United States Department of Agriculture

Forest Service

**Northeastern Research Station** 

Research Paper NE-722 

# James E. Smith Linda S. Heath 

# A Model of Forest Floor Carbon Mass **for United States Forest Types**Published by: For additional copies:
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### The Authors

JAMES E. SMITH and LINDA S. HEATH are research plant physiologist and research forester/project leader, respectively, with the Northeastern Research Station at Durham, New Hampshire 

### Abstract

We summarize a large set of published values of forest floor mass and develop large-scale estimates of carbon mass according to region and forest type. Published values of forest floor carbon mass or information relevant to compiling such summaries are scarce. We present a simulation model based on observations obtained from literature surveys for use in the 2002 version of FORCARB, a carbon budget model for U.S. forests. The forest floor is the distinct layer of dead and decaying plant material that accumulates on the soil surface, which lies above the mineral soil and includes small woody debris. Estimates of average forest floor carbon mass per hectare of forest applied to a 1997 summary forest inventory, sum to 4.5 Gt carbon stored in forests of the 48 contiguous United States.

Manuscript received for publication 22 April 2002

# A Model of Forest Floor Carbon Mass **for United States Forest Types**

**James E. Smith and Linda S. Heath**

**Acknowledgments**

We thank Coeli Hoover, Steve Prisley, Eric Vance, Ruth Yanai, and Sara Duke for helpful comments on drafts of this manuscript. Eric Fiegenbaum provided the cover art. This work was partly supported by the USDA Forest Service Northern Global Change Program.

Metric units and conversions

Mg = megagram, or metric tonne = 1.102 U.S. ton, or 2,205 pounds Mt = megatonne, 10 6 tonne, or teragram Gt = gigatonne, 10 9 tonne, or petagram
1 hectare = 2.471 acre1 

## Introduction
The role of forests and land-use change in the global carbon cycle interests scientists and policy makers because of the contribution forests make to the large annual carbon flux between terrestrial ecosystems and the atmosphere (Tans and White 1998). Forests and forest management projects have been a central component of proposed actions to help mitigate greenhouse gas emissions because forests can be an economical carbon sink (Rotter and Danish 2000). Our objective is to develop equations to estimate forest floor carbon for U.S. forests based on common forest inventory variables. Little comprehensive data exists for forest floor carbon pools of the U.S.

The development of these equations is part of a larger project to estimate forest carbon using a simulation model called FORCARB (Plantinga and Birdsey 1993; Heath and Birdsey 1993). The FORCARB model accounts for carbon in U.S. forests (Birdsey and Heath 1995) and forest products (Heath and others 1996; Skog and Nicholson 1998), has been used to produce projections for the 2001 U.S. Submission to the United Nations Framework Convention on Climate Change on Land Use, Land Use Change and Forestry (U.S. State Department 2000), and has been used to examine uncertainty in U.S. forest carbon budgets (Smith and Heath 2000; Heath and Smith 2000). FORCARB produces separate estimates for all forest carbon pools such as live trees, down dead wood, and soil organic carbon.

Predictions of forest floor carbon mass based on comprehensive sampling are not currently available, but such data are likely to accompany future forest inventories. In this study, we attempt to meet current needs for forest floor carbon information by developing estimates of forest floor carbon based on deriving relationships developed from published data. Our goal is to develop and present a transparent and readily updated simulation model to estimate forest floor carbon mass based on forest type, regional characteristics, and forest age since a major disturbance. “Transparent” means that it is possible for users to understand how any part of the estimate affects results, that is, all parts of the equations are clearly outlined. These estimates are applicable to developing a forest carbon budget of the entire U.S. or for estimating regional averages, and can be used at the stand level in the absence of local information.



## Forest Floor
Sparse information and the immediate need for tractable carbon estimates are the principal considerations in this study. Our approach is (1) to define the forest floor, (2) to develop a simple conceptual structure for making quantitative estimates, (3) to compile useful data from the literature, and (4) to sort and summarize data to develop estimates.

Forest floor definitions vary and have evolved over time. Establishing a working definition and conceptual structure help to identify relevant information. We are interested in broad classification variables to serve as useful predictors of forest floor carbon. These variables and their relative usefulness are discussed in detail below. Values summarized from the directly measured observations are assigned as representative of similarly classified forest land. Our approach is conceptually similar to other approaches that extracted data and made broad generalizations from published measurements of forest ecosystems (Vogt and others 1995; Vogt and others 1996; Johnson and others 2000). We identify important predictors of forest floor mass from literature reviews, usethese relationships and published values to make modelbased estimates, and update estimates where possible.

The forest floor includes nonliving plant mass in various states of mechanical and chemical decay. Large vertebrate detritus may sometimes be included in forest floor samples, but it is generally a small part of the forest floor. Plant material includes leaves, twigs, bark, and woody stems on the forest floor. Some forests also contain a significant amount of fine roots in the forest floor. Accumulation of plant material can form identifiable layers above the mineral soil. Layer identities are based on states of decomposition ranging from freshly fallen leaves and twigs, which are easily identified, to lower layers of humus that are at an advanced state of decomposition. The lowest layer can be amorphous and sometimes almost indistinguishable from upper layers of mineral soil (Waring and Schlesinger 1985). Organic layers above the mineral soil are usually identified as O i , O

e , and O

a (upper to lower) or L, F, and H according to a previous classification system (Federer 1982).

Distinctions among pools of coarse woody debris, the forest floor, and soil organic matter are necessary to avoid over- or under-counting carbon when separate estimates are made for each. Reconciling differences in forest floor data collection was difficult as many studies featured different protocols. For example, distinctions between coarse woody debris and the small woody material that is considered part of the forest floor are based on diameters of recently fallen branches and stems. Diameters ranging from less than a centimeter to more than 7 cm are reported as the distinction between coarse woody debris and forest floor (Rollinger and others 1998). Also, many reports either do not specify how a distinction was made, or they fail to identify the presence or absence of woody2 material. The state of decomposition is also a basis for distinguishing coarse woody debris from the forest floor because rotting logs eventually become classified as forest floor. The distinction between the lowest layers of forest floor and upper (generally A horizon) layers of mineral soil is sometimes clear. However, purely organic layers of forest floor and organic-rich layers of the mineral soil are sometimes difficult to discern. This can be even more difficult when mechanical mixing of layers has occurred (Ryan and others 1992). Field classifications are usually based on morphology and are closely related to an individual researcher’s experience (Federer 1982).

Accumulation of forest floor mass depends on rates of detrital inputs and the rates of loss through processes such as decomposition or physical damage or removal. Accumulation and loss can be spatially (Simmons and others 1996) and temporally (Nemeth 1973) heterogeneous. Processes can be influenced by season, climate, and edaphic factors, as well as stand composition, age and disturbance history (Schlesinger 1977; Mattson and Smith 1993; Binkley 1995).

Forest floor carbon mass is related to total biomass accumulation, but additional factors control specific carbon content. Specific carbon content of forest floor mass can vary by origin of material as well as history of decay or residence time in the forest floor. For example, freshly fallen wood usually contains more carbon per gram dry weight than fresh leaf litter, approximately 50 percent versus 45 percent (Fassnacht and Gower 1999). Loss of carbon through respiration and changes in chemical composition with decay result in progressively decreasing carbon content of the more decomposed material of lower forest floor layers (Huntington and others 1989; Schiffman and Johnson 1989). Decomposition rates are principally affected by quality and quantity of material as well as a favorable microenvironment (Schlesinger 1977; Hendrickson and others 1989; Berg and others 1996). Though quantity and quality of inputs affect carbon mass stored in forest floors, factors controlling carbon loss appear to be somewhat more important in controlling the carbon level in temperate forests (Vogt and others 1996). We assume that factors affecting gain and loss co-vary with forest type, location, and other general descriptors, and that such generalizations are useful for developing simple estimates at large scales.



### Regional characteristics
Numerous reviews report forest location and composition are associated with average amount of forest floor mass (Schlesinger 1977; Vogt and others 1986; Vogt and others 1995; Vogt and others 1996; Rollinger and others 1998). For example, Vogt and others (1995) reviewed a number of broad influences on soil and forest floor carbon. The goal was to identify influences on large-scale estimates. Their results demonstrated a trend of greater forest floor accumulation along a climatic gradient from tropical to temperate to boreal forests. The result of adding evergreen and deciduous classifications suggested their usefulness for predicting forest floor mass. Evidence further suggests that additional predictor variables such as soil type, stocking, productivity, or management intensity can affect forest floors, but these variables are not as consistently useful as region or forest type for making large-scale estimates (Vogt and others 1995; Vogt and others 1996).

Climate affects accumulation and loss of forest floor mass. Longer growing seasons and warmer temperatures are associated with greater productivity and litterfall, but they also are associated with more rapid decomposition, especially if litter retains sufficient moisture and aeration. Within a specific forest type or region, latitude or elevation gradients may be analogous to climate gradients. Estimating forest floor mass with latitude may depend on considering a wide range of either latitude or local environments (Vogt and others 1986; Vogt and others 1995; Simmons and others 1996).



### Forest Type by Region
Forests dominated by conifers usually accumulate more forest floor mass than deciduous forests (Schlesinger 1977; McClaugherty and others 1985; Finzi and others 1998). However, a number of exceptions to this trend also have been noted (Perala and Alban 1982a; Grigal and Ohmann 1992; Vogt and others 1995). The accumulation in softwoods is partly due to more decay-resistant litter, conditions that favor fungal decomposers, and cooler temperatures and microenvironmental conditions that slow decomposition. Rates of litter decomposition are usually lower for softwoods than for hardwoods. Vogt and others (1995) found generally greater forest floor mass in needle-leaved evergreen forests than in broadleaved deciduous forests in warm temperate regions. However, forest floor accumulation was greater in cold temperate climates with the two forest types having similar forest floor mass. Mixed forests of both needle-leaved evergreen and broadleaf deciduous species had significantly more forest floor mass than either type alone.

Forest type, as described by major component species, is clearly an important factor in accumulation of forest floor mass (Lang and Forman 1978; Cole and Rapp 1981; Vitousek and others 1982; Vogt and others 1986; Vogt and others 1996; Rollinger and others 1998). However, there are enough exceptions to predictive ability within forest types to suggest that classification by type alone3 might not be sufficient to develop a simulation model. For example, forest floor mass sampled from 40-year-old stands of aspen, white spruce, jack pine, and red pine were within a similar range. This included no substantial differences between hardwood and conifer species (Perala and Alban 1982b). Species composition alone also can produce apparently contradictory results. For example, sometimes the presence of alder leads to substantially greater forest floor mass in Douglas-fir stands in the Pacific Northwest, and sometimes inclusion of alder does not affect accumulation (Binkley and others 1992). Including bigleaf maple in Douglas-fir stands along the coastal range in Oregon had no affect on forest floor mass. Bigleaf maple did, however, increase measured litterfall and rates of decomposition (Fried and others 1990). Despite the many documented exceptions, location (region) and stand composition are probably the most useful estimators for forest floor mass.



### Development with Age
Forest age, in years since afforestation or a major disturbance, is assumed to be the next most useful predictor of forest floors after location-by-type influences. A change in land use to forests, such as afforestation of agricultural soils, often is associated with a rapid increase in forest floor mass (Schlesinger 1977; Binkley 1995). The surface organic layer, which becomes forest floor with afforestation, is generally greater in forests than in recently abandoned agricultural land or old-fields (Schiffman and Johnson 1989; Homann and Grigal 1996). Net forest floor mass accumulates at a relatively rapid rate during forest development. This rate slows considerably as the forest floor reaches a more mature state between 20 and 80 or more years, depending on the forest (Switzer and others 1979; Covington 1981; Means and others 1992; Edmonds and Chappell 1994; Smith and Resh 1999). Relatively slower rates of change characterize the much longer period from maturity through old growth. Forest floors of older undisturbed forests can sometimes be characterized as an approximately steady state.

These estimates depend on assuming a threshold age for mature forest floors based on the overstory age of a stand and assigning an average carbon mass for an approximately steady state. Covington (1981) and others (Federer 1984; Hendrickson and others 1989; Mattson and Smith 1993; Olsson and others 1996) identified forest floor dynamics following harvest, and defined “fully recovered” Northern hardwood forest floors between 40 and 60 years old. Development is much more rapid in Southern pine forests with ages between 15 and 25 years (Nemeth 1973; Switzer and others 1979; Gholz and others 1985; Lockaby and Taylor-Boyd 1986). Evidence suggests that western forests tend to develop forest floor mass more slowly (Smith and Resh 1999). The exceptions in the West are forests of the Pacific Northwest west of the Cascades (Turner and Long 1975); Douglas-fir forests develop forest floor mass relatively rapidly and continue slow increases through old growth. Differences between mature and old-growth forest floor mass vary by forest and region. However, approximate steady-state averages may be useful for long-term estimates for regions where old-growth stands are an increasingly smaller proportion of forest area.



### Effects of Disturbance
Relationships between disturbance and forest floor mass depend on severity of disturbance. Minor disturbances, such as creation of small gaps or low-intensity fires, may have little apparent measurable effect and can result in rapid recovery. For example, windthrow — creating small gaps — had no long-term effect on carbon storage inforest floors of hemlock-hardwood and northernhardwood forest in the Great Lakes region (Liechty and others 1997). Fire effects on forest floor mass, or carbon, can vary considerably. Some regular or low-intensity fires have little effect in reducing forest floor mass (Alban 1977; Little and Ohmann 1988; Clinton and others 1996), whereas most of the forest floor can be lost in more severe fires (Dyrness and others 1989; Vose and others 1999). Rapid recovery can occur when fire damage to overstory is limited (Bell and Binkley 1989).

Reductions in forest floor carbon are possible following a clearcut harvest. Harvests result in decreased litter input and increased decomposition (Johnson and others 1991; Alban and others 1994; Strong 1997; Rollinger and others 1998). Changes in decomposition are influenced by the altered microenvironment of the soil surface. In addition to rapid decomposition, immediate losses of forest floor with harvest may be due to mounding, mixing, and burial of organic matter (Federer 1984; Ryan and others 1992). Effects of harvesting on forest floor mass and the dynamics accompanying forest regrowth can have important consequences for estimates. If forest floor mass is lost quickly after harvest, then patterns of carbonstorage will follow closely those of afforestation. Timeaveraged carbon content would be considerably greater, however, if most forest floor mass remains after harvest, followed by slow decay during forest regrowth and accumulation of new forest floor mass.

Covington (1981) described the dynamics of forest floor mass for northern hardwood forests following clearcut harvesting. Forest floor organic matter decreased the first 15 years following clearcutting of northern hardwood forests in New Hampshire. A 50 percent decrease was4 followed by a slow recovery of forest floor for about 50 years before floor mass was within 5 percent of preharvest levels. These results initiated numerous field measurements and model simulations of this effect. Some reports failed to demonstrate the same dynamics (Hendrickson and others 1989; Schiffman and Johnson 1989), and others repeated the effect (Federer 1984; Snyder and Harter 1987; Mattson and Smith 1993; Johnson and others 1995), principally among northern hardwoods. Differences among most results were usually in the extent or timing of the minimum in forest floor mass. Restoration of forest floor mass with regrowth was due partly to rapid recovery of litterfall, often to preharvest levels within a few years of harvest (Covington and Aber 1980; Schiffman and Johnson 1989; Alban and Perala 1990). Another explanation for the dynamics described by Covington (1981) is that differences among harvest methods over time have impacted sites differently and forest floor mass partly reflects this record (Yanai and others 2000).



### Decomposition
Decomposition, a controlling process for net accumulation of forest floor mass, is affected by quantity and quality of material (Schlesinger 1977; Hyvonen and others 1998). Quantity varies with forest productivity and season. Quality varies with the input material and depth in forest floor, with fresh litter subject to the most rapid decomposition and humus decomposing slowly. Additionally, favorable microenvironments are functions of temperature and moisture. Controls on decomposer activities — temperature, moisture, and tissue chemistry — are reflected in large-scale attributes such as region, annual temperature and precipitation, latitude, elevation, and species composition (Vogt and others 1986). The general observation that forests with lower mean annual temperatures and dominated by evergreen species tended to have greater accumulation of forest floor (Vogt and others 1995; Vogt and others 1996) is consistent with these broad controls. Thus, the same broad forest characteristics that covary with forest floor mass — region and type — also predict decomposition, as expected.



