda L.) and shortleaf (Pinus echinata Mill.) pine now comprise 59.2% of the remaining live trees, up from 16.2% in 2006. Between 2006 and 2009, basal area dropped from 28.2 to 16.4 m2 /ha and stem density declined from 349.2 to 72.4 stems/ha, respectively. Total live biomass also fell from 224.8 Mg/ha in 2006 to 130.1 Mg/ha in 2009. While most of the pines in the LWDF are between 100 and 200 years old, ring counts on 102 randomly selected hardwood stumps yielded only one greater than 100 years old. Two-thirds of these hardwoods were less than 70 years old, having originated after the stand was set aside by the Crossett Lumber Company. Historical documentation and recent research suggest that the LWDF is now more similar to presettlement pine-dominated forests of southern Arkansas, which generally had lower stocking and fewer hardwoods

Modeling Loblolly Pine Aboveground Live Biomass in a Mature Pine-hardwood Stand: A Cautionary Tale

Carbon sequestration in forests is a growing area of interest for researchers and land managers. Calculating the quantity of carbon stored in forest biomass seems to be a straightforward task, but it is highly dependent on the function(s) used to construct the stand. For instance, there are a number of possible equations to predict aboveground live biomass for loblolly pine (Pinus taeda) growing in southeastern Arkansas. Depending on stem diameter at breast height (DBH), biomass varied considerably between four different prediction systems for loblolly pine. According to the tested models, individual tree oven-dry biomass for a 50 cm DBH loblolly pine ranged between 1,085 kg and 1,491 kg. Beyond this point, departures between these models became increasingly pronounced, with one even projecting an irrational decline to negative biomass for trees \u3e 138.7 cm DBH, while the others varied between 12,447 and 15,204 kg. Although some deviation is not surprising given the inherent differences in model form and three of the models were extrapolations across much of this diameter range, the difference between the extremes was unexpected. Such disparities significantly impact stand-level (cumulative) predictions of biomass in forests dominated by large-diameter individuals, as demonstrated for an existing stand (Hyatt’s Woods) in Drew County, Arkansas. Differences between these models caused loblolly pine aboveground live-tree biomass estimations in Hyatt’s Woods to vary by almost 34,000 kg/ha