a hybrid model for intensively managed douglas-ﬁr...

ORIGINAL PAPER

A hybrid model for intensively managed Douglas-fir plantationsin the Pacific Northwest, USA

Aaron R. Weiskittel • Douglas A. Maguire •

Robert A. Monserud • Gregory P. Johnson

Received: 6 July 2009 / Revised: 28 October 2009 / Accepted: 30 November 2009 / Published online: 30 December 2009

� Springer-Verlag 2009

Abstract Recent advances in traditional forest growth

models have been achieved by linking growth predictions

to key ecophysiological processes in a hybrid approach that

combines the strengths of both empirical and process-based

models. A hybrid model was constructed for intensively

managed Douglas-fir plantations in the Pacific Northwest,

USA, by embedding components representing fundamental

physiological processes and detailed tree allometrics into

an empirical growth model for projecting individual tree

and stand development. The simulated processes operated

at a variety of scales ranging from individual branches to

trees and stands. The canopy structure submodel improved

predictions of leaf area index at the stand level when

compared to allometric and other empirical approaches

(reducing mean square error by 30–42%). In addition, the

hybrid model achieved accuracy in short-term volume

growth prediction comparable to an empirical model.

Biases in 4-year stand growth predictions from the hybrid

model were similar to those from the empirical model

under thinning, fertilization, and the combination of these

treatments; however, volume growth predictions in

unmanaged plantations averaged approximately 36% less

bias. These improvements were attributed to detailed

information on crown structure (i.e. size, location, and

foliage mass of primary branches), simple representation of

key physiological processes, and improved site character-

ization. Soil moisture, temperature, and nitrogen mineral-

ization predicted by the hybrid model also agreed closely

with observed values from several previous studies.

Overall, the model framework will be helpful for future

analyses as it can lend insight into the influence of weather

and site edaphic factors on growth, help identify mecha-

nisms of response to silvicultural treatments, and facilitate

the design of sound management regimes for Douglas-fir

plantations across the Pacific Northwest region.

Keywords Hybrid model � Thinning � Fertilization �Growth and yield � Oregon �Washington � Leaf area index �Soil temperature � Soil moisture � Soil nitrogen

mineralization � Net primary production

Introduction

The effects of intensive management on tree growth and

stand yield are difficult to quantify empirically because

natural variability necessitates extensive replication of

silvicultural treatments across the full range of sites. Many

years must also pass before growth trajectories and impli-

cations for final yields become evident. Empirical growth

and yield models have been very effective for summarizing

Communicated by Uta Berger.

Electronic supplementary material The online version of thisarticle (doi:10.1007/s10342-009-0339-6) contains supplementarymaterial, which is available to authorized users.

A. R. Weiskittel (&)

School of Forest Resources, The University of Maine, Orono,

ME 04469, USA

e-mail: [email protected]

D. A. Maguire

Department of Forest Engineering, Resources & Management,

Oregon State University, Corvallis, OR 97331, USA

R. A. Monserud

PNW Research Station (retired), USDA Forest Service,

620 SW Main, Suite 400, Portland, OR 97205, USA

G. P. Johnson

Weyerhaeuser Company, P.O. Box 9777, Federal Way,

WA 98063, USA

123

Eur J Forest Res (2010) 129:325–338

DOI 10.1007/s10342-009-0339-6

http://dx.doi.org/10.1007/s10342-009-0339-6

large amounts of data from silvicultural trials or opera-

tional inventories in a way that allows the user to explore

the consequences of alternative treatments and regimes

through simulation (Pretzsch et al. 2006). However,

empirical models are more or less limited to the range of

conditions represented in available data and generally

consider site quality invariant. For this reason, they are

inappropriate for addressing many questions facing forest

managers currently, such as growth responses to changes in

water availability imposed by new cultural techniques,

likely effects of climate change, or potential growth

declines from depletion of soil nutrients under repeated

harvesting.

Models based on fundamental ecophysiological pro-

cesses have found increasing application in designing

optimal forest management regimes (Makela et al. 2000).

These models offer the advantage of simulating growth

responses to silvicultural treatments by incorporating key

ecophysiological mechanisms driving growth, and thereby

potentially yielding more robust extrapolations to untested

conditions and management regimes. However, a strong

theoretical basis does not currently exist for predicting all

aspects of tree growth from fundamental principles, and

proper parameterization for most process models is a dif-

ficult task because they often have multiple parameters,

extensive physiological data are not available for all spe-

cies, and the information necessary to initialize the models

is expensive to collect. The hybridization of empirical and

process-based models offers some promise for producing

models that draw on the strengths, and exceed the capa-

bilities, of both approaches (Landsberg 2003). However,

hybrid models have received less attention in some regions

because they have not achieved sufficient reliability or

flexibility as management tools (Pretzsch et al. 2008).

Hybrid models have been shown to improve stand-level

growth predictions in some cases relative to strictly

empirical models (Woollons et al. 1997; Snowdon 2001;

Pinjuv et al. 2006). However, the level of improvement has

varied significantly, in part because the breadth of condi-

tions covered by evaluation data relative to the modeling

data varies tremendously. Snowdon (2001) found a 23%

improvement for predicting Pinus radiata basal area

growth, while Pinjuv et al. (2006) reported only a 4%

improvement for the same species. Stand growth has gen-

erally been the metric for verifying hybrid model predic-

tions, but a more thorough evaluation of hybrid models

would include assessment of component mechanisms, for

example, by comparison of predicted and observed leaf

area index (LAI), soil moisture, and nutrient availability.