### Literature Bases for Structuring Estimates
Based on literature and the goals of our work, we choose to focus on region and latitude as climate analogs, and forest type (also affected by climate) as the principal predictors of forest floor mass. Forest age, in terms of years since afforestation or a major disturbance, is identified as the third general characteristic used in forming these estimates. The basic assumption about age effects is that greater changes occur in younger forests developing toward maturity than in the years between a mature state and old growth. “Mature” can be a difficult state to define, but it serves to organize the format of these basic estimates.



## Forest Floor Data from Literature
Our goal is to develop a transparent simulation model to estimate the forest floor carbon pool. The model is based on data derived from literature searches and a series ofsimplifying assumptions. We assume that relatively smallscale numerical relationships obtained from the literature can be applied to determine carbon for large areas. Estimates are based on averages of published values grouped according to forest and location. Relationships among average values are then applied to large areas defined by roughly similar forest composition, history, and regional characteristics.



### Conceptual Organization and Assumptions Based on Literature
Our base assumption is that mature forests, classified according to type and region, achieve an approximately steady state of forest floor carbon (Schlesinger 1977; Switzer and others 1979; Hough 1982; Waring and Schlesinger 1985; Lockaby and Taylor-Boyd 1986). While true steady states are unlikely, this is a necessary simplification. The changes in forest floor mass associated with a progression from mature forests to old growth — 40 to 60 years to hundreds of years — are likely to be much smaller than the accumulation during the first 20 to 60 years following regrowth after harvest. This assumption is most appropriate for large aggregate values (summed over thousands of hectares, for example), whereas individual stands are likely to exhibit greater temporal and spatial heterogeneity with respect to the dynamics of forest floor accumulation.

Our second assertion is that disturbances alter forest floor mass (Schlesinger 1977; Dyrness and others 1989; Johnson and others 1991; Alban and others 1994; Strong 1997; Rollinger and others 1998; Vose and others 1999). Any pattern of decrease or pulse increase in forest floor mass following a disturbance depends on the type and severity of the disturbance. Long-term effects depend on the specifics of the disturbance as well as time since the event. We also assume that over time the forest floor will return to the approximately steady state level of a mature forest.

Dynamics of forest regrowth following disturbance or with afforestation are assumed to affect the forest floor carbon pool. We assume that the early period of growth ends at a threshold age for maturity and the onset of the apparent steady state. This age may vary with forest type5 and region. We also assume that the forest floor reaches this approximately steady state sooner than soil carbon orannual increment of tree biomass. The same time-torecovery is applied to afforestation, regrowth, and major disturbances (such as widespread crown fires). We assume afforestation is accompanied by a relatively rapid increase from little or no surface organic layers to the mature level of forest floor mass. Partial cutting may have the same pattern with a more rapid recovery time.



### Specific Value Needs
The structure of all estimates depends on assigning forest area to generally homogeneous groups according to region, forest type, and age. This is the minimum classification scheme for all values extracted from the literature. Classifications are applied to both inputs from forest sector projections and from empirical relationships identified in the literature. Published data are used to determine an average age and carbon content for a mature forest. Published discussions about forest floor maturity and an informal examination of the data were the bases for assigning mature ages.

The transition from age zero to the mature forest is a relatively rapid growth phase for forest floor carbon. Regrowth also includes decaying forest floor material that starts at age zero with the precut mature level of carbon. Decay rates are set according to forest floor mass mean residence times by forest type and region. The initial forest floor carbon in regenerated forests generally reaches zero by the time the forest floor has returned to the mature state. Though it was not our intent, the sum of the two modeled estimates — rapid increase and exponential decay — at the same age qualitatively reproduces the time course described by Covington (1981).



### Identifying Published Values
The search for existing data on forest floor mass included peer-reviewed journals, technical reports, and the Internet. Information varied considerably among publications. A few directly addressed mechanisms of control on forest floor accumulation. However, the forest floor mass data were peripheral to the main purpose of most of these publications. The minimum data requirements were some description of the forest and a measure of forest floor mass.

We made an effort to avoid duplicate observations. Research projects often use the same field site and much of the site data can be reported in more than one publication. Where a number of forest floor values were reported for a single site within a publication, we pooled the values to a single observation. Separate sites in the same forest were counted as separate observations. Thus, publications with a number of values were sometimes used as a few points and sometimes included as a single mean, depending on our interpretation of the data. We made no effort to adjust for possible bias in location of experimental versus actual forest distribution within a forest-type by region classification. Similarly, seasonal influences on forest floor mass can vary, but we did not sort observations accordingly.

The values obtained from publications were as follows: a description of forest type; mass per unit area; mass identified as carbon, organic matter (ash free weight), or dry weight; values for converting organic matter or dry weight to carbon; stand age or time since significant disturbance; site history in terms of management or disturbances; location, including latitude, longitude, and elevation; and a measure of decomposition or mean residence time of forest floor material. Some discussion of forest floor definition and measurement was noted. Additional information, such as more precise species composition, stand density, site productivity, other carbon or biomass pools, or additional site history, was occasionally included in publications.

Our definition of forest floor does not include down coarse woody debris and mineral soil but these might have been included in some observations. Published values overestimate forest floor if larger woody material was considered part of forest floor without being mentioned in the method of collecting forest floor material. Similarly, other estimates will understate forest floor if they exclude all fine woody material from reported values. The same uncertainties exist for the distinction between forest floor and the upper layer of mineral soil. Thus, precise definitions for forest floor were ostensibly primary considerations in extracting data from the literature survey. Most reports provided little information on distinctions among coarse woody debris, forest floor, and the mineral soil pools. For these, we simply relied on the individual researcher’s experience for the vast majority of observations. Where possible, we excluded woody material greater than 7.5 cm in diameter, because this was defined as coarse woody debris.



### Forest-type and Region Classification
These estimates are based on region and forest-type classifications shown in Figure 1 and Table 1, respectively. General forest types were formed on the limited number of observations available. For example, a single pine type was formed for the South. Additional subdivision of types is possible in the future. Forest types not explicitly included were not represented in our dataset. Setting a minimum age for a mature forest floor was a somewhat subjective process. Ages were assigned after considering6 reports in the literature and forest ages in growth and yield models.

Northern forest floors were defined as mature when the overstory age was 50 years. Conifers were divided into two groups, pine and other conifer, which were mainlyspruce, fir, and hemlock. Aspen-birch and maple-beechbirch formed two distinct groups with a large number of observations in each. Other hardwoods were lumped as asingle group that included mostly oaks and some oakhickory forests as well as miscellaneous hardwoods. A sixth type was mixed conifer-hardwood.

Southern forest floors were defined as mature at overstory age 30 years. Pine was the only conifer classification possible from the dataset. All southern hardwoods were pooled to a single group, which was mostly oak-hickory. Very few bottomland hardwoods were included. A fourth type was mixed conifer-hardwood. The large areas of pine and the likely different effects of management make southern pines a candidate for future subdivision of forest types according to origin or productivity.

Pacific Northwest forest floors were defined as mature when overstory age was 40 years. The west side of the Pacific Northwest — the states of Oregon and Washington west of the Cascade Mountains — has a very different climate than the remainder of the Western United States. It is the only distinct subregion we established for the West. Conifers were divided into two types according to elevation. Higher elevation species were fir and hemlock. Lower elevation and coastal sites were principally Douglas-fir, Western hemlock, and Sitka spruce. All hardwoods were grouped as one type. The remainder of the West was considered one large region and included the Rocky Mountains, the Intermountain/Great Basin, and California. The age for mature forest floors was set at an overstory age of 80 years. The principal division in the West was between most conifers as pine or mixed conifer groups. Large areas of woodlands in the West including pinyon-juniper were maintained as a separate group due to size of area, however few values were identified. Hardwoods and redwoods/giant sequoia were two additional classifications.

We found some data for Alaska forests. However, too few reports were available for usefully classifying forests by age or type. Thus we do not develop equations for estimating forest floor carbon, but we did summarize values for interior Alaska (Table 1). We assume characteristics of forest floors of southeastern Alaska are more similar to those of the Pacific Northwest than of interior Alaska (Figure 1).



## Model-Based Estimates of Forest Floor Carbon

Most published values for forest floor mass were reported in dry weight. About 20 percent of the values were reported as carbon mass per unit area, with another 20percent reporting in terms of organic matter (that is, ashfree weight). We converted all values to megagram carbon per hectare based on ratios identified in the dataset, which were consistent with other reported values (Perala and Alban 1982b; Vitousek and others 1982; Huntington and others 1989; Cromack and others 1999; Vose and others 1999). Organic matter was converted to carbon by South West Interior

Pacific North

Northwest Alaska

South West Interior

Pacific North

Northwest Alaska

Figure 1.—Regions used to classify forest types. Note that Alaska is not drawn to scale.7 multiplying by 0.55. Mass of carbon per unit dry mass is likely to vary by region, forest type and layer or state of decomposition. Specific carbon contents reported in our dataset did show distinct layer effects. However, there were too few sites that included separate layers to calculate averages on this basis. The layers were pooled for average forest floor values of the subset of the data that included specific carbon content. No general trends emerged among regional averages or between conifers and hardwoods (Table 2). We multiplied dry weight by 0.37, a ratio obtained from our dataset, to estimate forest floor carbon.

Mean forest floor carbon for mature forests is shown in Table 1. Standard deviation, sample size, minimum and maximum values also are presented to show availability and variability in the data. The mature values represent the averages where age was greater than 90 percent of the minimum age set for mature forest floors or sites where the researchers described the stand as mature. The ratio of forest floor mass to mass of annual input to the forest floor, or mean residence time as described above, is provided in Table 3. The classification system and mean values for forest floor carbon mass generally are consistent with those reported by Birdsey (1992, 1996).



### Latitude or Elevation Effects
Many published values included site-specific information such as latitude and elevation. The expected association with accumulation of forest floor made these variables candidates for an additional level of classification. This information was included with about one-third of the observations identified as mature forest floors. Other reports included enough information about location that allowed us to estimate latitude. If the local topography was relatively flat, we also estimated elevation. Preliminary regression analyses found that neither latitude nor elevation was a useful predictor of forest floor carbon with the set of values we had obtained. Thus, latitude and elevation were not included in our model. Latitude and elevation are, however, included in the appendix of Table 1.—Mean forest floor carbon by region and forest type for forests identified as mature.

Region and forest type Carbon Standard Sample Minimum Maximum deviation size (Mg/ha) (Mg/ha) (Mg/ha) (Mg/ha)

North pine 13.8 4.6 13 5.4 19.8 spruce, fir, hemlock 33.7 23.2 6 4.6 68.1 mixed conifer-hardwood 29.7 26.6 5 5.4 75.0 aspen-birch 10.2 6.2 13 2.3 20.9 maple-beech-birch 27.7 17.8 28 2.8 89.5 mixed hardwood, oak 8.2 7.3 33 2.8 34.1

South pine 12.2 4.6 28 1.4 21.9 mixed conifer-hardwood 10.3 3.6 6 6.7 16.8 mixed hardwood, oak-hickory 6.0 5.7 20 0.8 24.8

Pacific Northwest Douglas-fir, western hemlock 27.5 31.3 69 2.6 165.6 fir-hemlock, higher elevation 29.5 16.3 7 16.8 55.3 hardwood 9.3 7.6 4 0.9 16.9

West pine 24.1 12.2 29 3.3 46.0 redwood, sequoia 62.2 31.3 3 35.9 96.9 pinyon, juniper 21.1 1.6 2 20.0 22.2 mixed conifer 37.2 11.5 24 23.3 73.9 hardwood 31.7 14.1 11 4.7 51.1

Interior Alaska a all mature 32.2 19.1 13 14.2 73.3

a Data for interior Alaska were few and showed no age effect; therefore, values represent all observations, not a subset determined by age.8 Table 2.—Summary of specific carbon content of entire forest floor, all layers grouped together. Values are sorted according to general type or region and were taken from observations extracted from literature (see Table A1).

Forest type or region Ratio of carbon mass to total dry mass Mean Standard deviation Sample size

All values 0.370 0.0601 59

conifer 0.365 0.0525 27 hardwood 0.361 0.0603 22 mixed 0.402 0.0737 10

North 0.376 0.0490 26 South 0.368 0.0834 14 Pacific Northwest 0.355 0.0618 13 West 0.379 0.0427 6

Table 3.—Mean residence time in years (forest floor mass divided by annual biomass input) for entire forest floor. Values reported as carbon, organic matter, or dry weight were pooled for these averages. Values are sorted according to general type or region and were taken from observations extracted from literature (see Table A1).

Region and forest type Mean residence Standard Sample Minimum Maximum time deviation size (years) (years)
North conifer 8.4 6.02 18 3.2 29.1 hardwood 9.2 9.49 26 1.1 35.8

South conifer 3.8 3.15 19 0.9 13.7 hardwood 3.2 1.92 16 0.4 6.3

Pacific Northwest conifer 16.0 17.44 59 0.9 80.0 hardwood 3.4 0.55 4 2.9 4.2

West conifer 24.1 16.04 22 8.7 60.0 hardwood 19.8 11.95 2 11.4 28.3

Alaska conifer 433.0 201.0 3 220.0 620.0 hardwood 24.5 5.46 5 19.7 33.29 observations because of their expected usefulness in simulation modeling.



### Simulation Based on Stand Age
Our model is in two parts: net accumulation and decay. Net accumulation of forest floor carbon mass with increasing age is represented as a simple model construct. Basic conditions for the model are that it passes through the origin, represents continuous net accumulation with age, and rate of accumulation decreases so that the line approaches an asymptote. We model net accumulation of forest floor carbon mass according to the following relationship:

Age is stand age in years, and A and B are coefficients describing the line relating age and forest floor carbon mass. This relationship conforms to our conceptual model. The coefficients are assigned according to the basic assumptions discussed above. We assume minimum ages represent mature forest floors and that means of published values are representative of mature forests. We set the upper limit for the model at the 95 th percentile of values for forest floor carbon mass. This is the value assigned to coefficient A. Since average carbon mass for mature forest floor represents all ages, we expect the line to pass below the ordered pair for mature forests: (minimum age, mean carbon mass). Preliminary regression analysis for northern hardwoods and southern pines (where many values were available) identified the mean carbon mass at a point approximately 30 percent greater than the assigned minimum age. Therefore, we model the relationship as passing through the ordered pair (minimum age × 1.33, mean carbon mass). Values for coefficients A and B are provided in Table 4. Table 4.—Coefficients to define modeled relationship between forest age and forest floor carbon mass (Mg/ha) for each combination of forest type by region. Columns A and B define net accumulation with age, and C and D describe the decay curve. Regrowth is the sum of accumulation and decay.

Forest type Accumulation: Decay:

AB C a D a

North pine 19.1 25.6 13.8 8.4 spruce, fir, hemlock 62.9 57.8 33.7 8.4 mixed conifer-hardwood 65.0 79.5 29.7 8.4 aspen-birch 18.4 53.7 10.2 9.2 maple-beech-birch 50.4 54.7 27.7 9.2 mixed hardwood, oak 24.9 134.2 8.2 9.2

South pine 20.4 27.1 12.2 3.8 mixed conifer-hardwood 15.4 20.1 10.3 3.8 mixed hardwood, oak-hickory 15.3 61.8 6.0 3.2

Pacific Northwest Douglas-fir, Western Hemlock 87.5 116.7 27.5 16.0 fir-hemlock, higher elevation 53.9 44.3 29.5 16.0 hardwood 16.5 41.1 9.3 3.4

West pine 43.9 87.3 24.1 24.1 redwood, sequoia 92.6 52.1 62.2 24.1 pinyon, juniper 21.1 mixed conifer 53.6 47.0 37.2 24.1 hardwood 50.1 62.0 31.7 19.8

a Values in Columns C and D are from Tables 1 and 3, respectively. 

