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Abstract Understanding the correspondence between ambient temperature and insect development is necessary to forecast insect phenology under novel environments. In the face of climate change, both conservation and pest control efforts require accurate phenological predictions. Here, we compare a suite of degree‐day models to assess their ability to predict the phenology of a common, oligophagous butterfly, the silver‐spotted skipper,Epargyreus clarus(Cramer) (Lepidoptera: Hesperiidae). To estimate model parameters, we used development time of eggs and larvae reared in the laboratory at six constant temperatures ranging from 8 to 38 °C and on two host plants of contrasting quality (kudzu and wisteria). We employed three approaches to determine the base temperature to calculate degree days: linear regression, modified reduced major axis regression, and application of a generic base temperature value of 10 °C, which is commonly used in the absence of laboratory data. To calculate the number of degree days required to complete a developmental stage, we used data from caterpillars feeding on high‐ and low‐quality hosts, both in the field and in the laboratory. To test model accuracy, we predicted development time of seven generations of larvae reared in the field on the same host plants across 3 years (2014–2016). To compare performance among models, we regressed predicted vs. observed development time, and found that r²values were significantly larger when accounting for host plant quality. The accuracy of development time predictions varied across the season, with estimates of the first two generations being more accurate than estimates of the third generation, when ambient temperatures dropped outside the range in which development rate and temperature have a linear relationship. Overall, we show that accounting for variation in host plant quality when calculating development time in the field is more important than the choice of the base temperature for calculating degree days. 

Abstract AimClimate variability threatens to destabilize production in many ecosystems. Asynchronous species dynamics may buffer against such variability when a decrease in performance by some species is offset by an increase in performance of others. However, high climatic variability can eliminate species through stochastic extinctions or cause similar stress responses among species that reduce buffering. Local conditions, such as soil nutrients, can also alter production stability directly or by influencing asynchrony. We test these hypotheses using a globally distributed sampling experiment. LocationGrasslands in North America, Europe and Australia. Time periodAnnual surveys over 5 year intervals occurring between 2007 and 2014. Major taxa studiedHerbaceous plants. MethodsWe sampled annually the per species cover and aboveground community biomass [net primary productivity (NPP)], plus soil chemical properties, in 29 grasslands. We tested how soil conditions, combined with variability in precipitation and temperature, affect species richness, asynchrony and temporal stability of primary productivity. We used bivariate relationships and structural equation modelling to examine proximate and ultimate relationships. ResultsClimate variability strongly predicted asynchrony, whereas NPP stability was more related to soil conditions. Species richness was structured by both climate variability and soils and, in turn, increased asynchrony. Variability in temperature and precipitation caused a unimodal asynchrony response, with asynchrony being lowest at low and high climate variability. Climate impacted stability indirectly, through its effect on asynchrony, with stability increasing at higher asynchrony owing to lower inter‐annual variability in NPP. Soil conditions had no detectable effect on asynchrony but increased stability by increasing the mean NPP, especially when soil organic matter was high. Main conclusionsWe found globally consistent evidence that climate modulates species asynchrony but that the direct effect on stability is low relative to local soil conditions. Nonetheless, our observed unimodal responses to variability in temperature and precipitation suggest asynchrony thresholds, beyond which there are detectable destabilizing impacts of climate on primary productivity. 

Abstract Microbial processing of aggregate‐unprotected organic matter inputs is key for soil fertility, long‐term ecosystem carbon and nutrient sequestration and sustainable agriculture. We investigated the effects of adding multiple nutrients (nitrogen, phosphorus and potassium plus nine essential macro‐ and micro‐nutrients) on decomposition and biochemical transformation of standard plant materials buried in 21 grasslands from four continents. Addition of multiple nutrients weakly but consistently increased decomposition and biochemical transformation of plant remains during the peak‐season, concurrent with changes in microbial exoenzymatic activity. Higher mean annual precipitation and lower mean annual temperature were the main climatic drivers of higher decomposition rates, while biochemical transformation of plant remains was negatively related to temperature of the wettest quarter. Nutrients enhanced decomposition most at cool, high rainfall sites, indicating that in a warmer and drier future fertilized grassland soils will have an even more limited potential for microbial processing of plant remains. 

Abstract Environmental change can result in substantial shifts in community composition. The associated immigration and extinction events are likely constrained by the spatial distribution of species. Still, studies on environmental change typically quantify biotic responses at single spatial (time series within a single plot) or temporal (spatial beta diversity at single time points) scales, ignoring their potential interdependence. Here, we use data from a global network of grassland experiments to determine how turnover responses to two major forms of environmental change – fertilisation and herbivore loss – are affected by species pool size and spatial compositional heterogeneity. Fertilisation led to higher rates of local extinction, whereas turnover in herbivore exclusion plots was driven by species replacement. Overall, sites with more spatially heterogeneous composition showed significantly higher rates of annual turnover, independent of species pool size and treatment. Taking into account spatial biodiversity aspects will therefore improve our understanding of consequences of global and anthropogenic change on community dynamics.