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Description
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Abstract
Climate change may soon threaten much of global biodiversity, especially if species cannot adapt to changing climatic conditions quickly enough. A critical question is how quickly climatic niches change, and if this speed is sufficient to prevent extinction as climates warm. Here, we address this question in the grass family (Poaceae). Grasses are fundamental to one of Earth's most widespread biomes (grasslands), and provide roughly half of all calories consumed by humans (including wheat, rice, corn and sorghum). We estimate rates of climatic niche change in 236 species and compare these with rates of projected climate change by 2070. Our results show that projected climate change is consistently faster than rates of niche change in grasses, typically by more than 5000-fold for temperature-related variables. Although these results do not show directly what will happen under global warming, they have troubling implications for a major biome and for human food resources. (2020-06-24)
Usage notes
ESM_guideSupplementary Figure S1Visual summary and flowchart of the methods used in this study.Appendix_S1Supplementary MethodsAppendix_S2Summary of climatic data for 170 species from Edwards & Smith [13] for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12). Climatic data for each species for each climatic variable are summarized by the minimum, median and maximum values among localities within its distribution, as well as the mean value across all localities that was used to calculate rates. Temperature values are in degrees Celsius*10 and precipitation values are in mm/year.Appendix_S3Summary of climatic data for 62 species from Tree 1 of Spriggs et al. [2] for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12). Climatic data for each species for each climatic variable are summarized by the minimum, median and maximum values identified within its distribution, as well as the mean value across all localities that was used to calculate rates. Temperature values are in degrees Celsius*10 and precipitation values are in mm/year.Appendix_S4Summary of climatic data for 60 species from Tree 2 of Spriggs et al. [2] for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12). Climatic data for each species for each climatic variable are summarized by the minimum, median and maximum values identified within its distribution, as well as the mean value across all localities that was used to calculate rates. Temperature values are in degrees Celsius*10 and precipitation values are in mm/year.Appendix_S5Climatic data for all localities (including latitude and longitude) extracted from WorldClim database at 30 second resolution for 170 species from the tree of Edwards & Smith [13] for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12). Note that temperature values are in degrees Celsius*10 and precipitation values are in mm/year.Appendix_S6Climatic data for all localities (including latitude and longitude) extracted from WorldClim database at 30 second resolution for 62 species from Tree 1 in Spriggs et al. [2] for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12). Note that temperature values are in degrees Celsius*10 and precipitation values are in mm/year.Appendix_S7Climatic data for all localities (including latitude and longitude) extracted from WorldClim database at 30 second resolution for 60 species from Tree 2 in Spriggs et al. [2] for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12). Note that temperature values are in degrees Celsius*10 and precipitation values are in mm/year.Appendix_S8Estimated node ages (in millions of years) and rates of climatic niche change for three trees under three different models of evolution (BM = Brownian Motion; OU = Ornstein-Uhlenbeck; Lambda = estimated lambda) for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12), along with estimated rates of future climate change under three scenarios (minimum [min], median [med], maximum [max]), and differences between rates of niche change and future climate change.Appendix_S9Summary of climatic data for the 102 focal species with one or more non-native localities. Only the focal species (those for which rates are estimated) were screened for non-native localities. The number of unique native localities (after removing non-native localities) is shown, along with raw means for climatic variables (including all localities), recalculated means (after excluding non-native localities), and the difference between the raw and recalculated means. Boldfaced species are those in which the raw and recalculated means differ by >1°C for one or more temperature variables. Species with no data for recalculated means are those for which there were no native localities in the dataset of Edwards & Smith [13].Appendix_S10Climatic data for all localities from the native range (x = longitude, y = latitude) for 102 species that included one or more non-native localities in the dataset of Edwards & Smith [13] (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12). The general continental region where each locality is located is also given.Table_S1Summary of past rates, projected rates of climate change and relative differences between past and projected rates for the tree from Edwards & Smith [13], Tree 1 and 2 from Spriggs et al. [2] for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12). For each tree and for each variable, we report the maximum, median and minimum values of niche rates among species, rates of projected future climate change, and the difference between niche rates and rates of future climate change.Table_S2Likelihood and AIC scores for each model for each subfamily for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12), using the tree of Edwards & Smith [13]. Boldface indicates the best fitting