| Literature DB >> 26240602 |
Emilie Snell-Rood1, Rickey Cothran2, Anne Espeset3, Punidan Jeyasingh4, Sarah Hobbie1, Nathan I Morehouse5.
Abstract
Variation in life-history traits can have major impacts on the ecological and evolutionary responses of populations to environmental change. Life-history variation often results from trade-offs that arise because individuals have a limited pool of resources to allocate among traits. However, human activities are increasing the availability of many once-limited resources, such as nitrogen and phosphorus, with potentially major implications for the expression and evolution of life-history trade-offs. In this review, we synthesize contemporary life history and sexual selection literature with current research on ecosystem nutrient cycling to highlight novel opportunities presented by anthropogenic environmental change for investigating life-history trait development and evolution. Specifically, we review four areas where nutrition plays a pivotal role in life-history evolution and explore possible implications in the face of rapid, human-induced change in nutrient availability. For example, increases in the availability of nutrients may relax historical life-history trade-offs and reduce the honesty of signaling systems. We argue that ecosystems experiencing anthropogenic nutrient inputs present a powerful yet underexplored arena for testing novel and longstanding questions in organismal life-history evolution.Entities:
Keywords: life-history traits; nitrogen; phosphorus; signals; trade-offs
Year: 2015 PMID: 26240602 PMCID: PMC4516417 DOI: 10.1111/eva.12272
Source DB: PubMed Journal: Evol Appl ISSN: 1752-4571 Impact factor: 5.183
Summary of questions and hypotheses about life-history evolution presented by anthropogenic nutrient change
| Questions about life-history traits and strategies |
| Why do species or populations vary in life-history traits? |
| H1: Anthropogenic changes in nutrients may allow some species or populations to allocate more to |
| Why do life-history trade-offs vary in intensity? |
| H2: Human-caused increases in nutrients over time and space may obscure trade-offs (while decreases in nutrients may make trade-offs more pronounced) |
| H3: Anthropogenic increases in one nutrient may result in a novel limiting nutrient that reveals new trade-offs and/or genetic variation |
| Why not invest maximally in a trait closely tied to fitness? |
| H4: Anthropogenic change in one nutrient may result in a novel nutrient limiting trait expression |
| H5: In high nutrient environments, relaxed selection on nutrient acquisition and/or assimilation may lead to lessened trait expression when anthropogenic nutrient increases are lessened |
| Why do species or populations vary in life-history |
| H6: For some nutrients, anthropogenic change will increase the spatial and temporal variability of nutrient availability, selecting for greater plasticity in response to that nutrient |
| Questions about sexual traits |
| Why does investment in sexual traits vary within and between species? |
| H7: Female choosiness may increase with nutrient status due to increased resources dedicated to choice and/or increased self-assessment of reproductive value by females |
| H8: Increasing nutrients may lead to increased population sizes/densities, which in turn can result in increased selection on traits involved in male-male competition |
| How do complex, honest signals evolve as part of the overall life-history strategy of an organism? |
| H9: Honesty of nutrient-limited sexual traits should decline with anthropogenic nutrient increases, potentially leading to relaxed selection on sexually selected traits and possibly individual quality |
| H10: As nutrient availability changes, selection shifts to favor novel signals linked to new resource limitations (signal diversification) |
| H11: As nutrient availability changes, selection favors increasing allocation to an existing signal (signal elaboration) |
| Questions about responses to rapid environmental change |
| Why might populations and species show different responses to rapid and novel anthropogenic environments? |
| H12: Increases in nutrient availability may allow some populations to allocate more to life-history traits that affect both survival (e.g. plasticity) and evolution (e.g. fecundity) in novel environments |
| H13: Changes in allele frequencies within populations may be driven by spatio-temporal nutrient variation that affects life-history traits independent of any other factors that vary across individuals |
| H14: Standing genetic variation in life-history responses to nutrition (G × E) may contribute to rapid evolutionary changes in nutrient acquisition, assimilation and allocation in novel nutrient environments |
| H15: Evolutionary processes such as population divergence may be sped up by anthropogenic increases in nutrients; alternatively, nutrient change may reduce divergence by introducing fluctuating selective regimes |
| H16: Ecological changes in community structure due to outcomes of competition in high nutrient environments may bias which species survive and diversify in high nutrient environments |
Figure 1Possible effects of changes in nutrient availability on nutrition at higher trophic levels. Nitrogen, phosphorus, calcium, and sodium from human activities are readily available to organisms. Changes in nutrient availability can affect both the nutritional quality and quantity of resources, because of individual-level responses to altered nutrient supply (e.g. increased growth or tissue nutrient concentrations) and changes in species composition (e.g. arising from variation in competitive ability for nutrients in resources). It is assumed that every species is adapted to some level of nutrients and performs poorly when nutrient levels are either so low they are limiting or so high they are toxic. As nutrient levels shift, competitive interactions among species result in altered community dynamics (Bobbink et al. 2010). These changes result in three possible changes in nutrition that can occur as a result of shifts in nutrient availability: (A) Altered resource quality because of changes in the amount of nutrients per individual, such as changes in leaf nutrient concentrations (moving up the red curve); (B) Altered resource quantity results in more nutrients per unit area, such as changes in biomass without accompanying changes in individual-level nutrients (moving up the blue curve prior to when nutrient levels increase to a stressful level); (C) Altered resource quality because of changes in community composition, such as change in the dominance of a higher quality resource (species B is of higher quality than A). Of course, in many cases, both the quality and quantity of nutrition can change.
