Based on 439 observations made in geothermal springs in Yellowstone National Park (YNP), Wyoming, a model was developed to determine how much geochemical variation affects the distribution of phototrophic metabolisms. To forecast the distribution of phototrophic metabolism as a function of spring temperature, pH, and total sulphide, Generalised Additive Models (GAMs) were created. Temperature-based GAMs accounted for 38.8% of the variation in the distribution of phototrophic metabolism, while sulfide- and pH-based GAMs accounted for 19.6 and 11.2% of the variation, respectively. These findings imply that temperature is the main factor limiting the spread of phototrophs in YNP out of the measured variables. A greater proportion of the variation in the distribution of phototrophic metabolism was explained by GAMs with more factors, demonstrating additive interactions between the variables. The dataset's highest volatility (53.4%) was best explained by a GAM that integrated temperature and sulphide while introducing the fewest degrees of freedom. We investigated the effect of sulphide and temperature on Dissolved Inorganic Carbon (DIC) absorption rates under both light and dark circumstances in order to confirm the extent to which phototroph distribution reflects restrictions on activity. In acidic, algaldominated systems, light-driven DIC uptake reduced systematically with rising sulphide concentrations, but was unaffected in alkaline, cyanobacterial-dominated systems. Light-driven DIC uptake was reduced in cultures incubated at temperatures 10°C higher than them in situ temperature in both alkaline and acidic systems. Together, these quantitative findings show that, besides the availability of light, the habitat range of phototrophs in YNP springs is largely determined by the restrictions placed first by temperature and then by sulphide on the activity of these populations that inhabit the habitat range's periphery. These results support the predictions made by GAMs and offer a mathematical framework for converting distributional patterns into fitness landscapes, which can then be used to evaluate the environmental limitations that have shaped this process' evolution throughout Earth history.
