Reproductive correlation and mean-variance scaling of reproductive output for a forest model

We analyse the mean-variance scaling of reproductive output for a previously published forest model. The model relates individual reproductive effort and pollen limitation to the degree of synchrony in reproduction throughout a forest. We show that the exponent of Taylor's power law reflects the degree of synchrony of reproduction because it indicates the covariance of reproductive behavior. Further, we are able to relate the three components of masting, individual variability, population variability and synchrony in reproductive output, using Taylor's power law. Therefore Taylor's power law can be used as a synoptic index of masting.     

Detection of arylsulfatase A activity after electrophoresis in polyacrylamide gels: problems and solutions.

When arylsulfatase extracted from normal human skin fibroblasts was electrophoresed in polyacrylamide gels with a Tris-glycine buffer at pH 8.4–8.6, two problems occurred. First, no arylsulfatase A activity was detected. Second, an artifactual fluorescent spot was generated when the gels were stained for arylsulfatase activity with 4-methylumbelliferyl sulfate as substrate. The artifact simulated arylsulfatase A activity in mobility but also appeared when 4-methylumbelliferyl substrates for other enzymes were used. It can be eliminated by prerunning or prolonged storage of the gets before use. The arylsulfatase A activity, however, could be recovered only when a low pH buffer system (pH 58–68) was used for electrophoresis. The highest percentage recovery (70%) of activity was obtained in acrylamide gels polymerized with ammonium persulfate, prerun for 0.5 h before use and electrophoresed with an anode buffer of acetic acid-triethanolamine at pH 5.8.     

A Fatty Acid Based Bayesian Approach for Inferring Diet in Aquatic Consumers

We modified the stable isotope mixing model MixSIR to infer primary producer contributions to consumer diets based on their fatty acid composition. To parameterize the algorithm, we generated a ‘consumer-resource library’ of FA signatures of Daphnia fed different algal diets, using 34 feeding trials representing diverse phytoplankton lineages. This library corresponds to the resource or producer file in classic Bayesian mixing models such as MixSIR or SIAR. Because this library is based on the FA profiles of zooplankton consuming known diets, and not the FA profiles of algae directly, trophic modification of consumer lipids is directly accounted for. To test the model, we simulated hypothetical Daphnia comprised of 80% diatoms, 10% green algae, and 10% cryptophytes and compared the FA signatures of these known pseudo-mixtures to outputs generated by the mixing model. The algorithm inferred these simulated consumers were comprised of 82% (63-92%) [median (2.5th to 97.5th percentile credible interval)] diatoms, 11% (4-22%) green algae, and 6% (0-25%) cryptophytes. We used the same model with published phytoplankton stable isotope (SI) data for δ¹³C and δ¹⁵N to examine how a SI based approach resolved a similar scenario. With SI, the algorithm inferred that the simulated consumer assimilated 52% (4-91%) diatoms, 23% (1-78%) green algae, and 18% (1-73%) cyanobacteria. The accuracy and precision of SI based estimates was extremely sensitive to both resource and consumer uncertainty, as well as the trophic fractionation assumption. These results indicate that when using only two tracers with substantial uncertainty for the putative resources, as is often the case in this class of analyses, the underdetermined constraint in consumer-resource SI analyses may be intractable. The FA based approach alleviated the underdetermined constraint because many more FA biomarkers were utilized (n < 20), different primary producers (e.g., diatoms, green algae, and cryptophytes) have very characteristic FA compositions, and the FA profiles of many aquatic primary consumers are strongly influenced by their diets.     

Dynamics of nutrient uptake strategies: lessons from the tortoise and the hare

Many autotrophs vary their allocation to nutrient uptake in response to environmental cues, yet the dynamics of this plasticity are largely unknown. Plasticity dynamics affect the extent of single versus multiple nutrient limitation and thus have implications for plant ecology and biogeochemical cycling. Here we use a model of two essential nutrients cycling through autotrophs and the environment to determine conditions under which different plastic or fixed nutrient uptake strategies are adaptive. Our model includes environment-independent costs of being plastic, environment-dependent costs proportional to the rate of plastic change, and costs of being mismatched to the environment, the last of which is experienced by both fixed and plastic types. In equilibrium environments, environment-independent costs of being plastic select for tortoise strategies—fixed or less plastic types—provided that they are sufficiently close to co-limitation. At intermediate levels of environmental fluctuation forced by periodic nutrient inputs, more hare-like plastic strategies prevail because they remain near co-limitation. However, the fastest is not necessarily the best. The most adaptive strategy is an intermediate level of plasticity that keeps pace with environmental fluctuations, but is not faster. At high levels of environmental fluctuation, the environment-dependent cost of changing rapidly to keep pace with the environment becomes prohibitive and tortoise strategies again dominate. The existence and location of these thresholds depend on plasticity costs and rate, which are largely unknown empirically. These results suggest that the expectations for single nutrient limitation versus co-limitation and therefore biogeochemical cycling and autotroph community dynamics depend on environmental heterogeneity and plasticity costs.     

CD11c controls herpes simplex virus 1 responses to limit virus replication during primary infection

CD11c is expressed on the surface of dendritic cells (DCs) and is one of the main markers for identification of DCs. DCs are the effectors of central innate immune responses, but they also affect acquired immune responses to infection. However, how DCs influence the efficacy of adaptive immunity is poorly understood. Here, we show that CD11c(+) DCs negatively orchestrate both adaptive and innate immunity against herpes simplex virus type 1 (HSV-1) ocular infection. The effectiveness and quantity of virus-specific CD8(+) T cell responses are increased in CD11c-deficient animals. In addition, the levels of CD83, CD11b, alpha interferon (IFN-α), and IFN-β, but not IFN-γ, were significantly increased in CD11c-deficient animals. Higher levels of IFN-α, IFN-β, and CD8(+) T cells in the CD11c-deficient mice may have contributed to lower virus replication in the eye and trigeminal ganglia (TG) during the early period of infection than in wild-type mice. However, the absence of CD11c did not influence survival, severity of eye disease, or latency. Our studies provide for the first time evidence that CD11c expression may abrogate the ability to reduce primary virus replication in the eye and TG via higher activities of type 1 interferon and CD8(+) T cell responses.     

The observed range for temporal mean-variance scaling exponents can be explained by reproductive correlation

The mean-variance scaling relationship known as Taylor's power law has been well documented empirically over the past four decades but a general theoretical explanation for the phenomenon does not exist. Here we provide an explanation that relates empirical patterns of temporal mean-variance scaling to individual level reproductive behavior. Initially, we review the scaling behavior of population growth models to establish theoretical limits for the scaling exponent b that is in agreement with the empirically observed range (1≤b≤2). We go on to show that the degree of reproductive covariance among individuals determines the scaling exponent b. Independent reproduction results in an exponent of one, while completely correlated reproduction results in the upper limit of two. Intermediate exponents, which are common empirically, can be generated through the decay of reproductive covariance with increasing population size. Finally, we describe how the link between reproductive correlation and the scaling exponent provides a way to infer properties of individual-level reproductive behavior, such as the relative influence of demographic stochasticity, from a macroecological pattern.