model (based on the lowest AIC).Table_S3Likelihood and AIC scores for each model for each subfamily for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12), using Tree 1 (younger ages) from Spriggs et al. [2]. Boldface indicates the best fitting model (based on the lowest AIC)Table_S4Likelihood and AIC scores for each model for each subfamily for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12), using Tree 2 (older ages) from Spriggs et al. [2]. Boldface indicates the best fitting model (based on the lowest AIC)Table_S5Results for 170 species based on the tree of Smith & Edwards [13] for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12), including estimated node ages (in million years), future rates of climate change projected for the year 2070 within their geographic range (for the maximum, median, and minimum estimated rate among projections: max, med, min), past rates of climatic niche change based on the best-fitting model of trait evolution, absolute differences in mean values (among localities) for the climatic variables for each species pair, and differences between projected rates of climate change and the past rates of niche change.Table_S6Results for 62 species from Tree 1 of Spriggs et al. [2] for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12), including estimated node ages, future rates of climate change projected for the year 2070 within their geographic range (for the maximum, median, and minimum estimated rate among projections: max med, min), past rates of climatic niche change based on the best-fitting model of trait evolution, absolute differences in mean values (among localities) for the climatic variables for each species pair, and differences between projected rates of climate change and the past rates of niche change.Table_S7Results for 60 species based on Tree 2 of Spriggs et al. [2] for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12), including estimated node ages, future rates of climate change projected for the year 2070 within their geographic range (for the maximum, median, and minimum estimated rate among projections: max med, min), past rates of climatic niche change based on the best-fitting model of trait evolution, absolute differences in mean values (among localities) for the climatic variables for each species pair, and differences between projected rates of climate change and the past rates of niche change.Table_S8Results of tests of the relationship between species age and rates of niche change for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12). Species ages and niche rates for all climatic variables initially failed the Shapiro-Wilk test for normality. Therefore results presented here are either ordinary-least squares (OLS) regressions after ln-transforming ages and nich rates, or (when one or both variables were still non-normal after ln-transformation), from a non-parametric test (Spearman’s rank correlation; SR). All OLS relationships are negative. Shapiro-Wilk test results are for the ln-transformed variables.Table_S9Summary of the number of species in which niche divergence between sister species differs by less than the magnitude of expected change under different climate scenarios representing the minimum, median, and maximum levels of change for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12). Species number indicates the total number of species in our analysis from each tree.Table_S10Summary of the impact of excluding species with one or more non-native localities on the difference in rates between past niche change among species and future climate change. Results shown are mean differences in rates among species for the intermediate model of future climate change, n is the number of species included in the comparison. “All species” are the original analyses, including species with some non-native localities. “Native only” indicates results after removing all species with any non-native localities. In the “Mostly native” comparisons, species with non-native localities were retained if they had similar mean values for climatic variables after the non-native localities were removed (i.e. all temperature variables differed by no more than 1°C when non-natives were removed).Table_S11Same as Table S5 (Tree 2010), but excluding species with any non-native localities.Table_S12Same as Table S5 (Tree 2010), but excluding only species with substantial differences in mean values for one or more temperature variables after removing non-native localities (difference >1°C). Species with one or more non-native localities are highlighed in yellow.Table_S13Same as Table S6 (Tree 2014-1), but excluding species with any non-native localities.Table_S14Same as Table S6 (Tree 2014-1), but excluding only species with substantial differences in mean values for one or more temperature variables after removing non-native localities (difference >1°C). Species with one or more non-native localities are highlighed in yellow.Table_S15Same as Table S7 (Tree 2014-2), but excluding species with any non-native localities.Table_S16Same as Table S7 (Tree 2014-2), but excluding only species with substantial differences in mean values for one or more temperature variables after removing non-native localities (difference >1°C). Species with one or more non-native localities are highlighed in yellow.Table_S17Relationship between the median and mean across all localities for each species for each climatic variable (MAT = mean annual temperature, Bio1; TMAX = maximum temperature of the warmest month, Bio5; TMIN = minimum temperature of the coldest month, Bio6; MAP = mean annual precipitation, Bio12). SR = Spearman rank corelation; OLS = ordinary least-squares regression. Shapiro-Wilk test results are for ln-transformed variables, except for the medians and means of MAT, TMAX and TMIN for the two 2014 trees. (2020-06-24)
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