Species interactions drive continuous assembly of freshwater communities in stochastic environments.

Understanding the factors driving the maintenance of long-term biodiversity in changing environments is essential for improving restoration and sustainability strategies in the face of global environmental change. Biodiversity is shaped by both niche and stochastic processes, however the strength of deterministic processes in unpredictable environmental regimes is highly debated. Since communities continuously change over time and space-species persist, disappear or (re)appear-understanding the drivers of species gains and losses from communities should inform us about whether niche or stochastic processes dominate community dynamics. Applying a nonparametric causal discovery approach to a 30-year time series containing annual abundances of benthic invertebrates across 66 locations in New Zealand rivers, we found a strong negative causal relationship between species gains and losses directly driven by predation indicating that niche processes dominate community dynamics. Despite the unpredictable nature of these system, environmental noise was only indirectly related to species gains and losses through altering life history trait distribution. Using a stochastic birth-death framework, we demonstrate that the negative relationship between species gains and losses can not emerge without strong niche processes. Our results showed that even in systems that are dominated by unpredictable environmental variability, species interactions drive continuous community assembly.

Scaling of biological rates with body size as a backbone in the assembly of metacommunity biodiversity.

The dispersal-body mass association has been highlighted as a main determinant of biodiversity patterns in metacommunities. However, less attention has been devoted to other well-recognized determinants of metacommunity diversity: the scaling in density and regional richness with body size. Among active dispersers, the increase in movement with body size may enhance local richness and decrease ß-diversity. Nevertheless, the reduction of population size and regional richness with body mass may determine a negative diversity-body size association. Consequently, metacommunity assembly probably emerges from a balance between the effect of these scalings. We formalize this hypothesis by relating the exponents of size-scaling rules with simulated trends in α-, ß- and γ-diversity with body size. Our results highlight that the diversity-body size relationship in metacommunities may be driven by the combined effect of different scaling rules. Given their ubiquity in most terrestrial and aquatic biotas, these scaling rules may represent the basic determinants-backbone-of biodiversity, over which other mechanisms operate determining metacommunity assembly. Further studies are needed, aimed at explaining biodiversity patterns from functional relationships between biological rates and body size, as well as their association with environmental conditions and species interactions.

Allometric scaling of interspecific RNA transcript abundance to extend the use of metatranscriptomics in characterizing complex communities.

Metatranscriptomics allows profiling of community mRNA and rRNA transcript abundance under certain environmental conditions. However, variations in the proportion of RNA transcripts across different community size structures remain less explained, thus limiting the possible applications of metatranscriptomics in community studies. Here, we extended the assumptions of the growth-rate hypothesis (GRH) and the metabolic theory of ecology (MTE) to validate the allometric scaling of interspecific RNA transcript (mRNA and rRNA) abundance through metatranscriptomic analysis of mock communities consisting of model organisms. The results suggest that body size imposes significant constraints on RNA transcript abundance. Interestingly, the relationship between the total mitochondrial transcript abundance (mRNA and rRNA slopes were -0.30 and -0.28, respectively) and body size aligned with the MTE assumptions with slopes close to -», while the nuclear transcripts displayed much steeper slopes (mRNA and rRNA slopes were -0.33 and -0.40, respectively). The assumed temperature dependence was not observed in this study. At the gene level, the allometric slopes range from 0 to -1. Overall, the above results showed that larger individuals have lesser RNA transcript abundance per tissue mass than smaller ones regardless of temperature. Analyses of field-collected microcrustacean zooplankton samples demonstrated that the correction of size effect, using the allometric exponents derived from the model organism mock community, explains better the patterns of interspecific RNA transcripts abundance within the metatranscriptome. Integrating allometry with metatranscriptomics can extend the use of RNA transcript reads in estimating ecological processes within complex communities.

Variable metabolic scaling breaks the law: from 'Newtonian' to 'Darwinian' approaches.

Life's size and tempo are intimately linked. The rate of metabolism varies with body mass in remarkably regular ways that can often be described by a simple power function, where the scaling exponent (b, slope in a log-linear plot) is typically less than 1. Traditional theory based on physical constraints has assumed that b is 2/3 or 3/4, following natural law, but hundreds of studies have documented extensive, systematic variation in b. This overwhelming, law-breaking, empirical evidence is causing a paradigm shift in metabolic scaling theory and methodology from 'Newtonian' to 'Darwinian' approaches. A new wave of studies focuses on the adaptable regulation and evolution of metabolic scaling, as influenced by diverse intrinsic and extrinsic factors, according to multiple context-dependent mechanisms, and within boundary limits set by physical constraints.

Biological scaling analyses are more than statistical line fitting.

