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1. Thermal performance curves (TPCs) have been estimated in multiple ectotherm species to understand their thermal plasticity and adaptation and to predict the effect of global warming. However, TPCs are typically assessed under constant temperature regimes, so their reliability for predicting thermal responses in the wild where temperature fluctuates diurnally and seasonally remains poorly documented. 2. Here, we use distant latitudinal populations of five species of sepsid flies (Diptera: Sepsidae) from the temperate region (Europe, North Africa, North America) to compare estimates derived from constant TPCs with observed development rate under fluctuating temperatures in laboratory and field conditions.3. TPCs changed across gradients in that flies originating from higher latitudes showed accelerated development at higher temperatures, an adaptive response.TPCs were then used to predict development rates observed under fluctuating temperatures; these predictions were relatively accurate in the laboratory but not the field. Interestingly, the precision of TPC predictions depended not only on the resolution of temperature data, with daily and overall temperature summing performing better than hourly temperature summing, but also on the frequency of temperatures falling below the estimated critical minimum temperature. Hourly temperature resolution most strongly underestimated actual development rates, because flies apparently either did not stop growing when temperatures dropped below this threshold, or they sped up their growth when the temperature rose again, thus most severely reflecting this error. 4. We conclude that when flies do not encounter cold temperatures, TPC predictions based on constant temperatures can accurately reflect performance under fluctuating temperatures if adequately adjusted for nonlinearities, but when encountering cold temperatures, this method is more error-prone. 5.Our study emphasizes the importance of the resolution of temperature data and cold temperatures in shaping thermal reaction norms. K E Y W O R D SAltitude, chilling, climate change, latitude, Sepsidae, temperature variation, thermal adaptation 1902 |

Historical museum records provide potentially useful data for identifying drivers of change in species occupancy. However, because museum records are typically obtained via many collection methods, methodological developments are needed to enable robust inferences. Occupancy–detection models, a relatively new and powerful suite of statistical methods, are a potentially promising avenue because they can account for changes in collection effort through space and time. We use simulated datasets to identify how and when patterns in data and/or modelling decisions can bias inference. We focus primarily on the consequences of contrasting methodological approaches for dealing with species' ranges and inferring species' non‐detections in both space and time. We find that not all datasets are suitable for occupancy–detection analysis but, under the right conditions (namely, datasets that are broken into more time periods for occupancy inference and that contain a high fraction of community‐wide collections, or collection events that focus on communities of organisms), models can accurately estimate trends. Finally, we present a case study on eastern North American odonates where we calculate long‐term trends of occupancy using our most robust workflow. These results indicate that occupancy–detection models are a suitable framework for some research cases and expand the suite of available tools for macroecological analysis available to researchers, especially where structured datasets are unavailable.