From species' traits to forest dynamics - A niche detector for hyperdiverse tropical forests
Zusammenfassung der Projektergebnisse
In order to sustainably manage tropical forests and to forecast the pace of climate change, it is necessary to be able to predict how fast regrowing or logged forests recover. To achieve this, certain parameters must be known; how quickly do the trees grow and how quickly do they die? How many offspring do they produce? Using data which has been recorded for 282 tree species in Panama over the past 40 years in one of the most researched tropical rainforests in the world, we were able to show that trees pursue different strategies during their development. On the one hand, they differ in terms of their pace of life; while ‘fast’ species both grow and die quickly, ‘slow’ species grow slowly and reach an old age. On the other hand, trees can differ regarding their stature, irrespective of pace of life. Here, ‘infertile giants’, also known as long-lived pioneers, grow relatively quickly and live relatively long – and consequently reach a tall stature – but produce only a few offspring per year. ‘Fertile dwarfs’, in contrast, are small shrubs and treelets which grow slowly and do not live long, but produce a large number of offspring. But how many, and which factors of this demographic diversity have to be taken into account in order to be able to predict the development of a diverse forest? We used a digital experiment to answer this question. In a computer model, we simulated how trees grow, die, produce offspring and compete for light as in a real forest. We allowed different configurations of the model to compete against each other; these contained either all 282 species from Panama or only a few selected ‘strategy types’. The species differed in only one or two respects; their pace of life and their stature. The respective model predictions were then compared with the observed recovery of real, regrowing secondary forests. We found that the model worked reliably with only five strategy types, but that both strategy dimensions must be taken into account. In particular, the long-lived pioneers are important because they account for a large share of the biomass – and carbon – in this forest at almost all ages, and not only in middle-aged forests as assumed so far. In sum, we were able to rigorously reduce the rich tropical tree diversity to a few strategy types which are essential to making accurate predictions of forest dynamics and carbon storage. Our approach is completely data-driven and does not rely on the usual tedious adjustment and calibration of unknown model parameters, thus saving both time and resources. Along with the increasing availability of tropical forest inventory data, such workflows advance our ability to predict the pace of climate change and to support the evidence-based planning of forest restoration and sustainable tropical forest management by predicting rates and trajectories of forest regrowth both at the species and community level.
Projektbezogene Publikationen (Auswahl)
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2018. Beyond the fast–slow continuum: demographic dimensions structuring a tropical tree community. Ecology Letters 21: 1075–1084
Rüger, N., L.S. Comita, R. Condit, D. Purves, B. Rosenbaum, M.D. Visser, S.J. Wright, and C. Wirth
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2019. Dry season soil water potential maps of a 50 hectare tropical forest plot on Barro Colorado Island, Panama. Scientific Data 6:63
Kupers, S.J., C. Wirth, B.M.J. Engelbrecht, and N. Rüger
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2019. Growth responses to soil water potential indirectly shape local species distributions of tropical forest seedlings. Journal of Ecology 107: 860–874
Kupers, S.J., B.M.J. Engelbrecht, S.J. Wright, A. Hernández, C. Wirth, and N. Rüger
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2019. Performance of tropical forest seedlings facing shade and drought: an interspecific tradeoff in demographic responses. Scientific Reports 9:18784
Kupers, S.J., C. Wirth, B.M.J. Engelbrecht, A. Hernández, R. Condit, S.J. Wright, and N. Rüger
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2020. Demographic trade-offs predict tropical forest dynamics. Science 368: 165–168
Rüger, N., R. Condit, D.H. Dent, S.J. DeWalt, S.P. Hubbell, J.W. Lichstein, O.R. Lopez, C. Wirth, and C.E. Farrior
