Jonathan A. Walter, Daniel C. Reuman, Kimberly R. Hall, Herman H. Shugart, and Lauren G. Shoemaker
Spatial synchrony is a key feature of pest and disease outbreaks and major source of instability, but little is known about how seasonality affects it. Walter et al. show using theoretical models how seasonality in population processes and environmental drivers alters synchrony.Cold winds and snow buffet the deer of an isolated valley. The harsh winter conditions dramatically reduce survival over the season, causing the deer population to plummet. We might expect a similar fate for the deer of a neighboring valley, but where does this intuition come from?
The essential concept in this scenario is spatial population synchrony, defined as the tendency of spatially separated populations to experience similar demographic change. One of the main causes of this synchrony is the response of populations to environmental conditions correlated over space, known as the Moran effect. We expect both valleys to experience particularly intense winters while simultaneously resulting in similar declines in the two deer populations. Overall, greater synchrony between populations is expected to destabilize metapopulations, reducing the chance that one subpopulation will survive and repopulate the landscape while increasing the probability of total extinction of the metapopulation.
Yet environmental conditions can vary over time and space; the same deer populations will experience spring, and environmental conditions in this season may or may not correlate with the winter. The degree of spatial correlation could differ between seasons, complicating our ability to predict how synchronous the populations will result over time. The impact of seasonality on spatial synchrony has gone relatively understudied despite the importance of seasonality to countless species. Seasons bring variations in environmental temperatures, precipitation, and population processes (e.g., seasonal reproduction and migration). Quantifying the many impacts of seasonality on spatial synchrony is challenging using empirical studies, as they require long-term data in several locations and can struggle to determine causality. Instead, theoretical studies can be employed to provide clear expectations and mechanistically link the different features of seasonality to spatial synchrony.
In this paper, Jonathan Walter and his colleagues expanded on classic models of spatial synchrony by adding seasonality, thereby exploring how environmental correlations between two populations in a winter and breeding season impact their synchrony over time. The authors analytically solved how population growth and synchrony depended on covariation between populations and seasons and used simulations to compare these relationships in various scenarios, including situations with dispersal and over-winter reproduction. Within certain contexts, the models behaved as expected, with greater environmental correlations between populations resulting in greater synchrony. However, the correlation between population change could become negative under certain scenarios, meaning even if the environments of both populations were correlated, the populations could be asynchronous depending on exactly how correlated the winter and breeding season environments were. Interactions between the spatial correlations of winter and breeding season conditions could also result in greater synchrony between the populations than in models without seasons. Finally, the relationship between environmental correlations and spatial synchrony depended on the strength of density dependence, where moving from weak to strong intraspecific competition sometimes flipped the relationship between parameters and spatial synchrony.
Overall, the authors found that across biologically relevant forms of seasonality, population synchrony can behave in unexpected ways. These findings could help explain known discrepancies between winter and breeding season population synchrony measurements used to monitor migratory bird populations. The authors also note that changing whether population size estimates were calculated for the breeding season or winter could change whether the populations appeared synchronous or asynchronous, identifying how the timing of population monitoring can bias estimates of spatial synchrony.
Cross-seasonal and spatial environmental correlations are changing in response to climate change in ways that could result in greater synchrony across populations. Whether a metapopulation synchronizes and is driven to extinction by a harsh winter or summer drought depends on a slew of parameters explored by Walter et al. The authors created a plethora of model worlds that can lay the groundwork for empirical studies into preserving populations in our rapidly changing world.
