Figure 2- - uploaded by Aaron Robert Weiskittel
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Comparison between average regional specific gravity and Miles and Smith (2009) reported specific gravity. Error bars are presented for the 95 percent confidence interval.
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Prediction of forest biomass and carbon is becoming important issues in the United States. However, estimating forest biomass and carbon is difficult and relies on empirically-derived regression equations. Based on recent findings from a national gap analysis and comprehensive assessment of the USDA Forest Service Forest Inventory and Analysis (USF...
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... was considerable regional variation in wood specific gravity for a given species and these values were generally significantly different than the value reported by Miles and Smith (2009) (Fig. 2). For example, mean specific gravity values for sugar maple (Acer saccharum Marsh.) ranged from 0.61 inches the northeast to 0.65 inches the north-central region, while Miles and Smith (2009) reports 0.56 ...
Citations
... A quantitative strategy that advances and extends the NLME approach and thus eliminates the need to obtain a set of parameters for each species (or species group) would be to consider each species as a random element of the stand mixture. The use of species as random effect has been used for a variety of growth and yield models including individual tree taper/volume (Weiskittel et al., 2015), biomass (Colmanetti et al., 2018), height (Lam et al., 2016), and height increment (Russell et al., 2014). The extension of this approach to ΔDBH is logical. ...
Tree diameter increment (ΔDBH) is a key component of a forest growth and yield model as predictions are passed to other submodels and tree-level estimates are scaled up to represent plot- and stand-level measures. A common problem faced in mixed-species stands is that ΔDBH needs to be characterized for numerous species, each with varying growth rates, shade tolerances, and competitive abilities. In addition, a variety of approaches have been used to model ΔDBH with unclear implications for general suitability for each species and overall prediction accuracy. This analysis used remeasurement data comprising 2,656,354 observations from 16,204 permanent sample plots across the Acadian Forest region of North America to develop and compare alternative approaches to estimating ΔDBH as well as stem basal area increment (ΔBA). Sixty-one species or genera including several with N < 10 were represented where observed mean growth rates ranged from 0 to 1.08 cm yr−1, depending on species. Analyzing several modeling approaches to project DBH of the 15 most abundant species using various evaluation statistics to quantify prediction performance, this study showed that i) modeling ΔDBH was generally superior compared to approaches that estimated ΔBA, ii) a two-stage modeling procedure predicting potential growth and a corresponding multiplicative modifier to derive ultimate increment was mostly inferior compared to strategies predicting realized ΔDBH or ΔBA in a unified model form, and iii) species-specific, realized increment models exhibited similar behavior and accuracy compared to models fitted with modeling species as random effect. These key findings became even more evident when projection lengths increased (≥ 30 years). Our study thus showed the efficiency and flexibility of diameter predictions by including tree species as a random effect to account for ΔDBH differences of trees in mixed-species stands, including infrequent species. However, curves for rare species derived with the mixed effects modeling approach still need to be evaluated for biological plausibility as unbalanced or biased data can lead to uncharacteristic and potentially illogical behavior. Overall, the study highlights the challenges of accurately predicting ΔDBH across a range of species and conditions, but offers a general framework for future analyses in mixed species forests.
... At the same time, the uncertainty can be controlled if a consistent set of models are developed and applied over time. Indeed, developing such a consistent set of models is a priority task of the US Forest Service Forest Inventory and Assessment (FIA) Program (Weiskittel et al. 2015a). ...
... Weiskittel et al. (2015b) outline a national effort to improve tree biomass estimates. Preliminary results from a new method, referred to as "CRM2," shows promise (Weiskittel et al. 2015a). However, based on recent discussions with our federal colleagues, the decision to revise the FIA methodology is 18 to 24 months away. ...
California has a pressing need to measure and manage forest carbon. Fusion of satellite-based data with plot-level information provides a promising means to measure forest biomass at relevant spatial and temporal scales. Key questions remain regarding accuracy and feasibility. Over a century of fire suppression complicates managing forest carbon in California's dry forests. Live tree biomass is at risk of loss due to wildfire. Here, we evaluated the performance of an emerging technology using Landsat imagery, forest inventory data, and gradient nearest neighbor imputation (referred to as LT-GNN) to measure annual aboveground live tree biomass (AGB) across multiple spatial scales. We also developed a means to quantify the trade-off between biomass storage and stability for fire-prone forests.
We relied on two independent estimates of AGB to evaluate LT-GNN results: local assessments calculated from field-data and airborne light detection, and county estimates calculated from Forest Inventory and Assessment plot results. We also used repeated measurements conducted in Forest Inventory and Analysis plots to quantify the ability of LT-GNN to detect trends in AGB. Finally, we extended a field experiment at Blodgett Forest Research Station in Georgetown, California to gain insights into biomass dynamics of fire-prone forests.
LT-GNN is a promising method to monitor live tree biomass. Its success at interpolating county-level tree biomass suggests an application-ready means to track annual biomass at a policy-relevant scale. However, improvements are needed to track change under stable conditions. At finer scales applications must be pursued with more caution. In particular, LT- GNN did not accurately predict AGB in an old-growth redwood forest. At Blodgett, we quantified the trade-off between biomass storage and stability. Fuel treatments did lower the overall biomass stored, but more biomass survived fire compared to the untreated forest. However, trade-off between biomass storage and stability critically depends on the probability of fire occurring in these stands.
... Recent work showed that depending on the region, FIA volume models may under-predict by as much as 19.2 percent ( Radtke et al. 2017). Preliminary efforts showed that a broad-scale multi- species taper model could 1) provide merchantable volume estimates on par with current regional volume models; 2) provide a unified, compatible framework across the eastern United States; and 3) allow for volume estimates to a flexible stump and top limit ( Weiskittel et al. 2016a). In this analysis, we expand our scope from the eastern United States to the entire United States. ...
... Five additional models were built dropping the lowest level in each subsequent model. The best performing model in terms of AIC was used to estimate stem diameter outside bark and converted to stem diameter inside bark using a simple bark thickness power function ( Weiskittel et al. 2016a). Section volumes were calculated using Smalian's formula on the taper-estimated and measured diameters and summed to provide taper-estimated and measured merchantable volumes. ...
Tree-level models used in large-scale inventories necessitate flexible modeling structures that can accommodate multiple species across varying sites and regions. Presently the United States Forest Service, Forest Inventory and Analysis Program (USFS-FIA) utilizes over 40 volume models of different forms specific to 22 geographic regions. Recently much of the data used to create these volume models has been compiled into a database including nearly 250,000 trees. This database provides the opportunity to formally assess tree-level variation in volume and taper among and within eco-physical regions and at varying taxonomic levels. In this analysis, we developed national-scale, non-linear, mixed effects outside bark taper and bark-thickness models to calculate merchantable volume in a consistent manner between regions and taxonomic groups. We assessed these models in terms of accuracy and precision and compared them to merchantable volume models currently used by FIA. The mixed effects taper-based approach performed well when compared to the conventional approach for estimating merchantable wood volume. Using a single, wide scale volume modeling system should lead to improved estimates of volume for some species particularly where little data is available.
