Island biogeography remains a popular topic in ecology and has gained renewed interest due to recent theoretical development. As experimental investigation of the theory is difficult to carry out, mechanistic simulation models provide useful alternatives. Several eco-evolutionary mechanisms have been identified to affect island biodiversity, but integrating more than a few of these processes into models remains a challenge. To get an overview of what processes mechanistic island models have integrated so far and what conclusions they came to, we conducted an exhaustive literature review of studies featuring island-specific mechanistic models. This was done using an extensive systematic literature search with subsequent manual filtering. We obtained a list of 28 studies containing mechanistic island models, out of 647 total hits. Mechanistic island models differ greatly in their integrated processes and computational structure. Their individual findings range from theoretical (such as humped-shaped extinction rates for oceanic islands) to system-specific dynamics (e.g., equilibrium and non-equilibrium dynamics for Galápagos' birds). However, most models so far only integrate theories and processes pair-wise, while focusing on hypothetical systems. Trophic interactions and explicit micro-evolution are largely underrepresented in models. We expect future models to continue integrating processes, thus promoting the full appraisal of biodiversity dynamics.

The response of populations and species to changing conditions determines how community composition will change functionally, including via trait shifts. Selection from standing variation has been suggested to be more efficient than acquiring new mutations. Yet, studies on community trait composition and trait selection largely focus on phenotypic variation in ecological traits, whereas the underlying genomic traits remain understudied. Using a genome‐explicit, niche‐ and individual‐based model, we address the potential interactions between genomic and ecological traits shaping communities under an environmental selective forcing, namely temporal positively autocorrelated environmental fluctuation. In this model, all ecological traits are explicitly coded by the genome. For our experiments, we initialized 90 replicate communities, each with ca 350 initial species, characterized by random genomic and ecological trait combinations, on a 2D spatially explicit landscape with two orthogonal gradients (temperature and resource use). We exposed each community to two contrasting scenarios: without (i.e. static environments) and with temporal variation. We then analyzed emerging compositions of both genomic and ecological traits at the community, population and genomic levels. Communities in variable environments were species poorer than in static environments, and populations more abundant, whereas genomes had lower genetic linkage, mean genetic variation and a non‐significant tendency towards higher numbers of genes. The surviving genomes (i.e. those selected by variable environments) coded for enhanced environmental tolerance and smaller biomass, which resulted in faster life cycles and thus also in increased potential for evolutionary rescue. Under temporal environmental variation, larger, less linked genomes retained more variation in mean dispersal ability at the population level than at genomic level, whereas the opposite trend emerged for biomass. Our results provide clues to how sexually‐reproducing diploid plant communities might react to variable environments and highlights the importance of genomic traits and their interaction with ecological traits for eco‐evolutionary responses to changing climates.

Species invasions are highly complex phenomena, influenced by several interacting factors, such as species traits, disturbance, or evolutionary history (Enders et al., 2020;Theoharides & Dukes, 2007). Gaining an understanding of these factors is necessary to understand the whole invasion process (Fleming & Dibble, 2015) and establish effective countermeasures (Novoa et al., 2020). Yet, the relative importance of various factors is difficult to derive from studies focusing only on single invasion events (Catford et al., 2009). Considering the impending global change scenarios and increased rate of biotic exchange, however, generalizable findings about biological invasions are still urgently needed (van Kleunen et al., 2015).

The study of island systems has provided the basis of much of what we understand about a number of biogeographic patterns. However, islands have also suffered numerous extinctions as a result of human activities. The extent to which these extinctions have influenced the many different patterns we study as island biogeographers, and thus what we consider to be “natural”, is largely unknown. Here, we use a simulation approach to illustrate the impacts of anthropogenic extinctions on various macroecological and biogeographical patterns on islands. We simulated an archipelago consisting of five islands and filled these islands with a realistic set of species, each possessing four functional traits. Using this dataset, we then calculated a number of biogeographic patterns, including the slope of the island species–area relationship, functional richness and beta‐diversity (taxonomic and functional). The next stage of the simulation modeled the colonization of the archipelago by humans, represented by a 50% reduction in the carrying capacity of the archipelago and by an associated wave of species extinctions. When the extinction simulation process was finished, the various metrics were re‐calculated. The results illustrate that all the analyzed patterns are affected to some degree by the human‐induced loss of species. Overall, our results highlight how the extinction of species as a consequence of human actions on islands can influence our interpretation of “natural” island biogeography patterns.

1The reaction of species to changing conditions determines how community com-2 position will change functionally -not only by (temporal) species turnover, 3 but also by trait shifts within species. For the latter, selection from standing 4 variation has been suggested to be more efficient than acquiring new mutations. 5 Yet, studies on community trait composition and trait selection largely focus on 6 phenotypic variation in ecological traits, whereas the underlying genomic traits 7 remain relatively understudied despite evidence of their role to standing varia-8 tion. Using a genome-explicit, niche-and individual-based model, we address 9 Keywords 32 standing variation, genomic traits, environmental variability, mechanistic model, 33 rapid evolution, eco-evolutionary feedbacks 34 203