Limits...
Predicting maximum tree heights and other traits from allometric scaling and resource limitations.

Kempes CP, West GB, Crowell K, Girvan M - PLoS ONE (2011)

Bottom Line: In addition to predicting maximum tree height in an environment, our framework can be extended to predict how other tree traits, such as stomatal density, depend on these resource constraints.Furthermore, it offers predictions for the relationship between height and whole canopy albedo, which is important for understanding the Earth's radiative budget, a critical component of the climate system.Because our model focuses on dominant features, which are represented by a small set of mechanisms, it can be easily integrated into more complicated ecological or climate models.

View Article: PubMed Central - PubMed

Affiliation: Department of Earth Atmosphere and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America. ckempes@mit.edu

ABSTRACT
Terrestrial vegetation plays a central role in regulating the carbon and water cycles, and adjusting planetary albedo. As such, a clear understanding and accurate characterization of vegetation dynamics is critical to understanding and modeling the broader climate system. Maximum tree height is an important feature of forest vegetation because it is directly related to the overall scale of many ecological and environmental quantities and is an important indicator for understanding several properties of plant communities, including total standing biomass and resource use. We present a model that predicts local maximal tree height across the entire continental United States, in good agreement with data. The model combines scaling laws, which encode the average, base-line behavior of many tree characteristics, with energy budgets constrained by local resource limitations, such as precipitation, temperature and solar radiation. In addition to predicting maximum tree height in an environment, our framework can be extended to predict how other tree traits, such as stomatal density, depend on these resource constraints. Furthermore, it offers predictions for the relationship between height and whole canopy albedo, which is important for understanding the Earth's radiative budget, a critical component of the climate system. Because our model focuses on dominant features, which are represented by a small set of mechanisms, it can be easily integrated into more complicated ecological or climate models.

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Comparisons between observed and predicted maximum tree heights.Maps of the continental United States comparing (A) observed and (B) predicted maximum heights of trees. (C) Histogram showing the distribution of deviations of the predicted maximum tree heights, , from their measured values, , expressed in terms of the dimensionless ratio . The median of the entire distribution is  and  values less than  were omitted from the histogram.
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pone-0020551-g001: Comparisons between observed and predicted maximum tree heights.Maps of the continental United States comparing (A) observed and (B) predicted maximum heights of trees. (C) Histogram showing the distribution of deviations of the predicted maximum tree heights, , from their measured values, , expressed in terms of the dimensionless ratio . The median of the entire distribution is and values less than were omitted from the histogram.

Mentions: Here we create a model of plant physiology that focuses almost entirely on these scaling laws which we connect with an energy budget approach and couple to environmental resources in order to calculate an important component of this variation. In particular, we incorporate the relationships between basal metabolic rate, water availability, incoming solar energy, heat loss and ambient temperature. Because the underlying scaling laws represent the average tendencies across many species we apply a single tree characterization to a variety of environments. In our framework plant diversity is encapsulated according to the average trends across many species and the scaling laws allow us to use a single parameter, tree size, to determine a range of physiological traits. We show that this model successfully predicts the local and regional variation of maximum tree heights from a small number of environmental parameters (Fig. 1). This coupling of various scaling laws also predicts more complicated relationships for tree traits such as the sigmoidal decrease in canopy albedo with increasing height. Our model can be extended to predict the variation of other plant traits and we show how stomatal density depends on local mean annual temperature.


Predicting maximum tree heights and other traits from allometric scaling and resource limitations.

Kempes CP, West GB, Crowell K, Girvan M - PLoS ONE (2011)

Comparisons between observed and predicted maximum tree heights.Maps of the continental United States comparing (A) observed and (B) predicted maximum heights of trees. (C) Histogram showing the distribution of deviations of the predicted maximum tree heights, , from their measured values, , expressed in terms of the dimensionless ratio . The median of the entire distribution is  and  values less than  were omitted from the histogram.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3113805&req=5

pone-0020551-g001: Comparisons between observed and predicted maximum tree heights.Maps of the continental United States comparing (A) observed and (B) predicted maximum heights of trees. (C) Histogram showing the distribution of deviations of the predicted maximum tree heights, , from their measured values, , expressed in terms of the dimensionless ratio . The median of the entire distribution is and values less than were omitted from the histogram.
Mentions: Here we create a model of plant physiology that focuses almost entirely on these scaling laws which we connect with an energy budget approach and couple to environmental resources in order to calculate an important component of this variation. In particular, we incorporate the relationships between basal metabolic rate, water availability, incoming solar energy, heat loss and ambient temperature. Because the underlying scaling laws represent the average tendencies across many species we apply a single tree characterization to a variety of environments. In our framework plant diversity is encapsulated according to the average trends across many species and the scaling laws allow us to use a single parameter, tree size, to determine a range of physiological traits. We show that this model successfully predicts the local and regional variation of maximum tree heights from a small number of environmental parameters (Fig. 1). This coupling of various scaling laws also predicts more complicated relationships for tree traits such as the sigmoidal decrease in canopy albedo with increasing height. Our model can be extended to predict the variation of other plant traits and we show how stomatal density depends on local mean annual temperature.

Bottom Line: In addition to predicting maximum tree height in an environment, our framework can be extended to predict how other tree traits, such as stomatal density, depend on these resource constraints.Furthermore, it offers predictions for the relationship between height and whole canopy albedo, which is important for understanding the Earth's radiative budget, a critical component of the climate system.Because our model focuses on dominant features, which are represented by a small set of mechanisms, it can be easily integrated into more complicated ecological or climate models.

View Article: PubMed Central - PubMed

Affiliation: Department of Earth Atmosphere and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America. ckempes@mit.edu

ABSTRACT
Terrestrial vegetation plays a central role in regulating the carbon and water cycles, and adjusting planetary albedo. As such, a clear understanding and accurate characterization of vegetation dynamics is critical to understanding and modeling the broader climate system. Maximum tree height is an important feature of forest vegetation because it is directly related to the overall scale of many ecological and environmental quantities and is an important indicator for understanding several properties of plant communities, including total standing biomass and resource use. We present a model that predicts local maximal tree height across the entire continental United States, in good agreement with data. The model combines scaling laws, which encode the average, base-line behavior of many tree characteristics, with energy budgets constrained by local resource limitations, such as precipitation, temperature and solar radiation. In addition to predicting maximum tree height in an environment, our framework can be extended to predict how other tree traits, such as stomatal density, depend on these resource constraints. Furthermore, it offers predictions for the relationship between height and whole canopy albedo, which is important for understanding the Earth's radiative budget, a critical component of the climate system. Because our model focuses on dominant features, which are represented by a small set of mechanisms, it can be easily integrated into more complicated ecological or climate models.

Show MeSH
Related in: MedlinePlus