Soil carbon stocks in temperate grasslands differ strongly across sites but are insensitive to decade-long fertilization.

Enhancing soil carbon (C) storage has the potential to offset human-caused increases in atmospheric CO2 . Rising CO2 has occurred concurrently with increasing supply rates of biologically limiting nutrients such as nitrogen (N) and phosphorus (P). However, it is unclear how increased supplies of N and P will alter soil C sequestration, particularly in grasslands, which make up nearly a third of non-agricultural land worldwide. Here, we leverage a globally distributed nutrient addition experiment (the Nutrient Network) to examine how a decade of N and P fertilization (alone and in combination) influenced soil C and N stocks at nine grassland sites spanning the continental United States. We measured changes in bulk soil C and N stocks and in three soil C fractions (light and heavy particulate organic matter, and mineral-associated organic matter fractions). Nutrient amendment had variable effects on soil C and N pools that ranged from strongly positive to strongly negative, while soil C and N pool sizes varied by more than an order of magnitude across sites. Piecewise SEM clarified that small increases in plant C inputs with fertilization did not translate to greater soil C storage. Nevertheless, peak season aboveground plant biomass (but not root biomass or production) was strongly positively related to soil C storage at seven of the nine sites, and across all nine sites, soil C covaried with moisture index and soil mineralogy, regardless of fertilization. Overall, we show that site factors such as moisture index, plant productivity, soil texture, and mineralogy were key predictors of cross-site soil C, while nutrient amendment had weaker and site-specific effects on C sequestration. This suggests that prioritizing the protection of highly productive temperate grasslands is critical for reducing future greenhouse gas losses arising from land use change.

Direct and indirect effects of the El Niño Southern Oscillation on development and survival of young of a tropical passerine.

The El Niño Southern Oscillation (ENSO) is a global phenomenon that influences climate variation and, in turn, the ecological processes affecting the abundance and distribution of populations across taxa. For example, the ENSO can profoundly influence the development and survival of pelagic species, but the extent to which the ENSO affects offspring of terrestrial species is less well known. We used piecewise structural equation modeling to investigate the direct and indirect relationship between the ENSO and offspring development and survival in a terrestrial tropical passerine, the lance-tailed manakin (Chiroxiphia lanceolata). The Oceanic Niño Index (ONI), a measure of the ENSO, was negatively related to individual growth rate, maximum number of lesion developed by nestlings, and hatching day-of-year; which in turn mediated indirect effects on fledging success and recruitment. Further the ONI was a better predictor of nestling development compared to local temperature and rainfall. Our study establishes a link between the ENSO and the development and survival of young of a terrestrial species and underscores the need to better understand how offspring cope with global climate variation.

A cross-scale trophic cascade from large predatory fish to algae in coastal ecosystems.

Trophic cascades occur in many ecosystems, but the factors regulating them are still elusive. We suggest that an overlooked factor is that trophic interactions (TIs) are often scale-dependent and possibly interact across spatial scales. To explore the role of spatial scale for trophic cascades, and particularly the occurrence of cross-scale interactions (CSIs), we collected and analysed food-web data from 139 stations across 32 bays in the Baltic Sea. We found evidence of a four-level trophic cascade linking TIs across two spatial scales: at bay scale, piscivores (perch and pike) controlled mesopredators (three-spined stickleback), which in turn negatively affected epifaunal grazers. At station scale (within bays), grazers on average suppressed epiphytic algae, and indirectly benefitted habitat-forming vegetation. Moreover, the direction and strength of the grazer-algae relationship at station scale depended on the piscivore biomass at bay scale, indicating a cross-scale interaction effect, potentially caused by a shift in grazer assemblage composition. In summary, the trophic cascade from piscivores to algae appears to involve TIs that occur at, but also interact across, different spatial scales. Considering scale-dependence in general, and CSIs in particular, could therefore enhance our understanding of trophic cascades.

Piecewise Structural Equation Modeling of the Quantity Implicature in Child Language.

