Disentangling the influences of mean body size and size structure on ecosystem functioning: an example of nutrient recycling by a non-native crayfish.

Body size is a fundamental functional trait that can be used to forecast individuals' responses to environmental change and their contribution to ecosystem functioning. However, information on the mean and variation of size distributions often confound one another when relating body size to aggregate functioning. Given that size-based metrics are used as indicators of ecosystem status, it is important to identify the specific aspects of size distributions that mediate ecosystem functioning. Our goal was to simultaneously account for the mean, variance, and shape of size distributions when relating body size to aggregate ecosystem functioning. We take advantage of habitat-specific differences in size distributions to estimate nutrient recycling by a non-native crayfish using mean-field and variance-incorporating approaches. Crayfishes often substantially influence ecosystem functioning through their omnivorous role in aquatic food webs. As predicted from Jensen's inequality, considering only the mean body size of crayfish overestimated aggregate effects on ecosystem functioning. This bias declined with mean body size such that mean-field and variance-incorporating estimates of ecosystem functioning were similar for samples at mean body sizes >7.5 g. At low mean body size, mean-field bias in ecosystem functioning mismatch predictions from Jensen's inequality, likely because of the increasing skewness of the size distribution. Our findings support the prediction that variance around the mean can alter the relationship between body size and ecosystem functioning, especially at low mean body size. However, methods to account for mean-field bias performed poorly in samples with highly skewed distributions, indicating that changes in the shape of the distribution, in addition to the variance, may confound mean-based estimates of ecosystem functioning. Given that many biological functions scale allometrically, explicitly defining and experimentally or statistically isolating the effects of the mean, variance, and shape of size distributions is necessary to begin generalizing relationships between animal body size and ecosystem functioning.

Evolutionary relatedness does not predict competition and co-occurrence in natural or experimental communities of green algae.

The competition-relatedness hypothesis (CRH) predicts that the strength of competition is the strongest among closely related species and decreases as species become less related. This hypothesis is based on the assumption that common ancestry causes close relatives to share biological traits that lead to greater ecological similarity. Although intuitively appealing, the extent to which phylogeny can predict competition and co-occurrence among species has only recently been rigorously tested, with mixed results. When studies have failed to support the CRH, critics have pointed out at least three limitations: (i) the use of data poor phylogenies that provide inaccurate estimates of species relatedness, (ii) the use of inappropriate statistical models that fail to detect relationships between relatedness and species interactions amidst nonlinearities and heteroskedastic variances, and (iii) overly simplified laboratory conditions that fail to allow eco-evolutionary relationships to emerge. Here, we address these limitations and find they do not explain why evolutionary relatedness fails to predict the strength of species interactions or probabilities of coexistence among freshwater green algae. First, we construct a new data-rich, transcriptome-based phylogeny of common freshwater green algae that are commonly cultured and used for laboratory experiments. Using this new phylogeny, we re-analyse ecological data from three previously published laboratory experiments. After accounting for the possibility of nonlinearities and heterogeneity of variances across levels of relatedness, we find no relationship between phylogenetic distance and ecological traits. In addition, we show that communities of North American green algae are randomly composed with respect to their evolutionary relationships in 99% of 1077 lakes spanning the continental United States. Together, these analyses result in one of the most comprehensive case studies of how evolutionary history influences species interactions and community assembly in both natural and experimental systems. Our results challenge the generality of the CRH and suggest it may be time to re-evaluate the validity and assumptions of this hypothesis.

Evolutionary history and the strength of species interactions: testing the phylogenetic limiting similarity hypothesis.

