Taylor's power law for freshwater fishes: Functional traits beyond statistical inevitability.

Taylor's power law (TPL) describes the expected range of parameters of the mean-variance scaling relationship and has been extensively used in studies examining temporal variations in abundance. Few studies though have focused on biological and ecological covariates of TPL, while its statistical inherences have been extensively debated. In the present study, we focused on species-specific features (i.e. functional traits) that could be influential to temporal TPL. We combined field surveys of 180 fish species from 972 sites varying from small streams to large rivers with data on 31 ecological traits describing species-specific characteristics related to three main niche dimensions (trophic ecology, life history, and habitat use). For each species, the parameters of temporal TPL (intercept and slope) were estimated from the log-log mean-variance relationships while controlling for spatial dependencies and biological covariates (species richness and evenness). Then, we investigated whether functional traits explained variations in TPL parameters. Differences in TPL parameters among species were explained mostly by life history and environmental determinants, especially TPL slope. Life history was the main determinant of differences in TPL parameters and thereby aggregation patterns, with traits related to body size being the most influential, thus showing a high contrast between small-sized species with short lifespans and large-bodied migratory fishes, even after controlling for phylogenetic resemblances. We found that life history traits, especially those related to body size, mostly affect TPL and, as such, can be determinants of temporal variability of fish populations. We also found that statistical effects and phylogenetic resemblances are embedded in mean-variance relationships for fish, and that environmental drivers can interact with ecological characteristics of species in determining temporal fluctuations in abundance.

Abundance-diversity relationship as a unique signature of temporal scaling in the fossil record.

Species diversity increases with the temporal grain of samples according to the species-time relationship (STR), impacting palaeoecological analyses because the temporal grain (time averaging) of fossil assemblages varies by several orders of magnitude. We predict a positive relation between total abundance and sample size-independent diversity (ADR) in fossil assemblages because an increase in time averaging, determined by a decreasing sediment accumulation, should increase abundance and depress species dominance. We demonstrate that, in contrast to negative ADR of non-averaged living assemblages, the ADR of Holocene fossil assemblages is positive, unconditionally or when conditioned on the energy availability gradient. However, the positive fossil ADR disappears when conditioned on sediment accumulation, demonstrating that ADR is a signature of diversity scaling induced by variable time averaging. Conditioning ADR on sediment accumulation can identify and remove the scaling effect caused by time averaging, providing an avenue for unbiased biodiversity comparisons across space and time.

Navigating uncertainty in maximum body size in marine metazoans.

Body size is a fundamental biological trait shaping ecological interactions, evolutionary processes, and our understanding of the structure and dynamics of marine communities on a global scale. Accurately defining a species' body size, despite the ease of measurement, poses significant challenges due to varied methodologies, tool usage, and subjectivity among researchers, resulting in multiple, often discrepant size estimates. These discrepancies, stemming from diverse measurement approaches and inherent variability, could substantially impact the reliability and precision of ecological and evolutionary studies reliant on body size data across extensive species datasets. This study examines the variation in reported maximum body sizes across 69,570 individual measurements of maximum size, ranging from <0.2 µm to >45 m, for 27,271 species of marine metazoans. The research aims to investigate how reported maximum size variations within species relate to organism size, taxonomy, habitat, and the presence of skeletal structures. The investigation particularly focuses on understanding why discrepancies in maximum size estimates arise and their potential implications for broader ecological and evolutionary studies relying on body size data. Variation in reported maximum sizes is zero for 38% of species, and low for most species, although it exceeds two orders of magnitude for some species. The likelihood of zero variation in maximum size decreased with more measurements and increased in larger species, though this varied across phyla and habitats. Pelagic organisms consistently had low maximum size range values, while small species with unspecified habitats had the highest variation. Variations in maximum size within a species were notably smaller than interspecific variation at higher taxonomic levels. Significant variation in maximum size estimates exists within marine species, and partially explained by organism size, taxonomic group, and habitat. Variation in maximum size could be reduced by standardized measurement protocols and improved meta-data. Despite the variation, egregious errors in published maximum size measurements are rare, and their impact on comparative macroecological and macroevolutionary research is likely minimal.

Dispersal-diversity feedbacks and their consequences for macroecological patterns.

