The adaptive challenge of extreme conditions shapes evolutionary diversity of plant assemblages at continental scales.

The tropical conservatism hypothesis (TCH) posits that the latitudinal gradient in biological diversity arises because most extant clades of animals and plants originated when tropical environments were more widespread and because the colonization of colder and more seasonal temperate environments is limited by the phylogenetically conserved environmental tolerances of these tropical clades. Recent studies have claimed support of the TCH, indicating that temperate plant diversity stems from a few more recently derived lineages that are nested within tropical clades, with the colonization of the temperate zone being associated with key adaptations to survive colder temperatures and regular freezing. Drought, however, is an additional physiological stress that could shape diversity gradients. Here, we evaluate patterns of evolutionary diversity in plant assemblages spanning the full extent of climatic gradients in North and South America. We find that in both hemispheres, extratropical dry biomes house the lowest evolutionary diversity, while tropical moist forests and many temperate mixed forests harbor the highest. Together, our results support a more nuanced view of the TCH, with environments that are radically different from the ancestral niche of angiosperms having limited, phylogenetically clustered diversity relative to environments that show lower levels of deviation from this niche. Thus, we argue that ongoing expansion of arid environments is likely to entail higher loss of evolutionary diversity not just in the wet tropics but in many extratropical moist regions as well.

Climate shapes and shifts functional biodiversity in forests worldwide.

Much ecological research aims to explain how climate impacts biodiversity and ecosystem-level processes through functional traits that link environment with individual performance. However, the specific climatic drivers of functional diversity across space and time remain unclear due largely to limitations in the availability of paired trait and climate data. We compile and analyze a global forest dataset using a method based on abundance-weighted trait moments to assess how climate influences the shapes of whole-community trait distributions. Our approach combines abundance-weighted metrics with diverse climate factors to produce a comprehensive catalog of trait-climate relationships that differ dramatically-27% of significant results change in sign and 71% disagree on sign, significance, or both-from traditional species-weighted methods. We find that (i) functional diversity generally declines with increasing latitude and elevation, (ii) temperature variability and vapor pressure are the strongest drivers of geographic shifts in functional composition and ecological strategies, and (iii) functional composition may currently be shifting over time due to rapid climate warming. Our analysis demonstrates that climate strongly governs functional diversity and provides essential information needed to predict how biodiversity and ecosystem function will respond to climate change.

Macroevolution of dimensionless life-history metrics in tetrapods.

Life-history traits represent organisms' strategies to navigate the fitness trade-offs between survival and reproduction. Eric Charnov developed three dimensionless metrics to quantify fundamental life-history trade-offs. Lifetime reproductive effort (LRE), relative reproductive lifespan (RRL) and relative offspring size (ROS), together with body mass can be used to classify life-history strategies across the four major classes of tetrapods: amphibians, reptiles, mammals and birds. First, we investigate how the metrics have evolved in concert with body mass within tetrapod lineages. In most cases, we find evidence for correlated evolution among body mass and the three dimensionless metrics. Second, we compare life-history strategies across the four classes of tetrapods and find that LRE, RRL and ROS delineate a space in which the major tetrapod classes occupy mostly unique subspaces. These distinct combinations of life-history strategies provide us with a framework to understand the impact of major evolutionary transitions in energetics, physiology and ecology.

Data Science in Undergraduate Life Science Education: A Need for Instructor Skills Training.

There is a clear demand for quantitative literacy in the life sciences, necessitating competent instructors in higher education. However, not all instructors are versed in data science skills or research-based teaching practices. We surveyed biological and environmental science instructors (n = 106) about the teaching of data science in higher education, identifying instructor needs and illuminating barriers to instruction. Our results indicate that instructors use, teach, and view data management, analysis, and visualization as important data science skills. Coding, modeling, and reproducibility were less valued by the instructors, although this differed according to institution type and career stage. The greatest barriers were instructor and student background and space in the curriculum. The instructors were most interested in training on how to teach coding and data analysis. Our study provides an important window into how data science is taught in higher education biology programs and how we can best move forward to empower instructors across disciplines.

Convergence of terrestrial plant production across global climate gradients.

