Effect of novel competitors
The addition of novel competitors did not significantly affect the
abundance of the alpine species, and none of the four trait axes of the
full PCA correlated with species’ demographic response to the treatment
(Figures S16-S17, Table S5).
Discussion
As climate warming continues (IPCC 2021), predicting which species will
“win” or “lose” is crucial for community- and ecosystem-level
predictions. Here, we measured the abundance change of 16 alpine plant
species as a response to climate warming in a manipulative field
experiment, and related these responses to species traits. We found that
species’ demographic responses to the manipulation could be predicted by
their size and water use strategy: small species with a more prolific
water use suffered most from the transplantation to warmer and drier
climates. Climate change is likely to influence water availability in
the Alps by increasing the frequency and severity of heatwaves (Beniston
2004). Consequently, water limitation is likely to become an important
driver of community change in alpine grasslands.
The advantage of traits related to conservative water use in a warming
climate has been shown before: morphological traits describing
conservative water use were related to increased abundance after warming
in mountain plant communities (Soudzilovskaia et al. 2013), and
drier conditions are likely to promote resource-conservative species in
the Arctic (Bjorkman et al. 2018) and in the Mediterranean
(Pérez-Ramos et al. 2012). Soil drying can be an important driver
of plant community dynamics in other alpine and Arctic systems (Harte &
Shaw 1995; Chapin III et al. 1996). In our experiment, the
largest change in species abundance occurred after a drought in 2018
that was particularly pronounced at the warmest site (Figure S18).
Increased frequency of these types of extreme events could be critical
for future plant community structure in the Alps (Jentsch &
Beierkuhnlein 2008; Liu et al. 2015).
Consistent with our assertion that climate change poses more of a water
than a temperature challenge in our study system, we did not observe a
shift towards species with higher thermal optima (i.e. higher
Topt and lower Q10). Such a shift would
be expected if changes in community composition were driven by
physiological adaptations to temperature per se . Previous studies
have recorded “thermophilization” of alpine and Arctic plant
communities due to climate warming, i.e. a shift towards
“warm-adapted” species, as inferred from their distribution (Gottfriedet al. 2012; Govaert et al. 2021; Lynn et al.2021). Nevertheless, the distributional limit of a species might not
reflect adaptation to temperature as such, but rather to correlated
factors, such as soil moisture or competition. For example, competitive
ability is likely to trade-off with cold tolerance (Koehler et
al. 2012; Pellissier et al. 2018), allowing species without
specific cold-adaptations to persist with higher levels of competition.
In general, higher temperatures are rarely detrimental for alpine or
arctic plants (Chapin 1983; Gauslaa 1984) and optimal temperatures for
plant gas exchange change only a little across temperature gradients
(Körner & Diemer 1987).
Predicting the winners and losers in our experiment was possible by
measuring either eco-physiological (long-term water use efficiency and
stomatal conductance) or size-related morphological traits, and could
have been possible with relatively few easily-measured traits (e.g.
width and leaf area). Even though the individual morphological traits
did not correlate with physiological processes, the whole morphological
trait space correlated with the physiological trait space. Consequently,
using size-related morphological traits resulted in a similar estimate
of winning and losing species than using the full trait data set or
eco-physiological traits only (Figure 4). Nevertheless, the
interpretation of the mechanism behind species either “winning” or
“losing” would be different depending on which traits are used for the
predictions: a correlation with size-related traits would not reveal the
role of water use strategy and decreasing soil moisture as potential
drivers of community change.
Traits explained 10% of the variation in cover and 12% of the
variation in frequency, less than for example 40% in Wright et
al. (2010) (but more than e.g., 3% in Paine et al. 2015).
Nevertheless, we think the variation explained by traits should be
compared to that explained by species identity (25% and 12%,
respectively). In our experiment, plant cover and frequency were likely
changing due to several factors which did not relate to differences
between species, and thus could not be captured by trait measurements
(e.g., chance events, microclimate). Our trait measurements captured
almost half (40%, Table S3) of the species-specific variation in cover
change and all the variation in species-specific frequency change. Thus,
in our study, traits were able to effectively capture the species-level
differences in demographic rates, although better for one metric
(frequency) than for the other (cover).
We observed within-species changes in most of the traits measured at
multiple elevations, with the exact responses differing between species
and traits. Contrary to previous studies (Pérez-Ramos et al.2019; Zhang et al. 2020) and to our expectations, trait
plasticity was not important in explaining demographic change (but see
Block et al. 2020). A potential explanation is that the magnitude
of plastic responses to (even severe) climate change is small compared
to trait difference between species (Aerts et al. 2007;
Soudzilovskaia et al. 2013, Table S8). Our results highlight
that, despite the potential importance of plasticity, species-level
trait values can be useful for demographic predictions (Albert et
al. 2011; Kichenin et al. 2013).
Although communities shifted towards species with more conservative
water use under warming, the plastic response showed the opposite
pattern: at warmer, lower -elevation sites, individual species showed
lower δ18O (higher stomatal conductance) and lower δ13C (lower water use efficiency). These trends likely
follow from the increasing atmospheric pressure and temperature with
decreasing altitude (Körner et al. 1991). Higher
CO2 partial pressure resulting in more constrained
CO2 diffusion through stomata (Smith & Donahue 1991;
Terashima et al. 1995; Wang et al. 2017), higher oxygen
partial pressure resulting in lower carboxylation efficiency of Rubisco
(Farquhar & Wong 1984), and higher temperature resulting in decreased
viscosity of water and faster transport from roots to leaves (Roderick
& Berry 2001), should all result in lower δ18O and
δ13C values within species at lower elevations (Körneret al. 1988, 1991). This elevation-related shift to more
inefficient water use might have resulted in a larger decrease in
abundance in our experiment than would have taken place due to warming
alone. Nevertheless, we think the mechanism identified (decreased water
availability due to warming and the importance of water use traits)
holds, even if the demographic effects of the water limitation might
have been overestimated.
Contrary to our predictions, traits did not explain demographic changes
caused by novel competitors. This is likely because the treatment had a
relatively small influence on the resident community (Figures S16-S17).
The treatment was set up to mimic the initial establishment of
low-elevation species into alpine communities, and the four years of the
experiment were likely not enough for them to significantly affect the
alpine species.