Biological invasions are a key component of global change, and understanding the drivers of global invasion patterns will aid in assessing and mitigating the impact of invasive species. While invasive species are most often studied in the context of one or two trophic levels, in reality species invade communities comprised of complex food webs. The complexity and integrity of the native food web may be a more important determinant of invasion success than the strength of interactions between a small subset of species within a larger food web. Previous efforts to understand the relationship between food web properties and species invasions have been primarily theoretical and have yielded mixed results. Here, we present a synthesis of empirical information on food web connectance and species invasion success gathered from different sources (estimates of food web connectance from the primary literature and estimates of invasion success from the Global Invasive Species Database as well as the primary literature). Our results suggest that higher-connectance food webs tend to host fewer invaders and exert stronger biotic resistance compared to low-connectance webs. We argue that while these correlations cannot be used to infer a causal link between food web connectance and habitat invasibility, the promising findings beg for further empirical research that deliberately tests for relationships between food web connectance and invasion.

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Decades of theory and scholarship on the concept of human well‐being have informed a proliferation of approaches to assess well‐being and support public policy aimed at sustainability and improving quality of life. Human well‐being is multidimensional, and well‐being emerges when the dimensions and interrelationships interact as a system. In this paper, we illuminate two crucial components of well‐being that are often excluded from policy because of their relative difficulty to measure and manage: equity and interrelationships between humans and the environment. We use a mixed‐methods approach to review and summarize progress to date in developing well‐being constructs (including frameworks and methods) that address these two components. Well‐being frameworks that do not consider the environment, or interrelationships between people and their environment, are not truly measuring well‐being in all its dimensions. Use of equity lenses to assess well‐being frameworks aligns with increasing efforts to more holistically characterize well‐being and to guide sustainability management in ethical and equitable ways. Based on the findings of our review, we identify several pathways forward for the development and implementation of well‐being frameworks that can inform efforts to leverage well‐being for public policy.

Estimates of species' ranges can inform many aspects of biodiversity research and conservationmanagement decisions. Many practical applications need high-precision range estimates that are sufficiently reliable to use as input data in downstream applications. One solution has involved expert-generated maps that reflect on-the-ground field information and implicitly capture various processes that may limit a species' geographic distribution. However, expert maps are often subjective and rarely reproducible. In contrast, species distribution models (SDMs) typically have finer resolution and are reproducible because of explicit links to data. Yet, SDMs can have higher uncertainty when data are sparse, which is an issue for most species. Also, SDMs often capture only a subset of the factors that determine species distributions (e.g., climate) and hence can require significant post-processing to better estimate species' current realized distributions. Here, we demonstrate how expert knowledge, diverse data types, and SDMs can be used together in a transparent and reproducible modeling workflow. Specifically, we show how expert knowledge regarding species' habitat use, elevation, biotic interactions, and environmental tolerances can be used to make and refine range estimates using SDMs and various data sources, including high-resolution remotely sensed products. This range-refinement approach is primed to use various data sources, including many with continuously improving spatial or temporal resolution. To facilitate such analyses, we compile a comprehensive suite of tools in a new R package, maskRangeR, and provide worked examples. These tools can facilitate a wide variety of basic and applied research that requires high-resolution maps of species' current ranges, including quantifications of biodiversity and its change over time.

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