Dispersal is a key process in ecology and evolution. While the effects of dispersal on diversity are broadly acknowledged, our understanding of the influence of diversity on dispersal remains limited. This arises from the dynamic, context-dependent, nonlinear and ubiquitous nature of dispersal. Diversity outcomes, such as competition, mutualism, parasitism and trophic interactions can feed back on dispersal, thereby influencing biodiversity patterns at several spatio-temporal scales. Here, we shed light on the dispersal-diversity causal links by discussing how dispersal-diversity ecological and evolutionary feedbacks can impact macroecological patterns. We highlight the importance of dispersal-diversity feedbacks for advancing our understanding of macro-eco-evolutionary patterns and their challenges, such as establishing a unified framework for dispersal terminology and methodologies across various disciplines and scales. This article is part of the theme issue 'Diversity-dependence of dispersal: interspecific interactions determine spatial dynamics'.

Chasing and surfing seasonal waves: Avian migration through the US tracks land surface phenology in fall, but not spring.

Climate change is altering the timing of seasonal events for many taxa. There is limited understanding of how northward/southward songbird migration follows or is limited by the latitudinal progression of seasonal transitions. Consistent environmental conditions that migrating birds encounter across latitudes likely represent or correlate with important resources or limiting factors for migration. We tested whether migratory passage-observed via radar-consistently tracked land surface variables and phenophases across latitudes in the US Central Flyway in both spring and fall. The daily temperatures, precipitation and vegetation greenness occurring on 10%, 50% and 90% cumulative passage dates changed substantially with latitude, indicating that most migrants experienced rapidly changing conditions as they headed north or south. Temperature did not limit the progression of migration in either season. Peak spring migration in the southern US occurred nearly 40 days after the spring green wave, the northward progression of vegetation growth, but nearly caught up to green-up at 48° N. Spring migration phenology may have evolved to prioritize earlier arrival for breeding. Across all latitudes, peak fall migration coincided with the same land surface phenophase, an interval of 26 days prior to dormancy onset. Migrants may rely on phenological events in vegetation during fall stopovers. Considering that (a) migratory passage tracked fall land surface phenology across latitudes at a continental scale, (b) previous studies at local scales have demonstrated the importance of fruit during fall migratory stopover and (c) fruiting phenology in North America is occurring later over time while fall migration is advancing, the potential for mismatch between fall fruiting and bird migration phenology urgently needs further investigation.

Towards a species-level phylogeny for Neotropical Myrtaceae: Notes on topology and resources for future studies.

PREMISE: Increasingly complete phylogenies underpin studies in systematics, ecology, and evolution. Myrteae (Myrtaceae), with ~2700 species, is a key component of the exceptionally diverse Neotropical flora, but given its complicated taxonomy, automated assembling of molecular supermatrices from public databases often lead to unreliable topologies due to poor species identification. METHODS: Here, we build a taxonomically verified molecular supermatrix of Neotropical Myrteae by assembling 3909 published and 1004 unpublished sequences from two nuclear and seven plastid molecular markers. We infer a time-calibrated phylogenetic tree that covers 712 species of Myrteae (~28% of the total diversity in the clade) and evaluate geographic and taxonomic gaps in sampling. RESULTS: The tree inferred from the fully concatenated matrix mostly reflects the topology of the plastid data set and there is a moderate to strong incongruence between trees inferred from nuclear and plastid partitions. Large, species-rich genera are still the poorest sampled within the group. Eastern South America is the best-represented area in proportion to its species diversity, while Western Amazon, Mesoamerica, and the Caribbean are the least represented. CONCLUSIONS: We provide a time-calibrated tree that can be more reliably used to address finer-scale eco-evolutionary questions that involve this group in the Neotropics. Gaps to be filled by future studies include improving representation of taxa and areas that remain poorly sampled, investigating causes of conflict between nuclear and plastid partitions, and the role of hybridization and incomplete lineage sorting in relationships that are poorly supported.

Vrba was right: Historical climate fragmentation, and not current climate, explains mammal biogeography.