### A age B age

×

+ C e age D 

### × −      

Forest floor carbon (Mg/ha) = ×

+ A age B age10 The model for the decay line is based on the average forest floor of mature forests and regional averages for apparent decay rates. Forest floor carbon mass following clearcutting is assumed to begin at the mature forest floor level of carbon. Decay of forest floor mass existing prior to the clearcut is described as an exponential function of years and mean residence time:

Coefficient C is average mature forest floor carbon mass from Table 1, coefficient D is the mean residence time from Table 3, and e is the exponential function. Values for coefficients C and D are provided in Table 4.

Total carbon mass during regrowth is the sum of estimates from the two models — accumulation and decay — defined in Table 4. Examples of simulated accumulation, decay, and totals are shown in Figure 2.



### Application of Estimators
Summaries in Tables 1 and 4 provide estimates of forest floor carbon mass per unit area for region by forest type definitions without and with the added influence of age, respectively. Many, but not all, forest inventory summaries provide age or disturbance history. However, total area is common to all forest inventory data and is an essential part of carbon budgets. Estimates presented here complement area and age information. The total carbon pool is the sum across all ages and areas.

Forest types defined for Tables 1 through 4 are based on data available in the literature. Determining estimators for all forest types entails establishing a reasonably close match of types when necessary. For example, northern maple-beech-birch values were combined with mean residence times for northern hardwoods to estimate forest floor response to regrowth. Similarly, the summaries in Tables 1 and 4 must be linked to forest inventory types to estimate total carbon pool sizes.



## Forest Floor Carbon Pool of the United States

Total carbon estimates were based on forest inventory data (Smith and others 2001). The database is a compilation of extensive forest inventory data for the United States. We applied the model summarized in Table 4 to the 1997 forest inventory database. The resulting estimate of forest floor carbon mass density (megagram per hectare), averaged over all forest types 

### Residual forest floor carbon (Mg/ha) = × −       

### C e age D

Figure 2.—Examples of forest floor carbon estimated as a function of stand age for three forest types. Diamonds represent observations with age, and x’s represent observations not linked to a specific forest age but identified simply as mature. The lower solid line represents estimated forest floor carbon with afforestation. The dashed line is an estimated path of decay following clearcut harvesting. The upper solid line represents net accumulation during regrowth and is the sum of afforestation and decay lines. The open circle represents the average mature forest floor value from Table 1. 0 20 40 60 80

0 40 80 120 Stand age (years)MgC/ha North, maple-beech-birch

0 10 20 30

0 25 50 75 Stand age (years)Mg C / ha South, pine

0 25 50

0 50 100 150 200 250 Stand age (years)Mg C / ha West, pine11 

### 0 10 20 30 40 North South West Pacific Northwest Alaska (entire state)

Forest floor carbon (Mg/ha) 0 500 1000 1500 2000 2500 North South West Pacific Northwest Alaska (entire state)

Forest floor carbon (Mt)

per region and totals, are shown in Figure 3. Approximately 4.5 Gt carbon is stored in the forest floor carbon pool in the 48 contiguous United States.

Forest floor carbon data should become increasingly available from the annualized USDA Forest Service Forest Inventory & Analysis Program. Assembling a database that can be readily reclassified and resorted is a quick and Figure 3.—Total (A) and average forest floor carbon per hectare (B) by region of the U.S., 1997. 

## A

**B**

simple approach to developing empirical estimates of forest floor carbon, which can be easily updated and revised. This accomplished the goal of tractable and transparent carbon estimates for U.S. forests, which focuses on actual rather than potential vegetation. Estimates are not restricted to any single form. The results provide flexible, transparent forest floor carbon estimators for U.S. forests.12 

## Literature Cited

Alban, D.H. 1977. Influence on soil properties of prescribed burning under mature red pine. Res. Pap. NC-139. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 8 p.

Alban, D.H.; Host, G.E.; Elioff, J.D.; Shadis, D.A. 1994. Soil and vegetation response to soil compaction and forest floor removal after aspen harvesting. Res. Pap. NC-315. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 8 p.

Alban, D.H.; Perala, D.A. 1990. Ecosystem carbon following aspen harvesting in the upper Great Lakes. In: Adams, R.D., ed. Proceedings of symposium: Aspen Symposium ’89; 1989 July 25-27; Duluth, MN. Gen. Tech. Rep. NC -140. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station: 123-131.

Bell, R.L.; Binkley, D. 1989. Soil nitrogen mineralization and immobilization in response to periodic prescribed fire in a loblolly pine plantation. Canadian Journal of Forest Research. 19: 816-820.

Berg, B.; Ekbohm, G.; Johansson, M.B.; McClaugherty, C.; Rutigliano, F.; De Santo, A.V. 1996. Maximum decomposition limits of forest litter types: a synthesis. Canadian Journal of Botany. 74: 659-672.

Binkley, D. 1995. The influence of tree species on forest soils: processes and patterns. In: Special Publication 10, Wellington, New Zealand: Agronomy Society of New Zealand. 1-33.

Binkley, D.; Sollins, P.; Bell, R.; Sachs, D.; Myrold, D. 1992. Biogeochemistry of adjacent conifer and alder-conifer stands. Ecology. 73: 2022-2033.

Birdsey, R.A. 1992. Carbon storage and accumulation in United States forest ecosystems. Gen. Tech. Rep. WO-59. Washington, DC: U.S. Department of Agriculture, Forest Service. 51 p.

Birdsey, R.A. 1996. Carbon storage for major forest types and regions in the coterminous United States. In: Sampson, R.N.; Hair, D., eds. Forests and global change: Forest management opportunities for mitigating carbon emissions. Washington, DC: American Forests: 1-25. Birdsey, R.A.; Heath, L.S. 1995. Carbon changes in U.S. forests. In: Joyce, L.A., ed. Productivity of America’s forests and climate change. Gen. Tech. Rep. RM-271. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station: 56-70.

Clinton, B.D.; Vose, J.M.; Swank, W.T. 1996. Shifts in aboveground and forest floor carbon and nitrogen pools after felling and burning in the southern Appalachians. Forest Science. 42: 431-441.

Cole, D.W.; Rapp, M. 1981. Elemental cycling in forest ecosystems. In: Reichle, D.E., ed. Dynamic properties of forest ecosystems. Cambridge, UK: Cambridge University Press: 341-409.

Covington, W.W. 1981. Changes in forest floor organic matter and nutrient content following clear cutting in northern hardwoods. Ecology. 62: 41-48.

Covington, W.W.; Aber, J.D. 1980. Leaf production during secondary succession in northern hardwoods. Ecology. 61: 200-204.

Cromack, K.; Miller, R.E.; Helgerson, O.T.; Smith, R.B.; Anderson, H.W. 1999. Soil carbon and nutrients in a coastal Oregon Douglas-fir plantation with red alder. Soil Science Society of America Journal. 63: 232-239.

Dyrness, C.T.; Van Cleve, K.; Levison, J.D. 1989. The effect of wildfire on soil chemistry in four forest types in interior Alaska. Canadian Journal of Forest Research. 19: 1389-1396.

Edmonds, R.L.; Chappell, H.N. 1994. Relationships between soil organic matter and forest productivity in western Oregon and Washington. Canadian Journal of Forest Research. 24: 1101-1106.

Fassnacht, K.S.; Gower, S.T. 1999. Comparison of the litterfall and forest floor organic matter and nitrogen dynamics of upland forest ecosystems in north central Wisconsin. Biogeochemistry. 45: 265- 284.

Federer, C.A. 1982. Subjectivity in the separation of organic horizons of the forest floor. Soil Science Society of America Journal. 46: 1090-1093.

Federer, C.A. 1984. Organic matter and nitrogen content of the forest floor in even-aged northern hardwoods. Canadian Journal of Forest Research. 14: 763-767.13 Finzi, A.C.; Van Breemen, N.; Canham, C.D. 1998. Canopy tree-soil interactions within temperature forests: species effects on soil carbon and nitrogen. Ecological Applications. 8: 440-446.

Fried, J.S.; Boyle, J.R.; Tappeiner, J.C.I.; Cromack, K.J. 1990. Effects of bigleaf maple on soils in Douglasfir forests. Canadian Journal of Forest Research. 20: 259-266.

Gholz, H.L.; Perry, C.S.; Cropper, W.P.J.; Hendry, L.C. 1985. Litterfall, decomposition, and nitrogen and phosphorus dynamics in a chronosequence of slash pine ( Pinus elliottii ) plantations. Forest Science. 31: 463-478.

Grigal, D.F.; Ohmann, L.F. 1992. Carbon storage in upland forests of the Lake States. Soil Science Society of America Journal. 56: 935-943.

Heath, L.S.; Birdsey, R.A. 1993. Carbon trends of productive temperate forests of the coterminous United States. Water, Air, and Soil Pollution. 70: 279- 293.

Heath, L.S.; Birdsey, R.A.; Row, C.; Plantinga, A.J. 1996. Carbon pools and flux in U.S. forest products. In: Apps, M.J.; Price, D.T., eds. Forest Ecosystems, Forest Management, and the Global Carbon Cycle. Berlin, Germany: Springer Verlag: 271-278.

Heath, L.S.; Smith, J.E. 2000. An assessment of uncertainty in forest carbon budget projections. Environmental Science and Policy. 3: 73-82.

Hendrickson, O.Q.; Chatarpaul, L.; Burgess, D. 1989. Nutrient cycling following whole-tree and conventional harvest in northern mixed forest. Canadian Journal of Forest Research. 19: 725-735.

Homann, P.S.; Grigal, D.F. 1996. Below-ground organiccarbon and decomposition potential in a fieldforest glacial-outwash landscape. Biology and Fertility of Soils. 23: 207-214.

Hough, W.A. 1982. Phytomass and nutrients in the understory and forest floor of slash/longleaf pine stands. Forest Science. 28: 359-372.

Huntington, T.G.; Johnson, C.E.; Johnson, A.H.; Siccama, T.G.; Ryan, D.F. 1989. Carbon organic matter and bulk density relationships in a forested spodosol. Soil Science. 148: 380-386. Hyvonen, R.; Agren, G.I.; Bosatta, E. 1998. Predicting long-term soil carbon storage from short-term information. Soil Science Society of America Journal. 62: 1000-1005.

Johnson, C.E.; Driscoll, C.T.; Fahey, T.J.; Siccama, T.G.; Hughes, J.W. 1995. Carbon dynamics following clear-cutting of a northern hardwood forest. In: McFee, W.W.; Kelly, J.M., eds. Carbon forms and functions in forest soils. Madison, WI: Soil Science Society of America: 463-488.

Johnson, C.E.; Johnson, A.H.; Huntington, T.G.; Siccama, T.G. 1991. Whole-tree clear-cutting effects on soil horizons and organic-matter pools. Soil Science Society of America Journal. 55: 497-502.

Johnson, C.M.; Zarin, D.J.; Johnson, A.H. 2000. Postdisturbance aboveground biomass accumulation in global secondary forests. Ecology. 81: 1395-1401.

Lang, G.E.; Forman, R.T.T. 1978. Detrital dynamics in a mature oak forest: Hutcheson Memorial Forest, New Jersey. Ecology. 59: 580-595.

Liechty, H.O.; Jurgensen, M.F.; Mroz, G.D.; Gale, M.R. 1997. Pit and mound topography and its influence on storage of carbon, nitrogen, and organic matter within an old-growth forest. Canadian Journal of Forest Research. 27: 1992-1997.

Little, S.N.; Ohmann, J.L. 1988. Estimating nitrogen lost from forest floor during prescribed fires in Douglas-fir/western hemlock clearcuts. Forest Science. 34: 152-164.

Lockaby, B.G.; Taylor-Boyd, J.E. 1986. Nutrient dynamics in the litter fall and forest floor of an 18- year-old loblolly pine plantation. Canadian Journal of Forest Research. 16: 1109-1112.

Mattson, K.G.; Smith, H.C. 1993. Detrital organic matter and soil CO 2 efflux in forests regenerating from cutting in West Virginia. Soil Biology and Biochemistry. 25: 1241-1248.

McClaugherty, C.A.; Pastor, J.; Aber, J.D.; Melillo, J.M. 1985. Forest litter decomposition in relation to soil nitrogen dynamics and litter quality. Ecology. 66: 266-275.

Means, J.E.; MacMillan, P.C.; Cromack, K.J. 1992. Biomass and nutrient content of Douglas-fir logs and other detrital pools in an old-growth forest,14 Oregon, U.S.A. Canadian Journal of Forest Research. 22: 1536-1546.

Nemeth, J.C. 1973. Dry matter production in young loblolly ( Pinus teada L.) and slash pine ( Pinus elliottii Engelm.) plantations. Ecological Monographs. 43: 21-41.

Olsson, B.A.; Staaf, H.; Lundkvist, H.; Bengtsson, J.; Rosen, K. 1996. Carbon and nitrogen in coniferous forest soils after clear-felling and harvests of different intensity. Forest Ecology and Management. 82: 19-32.

Perala, D.A.; Alban, D.H. 1982a. Biomass, nutrient distribution and litterfall in Populus
, Pinus and Picea stands on two different soils in Minnesota. Plant and Soil. 64: 177-192.

Perala, D.A.; Alban, D.H. 1982b. Rates of forest floor decomposition and nutrient turnover in aspen, pine, and spruce stands on two different soils. Res. Pap. NC-227. St Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 5 p.

Plantinga, A.J.; Birdsey, R.A. 1993. Carbon fluxes resulting from US private timberland management. Climatic Change. 23: 37-53.

Rollinger, J.L.; Strong, T.F.; Grigal, D.F. 1998. Forested soil carbon storage in landscapes of the Northern Great Lakes Region. In: Lal, R.; Kimble, J.M.; Follett, R.F.; Stewart, B.A., eds. Management of carbon sequestration in soil. Boca Raton, FL: CRC Press: 335- 350.

Rotter, J.; Danish, K. 2000. Forest carbon and the Kyoto Protocol’s clean development mechanism. Journal of Forestry. 98: 38-47.

Ryan, D.F.; Huntington, T.G.; Martin, C.W. 1992. Redistribution of soil nitrogen, carbon and organicmatter by mechanical disturbance during wholetree harvesting in northern hardwoods. Forest Ecology and Management. 49: 87-99.

Schiffman, P.M.; Johnson, W.C. 1989. Phytomass and detrital carbon storage during forest regrowth in the southeastern United States Piedmont. Canadian Journal of Forest Research. 19: 69-78.

Schlesinger, W.H. 1977. Carbon balance in terrestrial detritus. Annual Review of Ecology and Systematics. 8: 51-81. Simmons, J.A.; Fernandez, I.J.; Briggs, R.D.; Delaney, M.T. 1996. Forest floor carbon pools and fluxes along a regional climate gradient in Maine, USA. Forest Ecology and Management. 84: 81-95.

Skog, K.E.; Nicholson, G.A. 1998. Carbon cycling through wood products: the role of wood and paper products in carbon sequestration. Forest Products Journal. 48: 75-83.

Smith, J.E.; Heath, L.S. 2000. Considerations for interpreting probabilistic estimates of uncertainty of forest carbon. In: Joyce, L.; Birdsey, R., eds. The Impact of Climate Change on America’s Forests. Gen. Tech. Rep. RMRS-GTR-59. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station: 102-111.

Smith, F.W.; Resh, S.C. 1999. Age-related changes in production and below-ground carbon allocation in Pinus contorta forests. Forest Science. 45: 333-341.

Smith, W.B.; Vissage, J.S.; Darr, D.R.; Sheffield, R.M.
2001. Forest resources of the United States, 1997. Gen. Tech. Rep. NC-219. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Research Station. 190 p.

Strong, T.F. 1997. Harvesting intensity influences the carbon distribution in a northern hardwood
ecosystem. Res. Pap. NC-329. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Research Station. 7 p.

Snyder, K.E.; Harter, R.D. 1987. Forest floor dynamics in even-aged northern hardwood stands. Soil Science Society of America Journal. 51: 1381-1383.

Switzer, G.K.; Shelton, M.G.; Nelson, L.E. 1979. Successional development of the forest floor and soil surface on upland sites of the east gulf coastal plain. Ecology. 60: 1162-1171.

