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Divergent natural selection should lead to adaptive radiation-that is, the rapid evolution of phenotypic and ecological diversity originating from a single clade. The drivers of adaptive radiation have often been conceptualized through the concept of "adaptive landscapes," yet formal empirical estimates of adaptive landscapes for natural adaptive radiations have proven elusive. Here, we use a 17-year dataset of Darwin's ground finches (Geospiza spp.) at an intensively studied site on Santa Cruz (Galápagos) to estimate individual apparent lifespan in relation to beak traits. We use these estimates to model a multi-species fitness landscape, which we also convert to a formal adaptive landscape. We then assess the correspondence between estimated fitness peaks and observed phenotypes for each of five phenotypic modes (G. fuliginosa, G. fortis [small and large morphotypes], G. magnirostris, and G. scandens). The fitness and adaptive landscapes show 5 and 4 peaks, respectively, and, as expected, the adaptive landscape was smoother than the fitness landscape. Each of the five phenotypic modes appeared reasonably close to the corresponding fitness peak, yet interesting deviations were also documented and examined. By estimating adaptive landscapes in an ongoing adaptive radiation, our study demonstrates their utility as a quantitative tool for exploring and predicting adaptive radiation., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Society for the Study of Evolution (SSE).)

Disruptive natural selection within populations exploiting different resources is considered to be a major driver of adaptive radiation and the production of biodiversity. Fitness functions, which describe the relationships between trait variation and fitness, can help to illuminate how this disruptive selection leads to population differentiation. However, a single fitness function represents only a particular selection regime over a single specified time period (often a single season or a year), and therefore might not capture longer-term dynamics. Here, we build a series of annual fitness functions that quantify the relationships between phenotype and apparent survival. These functions are based on a 9-year mark-recapture dataset of over 600 medium ground finches ( Geospiza fortis ) within a population bimodal for beak size. We then relate changes in the shape of these functions to climate variables. We find that disruptive selection between small and large beak morphotypes, as reported previously for 2 years, is present throughout the study period, but that the intensity of this selection varies in association with the harshness of environment. In particular, we find that disruptive selection was strongest when precipitation was high during the dry season of the previous year. Our results shed light on climatic factors associated with disruptive selection in Darwin's finches, and highlight the role of temporally varying fitness functions in modulating the extent of population differentiation.