We present methods to evaluate how predation risk can alter the chemical quality of herbivore prey by inducing dietary changes to meet demands of heightened stress, and how the decomposition of carcasses from these stressed herbivores slows subsequent plant litter decomposition by soil microbes.
The quantity and quality of detritus entering the soil determines the rate of decomposition by microbial communities as well as recycle rates of nitrogen (N) and carbon (C) sequestration1,2. Plant litter comprises the majority of detritus3, and so it is assumed that decomposition is only marginally influenced by biomass inputs from animals such as herbivores and carnivores4,5. However, carnivores may influence microbial decomposition of plant litter via a chain of interactions in which predation risk alters the physiology of their herbivore prey that in turn alters soil microbial functioning when the herbivore carcasses are decomposed6. A physiological stress response by herbivores to the risk of predation can change the C:N elemental composition of herbivore biomass7,8,9 because stress from predation risk increases herbivore basal energy demands that in nutrient-limited systems forces herbivores to shift their consumption from N-rich resources to support growth and reproduction to C-rich carbohydrate resources to support heightened metabolism6. Herbivores have limited ability to store excess nutrients, so stressed herbivores excrete N as they increase carbohydrate-C consumption7. Ultimately, prey stressed by predation risk increase their body C:N ratio7,10, making them poorer quality resources for the soil microbial pool likely due to lower availability of labile N for microbial enzyme production6. Thus, decomposition of carcasses of stressed herbivores has a priming effect on the functioning of microbial communities that decreases subsequent ability to of microbes to decompose plant litter6,10,11.
We present the methodology to evaluate linkages between predation risk and litter decomposition by soil microbes. We describe how to: induce stress in herbivores from predation risk; measure those stress responses, and measure the consequences on microbial decomposition. We use insights from a model grassland ecosystem comprising the hunting spider predator (Pisuarina mira), a dominant grasshopper herbivore (Melanoplus femurrubrum),and a variety of grass and forb plants9.
1. Rearing Grasshoppers Under Stress and Stress Free Conditions
2. Validating Grasshopper Stress State
3. Validating Shift in Body Elemental Stoichiometry
4. Microbial Decomposition
An example plot of grasshopper standard metabolic rates in stress and stress free conditions are presented in Figure 2. Due to body mass differences among individual grasshoppers, and the fact that metabolic rate varies with body mass, plots should present metabolic rates in relation to grasshopper body mass. Parallel trends for the different treatments indicate that metabolic rate rises as a constant multiple of standard metabolic rate (i.e. there is no body mass x metabolic rate interaction) for all stressed individuals.
Grasshopper body C and N elemental contents in risk and risk free conditions are presented in Table 1. It is noteworthy that there is a very small (4%) difference in body C:N ratios between treatments. Nevertheless, these small differences can translate into large differences in grass litter decomposition by the soil microbial pool (Figure 3).
Adding grass litter to PVC collars previously amended with stressed or stress-free grasshoppers leads to different degrees of litter decomposition, as reflected in the curves describing cumulate CO2 release from the soil due to microbial respiration (Figure 3). Experiments should be monitored until cumulate curves begin to saturate.
Stress | Stress Free | |
Carbon (%) | 48.44±0.32 | 44.73±0.46 |
Nitrogen (%) | 12.11±0.08 | 11.62±0.12 |
Carbon: Nitrogen | 4.00±0.03 | 3.85±0.04 |
Table 1. Comparison of the chemical content of grasshopper herbivore carcasses from conditions in which they faced predation risk (stress) and in which predation risk was absent (stress free). Values are mean ± 1 standard error.
Figure 1. Illustration of the design of the field mesocosms used in the experiment and overall scheme of the experimental evaluation of risk effects on litter decomposition.
Figure 2. A plot of herbivore standard metabolic rate in relation to herbivore body mass. The data are divided into two classes according to experimental treatment: grasshoppers from mesocosms containing predators (predation) to induce stress, and mesocosms without predators (control) and hence no induced stress. Data are from D. Halwena and O.J. Schmitz 2010, unpublished.
Figure 3. Curves describing cumulative CO2 release by the microbial pool while decomposing experimental grass litter inputs in PVC collars. Plotted values are mean ± 1 standard error. The graph demonstrates that soils primed with stressed grasshopper carcasses (predator) result in 19% lower (ANOVA F1,6 = 9.06, P < 0.05) plant litter decomposition rates than soils primed with stress free grasshopper carcasses (control). The inset shows the PVC collar apparatus in the field. Figure reproduced from Hawlena et al.6 Cick here to view larger figure.
The sequence of methods presented here should allow systematic measurement of the way stress in species comprising above-ground food webs can prime soil microbial communities in ways that lead to alteration of subsequent decomposition of plant litter. The methods are ideal for studying ecosystems comprised of arthropod consumers and herbaceous plants because intact food webs can be spatially circumscribed and contained within mesocosms.
Spatial variability may exist due to gradients in background soil moisture, soil temperature, plant nutrient content, etc. The study design allows one to array mescosms and PVC collars to block along spatial environmental gradients and thereby account for such environmental variation when analyzing for effects.
Although intended for field use, the cavity ring-down spectroscopy instrument (Picarro Inc., Santa Clara, CA, USA; Model: G1101-i) readings are sensitive to movement. Therefore, one should erect a base measurement station central to all of the plots containing PVC collars, and connect the instrument to the collars with lengths of PVC tubing.
Soil litter decomposition has traditionally been measured by enclosing known quantities of litter into fiberglass mesh bags, depositing the bags onto the soil surface in the field and periodically re-measuring the bags to quantify litter disappearance rate (decomposition). The limitation of this method is that one is unable to trace the fate of the decomposed matter or determine the contribution to CO2 mineralization of the soil amendment (added litter) from background soil CO2 mineralization. The tracer method using labeled CO2 presented here helps alleviate this logistical constraint.
Ecosystem ecology and biogeochemistry have operated under the working paradigm that because uneaten plant-litter comprises the majority of detritus, belowground ecosystem processes are only marginally influenced by biomass inputs from higher trophic levels in aboveground food webs, such as herbivores themselves6. However, there is growing evidence that species in higher trophic levels of ecosystems can have a profound influence on belowground processes1,4,5. The method presented here stands to enhance quantification of the contribution of higher trophic levels, either directly through biomass from carcass deposition (e.g. 12, 13) or excretion and egestion (e.g. 14, 15) or indirectly through alteration of plant community composition (e.g. 9) on ecosystem nutrient cycling. Such quantification can help reveal the mechanisms by which animals control ecosystem dynamics as part of a concerted effort to enhance and revise the current working paradigm of biotic control over ecosystem functioning.
The authors have nothing to disclose.
This research was supported by funds from the Yale Climate and Energy Institute and the US National Science Foundation.
Name of the reagent or equipment | Company | Catalogue number | Comments (optional) |
Cavity ring down spectroscope | Picarro Inc., Santa Clara, CA, USA | Model # G1101-i | |
CO2 respirometer | Qubit Systems, Kingston, ON, Canada | Model # S151 | |
13C | Sigma-Aldrich | 372382 | |
Spectrophotometer | Thermo, San Jose CA, USA | Model: Delta V Plus Isotope Ratio Mass Spectrophotometer |