Tans, P.P.; White, J.W.C. 1998. The global carbon cycle: in balance, with a little help from the plants. Science. 281: 183-184.

Turner, J.; Long, J.N. 1975. Accumulation of organic matter in a series of Douglas-fir stands. Canadian Journal of Forest Research. 5: 681-690.

U.S. Department of State. 2000. U.S. Submission to UNFCCC on Land-Use, Land-Use Change, and Forestry. <http://www.state.gov/www/global/15 global_issues/climate/climate_2000_submiss.html> (5 April 2002).

Vitousek, P.M.; Gosz, J.R.; Grier, C.C.; Melillo, J.M.; Reiners, W.A. 1982. A comparative analysis of potential nitrification and nitrate mobility in forest
ecosystems. Ecological Monographs. 52: 155-177.

Vogt, K.A.; Grier, C.C.; Vogt, D.J. 1986. Production, turnover, and nutrient dynamics of above- and belowground detritus of world forests. Advances in Ecological Research. 15: 303-377.

Vogt, K.A.; Vogt, D.J.; Brown, S.; Tilley, J.P.; Edmonds, R.L.; Silver, W.L.; Siccama, T.G. 1995. Dynamics of forest floor and soil organic matter accumulation in boreal, temperate, and tropical forests. In: Lal, R.; Kimble, J.; Levine, E.; Stewart, B.A., eds. Soil management and greenhouse effect. Boca Raton, FL: CRC Lewis Publishers: 159-178. Vogt, K.A.; Vogt, D.J.; Palmiotto, P.A.; Boon, P.; O‘Hara, J.; Asbjornsen, H. 1996. Review of root dynamics in forest ecosystems grouped by climate, climatic forest type and species. Plant and Soil. 187: 159-219.

Vose, J.M.; Swank, W.T.; Clinton, B.D.; Knoepp, J.D.; Swift, L.W. 1999. Using stand replacement fires to restore southern Appalachian pine-hardwood ecosystems: effects on mass, carbon, and nutrient pools. Forest Ecology and Management. 114: 215- 226.

Waring, R.; Schlesinger, W. 1985. Forest ecosystems: concepts and management. Orlando, FL: Academic Press. 340 p.

Yanai, R.D.; Arthur, M.A.; Siccama, T.G.; Federer, C.A.
2000. Challenges of measuring forest floor organic matter dynamics: Repeated measures from a chronosequence. Forest Ecology and Management. 138: 273-283.16 

## Appendix

Table A1.—Forest floor carbon mass values obtained from literature.

Column headings: R Regions used for summarizing values (see Figure 1) C Carbon mass used for each observation, Mg C per hectare ff Form of forest floor mass for each observation: c, as carbon; o, as ash-free organic matter converted to carbon by multiplying by 0.55; and d, as dry weight converted to carbon by multiplying by 0.37 T Forest type assigned for use in our analysis (see Tables A2, 1, and 4) D Summary of forest composition from publication L State, province, or region (LS=Lake States, IM=Intermountain) A Years since major disturbance, or: m if information suggested mature; y, if information suggested not yet mature; and blank indicates that information was not provided but these were assumed to be mature La Latitude, degrees north Lo Longitude, degrees west E Elevation (km) c:dw Ratio of forest floor carbon mass to dry weight, if given mrt Mean residence time of forest floor, in years (forest floor biomass divided by annual biomass input) rf Form of biomass in mrt, if reported: c, as carbon; o, as ash-free organic matter; and d, as dry weight cite Citation

R C ff T D L A a La a Lo a E a c:dw mrt rf cite b
(Mg/ha) (years) (km) (years)
N p jack pine LS 0.35 99 N p red pine LS 0.35 99 N 4.5 d p jack pine MN 47 0.4 5.7 138 N 9.6 d p jack pine MN 47 0.4 12.5 138 N 8.9 d p jack pine MN 47 0.4 11.9 138 N 11.5 d p pine MN 47 0.4 13.6 138 N 7.7 d p white pine MN 47 0.4 10.4 138 N 15.4 d p pine MA 53 42 0.4 7.8 139 N 14.4 o p red pine plantation MN 90 2 N 16.5 o p red pine MN m 47 95 0.4 5 N 18.2 o p jack pine MN m 47 95 0.4 5 N 11.4 o p red pine plantation WI 37 44 90 0.4 18 N 10.1 o p red pine plantation WI 37 44 90 0.4 18 N 9.7 d p jack pine plantation LS 15-43 22 N 13.6 d p red pine plantation LS 21-180 22 N 13.0 d p jack pine MN m 48 92 0.5 45 N 18.6 d p jack pine MN m 48 92 0.5 45 N 16.0 c p jack pine LS 50 N 14.0 c p red pine LS 50 N 13.1 d p jack pine North 83 83, v N 16.0 o p white pine MA 34-96 42 72 0.1 85 N 5.5 o p white pine WI m 43 40 0.3 3.2 o 90 N 16.9 c p jack pine MN 39 47 95 0.4 5.8 c 104 N 13.5 c p jack pine MN 41 47 95 0.4 5.5 c 104 N 15.8 c p red pine MN 39 47 95 0.4 4.7 c 104 N 14.9 c p red pine MN 41 47 95 0.4 5.2 c 104 N 22.9 c p red pine plantation LS 105, 112 N 12.1 c p pine plantation IL 111, 114

Continued17 N 5.4 d p red pine MN m 47 93 0.4 4.1 d 126 N 19.8 c p red pine plantation MA 55 43 72 0.4 0.32 8.5 d 136 N 7.6 c p shortleaf pine plantation IN 33 39 86 0.2 0.44 3.5 d 136 N sf balsam fir LS 0.36 99 N 18.2 o sf spruce MN m 47 95 0.4 5 N 21.1 d sf hemlock MI, WI m 46 89 0.5 17 N 35.5 d sf spruce - fir North 8 28, v N 35.5 d sf spruce - fir North 8 28, v N 45.9 d sf spruce - fir North 8 28, v N 42.2 d sf spruce - fir North 8 28, v N 41.3 c sf hemlock CT 42 73 0.4 38 N 23.0 c sf balsam fir LS 50 N 68.1 o sf eastern hemlock MI m 46 89 0.5 57 N 43.0 c sf balsam fir NH m 44 72 1.3 0.38 76 N 4.6 o sf hemlock WI m 43 40 0.3 6.5 o 90 N 17.6 c sf spruce MN 39 47 95 0.4 7 c 104 N 14.1 c sf spruce MN 41 47 95 0.4 5.8 c 104 N 46.5 o sf fir NH 44 72 1.4 108 N 54.3 o sf fir NH 44 72 1.4 108 N 54.5 o sf fir NH 44 72 1.4 108 N 64.4 o sf fir NH 44 72 1.4 108 N 66.6 o sf fir NH 44 72 1.4 108 N 45.5 o sf spruce fir NH 44 72 1.0 108 N 47.0 c sf balsam fir NH 75 44 72 1.2 0.4 29.1 d 136 N 5.4 d mx mixed, oak-pine RI m 42 72 0.1 20 N 7.3 o mx mixed WI 35 N 18.4 o mx conifer - hardwood ON m 45 77 0.2 56 N 22.1 o mx conifer - hardwood ON 3 45 77 0.2 56 N 18.0 o mx conifer - hardwood ON 3 45 77 0.2 56 N 75.0 c mx hemlock - hardwood MI m 46 87 0.3 0.39 79 N 25.0 c mx aspen, jack pine North m 112 N 24.4 c mx oak - pine MA 65 42 70 0.0 0.42 13.8 d 136 N ab aspen LS 0.32 99 N 2.3 d ab paper birch MN 45 0.4 2.3 138 N 14.9 o ab aspen MN m 47 95 0.4 5 N 20.9 d ab aspen MI 47 47 89 0.5 4 N 7.0 d ab aspen MN 60 47 93 0.4 4 N 16.8 d ab aspen MN 66 47 95 0.4 4 N 16.6 c ab aspen MN 70 48 94 0.4 3 N 13.4 c ab aspen MN 70 48 94 0.4 3 N 10.7 d ab aspen - birch North 8, 20 N 15.0 c ab aspen LS 50 N 11.8 d ab aspen North 81 83, v N 2.9 o ab aspen WI m 43 40 0.3 1.6 o 90 N 3.1 d ab aspen WI m 46 90 0.5 1.8 d 102 N 13.5 c ab aspen MN 40 47 95 0.4 6.7 c 104 N 11.6 c ab aspen MN 49 47 95 0.4 6.1 c 104 N 5.7 d ab trembling aspen WI 8 45 90 0.4 113 N 6.3 d ab trembling aspen WI 14 45 90 0.4 113 Table A1.—Continued

Continued R C ff T D L A a La a Lo a E a c:dw mrt rf cite b
(Mg/ha) (years) (km) (years)18 N 2.7 d ab trembling aspen WI 18 45 90 0.4 113 N 6.3 d ab trembling aspen WI 32 45 90 0.4 113 N 2.9 d ab trembling aspen WI 63 45 90 0.4 113 N 8.6 d ab birch-aspen MI m 48 89 0.2 122 N 2.3 d ab birch MN m 47 93 0.4 2 d 126 N mb sugar maple LS 0.29 99 N 1.9 d mb maple WI 35 43 0.3 1.8 139 N 9.8 d mb sugar maple MI, WI 46 89 6, v N 10.8 d mb sugar maple MI, WI 50 46 89 6, v N 18.9 d mb northern hardwood MI, WI m 46 89 0.5 17 N 26.4 o mb maple - beech - birch NH 60 44 0.6 8.2 o 25 N 35.8 o mb maple - beech - birch NH 1 44 71 0.7 36 N 28.6 o mb maple - beech - birch NH 4 44 71 0.7 36 N 22.6 o mb maple - beech - birch NH 10 44 71 0.7 36 N 27.5 o mb maple - beech - birch NH 13 44 71 0.7 36 N 27.0 o mb maple - beech - birch NH 24 44 71 0.7 36 N 38.5 o mb maple - beech - birch NH 31 44 71 0.7 36 N 25.9 o mb maple - beech - birch NH 34 44 71 0.7 36 N 36.3 o mb maple - beech - birch NH 40 44 71 0.7 36 N 28.6 o mb maple - beech - birch NH 44 44 71 0.7 36 N 46.2 o mb maple - beech - birch NH 70 44 71 0.7 36 N 38.5 o mb maple - beech - birch NH 100 44 71 0.7 36 N 41.3 o mb maple - beech - birch NH 100 44 71 0.7 36 N 52.3 o mb maple - beech - birch NH 100 44 71 0.7 36 N 23.1 c mb beech CT 42 73 0.4 38 N 21.2 c mb red maple CT 42 73 0.4 38 N 12.1 c mb sugar maple CT 42 73 0.4 0.38 38 N 25.7 o mb northern hardwood NH 60 44 72 0.7 8.2 o 43 N 18.0 c mb sugar maple, hardwood LS 50 N 47.0 o mb maple - beech - birch MI m 46 89 0.5 57 N 30.0 c mb maple - beech - birch NH 65 44 72 0.6 0.34 61 N 31.0 c mb northern hardwood NH m 44 72 0.6 62 N 39.0 c mb northern hardwood NH 3 44 72 0.6 62 N 22.0 c mb northern hardwood NH 8 44 72 0.6 62 N 22.0 c mb northern hardwood MI m 46 87 0.3 0.29 79 N 10.8 o mb northern hardwood LS y 86 N 12.6 o mb northern hardwood LS m 86 N 14.2 o mb northern hardwood LS m 86 N 2.8 o mb sugar maple WI m 43 40 0.3 1.3 o 90 N 14.9 c mb maple - birch ON 225 47 84 96 N 20.2 c mb maple - beech - birch NY 100 44 74 96 N 9.2 d mb northern hardwood MI 51 47 89 0.3 97 N 14.2 d mb northern hardwood MI 51 47 89 0.3 97 N 22.5 d mb northern hardwood MI 49 47 89 0.3 97 N 5.4 d mb northern hardwood MI 3 47 89 0.3 97 N 6.3 d mb northern hardwood MI 3 47 89 0.3 97 N 6.5 d mb northern hardwood MI 3 47 89 0.3 97 N 16.8 c mb northern hardwood LS 105, 112 N 118.3 o mb northern hardwood NH 44 72 0.7 108 Table A1.—Continued

Continued R C ff T D L A a La a Lo a E a c:dw mrt rf cite b
(Mg/ha) (years) (km) (years)19 N 42.3 c mb maple - beech - birch ME >80 47 69 0.3 0.37 35.8 c 117 N 32.7 c mb maple - beech - birch ME >80 45 68 0.1 0.44 28.7 c 117 N 32.8 c mb maple - beech - birch ME >80 44 70 0.2 0.41 26.5 c 117 N 27.1 c mb maple - beech - birch ME >80 44 69 0.2 0.34 19 c 117 N 89.5 c mb northern hardwood NH 93 44 71 0.7 0.47 120 N 72.1 c mb northern hardwood NH 3 44 71 0.7 0.4 120 N 37.6 c mb northern hardwood NH 10 44 71 0.7 0.42 120 N 39.4 c mb northern hardwood NH 30 44 71 0.7 0.33 120 N 3.6 c mb maple IN 95 39 86 0.2 0.37 1.9 d 136 N 25.1 c mb northern hardwood NH 66 44 72 0.7 0.43 12.3 d 136 N 21.6 c mb maple - beech - birch NH m 44 72 0.7 8.4 c 144 N 12.4 d oh oak - maple MA 80 42 0.4 7.6 139 N 5.4 d oh black oak MO 20 38 91 0.4 27 N 7.4 d oh black oak MO 40 38 91 0.4 27 N 1.7 d oh oak WI 43 0.3 1.1 29, 139 N 5.1 o oh hardwood WI 35 N 30.7 c oh red oak CT 42 73 0.4 38 N 12.1 c oh white ash CT 42 73 0.4 38 N 16.0 c oh broad leaf deciduous LS 50 N 9.2 c oh oak MN 67 45 93 0.2 58 N 6.5 c oh oak MN 67 45 93 0.2 58 N 4.7 c oh oak MN 67 45 93 0.2 58 N 7.3 c oh oak MN 67 45 93 0.2 58 N 7.0 c oh oak MN 67 45 93 0.2 58 N 7.5 c oh oak MN 67 45 93 0.2 58 N 4.4 c oh oak MN 67 45 93 0.2 58 N 8.5 c oh upland deciduous MN y 45 93 0.2 64 N 4.8 c oh upland deciduous MN y 45 93 0.2 64 N 8.4 o oh mixed oak NJ 250 41 0.0 6.2 o 77 N 5.8 d oh oak MO 40 38 91 0.4 82 N 4.3 d oh hardwood WV 1 40 80 0.6 88 N 4.8 d oh hardwood WV m 40 80 0.6 88 N 4.1 d oh hardwood WV 2 40 80 0.6 88 N 8.1 d oh hardwood WV m 40 80 0.6 88 N 2.3 d oh hardwood WV 2 40 80 0.6 88 N 5.2 d oh hardwood WV m 40 80 0.6 88 N 2.8 d oh hardwood WV 4 40 80 0.6 88 N 3.9 d oh hardwood WV m 40 80 0.6 88 N 4.6 d oh hardwood WV 4 40 80 0.6 88 N 5.9 d oh hardwood WV m 40 80 0.6 88 N 6.3 d oh hardwood WV 6 40 80 0.6 88 N 5.7 d oh hardwood WV m 40 80 0.6 88 N 2.8 d oh hardwood WV 7 40 80 0.6 88 N 4.3 d oh hardwood WV m 40 80 0.6 88 N 6.5 d oh hardwood WV 7 40 80 0.6 88 N 8.8 d oh hardwood WV m 40 80 0.6 88 N 2.4 d oh hardwood WV 8 40 80 0.6 88 N 6.3 d oh hardwood WV m 40 80 0.6 88 N 5.0 d oh hardwood WV 11 40 80 0.6 88 Table A1.—Continued

