Textbook

2.4. Stand Dynamics: Stand Function

Introduction

Understanding several basic concepts of the ecophysiology of forest ecosystems will greatly improve your knowledge of stand dynamics. Forest ecophysiology includes the study of carbon allocation. Carbon makes up approximately 50% of the dry mass of trees, and how it is allocated to different pools and fluxes can explain differences in growth rates. A pool is a location where carbon is stored in biomass, such as the leaves, branches, stem, and roots of a tree. Other important pools in forest ecosystems include organic matter in the litter layer and O horizon of the soil, and organic matter distributed throughout the mineral soil. Fluxes are simply the movement of carbon between different pools. Several different key pools and fluxes are defined below, and shown on the simplified diagram that follows.

A diagram illustrating the fluxes and pools of a single tree carbon budget.

Figure 2.4.1. Carbon pools and fluxes in a forest ecosystem.

Fluxes

The fluxes described here are all rates. They are typically expressed in terms of mass of carbon per unit land area per year.

GPP: Gross Primary Productivity is the total of all carbon fixed through photosynthesis. Carbon is fixed by the plant as it filters carbon dioxide (CO2) from the atmosphere and converts it to glucose (C6H12O6) using light energy. Plants ability to do this is quite remarkable when you consider that CO2 is a trace gas that accounts for only approximately 0.04% (400ppm) of the atmosphere. The tallest coastal redwood on the planet (379.1 feet as of 2012) thus was able to construct its enormous bulk by filtering a minor trace gas from the atmosphere, breaking the molecules apart, and reassembling them into enough wood to build more than fifteen 2,000 square foot houses! GPP is positively correlated to temperature because it is essentially a biologically regulated chemical reaction. Regions with higher temperatures tend to have forests with higher GPP, while regions with cooler temperatures tend to have forests with lower GPP.

RA: Autotrophic Respiration is the carbon that a plant uses and loses in the process of constructing and maintaining its biomass. Like GPP, respiration is positively correlated to temperature because it is also essentially a biologically regulated chemical reaction. Thus, regions with higher temperatures tend to have forests with higher respiration rates, while regions with cooler temperatures tend to have forests with lower respiration rates. Just as you exhale CO2 when exercising or merely sitting here reading this, plants are constantly losing CO2 through their stems, branches, leaves, and roots. Not all tissues in a plant respire, however. Remember that the xylem that makes up the heartwood of a tree is actually dead. Dead tissue does not respire unless it is being decomposed by heterotrophic organisms. More on that in a moment. Only the living tissues of trees respire, which includes almost all of the leaves and fine roots. For branches, coarse roots, and the stems, the center is comprised of mostly dead xylem, while the exterior sheath is composed of the living cambium, phloem, and cork cambium layers. When you look at a tree, you can imagine the outer surface of everything you see as the portion of the tree that is alive and thus actively respiring. For this reason, ecophysiologists often express autotrophic respiration rates on a surface area basis, rather than on a mass basis. In the diagram and table below, you can visualize the effect that tree growth will have on autotrophic respiration rates.

A diagram showing a linear increase in the amount of sapwood required to support a tree as its diameter increases.

Figure 2.4.2. Living tissue (cambium, phloem, cork cambium), shown in green, only covers the outer circumference of a stem or branch. The xylem shown in brown is dead, and does not respire.

Data for tree species such as white oak shows that diameter growth rates remain relatively constant over time (Black et al. 2008). However, as the diameter of the tree grows larger you can see from the figure and table that the volume of living tissue increases linearly. The figure above shows the living tissue in green around a core of dead brown xylem. Based on these simplified calculations, on the butt log alone the respiratory tissue is six-times as the volume for a tree that is 6 feet in dbh versus a tree that is 1 foot in dbh. Factor in the larger branches and crowns that larger trees tend to develop, and you can see how big trees must meet an enormous respiratory carbon demand as they age just to maintain their large volume of living tissue.

