raits, broadly speaking, are measurable attributes or characteristics of organisms. Traits related to function (for example, leaf size, body mass, tooth size or growth form) are often used to understand how organisms interact with their environment and other species via key vital rates such as survival, development and reproduction 1-5. Trait-based approaches have long been used in systematics and macroevolution to delineate taxa and reconstruct ancestral morphology and function 6-8 and to link candidate genes to phentoypes 9-11. The broad appeal of the trait concept is its ability to facilitate quantitative comparisons of biological form and function. Traits also allow us to mechanistically link organismal responses to abiotic and biotic factors with measurements that are, in principle, relatively easy to capture across large numbers of individuals. For example, appropriately chosen and defined traits can help identify lineages that share similar life-history strategies for a given environmental regime 12,13. Documenting and understanding the diversity and composition of traits in ecosystems directly contributes to our understanding of organismal and ecosystem processes, functionality, productivity and resilience in the face of environmental change 14-19. In light of the multiple applications of trait data to address challenges of global significance (Box 1), a central question remains: How can we most effectively advance the synthesis of trait data within and across disciplines? In recent decades, the collection, compilation and availability of trait data for a variety of organisms has accelerated rapidly. Substantial trait databases now exist for plants 20-23 , reptiles 24,25 , invertebrates 23,26-29 , fish 30,31 , corals 32 , birds 23,33,34 , amphibians 35 , mammals 23,36-38 and fungi 23,39 , and parallel efforts are no doubt underway for other taxa. Though considerable effort has been made to quantify traits for some groups (for example, Fig. 1), substantial work remains. To develop and test theory in biodiversity science, much greater effort is needed to fill in trait data across the Tree of Life by combining and integrating data and trait collection efforts.

As the single opportunity for plants to move, seed dispersal has an important impact on plant fitness, species distributions and patterns of biodiversity. However, models that predict dynamics such as risk of extinction, range shifts and biodiversity loss tend to rely on the mean value of parameters and rarely incorporate realistic dispersal mechanisms. By focusing on the mean population value, variation among individuals or variability caused by complex spatial and temporal dynamics is ignored. This calls for increased efforts to understand individual variation in dispersal and integrate it more explicitly into population and community models involving dispersal. However, the sources, magnitude and outcomes of intraspecific variation in dispersal are poorly characterized, limiting our understanding of the role of dispersal in mediating the dynamics of communities and their response to global change. In this manuscript, we synthesize recent research that examines the sources of individual variation in dispersal and emphasize its implications for plant fitness, populations and communities. We argue that this intraspecific variation in seed dispersal does not simply add noise to systems, but, in fact, alters dispersal processes and patterns with consequences for demography, communities, evolution and response to anthropogenic changes. We conclude with recommendations for moving this field of research forward.

There is growing realization that intraspecific variation in seed dispersal can have important ecological and evolutionary consequences. However, we do not have a good understanding of the drivers or causes of intraspecific variation in dispersal, how strong an effect these drivers have, and how widespread they are across dispersal modes. As a first step to developing a better understanding, we present a broad, but not exhaustive, review of what is known about the drivers of intraspecific variation in seed dispersal, and what remains uncertain. We start by decomposing ‘drivers of intraspecific variation in seed dispersal’ into intrinsic drivers (i.e. variation in traits of individual plants) and extrinsic drivers (i.e. variation in ecological context). For intrinsic traits, we further decompose intraspecific variation into variation among individuals and variation of trait values within individuals. We then review our understanding of the major intrinsic and extrinsic drivers of intraspecific variation in seed dispersal, with an emphasis on variation among individuals. Crop size is the best-supported and best-understood intrinsic driver of variation across dispersal modes; overall, more seeds are dispersed as more seeds are produced, even in cases where per seed dispersal rates decline. Fruit/seed size is the second most widely studied intrinsic driver, and is also relevant to a broad range of seed dispersal modes. Remaining intrinsic drivers are poorly understood, and range from effects that are probably widespread, such as plant height, to drivers that are most likely sporadic, such as fruit or seed colour polymorphism. Primary extrinsic drivers of variation in seed dispersal include local environmental conditions and habitat structure. Finally, we present a selection of outstanding questions as a starting point to advance our understanding of individual variation in seed dispersal.

Many plants rely on animal mutualists for reproduction. Quantifying how animal mutualists impact plant performance provides a foundation for modelling how change in animal communities affects the composition and functioning of plant communities. We performed a meta-analysis of 2539 experiments, 6 times more than the last comprehensive meta-analysis, examining how gut passage by frugivores influences seed germination. We simultaneously analyzed multiple predictor variables related to study methodology, location, and frugivore identity to disentangle methodological from ecological impacts on effect sizes. We found that gut passage by birds, fish, reptiles, bats, primates, and other mammals on average increased seed germination, but that the magnitude varied across vertebrate groups. The positive effects of gut passage were largely explained by the de-inhibitory effects of pulp removal rather than by the scarification of seed tissues. Some previous studies and meta-analyses that found no effect of gut passage only tested scarification or did not distinguish between these tests of scarification and pulp removal. We found that, for a typical fleshy-fruited plant species, the lack of gut passage reduces germination by 60%. From an evolutionary perspective, this indicates a large risk associated with reliance on animal mutualists that is balanced against the benefits of animal-mediated seed dispersal. From a conservation perspective, this highlights the potential for large demographic consequences of frugivore declines on plant populations. Our database and findings advance quantitative predictions for the role of fruit-frugivore interactions in shaping plant communities in the Anthropocene.

Synthesising trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Despite the well-recognised importance of traits for addressing ecological and evolutionary questions, trait-based approaches still struggle with several basic data requirements to deliver openly accessible, reproducible, and transparent science. Here, we introduce the Open Traits Network (OTN) – a decentralised alliance of international researchers and institutions focused on collaborative integration and standardisation of the exponentially increasing availability of trait data across all organisms. The OTN embraces the use of Open Science principles in trait research, particularly open data, open source, and open methodology protocols and workflows, to accelerate the synthesis of trait data across the Tree of Life. Increased efforts at all levels – from individual scientists, research networks, scientific societies, funding agencies, to publishers – are necessary to fully exploit the opportunities offered by Open Science in trait research. Democratising access to data, tools and resources will facilitate rapid advances in the biological sciences and our ability to address pressing environmental and societal demands.