Evaluating alternative implementations of the Lake States FVS diameter increment model

Pokharel, Bharat; Froese, Robert E.

doi:10.1016/j.foreco.2007.11.035

Cited by 19 publications

(12 citation statements)

References 20 publications

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“…This tendency to underpredict was also seen in the model of dissolved SiO 2 by Jansen et al [2010]. This pattern of underprediction is also commonly seen in other applications of equivalence testing of slopes [e.g., Pokharel and Froese, 2008;Eitel et al, 2008], and we suspect it is at least partly caused by the regression process itself. We conclude that, although we have less confidence in our predictions at high levels, the majority of our predictions provide an unbiased estimate of background base flow stream chemistry.…”

Section: Model Limitationssupporting

confidence: 77%

Predicting natural base‐flow stream water chemistry in the western United States

Olson

Hawkins

2012

Water Resources Research

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[1] Robust predictions of stream solute concentrations expected under natural (reference) conditions would help establish more realistic water quality standards and improve stream ecological assessments. Models predicting solute concentrations from environmental factors would also help identify the relative importance of different factors that influence water chemistry. Although data are available describing the major factors controlling water chemistry (i.e., geology, climate, atmospheric deposition, soils, vegetation, topography), geologic maps do not adequately convey how rocks vary in their chemical and physical properties. We addressed this issue by associating rock chemical and physical properties with geological map units to produce continuous maps of percentages of CaO, MgO, S, uniaxial compressive strength, and hydraulic conductivity for western United States lithologies. We used catchment summaries of these geologic properties and other environmental factors to develop multiple linear regression (LR) and random forest (RF) models to predict base flow electrical conductivity (EC), acid neutralization capacity (ANC), Ca, Mg, and SO 4 . Models were derived from observations at 1414 reference-quality streams. RF models were superior to LR models, explaining 71% of the variance in EC, 61% in ANC, 92% in Ca, 58% in Mg, and 74% in SO 4 when assessed with independent observations. The root-mean-square error for predictions on validation sites were all <11% of the range of observed values. The relative importance of different environmental factors in predicting stream chemistry varied among models, but on average rock chemistry > temperature > precipitation > soil ¼ atmospheric deposition > vegetation > amount of rock/water contact > topography.Citation: Olson, J. R., and C. P. Hawkins (2012), Predicting natural base-flow stream water chemistry in the western United States,

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Section: Model Limitationssupporting

confidence: 77%

Predicting natural base‐flow stream water chemistry in the western United States

Olson

Hawkins

2012

Water Resources Research

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“…The observation that FVS-NE predictions did not exhibit an overtly spatial pattern (Figure 1) could signify that the geographic region for the model is appropriate for making these kinds of regional assessments. Results that tested the accuracy of ⌬dbh 5 predictions here generally agreed with those found for many of the same species in the Lake States implementation of FVS (Pokharel and Froese 2008): PA 15% values for the 20 species investigated were nearly all under 15% for ⌬dbh 5 , indicating poor performance for the large-tree ⌬dbh equation of FVS-NE. Results here showed FVS-NE to overpredict ⌬dbh 5 for both quaking aspen and black spruce, but Lacerte et al (2004) found general agreement between the observed and predicted ⌬dbh for the two species in Ontario at various projection lengths.…”

Section: Fvs-ne Benchmarkingsupporting

confidence: 71%

“…They conclude that improvements could be made in refining estimates of mortality (which ultimately influences stand density and, thus, BA) and site index (Lacerte et al 2004). By assessing the ⌬dbh function of FVS-LS, Pokharel and Froese (2008) found that it overpredicted ⌬dbh by 17% on average, and Canavan and Ramm (2000) observed similar results. These studies highlight the need for a careful examination of the individual-tree submodels within the existing FVS framework, as bias at the tree level can compound to the plot and stand levels.…”

mentioning

confidence: 89%

“…Researchers have observed various levels of success in updating equations and their predictions provided by the various submodels of FVS. In FVS-LS, recalibrating Holdaway's (1985) ⌬dbh AF did not lead to substantial improvements in ⌬dbh predictions for 30 species in Michigan (Pokharel and Froese 2008). Refitting submodels such as ⌬dbh and height increment (⌬ht) did, however, lead to considerable improvements in biological consistency over FVS-LS model predictions (Lacerte et al 2006).…”

mentioning

confidence: 90%

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Benchmarking and Calibration of Forest Vegetation Simulator Individual Tree Attribute Predictions Across the Northeastern United States