We review an array of experimental methodological factors that either contribute to or detract from the measurement of pragmatic implicatures in child language. We carry out a truth value judgment task to measure children's interpretations of the Spanish existential quantifier algunos in implicature-consistent and implicature-inconsistent contexts. Independently, we take measures of children's inhibition, working memory, attention, approximate number ability, phrasal syntax, and lexicon. We model the interplay of these variables using a piecewise structural equation model (SEM), common in the life sciences, but not in the social and behavioral sciences. By 6 years of age, the children in our sample were not statistically different from adults in their interpretations. Syntax, lexicon, and inhibition significantly predict implicature generation, each accounting for unique variance. The approximate number system and inhibition significantly predict lexical development. The statistical power of the piecewise SEM components, with a sample of 64 children, is high, in comparison to a traditional, globally estimated SEM of the same data.

Species asynchrony stabilizes productivity over 20 years in Northeast China.

The stability of forest productivity can reflect the functioning of forest ecosystems. It is a crucial topic to understand the relationship between biodiversity and ecosystem functions in ecology. Although previous studies have made great progress in understanding the effects of diversity, species asynchrony, and other factors on community biomass and productivity, few studies have explored how these factors affect the temporal stability of productivity. In this study, we hypothesized that diversity, species asynchrony, and topography would directly or indirectly impact the temporal stability of productivity. To test this hypothesis, we used a multiple regression model and a piecewise structural equation model based on the inventory data over 20 years (5-year intervals) from 1992 to 2012 at Jingouling Forest Farm in Northeast China. Our results showed that species asynchrony was the main driving factor affecting the temporal stability of productivity. Structural diversity significantly decreased community stability, while species diversity had a nonsignificant effect on it. We found the combination of a multiple regression model and a piecewise structural equation model is an effective method for evaluating the factors that influence community stability. The effect of species asynchrony is crucial for understanding the ecological mechanisms underlying the diversity-stability relationship in mixed forests.

Metabolic rate allometry in intertidal mussels across environmental gradients: The role of coastal carbonate system parameters in mediating the effects of latitude and temperature.

We assess the role of direct and indirect effects of coastal environmental drivers (including the parameters of the carbonate system) on energy expenditure (MR) and body mass (M) of the intertidal mussel, Perumytilus purpuratus, across 10 populations distributed over 2800 km along the Southern Eastern Pacific (SEP) coast. We find biogeographic and local variation in carbonate system variables mediates the effects of latitude and temperature on metabolic rate allometry along the SEP coast. Also, the fitted Piecewise Structural Equation models (PSEM) have greater predictive ability (conditional R2 = 0.95) relative to the allometric scaling model (R2 = 0.35). The largest standardized coefficients for MR and M were determined by the influence of temperature and latitude, followed by pCO2, pH, total alkalinity, and salinity. Thus, physiological diversity of P. purpuratus along the SEP coast emerges as the result of direct and indirect effects of biogeographic and local environmental variables.

Indirect effects of water availability in driving and predicting productivity in the Gobi desert.

Climate is the fundamental determinant of plant metabolism and net primary productivity (NPP). However, whether climate drives NPP directly or indirectly is not well understand. The Gobi desert across a precipitation gradient in the arid zone provides an ideal naturally-controlled platform for studying the precipitation-productivity relationships. We conducted 3-year experiments in four Gobi desert shrublands across an aridity gradient in Gansu Province of China to test the relationship between water availability and shrub productivity as well as the relative importance of the possible factors driving productivity (using piecewise structural equation modeling) and to explore the appropriate variables for predicting productivity (using three spatial models). The results showed that water availability indirectly affected the NPP via stand biomass, while stand biomass had a significant direct effect on NPP regardless of whether the leaf water content and stand height were considered. The model based on stand size (71.6%) and the model that contained both stand size and water availability (72.3%) explained more of the variation in the water-NPP relationships than the model based on water availability (37.3%). Our findings suggest that even in extremely water-limited areas, the effects of water availability on plant growth and the kinetics of plant metabolism could be indirect via plant size, demonstrating the importance of plant size as an indicator of shrub productivity. This study explains the mechanisms underlying the NPP driving pattern and proposes a practical NPP model for arid ecosystems.