Continued R C ff T D L A a La a Lo a E a c:dw mrt rf cite b
(Mg/ha) (years) (km) (years)20 N 7.6 d oh hardwood WV m 40 80 0.6 88 N 2.9 d oh hardwood WV 20 40 80 0.6 88 N 8.3 d oh hardwood WV m 40 80 0.6 88 N 2.3 d oh hardwood WV 20 40 80 0.6 88 N 3.5 d oh hardwood WV m 40 80 0.6 88 N 5.6 d oh hardwood WV 23 40 80 0.6 88 N 4.0 d oh hardwood WV m 40 80 0.6 88 N 3.8 d oh hardwood WV 23 40 80 0.6 88 N 7.8 d oh hardwood WV m 40 80 0.6 88 N 5.3 d oh hardwood WV 23 40 80 0.6 88 N 9.1 d oh hardwood WV m 40 80 0.6 88 N 3.0 o oh white oak WI m 43 40 0.3 1.8 o 90 N 33.7 o oh oak MN 50 45 93 0.2 19 o 107 N 34.1 o oh oak MN 50 45 93 0.2 14.1 o 109, 77 N 2.8 o oh oak - hickory MO 35-92 39 1.6 o 110, 77 N 8.6 c oh oak IN 81 39 86 0.2 0.44 2.9 d 136 N 19.0 c oh oak - red maple MA 50 43 72 0.4 0.32 12.2 d 136 N 3.8 d oh oak North 115-120 148, v N 3.6 d oh oak North 115-120 148, v N 2.8 d oh oak North 115-120 148, v N 6.9 o conifer WI 35 N 17.0 c needle leaf evergreen LS 50 N 10.9 c upland conifer MN y 45 93 0.2 64 N 100.0 c lowland conifer MN y 45 93 0.2 64 N 31.4 c black spruce wetland MI m 46 87 0.3 92 N 8.9 c black spruce wetland MI 5 46 87 0.3 92 N 12.7 c black spruce wetland MI 5 46 87 0.3 92 N 503.3 o cedar swamp MN 100 45 93 0.2 265 o 107 N 172.2 o krummholz spruce - fir NH 44 72 1.4 108 N 29.9 o krummholz spruce - fir NH 44 72 1.4 108 N 47.9 o krummholz spruce - fir NH 44 72 1.4 108 N 53.7 o krummholz spruce - fir NH 44 72 1.4 108 N 104.0 c lowland deciduous MN y 45 93 0.2 64

S 3.0 d p pine FL 7 3.1 139 S 12.2 d p pine FL 27 6.5 139 S 6.9 d p loblolly pine SC 34 0.2 3.7 138 S 5.4 d p loblolly pine SC 34 0.2 3.4 138 S 9.7 d p shortleaf pine SC 34 0.2 7.9 138 S 15.1 o p loblolly pine plantation SC 56 33 80 0.0 10 S 10.3 o p loblolly pine plantation SC 56 33 80 0.0 10 S 9.5 o p loblolly pine plantation SC 56 33 80 0.0 10 S 16.3 o p loblolly pine plantation SC 56 13 S 14.1 o p loblolly pine plantation SC 56 13 S 20.9 o p loblolly pine plantation SC 56 33 80 0.0 14 S 1.4 d p longleaf pine South m 31 87 0.1 1.9 d 21 S 14.9 o p shortleaf pine TN 30 36 0.3 6.5 o 25 S 17.2 d p pine TN 30 36 0.3 13.7 29, 139 S 5.3 d p white pine NC 35 0.8 3.9 29, 139 Table A1.—Continued

Continued R C ff T D L A a La a Lo a E a c:dw mrt rf cite b
(Mg/ha) (years) (km) (years)21 S 7.8 c p loblolly pine TN m 36 84 0.2 0.29 41 S 16.1 o p pitch - Virginia pine South 51, v S 13.1 o p pitch - Virginia pine South 51, v S 17.8 o p pitch - Virginia pine South 51, v S 10.1 o p slash pine plantation FL 25 52 S 2.2 d p loblolly pine NC 35 0.1 1.2 53, 138 S 9.2 c p slash - loblolly pine South 37 60 S 9.7 o p slash pine plantation FL 16 31 82 0.0 65 S 16.8 c p loblolly pine NC 19 36 79 0.2 4.3 c 66 S 19.5 c p loblolly pine NC 40 36 79 0.2 5.1 c 66 S 9.0 c p loblolly pine plantation NC 14 36 0.1 3 69 S 13.4 d p loblolly pine plantation SC 14 74 S 7.3 d p loblolly pine South 7 75, v S 5.8 d p loblolly pine South 7 75, v S 4.1 d p loblolly pine plantation LA 19 32 92 0.1 1.7 d 81 S 14.4 o p loblolly pine SC 70 33 80 0.0 91 S 7.6 o p longleaf pine AL 65 31 87 0.1 91 S 21.9 o p longleaf pine LA 65 32 92 0.0 91 S 16.0 o p longleaf - slash pine FL 65 30 82 0.0 91 S 7.3 d p loblolly - shortleaf pine South 25 94, v S 13.6 o p loblolly pine VA 16 37 79 0.2 95 S 8.3 o p shortleaf pine VA 16 37 79 0.2 95 S 9.1 o p Virginia pine VA 16 37 79 0.2 95 S 5.9 o p white pine VA 16 37 79 0.2 95 S 1.4 d p loblolly - slash pine NC 5 35 77 0.0 98 S 1.4 d p loblolly - slash pine NC 7 35 77 0.0 98 S 2.1 d p loblolly - slash pine NC 8 35 77 0.0 1.6 98 S 2.1 d p loblolly - slash pine NC 10 35 77 0.0 1.6 98 S 2.1 d p loblolly - slash pine NC 11 35 77 0.0 1.6 98 S 10.5 d p slash pine GA 22 32 84 0.2 103 S 1.6 c p loblolly & Virginia pine VA 1 38 78 0.1 114 S 1.7 c p loblolly & Virginia pine VA 2 38 78 0.1 114 S 5.1 c p loblolly & Virginia pine VA 3 38 78 0.1 114 S 3.5 c p loblolly & Virginia pine VA 5 38 78 0.1 114 S 6.1 c p loblolly & Virginia pine VA 8 38 78 0.1 114 S 4.8 c p loblolly & Virginia pine VA 11 38 78 0.1 114 S 9.1 c p loblolly & Virginia pine VA 14 38 78 0.1 114 S 8.6 c p loblolly & Virginia pine VA 17 38 78 0.1 114 S 7.3 c p loblolly & Virginia pine VA 20 38 78 0.1 114 S 10.4 c p loblolly & Virginia pine VA 23 38 78 0.1 114 S 10.1 c p loblolly & Virginia pine VA 26 38 78 0.1 114 S 16.2 c p loblolly & Virginia pine VA 25 38 78 0.1 114 S 7.4 c p loblolly & Virginia pine VA 32 38 78 0.1 114 S 7.6 c p loblolly & Virginia pine VA 34 38 78 0.1 114 S 8.8 c p loblolly & Virginia pine VA 35 38 78 0.1 114 S 11.8 c p loblolly & Virginia pine VA 36 38 78 0.1 114 S 11.8 c p loblolly & Virginia pine VA 40 38 78 0.1 114 S 14.5 c p loblolly & Virginia pine VA 46 38 78 0.1 114 S 9.3 c p loblolly & Virginia pine VA 47 38 78 0.1 0.38 114 Table A1.—Continued

Continued R C ff T D L A a La a Lo a E a c:dw mrt rf cite b
(Mg/ha) (years) (km) (years)22 S 10.4 o p loblolly pine NC 55 36 79 115 S 8.9 o p loblolly pine NC 55 36 79 115 S 11.7 o p loblolly pine NC 55 36 79 115 S 5.6 d p loblolly pine plantation MS 18 124, 81 S 9.7 c p pine MS 25 33 89 0.1 125 S 10.3 c p pine MS 40 33 89 0.1 125 S 6.9 d p loblolly pine plantation SC 17 132 S 7.7 d p loblolly pine plantation SC 18 134, 81 S 11.1 d p loblolly pine plantation NC 16 143, 81 S 6.1 d p loblolly pine South 12 146 S 9.6 c mx conifer - hardwood NC, TN m 36 84 0.9 0.24 41 S 16.8 c mx pine - hardwood NC, TN m 36 84 1.7 0.32 94, v S 6.7 d mx hardwood - pine South 40 125 S 7.6 c mx mixed MS 200 33 89 0.1 125 S 9.6 c mx pine - hardwood MS 130 33 89 0.1 125 S 11.3 c mx pine - hardwood MS 65 33 89 0.1 140 S 14.3 c mx pine - hardwood NC 35 84 1.4 0.46 140 S 16.4 c mx pine - hardwood NC 35 84 1.4 0.41 140 S 12.6 c mx pine - hardwood NC 35 84 1.4 0.39 141 S 19.8 c mx pine - hardwood NC 35 84 1.4 0.46 141 S 10.6 c mx pine - hardwood NC 35 84 1.4 0.46 141 S 8.7 c mx hickory NC 35 84 1.4 0.46 138 S 3.3 d hw oak SC 34 0.2 1.9 138 S 5.4 d hw yellow poplar SC 34 0.2 3.7 138 S 5.0 d hw mixed hardwood SC 34 0.2 3.2 139 S 3.3 d hw Nyssa - Acer VA 78 1.4 139 S 2.4 d hw oak - hickory VA 52 1 11 S 4.2 d hw oak - hickory NC m 35 84 0.9 11 S 4.3 d hw oaks NC m 35 84 0.9 16, 77 S 2.3 o hw Liriodendron TN 75 36 25 S 3.3 o hw Liriodendron , hardwood TN 50 36 0.2 1.4 o 25 S 0.8 o hw oak - hickory TN 30-80 36 0.3 0.4 o 25 S 14.9 o hw chestnut oak TN 30-80 36 0.3 5.6 o 25 S 13.8 o hw oak - hickory TN 30-80 36 0.3 5.6 o 25 S 5.2 o hw Liriodendron NC 60-200 35 0.8 2.2 o 29, 139 S 8.7 d hw maple - oak TN 55 36 0.3 6.3 29, 139 S 3.5 d hw mixed hardwood NC 35 0.9 2.2 41 S 6.6 c hw mixed hardwood TN m 36 84 0.3 0.21 41 S 24.8 c hw chestnut oak NC, TN m 36 84 1.0 0.34 77 S 5.2 o hw oak - hickory TN 36 0.3 5.4 o 77 S 5.6 o hw oak - hickory TN 36 0.3 4.6 o 77 S 2.6 o hw oak - hickory GA 150 32 77 S 3.7 o hw oak FL 100 28 0.0 77 S 3.7 o hw oak - hickory NC 36 0.8 4.9 o 89 S 7.4 o hw oak - hickory NC 4 35 83 1.0 89 S 12.0 o hw oak - hickory NC 7 35 83 0.9 89 S 6.3 o hw hardwood NC 50 35 83 0.9 94, v S 4.6 d hw oak - hickory South 12 94, 77 S 4.5 o hw scrub oak SC 150 34 1.9 o 103 Table A1.—Continued

Continued R C ff T D L A a La a Lo a E a c:dw mrt rf cite b
(Mg/ha) (years) (km) (years)23 S 4.3 d hw hardwood GA 22 32 84 0.2 116 S 3.0 d hw hardwood NC m 31 87 0.9 116 S 3.6 d hw hardwood NC 0 31 87 0.9 116 S 3.3 d hw pin oak NC m 31 87 0.8 118, 77 S 2.6 d hw upland hardwood NC m 35 127 S 7.0 c hw oak TN 36 84 0.3 0.36 133 S 3.4 d hw red spruce SC 35 83 41 S 53.8 c conifer - hardwood NC, TN m 36 84 1.7 0.36 41 S 2.4 d Chamaecyparis VA 57 0.9 139 S 2.5 d Taxodium VA 86 1 139

P 8.6 d df Douglas-fir WA 40 47 11.6 139 P 5.0 d df Douglas-fir OR 44 0.3 5.6 138 P 10.7 d df Douglas-fir OR 70 44 0.6 14.5 139 P 2.6 d df Douglas-fir OR 43 44 2.6 139 P 12.4 d df alder, Douglas-fir BC 23 50 124 0.5 12 P 8.5 d df alder, Douglas-fir WA 25 48 122 0.0 12 P 2.6 d df Douglas-fir BC 23 50 124 0.5 12 P 7.8 d df Douglas-fir WA 25 48 122 0.0 12 P 8.6 o df Douglas-fir WA 55 46 122 0.6 3.6 o 15 P 16.1 o df Douglas-fir, alder WA 55 46 122 0.6 2.4 o 15 P 14.3 o df Douglas-fir, conifer OR 55 45 124 0.2 3.8 o 15 P 11.6 o df Douglas-fir, conifer OR 55 45 124 0.2 0.9 o 15 P 5.3 d df Douglas-fir WA 26 0.3 19 P 9.0 d df Douglas-fir WA 30.5 0.3 19 P 9.2 d df Douglas-fir WA 33.3 0.3 19 P 8.0 d df Douglas-fir WA 38 0.3 19 P 120.2 o df Douglas-fir OR 450 44 0.6 35.6 o 25 P 165.6 o df western hemlock OR 121 45 0.2 49 o 25 P 43.1 c df Douglas-fir OR 150 44 124 0.1 0.47 26 P 9.2 c df Douglas-fir OR 150 44 124 0.1 0.42 26 P 3.7 c df Douglas-fir plantation OR 9 44 124 0.1 0.38 26 P 6.7 c df Douglas-fir WA 38 32 P 9.7 c df Douglas-fir WA 38 32 P 8.7 c df Douglas-fir WA 38 32 P 6.5 c df Douglas-fir OR 38 32 P 8.1 c df Douglas-fir OR 38 32 P 8.2 c df Douglas-fir OR 38 32 P 11.9 c df western hemlock WA 32 32 P 13.7 c df western hemlock WA 32 32 P 10.6 c df western hemlock OR 32 32 P 5.8 d df Douglas-fir OR 48 45 123 0.3 6.1 d 39 P 5.5 d df Douglas-fir OR 48 45 123 0.3 4.8 d 39 P 5.5 d df Douglas-fir OR 48 45 123 0.3 4.3 d 39 P 6.0 d df Douglas-fir OR 48 45 123 0.3 4 d 39 P 9.8 d df Douglas-fir OR 48 45 123 0.3 10.4 d 39 P 5.3 d df Douglas-fir, bigleaf maple OR 48 45 123 0.3 2.9 d 39 P 6.8 d df Douglas-fir, bigleaf maple OR 48 45 123 0.3 4.3 d 39 P 4.5 d df Douglas-fir, bigleaf maple OR 48 45 123 0.3 3.1 d 39 Table A1.—Continued