Climate plays a crucial role in shaping species distribution and evolution over time. Dr Vrba's Resource-Use hypothesis posited that zones at the extremes of temperature and precipitation conditions should host a greater number of climate specialist species than other zones because of higher historical fragmentation. Here, we tested this hypothesis by examining climate-induced fragmentation over the past 5 million years. Our findings revealed that, as stated by Vrba, the number of climate specialist species increases with historical regional climate fragmentation, whereas climate generalist species richness decreases. This relationship is approximately 40% stronger than the correlation between current climate and species richness for climate specialist species and 77% stronger for generalist species. These evidences suggest that the effect of climate historical fragmentation is more significant than that of current climate conditions in explaining mammal biogeography. These results provide empirical support for the role of historical climate fragmentation and physiography in shaping the distribution and evolution of life on Earth.

Scaling approaches and macroecology provide a foundation for assessing ecological resilience in the Anthropocene.

In the Anthropocene, intensifying ecological disturbances pose significant challenges to our predictive capabilities for ecosystem responses. Macroecology-which focuses on emergent statistical patterns in ecological systems-unveils consistent regularities in the organization of biodiversity and ecosystems. These regularities appear in terms of abundance, body size, geographical range, species interaction networks, or the flux of matter and energy. This paper argues for moving beyond qualitative resilience metaphors, such as the 'ball and cup', towards a more quantitative macroecological framework. We suggest a conceptual and theoretical basis for ecological resilience that integrates macroecology with a stochastic diffusion approximation constrained by principles of biological symmetry. This approach provides an alternative novel framework for studying ecological resilience in the Anthropocene. We demonstrate how our framework can effectively quantify the impacts of major disturbances and their extensive ecological ramifications. We further show how biological scaling insights can help quantify the consequences of major disturbances, emphasizing their cascading ecological impacts. The nature of these impacts prompts a re-evaluation of our understanding of resilience. Emphasis on regularities of ecological assemblages can help illuminate resilience dynamics and offer a novel basis to predict and manage the impacts of disturbance in the Anthropocene more efficiently. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Tree species occurring in Amazonian wetland forests consistently show broader range sizes and niche breadths than trees in upland forests.

Generally, species with broad niches also show large range sizes. We investigated the relationship between hydrological niche breadth and geographic range size for Amazonian tree species seeking to understand the role of habitat specialization to Amazonian wetlands and upland forests on the current distribution of tree species. We obtained 571,092 valid occurrence points from GBIF and SpeciesLink to estimate the range size and the niche breadth of 76% of all known Amazonian tree species (5150 tree species). Hydrological niche breadth was measured on different unidimensional axes defined by (1) total annual precipitation; (2) precipitation seasonality; (3) actual evapotranspiration; and (4) water table depth. Geographic range sizes were estimated using alpha-hull adjustments. General linear models were used to relate niche breadth to range size while contrasting tree species occurring and not occurring in wetlands. The hydrological niche breadth of Amazonian tree species varied mostly along the water table depth axis. The average range size for an Amazonian tree species was 751,000 km2 (median of 154,000 km2 and standard deviation of 1,550,000 km2). Niche breadth-range size relationships for Amazonian tree species were positive for all models, and the explanatory power of the models improved when including whether a species occurred in wetlands or in terrestrial uplands. Wetland species had steeper positive slopes for the niche breadth-range size relationship, and consistently larger range sizes for a given niche breadth. Amazonian tree species varied strongly in hydrological niche breadth and range size, but most species had narrow niche breadths and range sizes. Our results suggest that the South American riverscape may have been acting as a corridor for species dispersal in the Neotropical lowlands.

Plant size traits are key contributors in the spatial variation of net primary productivity across terrestrial biomes in China.

Understanding the spatial variability of ecosystem functions is an important step forward in predicting changes in ecosystems under global transformations. Plant functional traits are important drivers of ecosystem functions such as net primary productivity (NPP). Although trait-based approaches have advanced rapidly, the extent to which specific plant functional traits are linked to the spatial diversity of NPP at a regional scale remains uncertain. Here, we used structural equation models (SEMs) to disentangle the relative effects of abiotic variables (i.e., climate, soil, nitrogen deposition, and human footprint) and biotic variables (i.e., plant functional traits and community structure) on the spatial variation of NPP across China and its eight biomes. Additionally, we investigated the indirect influence of climate and soil on the spatial variation of NPP by directly affecting plant functional traits. Abiotic and biotic variables collectively explained 62.6 % of the spatial differences of NPP within China, and 28.0 %-69.4 % across the eight distinct biomes. The most important abiotic factors, temperature and precipitation, had positive effects for NPP spatial variation. Interestingly, plant functional traits associated with the size of plant organs (i.e., plant height, leaf area, seed mass, and wood density) were the primary biotic drivers, and their positive effects were independent of biome type. Incorporating plant functional traits improved predictions of NPP by 6.7 %-50.2 %, except for the alpine tundra on the Qinghai-Tibet Plateau. Our study identifies the principal factors regulating NPP spatial variation and highlights the importance of plant size traits in predictions of NPP variation at a large scale. These results provide new insights for involving plant size traits in carbon process models.

