Sequence-shifted temperatures and ectotherm thermal performance

Background/Question/Methods

While much attention has been given to average temperature increases resulting from climate change, biological impacts of shifted temperature patterns such as night warming and high autocorrelation remain to be well understood. Night warming consists of a disproportionate increase in night temperatures in relation to daytime. Highly autocorrelated temperatures are characterized by sequences of warmer or colder than average conditions. Both phenomena have a demonstrated impact in the performance of organisms, although no studies have investigated effects to thermal performance curves. In a climate change context where temperatures are becoming more autocorrelated and nights are becoming warmer, understanding potential impacts is fundamental to make ecological predictions for ectotherms in general. This study investigated the effects of highly autocorrelated temperatures and night warming on the reproduction of duckweeds and aphids, widely distributed model organisms of commercial utility and pest control interest, respectively. In suboptimal conditions, such temperature shifts are expected to result in divergent responses in comparison with constant and randomly fluctuating conditions, namely reduced reproduction in high temperatures and improved performance in low temperatures. Additionally, because preliminary analyses show that autocorrelation trends are increasingly divergent when comparing maximum and minimum yearly temperatures from 1950 to present days, night warming treatments are included in the experiment. Statistical analyses were conducted to assess differences among experimental groups

Results/Conclusions

We found no significant difference in average number of offspring for aphids and duckweeds in highly autocorrelated and control groups submitted to both suboptimal and optimal temperatures. It is unclear if the constant conditions used before starting the temperature exposures had a disproportionate impact on the results, and if our suboptimal conditions were far enough from the temperature of peak performance in order to detect an impact. Modeling studies have suggested that population dynamics disruptions following exposure to highly autocorrelated temperatures may occur depending on the duration and magnitude of unfavorable conditions. Therefore, our next experimental efforts are focused on extended sample sizes and exposure periods, and on average temperatures more distant from optimal conditions. Indeed, a preliminary analysis including limited replicates and an average temperature of 10 °C yielded statistically significant differences among average summed offspring, with a strong autocorrelation enhancing reproduction in duckweeds, according to our original hypothesis. Additionally, night warming treatments are being included to investigate how organisms respond to disproportional increases of temperatures close to the minimum. The continuity of such experiments is relevant for elucidating biological impacts resulting from shifted temperature sequences, enabling more accurate predictions related to ecological processes such as invasions.