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Understanding spatiotemporal variation in environmental conditions is important to determine how climate change will impact ecological communities. The spatial and temporal autocorrelation of temperature can have strong impacts on community structure and persistence by increasing the duration and the magnitude of unfavorable conditions in sink populations and disrupting spatial rescue effects by synchronizing spatially segregated populations. Although increases in spatial and temporal autocorrelation of temperature have been documented in historical data, little is known about how climate change will impact these trends. We examined daily air temperature data from 21 General Circulation Models under the business-as-usual carbon emission scenario to quantify patterns of spatial and temporal autocorrelation between 1871 and 2099. Although both spatial and temporal autocorrelation increased over time, there was significant regional variation in the temporal autocorrelation trends. Additionally, we found a consistent breakpoint in the relationship between spatial autocorrelation and time around the year 2030, indicating an acceleration in the rate of increase of the spatial autocorrelation over the second half of the 21^stcentury. Overall, our results suggest that ecological populations might experience elevated extinction risk under climate change because increased spatial and temporal autocorrelation of temperature is expected to erode both spatial and temporal refugia.

Virtual reality environments are becoming increasingly popular as educational tools, but it remains unclear when these environments enhance learning or when they are a distraction from the learning process. We compared two dif- ferent methods for teaching ecological concepts about the rocky intertidal zone by comparing an experimental (virtual) class with a control (traditional) type of class. We investigated whether cognitive (i.e., knowledge) and affective (i.e., attitudes, perceptions) outcomes are enhanced when students use lesson plans presented in a virtual reality environment compared with lesson plans facilitated via traditional methods. We also assessed the extent to which these attributes are enhanced when students create their own virtual tours as part of a field-based learning experience. The experimental group showed significantly higher maintenance of knowledge gain than the traditional group at the conclusion of the study, but there were no other significant differences among treatment groups. Feedback from teachers reported that students were more engaged, had better recall, and enjoyed the change from the traditional lecture style. Lack of statistically different scores measuring excitement suggests a need for improvement in the design and implementation of these virtual environments to maximize their appeal to students. However, our results suggest that virtual realitymore »technologies provide an innovative alternative to standard lesson plans that can help improve knowledge retention about ecological concepts.« less

Abstract The rocky intertidal zone is a highly dynamic and thermally variable ecosystem, where the combined influences of solar radiation, air temperature and topography can lead to differences greater than 15°C over the scale of centimetres during aerial exposure at low tide. For most intertidal organisms this small-scale heterogeneity in microclimates can have enormous influences on survival and physiological performance. However, the potential ecological importance of environmental heterogeneity in determining ecological responses to climate change remains poorly understood. We present a novel framework for generating spatially explicit models of microclimate heterogeneity and patterns of thermal physiology among interacting organisms. We used drone photogrammetry to create a topographic map (digital elevation model) at a resolution of 2 × 2 cm from an intertidal site in Massachusetts, which was then fed into to a model of incident solar radiation based on sky view factor and solar position. These data were in turn used to drive a heat budget model that estimated hourly surface temperatures over the course of a year (2017). Body temperature layers were then converted to thermal performance layers for organisms, using thermal performance curves, creating ‘physiological landscapes’ that display spatially and temporally explicit patterns of ‘microrefugia’. Our framework shows how non-linear interactionsmore »between these layers lead to predictions about organismal performance and survivorship that are distinct from those made using any individual layer (e.g. topography, temperature) alone. We propose a new metric for quantifying the ‘thermal roughness’ of a site (RqT, the root mean square of spatial deviations in temperature), which can be used to quantify spatial and temporal variability in temperature and performance at the site level. These methods facilitate an exploration of the role of micro-topographic variability in driving organismal vulnerability to environmental change using both spatially explicit and frequency-based approaches.« less