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Keywords:

  • CAIN;
  • competition;
  • dynamic vegetation models;
  • eastern USA;
  • forest dynamics;
  • gap model;
  • plant functional types;
  • process-based modelling;
  • range limits;
  • tree demography

Abstract

Aim

The geographic distributions of different forest types are expected to shift in the future under altered climatic conditions. At present, the nature, magnitude and timing of these shifts are uncertain because we lack a quantitative understanding of how forest distributions emerge from climate- and competition-related variation in underlying demographic processes. Forest dynamics result primarily from the manner in which the physical environment and competition for limiting resources affect tree growth, mortality and recruitment. We sought to uncover the relative importance of these processes in controlling the geographic limits of different forest types.

Location

Eastern USA.

Methods

We parameterized a climate-dependent forest dynamics model with extensive observations of tree growth, mortality and recruitment from forest inventory data. We then implemented the resulting demographic models in simulations of joint population dynamics for seven plant functional types (PFTs) across the region. By removing various climate effects in a series of simulation experiments, we assessed the importance of climate-dependent demography and competition in limiting forest distributions.

Results

Distributions that emerged from simulated population dynamics approximated the current distributions for all seven PFTs well and captured several known patterns of succession. Temperature-related increases in mortality determined the southern boundaries of three out of four boreal and northern temperate PFTs, whereas temperature-related decreases in recruitment controlled the northern limit of all three southern temperate PFTs. Changes in growth rates and competitor performance had only minor effects on the distribution limits of most PFTs.

Main conclusions

Our results imply that dynamic global vegetation models, which are widely used to predict future vegetation distributions under climate change, should seek to more appropriately capture the observed climate sensitivity of mortality and recruitment. Understanding the mechanisms controlling forest distributions will enable better predictions of their future responses to climate change.