Although hybrid models generally reduce the number of

necessary parameters in comparison with purely process-

based models, the cost of requiring fewer parameters

results in some loss in site specificity. Hybrid models often

require attributes such as LAI and stand biomass compo-

nents that must be estimated from other tree dimensions

routinely measured in forest inventories or silvicultural

research trials. Consequently, these models usually involve

the use of regional allometric equations, despite recogni-

tion that they can be significantly biased when applied to

stands managed under widely varying intensities (e.g. Grier

et al. 1984). An effective hybrid model must therefore

account for silvicultural effects on allometric relationships

and the implications for related physiological processes.

The primary goal of this research project was to develop

a hybrid model for intensively managed Douglas-fir stands

and to test its performance against several long-term sil-

vicultural research trials in the northwestern United States

(hereafter referred to as the Pacific Northwest, or PNW).

The challenge was to identify those process features that

appear robust among widely differing biomes, while

adapting or adding others that seem uniquely important for

predicting the growth of Douglas-fir in intensively man-

aged PNW plantations. Output was required to include the

quantity and quality of wood at both the stand and indi-

vidual-tree levels as this information is required by forest

managers. Of particular interest was the strong control on

productivity exerted by moisture availability in the PNW,

and known structural relationships between wood quality

and responses of crown size, branching structure, and foliar

mass to silvicultural treatments (Maguire et al. 1991). This

paper describes the resulting model architecture and its

performance in simulating growth and several key pro-

cesses influencing site resource availability. Specific

objectives were to: (1) develop and assess an approach for

estimating biomass components and LAI that makes use of

branch-level detail needed for simulating silvicultural

effects on wood quality; (2) compare alternative approa-

ches for modeling key ecophysiological processes; (3) test

stand-level performance of the hybrid model across a wide

range of intensively managed plantations relative to an

empirical model developed in parallel, and (4) validate

simulations of daily soil temperature, soil moisture, and

nitrogen mineralization. Although the model was designed

to be applicable to Douglas-fir in all regions, the most

appropriate use of the model is in the PNW region of USA,

particularly in areas west of the Cascades Mountain region.

Methods

Model development

The model architecture emphasized a hierarchy of multiple

processes, with some predictions made at the branch level,

some at the tree level, and others at the stand level. The

desired temporal scale for growth predictions was annual,

326 Eur J Forest Res (2010) 129:325–338

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but some key processes depended on diurnal cycles of

resource availability and tree physiology. The architecture

of DF.HGS (Douglas-fir Hybrid Growth System) was

intended to take advantage of the current state of knowl-

edge at each scale appropriate for representing inherent site

productivity and simulating response to silvicultural treat-

ment. It also needed the flexibility to accommodate future

modifications as better physiological and morphological

data, parameters, and submodels become available. Three

primary components comprise DF.HGS, one to character-

ize branch, crown, and canopy structure (BCACS), one to

estimate annual net primary production (NPP), and one to

allocate carbon and growth to different stand and tree

compartments (ALOGRO) (Fig. 1).

Branch, crown, and canopy simulator

Branch, crown, and canopy simulator (BCACS) contains a

set of empirical equations that predict the location, diam-

eter, and biomass of every branch for each tree measured

on a sample plot. Model input includes stand age and site

index and the following attributes for each tree: diameter at

breast height (DBH), total height (HT), height to crown

base (HCB; lowest live branch), and expansion factor

(EXPF, in trees per ha). The inputted site index is only used

to reconstruct past height growth to determine the location

of annual whorls of branches and the overall model is

relatively insensitive to it. Branch diameter, length, and

angle are predicted from basic tree dimensions using the

equations developed by Weiskittel et al. (2007b). Branch

location within an annual segment of the bole was assumed

to follow the empirical distribution described by Maguire

et al. (1994). Woody biomass, foliage biomass by age

class, and projected foliage area by age class of all bran-

ches were predicted from basal diameter and relative height

in the crown (Weiskittel et al. 2006). Woody surface area

(all-sided) of all branches was estimated at the tree level

from DBH, crown length, crown ratio, and sapwood area

(Weiskittel and Maguire 2006). These attributes were then

summed to estimate biomass and surface area at the tree-

and stand-levels.

Total stem and sapwood volume were estimated at the

tree-level from existing stem volume (Walters et al. 1985)

and sapwood taper equations (Maguire and Batista 1996).

Stem volumes were converted to biomass by applying

regional values for total and sapwood density (500 and

455 kg m-3, respectively). Belowground biomass at the

stand level was estimated from total aboveground biomass

(Ranger and Gelhaye 2001). Crown projection areas were

calculated from individual-tree crown widths computed

from branch lengths and angles, and these areas were then

summed and corrected for overlap to determine percent

canopy cover using the approach of Crookston and Stage

(1999).

Fig. 1 Components and flow of

the simulation model DF.HGS

for Douglas-fir in the Pacific

Northwest

Eur J Forest Res (2010) 129:325–338 327

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Net primary production

Previous reviews of process-based models and their com-

ponents (Schwalm and Ek 2001; Landsberg 2003) have

suggested a common list of attributes that future models

should possess to accurately capture the effects of silvi-

cultural treatments and climate on NPP. These attributes

include: (1) daily time-step; (2) separation of direct and

diffuse radiation; (3) light extinction coefficients dependent

on solar geometry, canopy structure, and type of radiation;

(4) separation of sunlit and shaded leaf area; (5) photo-

synthesis estimates based on the Farquhar et al. (1980)

biochemical equation, (6) modification of diurnal distri-

bution of radiation and fraction of sunlit leaf area by slope

and aspect, particularly in areas with complex terrain; (7)

estimates of stomatal conductance that are sensitive to

vapor pressure deficit and soil water availability; and (8)

canopy gas exchange linked to soil water and nutrient

availability.

All of these desired attributes were incorporated into the

NPP submodel. Inputs were kept as simple as possible to

capture the fundamental processes (Table 1), so included:

(1) daily weather data (precipitation, temperature, relative

humidity, solar radiation) obtained from DAYMET (http://

www.daymet.org); (2) site physiographic features (eleva-

tion, slope, aspect); (3) stand structural attributes from

BCACS (Table 2); (4) basic soils information (rooting

depth, texture, rock content), (5) foliar nitrogen concen-

tration; and (6) physiological parameters obtained from the

literature (Appendix 1 in supplementary material). The

model runs on a daily time-step but estimates gross primary

production (GPP) five times daily based on Gaussian

integration. The development of the current-year foliage

was assumed to occur linearly for 30 days following bud

burst, with date of bud burst predicted from growing degree

days. Annual foliage litterfall and its seasonal distribution

were predicted from stand density, age, foliage retention,

crown density, slope and aspect (Weiskittel and Maguire

Table 1 Input variables

required to run Douglas-fir

hybrid growth system

(DF.HGS) for intensively

managed Douglas-fir plantations

Variable Units Definition

Tree

DBH cm Diameter at breast height (1.3 m)

HT m Total height

HCB m Height to crown base

EXPF Trees ha-1 Expansion factor

Site

SI m Site index; expected height of dominant trees

at 50 years breast height age (Bruce 1981)

SLOPE % Topographic slope

ASPECT Degrees Topographic aspect

ELEV m Elevation

Soil

SOIL_CLAY % Soil clay content by weight

SOIL_SILT % Soil silt content by weight

SOIL_SAND % Soil sand content by weight

SOIL_C % Soil carbon content by weight

SOIL_DEP m Soil root depth

SOIL_ROCK % Rock content by volume

Weather

Tmax �C Daily maximum air temperature

Tmin �C Daily minimum air temperature

Tmean �C Daily average air temperature

PRCP mm Daily total precipitation

VPD Pa Daily average vapor pressure deficit

SW.RADday W m-2 Daily shortwave solar radiation

DAYLEN Hours Day length

Geographic

LAT Degrees Latitude (to the nearest hundredths)

LONG Degrees Longitude (to the nearest hundredths)

328 Eur J Forest Res (2010) 129:325–338

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http://www.daymet.org

http://www.daymet.org

2007). Details of NPP components follow and are also

described further in Appendix 2 in supplementary material.

Light interception Although highly detailed light inter-

ception models have been developed, they still remain

quite computer intensive and too complex for application

in management-oriented hybrid models. Estimating light

interception for an individual-tree crown based on canopy-

level principles does not fully account for the competitive

position of the tree within the stand. These limitations lead

to light interception being estimated by applying the Beer–

Lambert law after accounting for the effects of incomplete

canopy closure on the sunlit and shaded portions of the

canopy. Mean daily radiation was separated into direct and

diffuse components following the approach outlined by

Bristow and Campbell (1985), which is based on the ratio

of actual incoming shortwave radiation to potential short-

wave radiation. The amount of direct and diffuse radiation

at a given time of the day was estimated from cosine-

diurnal distribution following the procedure outlined by

Wang et al. (2002), in contrast to the more common

approach of assuming a sinusoidal pattern to diurnal radi-

ation. Light extinction coefficients for direct and diffuse

radiation were based on the relationships described by

Smith (1993) and Campbell and Norman (1998), respec-

tively. The direct radiation extinction coefficient was a

function of solar zenith angle, LAI, and stand relative

density, while the diffuse radiation extinction coefficient

was simply a linear function of LAI. Clumpiness was

accounted for by an equation presented in Kucharik et al.

(1999) that included the ratio of stand mean crown depth to

crown diameter and the solar zenith angle. The effects of

slope and aspect on the amount of incoming radiation were

assumed to be sufficiently accounted for by DAYMET.

Photosynthesis Net photosynthetic rates were estimated

with the Farquhar et al. (1980) model for both sunlit

(foliage receiving direct, diffuse, and scattered radiation)

and shaded (foliage receiving only diffuse and scattered

radiation) current-year foliage. Maximum Rubisco activity

(Vcmax), electron transport capacity (Jmax), and dark respi-

ration rate (Rdark) were estimated from their relationship to

mean canopy foliar nitrogen concentrations (Manter et al.

2005). These rates were assumed to be the same for both

sunlit and shaded foliage. Temperature modifiers for Vcmax

and Jmax were obtained from Manter et al. (2003). Other

standard parameters such as CO2 compensation point in the

absence of mitochondrial respiration and the Michaelis–

Menten constant of Rubisco were estimated from equations

given by Schwalm and Ek (2004).

To account for the effects of complex terrain on canopy

photosynthesis, the canopy was split into sunlit and shaded

leaf area based on total leaf area, slope and aspect of the

site, and solar azimuth and zenith angle (Wang et al. 2002).

