Thu, Aug 18, 2022: 5:00 PM-6:30 PM
ESA Exhibit Hall
Background/Question/Methods
: Spatial population synchrony is when populations of the same species at different locations exhibit similar fluctuations through time in density or abundance. Population synchrony is often caused by synchrony of environmental variables which impact the populations, through a process called the Moran effect. Recent work shows that when two environmental drivers both impact the same set of populations (e.g., temperature and rainfall), the Moran effects of the distinct drivers can interact, either synergistically or destructively. Interaction effects are due to so-called “cross-variable synchrony†between the drivers, a term which refers to a tendency for driver 1 in one location to be associated, possibly in a lagged or phase shifted manner, with driver 2 in another location. Though recent important case studies and theory suggest interactions between Moran effects can be important for population synchrony and may be common, to the best of our knowledge no researcher has yet broadly assessed the extent and nature of cross-variable synchrony in temperature and rainfall variables which are commonly important for many population systems. We used weather station data from the U.S. Historical Climatology Network (USHCN) and plots of time series correlations against distance between stations to fill this gap in knowledge.
Results/Conclusions
: Seasonally averaged values of monthly minimum, maximum and average temperatures, and precipitation were extracted for the period 1922-2021 for hundreds of weather stations across the USA. Whereas classical plots of one-variable synchrony versus distance for environmental variables always show steep declines in synchrony with distance between weather stations, patterns of cross-variable synchrony were markedly different. Cross-variable synchrony between temperature variables from different seasons frequently showed low but significantly positive values that did not decline with distance, even out to distances of 3000-4000km. Cross-variable synchrony between temperature and precipitation variables from the same or different seasons were often strongly negative at short distances, rising to zero as distances approached 1000-3000km, and sometimes rising to positive values for the longest available distances; though other patterns also occurred. Though our results are principally valuable as the first (to our knowledge) survey of cross-variable synchrony of temperature and precipitation variables, they also suggest that interactions between Moran effects may be an especially important mechanism of population synchrony at longer distances, whether same-variable environmental synchrony can apparently be weaker than cross-variable environmental synchrony.
: Spatial population synchrony is when populations of the same species at different locations exhibit similar fluctuations through time in density or abundance. Population synchrony is often caused by synchrony of environmental variables which impact the populations, through a process called the Moran effect. Recent work shows that when two environmental drivers both impact the same set of populations (e.g., temperature and rainfall), the Moran effects of the distinct drivers can interact, either synergistically or destructively. Interaction effects are due to so-called “cross-variable synchrony†between the drivers, a term which refers to a tendency for driver 1 in one location to be associated, possibly in a lagged or phase shifted manner, with driver 2 in another location. Though recent important case studies and theory suggest interactions between Moran effects can be important for population synchrony and may be common, to the best of our knowledge no researcher has yet broadly assessed the extent and nature of cross-variable synchrony in temperature and rainfall variables which are commonly important for many population systems. We used weather station data from the U.S. Historical Climatology Network (USHCN) and plots of time series correlations against distance between stations to fill this gap in knowledge.
Results/Conclusions
: Seasonally averaged values of monthly minimum, maximum and average temperatures, and precipitation were extracted for the period 1922-2021 for hundreds of weather stations across the USA. Whereas classical plots of one-variable synchrony versus distance for environmental variables always show steep declines in synchrony with distance between weather stations, patterns of cross-variable synchrony were markedly different. Cross-variable synchrony between temperature variables from different seasons frequently showed low but significantly positive values that did not decline with distance, even out to distances of 3000-4000km. Cross-variable synchrony between temperature and precipitation variables from the same or different seasons were often strongly negative at short distances, rising to zero as distances approached 1000-3000km, and sometimes rising to positive values for the longest available distances; though other patterns also occurred. Though our results are principally valuable as the first (to our knowledge) survey of cross-variable synchrony of temperature and precipitation variables, they also suggest that interactions between Moran effects may be an especially important mechanism of population synchrony at longer distances, whether same-variable environmental synchrony can apparently be weaker than cross-variable environmental synchrony.