Plastic Population Effects and Conservative Leaf Traits in a Reciprocal Transplant Experiment Simulating Climate Warming in the Himalayas

Abstract

Climate warming poses considerable challenges for alpine plant species, especially for competitively inferior ones with resource-conservative adaptations to cold climates. The Himalayas are warming at rates considerably faster than the global average, so it is particularly important to assess how and through which mechanisms alpine plant species are affected there. We employed a demographic approach in a climate change experiment, where vegetation turfs were transplanted reciprocally between the central parts of the study species' (Viola biflora L. var. rockiana) range and the warmer range margin, with a temperature difference of ca. 1°C. In addition, turfs were also transplanted outside the range to warmer habitats, simulating two different scenarios of climate warming, +1 and +4°C. Transplanting to warmer sites negatively impacted population growth rates (λ), survival and clonality, but did not affect growth and fecundity, while the productivity of the plant community increased. The reciprocal transplants to the colder habitat showed the opposite effects, for both V. biflora and the plant community, indicating plastic responses of the study species, driven by changes in plant-plant competition. However, the leaf traits underlying the modeled population growth rates were origin-site specific and not affected by the climate-change treatments over the study period, suggesting local adaptation of growth form to competition in the warmer range margin, and to climate adversity in the colder range center. The transplants outside the present species' range showed consistently stronger reductions in population growth rate and survival, with mortality of 90-100% in the +4°C treatment. This illustrates that climatic changes beyond species' present climatic ranges pose a serious risk for range contraction and extinction for Himalayan alpine species in the near future. As V. biflora seems mostly limited by competition under warming, its persistence in a future climate may become increasingly dependent on keeping competitive effects from the surrounding community low, for instance by management interventions like grazing and mowing.

Keywords: Viola biflora var. rockiana; alpine; altitudinal gradient; climate change; leaf traits; population growth rate; reciprocal transplant experiment; vital rate.

FIGURE 1

Geographic location and experimental setup for the transplant experiment. Arrows indicate direction of transplantation; for each of the four sites altitude and mean annual temperature are indicated.

FIGURE 2

Population growth rates (λ) for each transition (i.e., annual transitions: 2012–2013, 2013–2014, and 2014–2015) in controls at the site of origin and transplants at the target sites (A–D) and contributions to differences in population growth rates between transplants and the respective controls at the site of origin (E–H). Treatment colors in panels (A–D) match the colors in Figure 1. Error bars in panels (A–D) show ±1 standard deviation of λ from the bootstrapped datasets (n = 2200). Significant differences between λ in controls and transplants indicated by asterisks: ^∗∗∗p < 0.001, ^∗∗p < 0.01, ^∗p < 0.05, °p < 0.1.

FIGURE 3

Differences in community height (A–D) and cover (E–H) between transplants at the target sites and controls at the site of origin. Error bars indicate 95% confidence intervals. Significant differences between community height/cover in controls and transplants indicated by asterisks: ^∗∗∗p < 0.001, ^∗∗p < 0.01, ^∗p < 0.05, °p < 0.1. Treatments are indicated by symbols: open symbols and dashed lines for transplants, filled symbols and solid lines for controls at the site of origin. The positions of the different time series are slightly shifted along the x-axis to facilitate readability.

FIGURE 4

Leaf traits (A–C: Number of leaves, Leaf stalk length and Leaf size) in transplants (dashed and dotted lines) and controls (solid lines) from high alpine (blue, filled symbols) and alpine origin (orange, open symbols) over the study period. Error bars indicate 95% confidence intervals. The positions of the different time series are slightly shifted along the x-axis to facilitate readability.