We present a novel method to quantify the ecophysiological effects of changes in CO2 concentration during the reconstruction of climate changes from fossil pollen assemblages. The method does not depend on any particular vegetation model. Instead, it makes use of general equations from ecophysiology and hydrology that link moisture index (MI) to transpiration and the ratio of leaf-internal to ambient CO2 (χ). Statistically reconstructed MI values are corrected post facto for effects of CO2 concentration. The correction is based on the principle that e, the rate of water loss per unit carbon gain, should be inversely related to effective moisture availability as sensed by plants. The method involves solving a non-linear equation that relates e to MI, temperature and CO2 concentration via the Fu-Zhang relation between evapotranspiration and MI, Monteith's empirical relationship between vapour pressure deficit and evapotranspiration, and recently developed theory that predicts the response of χ to vapour pressure deficit and temperature. The solution to this equation provides a correction term for MI. The numerical value of the correction depends on the reconstructed MI. It is slightly sensitive to temperature, but primarily sensitive to CO2 concentration. Under low LGM CO2 concentration the correction is always positive, implying that LGM climate was wetter than it would seem from vegetation composition. A statistical reconstruction of last glacial maximum (LGM, 21±1 kyr BP) palaeoclimates, based on a new compilation of modern and LGM pollen assemblage data from Australia, is used to illustrate the method in practice. Applying the correction brings pollen-reconstructed LGM moisture availability in southeastern Australia better into line with palaeohydrological estimates of LGM climate.