Table 2.4.1. A simplified calculation of living tissue volume by tree diameter. In this case a 16 foot butt log was assumed, with no taper.
dbh
(feet)
Circumference
(feet)
New Live Tissue
(in)
New Live Tissue
(in2)
Butt Log Live Tissue
(in3)
1 3.1 0.04 0.13 24.1
2 6.3 0.04 0.25 48.3
3 9.4 0.04 0.38 72.4
4 12.6 0.04 0.50 96.5
5 15.7 0.04 0.63 120.6
6 18.8 0.04 0.75 144.8

RH: Heterotrophic Respiration is the carbon that is released to the atmosphere by consumers or decomposers that are breaking down organic matter that originally came from plants. This flux also includes carbon utilized by deer, bears, birds, and other forest wildlife. However the vast majority of heterotrophic respiration is derived from decomposers such as fungi or bacteria (Kuzyakov 2006). When combined with autotrophic respiration, the total respiration of a forested ecosystem (often called RE for ecosystem respiration) is actually the second largest carbon flux, only behind GPP (Raich and Schlesinger 1992). In other words, forests lose more carbon to respiration on average than they are able to store in biomass. Heterotrophic respiration may be derived from the decomposition of leaf litter and any dead branches or stems that have fallen to the forest floor. One of the largest sources of organic matter for decomposers though is fine roots. Fine roots, or those that are less than 2 mm in diameter, die and are replaced more rapidly than any other plant tissue except for leaves (Matamala et al. 2003). These dead fine roots are rapidly decomposed by fungi and bacteria, releasing almost all of their carbon back to the atmosphere with little to none stored in the soil (Kuzyakov 2006).

Pools

The pools described here are often treated incrementally so they can be compared directly in the same units as the fluxes above. In this context we examine how much mass of carbon per unit land area is added or lost from each pool per year due to the various fluxes described above.

NPP: Net Primary Productivity is the total of all carbon fixed into plant biomass. This pool consists of the leaves, branches, stem, and roots of a tree. This is the variable we are usually most interested in assessing, since biomass is the product of a forest that we typically manage for regardless of whether our objectives are timber, wildlife, recreation, carbon sequestration, or others.

OM: Organic Matter is often included in NPP, but will be treated separately here. OM is most abundant in the O horizon of forest soils, which consist of the Oi, Oe, and Oa layers. These layers are found from top to bottom, respectively, and increase in the extent to which leaf litter is decomposed and mixed with mineral soil. The Oi is analogous to the litter layer found in many forest types, particularly pine dominated stands. The litter layer of a forest not only contains a substantial amount of carbon, but is typically also rich in nutrients such as nitrogen and phosphorous. This is why in mesic regions of the country (basically the entire eastern US falls within this classification), the O horizon is packed full of roots. Litter layers tend to be thicker in regions with slower decomposition rates. Thus drier and colder regions often have thicker litter layers, as long as there is enough moisture and a long enough growing season available for tree growth to provide the leaf litter in the first place. Warmer and wetter regions may have forests that produce far more leaf litter by comparison, but it may decompose in only a few months, thus turning over very rapidly and leaving a relatively thin O horizon.

Soil C: Soil Carbon may take a variety of forms, and may be stored in the soil from a few hours up to many centuries. Charcoal from wildfires may reside in soils for thousands of years, thus accounting for a substantial portion of sequestered soil carbon in temperate forest ecosystems (DeLuca and Aplet 2008). In general though soil carbon follows similar trends to leaf litter, as its presence is most closely tied to decomposition rates. Peat bogs or other swampy areas that are flooded year-round can sequester enormous amounts of soil C because water excludes oxygen, which decomposers need to metabolize soil C.

NEP: Net Ecosystem Productivity is the total of all sequestered C. It can also be described as NEP = GPP - RE, which is algebraically equivalent to NEP = NPP - RH. This quantity is often used when examining how much carbon forests actually sequester for use in carbon trading or climate change modeling.

Carbon Allocation Helps Us Understand Forests

Generally speaking as leaf area increases, GPP increases because more leaves corresponds to greater photosynthetic capacity. As GPP increases, allocation to other fluxes and pools tends to increase proportionally (Litton et al. 2007). Thus, increased leaf area corresponds to increased growth (NPP), and thus, increased production of biomass and forest products. To quantify leaf area we typically use Leaf Area Index, or LAI. LAI is a unitless variable that equates to the area of leaves above a given area of ground. The units cancel out, leaving LAI unitless (e.g. m2 / m2 or ft2 / ft2). To simplify matters, we only consider one side of the leaf, since light primarily strikes the top of the leaf, which is where the chloroplasts are concentrated. For conifers this becomes problematic since their leaves are often not broad and flat, so we instead use half the total leaf area as an approximation.

