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Abstract Islands make up a large proportion of Earth's biodiversity, yet are also some of the most sensitive systems to environmental perturbation. Biogeographic theory predicts that geologic age, area, and isolation typically drive islands' diversity patterns, and thus potentially impact non‐native spread and community homogenization across island systems. One limitation in testing such predictions has been the difficulty of performing comprehensive inventories of island biotas and distinguishing native from introduced taxa. Here, we use DNA metabarcoding and statistical modelling as a high throughput method to survey community‐wide arthropod richness, the proportion of native and non‐native species, and the incursion of non‐natives into primary habitats on three archipelagos in the Pacific – the Ryukyus, the Marianas and Hawaii – which vary in age, isolation and area. Diversity patterns largely match expectations based on island biogeography theory, with the oldest and most geographically connected archipelago, the Ryukyus, showing the highest taxonomic richness and lowest proportion of introduced species. Moreover, we find evidence that forest habitats are more resilient to incursions of non‐natives in the Ryukyus than in the less taxonomically rich archipelagos. Surprisingly, we do not find evidence for biotic homogenization across these three archipelagos: the assemblage of non‐native species on each island is highly distinct. Our study demonstrates the potential of DNA metabarcoding to facilitate rapid estimation of biogeographic patterns, the spread of non‐native species, and the resilience of ecosystems. 

ABSTRACT Genetic technologies such as DNA barcoding make it easier and less expensive to monitor biodiversity and its associated ecosystem services, particularly in biodiversity hotspots where traditional assessments are challenging. Successful use of these data‐driven technologies, however, requires access to appropriate reference data. We reviewed the >373,584 reference plant DNA barcodes in public repositories and found that they cumulatively cover a remarkable quarter of the ~435,000 extant land plant species (Embryophyta). Nevertheless, coverage gaps in tropical biodiversity hotspots reflect well‐documented biases in biodiversity science – most reference specimens originated in the Global North. Currently, at least 17% of plant families lack any reference barcode data whatsoever, affecting tropical and temperate regions alike. Investigators often emphasise the importance of marker choice and the need to ensure protocols are technically capable of detecting and identifying a broad range of taxa. Yet persistent geographic and taxonomic gaps in the reference datasets show that these protocols rely upon risk undermining all downstream applications of the strategy, ranging from basic biodiversity monitoring to policy‐relevant objectives – such as the forensic authentication of materials in illegal trade. Future networks of investigators could work strategically to improve data coverage, which will be essential in global efforts to conserve biodiversity while advancing more fair and equitable access to benefits arising from genetic resources. 

Abstract BackgroundMacArthur and Wilson's theory of island biogeography has been a foundation for obtaining testable predictions from models of community assembly and for developing models that integrate across scales and disciplines. Historically, however, these developments have focused on integration across ecological and macroevolutionary scales and on predicting patterns of species richness, abundance distributions, trait data and/or phylogenies. The distribution of genetic variation across species within a community is an emerging pattern that contains signatures of past population histories, which might provide an historical lens for the study of contemporary communities. As intraspecific genetic diversity data become increasingly available at the scale of entire communities, there is an opportunity to integrate microevolutionary processes into our models, moving towards development of a genetic theory of island biogeography. Motivation/goalWe aim to promote the development of process‐based biodiversity models that predict community genetic diversity patterns together with other community‐scale patterns. To this end, we review models of ecological, microevolutionary and macroevolutionary processes that are best suited to the creation of unified models, and the patterns that these predict. We then discuss ongoing and potential future efforts to unify models operating at different organizational levels, with the goal of predicting multidimensional community‐scale data including a genetic component. Main conclusionsOur review of the literature shows that despite recent efforts, further methodological developments are needed, not only to incorporate the genetic component into existing island biogeography models, but also to unify processes across scales of biological organization. To catalyse these developments, we outline two potential ways forward, adopting either a top‐down or a bottom‐up approach. Finally, we highlight key ecological and evolutionary questions that might be addressed by unified models including a genetic component and establish hypotheses about how processes across scales might impact patterns of community genetic diversity. 

Abstract Despite the importance of seed dispersal as a driving process behind plant community assembly, our understanding of the role of seed dispersal in plant population persistence and spread remains incomplete. As a result, our ability to predict the effects of global change on plant populations is hampered. We need to better understand the fundamental link between seed dispersal and population dynamics in order to make predictive generalizations across species and systems, to better understand plant community structure and function, and to make appropriate conservation and management responses related to seed dispersal. To tackle these important knowledge gaps, we established the CoDisperse Network and convened an interdisciplinary, NSF-sponsored Seed Dispersal Workshop in 2016, during which we explored the role of seed dispersal in plant population dynamics (NSF DEB Award # 1548194). In this Special Issue, we consider the current state of seed dispersal ecology and identify the following collaborative research needs: (i) the development of a mechanistic understanding of the movement process influencing dispersal of seeds; (ii) improved quantification of the relative influence of seed dispersal on plant fitness compared to processes occurring at other life history stages; (iii) an ability to scale from individual plants to ecosystems to quantify the influence of dispersal on ecosystem function; and (iv) the incorporation of seed dispersal ecology into conservation and management strategies. 

Abstract The distribution and abundance of plants across the world depends in part on their ability to move, which is commonly characterized by a dispersal kernel. For seeds, the total dispersal kernel (TDK) describes the combined influence of all primary, secondary and higher-order dispersal vectors on the overall dispersal kernel for a plant individual, population, species or community. Understanding the role of each vector within the TDK, and their combined influence on the TDK, is critically important for being able to predict plant responses to a changing biotic or abiotic environment. In addition, fully characterizing the TDK by including all vectors may affect predictions of population spread. Here, we review existing research on the TDK and discuss advances in empirical, conceptual modelling and statistical approaches that will facilitate broader application. The concept is simple, but few examples of well-characterized TDKs exist. We find that significant empirical challenges exist, as many studies do not account for all dispersal vectors (e.g. gravity, higher-order dispersal vectors), inadequately measure or estimate long-distance dispersal resulting from multiple vectors and/or neglect spatial heterogeneity and context dependence. Existing mathematical and conceptual modelling approaches and statistical methods allow fitting individual dispersal kernels and combining them to form a TDK; these will perform best if robust prior information is available. We recommend a modelling cycle to parameterize TDKs, where empirical data inform models, which in turn inform additional data collection. Finally, we recommend that the TDK concept be extended to account for not only where seeds land, but also how that location affects the likelihood of establishing and producing a reproductive adult, i.e. the total effective dispersal kernel. 

Abstract 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.