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Drought and small-bodied herbivores modify nutrient cycling in the semi-arid shortgrass steppe

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Abstract

Climate change will increase the frequency of droughts over the next century, with severe consequences for ecosystem function in semi-arid grasslands. The shortgrass steppe (SGS) experiences some of the largest interannual variation in precipitation among terrestrial biomes and exhibits extremely high sensitivity to drought. Yet despite decades of research describing the consequences of drought for ecosystem function in the SGS, we currently have little information regarding the impact of drought on bioavailability of important nutrients other than nitrogen, the contribution of herbivores to bioavailable concentrations of these nutrients, and whether drought alters herbivore-derived nutrient cycling. To quantify the impacts of long-term drought and small-bodied herbivores on nutrient cycling and aboveground net primary production (ANPP), we factorially manipulated rainfall and herbivore presence in the SGS of northern Colorado. Specifically, we measured the impacts of drought and herbivores on bioavailability of ten important nutrients: aluminum, calcium, iron, potassium, magnesium, manganese, nitrate, phosphorus, sulfur, and zinc. We then correlated these nutrients with grass production to determine whether reduced plant growth under drought conditions causes a belowground buildup of nutrients. Drought reduced ANPP as expected, and also altered concentrations of many nutrients apart from N, which clustered in their drought response. In contrast, small-bodied herbivores did not affect ANPP or soil N. However, they did contribute to the bioavailable soil concentrations of two important nutrients: PO4-P and S. Importantly, drought generally did not modify the contribution of herbivores to nutrient cycling, suggesting that herbivores might be a critical component of biogeochemical cycling regardless of precipitation in semi-arid grasslands.

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Acknowledgements

We are very grateful for the dedicated and hardworking undergraduates of Colorado State: Abigail Lock, Madison Rode, Holly Perretta, Megan Coyle, Abby Lathrop-Melting, and Sam Rollman, who helped construct cages in a subfreezing April snowstorm, harvest biomass around cacti, and sort dried plant material in the lab. We also thank the EDGE crew: John Dietrich, Maddie Shields, Lauren Bauer, Ava Hoffman, Mao Wei, Tyler Roberts, Gene Halsey, Elsie Denton, and Melissa Johnson, who were responsible for maintaining the drought shelters each year and who helped us deploy insect cages. This work was supported by a United States Department of Agriculture—National Institute of Food and Agriculture—Agriculture and Food Research Initiative postdoctoral fellowship (Grant No. 2016-67012-25169) and an NSF DEB award (1754124) to NPL, as well as an NSF DEB Macrosystems grant to MDS.

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  1. Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, USA

    Nathan P. Lemoine & Melinda D. Smith

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  1. Nathan P. Lemoine
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Appendix 1: Comparison of priors for Bayesian models

Appendix 1: Comparison of priors for Bayesian models

Weakly informative priors constrain large effect sizes in the presence of lower statistical power (i.e., small sample sizes, noisy data). These priors are therefore more conservative than noninformative priors, which are analogous to conducting frequentist statistics (the p-values and confidence intervals are identical between noninformative priors and frequentist methods). To assess the impact of prior choice on model output, we conducted all analyses with both weakly informative [N(0,1)] and noninformative [N(0,10000)] on regression coefficients.

MANOVA of nutrient availability

See Tables 3 and 4.

Table 3 Pr(effect) values from the split-plot MANOVA for all nutrients using weakly informative priors (this is identical to Table 1 of the main text)
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Table 4 Pr(Effect) values from the split-plot MANOVA for all nutrients using noninformative priors
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Results from weakly informative priors were qualitatively similar to, but slightly weaker than, noninformative priors. This is to be expected, due to the ability of N(0,1) priors to constrain effect sizes. The biggest difference occurred for Fe, where weakly informative priors negated marginally significant main effects of herbivory and drought and reduced the significant interaction to marginal significance. Thus, the weakly informative priors were more conservative then traditional statistics.

ANOVA of ANPP

See Tables 5, 6.

Table 5 Pr(Effect) values from the split-plot ANOVAs for forb and grass ANPP using weakly informative priors
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Table 6 Pr(Effect) values from the split-plot ANOVAs for forb and grass ANPP using noninformative priors
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Lemoine, N.P., Smith, M.D. Drought and small-bodied herbivores modify nutrient cycling in the semi-arid shortgrass steppe. Plant Ecol 220, 227–239 (2019). https://doi.org/10.1007/s11258-019-00908-1

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