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Jesse B Nippert

Publications and source records attributed to Jesse B Nippert.

2 recordsLinked to original sources

Estimating leaf-level parameters for ecosystem process models: a study in mixed conifer canopies on complex terrain.

Ecosystem process models are often used to predict carbon flux on a landscape or on a global scale. Such models must be aggregate and canopies are often treated as a uniform unit of foliage. Parameters that are known to vary within the canopy, e.g., nitrogen content and leaf mass per area, are often estimated by a mean value for the canopy. Estimating appropriate means is complicated, especially in mixed-species stands and in complex terrain. We analyzed sources of variation in specific parameters with the goal of testing various simplifying assumptions. The measurements came from mixed-species forests in the northern Rocky Mountains. We found that, for three important parameters (nitrogen concentration and content, and leaf mass per area), a sample taken near the vertical center of the crown provided a good estimate of the mean values for the crown. Altitude (700-1700 m), solar insolation (4200-5400 MJ m(-2) year(-1)) and leaf area index (1-11) had negligible effects on the parameters; only species differences were consistently detected. The correlation between mass-based photosynthetic rates and mass-based nitrogen concentrations was much weaker than the correlation between area-based photosynthetic rates and area-based nitrogen concentration. Comparison of photosynthesis-nitrogen relationships for a wide variety of conifer species and sites revealed a broad general trend that can be used in models. These results suggest important potential simplifications in model parameterization, most notably that canopy means can be estimated with ease, that complex terrain is a minor source of variation in these parameters and that use of one photosynthesis-nitrogen relationship for conifer species does not result in large errors. Species-to-species variation, however, was large and needs to be accounted for when parameterizing process models.

Altitude↗

Sources of variation in ecophysiological parameters in Douglas-fir and grand fir canopies.

Forest process models predict ecosystem responses from climate variables and physiological parameters. The parameters describe key ecosystem attributes, often as lumped averages. However, the sources and magnitude of variation in these physiological parameters are unknown, which complicates sampling if models are to be parameterized with field measurements. We measured several key parameters, which had been identified by sensitivity analyses of three models, in Abies grandis (Dougl.) Lindl. and Pseudotsuga menziesii var. glauca (Beissn.) Franco trees throughout the growing season. Trees were sampled at eight sites across the interior northwest of the USA. At each site, fertilized and control plots were sampled. The design provided statistical replication for the analysis of variance within a site, allowing us to draw inferences about a regional population of stands. Specific leaf area (SLA) varied by canopy position and treatment (P = 0.0003), by date of sampling (P < 0.0001) and by species (P = 0.0188). Mass-based foliar nitrogen concentration (%N) increased during the summer in both species (P = 0.0019), but at a faster rate in P. menziesii var. glauca than in A. grandis. Sun foliage had a higher mean %N (1.00, SE = 0.02%) than shade foliage (0.92 +/- 0.01%). Apparent quantum yield (Phi) varied among treatments, between species and between canopy positions; each of these variables interacted with date of sampling (P = 0.0207, P < 0.0001 and P = 0.0344, respectively). In A. grandis, mean Phi values (+/- SE) were 0.048 +/- 0.006 mol CO2 (mol incident photon)-1 for sun foliage and 0.067 +/- 0.007 mol CO2 (mol incident photon)(-1) for shade foliage. In P. menziesii, the corresponding mean Phi values were 0.032 +/- 0.003 and 0.047 +/- 0.004 mol CO2 (mol incident photon)-1. Parameters SLA, %N and Phi were all influenced by date, fertilizer treatment, species and crown position. We discuss methods of inferring quantum yields from light response curves and their utility for parameterizing process models. Parameter mean values are presented for each site; these tables provide a documented data set for the parameterization of models describing the western interior forests of the USA.

Cell Respiration↗