Forest management is a key strategy for climate change mitigation: incentives such as the UN REDD+ policy framework, have emerged to safeguard forest areas acting as natural carbon reservoirs. However, to ensure that forests are managed effectively, researchers need a better understanding of how individual species behave over time, and how carbon storage in their biomass will respond to climate change.
New research, led by Nadja Rüger of the German Centre for Integrative Biodiversity Research, and Caroline Farrior of the University of Texas at Austin, could help researchers accurately predict forest carbon dynamics in the future.
‘As climate change looms, we’re moving into scenarios that we haven’t seen before,’ says Farrior. ‘There’s so much forest across the world that isn’t managed effectively. Having a mechanistic understanding of the carbon storage potential of forests, both in the present and future, has huge implications for predicting the effects of climate change.’
Rüger and the team have a clear mission: ‘To improve vegetation models, so that they can be reliably coupled with climate models.’ Simple enough – the only snag is that tropical forests form some of the richest biomes on earth. Diverse forests will not change as monolithic units; each species of tree will react differently, forming dynamic structures of forests that current vegetation models are unequipped to accurately predict.
The team’s research could simplify the problem of this diversity. Using trait data of 282 tree species within the tropical forest of Barro Colorado Island, Panama, they demonstrated that complex tree dynamics, such as growth, reproduction, and biomass, can be modelled using just two axes of tree characteristics.
The traits of individual forest species are usually mapped according to the balance between growth and survival – organisms that grow fast usually die young, or they grow slowly and reach longevity. However, the new research factors in the characteristics of stature and reproduction – organisms that grow tall invest lightly in reproduction, whereas shorter ones produce many offspring.
By incorporating the stature-reproduction axis, the researchers were able to factor in the taller, older trees that were overlooked by previous models of growth and survival. The new model shows that so called ‘long-lived pioneer’ species that reproduce slowly, constitute a large proportion of forest biomass and are therefore critical for long-term carbon storage.
Farrior thinks that researchers are now sharpening their predictive toolkit for understanding forests’ responses to climate change: ‘We’re getting closer to having a model that’s predictive.’ The next step will be to use predictive forest models to guide management strategies that protect the species which have the highest carbon-storage potential.