OOS 54-5
Competitive interactions between tree species will slow compositional turnover with climate change
Biotic interactions present a challenge in determining whether species’ distributions will track climate change. On the one hand, climate is known to strongly influence species distributions, suggesting climate change should predictably lead to uphill and poleward shifts in these distributions. On the other hand, biotic interactions are ubiquitous and can strongly influence population growth, suggesting climate change induced range shifts will be constrained by biotic interactions. Unfortunately, few studies assess the strength of biotic interactions across large climatic gradients, making it difficult to assess how likely they are to influence compositional turnover with climate change. Here, we combine extensive tree growth data from several dominant conifers in spatially mapped stands distributed across a large elevational gradient on Mt. Rainier (WA, USA) to ask: 1) how strongly is annual growth influenced by competitive neighborhoods across large climatic gradients?; 2) does the strength of competitive interactions depend on the identity of the species competing?; and 3) how closely do estimates of competitive interaction strengths correspond to negative covariances between species estimated from Joint Species Distribution Models (JDSM’s)?
Results/Conclusions
Our results suggest annual tree growth is strongly constrained by competitive interactions for all focal species, suggesting the displacement of cold-adapted and moisture-loving species by warm-adapted and drought tolerant species might lag rapid rates of climate change forecast for the region. Competitive interactions tended to be more negative in warmer and moister climate space, implying competitive dynamics may be particularly important at low elevations where trees are not physiologically stressed. Moreover, results suggest that in many cases, the strength of competitive interactions depend on the identity of the competing species – introducing additional complexity to climate change induced compositional turnover. Interestingly, pairwise competitive interactions quantified from tree growth data are qualitatively similar to covariances between species estimated using JDSM’s applied to the distribution of the same species across large climatic gradients. This suggests that species distribution models which jointly quantify the occurrence of all species in communities relative to the environment and each other could be used to forecast short-term changes in species distributions with climate change. In all, our results suggest that competitive interactions will both slow and add significant complexity to compositional turnover with climate change in forests in the Pacific Northwest, unless disturbance regimes are altered.