Variation in terrestrial net primary production (NPP) with climate is thought to originate from a direct influence of temperature and precipitation on plant metabolism. However, variation in NPP may also result from an indirect influence of climate by means of plant age, stand biomass, growing season length and local adaptation. To identify the relative importance of direct and indirect climate effects, we extend metabolic scaling theory to link hypothesized climate influences with NPP, and assess hypothesized relationships using a global compilation of ecosystem woody plant biomass and production data. Notably, age and biomass explained most of the variation in production whereas temperature and precipitation explained almost none, suggesting that climate indirectly (not directly) influences production. Furthermore, our theory shows that variation in NPP is characterized by a common scaling relationship, suggesting that global change models can incorporate the mechanisms governing this relationship to improve predictions of future ecosystem function.

The latitudinal species richness gradient in New World woody angiosperms is consistent with the tropical conservatism hypothesis.

Plant diversity, like that of most other taxonomic groups, peaks in the tropics, where climatic conditions are warm and wet, and it declines toward the temperate and polar zones as conditions become colder and drier, with more seasonally variable temperatures. Climate and evolutionary history are often considered competing explanations for the latitudinal gradient, but they are linked by the evolutionarily conserved environmental adaptations of species and the history of Earth's climate system. The tropical conservatism hypothesis (TCH) invokes niche conservatism, climatic limitations on establishment and survival, and paleoclimatic history to explain the latitudinal diversity gradient. Here, we use latitudinal distributions for over 12,500 woody angiosperm species, a fossil-calibrated supertree, and null modeling to test predictions of the TCH. Regional assemblages in the northern and southern temperate zones are less phylogenetically diverse than expected based on their species richness, because temperate taxa are clustered into relatively few clades. Moreover, lineages with temperate affinities are generally younger and nested within older, more tropical lineages. As predicted by the TCH, the vast majority of temperate lineages have arisen since global cooling began at the Eocene-Oligocene boundary (34 Mya). By linking physiological tolerances of species to evolutionary and biogeographic processes, phylogenetic niche conservatism may provide a theoretical framework for a generalized explanation for Earth's predominant pattern of biodiversity.

Biological scaling: does the exception prove the rule?

Reich et al. report that the whole-plant respiration rate, R, in seedlings scales linearly with plant mass, M, so that R=C(R)M(theta) when theta approximately 1, in which c(R) is the scaling normalization and theta is the scaling exponent. They also state that because nitrogen concentration (N) is correlated with c(R), variation in N is a better predictor of R than M would be. Reich et al. and Hedin incorrectly claim that these "universal" findings question the central tenet of metabolic scaling theory, which they interpret as predicting theta = (3/4), irrespective of the size of the plant. Here we show that these conclusions misrepresent metabolic scaling theory and that their results are actually consistent with this theory.

A general integrative model for scaling plant growth, carbon flux, and functional trait spectra.

Linking functional traits to plant growth is critical for scaling attributes of organisms to the dynamics of ecosystems and for understanding how selection shapes integrated botanical phenotypes. However, a general mechanistic theory showing how traits specifically influence carbon and biomass flux within and across plants is needed. Building on foundational work on relative growth rate, recent work on functional trait spectra, and metabolic scaling theory, here we derive a generalized trait-based model of plant growth. In agreement with a wide variety of empirical data, our model uniquely predicts how key functional traits interact to regulate variation in relative growth rate, the allometric growth normalizations for both angiosperms and gymnosperms, and the quantitative form of several functional trait spectra relationships. The model also provides a general quantitative framework to incorporate additional leaf-level trait scaling relationships and hence to unite functional trait spectra with theories of relative growth rate, and metabolic scaling. We apply the model to calculate carbon use efficiency. This often ignored trait, which may influence variation in relative growth rate, appears to vary directionally across geographic gradients. Together, our results show how both quantitative plant traits and the geometry of vascular transport networks can be merged into a common scaling theory. Our model provides a framework for predicting not only how traits covary within an integrated allometric phenotype but also how trait variation mechanistically influences plant growth and carbon flux within and across diverse ecosystems.

Testing the metabolic theory of ecology.

The metabolic theory of ecology (MTE) predicts the effects of body size and temperature on metabolism through considerations of vascular distribution networks and biochemical kinetics. MTE has also been extended to characterise processes from cellular to global levels. MTE has generated both enthusiasm and controversy across a broad range of research areas. However, most efforts that claim to validate or invalidate MTE have focused on testing predictions. We argue that critical evaluation of MTE also requires strong tests of both its theoretical foundations and simplifying assumptions. To this end, we synthesise available information and find that MTE's original derivations require additional assumptions to obtain the full scope of attendant predictions. Moreover, although some of MTE's simplifying assumptions are well supported by data, others are inconsistent with empirical tests and even more remain untested. Further, although many predictions are empirically supported on average, work remains to explain the often large variability in data. We suggest that greater effort be focused on evaluating MTE's underlying theory and simplifying assumptions to help delineate the scope of MTE, generate new theory and shed light on fundamental aspects of biological form and function.

Colloquium paper: microbes on mountainsides: contrasting elevational patterns of bacterial and plant diversity.

The study of elevational diversity gradients dates back to the foundation of biogeography. Although elevational patterns of plant and animal diversity have been studied for centuries, such patterns have not been reported for microorganisms and remain poorly understood. Here, in an effort to assess the generality of elevational diversity patterns, we examined soil bacterial and plant diversity along an elevation gradient. To gain insight into the forces that structure these patterns, we adopted a multifaceted approach to incorporate information about the structure, diversity, and spatial turnover of montane communities in a phylogenetic context. We found that observed patterns of plant and bacterial diversity were fundamentally different. While bacterial taxon richness and phylogenetic diversity decreased monotonically from the lowest to highest elevations, plants followed a unimodal pattern, with a peak in richness and phylogenetic diversity at mid-elevations. At all elevations bacterial communities had a tendency to be phylogenetically clustered, containing closely related taxa. In contrast, plant communities did not exhibit a uniform phylogenetic structure across the gradient: they became more overdispersed with increasing elevation, containing distantly related taxa. Finally, a metric of phylogenetic beta-diversity showed that bacterial lineages were not randomly distributed, but rather exhibited significant spatial structure across the gradient, whereas plant lineages did not exhibit a significant phylogenetic signal. Quantifying the influence of sample scale in intertaxonomic comparisons remains a challenge. Nevertheless, our findings suggest that the forces structuring microorganism and macroorganism communities along elevational gradients differ.

Ecosystem allometry: the scaling of nutrient stocks and primary productivity across plant communities.

A principal challenge in ecology is to integrate physiological function (e.g. photosynthesis) across a collection of individuals (e.g. plants of different species) to understand the functioning of the entire ensemble (e.g. primary productivity). The control that organism size exerts over physiological and ecological function suggests that allometry could be a powerful tool for scaling ecological processes across levels of organization. Here we use individual plant allometries to predict how nutrient content and productivity scale with total plant biomass (phytomass) in whole plant communities. As predicted by our model, net primary productivity as well as whole community nitrogen and phosphorus content all scale allometrically with phytomass across diverse plant communities, from tropical forest to arctic tundra. Importantly, productivity data deviate quantitatively from the theoretically derived prediction, and nutrient productivity (production per unit nutrient) of terrestrial plant communities decreases systematically with increasing total phytomass. These results are consistent with the existence of pronounced competitive size hierarchies. The previously undocumented generality of these 'ecosystem allometries' and their basis in the structure and function of individual plants will likely provide a useful quantitative framework for research linking plant traits to ecosystem processes.

Phylogenetic and growth form variation in the scaling of nitrogen and phosphorus in the seed plants.

Plant biomass and nutrient allocation explicitly links the evolved strategies of plant species to the material and energy cycles of ecosystems. Allocation of nitrogen (N) and phosphorus (P) is of particular interest because N and P play pivotal roles in many aspects of plant biology, and their availability frequently limits plant growth. Here we present a comparative scaling analysis of a global data compilation detailing the N and P contents of leaves, stems, roots, and reproductive structures of 1,287 species in 152 seed plant families. We find that P and N contents (as well as N : P) are generally highly correlated both within and across organs and that differences exist between woody and herbaceous taxa. Between plant organs, the quantitative form of the scaling relationship changes systematically, depending on whether the organs considered are primarily structural (i.e., stems, roots) or metabolically active (i.e., leaves, reproductive structures). While we find significant phylogenetic signals in the data, similar scaling relationships occur in independently evolving plant lineages, which implies that both the contingencies of evolutionary history and some degree of environmental convergence have led to a common set of rules that constrain the partitioning of nutrients among plant organs.