Foliage age structure is also known to influence total

photosynthesis in conifer canopies, but actual Vcmax, Jmax,

and Rdark measurements for age classes older than the

current year were not available. Therefore, the net photo-

synthetic rates for the 1-, 2-, 3-, and C4-year-old foliage

age classes were assumed to be 75, 50, 30, and 10%,

respectively, of the net photosynthetic rates of current year

foliage calculated from the Farquhar et al. (1980) equation

and were inferred from information available in the liter-

ature (Ethier et al. 2006). The estimated net photosynthesis

rate for sunlit and shaded foliage was multiplied by the

amount of leaf area in each class to obtain an estimate of

stand-level GPP.

Water stress effects on canopy photosynthesis are par-

ticularly important in the PNW because of high evaporative

demand during the warm, dry summer. In a recent review

of models for simulating the effect of water stress on

canopy photosynthesis, Grant et al. (2006) found approa-

ches ranging from simple scaling factors to complex iter-

ative solutions. Proper model behavior requires the

Table 2 Stand attributes generated by submodel branch, canopy, and crown simulator (BCACS) and passed to submodel net primary production

(NPP) as the basis for estimating growth on the 67 Stand Management Cooperative plots of intensively managed Douglas-fir

Attribute Mean Standard deviation Minimum Maximum

Leaf area index (m2 m-2) 4.14 2.08 0.87 9.10

Stand-level belowground biomass (kg ha-1) 13.53 7.79 2.46 33.68

Stand-level aboveground biomass (kg ha-1) 104.72 60.37 21.04 276.33

Branch area index (m2 m-2) 0.35 0.16 0.09 0.70

Canopy cover (%) 0.89 0.11 0.54 0.99

% of leaf area in age class 1 0.28 0.008 0.25 0.30




% of leaf area in age class 5? 0.09 0.005 0.07 0.10

Eur J Forest Res (2010) 129:325–338 329

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interactive effects of soil and atmospheric water deficits on

CO2 fixation (Grant et al. 2006). The simplest approach

was to predict stomatal conductance from both soil and

atmospheric water deficits with the equation developed by

Bond and Kavanagh (1999). Stomatal conductance was

also modified by the amount of intercepted radiation and

time since sunrise. Intercellular CO2 concentration was

then estimated from the model presented in Katul et al.

(2000) with the critical stomatal conductance set at

50 lmol m-2 s-1, and the maximum ratio of ambient to

intercellular CO2 was 0.66. One limitation of this approach

is the assumption that water deficit effects on CO2 fixation

are entirely stomatal, which is not entirely true. However, a

better understanding of the relationship between stomatal

conductance and leaf internal transfer conductance, and the

response of both to environment conditions, is required

before they can be better integrated into models (Warren

and Adams 2006).

Respiration One key simplification in the hybrid model

3-PG (Landsberg and Waring 1997) is the assumption that

NPP is a constant fraction of GPP (*0.5; Waring et al.

1998). This assumption has generated considerable debate

in the literature (e.g. Medlyn and Dewar 1999), but results

of several studies have supported the generality of this

NPP/GPP fraction across a wide range of forest types (e.g.

Litton et al. 2007). Three alternatives to this simplification

were also tested, including: (1) daily respiration as a

function of biomass and temperature (Schwalm and Ek

2004); (2) daily respiration as a function of nitrogen con-

tent and both a short- and long-term response to tempera-

ture (Kirschbaum 1999); and (3) annual respiration as a

function of nitrogen content and temperature (Battaglia

et al. 2004). However, estimating NPP as a constant frac-

tion of GPP yielded the strongest correlation with observed

stem volume growth and was therefore the approach taken

in DF.HGS.

Soil water and nutrients Daily soil water balance was

simulated in a manner similar to that described by Sch-

walm and Ek (2004). Soil water holding capacity was

estimated from rooting depth, texture, and rock content

using equations and data available in the literature (Saxton

and Rawls 2006). Daily canopy transpiration and soil

evaporation were simulated with an approach outlined by

Watt et al. (2003). In the canopy transpiration equation,

mean daily stomatal conductance was estimated from leaf

and soil water potential, leaf to air vapor pressure gradient,

and leaf specific conductance (Bond and Kavanagh 1999).

Daily soil water balance was determined by subtracting

canopy transpiration and soil evaporation from soil water

and adding daily net precipitation after subtracting inter-

ception by canopy leaf and branch surface area. The

amount of intercepted precipitation was based on empirical

rainfall attenuation in Douglas-fir stands (Keim 2004).

Although fog is an important source of moisture in some

ecosystems (Dawson 1998), prediction of its occurrence is

very difficult and it also commonly only occurs on a very

narrow belt along the Pacific Coast, so it was not directly

incorporated in the model.

For simplicity, daily nitrogen mineralization was the

only aspect of nutrient availability that was simulated in

the model. Driving variables included soil temperature,

water content, texture, bulk density, and water holding

capacity, as well as daily air temperature, rainfall, and solar

radiation (Paul et al. 2002). The mass and height of the

litter layer, the stand leaf area index, and site slope must

also be known or estimated. Simulation of daily nitrogen

mineralization is achieved by considering the influence of

all these factors on the optimum nitrogen mineralization

rate estimated from published data (Chappell et al. 1999).

Daily soil temperature was calculated from air temperature

as modified by the effects of the tree canopy, understory

vegetation, litter mass, and depth of soil layer (Paul et al.

