Local assemblages are embedded in networks of communities connected by dispersal, and understanding the processes that mediate this local-regional interaction is central to understanding biodiversity patterns. In this network (i.e. metacommunity), the strength of dispersal relative to the intensity of environmental selection typically determines whether local communities are comprised of species well-adapted to the local environment (i.e. species sorting) or are dominated by regionally successful species that may not be locally adapted (i.e. mass effects), which by extension determines the capacity of the landscape to sustain diversity. Despite the fundamentally spatial nature of these dispersal-mediated processes, much of our theoretical understanding comes from spatially implicit systems, a special case of spatial structure in which patches are all connected to each other equally. In many real systems, both the connections among patches (i.e. network topology) and the distributions of environments across patches (i.e. spatial autocorrelation) are not arranged uniformly. Here, we use a metacommunity model to investigate how spatial heterogeneities may change the balance between species sorting versus mass effects and diversity outcomes. Our simulations show that, in general, the spatially implicit model generates an outlier in biodiversity patterns compared to other networks, and most likely amplifies mass effects relative to species sorting. Network topology has a strong effect on metacommunity outcome, with topologies of sparse connections and few loops promoting sorting of species into suitable patches. Spatial autocorrelation is another key factor; by interacting with spatial topology, intermediate-scale clusters of similar patches can emerge, leading to a reduction of regional competition, and hence maintenance of gamma diversity. These results provide a better understanding of the role that complex spatial landscape structure plays in metacommunity processes, a necessary step to understanding how metacommunity processes relate to biodiversity conservation.
Our knowledge of ecological stability is built on assumptions of scale. These assumptions limit our ability to reach a generalizable and mechanistic understanding of stability under global environmental change. Moving towards a multiscale approach—across space, time and environment—will allow us to better understand the intrinsic (e.g., demographic) and extrinsic (environmental) drivers of ecological stability. In this perspective, we review multiple sources of variation responsible for shaping ecological dynamics, and how scale affects our observation of these dynamics through its confounding effect on drivers of variation in ecosystems. We discuss the effect of temporal scale when combining empirical dynamic modeling with high‐resolution population time series to consider the time‐varying nature of multispecies interaction networks, highlighting interspecific interactions as an intrinsic driver of community dynamics. Next, we examine energy landscape analysis as a method for inferring stability and transience during community assembly and its interaction with spatial scale, emphasizing the intrinsic role of compositional variability in assembly dynamics. We then examine population dynamics at species' range margins and show how considering the interaction between spatial and temporal environmental heterogeneity, an extrinsic driver of population dynamics, can facilitate a nuanced understanding of population expansions, range shifts, and species invasions. Finally, we discuss broadly how the sources of intrinsic and extrinsic variation interact with each other and with spatiotemporal scale to shape ecological dynamics. Better recognition of the scale‐dependent nature of the relationship between drivers of variation and ecological dynamics will be invaluable to illuminate the dynamics influencing ecological stability across scales.
Ecological communities are assembled through a series of multiple processes, including dispersal, abiotic and biotic filtering, and ecological drift. Although these assembly processes act in concert to structure local communities, their relative importance is considerably variable among study systems. While such contingency of community assembly has been widely appreciated, the empirical and theoretical evidence is scattered around in the literature, and few efforts have been made to synthesize it. In this mini‐review, we summarize the accumulated evidence of the context‐dependency of community assembly rules, to reach a rough generalization of the contingency. Specifically, we argue that spatial and temporal dimensions can serve as general axes that regulate the relative importance of assembly processes. To this end, we synthesize the current understanding of how the relative importance of multiple assembly processes changes with spatial scales and complexity, and with time in the long and short terms. This review concludes that spatial and temporal dimensions can be common currencies of community assembly rules that are shared across various systems.
In this study, the authors tackle the topic of transgenerational immune priming in invertebrates. The authors designed a large experiment taking advantage of clonal Daphnia to test whether infecting parental generations with different parasite strains improves the offspring's resistance to that parasite overall and if yes, if they resist that specific strain more effectively than other strains. This experiment essentially tests the specificity of immune priming at a very fine "strain" scale. The results did not support parental infection strain differentially affecting offspring resistance to different strains, suggesting that immune priming is not specific to the strain level in this system. However, a mathematical model the authors developed for that study fits the data exceptionally well, which means this model could potentially be used in a predictive manner for this or similar systems. Additionally, the unexpected result that one strain actually facilitates specific infection in the offspring is surprising and opens the door to additional inquiry and future experimentation. Overall this study is very interesting and well-presented, but there are a few concerns that could be addressed and improved in the next version of the manuscript.
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