Homeostasis of element composition is one of the central concepts of ecological stoichiometry. In this context, homeostasis is the resistance to change of consumer body composition in response to the chemical composition of consumer's food. To simplify theoretical analysis, it has generally been assumed that autotrophs exhibit flexibility in their composition, while heterotrophs are confined to a constant (strictly homeostatic) body composition. Yet, recent studies suggest that heterotrophs are not universally strictly homeostatic. We examined the degree to which autotrophs and heterotrophs regulate stoichiometric homeostasis (P:C, N:C, N:P, or %P and %N). We conducted a quantitative review and meta‐analysis using 132 datasets extracted from 57 literature sources which examined the dependence of organismal stoichiometry on resource stoichiometry. Among individual datasets, there was a wide range of responses from strictly homeostatic to non‐homeostatic. Even within heterotrophic organisms, varying levels of homeostasis were observed. Comparing the degree of homeostasis between organisms based on large‐scale habitat types using meta‐analysis indicated some significant differences between groups. For example, aquatic macroinvertebrates were significantly more homeostatic in terms of P:C than terrestrial invertebrates. Our meta‐analysis also confirmed that, with regard to N:P, heterotrophs are significantly more homeostatic than autotrophs. Furthermore, our analysis indicated that the homeostasis parameter 1/H, despite being a potentially useful predictive metric, has to be utilized with caution since it oversimplifies some important aspects of the responses of organisms to elemental imbalances. This critical evaluation of stoichiometric homeostasis contributes to a better understanding of many food‐web interactions, which are commonly driven by elemental imbalances between consumers and their resources.

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Because both intrinsic and extrinsic factors influence insect population dynamics, operating at a range of temporal and spatial scales, it is difficult to assess their contributions. Long-term studies are ideal for assessing the relative contributions of multiple factors to abundance and community dynamics. Using data spanning 25 years, we investigate the contributions of weather at annual and decadal scales, fire return interval, and grazing by bison to understand the dynamics of abundance and community composition in grasshopper assemblages from North American continental grassland. Each of these three primary drivers of grassland ecosystem dynamics affects grasshopper population and community dynamics. Negative feedbacks in abundances, as expected for regulated populations, were observed for all feeding guilds of grasshoppers. Abundance of grasshoppers did not vary in response to frequency of prescribed burns at the site. Among watersheds that varied with respect to controlled spring burns and grazing by bison, species composition of grasshopper assemblages responded significantly to both after 25 years. However, after more than 20 years of fire and grazing treatments, the number of years since the last fire was more important than the managed long-term fire frequency per se. Yearly shifts in species composition (1983-2005), examined using non-metric multidimensional scaling and fourth-corner analysis, were best explained by local weather events occurring early in grasshopper life cycles. Large-scale patterns were represented by the Palmer Drought Severity Index and the North Atlantic Oscillation (NAO). The NAO was significantly correlated with annual mean frequencies of grasshoppers, especially for forb- and mixed-feeding species. Primary grassland drivers-fire, grazing and weather-contributing both intrinsic and extrinsic influences modulate long-term fluctuations in grasshopper abundances and community taxonomic composition.

Revegetation by seeding is an important tool in restoration. Seeding practices for restoration often rely on standard prescriptions for seed mix diversity and seeding rates. Seed mix diversity and rates are generally low within restoration projects and these practices are typically not informed by research. The objective of this study was to explore a new method for determining an optimal seed mix diversity and seeding rate for restoration of a semiarid grassland. We examined restoration success associated with differing seed mix diversity levels (5-50 species) and seeding rates (400-1,600 pure live seeds [PLS]/m 2 ) using a response surface regression (RSR) experimental design at 12 disturbed sites in northeastern Colorado. Overall restoration success was evaluated based on optimizing desirability across nine individual responses: biomass and diversity of seeded, volunteer native, noxious, non-native species, and the density of seeded species. Greatest restoration success after four growing seasons occurred at a seed mix diversity of 35 species and a seeding rate of 1,366 PLS/m 2 . RSR experimental design and analysis has seldom been used to answer ecological questions. This novel approach to address a pressing restoration challenge provided unique insight into how seed mix diversity and seeding rate, singly or in combination, influence the first 4 years of plant community development and overall restoration success. These results suggest that including more native species and seeding at higher rates than current practice could lead to greater restoration success in grasslands.

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