2004). Daily nitrogen uptake was estimated as a function of

fine root biomass, root nitrogen concentration, soil tem-

perature, and the amount of available soil nitrogen

(Thornley 1991).

Allocation and growth (ALOGRO)

Allocation Several reviews on carbon allocation have

outlined the range of approaches to quantifying the sources

of its variability. However, no single solution is yet widely

accepted (Lacointe 2000). The 3-PG approach of empirical

allometric ratios (Landsberg and Waring 1997) is robust

and provides realistic values, but for many if not most

species these ratios are based on empirical relationships in

unmanaged stands. Similarly, Makela (1997) maintained a

constant ratio of foliage to fine root biomass to reflect an

expected functional balance between the two, regardless of

growing conditions. Carbon allocation, however, is highly

sensitive to intensive management, as well as to inherent

site resource availability, particularly belowground. Allo-

cation conditional on site resource availability was, there-

fore, initially built into the model. A variety of approaches

were examined, including those of Running and Gower

(1991), Johnson and Thornley (1987), Kirschbaum (1999),

and Landsberg and Waring (1997). Preliminary analysis,

however, suggested that a modified 3-PG approach resulted

in the highest correlation between simulated above-ground

NPP and observed stem volume growth. The modifications

to the 3-PG allocation approach involved estimation of the

site fertility rating from canopy N percentage, similar to

Swenson et al. (2005), and applying a correction for

inherent bias when estimating stand-level biomass (or its

330 Eur J Forest Res (2010) 129:325–338

123

allocation in this case) from stand-level mean tree size

(Duursma and Robinson 2003).

Leaf area index

Data from 14 Stand Management Cooperative (SMC;

University of Washington) installations in Oregon and

Washington, USA, comprised the dataset for validating

estimates of stand LAI (Maguire and Bennett 1996). The

installations covered a range of stand ages and site indices.

At each installation, 5–12 plots with varying silvicultural

treatment regimes (e.g. thinning intensities, fertilization)

were sampled. Multiple trees per plot were destructively

sampled and used to construct plot-specific tree leaf area

equations (Maguire and Bennett 1996). The mean LAI in

the verification dataset was 5.12 ± 3.23 (mean ± standard

deviation) with a range between 0.33 and 13.25.

LAI was estimated with BCACS and three other meth-

ods, including application of: (1) an allometric function of

DBH (Gholz et al. 1979); (2) a constant ratio of leaf area to

predicted sapwood area at crown base estimated with the

equation of Maguire and Batista (1996) (0.58 m2 cm-1;

CBSAP); and (3) an empirical function of crown length,

DBH, and height (Maguire and Bennett 1996).

Growth

Growth data from nine SMC installations in Oregon and

Washington, USA, comprised the dataset for verification of

growth (Table 3). Twenty-year mean annual rainfall for

these locations ranged from 150 to 315 cm, and January

mean minimum and July mean maximum temperatures

ranged from -2.2 to 3.5�C and 21.3 to 26.3�C, respec-

tively. Elevation ranged from 25 to 300 m above sea level

and all aspects were represented. Soils varied from a

moderately deep sandy loam to a very deep clay loam. The

plantations were established between 1971 and 1982 at a

range in tree density (905–1,575 stems per ha) and under

varying levels of vegetation control.

A set of 0.2-ha permanent plots was established by the

SMC at each installation between 1986 and 1992. Since

establishment, the 67 plots have received a variety of sil-

vicultural regimes that have involved thinning (n = 21),

nitrogen fertilization (224 kg ha-1 of urea every 4 years;

Table 3 Attributes of research plots in Oregon and Washington simulated during verification of Douglas-fir hybrid growth system (DF.HGS)

Attribute Mean Standard deviation Minimum Maximum

Leaf area index (nplot = 36)

Basal area (m2 ha-1) 37.9 15.4 10.5 76.8

Stems per ha 663.3 372.7 175.0 1,790.0

Total age (yrs) 28.8 13.9 11.0 61.0

Site index (m at 50 yrs) 39.4 4.2 26.6 46.2

Soil water holding capacity (mm) 175.2 40.2 105.2 301.5

Volume growth (nplot = 67)

Basal area (m2 ha-1) 16.5 8.8 3.3 40.5

Stems per ha 720.7 452.2 242.2 1,818.7

Total age (yrs) 17.3 3.7 12.0 24.0



Soil temperature and moisture (nplot = 1, measured 3 different years)

Mean seedling stem diameter (mm) 17.9 0.9 2.0 34.0

Mean seedling stem height (cm) 93.4 5.2 17.0 158

Total age (yrs) 2.0 1.0 1.0 3.0

Site index (m at 50 yrs) 42.0a – – –

Soil water holding capacity (mm) 527.3 – – –

Soil nitrogen mineralization (nplot = 10)

Basal area (m2 ha-1) 27.8 8.8 11.6 40.0

Stems per ha 616.3 233.8 382.9 1,112.0

Total age (yrs) 22.1 3.0 16.0 27.0



a Determined from the previous stand

Eur J Forest Res (2010) 129:325–338 331

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n = 9), and a combination of thinning and fertilization

(n = 22) with the remaining plots serving as controls

(n = 15). Canopy mean plot foliage N concentration ran-

ged from 1.26 to 2.98%. All trees on each plot were

remeasured for DBH every 4 years at the end of the

growing season, and at each remeasurement a subsample of

at least 40 Douglas-fir trees was also measured for total

height and height to crown base. Four to eight years after

plot establishment, current-year foliage was sampled from

the upper crown of 12 trees in each plot, and analyzed for

nutrient content. Climate information for the growth peri-

ods represented on the SMC plots was obtained from

DAYMET.

