Abstract
AbstractAimClimate change will likely modify the global distribution of biomes, but the magnitude of change is debated. Here, we followed a trait‐based, statistical approach to model the influence of climate change on the global distribution of biomes.LocationGlobal.MethodsWe predicted the global distribution of plant community mean specific leaf area (SLA), height and wood density as a function of climate and soil characteristics using an ensemble of statistical models. Then, we predicted the probability of occurrence of biomes as a function of the three traits with a classification model. Finally, we projected changes in plant community mean traits and corresponding changes in biome distributions to 2070 for low (RCP 2.6; +1.2°C) and extreme (RCP 8.5; +3.5°C) future climate change scenarios.ResultsWe estimated that under the low climate change scenario (sub)tropical biomes will expand (forest by 18%–22%, grassland by 9%–14% and xeric shrubland by 5%–8%), whereas tundra and temperate broadleaved and mixed forests contract by 30%–34% and 16%–21%, respectively. Our results also indicate that over 70%–75% of the current distribution of temperate broadleaved and mixed forests and temperate grasslands is projected to shift northwards. These changes become amplified under the extreme climate change scenario in which tundra is projected to lose more than half of its current extent.Main conclusionsOur results indicate considerable imminent alterations in the global distribution of biomes, with possibly major consequences for life on Earth. The level of accuracy of our model given the limited input data and the insights on how trait–environment relationships can influence biome distributions suggest that trait‐based correlative approaches are a promising tool to forecast vegetation change and to provide an independent, complementary line of evidence next to process‐based vegetation models.
Highlights
To draw sufficiently grounded conclusions on biome expansions, contractions and shifts in response to climate change, the extent of biomes should be large enough to have a good predictive accuracy (Table 1), which is why we focused on the seven most widespread biomes: tundra, boreal forest, tropical moist forest, temperate mixed forest, tropical grassland, temperate grassland and xeric shrubland
We have built upon global models linking climate to plant traits and plant traits to biomes (e.g. Boonman et al, 2020; Madani et al, 2018; van Bodegom et al, 2014) to project biome distribution changes under a low and extreme climate change scenario
Our results suggest that tropical biomes will flourish, while temperate biomes will shift northwards and reduce in extent, tundra
Summary
Similar to how DGVMs use physiological processes as an intermediate step between climate and vegetation structure, this intermediate step allows us to include trait variation of different species in similar environments and trait adaptation of similar species in different environments This intermediate step introduces a causal link between climate and biomes (e.g. the conversion of water availability to respiration via specific leaf area, and of temperature to metabolism via wood density and height), reducing the risk of establishing spurious relationships Alo & Wang, 2008; Gonzalez et al, 2010; Scholze et al, 2006; Sitch et al, 2008), this study may bring new insights into the underlying causes of vegetation change (Boonman et al, 2020; Madani et al, 2018; van Bodegom et al, 2014) This may help to assess ecological consequences of climate change and may aid the allocation of large-scale conservation efforts (Laughlin, 2014)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