Incorporating plant phenological responses into species distribution models reduces estimates of future species loss and turnover.

Anthropogenetic climate change has caused range shifts among many species. Species distribution models (SDMs) are used to predict how species ranges may change in the future. However, most SDMs rarely consider how climate-sensitive traits, such as phenology, which affect individuals' demography and fitness, may influence species' ranges. Using > 120 000 herbarium specimens representing 360 plant species distributed across the eastern United States, we developed a novel 'phenology-informed' SDM that integrates phenological responses to changing climates. We compared the ranges of each species forecast by the phenology-informed SDM with those from conventional SDMs. We further validated the modeling approach using hindcasting. When examining the range changes of all species, our phenology-informed SDMs forecast less species loss and turnover under climate change than conventional SDMs. These results suggest that dynamic phenological responses of species may help them adjust their ecological niches and persist in their habitats as the climate changes. Plant phenology can modulate species' responses to climate change, mitigating its negative effects on species persistence. Further application of our framework will contribute to a generalized understanding of how traits affect species distributions along environmental gradients and facilitate the use of trait-based SDMs across spatial and taxonomic scales.

Contrasting impacts of non-native and threatened species on morphological, life history, and phylogenetic diversity in bird assemblages.

Human activities have altered the species composition of assemblages through introductions and extinctions, but it remains unclear how those changes can affect the different facets of biodiversity. Here we assessed the impact of changes in species composition on taxonomic, functional, and phylogenetic diversity across 281 bird assemblages worldwide. To provide a more nuanced understanding of functional diversity, we distinguished morphological from life-history traits. We showed that shifts in species composition could trigger a global decline in avian biodiversity due to the high number of potential extinctions. Moreover, these extinctions were not random but unique in terms of function and phylogeny at the regional level. Our findings demonstrated that non-native species cannot compensate for these losses, as they are both morphologically and phylogenetically close to the native fauna. In the context of the ongoing biodiversity crisis, such alterations in the functional and phylogenetic structure of bird assemblages could heighten ecosystem vulnerability.

Speed and degree of functional and compositional recovery varies with latitude and community age.

Rates at which a community recovers after disturbance, or its resilience, can be accelerated by increased net primary productivity and recolonization dynamics such as recruitment. These mechanisms can vary across biogeographic gradients, such as latitude, suggesting that biogeography is likely important to predicting resilience. To test whether community resilience, informed by functional and compositional recovery, hinges on geographic location, we employed a standardized replicated experiment on marine invertebrate communities across four regions from the tropics to the subarctic zone. Communities assembled naturally on standardized substrate while experiencing distinct levels of biomass removal (no removal, low disturbance, and high disturbance), which opened space for new colonizers, thereby providing a pulse of limited resource to these communities. We then quantified functional (space occupancy and biomass) and compositional recovery from these repeated pulse disturbances across two community assembly timescales (early and late at 3 and 12 months, respectively). We documented latitudinal variation in resilience across 47° latitude, where speed of functional recovery was higher toward lower latitudes yet incomplete at late assembly in the tropics and subtropics. The degree of functional recovery did not coincide with compositional recovery, and regional differences in recruitment and growth likely contributed to functional recovery in these communities. While biogeographic variation in community resilience has been predicted, our results are among the first to examine functional and compositional recovery from disturbance in a single large-scale standardized experiment.

Saccharomycotina yeasts defy long-standing macroecological patterns.

