This new paper by Kempes et al published in the journal Plos One adds uncertainty to the already uncertain science of dendrochronology and the attempts at tracking temperature from tree rings.
According to this BBC story:
They found that a 2C (3.6F) increase resulted in the average maximum height of trees shrinking by 11%, while a 2C decrease in the nation’s average temperature saw a 13% increase in the predicted maximum height of trees.
Here’s a figure from the paper showing height change with temperature:
The BCC story continues:
“This looks at the basic physics affecting a tree, such as internal fluid flow and the structure of the canopy,” he told BBC News.
“We really wanted something that was based in those mechanisms but at the same time was, conceptually, relatively simple.”
He said tree branches formed a fractal, which meant that if you effectively cut off a branch and then enlarged it, it looked like a whole tree.
“If you nail down that network structure correctly, then you can use it to predict how things change with size.”
From this framework, the team then incorporated local meteorological data, such as rainfall and mean annual temperatures, to allow them to predict the maximum height of trees in the area.
When compared with official data collected by the US Forest Service, the team found that their predictions tied in closely with the actual measurements.
Clearly, there’s more to tree growth than a simple linear relationship with temperature, and this finding shows an inverse relation with temperature to tree height. Maybe this is why Briffa had to truncate uncooperative tree ring data post 1960 and Mike’s Nature trick was used to “hide the decline”.
Here’s the paper abstract, link to the full paper follows.
Predicting Maximum Tree Heights and Other Traits from Allometric Scaling and Resource Limitations
Christopher P. Kempes, Geoffrey B. West, Kelly Crowell, Michelle Girvan
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.
Here’s how the model and observations match: