The Role of Endocytosis during Morphogenetic Signaling

Morphogens are signaling molecules that are secreted by a localized source and spread in a target tissue where they are involved in the regulation of growth and patterning. Both the activity of morphogenetic signaling and the kinetics of ligand spreading in a tissue depend on endocytosis and intracellular trafficking. Here, we review quantitative approaches to study how large-scale morphogen profiles and signals emerge in a tissue from cellular trafficking processes and endocytic pathways. Starting from the kinetics of endosomal networks, we discuss the role of cellular trafficking and receptor dynamics in the formation of morphogen gradients. These morphogen gradients scale during growth, which implies that overall tissue size influences cellular trafficking kinetics. Finally, we discuss how such morphogen profiles can be used to control tissue growth. We emphasize the role of theory in efforts to bridge between scales.A fundamental challenge in biology is to understand how morphologies and complex patterns form in multicellular systems by the collective organization of many cells. Cells divide and undergo apoptosis, and they communicate via signaling pathways that use molecules as information carriers. In tissues, large-scale patterns of gene expression emerge from the coordinated signaling activity and response of many cells. The establishment of such patterns is often guided by long-range concentration profiles of morphogens. Cell divisions and cell rearrangements must be coordinated over large distances to achieve specific tissue sizes and shapes. To unravel how molecular processes and interactions can eventually be responsible for the formation of structures and patterns in tissues during development, it is important to study processes at different scales and understand how different levels of organization are connected. Such an approach becomes strongest if it involves a combination of quantitative experimental studies with theory.In the present article, we discuss several such approaches on different scales with a particular emphasis on theory. Starting from the kinetic and dynamic properties of endosomal networks inside a cell, we discuss transport processes in a tissue that can be related to kinetic trafficking parameters. Such transport processes are then responsible for the formation of graded morphogen concentration profiles. To permit scalable patterns in tissues of different sizes, it has been suggested that morphogen gradients scale during growth. This can be achieved on the tissue level by feedback systems that are sensitive to tissue size and regulate, for example, morphogen degradation. Finally, morphogen gradients that scale with tissue size can provide a system to robustly organize cell division in a large tissue and generate homogeneous growth. Theory can play an important role to bridge scales and understand how molecular and cellular processes can control pattern formation and tissue growth on larger scales.Morphogens are signaling molecules that are secreted in specific regions of developing tissues and can induce signaling activity far from their source. They typically form graded concentration profiles and therefore endow cells with positional information (cells can obtain information about their position in a tissue). Thus, they can guide cells to differentiate into complex morphological patterns. Morphogens also control cell growth and cell division. Because they control both patterning and growth, they may play a key role to coordinate these two processes. Such coordination is important because the size of morphological patterns must adjust during growth, whereas growth influences such patterns. A well-studied morphogen is Decapentaplegic (Dpp), which controls morphogenesis in the imaginal wing disc of developing Drosophila. Consequently, mutations in Dpp or defects in the trafficking pathways that control its graded concentration profiles and signaling affect the formation and structure of the adult wing.The study of morphogens was traditionally approached from a genetic perspective: Which gene products behave like morphogens? Which mutants affect patterning and growth? The realization that morphogens typically operate by a gradient of concentration raised the question of how morphogen gradients are generated. It became clear that the cellular trafficking of morphogens is a key issue for the generation of morphogen profiles. Morphogens are secreted ligands that bind receptors in the plasma membrane. The secretion of the ligands and the concentrations of receptor, ligand, and receptor/ligand complex at the plasma membrane are governed by their trafficking in the cell by vesicular transport. In particular, it was shown that trafficking through the endocytic pathway has an important impact on the formation of morphogen gradients (reviewed in Gonzalez-Gaitan 2003; see Bökel and Brand 2014). This is, to a large extent, how the cells respond to morphogens and contribute to set their local concentrations. To understand functions of morphogens in a tissue, we need to study how the gradient is formed. This, in turn, requires insights into morphogen trafficking through the endocytic pathway. The problem of morphogen behavior, therefore, becomes a problem spanning several levels of complexity: the organ level, the tissue level, the cell level, the organelle level, and the molecular level. Theoretical approaches motivated by physics combined with quantitative experimental approaches provide an ideal framework to understand how these different levels of complexity are intertwined.Two recent discoveries highlighted such integration. (1) The observation that profiles of the morphogen Dpp scale during growth, which implies that the rate of Dpp degradation mediated by the endocytic pathway of each of the cells in the tissue depends on the size of the overall tissue. This suggests that two levels of complexity are linked because cellular trafficking receives cues about the global tissue size. (2) As a result of the changes of the degradation rate that leads to gradient scaling, cells receive an increasing level of signaling. This, in turn, can be used by the cells to decide when to divide. This regulation again involves two levels of complexity because regulation at the endocytic pathway determines the growth properties of the tissue and, ultimately, its final size.In the following, we discuss quantitative approaches to study cellular signaling processes on different scales. Here, the aim is to understand how patterns on large scales can emerge during development from molecular processes and signaling pathways that involve endocytosis and cellular trafficking. We begin by describing trafficking of ligands in the endocytic pathway. We then consider the situation of a morphogen ligand and its impact in gradient formation. Subsequently, we discuss how gradient scaling might be realized. Finally, we discuss how such scaling processes play an important role in the regulation of morphogenetic growth.     

DNA metabarcoding reveals changes in the contents of carnivorous plants along an elevation gradient

Resource variation along abiotic gradients influences subsequent trophic interactions and these effects can be transmitted through entire food webs. Interactions along abiotic gradients can provide clues as to how organisms will face changing environmental conditions, such as future range shifts. However, it is challenging to find replicated systems to study these effects. Phytotelmata, such as those found in carnivorous plants, are isolated aquatic communities and thus form a good model for the study of replicated food webs. Due to the degraded nature of the prey, molecular techniques provide a useful tool to study these communities. We studied the pitcher plant Sarracenia purpurea L. in allochthonous populations along an elevational gradient in the Alps and Jura. We predicted that invertebrate richness in the contents of the pitcher plants would decrease with increasing elevation, reflecting harsher environmental conditions. Using metabarcoding of the COI gene, we sequenced the invertebrate contents of these pitcher plants. We assigned Molecular Operational Taxonomic Units at ordinal level as well as recovering species‐level data. We found small but significant changes in community composition with elevation. These recovered sequences could belong to invertebrate prey, rotifer inquilines, pollinators and other animals possibly living inside the pitchers. However, we found no directional trend or site‐based differences in MOTU richness with elevational gradient. Use of molecular techniques for dietary or contents analysis is a powerful way to examine numerous degraded samples, although factors such as DNA persistence and the relationship with species presence still have to be completely determined.     

Two-Sided Edge Effect Studies and the Restoration of Endangered Ecosystems

Edge effect is the modification of ecological patterns and processes that occur around the edge of two adjacent ecosystems. Depending on their aim, edge effect studies have adopted one of the following methodological approaches: (1) the one‐sided approach—which studies ecological patterns and processes from an edge to the interior of just one of the habitats and (2) the two‐sided approach—which studies ecological patterns and processes across the whole gradient from the interior of one habitat to the interior of the other habitat, passing through the edge zone. A database containing information on 317 published papers revealed that both methodological approaches were equally used until the end of the 1980s. During the 1990s, the question of how organisms respond to habitat destruction and fragmentation led to an abrupt increase in the number of one‐sided studies. Recently, however, two‐sided studies have become more frequent. In this review, we put forth theoretical arguments of why the two‐sided edge effect approach can produce a broader understanding of the ecological processes associated with edges. We highlight that two‐sided edge effect studies must become more experimental and predictive, focusing on the factors controlling edge dynamics. Finally, we point out that two‐sided edge effect studies have the potential to create a positive research agenda for the restoration and expansion of endangered ecosystems.     

Density‐dependent dispersal and the formation of range borders.

Knowledge about the mechanisms of range formation is crucial for scientifically based species conservation strategies in the face of ongoing global climate change. In recent years an increasing amount of studies have focused on the influences of density‐dependent dispersal on demographic and biogeographical patterns. However, it still remains unclear, to what extent and in what ways this strategy would affect the range formation of species. In order to fill this gap, we present a study using individual‐based simulations of a species with discrete generations living along a dispersal mortality gradient. We compare the evolution of range sizes for species following density‐dependent and density‐independent emigration. Furthermore we assess the influence of environmental stochasticity and Allee effects on range formation, as both processes are known to play an important role for dispersal evolution. We find that density‐dependent dispersal always results in much wider ranges than unconditional dispersal. Increasing environmental stochasticity, a predicted consequence of climate change, can remarkably expand the ranges of species living in such connectivity gradients if dispersal decisions are based on local population density. A strong Allee effect causes range contraction for both strategies, but the effect is considerably less dramatic under density‐dependent compared to density‐independent emigration. We strongly recommend accounting for these findings in future attempts to model species’ range shifts due to climate change.     

Cell,Isoform, and Environment Factors Shape Gradients and Modulate Chemotaxis

Chemokine gradient formation requires multiple processes that include ligand secretion and diffusion, receptor binding and internalization, and immobilization of ligand to surfaces. To understand how these events dynamically shape gradients and influence ensuing cell chemotaxis, we built a multi-scale hybrid agent-based model linking gradient formation, cell responses, and receptor-level information. The CXCL12/CXCR4/CXCR7 signaling axis is highly implicated in metastasis of many cancers. We model CXCL12 gradient formation as it is impacted by CXCR4 and CXCR7, with particular focus on the three most highly expressed isoforms of CXCL12. We trained and validated our model using data from an in vitro microfluidic source-sink device. Our simulations demonstrate how isoform differences on the molecular level affect gradient formation and cell responses. We determine that ligand properties specific to CXCL12 isoforms (binding to the migration surface and to CXCR4) significantly impact migration and explain differences in in vitro chemotaxis data. We extend our model to analyze CXCL12 gradient formation in a tumor environment and find that short distance, steep gradients characteristic of the CXCL12-γ isoform are effective at driving chemotaxis. We highlight the importance of CXCL12-γ in cancer cell migration: its high effective affinity for both extracellular surface sites and CXCR4 strongly promote CXCR4+ cell migration. CXCL12-γ is also more difficult to inhibit, and we predict that co-inhibition of CXCR4 and CXCR7 is necessary to effectively hinder CXCL12-γ-induced migration. These findings support the growing importance of understanding differences in protein isoforms, and in particular their implications for cancer treatment.     

Application of multivariate statistical techniques in microbial ecology

Recent advances in high‐throughput methods of molecular analyses have led to an explosion of studies generating large‐scale ecological data sets. In particular, noticeable effect has been attained in the field of microbial ecology, where new experimental approaches provided in‐depth assessments of the composition, functions and dynamic changes of complex microbial communities. Because even a single high‐throughput experiment produces large amount of data, powerful statistical techniques of multivariate analysis are well suited to analyse and interpret these data sets. Many different multivariate techniques are available, and often it is not clear which method should be applied to a particular data set. In this review, we describe and compare the most widely used multivariate statistical techniques including exploratory, interpretive and discriminatory procedures. We consider several important limitations and assumptions of these methods, and we present examples of how these approaches have been utilized in recent studies to provide insight into the ecology of the microbial world. Finally, we offer suggestions for the selection of appropriate methods based on the research question and data set structure.     

Pom1 gradient buffering through intermolecular auto‐phosphorylation

Concentration gradients provide spatial information for tissue patterning and cell organization, and their robustness under natural fluctuations is an evolutionary advantage. In rod‐shaped Schizosaccharomyces pombe cells, the DYRK‐family kinase Pom1 gradients control cell division timing and placement. Upon dephosphorylation by a Tea4‐phosphatase complex, Pom1 associates with the plasma membrane at cell poles, where it diffuses and detaches upon auto‐phosphorylation. Here, we demonstrate that Pom1 auto‐phosphorylates intermolecularly, both in vitro and in vivo, which confers robustness to the gradient. Quantitative imaging reveals this robustness through two system's properties: The Pom1 gradient amplitude is inversely correlated with its decay length and is buffered against fluctuations in Tea4 levels. A theoretical model of Pom1 gradient formation through intermolecular auto‐phosphorylation predicts both properties qualitatively and quantitatively. This provides a telling example where gradient robustness through super‐linear decay, a principle hypothesized a decade ago, is achieved through autocatalysis. Concentration‐dependent autocatalysis may be a widely used simple feedback to buffer biological activities.     

Combining contemporary ecology and palaeolimnology to understand shallow lake ecosystem change

1. Palaeolimnology and contemporary ecology are complementary disciplines but are rarely combined. By reviewing the literature and using a case study, we show how linking the timescales of these approaches affords a powerful means of understanding ecological change in shallow lakes. 2. Recently, palaeolimnology has largely been pre‐occupied with developing transfer functions which use surface sediment‐lake environment datasets to reconstruct a single environmental variable. Such models ignore complex controls over biological structure and can be prone to considerable error in prediction. Furthermore, by reducing species assemblage data to a series of numbers, transfer functions neglect valuable ecological information on species’ seasonality, habitat structure and food web interactions. These elements can be readily extracted from palaeolimnological data with the interpretive assistance of contemporary experiments and surveys. For example, for one shallow lake, we show how it is possible to infer long‐term seasonality change from plant macrofossil and fossil diatom data with the assistance of seasonal datasets on macrophyte and algal dynamics. 3. On the other hand, theories on shallow lake functioning have generally been developed from short‐term (<1–15 years) studies as opposed to palaeo‐data that cover the actual timescales (decades–centuries) of shallow lake response to stressors such as eutrophication and climate change. Palaeolimnological techniques can track long‐term dynamics in lakes whilst smoothing out short‐term variability and thus provide a unique and important means of not only developing ecological theories, but of testing them. 4. By combining contemporary ecology and palaeolimnology, it should be possible to gain a fuller understanding of changing ecological patterns and processes in shallow lakes on multiple timescales.     

Using geometric morphometric visualizations of directional selection gradients to investigate morphological differentiation

Researchers studying extant and extinct taxa are often interested in identifying the evolutionary processes that have lead to the morphological differences among the taxa. Ideally, one could distinguish the influences of neutral evolutionary processes (genetic drift, mutation) from natural selection, and in situations for which selection is implicated, identify the targets of selection. The directional selection gradient is an effective tool for investigating evolutionary process, because it can relate form (size and shape) differences between taxa to the variation and covariation found within taxa. However, although most modern morphometric analyses use the tools of geometric morphometrics (GM) to analyze landmark data, to date, selection gradients have mainly been calculated from linear measurements. To address this methodological gap, here we present a GM approach for visualizing and comparing between‐taxon selection gradients with each other, associated difference vectors, and “selection” gradients from neutral simulations. To exemplify our approach, we use a dataset of 347 three‐dimensional landmarks and semilandmarks recorded on the crania of 260 primate specimens (112 humans, 67 common chimpanzees, 36 bonobos, 45 gorillas). Results on this example dataset show how incorporating geometric information can provide important insights into the evolution of the human braincase, and serve to demonstrate the utility of our approach for understanding morphological evolution.     

Riparian vegetation‐environment relationships: complimentarity of gradients versus patch hierarchy approaches

Abstract. Two prominent conceptual frameworks, environmental gradients and patch hierarchies, are used in combination to describe vegetation patterns along a riparian corridor in a semi‐arid South African system. We adopt both approaches, since riparian corridors are characterized by both strong environmental gradients above, away from and along the river, as well as a mosaic of patches in the geomorphology at multiple hierarchical scales. Constrained and unconstrained ordinations were used to determine the variability in vegetation pattern accounted for by the gradient and the geomorphic patch hierarchy data sets. The gradient data set consisted of vertical, lateral and longitudinal dimensions of the macro‐channel, while the patch hierarchy data set consisted of substratum type, morphological unit and channel type. Elevation up the macro‐channel bank, of the gradient data set, explained the main variation in vegetation pattern, and alluded to overriding processes of flooding frequency and water availability as determinants of vegetation pattern. Along the fluvially dynamic macro‐channel floor (lower elevation range), patchiness at the scale of the morphological unit best explained vegetation pattern. This relationship with morphological units suggests that the formation of well developed alluvial bars, and the degree of bedrock influence are important processes. The nested hierarchical framework used provided a good basis for identifying scale specific pattern in a relational manner. In systems characterized by strong environmental gradients as well as a patch mosaic at different spatial and temporal scales, the combined use of both perspectives to develop a fuller understanding of vegetation pattern is imperative and is encouraged.     

Shaping Morphogen Gradients by Proteoglycans

During development, secreted morphogens such as Wnt, Hedgehog (Hh), and BMP emit from their producing cells in a morphogenetic field, and specify different cell fates in a direct concentration-dependent manner. Understanding how morphogens form their concentration gradients to pattern tissues has been a central issue in developmental biology. Various experimental studies from Drosophila have led to several models to explain the formation of morphogen gradients. Over the past decade, one of the main findings in this field is the characterization of heparan sulfate proteoglycan (HSPG) as an essential regulator for morphogen gradient formation. Genetic and cell biological studies have showed that HSPGs can regulate morphogen activities at various steps including control of morphogen movement, signaling, and intracellular trafficking. Here, we review these data, highlighting recent findings that reveal mechanistic roles of HSPGs in controlling morphogen gradient formation.Embryonic development involves many spatial and temporal patterns of cell and tissue organization. These patterning processes are controlled by gradients of morphogens, the “form-generating substances” (Tabata and Takei 2004; Lander 2007). Secreted morphogen molecules, including members of Wnt, Hedgehog (Hh), and transforming growth factor-β (TGF-β) families, are generated from organizing centers and form concentration gradients to specify distinct cell fates in a concentration-dependent manner. Understanding how morphogen gradients are established during development has been a central question in developmental biology. Over the past decade, studies in both Drosophila and vertebrates have yielded important insights in this field. One of the important findings is the characterization of heparan sulfate proteoglycan (HSPG) as an essential regulator for morphogen gradient formation. In this review, we first discuss various models for morphogen movement. Then, we focus on the functions of HSPGs in morphogen movement, signaling, and trafficking.     

Does phylogenetic distance aid in detecting environmental gradients related to species composition?

Questions: How should we evaluate the success of new distance measures combining community abundance and phylogenetic information? How do we interpret ordinations using these metrics? Methods: We generated synthetic data along a known environmental gradient with two hypothetical underlying phylogenetic structures: niche phylogenetically conserved or dispersed along a gradient. We also examined tree species composition associated with gradients in elevation and longitude in Oregon, USA. NMS ordinations of plots in species space from phylogenetic (PD) and Sørensen distance (SD) matrices allowed comparison of the use of PD in different scenarios. Results: PD caused plots to cluster based on the clades that they contained, reducing stress with the synthetic data but not with the real example. Phylogenetic distance highlighted clades related to gradients when these were associated. When phylogeny was not conserved along a gradient, that gradient was less strong. Regardless of phylogenetic conservation, NMS using SD consistently extracted the strongest gradients in species composition. Conclusions: The success of PD should be evaluated on how well it extracts gradients in species composition and allows community ecologists to determine which gradients are partially explained by phylogeny and not based on its ability to reduce ordination stress. PD ordinations can help community ecologists interpret niche conservation but may obscure gradients related to species composition when niches are not conserved along the gradient of interest at the scale of the study.     

Multiple environmental determinants of regional species richness and effects of geographic range size

Understanding patterns of species richness at broad geographic extents remains one of the most challenging yet necessary scientific goals of our time. Many hypotheses have been proposed to account for spatial variation in species richness; among them, environmental determinants have played a central role. In this study, we use data on regional bat species richness in the New World to study redundancy and complementarity of three environmental hypotheses: energy, heterogeneity and seasonality. We accomplish this by partitioning variation in species richness among components associated with unique and combined effects of variables from each hypotheses, and by partitioning the overall richness gradient into gradients of species with varying breadths of geographic distribution. These three environmental hypotheses explain most variation in the species richness gradient of all bats, but do not account for all positive spatial autocorrelation at short distances. Although environmental predictors are highly redundant, energy and seasonality explain different and complementary fractions of variation in species richness of all bats. On the other hand, heterogeneity variables contribute little to explain this gradient. However, results change dramatically when richness is estimated for groups of species with different sizes of geographic distribution. First, the amount of variation explained by environment decreases with a decrease in range size; this suggests that richness gradients of small‐ranged species can not be explained as easily as those of broadly distributed species, as has been implied by analyses that do not consider differences in range size among species. Second, the relative contribution of environmental predictors to explained variation also changes with change in range size. Seasonality and energy are good predictors of species with broad distributions, but they loose almost all explanatory power for richness of species with small ranges. In contrast, heterogeneity, which is a relatively poor predictor of richness of species with large ranges, becomes the main predictor of richness gradients of species with restricted distributions. This suggests that range size is a different dimension on which heterogeneity and other environmental characteristics are complementary to each other. Our results suggest that determinants of species richness gradients might be complex, or at least more complex than many studies have previously suggested.     

When should species richness be energy limited,and how would we know?

Energetic constraints are fundamental to ecology and evolution, and empirical relationships between species richness and estimates of available energy (i.e. resources) have led some to suggest that richness is energetically constrained. However, the mechanism linking energy with richness is rarely specified and predictions of secondary patterns consistent with energy‐constrained richness are lacking. Here, we lay out the necessary and sufficient assumptions of a causal relationship linking energy gradients to richness gradients. We then describe an eco‐evolutionary simulation model that combines spatially explicit diversification with trait evolution, resource availability and assemblage‐level carrying capacities. Our model identified patterns in richness and phylogenetic structure expected when a spatial gradient in energy availability determines the number of individuals supported in a given area. A comparison to patterns under alternative scenarios, in which fundamental assumptions behind energetic explanations were violated, revealed patterns that are useful for evaluating the importance of energetic constraints in empirical systems. We use a data set on rockfish (genus Sebastes) from the northeastern Pacific to show how empirical data can be coupled with model predictions to evaluate the role of energetic constraints in generating observed richness gradients.     