The allometry of coarse root biomass: log-transformed linear regression or nonlinear regression?

Precise estimation of root biomass is important for understanding carbon stocks and dynamics in forests. Traditionally, biomass estimates are based on allometric scaling relationships between stem diameter and coarse root biomass calculated using linear regression (LR) on log-transformed data. Recently, it has been suggested that nonlinear regression (NLR) is a preferable fitting method for scaling relationships. But while this claim has been contested on both theoretical and empirical grounds, and statistical methods have been developed to aid in choosing between the two methods in particular cases, few studies have examined the ramifications of erroneously applying NLR. Here, we use direct measurements of 159 trees belonging to three locally dominant species in east China to compare the LR and NLR models of diameter-root biomass allometry. We then contrast model predictions by estimating stand coarse root biomass based on census data from the nearby 24-ha Gutianshan forest plot and by testing the ability of the models to predict known root biomass values measured on multiple tropical species at the Pasoh Forest Reserve in Malaysia. Based on likelihood estimates for model error distributions, as well as the accuracy of extrapolative predictions, we find that LR on log-transformed data is superior to NLR for fitting diameter-root biomass scaling models. More importantly, inappropriately using NLR leads to grossly inaccurate stand biomass estimates, especially for stands dominated by smaller trees.

Ontogenetic scaling of metabolism, growth, and assimilation: testing metabolic scaling theory with Manduca sexta larvae.

Metabolism, growth, and the assimilation of energy and materials are essential processes that are intricately related and depend heavily on animal size. However, models that relate the ontogenetic scaling of energy assimilation and metabolism to growth rely on assumptions that have yet to be rigorously tested. Based on detailed daily measurements of metabolism, growth, and assimilation in tobacco hornworms, Manduca sexta, we provide a first experimental test of the core assumptions of a metabolic scaling model of ontogenetic growth. Metabolic scaling parameters changed over development, in violation of the model assumptions. At the same time, the scaling of growth rate matches that of metabolic rate, with similar scaling exponents both across and within developmental instars. Rates of assimilation were much higher than expected during the first two instars and did not match the patterns of scaling of growth and metabolism, which suggests high costs of biosynthesis early in development. The rapid increase in size and discrete instars observed in larval insect development provide an ideal system for understanding how patterns of growth and metabolism emerge from fundamental cellular processes and the exchange of materials and energy between an organism and its environment.

Global patterns of city size distributions and their fundamental drivers.

Urban areas and their voracious appetites are increasingly dominating the flows of energy and materials around the globe. Understanding the size distribution and dynamics of urban areas is vital if we are to manage their growth and mitigate their negative impacts on global ecosystems. For over 50 years, city size distributions have been assumed to universally follow a power function, and many theories have been put forth to explain what has become known as Zipf's law (the instance where the exponent of the power function equals unity). Most previous studies, however, only include the largest cities that comprise the tail of the distribution. Here we show that national, regional and continental city size distributions, whether based on census data or inferred from cluster areas of remotely-sensed nighttime lights, are in fact lognormally distributed through the majority of cities and only approach power functions for the largest cities in the distribution tails. To explore generating processes, we use a simple model incorporating only two basic human dynamics, migration and reproduction, that nonetheless generates distributions very similar to those found empirically. Our results suggest that macroscopic patterns of human settlements may be far more constrained by fundamental ecological principles than more fine-scale socioeconomic factors.

Relationships between body size and abundance in ecology.

Body size is perhaps the most fundamental property of an organism and is related to many biological traits, including abundance. The relationship between abundance and body size has been extensively studied in an attempt to quantify the form of the relationship and to understand the processes that generate it. However, progress has been impeded by the under appreciated fact that there are four distinct, but interrelated, relationships between size and abundance that are often confused in the literature. Here, we review and distinguish between these four patterns, and discuss the linkages between them. We argue that a synthetic understanding of size-abundance relationships will result from more detailed analyses of individual patterns and from careful consideration of how and why the patterns are related.

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.