Legacies of change:how past environments shape population responses to sequential stressors

rivers of population growth and functioning are multifaceted. With accelerating global change, these drivers can show shifts in terms of intensity, frequency, and duration, with profound implications for population dynamics. Notably, a ubiquitous feature of global change is the potential for drivers to form sequences. When shift in environments is sequential rather than simultaneous, a key question is how past environments may influence population responses during subsequent environmental shifts. This knowledge gap is critical, as the imprint of past environments can persist long after the initial exposure and thus, have consequences for population persistence in the long term.<br/><br/>In this study, we investigated how past environments influence population responses to sequences of environmental drivers using phytoplankton as a model system. We conducted a full-factorial experiment on six strains of Synechococcus sp., a globally abundant marine pico-phytoplankton, from different biogeographic regions. Populations were exposed to thermal shifts and polluted media (herbicide atrazine). In marine ecosystems both these factors are known to cause photosynthetic inhibition and significantly alter phytoplankton growth rates community structure. Overall, for nine different environmental sequences, we tracked population growth metrics (density and per-capita growth rate) and functional traits (cell size and chlorophyll content) every 24h for 17 days. With the resulting data from experiments, we tested two hypotheses: first, that the degree of influence of the past environment is related to the inherent sensitivity of a strain to an environment; second, population growth in sequential environments are mediated by functional traits. Statistical inference using repeated-measures ANOVA and post-hoc tests on our data reveal the following-<br/><br/>In 66 percent of the cases we find a significant influence (p &lt; 0.05) of past environments in driving population growth and traits, particularly for sequences with contrasting environments.<br/><br/>In cases where its significant, the influence of past environments is contingent upon the inherent sensitivity of a population to the particular environmental driver.<br/><br/>Changes in population growth in sequential environments are decoupled to changes in functional traits.<br/><br/><br/>In conclusion, we present a sensitivity-based perspective to explain the ways past environments may influence population persistence in temporally dynamic conditions. Further research can leverage bioassay data to quantify species sensitivities, and thereby improve predictions of population responses in a rapidly changing world.<br/><br/>