Continued R C ff T D L A a La a Lo a E a c:dw mrt rf cite b
(Mg/ha) (years) (km) (years)24 P 4.6 d df Douglas-fir, bigleaf maple OR 48 45 123 0.3 2.4 d 39 P 11.4 d df Douglas-fir, bigleaf maple OR 48 45 123 0.3 5.8 d 39 P 81.4 d df western hemlock - fir BC m 49 125 0.5 40 P 44.4 d df western hemlock - fir BC m 49 125 0.5 40 P 55.5 d df western hemlock - fir BC m 49 125 0.6 40 P 92.5 d df western hemlock - fir BC m 49 125 0.5 40 P 58.1 d df Douglas-fir OR, WA m 42, 33 P 11.3 d df Douglas-fir OR 44 0.3 8.6 138 P 14.5 d df Douglas-fir OR 44 0.9 9.9 138 P 12.6 d df hemlock - spruce OR 44 0.2 9.6 138 P 78.7 o df Douglas-fir OR, WA 40 48, v P 7.9 o df Douglas-fir OR, WA 40 48, v P 8.1 d df hemlock - spruce OR 26 45 0.2 3.1 46, 139 P 26.3 o df Douglas-fir OR, WA 23 49, v P 82.2 o df Douglas-fir OR, WA 80 49, v P 31.4 o df Douglas-fir OR 450 44 123 0.6 13.4 o 47 P 27.1 o df Douglas-fir OR 450 44 123 0.6 10 o 47 P 15.1 o df Douglas-fir OR 450 44 123 0.6 7.3 o 47 P 31.3 o df Douglas-fir OR 450 44 123 0.6 12.9 o 47 P 25.1 o df Douglas-fir OR 450 44 123 0.6 10.8 o 47 P 14.8 d df Douglas-fir WA 47 0.5 19.5 55, 138 P 8.3 d df Douglas-fir WA 47 0.2 18.3 55, 138 P 13.2 d df Douglas-fir WA 47 0.2 16 55, 138 P 8.8 d df Douglas-fir WA 47 0.1 12 55, 138 P 28.3 d df Douglas-fir WA 47 0.1 48.1 55, 138 P 2.9 c df Douglas-fir OR <30 46 123 0.38 59 P 8.2 c df Douglas-fir WA 63, 32 P 17.0 c df western hemlock OR 63, 32 P 33.0 d df Douglas-fir, w. hemlock OR m 80 P 25.7 d df Douglas-fir, w. hemlock OR m 80 P 31.2 d df Douglas-fir, w. hemlock OR m 80 P 36.2 d df Douglas-fir, w. hemlock OR m 80 P 44.3 d df Douglas-fir, w. hemlock OR m 80 P 45.4 d df Douglas-fir, w. hemlock OR m 80 P 45.3 d df Douglas-fir, w. hemlock OR m 80 P 59.8 d df Douglas-fir, w. hemlock WA m 80 P 71.3 d df Douglas-fir, w. hemlock WA m 80 P 55.2 d df Douglas-fir, w. hemlock WA m 80 P 91.1 d df Douglas-fir, w. hemlock WA m 80 P 31.4 c df Douglas-fir OR m 44 122 1.0 93 P 18.1 d df western hemlock WA 48 124 0.1 106 P 27.4 d df western hemlock WA 46 123 0.4 106 P 17.8 d df western hemlock WA 48 124 0.2 106 P 10.4 d df western hemlock WA 48 124 0.1 106 P 14.1 d df western hemlock WA 47 124 0.2 106 P 10.7 d df western hemlock WA 47 124 0.2 106 P 14.8 d df western hemlock WA 48 125 0.1 106 P 8.1 d df western hemlock WA 47 124 0.1 106 P 17.8 d df western hemlock WA 0.9 106 Table A1.—Continued

Continued R C ff T D L A a La a Lo a E a c:dw mrt rf cite b
(Mg/ha) (years) (km) (years)25 P 30.3 d df western hemlock WA 49 122 0.7 106 P 14.4 d df western hemlock WA 0.3 106 P 16.3 d df western hemlock WA 47 122 0.5 106 P 10.7 d df western hemlock WA 48 122 0.2 106 P 11.8 d df western hemlock WA 0.1 106 P 19.2 d df western hemlock WA 0.9 106 P 11.5 d df western hemlock WA 0.3 106 P 11.4 d df Douglas-fir OR, WA 46 129, v P 1.4 d df Douglas-fir WA 9 47 0.2 1.6 128, 139 P 11.0 o df Douglas-fir WA 22 47 121 0.2 4.4 o 130 P 8.4 o df Douglas-fir WA 30 47 121 0.2 3.7 o 130 P 8.4 o df Douglas-fir WA 30 47 121 0.2 7.7 o 130 P 9.4 o df Douglas-fir WA 42 47 121 0.2 5.3 o 130 P 12.8 o df Douglas-fir WA 42 47 121 0.2 7.8 o 130 P 14.6 o df Douglas-fir WA 49 47 121 0.2 12.1 o 130 P 21.6 o df Douglas-fir WA 73 47 121 0.2 29.1 o 130 P 8.6 c df coastal hemlock OR 120 45 124 0.2 0.41 3.4 d 136 P 4.6 c df Douglas-fir WA 300 47 122 0.2 0.38 3.2 d 136 P 6.4 c df Douglas-fir WA 45 47 122 0.2 0.36 5.5 d 136 P 7.4 d df Douglas-fir WA 150 47 12.6 137, 139 P 10.4 d df Douglas-fir WA 70 47 31.1 137, 139 P 3.7 d df Douglas-fir WA 1 47 137, 139 P 5.9 d df Douglas-fir WA 10 47 80 137, 139 P 10.0 d df Douglas-fir WA 40 47 32.9 137, 139 P 8.5 d df Douglas-fir WA 40 47 20 137, 139 P 11.1 d df Douglas-fir WA 150 47 11.4 137, 139 P 12.2 d df Douglas-fir WA 1 47 137, 139 P 6.7 d df Douglas-fir WA 10 47 39.1 137, 139 P 8.5 d df Douglas-fir WA 70 47 22.8 137, 139 P 14.3 d df Douglas-fir OR, WA 100 149, v P 17.7 d fh fir, hemlock WA 23 47 1.2 31.7 139 P 55.3 d fh fir, hemlock WA 180 47 1.2 68.6 139 P 31.6 d fh noble fir, Douglas-fir OR 44 1.2 17.4 138 P 35.1 d fh fir - hemlock OR 44 1.5 28.8 138 P 21.7 c fh mountain hemlock OR 215 44 122 1.8 0.28 87 P 17.7 c fh mountain hemlock OR 18 44 122 1.8 0.3 87 P 16.8 c fh mountain hemlock OR 35 44 122 1.8 0.25 87 P 18.3 c fh mountain hemlock OR 74 44 122 1.8 0.3 87 P 19.8 d fh fir, hemlock WA 175 47 121 1.2 17.7 d 131 P 50.8 c fh Pacific silver fir WA 200 47 121 1.2 0.35 66.5 d 136 P 23.5 d fh fir, hemlock OR, WA m 145 P 5.3 d hw red alder WA 5.2 0.3 19 P 7.6 d hw red alder WA 10 0.3 19 P 5.0 d hw red alder WA 11.5 0.3 19 P 4.8 d hw red alder WA 13.7 0.3 19 P 14.2 d hw red alder WA 24.4 0.3 19 P 13.1 d hw red alder WA 28.7 0.3 19 P 14.5 d hw red alder WA 40.6 0.3 19 P 36.5 o hw red alder WA 30 47 0.2 4.2 o 25 Table A1.—Continued

Continued R C ff T D L A a La a Lo a E a c:dw mrt rf cite b
(Mg/ha) (years) (km) (years)26 P 1.3 d hw red alder OR, WA 14 84, v P 0.9 d hw red alder OR, WA 24 84, v P 0.9 d hw red alder OR, WA 65 84, v P 16.9 d hw elm WA 36 47 0.2 2.9 128, 139 P 5.0 c hw alder WA 40 47 122 0.3 0.34 3.1 d 136 P 7.0 d hw red alder OR 44 3.5 150, 138

W 9.0 c p lodgepole pine OR 100 44 121 1.7 23 W 19.5 o p lodgepole pine WY m 43 110 2.9 30 W 13.9 o p lodgepole pine WY 105 41 106 2.8 20.6 o 34 W 13.1 o p lodgepole pine WY 105 41 106 2.8 18.8 o 34 W 18.6 o p lodgepole pine WY 105 41 106 2.8 21.7 o 34 W 16.9 o p lodgepole pine WY 105 41 106 2.9 19.6 o 34 W 9.5 o p lodgepole pine WY 70 41 106 3.1 12 o 34 W 13.1 o p lodgepole pine WY 240 41 106 3.0 11.7 o 34 W 10.7 o p lodgepole pine WY 15 41 106 2.8 49.9 o 119 W 8.9 o p lodgepole pine WY 30 41 106 2.8 8.7 o 119 W 10.2 o p lodgepole pine WY 50 41 106 2.8 10.7 o 119 W 12.0 o p lodgepole pine WY 100 41 106 2.8 13.6 o 119 W 15.1 o p lodgepole pine WY 260 41 106 2.8 18.8 o 119 W 45.5 d p lodgepole pine CO m 40 106 2.8 123 W 34.0 d p lodgepole pine CO m 40 106 2.8 123 W 31.5 d p lodgepole pine CO m 40 106 2.8 123 W 27.8 d p lodgepole pine CO m 40 106 2.8 123 W 27.0 d p lodgepole pine CO m 40 106 2.9 123 W 36.3 d p lodgepole pine CO m 40 106 3.0 123 W 33.3 d p lodgepole pine CO m 41 107 3.0 123 W 40.0 d p lodgepole pine CO m 41 107 2.9 123 W 33.7 d p lodgepole pine CO m 41 106 3.2 123 W 41.4 d p lodgepole pine CO m 41 106 2.9 123 W 23.0 d p lodgepole pine CA m 135 W 15.6 o p lodgepole pine WY 85 41 106 2.8 20.3 o 147 W 69.7 d p ponderosa pine CA 38 1.5 60 138 W 12.1 d p ponderosa pine AZ 35 2.2 15.5 138 W 2.6 d p ponderosa pine, conifer CA 37 119 1.5 1 W 10.0 d p ponderosa pine IM 50 7, v W 12.0 d p ponderosa pine IM 50 7, v W 8.5 d p ponderosa pine IM 50 7, v W 5.8 d p ponderosa pine IM v W 7.7 d p ponderosa pine AZ y 37 W 3.3 d p ponderosa pine MT m 67 W 40.7 d p ponderosa pine, conifer CA 70 39 121 1.3 68 W 4.6 d p ponderosa pine IM 49 70, v W 13.8 d p ponderosa pine IM 50 71, v W 30.7 d p ponderosa pine IM 50 71, v W 19.2 d p ponderosa pine West 73, 33 W 14.8 c p ponderosa pine AZ m 34 111 2.2 0.4 72 W 9.9 c p ponderosa pine AZ m 34 111 2.2 0.42 72 W 11.5 d p ponderosa pine AZ 35 112 2.1 78 Table A1.—Continued

Continued R C ff T D L A a La a Lo a E a c:dw mrt rf cite b
(Mg/ha) (years) (km) (years)27 W 24.4 d p ponderosa pine AZ 35 112 2.1 78 W 46.0 d p ponderosa pine CA m 135 W 35.8 c p ponderosa pine NM 200 36 106 2.7 0.32 48.7 d 136 W 18.1 d p ponderosa pine AZ 56 142, 139 W 25.0 d p Jeffrey pine, conifer CA m 39 121 1.4 68 W 34.6 d p Jeffrey pine CA m 135 W 9.9 d p western white pine CA m 135 W 3.3 d rs white fir, giant sequoia CA 37 119 1.8 1 W 35.9 o rs Sequoia CA 100, v W 53.8 d rs giant sequoia CA m 135 W 96.9 c rs giant sequoia CA m 2.3 15.2 121 W 22.2 d pj singleleaf pinyon IM m 2.2 33 W 20.0 d pj pinyon - juniper CA m 135 W 23.2 o mc Douglas-fir, spruce, fir NM 50 35 107 2.9 13.4 o 44 W 23.3 d mc Douglas-fir MT m 67 W 47.0 d mc Douglas-fir, incense-cedar CA 110 39 121 1.0 68 W 23.6 d mc Douglas-fir CA m 135 W 25.2 d mc spruce - fir CO 350 40 106 3.6 40 d 9 W 26.3 d mc cedar - hemlock ID m 67 W 37.4 d mc cedar - hemlock MT m 67 W 26.6 d mc subalpine fir MT m 67 W 43.7 d mc spruce - fir CO m 40 106 3.1 123 W 37.0 d mc spruce - fir CO m 40 106 3.0 123 W 34.8 d mc spruce - fir CO m 40 106 3.2 123 W 43.3 d mc spruce - fir CO m 40 106 2.8 123 W 36.3 d mc spruce - fir CO m 40 106 3.0 123 W 38.5 d mc spruce - fir CO m 41 107 3.0 123 W 44.4 d mc spruce - fir CO m 40 106 3.4 123 W 54.8 d mc spruce - fir CO m 41 106 3.3 123 W 38.1 d mc spruce - fir CO m 41 106 3.0 123 W 45.5 d mc spruce - fir CO m 41 106 2.8 123 W 31.9 d mc incense-cedar CA m 135 W 41.9 d mc mountain hemlock CA m 135 W 31.6 d mc red and white fir CA m 135 W 24.1 c mc spruce - fir NM 300 36 106 3.4 0.37 58.9 d 136 W 19.3 d mc mixed conifer IM v W 29.1 o mc fir, cedar, pine CA m 39 121 1.3 13.3 o 54 W 73.9 c mc fir - pine CA m 2.1 17 121 W 34.6 c mc mixed conifer NM 200 36 106 2.7 0.42 21 d 136 W 34.0 d hw aspen CO m 40 106 2.8 123 W 34.4 d hw aspen CO m 40 106 2.8 123 W 51.1 d hw aspen CO m 40 106 2.8 123 W 37.4 d hw aspen CO m 40 106 2.8 123 W 49.2 d hw aspen CO m 40 106 2.8 123 W 17.8 d hw aspen CO m 41 107 2.8 123 W 25.2 d hw aspen CO m 41 107 2.8 123 W 33.3 d hw aspen CO m 41 107 2.8 123 W 18.5 d hw aspen CO m 41 107 2.7 123 W 43.3 d hw aspen CO m 41 106 2.7 123 Table A1.—Continued

Continued R C ff T D L A a La a Lo a E a c:dw mrt rf cite b
(Mg/ha) (years) (km) (years)28 W 10.0 c hw aspen NM 60 36 106 3.1 0.35 11.4 d 136 W 16.2 d hw black oak CA 38 1.5 28.3 138 W 13.8 d hw gambel oak West 24, 33 W 20.7 d hw gambel oak AZ 35 112 2.1 78 W 4.7 d hw oak, chaparral AZ m 34 111 1.6 101

A 30.2 o sw black spruce AK 130 65 148 0.3 31 A 20.6 o sw white spruce AK 160 65 148 0.2 31 A 73.3 o sw black spruce AK 55 65 0.5 460 o 25 A 48.8 o sw black spruce (muskeg) AK 51 65 0.2 620 o 25 A 65.6 o sw black spruce AK 130 64 220 o 25 A 14.2 d hw aspen AK 64 0.1 20.5 138 A 21.9 d hw aspen AK 64 0.1 33.2 138 A 16.2 d hw birch AK 64 0.1 19.7 138 A 18.2 d hw birch AK 64 0.1 23 138 A 19.1 o hw aspen AK 70 65 148 0.3 31 A 27.2 o hw paper birch AK 110 65 148 0.3 31 A 25.5 d hw birch AK 50 64 26 139 A 37.8 o hw paper birch AK 50 64 26 o 25

a Some papers did not explicitly provide age, latitude, longitude, or elevation. However, a number of these also provided enough information to include an approximate value; these columns include these values as well as values directly from site descriptio ns.

b Observations with two citations are those where the primary reference was identified (the first citation) but the value was obt ained from another source (the second citation). Citations “v” are from an unpublished report by K. A. Vogt, 1996; on file at the USD A Forest Service Northeastern Research Station, Durham, NH. Table A1.—Continued

R C ff T D L A a La a Lo a E a c:dw mrt rf cite b
(Mg/ha) (years) (km) (years)29 Table A2. —Forest types used for summarizing data.

Region Forest type Type description
North p pine sf spruce, fir, hemlock mx mixed conifer-hardwood ab aspen-birch mb maple-beech-birch, northern hardwood oh mixed hardwood, oak, hickory
South p pine mx mixed conifer-hardwood hw mixed hardwood, oak, hickory
Pacific Northwest df Douglas-fir, Western hemlock, Sitka spruce sfh fir-hemlock, higher elevation hw hardwood

West p pine rs redwood/sequoia pj pinyon/juniper mc mixed conifer hw hardwood

Alaska sw softwood hw hardwood30 

## Literature Cited in Appendix

1. Agee, J.K. 1973. Prescribed fire effects on physical and hydrologic properties of mixed-conifer forest floor and soil. Water Resources Center, No. 143. Davis, CA: University of California. 57 p.

2. Alban, D.H. 1977. Influence on soil properties of prescribed burning under mature red pine. Res. Pap. NC-139. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 8 p.