A diagram illustrating that leaf area index is defined as the number of single-sided leaf layers over a unit area of ground.

Figure 2.4.3. A simplified depiction LAI = 3 versus LAI = 1. The greater LAI, the more leaf area a tree or stand has.

LAI has been increasingly incorporated into operational decision making in the management of forests by large corporate landowners in the last decade thanks in no small part to the ability to easily and relatively accurately estimate it over large land areas using readily available Landsat data (Flores et al. 2006).

Leaf area index, and thus GPP and NPP, are affected by a number of different variables (Fox et al. 2007).

  • Leaves require nitrogen to form proteins, phosphorous to form cell membranes and transfer energy, and a number of other macro- and micro-nutrients. Stands with more available nutrients tend to have higher LAI. Because of this, it is possible to identify using geospatial data what stands will respond to fertilizer application and what stands will show little growth response. Stands with relatively low LAI in the southern US are most often growth limited by one or more nutrients (usually N or P). They often respond to fertilizer application with greatly increased growth rates. Stands with a high LAI are not limited due to nutrient deficiencies, and usually will not respond enough to fertilizer addition to make it an economically viable treatment.
  • Photosynthesis invariably results in the loss of water through the process of transpiration. To get the trace gas CO2 to diffuse from the atmosphere into leaves so that it may be fixed into sugar, leaves must open small pores in their surface called stomata. When they do this water in the moist interior of the leaf evaporates into the drier air outside the leaf. If trees do not have enough water, they close their stomata to prevent the loss of further water. This also prevents them from acquiring more CO2, and thereby reduces GPP and NPP. Simply put, when water is not plentiful, trees cannot maintain as much leaf area.
  • Different species, and even different individuals within a species, may have different photosynthetic efficiencies. Individuals with different genes are called genotypes. This means that with a given amount of nutrients or water, a more efficient genotype can photosynthesize more and thus grow more than a less efficient tree. It often does so by maintaining greater leaf area, although it is also possible that a highly efficient genotype can actually grow more with the same or fewer leaves (Stovall et al. 2011; Tyree et al. 2009). Despite this complication, across the vast majority of genotypes those with more leaf area are those that grow faster.
  • Within a given genotype, a certain minimum amount of light is required for a single leaf to produce more sugar than it requires for respiration. As trees grow larger, their canopies get taller and lower branches get more and more shaded. Eventually the older branches near the bottom of the canopy no longer receive enough light for the leaves on those branches to support the respiratory cost of maintaining the branch. The trees response to this is self-preservation: it self prunes, shedding the branch that is no longer supporting the growth of the rest of the tree. Due to self-pruning, there is a natural upper limit to the live crown ratio (LCR) of an individual tree and on the LAI of a stand. This limit varies by species, region, and nutrient and water availability.

From these concepts can be derived explanations of why we observe the stand dynamics described in the previous section. For example, on most sites in the south, loblolly pine will maintain about 25 to 30 feet of live crown when growing in a stand. As the tree begins growth, it is shorter than 30 feet, and maintain branches all the way to the ground. Also recall that respiration will be lower in a small tree because it has less sapwood surface area, that sheath of living tissue enveloping all woody parts of the tree. Thus NPP is a larger percentage of GPP in smaller trees, and growth rates are rapid. As the tree exceeds 30 feet in height, the lower branches begin self pruning. The crown may widen over time, but as the tree grows it eventually puts on all the leaf area that it can hold in the space available to it. This is a natural limit on GPP. Simultaneously, the tree is growing larger, and the area of sapwood, fine roots, and other respiratory tissues are increasing. Thus the tree must allocate an ever greater percentage of GPP to respiration as it grows larger, leaving it less and less to allocate to NPP. This progression corresponds to the structures and processes observed in stand initiation, stem exclusion, and understory reinitiation.

Despite the complex ecophysiology involved, the take-home message is simple: young trees grow rapidly at first, but as they become larger, growth slows. This is depicted in the figure and simple equations below. The figure shows what is called a logistic growth curve. This is a common pattern in ecology that characterizes populations or individuals that grow rapidly at first, but eventually reach some sort of carrying capacity, where resources become limiting and growth eventually levels off.

A logistic growth curve showing rapid initial growth that eventually slows to nearly zero growth over time.