The magnitude of many biological traits relates strongly and regularly to body size. Consequently, a major goal of comparative biology is to understand and apply these 'size-scaling' relationships, traditionally quantified by using linear regression analyses based on log-transformed data. However, recently some investigators have questioned this traditional method, arguing that linear or non-linear regression based on untransformed arithmetic data may provide better statistical fits than log-linear analyses. Furthermore, they advocate the replacement of the traditional method by alternative specific methods on a case-by-case basis, based simply on best-fit criteria. Here, I argue that the use of logarithms in scaling analyses presents multiple valuable advantages, both statistical and conceptual. Most importantly, log-transformation allows biologically meaningful, properly scaled (scale-independent) comparisons of organisms of different size, whereas non-scaled (scale-dependent) analyses based on untransformed arithmetic data do not. Additionally, log-based analyses can readily reveal biologically and theoretically relevant discontinuities in scale invariance during developmental or evolutionary increases in body size that are not shown by linear or non-linear arithmetic analyses. In this way, log-transformation advances our understanding of biological scaling conceptually, not just statistically. I hope that my Commentary helps students, non-specialists and other interested readers to understand the general benefits of using log-transformed data in size-scaling analyses, and stimulates advocates of arithmetic analyses to show how they may improve our understanding of scaling conceptually, not just statistically.

Non-dimensional physics of pulsatile cardiovascular networks and energy efficiency.

In Nature, there exist a variety of cardiovascular circulation networks in which the energetic ventricular load has both steady and pulsatile components. Steady load is related to the mean cardiac output (CO) and the haemodynamic resistance of the peripheral vascular system. On the other hand, the pulsatile load is determined by the simultaneous pressure and flow waveforms at the ventricular outlet, which in turn are governed through arterial wave dynamics (transmission) and pulse decay characteristics (windkessel effect). Both the steady and pulsatile contributions of the haemodynamic power load are critical for characterizing/comparing disease states and for predicting the performance of cardiovascular devices. However, haemodynamic performance parameters vary significantly from subject to subject because of body size, heart rate and subject-specific CO. Therefore, a 'normalized' energy dissipation index, as a function of the 'non-dimensional' physical parameters that govern the circulation networks, is needed for comparative/integrative biological studies and clinical decision-making. In this paper, a complete network-independent non-dimensional formulation that incorporates pulsatile flow regimes is developed. Mechanical design variables of cardiovascular flow systems are identified and the Buckingham Pi theorem is formally applied to obtain the corresponding non-dimensional scaling parameter sets. Two scaling approaches are considered to address both the lumped parameter networks and the distributed circulation components. The validity of these non-dimensional number sets is tested extensively through the existing empirical allometric scaling laws of circulation systems. Additional validation studies are performed using a parametric numerical arterial model that represents the transmission and windkessel characteristics, which are adjusted to represent different body sizes and non-dimensional haemodynamic states. Simulations demonstrate that the proposed non-dimensional indices are independent of body size for healthy conditions, but are sensitive to deviations caused by off-design disease states that alter the energetic load. Sensitivity simulations are used to identify the relationship between pulsatile power loss and non-dimensional characteristics, and optimal operational states are computed.

Is the scaling of swim speed in sharks driven by metabolism?

The movement rates of sharks are intrinsically linked to foraging ecology, predator-prey dynamics and wider ecosystem functioning in marine systems. During ram ventilation, however, shark movement rates are linked not only to ecological parameters, but also to physiology, as minimum speeds are required to provide sufficient water flow across the gills to maintain metabolism. We develop a geometric model predicting a positive scaling relationship between swim speeds in relation to body size and ultimately shark metabolism, taking into account estimates for the scaling of gill dimensions. Empirical data from 64 studies (26 species) were compiled to test our model while controlling for the influence of phylogenetic similarity between related species. Our model predictions were found to closely resemble the observed relationships from tracked sharks, providing a means to infer mobility in particularly intractable species.

Reconciling theories for metabolic scaling.

Metabolic theory specifies constraints on the metabolic organisation of individual organisms. These constraints have important implications for biological processes ranging from the scale of molecules all the way to the level of populations, communities and ecosystems, with their application to the latter emerging as the field of metabolic ecology. While ecologists continue to use individual metabolism to identify constraints in ecological processes, the topic of metabolic scaling remains controversial. Much of the current interest and controversy in metabolic theory relates to recent ideas about the role of supply networks in constraining energy supply to cells. We show that an alternative explanation for physicochemical constraints on individual metabolism, as formalised by dynamic energy budget (DEB) theory, can contribute to the theoretical underpinning of metabolic ecology, while increasing coherence between intra- and interspecific scaling relationships. In particular, we emphasise how the DEB theory considers constraints on the storage and use of assimilated nutrients and derive an equation for the scaling of metabolic rate for adult heterotrophs without relying on optimisation arguments or implying cellular nutrient supply limitation. Using realistic data on growth and reproduction from the literature, we parameterise the curve for respiration and compare the a priori prediction against a mammalian data set for respiration. Because the DEB theory mechanism for metabolic scaling is based on the universal process of acquiring and using pools of stored metabolites (a basal feature of life), it applies to all organisms irrespective of the nature of metabolic transport to cells. Although the DEB mechanism does not necessarily contradict insight from transport-based models, the mechanism offers an explanation for differences between the intra- and interspecific scaling of biological rates with mass, suggesting novel tests of the respective hypotheses.