3. Alban, D.H.; Host, G.E.; Elioff, J.D.; Shadis, D.A. 1994. Soil and vegetation response to soil compaction and forest floor removal after aspen harvesting. Res. Pap. NC-315. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 8 p.

4. Alban, D.H.; Perala, D.A. 1990. Ecosystem carbon following aspen harvesting in the upper Great Lakes. In: Adams, R.D., ed. Proceedings of symposium: Aspen Symposium ’89; 1989 July 25-27; Duluth, MN. Gen. Tech. Rep. NC -140. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station: 123-131.

5. Alban, D.H.; Perala, D.A.; Schlaegel, B.E. 1978. Biomass and nutrient distribution in aspen, pine, and spruce stands on the same soil type in Minnesota. Canadian Journal of Forest Research. 8: 290-299.

6. Albert, D.A.; Barnes, B.V. 1987. Effects of clearcutting on the vegetation and soil of a sugar maple-dominated ecosystem, western Upper Michigan. Forest Ecology and Management. 18: 283- 298.

7. Aldon, E.F. 1968. Moisture loss and weight of the forest floor under pole-sized ponderosa pine. Journal of Forestry. 66: 70-71.

8. Alway, F.J.; Kittredge, J. 1933. The forest floor under stands of aspen and paper birch. Soil Science. 35: 307-312.

9. Arthur, M.A.; Fahey, T.J. 1992. Biomass and nutrients in an Engelmann spruce-subalpine fir forest in north central Colorado: pools, annual production, and internal cycling. Canadian Journal of Forest Research. 22: 315-325.

10. Bell, R.L.; Binkley, D. 1989. Soil nitrogen mineralization and immobilization in response to periodic prescribed fire in a loblolly pine plantation. Canadian Journal of Forest Research. 19: 816-820.

11. Berish, C.W.; Ragsdale, H.L. 1986. Metals in lowelevation, southern Appalachian forest floor and soil. Journal of Environmental Quality. 15: 183-187.

12. Binkley, D. 1983. Ecosystem production in Douglas-fir plantations: interaction of red alder and site fertility. Forest Ecology and Management. 5: 215-227.

13. Binkley, D. 1986. Soil acidity in loblolly pine stands with interval burning. Soil Science Society of America Journal. 50: 1590-1594.

14. Binkley, D.; Richter, D.; David, M.B.; Caldwell, B. 1992a. Soil chemistry in a loblolly/longleaf pine forest with interval burning. Ecological Applications. 2: 157-164.

15. Binkley, D.; Sollins, P.; Bell, R.; Sachs, D.; Myrold, D. 1992b. Biogeochemistry of adjacent conifer and alder-conifer stands. Ecology. 73: 2022-2033.

16. Blow, F.E. 1958. Quality and hydroligic characteristics of litter under upland oak forests in eastern Tennessee. Journal of Forestry. 53: 190-195.

17. Bockheim, J.G. 1997. Soils in hemlock-hardwood ecosystem mosaic in the Southern Lake Superior Uplands. Canadian Journal of Forest Research. 27: 1147-1153.

18. Bockheim, J.G.; Leide, J.E.; Tavella, D.S. 1986. Distribution and cycling of macronutrients in a Pinus resinosa plantation fertilized with nitrogen and potassium. Canadian Journal of Forest Research. 16: 778-785.

19. Bormann, B.T.; DeBell, D.S. 1981. Nitrogen content and other soil properties related to age of red alder stands. Soil Science Society of America Journal. 45: 428-432.

20. Bourn, T.G.; Brown, J.H.J. 1971. Mixed oak forest floor: some characteristics. Rhode Island Agricultural Experiment Sta. Bull. 407. Kingston, RI: University of Rhode Island Agricultural Experiment Station. 10 p.

21. Boyer, W.D. 1966. Litter in longleaf pine stands thinned to prescribed densities. Res. Note SO-31. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station. 4

p.31 22. Brown, J.K. 1966. Forest floor fuels in red and jack pine stands. Res. Note NC-9. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 4 p.

23. Busse, M.D. 1994. Downed bole-wood decomposition in lodgepole pine forests of central Oregon. Soil Science Society of America Journal. 58: 221-227.

24. Clary, W.P.; Tiedemann, A.R. 1986. Distribution of biomass within small tree and shrub form Quercus gambelii stands. Forest Science. 32: 234-242.

25. Cole, D.W.; Rapp, M. 1981. Elemental cycling in forest ecosystems. In: Reichle, D.E., ed. Dynamic properties of forest ecosystems. Cambridge, UK: Cambridge University Press: 341-409.

26. Cromack, K.; Miller, R.E.; Helgerson, O.T.; Smith, R.B.; Anderson, H.W. 1999. Soil carbon and nutrients in a coastal Oregon Douglas-fir plantation with red alder. Soil Science Society of America Journal. 63: 232-239.

27. Crosby, J.S. 1974. Some forest floor fuelbed characteristics of black oak stands in southeast Missouri. Res. Note NC-162. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 4 p.

28. Czapowskyj, M.M.; Rourke, R.V.; Frank, R.M. 1977. Strip clearcutting did not degrade the site in a spruce-fir forest in central Maine. Res. Pap. NE-367. Upper Darby, PA: U.S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station. 8 p.

29. DeAngelis, D.L.; Gardner, R.H.; Shugart, H.H. 1981. Productivity of forest ecosystems studied during the IBP: The woodlands data set. In: Reichle, D.E., ed. Dynamic properties of forest ecosystems. International Biological Program 23. London: Cambridge University Press: 567-672.

30. DeByle, N.V. 1980. Harvesting and site treatment influences on the nutrient states of lodgepole pine forests in western Wyoming. Environmental consequences of timber harvesting in Rocky Mountain coniferous forests: symposium proceedings; 1979 Sept. 11-13; Missoula, MT. Gen. Tech. Rep. INT-90. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station: 137-156. 31. Dyrness, C.T.; Van Cleve, K.; Levison, J.D. 1989. The effect of wildfire on soil chemistry in four forest types in interior Alaska. Canadian Journal of Forest Research. 19: 1389-1396.

32. Edmonds, R.L.; Chappell, H.N. 1994. Relationships between soil organic matter and forest productivity in western Oregon and Washington. Canadian Journal of Forest Research. 24: 1101-1106.

33. Everett, R.L.; Thran, D.F. 1992. Above-ground biomass and nitrogen phosphorus and sulfur capital in singleleaf pinyon woodlands. Journal of Environmental Management. 34: 137-147.

34. Fahey, T.J. 1983. Nutrient dynamics of aboveground detritus in lodgepole pine ( Pinus Contorta ssp. latifolia ) ecosystems, southeastern Wyoming. Ecological Monographs. 53: 51-72.

35. Fassnacht, K.S.; Gower, S.T. 1999. Comparison of the litterfall and forest floor organic matter and nitrogen dynamics of upland forest ecosystems in north central Wisconsin. Biogeochemistry. 45: 265- 284.

36. Federer, C.A. 1982. Subjectivity in the separation of organic horizons of the forest floor. Soil Science Society of America Journal. 46: 1090-1093.

37. Ffolliott, P.F. 1968. Some characteristics of the forest floor under ponderosa pine in Arizona. Res. Note RM-127. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station. 4 p.

38. Finzi, A.C.; Van Breemen, N.; Canham, C.D. 1998. Canopy tree-soil interactions within temperature forests: species effects on soil carbon and nitrogen. Ecological Applications. 8: 440-446.

39. Fried, J.S.; Boyle, J.R.; Tappeiner, J.C.I.; Cromack, K.J. 1990. Effects of bigleaf maple on soils in Douglas-fir forests. Canadian Journal of Forest Research. 20: 259-266.

40. Fyles, J.W.; Fyles, I.H.; Beese, W.J.; Feller, M.C. 1991. Forest floor characteristics and soil nitrogen availability on slash-burned sites in coastal British Colombia. Canadian Journal of Forest Research. 21: 1516-1522.

41. Garten, C.T.; Cooper, L.W.; Post, W.M.; Hanson, P.J.
2000. Climate controls on forest soil C isotope32 ratios in the southern Appalachian Mountains. Ecology. 81: 1108-1119.

42. Gessel, S.P.; Balci, A.N. 1965. Amount and composition of forest floors under Washington coniferous forests. In: Youngberg, C.T., ed. Forest-soil relationships in North America. Corvalis, OR: Oregon State University Press: 11-23.

43. Gosz, J.R.; Likens, G.E.; Bormann, F.H. 1976. Organic matter and nutrient dynamics of the forest floor in the Hubbard Brook Forest. Oecologia. 22: 305-320.

44. Gower, S.T.; Vogt, K.A.; Grier, C.C. 1992. Carbon dynamics of Rocky Mountain Douglas-fir. Ecological Monographs. 62: 43-65.

45. Green, D.C.; Grigal, D.F. 1980. Nutrient accumulations in Jack pine stands on deep and shallow soils over bedrock. Forest Science. 26: 325- 333.

46. Grier, C.C. 1976. Biomass productivity and nitrogen-phosphorous cycles in hemlock-spruce stands of the central Oregon coast. In: Atkinson, W.A.; Zasoski, R.J., eds. Western hemlock management. Seattle, WA: University of Washington Press: 71-81.

47. Grier, C.C.; Logan, R.S. 1977. Old-growth Pseudotsuga menziesii communities of western Oregon watershed: biomass distribution and production budgets. Ecological Monographs. 47: 373-400.

48. Grier, C.C.; McColl, J.G. 1971. Forest floor characteristics within a small plot in Douglas-fir in western Washington. Soil Science Society of America Proceedings. 35: 988-991.

49. Grier, C.C.; Vogt, K.A.; Keyes, M.R.; Edmonds, R.L. 1981. Biomass distribution and above- and belowground production in young and mature Abies amabilis zone ecosystems of the Washington Cascades. Canadian Journal of Forest Research. 11: 155-167.

50. Grigal, D.F.; Ohmann, L.F. 1992. Carbon storage in upland forests of the Lake States. Soil Science Society of America Journal. 56: 935-943.

51. Groeschl, D.A.; Johnson, J.E.; Smith, D.W. 1990. Forest soil characteristics following wildfire in the Shenandoah National Park, Virginia. In: Nodvin, S.C.; Waldrop, T.A., eds. Fire and environment: ecological and cultural perspectives. Gen. Tech. Rep. SE-69. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station: 129-137.

52. Harding, R.B.; Jokela, E.J. 1994. Long-term effects of forest fertilization on site organic matter nutrients. Soil Science Society of America Journal. 58: 216-221.

53. Harris, W.F.; Kinerson, R.S., Jr.; Edwards, N.T. 1977. Comparison of belowground biomass of natural deciduous forest and loblolly pine plantations. Pedobiologia. 17: 369-381.

54. Hart, S.C.; Firestone, M.K. 1991. Forest floormineral soil interactions in the internal nitrogen cycle of an old-growth forest. Biogeochemistry. 12: 103-127.

55. Heilman, P.E. 1961. Effects of nitrogen fertilization on the growth and nitrogen nutrition of low-site Douglas-fir stands. Seattle, WA: University of Washington. 213 p. Ph.D. dissertation.

56. Hendrickson, O.Q.; Chatarpaul, L.; Burgess, D. 1989. Nutrient cycling following whole-tree and conventional harvest in northern mixed forest. Canadian Journal of Forest Research. 19: 725-735.

57. Hix, D.M.; Barnes, B.V. 1984. Effects of clearcutting on the vegetation and soil of an eastern hemlock dominated ecosystem, western Upper Michigan. Canadian Journal of Forest Research. 14: 914-923.

58. Homann, P.S.; Grigal, D.F. 1996. Below-ground organic carbon and decomposition potential in a field-forest glacial-outwash landscape. Biology and Fertility of Soils. 23: 207-214.

59. Hopmans, P.; Chappell, H.N. 1994. Growth response of young, thinned Douglas-fir stands to nitrogen fertilizer in relation to soil properties and tree nutrition. Canadian Journal of Forest Research. 24: 1684-1688.

60. Hough, W.A. 1982. Phytomass and nutrients in the understory and forest floor of slash/longleaf pine stands. Forest Science. 28: 359-372.

61. Huntington, T.G.; Ryan, D.F.; Hamburg, S.P. 1988. Estimating soil nitrogen and carbon pools in a33 northern hardwood forest ecosystem. Soil Science Society of America Journal. 52: 1162-1167.

62. Johnson, C.E.; Driscoll, C.T.; Fahey, T.J.; Siccama, T.G.; Hughes, J.W. 1995. Carbon dynamics following clear-cutting of a northern hardwood forest. In: McFee, W.W.; Kelly, J.M., eds. Carbon forms and functions in forest soils. Madison, WI: Soil Science Society of America: 463-488.

63. Johnson, D.W.; Cole, D.W.; Bledsoe, C.S.; Cromack, K.; Edmonds, R.L.; Gessel, S.P.; Grier, C.C.; Richards, B.N.; Vogt, K.A. 1982. Nutrient cycling in the Pacific Northwest. In: Edmonds, R.L., ed. Analysis of coniferous forest ecosystems in the western United States. Stroudsburg, PA: Hutchinson Ross: 186-232.

64. Johnston, M.H.; Homann, P.S.; Engstrom, J.K.; Grigal, D.F. 1996. Changes in ecosystem carbon storage over 40 years on an old-field/forest landscape in east-central Minnesota. Forest Ecology and Management. 83: 17-26.

65. Jokela, E.J.; McFee, W.W.; Stone, E.L. 1991. Micronutrient deficiency in slash pine: response and persistence of added manganese. Soil Science Society of America Journal. 55: 492-496.

66. Jorgensen, J.R.; Wells, C.G.; Metz, L.J. 1980. Nutrient changes in decomposing loblolly pine forest floor. Soil Science Society of America Journal. 44: 1307-1314.

67. Jurgensen, M.F.; Harvey, A.E.; Graham, R.T.; Page, D.D.S.; Tonn, J.R.; Larsen, M.J.; Jain, T.B. 1997. Impacts of timber harvesting on soil organic matter, nitrogen, productivity, and health of inland Northwest forests. Forest Science. 43: 234-251.

68. Kauffman, J.B.; Martin, R.E. 1989. Fire behavior, fuel consumption, and forest-floor changes following prescribed understory fires in Sierra Nevada mixed conifer forests. Canadian Journal of Forest Research. 19: 455-462.

69. Kinerson, R.S.; Ralston, C.W.; Wells, C.G. 1977. Carbon cycling in a loblolly pine plantation. Oecologia. 29: 1-10.

70. Klemmedson, J.O. 1975. Nitrogen and carbon regimes in an ecosystem of young dense ponderosa pine in Arizona. Forest Science. 21: 163-168.

71. Klemmedson, J.O. 1976. Effect of thinning and slash burning on nitrogen and carbon in ecosystems of young dense ponderosa pine. Forest Science. 22: 45-53.

72. Klemmedson, J.O. 1994. New Mexican locust and parent material: influence on forest floor and soil macronutrients. Soil Science Society of America Journal. 58: 974-980.

73. Klemmedson, J.L.; Schultz, A.M.; Jenny, H.; Biswell, H.H. 1962. Effect of prescribed burning of forest litter on total soil nitrogen. Soil Science Society Proceedings. 26: 200-202.

74. Kodama, H.E.; Van Lear, D.H. 1980. Prescribed burning and nutrient cycling relationships in young loblolly pine plantations. Southern Journal of Applied Forestry. 4: 118-121.

75. Lane, C.L. 1975. Forest stand conversion from hardwoods to pines: effects on soil nutrients microorganisms and forest floor weight during the first seven years. Forest Science. 21: 155-159.

76. Lang, G.E.; Cronan, C.S.; Reiners, W.A. 1981. Organic matter and major elements of the forest floors and soils in subalpine balsam fir forests. Canadian Journal of Forest Research. 11: 388-399.

77. Lang, G.E.; Forman, R.T.T. 1978. Detrital dynamics in a mature oak forest: Hutcheson Memorial Forest, New Jersey. Ecology. 59: 580-595.