Figure 2.4.4. A logistic growth curve relating growth rates (the steepness of the line) to time as a tree ages.

An equation showing that when photosynthesis equals respiration, there is no growth.

Understanding the logistic growth trend explains much of what we do to manage forests.

  • Forest plantations anywhere in the world are grown on relatively short rotations (10-40 years) compared to natural stands. One major driving factor behind this is naturally slowing growth rates that tend to make it more valuable to harvest an existing but slowly growing stand and start anew.
  • We often do not consider thinning natural stands late in a rotation. This is because growth rates have slowed, and allocating more resources to crop trees at this point will only marginally increase the growth rates of already slow-growing trees.

This pattern also explains a tradeoff we face in carbon sequestration in forest ecosystems. If we manage for old growth forest structure, we can store a large amount of carbon over long rotations, but we sequester carbon from the atmosphere at a slow rate because the older trees are growing more slowly and allocating most of GPP to respiration. Conversely, if we manage young, rapidly growing plantations, we store relatively less carbon on site since the trees are smaller, but the rate at which we sequester carbon from the atmosphere is higher since more of GPP is allocated to NPP versus respiration than in an older stand. In deciding what type of stand structure to manage for, it is critical to first determine which is more important: storing more carbon, or sequestering more carbon from the atmosphere (Caroll et al. 2012).

Variables Affecting Carbon Allocation

Trends in carbon allocation vary regionally due to differences in temperature and precipitation. The coldest regions including the subalpine conifer and beech stands on the figure below exhibit the lowest magnitude of all fluxes and pools. Growing seasons are shorter and cooler in cold climates, so GPP (sum of NPP and RA on this diagram) and respiration are less. Warmer climates such as the loblolly pine stand in the US and rain forest in Africa show a greater magnitude of all fluxes, but vary in their allocation to NPP. The loblolly pine stand happens to be younger, and as we have seen previously, is therefore allocating more of GPP to NPP. The greatest GPP (NPP + RA) by far is the Douglas fir stand in the US Pacific Northwest. The Pacific Northwest has forests with greater standing biomass than anywhere else on earth thanks to its combination of high rainfall and moderate temperatures. However, of all these forests this particular stand happens to be the oldest and has the greatest standing biomass (388 tons / acre versus the next highest at 142). Thus this stand is at the top of the logistic growth curve, and must allocate the vast majority of GPP to respiration just to maintain its enormous surface area of living tissue.

A stacked bar graph showing carbon allocation in six forest ecosystems from around the world.

Figure 2.4.5. Differences in carbon allocation from six different forested ecosystems throughout the world that vary in temperature, precipitation, the silvics of the species, and stand structure. Adapted from Waring and Schlesinger (Waring and Schlesinger 1985) with data derived from other sources (Edwards et al. 1981; Grier and Logan 1977; Kinerson et al. 1977).

Trends in carbon allocation also vary within a species and region due to nutrient and water availability. Four treatments were installed, including an untreated control, irrigated, fertilized, and fertilized plus irrigated. From the results below, you can see that as nutrients in particular become less limiting, the trees are able to allocate more total carbon to NPP, and thus growth. This was attributable in large part to an increase in LAI (Albaugh et al. 1998). Despite the total increase in NPP, in all cases NPP remains relatively constant, around 40-43% of GPP. LAI increases GPP, and while the same proportion of GPP is allocated to NPP, NPP does increase in magnitude as a result.

A stacked bar graph showing carbon allocation in 4 loblolly pine stands with varying resource availability.

Figure 2.4.6. How carbon is allocated in a loblolly pine plantation on a nutrient and water deficient sandy site in North Carolina. Adapted from Maier et al. (Maier et al. 2004).

References

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Black, B. A., J. J. Colbert, and N. Pederson. 2008. Relationships between radial growth rates and lifespan within North American tree species. Ecoscience 15:349-357. http://dx.doi.org/10.2980/15-3-3149

Carroll, M., B. Milakovsky, A. Finkral, A. Evans, and M. S. Ashton. 2012. Managing Carbon Sequestration and Storage in Temperate and Boreal Forests. Pages 205-226 in M. S. Ashton, M. L. Tyrrell, D. Spalding, and B. Gentry, editors. Managing Forest Carbon in a Changing Climate. Springer Netherlands. http://dx.doi.org/10.1007/978-94-007-2232-3_10

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