LAI and growth were simulated with DF.HGS (BCACS,

NPP, and ALOGRO) on each of the 67 SMC plots. The

same plots were also simulated with an empirical growth

and yield model assembled from individual-tree diameter

and height growth equations that project on an annual cycle

(Weiskittel et al. 2007a). Relative performance of the

models was assessed by comparing predicted 4-year

growth to observed growth.

Soil temperature and moisture

Soil temperature and moisture on a set of plots at the Fall

River Long-Term Site Productivity study in coastal

Washington (Ares et al. 2007) were predicted from the

NPP portion of DF.HGS. The site is located approximately

56 km from the Pacific Ocean, has a mean elevation of

330 m, and receives an average of 226 cm of annual pre-

cipitation. The soil at Fall River is deep, well-drained,

mostly stone-free silty clay loam that has a low bulk den-

sity and high organic carbon content. The site is highly

productive with a site index of 41–43 m at base age 50. In

1999, the site was harvested and planted with Douglas-fir,

and various tree and soil responses have been intensively

monitored. Soil temperature and volumetric moisture

content were measured daily at multiple depths with

HOBO H8 data loggers and hydrosense CS620 moisture

probe, respectively. The daily mean measurements at

10 cm in the bole-only harvest with complete vegetation

control treatment were utilized for verification in this

analysis. Actual daily climate and stand biomass data from

Fall River were input to DF.HGS to drive the predictions.

Soil nitrogen mineralization

Simulation of annual soil nitrogen mineralization was

verified against data collected by Sinkhorn (2007) from ten

approximately 30-year old plantations in the northern

Oregon Coast Range. All the sites were located within

25 km of the Pacific Ocean and had soils derived from

sedimentary parent material. The sites covered a range of

Swiss needle cast (SNC) severity with mean ocular foliage

retention rating ranging from 1.4 (very severe SNC) to 4.1

(low SNC). The sites were specifically chosen to represent

a gradient in soil nitrogen ranging from 9.2 to

28.7 Mg N ha-1 (Sinkhorn 2007). In 2003, net minerali-

zation and nitrification rates in the top 10 cm of mineral

soil were assessed monthly with six buried bags per site

(Sinkhorn 2007). LAI was estimated with BCACS, climate

information for 2003 was obtained from DAYMET, and

nitrogen mineralization was simulated for the same time

period with the NPP portion of DF.HGS.

Results

Leaf area index

All four methods for estimating LAI were significantly

correlated with observed LAI (P \ 0.0001; Fig. 2). The

relative strengths of these correlations, in descending order,

were: (1) CBSAP (r = 0.93); (2) BCACS (r = 0.92); (3)

Gholz et al. (1979) (r = 0.81); and (4) Maguire and Bennett

(1996) (r = 0.59). Graphs between observed and predicted

LAI indicate a clear bias in all approaches, except BCACS.

Mean absolute error of the BCACS predictions was

1.56 ± 1.23, which was 42, 34, and 30% lower than that

from Gholz et al. (1979), CBSAP, and Maguire and

Bennett (1996) approaches, respectively.

Growth

Simulated stem volume increment was closely correlated

with observed volume growth (P \ 0.0001; r = 0.73;

Fig. 3). Mean bias in 4-year stand volume growth from

DF.HGS was 1.61 ± 12.53 m3 ha-1, while the mean

absolute error was 9.84 ± 7.82 m3 ha-1, relative to a

range in observed 4-year growth of approximately 15–

110 m3 ha-1. In comparison, mean bias and absolute error

in 4-year stand volume growth from the empirical model

were 1.49 ± 13.74 and 9.91 ± 9.56 m3 ha-1, respectively.

Although the mean error for both models was similar, the

coefficient of variation of absolute error was 23.3% lower

for hybrid model. The hybrid approach in DF.HGS sub-

stantially improved predictions of volume growth in the

control and fertilized ? thinned stands in comparison with

the empirical model, and the two approaches performed

similarly for plots that were thinned only or fertilized only

(Fig. 4). Improvements from the hybrid model were most

significant for the control stands, amounting to an

approximate 36% reduction in mean absolute error.

At the individual tree-level, MSE was reduced by 6.1 and

12.4% for 4-year diameter and height growth, respectively,

when compared to a purely empirical approach.

332 Eur J Forest Res (2010) 129:325–338

123

Fig. 2 Relationship between

predicted and observed leaf area

index (LAI) for 113 Stand

Management Cooperative

research installations based on

the data of Maguire and Bennett

(1996). LAI was predicted using

four different methods:

(1) constant leaf area per unit of

predicted sapwood area at

crown base (0.58 m2 cm-2);

(2) Gholz et al. (1979)

allometric equation as a

function of DBH; (3) Maguire

and Bennett (1996) allometric

equation as a function of crown

length, tree height, and DBH;

and (4) Branch, crown, and

canopy simulator (BCACS)

Fig. 3 Results from simulation

of 67 Stand Management

Cooperative research plots in

the Pacific Northwest, USA,

with both the hybrid model

DF.HGS and a set of empirical

diameter and height growth

equations for individual trees

(Weiskittel et al. 2007a): arelationship between observed

and predicted 4-year stand

volume growth (left; m3 ha-1);

and b prediction bias

(predicted–observed) over

predicted volume growth

Eur J Forest Res (2010) 129:325–338 333

123

Soil temperature and moisture

Simulated daily mean soil temperature and volumetric

water content were both closely correlated with observed

temperature and water (P \ 0.0001; Fig. 5). However, the

strength of the correlation was much higher for soil tem-

perature (r = 0.93 vs. 0.49 for soil moisture). DF.HGS

generally underpredicted soil temperature by approxi-

mately 0.5–1.0�C, particularly in the mid-summer. Soil

moisture also was overpredicted on average, particularly at

volumetric moisture contents above 0.25. However, during

the growing season, predictions of soil water dynamics

were closely aligned with observed values.