A longstanding concept in community ecology is that closely related species compete more strongly than distant relatives. Ecologists have invoked this "limiting similarity hypothesis" to explain patterns in the structure and function of biological communities and to inform conservation, restoration, and invasive-species management. However, few studies have empirically tested the validity of the limiting similarity hypothesis. Here we report the results of a laboratory microcosm experiment in which we used a model system of 23 common, co-occurring North American freshwater green algae to quantify the strength of 216 pairwise species' interactions (the difference in population density when grown alone vs. in the presence of another species) along a manipulated gradient of evolutionary relatedness (phylogenetic distance, as the sum of branch lengths separating species on a molecular phylogeny). Interspecific interactions varied widely in these bicultures of phytoplankton, ranging from strong competition (ratio of relative yield in polyculture vs. monoculture << 1) to moderate facilitation (relative yield > 1). Yet, we found no evidence that the strength of species' interactions was influenced by their evolutionary relatedness. There was no relationship between phylogenetic distance and the average, minimum (inferior competitor), nor maximum (superior competitor) interaction strength across all biculture communities (respectively, P = 0.19, P = 0.17, P = 0.14; N = 428). When we examined each individual species, only 17% of individual species' interactions strengths varied as a function of phylogenetic distance, and none of these relationships remained significant after Bonferoni correction for multiple tests (N = 23). Last, when we grouped interactions into five qualitatively different types, the frequency of these types was not related to phylogenetic distance among species pairs (F4,422 = 1.63, P = 0.15). Our empirical study adds to several others that suggest the biological underpinnings of competition may not be evolutionarily conserved, and thus, ecologists may need to re-evaluate the previously assumed generality of the limiting similarity hypothesis.

Practical science communication strategies for graduate students.

Development of skills in science communication is a well-acknowledged gap in graduate training, but the constraints that accompany research (limited time, resources, and knowledge of opportunities) make it challenging to acquire these proficiencies. Furthermore, advisors and institutions may find it difficult to support graduate students adequately in these efforts. The result is fewer career and societal benefits because students have not learned to communicate research effectively beyond their scientific peers. To help overcome these hurdles, we developed a practical approach to incorporating broad science communication into any graduate-school time line. The approach consists of a portfolio approach that organizes outreach activities along a time line of planned graduate studies. To help design the portfolio, we mapped available science communication tools according to 5 core skills essential to most scientific careers: writing, public speaking, leadership, project management, and teaching. This helps graduate students consider the diversity of communication tools based on their desired skills, time constraints, barriers to entry, target audiences, and personal and societal communication goals. By designing a portfolio with an advisor's input, guidance, and approval, graduate students can gauge how much outreach is appropriate given their other commitments to teaching, research, and classes. The student benefits from the advisors' experience and mentorship, promotes the group's research, and establishes a track record of engagement. When graduate student participation in science communication is discussed, it is often recommended that institutions offer or require more training in communication, project management, and leadership. We suggest that graduate students can also adopt a do-it-yourself approach that includes determining students' own outreach objectives and time constraints and communicating these with their advisor. By doing so we hope students will help create a new culture of science communication in graduate student education.

Biodiversity simultaneously enhances the production and stability of community biomass, but the effects are independent.

To predict the ecological consequences of biodiversity loss, researchers have spent much time and effort quantifying how biological variation affects the magnitude and stability of ecological processes that underlie the functioning of ecosystems. Here we add to this work by looking at how biodiversity jointly impacts two aspects of ecosystem functioning at once: (1) the production of biomass at any single point in time (biomass/area or biomass/ volume), and (2) the stability of biomass production through time (the CV of changes in total community biomass through time). While it is often assumed that biodiversity simultaneously enhances both of these aspects of ecosystem functioning, the joint distribution of data describing how species richness regulates productivity and stability has yet to be quantified. Furthermore, analyses have yet to examine how diversity effects on production covary with diversity effects on stability. To overcome these two gaps, we reanalyzed the data from 34 experiments that have manipulated the richness of terrestrial plants or aquatic algae and measured how this aspect of biodiversity affects community biomass at multiple time points. Our reanalysis confirms that biodiversity does indeed simultaneously enhance both the production and stability of biomass in experimental systems, and this is broadly true for terrestrial and aquatic primary producers. However, the strength of diversity effects on biomass production is independent of diversity effects on temporal stability. The independence of effect sizes leads to two important conclusions. First, while it may be generally true that biodiversity enhances both productivity and stability, it is also true that the highest levels of productivity in a diverse community are not associated with the highest levels of stability. Thus, on average, diversity does not maximize the various aspects of ecosystem functioning we might wish to achieve in conservation and management. Second, knowing how biodiversity affects productivity gives no information about how diversity affects stability (or vice versa). Therefore, to predict the ecological changes that occur in ecosystems after extinction, we will need to develop separate mechanistic models for each independent aspect of ecosystem functioning.