Differences in adult survival drive divergent demographic responses to warming on the Tibetan Plateau
Data files
Nov 25, 2024 version files 10.63 KB
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PARAMETERS_FOR_VITAL_RATES.rar
810 B
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RCODE.rar
6.42 KB
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README.md
3.40 KB
Abstract
A central question in biodiversity conservation is whether species will maintain viable populations under climate warming. Assessing species viability under climate warming requires demographic studies integrating vital rate responses to long-term warming throughout species’ life cycle. However, studies of this nature are rare. Our Integral Projection Models (IPMs) parameterised with demographic data show differing responses of two functionally similar co-occurring species, Elymus nutans Griseb. and Helictotrichon tibeticum (Roshev.) Holub, to 10 years of in situ active warming by 2℃. Our IPMs estimated that the life expectancy is higher in H. tibeticum (6.7 years) than that in E. nutans (4.5 years) under ambient conditions, and the difference is larger under warmed conditions. We found that while warming decreased individual-level growth in both species, H. tibeticum, which has a longer life expectancy, compensated with increased survival, and thereby increased projected population-level growth under warming. Contrastingly, E. nutans, which has a shorter life expectancy, is projected to have decreased population-level performance. Furthermore, our elasticity analyses show that survival is the most important vital rate for population viability in both species under both ambient and warmed conditions. Moreover, our retrospective Life Table Response Experiment (LTRE) analysis reveals that the contrasting fates of the two species under warming mainly arise from the different responses of adult survival, which is significantly promoted in H. tibeticum but slightly reduced in E. nutans. Individual shrinkage occurred 1.6-fold more frequently under warming than ambient conditions for both species, and made considerable negative contributions to their population growth rates in warmed plots. However, such negative effects are offset in H. tibeticum (but not E. nutans) by the positive contribution to population growth rate of the associated increased survival. Our results illustrate that the responses to climate warming may vary considerably between similar co-occurring species, and species with a demographically compensatory strategy may avoid population collapse. Furthermore, our study demonstrates the potential of using life-history traits to predict species’ viability facing warming, so as to inform biodiversity conservation under climate change.
https://doi.org/10.5061/dryad.612jm64b8
These file provide the demographic parameters for vital rates (params.Rdata and domains.Rdata) and R script (Population dynamics under warming_script.R and Kernel.R) to run the analyses in the manuscript “Differences in adult survival drive divergent demographic responses to warming on the Tibetan Plateau”.
Description of the data and file structure
Demographic parameters are contained in the PARAMETERS FOR VITAL RATES/
directory.
This dataset includes the estimated parameters for each vital rate and domains of plant heights for Elymus nutans and Helictotrichon tibeticum under ambient and warming treatments: (i) The estimated parameters consist of the intercept and slope of the linear regression for each vital rate, such as survival, growth, probability of reproduction, number of seeds/spikes per reproductive individual, probability of seedling recruitment, and recruit size [cm]; (ii) The domain of plant heights [cm] includes the minimum and maximum of plant heights for each species under each treatment.
params.Rdata
- params_elym.ambi.vec: Demographic parameters for Elymus nutans under ambient treatment.
- params_elym.warm.vec: Demographic parameters for Elymus nutans under warming treatment.
- params_heli.ambi.vec: Demographic parameters for Helictotrichon tibeticum under ambient treatment.
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params_heli.warm.vec: Demographic parameters for Helictotrichon tibeticum under warming treatment.
- s_int: Intercept of survival
- s_slope: Slope of survival
- g_int: Intercept of growth
- g_slope: Slope of growth
- g_sd: Standard deviation of growth
- pr_int: Intercept of probability of reproduction
- pr_slope: Slope of probability of reproduction
- f_int: Intercept of number of seeds/spikes per reproductive individual
- f_slope: Slope of number of seeds/spikes per reproductive individual
- p.r: Probability of seedling recruitment
- r_mu: Mean height of new recruits [cm]
- r_sd: Standard deviation of height for new recruits
domains.Rdata
- domain_elym.ambi: The minimum and maximum of plant heights [cm] for Elymus nutans under ambient treatment
- domain_elym.warm: The minimum and maximum of plant heights [cm] for Elymus nutans under warming treatment
- domain_heli.ambi: The minimum and maximum of plant heights [cm)] for Helictotrichon tibeticum under ambient treatment
- domain_heli.warm: The minimum and maximum of plant heights [cm] for Helictotrichon tibeticum under warming treatment
The script is contained in the RCODE/
directory.
This script includes computational processes for modeling population dynamics of Elymus nutans and Helictotrichon tibeticum under ambient and warming treatments: (i) Population growth rates; (ii) stable size distributions; (iii) Life-history traits (i.e., generation time [years] and life expectancy [years]); (iv) Elasticity of vital rates; (v) Life table response experiment analysis.
R is required to run the script “Population dynamics under warming_script.R” and source “Kernel.R”; the script was created using version 4.0.5
Annotations are provided throughout the script through 1) library loading, 2) dataset loading, 3) analyses, and 4) figure creation.
We examine how climate warming affects the population dynamics of two dominant plant species, Elymus nutans Griseb. and Helictotrichon tibeticum (Roshev.) Holub, on the alpine grassland of the Tibetan Plateau. Our study sites have received a 2℃ active warming starting in 2011. To quantify the responses of both species to warming, we parameterised Integral Projection Models with demographic data collected in 2019 and 2020.