Soil nitrogen mineralization

Observed annual soil nitrogen mineralization rates aver-

aged 66.9 ± 26.1 kg ha-1 year-1 (range of 15.9–99.1 kg

ha-1 year-1), while predicted rates averaged 60.5 ±

17.9 kg ha-1 year-1 (range of 30.1–97.3 kg ha-1 year-1).

The hybrid model DF.HGS tended to underpredict annual

soil nitrogen mineralization by 10.6 ± 0.33 kg ha-1

year-1, but observed and predicted mineralization rates

were closely correlated (r = 0.75; P \ 0.0001; Fig. 6).

Discussion

The goal of this project was to develop a hybrid model for

assessing silvicultural strategies for intensively managed

Douglas-fir plantations. Components were selected on the

basis of their potential for explaining responses to intensive

silvicultural treatments and for representing the short-term

effects of environmental factors that impose spatial and

temporal variation in growth responses to silvicultural

manipulation. Physiological submodels and parameters

were largely gleaned from the literature and combined with

detailed stand structural information to ensure that the

framework was useful to both researchers and forest

managers. Models that rely on simpler approaches such as

radiation-use efficiency and 0–1 environmental modifiers

perform well, particularly across steep gradients in envi-

ronmental conditions (e.g. Landsberg et al. 2003). How-

ever, models designed to differentiate among alternative

silvicultural regimes on a given site, or the interaction of

alternative regimes with site factors (e.g., mineralization

rates and water availability), require more explicit treat-

ment of processes. The framework developed here for

Douglas-fir resembles many first-generation process-based

models (reviewed by Ryan et al. 1996), but with some

important refinements for simulating responses to intensive

Fig. 4 Mean absolute error in

predicted 4-year stand volume

growth (m3 ha-1) for 67 Stand

Management Cooperative

research plots in the Pacific

Northwest, USA. Plot growth

was simulated with both the

hybrid model DF.HGS and a set

of empirical, individual-tree

diameter and height growth

equations (Weiskittel et al.

2007a)

334 Eur J Forest Res (2010) 129:325–338

123

silvicultural treatments. These refinements include: (1)

hierarchical treatment of growth at branch, tree and stand

levels; (2) explicit representation of crown structure

influence on growth processes; (3) incorporation of slope

and aspect effects on canopy processes; (4) clear connec-

tion between water stress and reductions in photosynthesis;

(5) patterns in light extinction that depend on stand struc-

ture and site factors; (6) net photosynthesis rates dependent

on foliage age class distribution; and (7) initiation from

conventional inventory data.

The hybrid model presented here was designed specifi-

cally to give crown dynamics a central role in driving total

production and controlling responses to silvicultural treat-

ment. Unbiased estimation of LAI and stand biomass is

critical to any process-based and hybrid model; however,

accurately estimating these components can be challeng-

ing, particularly under the wide variety of treatment com-

binations typically imposed by intensive silviculture.

Allometric equations based only on DBH are particularly

biased in young fertilized and thinned Douglas-fir planta-

tions (Grier et al. 1984) and those with varying intensities

of competing vegetation control (Petersen et al. 2008) but

similar equations are still generally used to initiate hybrid

models. In this study, BCACS performed significantly

better than several alternative approaches across a range of

observed LAIs because it directly accounts for crown size

and the fact that it can vary widely for trees of a given

DBH, depending on silvicultural regime. However, the

Fig. 5 Relationship between

observed and predicted daily

mean soil volumetric water

content (left panel) and soil

temperature at 10 cm (rightpanel) for 2001, 2002, and 2003

at the Fall River Long-Term

Site Productivity study in

coastal Washington (Ares et al.

2007)

Fig. 6 Relationship between observed and predicted annual soil

nitrogen mineralization (kg ha-1) in Douglas-fir plantations from the

Oregon Coast Ranges. Simulations were started with initial stand and

site data from Sinkhorn (2007) and daily weather data from DAYMET

Eur J Forest Res (2010) 129:325–338 335

123

CBSAP method showed the highest correlation with

observed LAI and would suggest that determining the

optimal leaf area to sapwood area ratio is the only limita-

tion of this particular approach. On the other hand, there

can be large within-stand variation in the leaf area to

sapwood area ratio (Dean and Long 1986) and its deter-

mination would require destructive sampling, which may

limit its usefulness. Furthermore, in PNW Douglas-fir

plantations, wood quality can also vary tremendously

among alternative management regimes, primarily due to

resulting crown length and branch size. Representation of

crown structure is therefore highly desirable not only from

an ecophysiological perspective, but also in the context of

predicting consequences for wood product attributes and

performance.