The Saccharomycotina yeasts ("yeasts" hereafter) are a fungal clade of scientific, economic, and medical significance. Yeasts are highly ecologically diverse, found across a broad range of environments in every biome and continent on earth; however, little is known about what rules govern the macroecology of yeast species and their range limits in the wild. Here, we trained machine learning models on 12,816 terrestrial occurrence records and 96 environmental variables to infer global distribution maps at ~1 km2 resolution for 186 yeast species (~15% of described species from 75% of orders) and to test environmental drivers of yeast biogeography and macroecology. We found that predicted yeast diversity hotspots occur in mixed montane forests in temperate climates. Diversity in vegetation type and topography were some of the greatest predictors of yeast species richness, suggesting that microhabitats and environmental clines are key to yeast diversity. We further found that range limits in yeasts are significantly influenced by carbon niche breadth and range overlap with other yeast species, with carbon specialists and species in high-diversity environments exhibiting reduced geographic ranges. Finally, yeasts contravene many long-standing macroecological principles, including the latitudinal diversity gradient, temperature-dependent species richness, and a positive relationship between latitude and range size (Rapoport's rule). These results unveil how the environment governs the global diversity and distribution of species in the yeast subphylum. These high-resolution models of yeast species distributions will facilitate the prediction of economically relevant and emerging pathogenic species under current and future climate scenarios.

Body size and trophic structure explain global asymmetric response of tetrapod diversity to climate effects.

Although climate-based hypotheses are widely used to explain large-scale diversity patterns, they fall short of explaining the spatial variation among taxonomic groups. Integrating food web and metabolic theories into macroecology is a promising step forward, as they allow including explicit taxon-specific traits that can potentially mediate the relationship between climate and diversity. Our investigation focuses on the role of body size and trophic structure in mediating the influence of contemporary climate and historical climate change on global tetrapods species richness. We used piecewise structural equation modeling to assess the direct effects of contemporary climate and climate instability of species richness and the indirect effects of climate on tetrapod richness mediated by community-wide species traits. We found that birds and mammals are less sensitive to the direct effect of contemporary climate than amphibians and squamates. Contemporary climate and climate instability favored the species richness of mammals and amphibians. However, for birds and squamates, this link is only associated with contemporary climate. Moreover, we showed that community-wide traits are correlated with species richness gradients. However, we highlight that this relationship is dependent upon the specific traits and taxonomic groups. Specifically, bird communities with smaller bodies and bottom-heavy structures support higher species richness. Squamates also tend to be more diverse in communities with prevalence of smaller bodies, while mammals are correlated with top-heavy structures. Moreover, we showed that higher contemporary climate and climate instability reduce the species richness of birds and mammals through community-wide traits and indirectly increase squamate species richness. We also showed that body size and trophic structure are driving a global asymmetric response of tetrapod diversity to climate effects, which highlights the limitation to use the "typical" climate-based hypotheses. Furthermore, by combining multiple theories, our research contributes to a more realistic and mechanistic understanding of diversity patterns across taxonomic groups.

Mean reef fish body size decreases towards warmer waters.

Aquatic ectotherms often attain smaller body sizes at higher temperatures. By analysing ~15,000 coastal-reef fish surveys across a 15°C spatial sea surface temperature (SST) gradient, we found that the mean length of fish in communities decreased by ~5% for each 1°C temperature increase across space, or 50% decrease in mean length from 14 to 29°C mean annual SST. Community mean body size change was driven by differential temperature responses within trophic groups and temperature-driven change in their relative abundance. Herbivores, invertivores and planktivores became smaller on average in warmer temperatures, but no trend was found in piscivores. Nearly 25% of the temperature-related community mean size trend was attributable to trophic composition at the warmest sites, but at colder temperatures, this was <1% due to trophic groups being similarly sized. Our findings suggest that small changes in temperature are associated with large changes in fish community composition and body sizes, with important ecological implications.

A gentle introduction to computer vision-based specimen classification in ecological datasets.

