Nutritional Dimensions of Invasive Success

Abstract

Despite mounting calls for predictive ecological approaches rooted in physiological performance currencies, the field of invasive species biology has lagged behind. For instance, successful invaders are often predicted to consume diverse foods, but the nutritional complexity of foods often leaves food-level analyses short of physiological mechanisms. The emerging field of nutritional geometry (NG) provides new theory and empirical tools to predict invasive potential based on fundamental and realized nutritional niches. We review recent advances and synthesize NG predictions about behavioral traits that favor invasive establishment, and evolutionary dynamics that promote invasive spread. We also provide practical advice for applying NG approaches, and discuss the power of nutrition to achieve a more predictive invasion biology that explicitly integrates physiological mechanisms. Moving from Food-Level to Nutrient-Level Predictions about Invasive Potential HighlightsSpecies invasions represent a global threat to biodiversity.

Nutritional niches reveal fundamental domestication trade-offs in fungus-farming ants

“…Given these historical domestication patterns, we hypothesized that: 1) ant farmers have solved a tradeoff between crop yield and cultivar vulnerability, and 2) this tradeoff hinges upon nutrient availability as the core commodity of crop provisioning and yield. We used the well-established nutritional geometry approach to test this hypothesis, capitalizing on its conceptual and empirical tools for visualizing and modelling tradeoffs that organisms navigate to maintain nutritional homeostasis 26 – 29 . Our present study builds on an earlier one in which we used nutritional geometry to quantify a related type of nutritional tradeoff in the ant Mycocepurus smithii , a representative of the paleoattine clade that is sister to the neoattines that evolved more organizationally-complex farming systems.…”

“…We tested the domestication tradeoff between yield and vulnerability by performing a study with the following three objectives: 1) To quantify and visualize the breadth of fundamental nutrient niches (FNNs) 29 , 31 when fungal cultivars are grown in vitro across artificial nutritional landscapes varying in absolute and relative abundance of protein and carbohydrate macronutrients ( Fig. 1b ).…”

The multidimensional nutritional niche of fungus-cultivar provisioning in free-ranging colonies of a neotropical leafcutter ant

“…Second, the leaf RNN spanned broader total macronutrient concentrations (5% to 50%) and tended to have more protein than flowers or fruits (Figure 4B-C). Leaves were also the dominant substrate type and thus governed each colony’s overall intake target, defined as the nutritional blend selected by a colony that in principle maximizes the cultivar’s performance, and against which surplus or deficient intake can be inferred (4, 5, 8). As a result, the intake target selected by ant foragers was biased towards protein levels that were beyond the cultivar’s FNN for maximal hyphal growth (Figure 4C, Figure S7), but near the protein-biased RNN for maximal staphyla density (Figure 4D, Figure S8).…”

The geometry of resource constraint: An empirical study of the golden snub‐nosed monkey

“…Several studies have attempted to incorporate nutritional geometry into ecological theory and its application. These include examinations of constraints on food webs (Raubenheimer et al., 2009; Wilder et al., 2013), trait‐based models of community structure (Simpson et al, 2010), niche theory (Behmer & Joern, 2008; Kearney et al., 2010; Machovsky‐Capuska, Senior, et al, 2016), conservation ecology (Birnie‐Gauvin et al., 2017; Raubenheimer & Simpson, 2006; Raubenheimer et al., 2012), invasion ecology (Krabbe et al., 2019; Shik & Dussutour, 2020), foraging theory (Bressendorff & Toft, 2011; Raubenheimer & Simpson, 2018), urban ecology (Coogan et al., 2018) and models predicting human–wildlife conflict (Coogan & Raubenheimer, 2016). A recent modelling study demonstrated that explicitly distinguishing resource quantity and quality in a multi‐dimensional context can yield counter‐intuitive insights.…”