Knowing When to Draw the Line: Designing More Informative Ecological Experiments

Linear regression and analysis of variance (ANOVA) are two of the most widely used statistical techniques in ecology. Regression quantitatively describes the relationship between a response variable and one or more continuous independent variables, while ANOVA determines whether a response variable differs among discrete values of the independent variable(s). Designing experiments with discrete factors is straightforward because ANOVA is the only option, but what is the best way to design experiments involving continuous factors? Should ecologists prefer experiments with few treatments and many replicates analyzed with ANOVA, or experiments with many treatments and few replicates per treatment analyzed with regression? We recommend that ecologists choose regression, especially replicated regression, over ANOVA when dealing with continuous factors for two reasons: (1) regression is generally a more powerful approach than ANOVA and (2) regression provides quantitative output that can be incorporated into ecological models more effectively than ANOVA output

Hypersaline lakes harbor more active bacterial communities

ABSTRACT Extremophiles employ a diverse array of resistance strategies to thrive under harsh 18 environmental conditions but maintaining these adaptations comes at an energetic cost. If energy reserves to drop too low, extremophiles may enter a dormant state of reduced 20 metabolic activity to survive. Dormancy is frequently offered as a plausible explanation for the persistence of bacteria under suboptimal environmental conditions with the 22 prevalence of this mechanism only expected to rise as stressful conditions intensify. We estimated dormancy in ten hypersaline and freshwater lakes across the Western United 24 States. To our surprise, we found that extreme environmental conditions did not induce higher levels of bacterial dormancy. Based on our approach using rRNA:rDNA gene 26 ratios to estimate activity, halophilic and halotolerant bacteria were classified as inactive at a similar percentage as freshwater bacteria, and the proportion of the community 28 exhibiting dormancy was considerably lower (16%) in hypersaline than freshwater lakes across a range of cutoffs estimating activity. Of the multiple chemical characteristics we 30 evaluated, salinity and, to a lesser extent, total phosphorus concentrations influenced activity. But instead of dormancy being more common as stressful conditions intensified, 32 the percentage of the community residing in an inactive state decreased with increasing salinity in freshwater and hypersaline lakes, suggesting that salinity acts as a strong 34 environmental filter selecting for bacteria that persist and thrive under saltier conditions. Within the compositionally distinct and less diverse hypersaline communities, abundant 36 taxa were disproportionately active and localized in families Microbacteriacea

Ecological networks of dissolved organic matter and microorganisms under global change

Microbes regulate the composition and turnover of organic matter. Here we developed a framework called Energy-Diversity-Trait integrative Analysis to quantify how dissolved organic matter and microbes interact along global change drivers of temperature and nutrient enrichment. Negative and positive interactions suggest decomposition and production processes of organic matter, respectively. We applied this framework to manipulative field experiments on mountainsides in subarctic and subtropical climates. In both climates, negative interactions of bipartite networks were more specialized than positive interactions, showing fewer interactions between chemical molecules and bacterial taxa. Nutrient enrichment promoted specialization of positive interactions, but decreased specialization of negative interactions, indicating that organic matter was more vulnerable to decomposition by a greater range of bacteria, particularly at warmer temperatures in the subtropical climate. These two global change drivers influenced specialization of negative interactions most strongly via molecular traits, while molecular traits and bacterial diversity similarly affected specialization of positive interactions. Microbes are intimately linked with the fate of organic matter. Here the authors develop an ecological network framework and show how microbes and dissolved organic matter interact along global change drivers of temperature and nutrient enrichment via manipulative field experiments on mountains.Peer reviewe

Integrating microbial ecology into ecosystem models: challenges and priorities

Microbial communities can potentially mediate feedbacks between global change and ecosystem function, owing to their sensitivity to environmental change and their control over critical biogeochemical processes. Numerous ecosystem models have been developed to predict global change effects, but most do not consider microbial mechanisms in detail. In this idea paper, we examine the extent to which incorporation of microbial ecology into ecosystem models improves predictions of carbon (C) dynamics under warming, changes in precipitation regime, and anthropogenic nitrogen (N) enrichment. We focus on three cases in which this approach might be especially valuable: temporal dynamics in microbial responses to environmental change, variation in ecological function within microbial communities, and N effects on microbial activity. Four microbially-based models have addressed these scenarios. In each case, predictions of the microbial-based models differ—sometimes substantially—from comparable conventional models. However, validation and parameterization of model performance is challenging. We recommend that the development of microbial-based models must occur in conjunction with the development of theoretical frameworks that predict the temporal responses of microbial communities, the phylogenetic distribution of microbial functions, and the response of microbes to N enrichment