Russell¹,

Weiskittel²,

Kershaw³

2013

Northern Journal of Applied Forestry

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This study used permanent sample plot data from the USDA Forest Service's Forest Inventory and Analysis database to benchmark and calibrate three key submodels of the Forest Vegetation Simulator-Northeast variant (FVS-NE). Model predictions for total tree height (ht) and 5-year diameter (⌬dbh 5) and height increment (⌬ht 5) for the 20 most abundant species did not indicate any serious spatial trends. FVS-NE predictions for total ht performed moderately well, as mean bias averaged Ϫ0.9 Ϯ 5.2 ft (mean Ϯ SD) across all species. FVS-NE ⌬dbh 5 predictions fell within 15% of observed values between 8.4 and 17.3% of the time and performed best for shade-tolerant species and worst for intermediate shade intolerants. For ⌬ht 5 , the number of predictions that fell within 15% of observed values averaged 7.7%. Submodel performance generally improved after calibrating FVS-NE predictions using tree size, site, and climate variables. After employing a calibrated ⌬dbh 5 , 5-year basal area growth continued to be underpredicted across all ecoregions and forest types. Results indicate that (1) an assessment of overall model performance should be conducted if calibrated submodels are used and (2) alternative modeling strategies be explored to better represent the allometry and growth of the important trees species across the northeastern United States.

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“…In many such examples, red maple has been combined with other species (e.g., silver maple (Acer saccharinum L.)) for analysis (Lessard et al 2001). After evaluating individual-tree measurements across Michigan, Pokharel and Froese (2008) observed that current and adjusted models of red maple diameter increment were overpredicted by 8.0%-17.6%, suggesting that errors could be amplified when scaling to stand-level values such as basal area. In contrast, growth and yield models may underpredict diameter growth in stands with varied management histories (Kiernan et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Analysis of stand basal area development of thinned and unthinned Acer rubrum forests in the upper Great Lakes region, USA

et al. 2016

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Red maple (Acer rubrum L.), historically a common but not abundant tree species in North America, has increased in abundance throughout its range over the last several decades; however, it has received little attention in growth and yield studies. The objectives of this study were to (i) evaluate the effects of stocking level and stand density on overall patterns of red maple stand productivity and (ii) quantify these relationships across a wide range of stand age, site quality, geographic location, and climatic conditions. We used long-term measurements from 52 sites in Wisconsin and Michigan to examine growth responses of even-aged red maple stands to various levels of thinning. Using linear, mixed-effects modeling, future stand-level red maple basal area was modeled as a function of stand and plot characteristics and climatic variables. Growing season precipitation and its interaction with initial red maple basal area were significant predictors; however, they only collectively reduced the mean squared error by 2.1% relative to a base model containing solely stand and plot factors. Model projections indicated there was little difference in predicted future basal area for the range of climate conditions experienced by these stands highlighting red maple’s wide tolerance of environmental conditions across the region.

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Evaluating alternative implementations of the Lake States FVS diameter increment model

Cited by 19 publications

References 20 publications

Predicting natural base‐flow stream water chemistry in the western United States

Predicting natural base‐flow stream water chemistry in the western United States

Benchmarking and Calibration of Forest Vegetation Simulator Individual Tree Attribute Predictions Across the Northeastern United States

Analysis of stand basal area development of thinned and unthinned Acer rubrum forests in the upper Great Lakes region, USA

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