Classifying specimens is a critical component of ecological research, biodiversity monitoring and conservation. However, manual classification can be prohibitively time-consuming and expensive, limiting how much data a project can afford to process. Computer vision, a form of machine learning, can help overcome these problems by rapidly, automatically and accurately classifying images of specimens. Given the diversity of animal species and contexts in which images are captured, there is no universal classifier for all species and use cases. As such, ecologists often need to train their own models. While numerous software programs exist to support this process, ecologists need a fundamental understanding of how computer vision works to select appropriate model workflows based on their specific use case, data types, computing resources and desired performance capabilities. Ecologists may also face characteristic quirks of ecological datasets, such as long-tail distributions, 'unknown' species, similarity between species and polymorphism within species, which impact the efficacy of computer vision. Despite growing interest in computer vision for ecology, there are few resources available to help ecologists face the challenges they are likely to encounter. Here, we present a gentle introduction for species classification using computer vision. In this manuscript and associated GitHub repository, we demonstrate how to prepare training data, basic model training procedures, and methods for model evaluation and selection. Throughout, we explore specific considerations ecologists should make when training classification models, such as data domains, feature extractors and class imbalances. With these basics, ecologists can adjust their workflows to achieve research goals and/or account for uncertainty in downstream analysis. Our goal is to provide guidance for ecologists for getting started in or improving their use of machine learning for visual classification tasks.

Investigating macroecological patterns in coarse-grained microbial communities using the stochastic logistic model of growth.

The structure and diversity of microbial communities are intrinsically hierarchical due to the shared evolutionary history of their constituents. This history is typically captured through taxonomic assignment and phylogenetic reconstruction, sources of information that are frequently used to group microbes into higher levels of organization in experimental and natural communities. Connecting community diversity to the joint ecological dynamics of the abundances of these groups is a central problem of community ecology. However, how microbial diversity depends on the scale of observation at which groups are defined has never been systematically examined. Here, we used a macroecological approach to quantitatively characterize the structure and diversity of microbial communities among disparate environments across taxonomic and phylogenetic scales. We found that measures of biodiversity at a given scale can be consistently predicted using a minimal model of ecology, the Stochastic Logistic Model of growth (SLM). This result suggests that the SLM is a more appropriate null-model for microbial biodiversity than alternatives such as the Unified Neutral Theory of Biodiversity. Extending these within-scale results, we examined the relationship between measures of biodiversity calculated at different scales (e.g. genus vs. family), an empirical pattern previously evaluated in the context of the Diversity Begets Diversity (DBD) hypothesis (Madi et al., 2020). We found that the relationship between richness estimates at different scales can be quantitatively predicted assuming independence among community members, demonstrating that the DBD can be sufficiently explained using the SLM as a null model of ecology. Contrastingly, only by including correlations between the abundances of community members (e.g. as the consequence of interactions) can we predict the relationship between estimates of diversity at different scales. The results of this study characterize novel microbial patterns across scales of organization and establish a sharp demarcation between recently proposed macroecological patterns that are not and are affected by ecological interactions.

The role of abiotic and biotic factors in the unequal body shape diversification of a Gondwanan fish radiation (Otophysi: Characiformes).

Understanding why some clades diversify greatly while others do not is a major goal of evolutionary biology. Both abiotic and biotic factors are important in driving unequal morphological diversity across the tree of life. However, few studies have quantified how abiotic habitat and community composition differences influence unequal morphological diversification in spatiotemporally diffuse radiations. We use geometric morphometrics, abiotic habitat data generated by Geographic Information Systems (GIS) analyses, evolutionary simulations, and phylogenetic comparative methods to determine whether random evolution, habitat variation, competition for niches, or a combination of factors influenced the unequal body shape diversity of a Gondwanan freshwater fish radiation. We find that Neotropical characiform lineages, which exhibit substantially more body shape diversity than their African counterparts, occupy significantly more slope and elevation habitats than African lineages. Differences in habitat occupation between the continental radiations occur through a combination of likely competition with cypriniform fishes in Africa restricting access to higher slope and elevation habitats and significantly more low-elevation and slope habitats available in the Neotropics. Our findings suggest that spatiotemporally widespread radiations, like Characiformes, do not diversify across homogenized habitats and biotic assemblages, with differences in community structure and physical habitat playing an important role in driving unequal morphological diversification.

Novel community data in ecology-properties and prospects.

New technologies for monitoring biodiversity such as environmental (e)DNA, passive acoustic monitoring, and optical sensors promise to generate automated spatiotemporal community observations at unprecedented scales and resolutions. Here, we introduce 'novel community data' as an umbrella term for these data. We review the emerging field around novel community data, focusing on new ecological questions that could be addressed; the analytical tools available or needed to make best use of these data; and the potential implications of these developments for policy and conservation. We conclude that novel community data offer many opportunities to advance our understanding of fundamental ecological processes, including community assembly, biotic interactions, micro- and macroevolution, and overall ecosystem functioning.