78. Lefevre, R.E.; Klemmedson, J.O. 1980. Effect of Gambel oak on forest floor and soil of a ponderosa pine forest. Soil Science Society of America Journal. 44: 842-846.

79. Liechty, H.O.; Jurgensen, M.F.; Mroz, G.D.; Gale, M.R. 1997. Pit and mound topography and its influence on storage of carbon, nitrogen, and organic matter within an old-growth forest. Canadian Journal of Forest Research. 27: 1992-1997.

80. Little, S.N.; Ohmann, J.L. 1988. Estimating nitrogen lost from forest floor during prescribed fires in Douglas-fir/western hemlock clearcuts. Forest Science. 34: 152-164.

81. Lockaby, B.G.; Taylor-Boyd, J.E. 1986. Nutrient dynamics in the litter fall and forest floor of an 18- year-old loblolly pine plantation. Canadian Journal of Forest Research. 16: 1109-1112.

82. Loomis, R.M. 1975. Annual changes in forest floor weights under a southeast Missouri oak stand. Res.34 Note NC-184. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 3 p.

83. Loomis, R.M. 1977. Jack pine and aspen forest floors in northeastern Minnesota. Res. Note NC-222. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 3 p.

84. Luken, J.; Fonda, R. 1983. Nitrogen accumulation in a chronosequence of red alder communities along the Hoh River, Olympic National Park, Washington. Canadian Journal of Forest Research. 13: 1228-1237.

85. Mader, D.L.; Lull, H.W. 1968. Depth, weight, and water storage of the forest floor in white pine stands in Massachusetts. Res. Pap. NE-109. Upper Darby, PA: U.S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station. 35 p.

86. Mader, D.L.; Lull, H.W.; Swenson, E.I. 1977. Humus accumulation in hardwood stands in the Northeast. Res. Bull. 648. Amherst, MA: Massachusetts Agricultural Experiment Station. 31 p.

87. Matson, P.A.; Boone, R.D. 1984. Naturaldisturbance and nitrogen mineralization: waveform dieback of mountain hemlock in the Oregon Cascades. Ecology. 65: 1511-1516.

88. Mattson, K.G.; Smith, H.C. 1993. Detrital organic matter and soil CO 2 efflux in forests regenerating from cutting in West Virginia. Soil Biology and Biochemistry. 25: 1241-1248.

89. Mattson, K.G.; Swank, W.T. 1989. Soil and detrital carbon dynamics following forest cutting in the Southern Appalachians. Biology and Fertility of Soils. 7: 247-253.

90. McClaugherty, C.A.; Pastor, J.; Aber, J.D.; Melillo, J.M. 1985. Forest litter decomposition in relation to soil nitrogen dynamics and litter quality. Ecology. 66: 266-275.

91. McKee, W.H. 1982. Changes in soil fertility following prescribed burning on coastal plain pine sites. Res. Pap. SE-234. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. 23 p.

92. McLaughlin, J.W.; Liu, G.; Jurgensen, M.F.; Gale, M.R. 1996. Organic carbon characteristics in a spruce swamp five years after harvesting. Soil Science Society of America Journal. 60: 1228-1236.

93. Means, J.E.; MacMillan, P.C.; Cromack, K.J. 1992. Biomass and nutrient content of Douglas-fir logs and other detrital pools in an old-growth forest, Oregon, U.S.A. Canadian Journal of Forest Research. 22: 1536-1546.

94. Metz, L.J. 1954. Forest floor in the Piedmont region of South Carolina. Soil Science Society of America Proceedings. 18: 335-338.

95. Metz, L.J.; Wells, C.G.; Kormanik, P.P. 1970. Comparing the forest floor and surface soil beneath four pine species in the Virginia Piedmont. Res. Pap. SE-55. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. 8 p.

96. Mitchell, M.J.; Foster, N.W.; Shepard, J.P.; Morrison, I.K. 1992. Nutrient cycling in Huntington Forest and Turkey Lakes deciduous stands: nitrogen and sulfur. Canadian Journal of Forest Research. 22: 457- 464.

97. Mroz, G.D.; Jurgensen, M.F.; Frederick, D.J. 1985. Soil nutrient changes following whole tree harvesting on three northern hardwood sites. Soil Science Society of America Journal. 49: 1552-1557.

98. Nemeth, J.C. 1973. Dry matter production in young loblolly ( Pinus teada L.) and slash pine ( Pinus elliottii Engelm.) plantations. Ecological Monographs. 43: 21-41.

99. Ohmann, L.F.; Grigal, D.F. 1991. Properties of soils and tree wood tissue across a Lake States sulfate deposition gradient. Res. Bull. NC-130. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 65 p.

100. Parsons, D.J. 1978. Fire and fuel accumulation in a giant sequoia forest. Journal of Forestry. 76: 104- 105.

101. Pase, C.P. 1972. Litter production by oakmountainmahogany chaparral in Central Arizona. Res. Note RM-214. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station. 7 p.

102. Pastor, J.; Bockheim, J.G. 1984. Distribution and cycling of nutrients in an aspen-mixed-hardwood-35 spodosol ecosystem in northern Wisconsin. Ecology. 65: 339-353.

103. Pehl, C.E.; Shellnutt, H.E.J. 1986. Forest floor and soil nutrient conditions in the Georgia sandhills. Georgia Forest Res. Pap. No. 62. Dry Branch, GA: Georgia Forestry Commission. 11 p.

104. Perala, D.A.; Alban, D.H. 1982. Rates of forest floor decomposition and nutrient turnover in aspen, pine, and spruce stands on two different soils. Res. Pap. NC-227. St Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. 5 p.

105. Perala, D.A.; Rollinger, J.L.; Wilson, D. 1995. Comparison between soil and biomass carbon in adjacent hardwood and red pine forests. World Resource Review. 7: 231-243.

106. Radwan, M.A.; Shumway, J.S. 1983. Soil nitrogen, sulfur, and phosphorus in relation to growth response of western hemlock to nitrogen fertilization. Forest Science. 29: 469-477.

107. Reiners, W.A. 1972. Structure and energetics of three Minnesota forests. Ecological Monographs. 42: 71-94.

108. Reiners, W.A.; Marks, R.H.; Vitousek, P.M. 1975. Heavy metals in subalpine and alpine soils in New Hampshire. Oikos. 26: 264-275.

109. Reiners, W.A.; Reiners, N.M. 1970. Energy and nutrient dynamics of forest floors in three Minnesota forests. Journal of Ecology. 58: 497-519.

110. Rochow, J.J. 1975. Mineral nutrient pool and cycling in a Missouri forest. Journal of Ecology. 63: 985-994.

111. Rolfe, G.L.; Boggess, W.R. 1973. Soil conditions under old field and forest cover in southern Illinois. Soil Science Society of America Proceedings. 37: 314- 318.

112. Rollinger, J.L.; Strong, T.F.; Grigal, D.F. 1998. Forested soil carbon storage in landscapes of the Northern Great Lakes Region. In: Lal, R.; Kimble, J.M.; Follett, R.F.; Stewart, B.A. eds. Management of carbon sequestration in soil. Boca Raton, FL: CRC Press: 335-350.

113. Ruark, G.A.; Bockheim, J.G. 1988. Biomass, net primary production, and nutrient distribution for an age sequence of Populus tremuloides ecosystems. Canadian Journal of Forest Research. 18: 435-443.

114. Schiffman, P.M.; Johnson, W.C. 1989. Phytomass and detrital carbon storage during forest regrowth in the southeastern United States Piedmont. Canadian Journal of Forest Research. 19: 69-78.

115. Schoch, P.; Binkley, D. 1986. Prescribed burning increased nitrogen availability in a mature loblolly pine stand. Forest Ecology and Management. 14: 13-
22.

116. Seastedt, T.R.; Crossle, D.A.J. 1981. Microarthropod response following cable logging and clear-cutting in the southern Appalachians. Ecology. 62: 126-135.

117. Simmons, J.A.; Fernandez, I.J.; Briggs, R.D.; Delaney, M.T. 1996. Forest floor carbon pools and fluxes along a regional climate gradient in Maine, USA. Forest Ecology and Management. 84: 81-95.

118. Sims, I.H. 1932. Litter deposition and accumulation in the pine-oak type of the southern Appalachians. Journal of Forestry. 30: 90-91.

119. Smith, F.W.; Resh, S.C. 1999. Age-related changes in production and below-ground carbon allocation in Pinus contorta forests. Forest Science. 45: 333- 341.

120. Snyder, K.E.; Harter, R.D. 1987. Forest floor dynamics in even-aged northern hardwood stands. Soil Science Society of America Journal. 51: 1381- 1383.

121. Stohlgren, T.J. 1988. Litter dynamics in two Sierran mixed conifer forests. I. Litterfall and decomposition rates. Canadian Journal of Forest Research. 18: 1127-1135.

122. Stottlemyer, R.; Toczydlowski, D. 1999. Seasonal relationships between precipitation, forest floor, and streamwater nitrogen, Isle Royale, Michigan. Soil Science Society of America Journal. 63: 389-398.

123. Stump, L.M.; Binkley, D. 1993. Relationships between litter quality and nitrogen availability in Rocky Mountain forests. Canadian Journal of Forest Research. 23: 492-502.

124. Switzer, G.L.; Nelson, L.E. 1972. Nutrient accumulation of cycling in loblolly pine ( Pinus taeda L.) plantation ecosystems: the first twenty36 years. Soil Science Society of America Proceedings. 36: 143-147.

125. Switzer, G.K.; Shelton, M.G.; Nelson, L.E. 1979. Successional development of the forest floor and soil surface on upland sites of the east gulf coastal plain. Ecology. 60: 1162-1171.

126. Tappeiner, J.C.; Alm, A.A. 1975. Undergrowth vegetation affects the nutrient content of litterfall and soils in red pine and birch stands in northern Minnesota. Ecology. 56: 1193-1200.

127. Trettin, C.C.; Johnson, D.W.; D. E. Todd, J. 1999. Forest nutrient and carbon pools at Walker Branch watershed: changes during a 21-year period. Soil Science Society of America Journal. 63: 1436-1448.

128. Turner, J. 1975. Nutrient cycling in a Douglas-fir ecosystem with respect to age and nutrient status. Seattle, WA: University of Washington. 190 p. Ph.D. dissertation.

129. Turner, J. 1977. Effect of nitrogen availability on nitrogen cycling in a Douglas-fir stand. Forest Science. 23: 307-316.

130. Turner, J.; Long, J.N. 1975. Accumulation of organic matter in a series of Douglas-fir stands. Canadian Journal of Forest Research. 5: 681-690.

131. Turner, J.; Singer, M.J. 1976. Nutrient distribution and cycling in a sub-alpine coniferous forest ecosystem. Journal of Applied Ecology. 13: 295-301.

132. Van Lear, D.H. 1980. Effects of nitrogen, phosphorus, and lime on the forest floor and growth of pole-size loblolly pine. Soil Science Society of America Journal. 44: 838-841.

133. Van Lear, D.H.; Danielovich, S.J. 1988. Soil movement after broadcast burning in the southern Appalachians. Southern Journal of Applied Forestry. 12: 49-53.

134. Van Lear, D.H.; Goebel, N.B. 1976. Leaf fall and forest tree characteristics in loblolly pine plantations in the South Carolina Piedmont. Soil Science Society of America Journal. 40: 116-119.

135. van Wagtendonk, J.W.; Benedict, J.M.; Sydoriak, W.M. 1998. Fuel bed characteristics of Sierra Nevada conifers. Western Journal of Applied Forestry. 13: 73-84. 136. Vitousek, P.M.; Gosz, J.R.; Grier, C.C.; Melillo, J.M.; Reiners, W.A. 1982. A comparative analysis of potential nitrification and nitrate mobility in forest ecosystems. Ecological Monographs. 52: 155-177.

137. Vogt, D.J. 1987. Douglas-fir ecosystems in western Washington: biomass and production as related to site quality and stand age. Seattle, WA: University of Washington. 164 p. Ph.D. dissertation.

138. Vogt, K.A.; Grier, C.C.; Vogt, D.J. 1986. Production, turnover, and nutrient dynamics of above- and belowground detritus of world forests. Advances in Ecological Research. 15: 303-377.

139. Vogt, K.A.; Vogt, D.J.; Palmiotto, P.A.; Boon, P.; O‘Hara, J.; Asbjornsen, H. 1996. Review of root dynamics in forest ecosystems grouped by climate, climatic forest type and species. Plant and Soil. 187: 159-219.

140. Vose, J.M.; Swank, W.T. 1993. Site preparationburning to improve southern Appalachian pinehardwood stands: aboveground biomass, forest floor mass, and nitrogen and carbon pools. Canadian Journal of Forest Research. 23: 2255-2262.

141. Vose, J.M.; Swank, W.T.; Clinton, B.D.; Knoepp, J.D.; Swift, L.W. 1999. Using stand replacementfires to restore southern Appalachian pinehardwood ecosystems: effects on mass, carbon, and nutrient pools. Forest Ecology and Management. 114: 215-226.

142. Welch, T.G.; Klemmedson, J.O. 1975. Influence of the biotic factor and parent material on distribution of nitrogen and carbon on ponderosa pine ecosystems. In: Bernier, B.; Winget, C.H., eds. Forest soils and forest land management. Quebec City, PQ: Laval University Press: 159-178.

143. Wells, C.G.; Jorgensen, J.R. 1975. Nutrient cycling in loblolly pine plantations in forest soils and forest land management. In: Bernier, B.; Winget, C.H., eds. Forest soils and forest land management. Quebec City, PQ: Laval University Press: 137-158.

144. Whittaker, R.H.; Likens, G.E.; Bormann, F.H.; Eaton, J.S.; Siccama, T.G. 1979. The Hubbard Brook ecosystem study: forest nutrient cycling and element behavior. Ecology. 60: 203-220.

145. Williams, C.B.; Dyrness, C.T. 1967. Some characteristics of forest floors and soils under true fir-hemlock stands in the Cascade Range. Res. Pap.37 PNW-37. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Forest and Range Experiment Station. 19 p.

146. Williston, H.L. 1965. Forest floor in loblolly pine plantations as related to stand characteristics. Res. Note SO-26. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station. 3 p.

147. Yavitt, J.B.; Fahey, T.J. 1986. Litter decay and leaching from the forest floor in Pinus contorta (lodgepole pine) ecosystems. Journal of Ecology. 74: 525-545. 148. Yin, X.; Perry, J.A.; Dixon, R.K. 1989. Influence of canopy removal on oak forest floor decomposition. Canadian Journal of Forest Research. 16: 204-214.

149. Youngberg, C.T. 1966. Forest floors in Douglas-fir forests: I. Dry weight and chemical properties. Soil Science Society of America Journal. 30: 406-409.

150. Zavitkovski, J.; Newton, M. 1971. Litterfall and litter accumulation in red alder stands in western Oregon. Plant and Soil. 35: 257-268.Printed on Recycled Paper Smith, James E.; Heath, Linda S. 2002. **A model of forest floor carbon mass for United States forest types.**  Res. Pap. NE-722. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northeastern Research Station. 37 p.

Includes a large set of published values of forest floor mass and develop largescale estimates of carbon mass according to region and forest type. Estimates of average forest floor carbon mass per hectare of forest applied to a 1997 summary forest inventory, sum to 4.5 Gt carbon stored in forests of the 48 contiguous United States.

**Keywords** : forest carbon budget; carbon sequestration; afforestation**Headquarters of the Northeastern Research Station is in Newtown Square, Pennsylvania. Field laboratories are maintained at:** 

**Amherst, Massachusetts, in cooperation with the University of Massachusetts**

**Burlington, Vermont, in cooperation with the University of Vermont**

**Delaware, Ohio**

**Durham, New Hampshire, in cooperation with the University of New Hampshire**

**Hamden, Connecticut, in cooperation with Yale University**

**Morgantown, West Virginia, in cooperation with West Virginia University**

**Parsons, West Virginia**

**Princeton, West Virginia**

**Syracuse, New York, in cooperation with the State University of New York, College of Environmental Sciences and Forestry at Syracuse University** 

**Warren, Pennsylvania**

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