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1. Plant-plant interactions are known to vary with changing environmental conditions; however, we have little empirical knowledge of the impact of abrupt environmental changes on millennial scale plant-plant interaction outcomes for long-lived plant species. Here, we used palaeoecological data (13-7.6 k years bp) and a novel statistical modelling approach to determine the impact of multiple environmental drivers on predicted tree “grass population interaction outcomes from our study site in eastern England. 2. Changes from high to low herbivore density shortly preceded changes to low fire levels and a shift to warmer summers. These transitions occurred during a period of increasing nitrogen (N) availability. Shortly thereafter, there was a shift in landscape dominance from grasses to oaks and then a change to decreasing N availability. 3. Model predictions of tree-grass interaction outcomes varied over time with respect to all environmental changes. During the time of high disturbances and cool summers, grasses were predicted to out-compete oaks. After climate warming and the loss of regular disturbances, the predicted outcome was stable coexistence. However, changes in the N cycle corresponded with different predicted outcomes: unstable competition under increasing N availability and facilitation of oaks by grasses when N availability was declining. 4. Akaike Information Criterion weights indicate that climate warming and fewer fires were consistent with the best-fitting model of oak-grass interactions for the entire time series (i.e. competitive exclusion to stable coexistence). However, reconciling the conflicting model predictions with the observed population dynamics suggests that a temporary period of unstable competition preceded the predicted shift to stable coexistence. This dynamic behaviour is consistent with known patterns of shifts between alternative stable states. 5. Synthesis. We show that abrupt changes in environmental conditions over time lead to similarly abrupt changes in tree “grass interaction outcomes, which were shown to vary in contrasting directions with respect to resource versus non-resource variables. The approach described here allows plant ecologists to test hypotheses of plant “plant interactions over successional time scales for long-lived species and thus can lead to new knowledge about the structural role of these interactions in community dynamics.