A trophic interaction framework for identifying the invasive capacity of novel organisms

1. The likelihood and impacts of invasions by novel organisms (e.g. non-native species, genetically modified organisms) on the composition and functioning of receiving biological communities hinges on their capacity to exploit resources and/or avoid predation relative to resident counterparts. While assessment of invasion risk based on the comparison of functional responses (per-capita consumption rate as a function of resource density) of novel species with native analogues has been gaining popularity, it may be undermined if alternative prey and potential predators are not represented realistically. 2. Here, we propose a conceptual framework that enables rigorous identification of trophic traits conducive to invasion success by novel organisms—irrespective of their trophic position—and their likely ecological impacts, given their arrival and establishment. We focus on consumption here, but our framework can also be used for autotrophic energy acquisition, and extended to non-trophic and indirect interactions. 3. The framework enables a structured and prioritized selection of subsets of trophic links for invasion risk assessment. It is based on foraging theory and advances in comparative functional responses in invasion ecology. It can even be used in the absence of a resident comparator organism and when resources or predators are only partly known. 4. Our approach enhances the predictive power of species screening, and thus advances prevention and management of invasions under a common framework for all types of novel organisms

Remote detection of invasive alien species

The spread of invasive alien species (IAS) is recognized as the most severe threat to biodiversity outside of climate change and anthropogenic habitat destruction. IAS negatively impact ecosystems, local economies, and residents. They are especially problematic because once established, they give rise to positive feedbacks, increasing the likelihood of further invasions and spread. The integration of remote sensing (RS) to the study of invasion, in addition to contributing to our understanding of invasion processes and impacts to biodiversity, has enabled managers to monitor invasions and predict the spread of IAS, thus supporting biodiversity conservation and management action. This chapter focuses on RS capabilities to detect and monitor invasive plant species across terrestrial, riparian, aquatic, and human-modified ecosystems. All of these environments have unique species assemblages and their own optimal methodology for effective detection and mapping, which we discuss in detail