Analysis of a Farquhar-von Caemmerer-Berry leaf-level photosynthetic rate model for Populus tremuloides in the context of modeling and measurement limitations.

The balance of mechanistic detail with mathematical simplicity contributes to the broad use of the Farquhar, von Caemmerer and Berry (FvCB) photosynthetic rate model. Here the FvCB model was coupled with a stomatal conductance model to form an [A,g(s)] model, and parameterized for mature Populus tremuloides leaves under varying CO(2) and temperature levels. Data were selected to be within typical forest light, CO(2) and temperature ranges, reducing artifacts associated with data collected at extreme values. The error between model-predicted photosynthetic rate (A) and A data was measured in three ways and found to be up to three times greater for each of two independent data sets than for a base-line evaluation using parameterization data. The evaluation methods used here apply to comparisons of model validation results among data sets varying in number and distribution of data, as well as to performance comparisons of [A,g(s)] models differing in internal-process components.

Forest patch modeling: using high performance computing to simulate aboveground interactions among individual trees.

Functional-structural plant models (FSPMs) typically integrate suites of detailed physiological and phenological processes to simulate the growth of individual plants. Recent advances in high-performance computing have allowed FSPMs to be extended to patches of interacting trees. Here, we describe a parallel modelling strategy to run simultaneous individual tree models across an 8 × 8 patch of trees. The 64 'core' trees are surrounded by multiple rings of neighbour trees to remove edge effects. A sensitivity analysis of the patch model demonstrates that computational factors such as the number of independently simulated trees (9 v. 36) or number of neighbour rings (3 v. 6) did not significantly influence model estimates of tree volume growth. Updated submodels for phenology and redistribution of overwinter carbohydrate storage allow the simulation to be more responsive to above ground competition among trees in a patch over multiple growing seasons. An 8-year patch-scale simulation of aspen clones 216 and 259 was conducted using high-resolution environmental data from the Aspen FACE Experiment, a long-term free-air carbon dioxide enrichment (FACE) study. Tree heights and volumes were comparable to 8-year growth measurements made at the Aspen FACE site.

Integrated measures of anthropogenic stress in the U.S. Great lakes basin.

Integrated, quantitative expressions of anthropogenic stress over large geographic regions can be valuable tools in environmental research and management. Despite the fundamental appeal of a regional approach, development of regional stress measures remains one of the most important current challenges in environmental science. Using publicly available, pre-existing spatial datasets, we developed a geographic information system database of 86 variables related to five classes of anthropogenic stress in the U.S. Great Lakes basin: agriculture, atmospheric deposition, human population, land cover, and point source pollution. The original variables were quantified by a variety of data types over a broad range of spatial and classification resolutions. We summarized the original data for 762 watershed-based units that comprise the U.S. portion of the basin and then used principal components analysis to develop overall stress measures within each stress category. We developed a cumulative stress index by combining the first principal component from each of the five stress categories. Maps of the stress measures illustrate strong spatial patterns across the basin, with the greatest amount of stress occurring on the western shore of Lake Michigan, southwest Lake Erie, and southeastern Lake Ontario. We found strong relationships between the stress measures and characteristics of bird communities, fish communities, and water chemistry measurements from the coastal region. The stress measures are taken to represent the major threats to coastal ecosystems in the U.S. Great Lakes. Such regional-scale efforts are critical for understanding relationships between human disturbance and ecosystem response, and can be used to guide environmental decision-making at both regional and local scales.

Environmentally stratified sampling design for the development of Great Lakes environmental indicators.

Understanding the relationship between human disturbance and ecological response is essential to the process of indicator development. For large-scale observational studies, sites should be selected across gradients of anthropogenic stress, but such gradients are often unknown for apopulation of sites prior to site selection. Stress data available from public sources can be used in a geographic information system (GIS) to partially characterize environmental conditions for large geographic areas without visiting the sites. We divided the U.S. Great Lakes coastal region into 762 units consisting of a shoreline reach and drainage-shed and then summarized over 200 environmental variables in seven categories for the units using a GIS. Redundancy within the categories of environmental variables was reduced using principal components analysis. Environmental strata were generated from cluster analysis using principal component scores as input. To protect against site selection bias, sites were selected in random order from clusters. The site selection process allowed us to exclude sites that were inaccessible and was shown to successfully distribute sites across the range of environmental variation in our GIS data. This design has broad applicability when the goal is to develop ecological indicators using observational data from large-scale surveys.

An interregional validation of ECOPHYS, a growth process model of juvenile poplar clones.

Field data from poplar plantations in Michigan, Washington, and Wisconsin were used to validate ECOPHYS, a whole-tree growth process model for juvenile poplar. Five clones representing a range of morphological, phenological, and physiological characteristics were planted on the same date at the three sites. Height and diameter measurements were made monthly on 20 trees per clone, and intensive morphological measurements were made every two weeks on two trees per clone. Hourly solar radiation and temperature data were recorded at each site over the growing season. The model was run for each clone x site combination with the weather data and clonal parameters as inputs. A repeated measures ANOVA indicated that there were significant differences in height growth patterns among both clones and sites, as well as significant clone x site interactions. The model generally predicted height growth within a standard deviation of the field plantation means; three of the 15 clone x site simulations were significantly different from the plantation means. The median error between predicted and observed values was 5%. Evaluation of the clonal parameters showed that differences in photosynthetic rates, morphological attributes such as specific leaf area, and timing of budset are primary factors leading to differences in growth.

Validation of photosynthate production in ECOPHYS, an ecophysiological growth process model of Populus.

A model of photosynthate production is the central component of a larger whole-tree ecophysiological growth process model for Populus (ECOPHYS). This photosynthesis model was validated by comparing predicted photosynthate production values for individual leaves and the total tree with hourly field measurements collected on four days spaced throughout a growing season. Simulated trees had identical numbers of leaves and leaf areas as the sample trees studied in the field, and hourly weather data collected on the plantation site were supplied as a model input. Total production for the four sample days ranged between 200 and 4900 mg CO(2) tree(-1) day(-1). Model predictions of total daily photosynthate production were within 12% of the observed rates for three of the four sampling days. Diurnal variations in stomatal conductance and ambient CO(2) concentrations and seasonal variations in area leaf weight were the primary sources of error. Total leaf area, proportion of sunlit leaf area, and photosynthetic efficiency were the most important factors influencing carbon dioxide exchange rates.