Large size and high light do not lower the cost of reproduction for the Neotropical herb Goeppertia marantifolia.

UNLABELLED: • PREMISE OF THE STUDY: Sexual reproduction is often associated with a cost in terms of reduced survival, growth, or future reproduction. It has been proposed that plant size and the environment (availability of key resources) can sometimes lower or even nullify the cost of reproduction.• METHODS: We address this issue experimentally with the Neotropical herb Goeppertia marantifolia, by manipulating sexual reproductive effort and measuring the demographic performance of plants and of their clonal offspring, in the context of natural variation in light availability.• KEY RESULTS: Plants in the high-reproductive-effort treatment grew less between seasons but did not differ in their probability of flowering the second season or in inflorescence size compared with plants in the low-effort treatment. Reproductive effort of parent plants influenced the leaf area of their clonal offspring. Plants that invested less in sexual reproduction produced clonal offspring that were initially larger than those produced by plants that invested more in reproduction. The magnitude of this effect was greater in parent plants that received two seasons of the manipulated reproductive effort than in those that received a single season. The trade-off between reproductive modes dampened with time, leading to smaller differences in clonal offspring leaf area between treatments over time.• CONCLUSIONS: We found evidence of a cost of reproduction and trade-offs between reproductive modes, although the magnitude of these costs was small. However, we found no evidence of lower costs of reproduction for larger plants or for plants in higher-light environments over our 2-yr study period.

Plant Species' Capacity for Range Shifts at the Habitat and Geographic Scales: A Trade-Off-Based Framework.

Climate change is causing rapid shifts in the abiotic and biotic environmental conditions experienced by plant populations, but we lack generalizable frameworks for predicting the consequences for species. These changes may cause individuals to become poorly matched to their environments, potentially inducing shifts in the distributions of populations and altering species' habitat and geographic ranges. We present a trade-off-based framework for understanding and predicting whether plant species may undergo range shifts, based on ecological strategies defined by functional trait variation. We define a species' capacity for undergoing range shifts as the product of its colonization ability and the ability to express a phenotype well-suited to the environment across life stages (phenotype-environment matching), which are both strongly influenced by a species' ecological strategy and unavoidable trade-offs in function. While numerous strategies may be successful in an environment, severe phenotype-environment mismatches result in habitat filtering: propagules reach a site but cannot establish there. Operating within individuals and populations, these processes will affect species' habitat ranges at small scales, and aggregated across populations, will determine whether species track climatic changes and undergo geographic range shifts. This trade-off-based framework can provide a conceptual basis for species distribution models that are generalizable across plant species, aiding in the prediction of shifts in plant species' ranges in response to climate change.

The Net Effect of Functional Traits on Fitness.

Generalizing the effect of traits on performance across species may be achievable if traits explain variation in population fitness. However, testing relationships between traits and vital rates to infer effects on fitness can be misleading. Demographic trade-offs can generate variation in vital rates that yield equal population growth rates, thereby obscuring the net effect of traits on fitness. To address this problem, we describe a diversity of approaches to quantify intrinsic growth rates of plant populations, including experiments beyond range boundaries, density-dependent population models built from long-term demographic data, theoretical models, and methods that leverage widely available monitoring data. Linking plant traits directly to intrinsic growth rates is a fundamental step toward rigorous predictions of population dynamics and community assembly.