All models will likely struggle to predict long-term

growth trends accurately, but short-term predictions (i.e.

5–10 years) can also be difficult in fast-growing species,

particularly under intensive management regimes and

across regions with widely varying growing conditions

like the PNW. Thus, an effective tool for assessing

intensive management of Douglas-fir plantations must

recognize that appropriate silvicultural regimes vary by

site and current stand structure. Developing a hybrid

model for intensively managed Douglas-fir plantations of

the PNW presents challenges beyond those typically

experienced in other regions, including: (1) complex ter-

rain with extremely steep slopes; (2) closed-canopy

plantations with relatively high LAIs (i.e. 7–10); (3)

severe moisture limitations imposed by extremely dry

summers; and (4) a wide variety of soil parent materials

and rock content. These factors drove many of the deci-

sions on the approaches taken in the hybrid model pre-

sented. For example, application of the radiation use

efficiency (RUE) may be questionable for Douglas-fir

stands because nearly 95% of the incoming radiation is

absorbed at a LAI of 6, which is a level exceeded by

many plantations in the PNW. Consequently, photosyn-

thesis in DF.HGS was predicted under mechanistic con-

straints imposed by daily soil moisture availability and

vapor pressure deficit. Scalars that vary from zero to one

are often insufficiently flexible to capture net effects of

daily water relations (Grant et al. 2006). Simulation

results from DF.HGS demonstrated its efficacy for cap-

turing the short-term variation in growth.

The relative performance of process-based, purely

empirical, and hybrid models depends on many factors

besides the extent to which mechanisms are represented

in their architecture, for example, conditions covered by

modeling versus evaluation datasets. A hybrid model

developed by Pinjuv et al. (2006) that accounted for

seasonal soil water availability reduced mean square error

of predicted stand basal area by *4% relative to an

empirical model. Dzierzon and Mason (2006) achieved a

reduction of 14 and 8% with a hybrid model for stand

basal area and top height growth, respectively, across

Pinus radiata plantations in New Zealand when com-

pared to regional empirical equations that relied on stand

age and site index. In contrast, DF.HGS achieved a level

of mean bias similar to a comparable set of individual

tree empirical growth equations across the full range of

tested silvicultural treatments. However, DF.HGS signif-

icantly reduced variance and bias of growth predictions

in unmanaged plantations in comparison with the

empirical model. This relative performance was attribut-

able only in part to incorporation of physiological pro-

cesses (total carbon assimilation, potential dry matter

production, and carbon allocation to volume production);

in reality, site-specific soils and climate information

localized the hybrid model to some degree. The empirical

approach relied solely on site index and therefore on a

single component of productivity. Improving growth

predictions in managed plantations will require future

refinements such as a better representation of stand

structural influences on radiation interception and improved

prediction of carrying capacity and nutrient dynamics

following fertilization. The challenge, however, is finding

the right balance between complexity and functionality

appropriate for accurately simulating stand and tree

responses to alternative management regimes. Several

existing models address many complex soil processes,

but the level of required input on soil nitrogen and car-

bon stores limits wide application of these models by

forest managers. Results from DF.HGS simulations sug-

gested that a simplified approach may be adequate for

predicting soil temperature, soil moisture, and nitrogen

mineralization.

Many shortcomings of the Douglas-fir hybrid model are

similar to those found by Ryan et al. (1996) in his

assessment of several first-generation process-based mod-

els. Missing or poorly represented components include

long-term controls on nitrogen mineralization, the uptake

and allocation of nitrogen by plants, allocation of carbon to

different tree components and processes (e.g., respiration)

and the response of all to changes in resource availability.

Satisfactory understanding of these key processes is still

lacking, so the necessary assumptions erode confidence in

model predictions. As one example, many process-based

models are built on the assumption that priorities exist for

carbon allocation. However, recent empirical evidence

does not support the hypothesized priorities (Litton et al.

2007). Resolving these differences through focused

research will be necessary before improvements in model

predictions can be realized.

336 Eur J Forest Res (2010) 129:325–338

123

Conclusions

Hybrid models that combine the features of empirical and

process-based models have been suggested as the next step

forward for improving growth projections in managed

stands (e.g. Landsberg 2003). A hybrid model constructed

for intensively managed Douglas-fir plantations in the

PNW significantly improved predictions of canopy attri-

butes, while the accuracy of volume growth predictions

were comparable to other modeling approaches. The

model’s robust performance resulted directly from: (1)

more detailed representation of individual tree crown

structure; (2) inclusion of major physiological mechanisms

at an appropriate spatial and temporal resolution; and (3)

the use of site-specific soils and climate information. Based

on this analysis, facets of hybrid models requiring future

improvement include: (1) effects of soil water and nutrient

availability on physiological processes, particularly respi-

ration and carbon allocation; (2) effects of silviculture and

environmental conditions on foliage age class dynamics,

seasonal variation in LAI, and net photosynthesis; and (3)

rigorous estimation and evaluation of key physiological

parameters.

Acknowledgments Data were generously made available by Adrian

Ares, Andreas Brunner, Hiroshii Ishii, Nathan McDowell, Cindy

Prescott, Emily Sinkhorn, Lars Vesterdal, and the Stand Management

Cooperative. Thanks to Uta Berger, David Marshall, David Hyink,

Jenny Grace, and Hans Pretzsch for reviewing a previous version of

this manuscript. This project was funded by the USDA Forest Service

PNW Research Station.

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