Early mechanisms of amyloid fibril nucleation in model and disease-related proteins

Protein amyloid aggregation is a hallmark in neuropathologies and other diseases of tremendous impact such as Alzheimer’s or Parkinson’s diseases. During the last decade, it has become increasingly evident that neuronal death is mainly induced by proteinaceous oligomers rather than the mature amyloid fibrils. Therefore, the earliest molecular events occurring during the amyloid aggregation cascade represent a growing interest of study.Important breakthroughs have been achieved using experimental data from different proteins, used as models, as well as systems related to diseases. Here, we summarize the structural properties of amyloid oligomeric and fibrillar aggregates and review the recent advances on how biophysical techniques can be combined with quantitative kinetic analysis and theoretical models to study the detailed mechanism of oligomer formation and nucleation of fibrils.These insights into the mechanism of early oligomerization and amyloid nucleation are of relevant interest in drug discovery and in the design of preventive strategies against neurodegenerative diseases.     

A data‐driven approach to modeling the tripartite structure of multidrug resistance efflux pumps

Many bacterial pathogens are becoming increasingly resistant to antibiotic treatments, and a detailed understanding of the molecular basis of antibiotic resistance is critical for the development of next‐generation approaches for combating bacterial infections. Studies focusing on pathogens have revealed the profile of resistance in these organisms to be due primarily to the presence of multidrug resistance efflux pumps: tripartite protein complexes which span the periplasm bridging the inner and outer membranes of Gram‐negative bacteria. An atomic‐level resolution tripartite structure remains imperative to advancing our understanding of the molecular mechanisms of pump function using both theoretical and experimental approaches. We develop a fast and consistent method for constructing tripartite structures which leverages existing data‐driven models and provide molecular modeling approaches for constructing tripartite structures of multidrug resistance efflux pumps. Our modeling studies reveal that conformational changes in the inner membrane component responsible for drug translocation have limited impact on the conformations of the other pump components, and that two distinct models derived from conflicting experimental data are both consistent with all currently available measurements. Additionally, we investigate putative drug translocation pathways via geometric simulations based on the available crystal structures of the inner membrane pump component, AcrB, bound to two drugs which occupy distinct binding sites: doxorubicin and linezolid. These simulations suggest that smaller drugs may enter the pump through a channel from the cytoplasmic leaflet of the inner membrane, while both smaller and larger drug molecules may enter through a vestibule accessible from the periplasm. Proteins 2015; 83:46–65. © 2014 Wiley Periodicals, Inc.     

Bet‐hedging germination in annual plants: a sound empirical test of the theoretical foundations

Seed dormancy is thought to be a key mechanism allowing annual plants to spread extinction risk in unpredictably varying environments. Theory predicts increasing germination fractions with increasing probability of reproductive success but solid empirical evidence is scarce and often confounded with environmental factors. Here we provide an empirical test of bet‐hedging via delayed germination for three annual plant species along a ‘predictability gradient’ in Israel. We excluded confounding environmental and maternal effects by raising inbred seed families and germinating them under controlled conditions. Additionally, we germinated field‐collected seeds in three consecutive seasons to compare their germination with inbred families where maternal effects were removed. Risk of reproductive failure was quantified using demographic data from the field and from second‐generation inbred lines raised in a rainfall gradient in the greenhouse. Our findings were consistent with bet‐hedging theory in that germination fraction was negatively related to species‐ and site‐specific risk of reproductive failure. Both field and hand‐raised seeds of one species exhibited higher dormancy with increasing risk of reproductive failure across sites, and hand‐raised seeds of another species showed the same pattern. The third species exhibited a rather random pattern of germination between years and sites, corresponding to the lack of site‐specific risk of reproductive failure. Species‐specific patterns of dormancy and risk could be related to alternative risk‐spreading strategies such as high adult survival, but were also affected by phylogeny. We provide strong empirical evidence for seed dormancy being a mechanism to reduce the risk of reproductive failure in highly variable environments, but a larger number of rigorous experimental tests of bet hedging germination are needed. Specifically, the genetic basis of bet‐hedging must be shown in species with different life histories, for demonstrating that dormancy is adaptive and how it is modified by other risk‐spreading traits.