Figure 2Operational definition of life-history traits. In this review, we adopt a broad definition of life-history traits as any trait tied to reproduction, survival or somatic maintenance. In the past, life-history traits have been traditionally defined as traits that compose the life table of a population—traits tied closely to fitness such as growth, body size, annual reproductive rates, and survival. In more recent decades, other traits closely tied to fitness have been argued to fall under the general umbrella of life-history traits. In particular, sexually selected traits can be thought of as an investment in reproductive effort and thus understanding their expression requires a life-history approach (Andersson 1994; Badyaev and Qvarnström 2002). In fact, the intimate relationship between sexually selected traits and life history was realized early in evolutionary ecology as an explanation for why the sexes differ in life-history traits (Orians 1969). Sexually selected traits are often expensive to build and maintain and may compete strongly with other life-history traits for resources (Ryan 1988; Balmford et al. 1993). This competition for shared resources can ultimately lead to trade-offs between investment in sexually selected traits and other life-history traits (Gustafsson et al. 1995; Kotiaho 2000). Therefore, these two types of traits are likely to be linked and both are expected to be sensitive to fluctuations in the resource environment. Similar arguments could be made for other traits closely tied to fitness such as brain size. In particular, the cognitive buffer hypothesis links brain size to survival in the face of environmental variation and complex decision making (Kaplan and Robson 2002; Sol 2009; Møller and Erritzoe 2014). This, combined with observations of trade-offs between brain size and other traits such as gut length or muscle mass (Isler and van Schaik 2006; Kotrschal et al. 2013), suggest that brains should also be considered a life-history trait. For the purposes of this review, life-history allocation refers to how an individual or genotype allocates limited resources to the entire set of life-history traits that determine their overall fitness.
Figure 3The influence of nutrition on life-history traits—Daphnia as an example. It seems almost a given that nutrient availability should affect life-history traits such as offspring number and life span, here illustrated by Daphnia, which feed on algae. Algal phosphorus (P) content often closely tracks inorganic P supply (Rhee 1973), although algal cells continue photosynthesis and become carbon (C) rich (Tillberg and Rowley 1989). Consequently, Daphnia inhabiting lakes with varying P supply experience contrasting diets in terms of both P and C (Sterner and Hessen 1994). Such variation has major consequences on key life-history traits of Daphnia. Specifically, compared to daphniids feeding on high P algae, those in low P grow slower, delay reproduction, reproduce at a smaller size, and produce smaller broods (e.g. Lurling and Van Donk 1997). Importantly, such life-history shifts are not only driven by P availability, but also due to excess C (Anderson et al. 2005). This figure shows results (mean ± SD) from Jeyasingh and Weider (2005) where <12 h-old clonal sisters of D. pulex were exposed to contrasting P supply conditions. The growth and fecundity penalties of low P after 10 days are quite apparent. Note that total amount of energy in both dietary treatments were the same (1 mg C L−1 day−1). While variable nutrition clearly affects the expression of life-history traits in Daphnia, the effects of nutrition may vary with the specific nutrients considered, sex- and developmental stage-specific responses to changes in nutrients, and differences across genotypes in nutrient acquisition ability. Furthermore, nutrient variation may differentially influence generalists versus specialists and active foragers versus passive feeders.
Figure 4How anthropogenic nutrient increase may obscure underlying trade-offs. (A) In this landscape, runoff from a field with high fertilizer application (nitrogen, phosphorus, and potassium inputs) enters the watershed. Imagine genotypes of an aquatic species (circles) sampled across this region: those downstream of the source (in black) may be heavily affected, while those upstream of the source may be less affected (light gray). (B) Variation in nutrient inputs across this landscape may result in a positive correlation between life-history traits (dotted line) because some genotypes have greater overall nutrition (black), even if there is an underlying trade-off within each resource level (solid lines).
Figure 5Routes by which nutrition may affect life-history trade-offs. Variation in life-history traits (phenotypes, ‘P’) can come through variation in resource availability (the environment, ‘E’), genetic variation in resource acquisition (‘GAQ’), which both influence an individual’s condition (‘C’) or genetic variation in how resources are allocated across life-history traits (‘GAL’). Variation in resource availability or acquisition can generate positive life-history trait correlations across genotypes even when there are underlying trade-offs across traits—in other words, higher condition individuals can simply allocate more resources to all traits such as survival (‘S’), reproduction (‘R’), or ornamentation (‘O’). When variation in acquisition is higher than variation in allocation, position relationships will be seen; when variation in acquisition is less than variance in allocation, negative relationships will be seen. Figure modified from (Rowe and Houle 1996; Morehouse 2014).