Nitrogen productivity of Alaskan tree species at an individual tree and landscape level

Ecology, Dec, 1997 by John Yarie

INTRODUCTION

The N-productivity concept (Ingestad 1977, 1987, Agren 1983, 1996) or the foliage nitrogen efficiency concept (Kimmins 1993) represents an approach to estimate primary production of an individual tree to stand or landscape levels across the earth's surface. Linking the understanding of spatial, temporal, and spectral components of a landscape will be a challenging task over the next several years (Roughgarden et al. 1991, Ustin et al. 1991). The development of methods to estimate the thermal structure of the land surface are well on the way (Wessman 1990, Rignot et al. 1994a). The estimation of various land surface characteristics, such as vegetation biomass (Rignot et al. 1994b) and foliage chemical concentrations (Matson et al. 1994), is also progressing. However, the use of data sets in simulation models at the tree, stand, and landscape levels is just starting. One means of facilitating this development is to run ecosystem simulation models within a Geographic Information System (GIS) framework at various plot (individual unit, cell) sizes without changing the structure of the entire model. The capability to model ecosystem dynamics at various spatial scales within a GIS framework will result from a simple change of the basic cell size. It should be possible to easily expand from an individual tree model of growth at a cell size of 1 [m.sup.2] to a stand or landscape level with cell sizes of 1 ha to 1 [km.sup.2] or greater. As a first step in this process, the nitrogen (N)-productivity concept (Ingestad 1977, 1987, Agren 1983, 1996) can be used to model forest growth as a subroutine within a GIS environment.

This paper will examine the use of a simple equation, based on the N-productivity concept, to estimate plant production from the individual tree to stand-level geographic units. It then will be possible to estimate the maximum production for areas of the land surface based on foliar N content derived from a combination of Synthetic Aperture Radar (SAR) estimates for aboveground biomass (Rignot et al. 1994b) and multichannel remote sensing measures of canopy chemistry (Matson et al. 1994).

Nitrogen-productivity concept

The N-productivity concept (Ingestad 1977, 1980, 1981, Agren 1983, 1985) can be defined as the amount of annual production per unit of foliar nitrogen:

dW/dt = Pn x N (f x [W.sub.f]) (1)

where W is plant or stand aboveground biomass, t is the time frame of consideration (day to year), Pn is the N productivity (biomass production/foliar nitrogen content), N is foliar nitrogen content, f is the rate of foliage tissue mortality, and [W.sub.f] is foliage biomass.

At steady state nutrition [d(N/W)/dt = 0] the plant growth rate is proportional to the amount of foliar nitrogen and the N productivity (Pn). The N productivity is at a maximum during the exponential growth phase and is dependent on a number of plant properties, including genotypic properties, weather conditions, self-shading, and ageing. There is a decrease in the N productivity factor due to self-shading and plant ageing (Agren 1983) such that:

Pn = [Pn.sub.max] - (b x [W.sub.f]) (2)

where [Pn.sub.max] is the maximum N productivity and b is considered an ageing and/or light extinction parameter.

Eq. 2 represents a method to calculate the N productivity of individual seedlings (Ingestad 1979a, b, Ingestad and Kahr 1985) and stands of trees (Agren 1983). The decrease in N productivity due to self-shading and ageing will vary during growth and may be zero in the early stages of the growth of the plant. Then b in Eq. 2 can be represented by a simple function that is zero until a defined foliage biomass is accumulated. It should be possible to develop both Eqs. 1 and 2 for calculation of the N productivity for individual trees and forest stands on a specified land area basis.

METHODS

Individual-tree N productivity

A total of 239 white spruce (Picea glauca), 24 aspen (Populus tremuloides), 58 white birch (Betula papyrifera), and 33 balsam poplar (Populus balsarnifera) trees were available for calculation of the observed N productivity. The trees were randomly selected from a number of successional sites within the Bonanza Creek Experimental Forest (BNZ) Long-Term Ecological Research (LTER) program (unpublished data available on BNZ LTER World Wide Web home page)(1) and Yarie and Van Cleve (1996). N productivity was calculated based on (1) midseason, green-foliage (dry mass) N content for 1989 and (2) aboveground tree production based on the difference in calculated biomass between 1989 and 1993 converted to a yearly average. N productivity was calculated for all the sampled trees. The trees that represented maximum N productivity values for 2-cm diameter classes were selected for the N productivity analysis. This subset included 33 white spruce, 10 aspen, 14 white birch, and 26 balsam poplar, and represent the maximum N productivity.

N productivity for individual trees was calculated by dividing estimated aboveground production by the foliar N content. Aboveground tree biomass was calculated by determining stemwood and foliage biomass for the hardwoods and total biomass for white spruce in 1993 and 1989. The biomass estimates were based on a set of allometric equations developed from sample trees within interior Alaska (Yarie et al., unpublished data). Annual production for hardwoods was calculated by subtracting the two stemwood biomass values and dividing by the number of years between the estimates of biomass. Foliage production for hardwoods was estimated as the biomass in both years and divided by two to obtain an average. Annual production for white spruce was estimated by calculating the difference in total biomass in 1993 and 1989 and then dividing by the number of years. This will result in a small decrease in total aboveground production for white spruce because litterfall was not included. This yielded a data set that was not associated with a specific landscape unit but instead represented a range of site qualities.