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The more an ecosystem varies through time, the greater the likelihood of low values of ecosystem services or abundances. Now, low abundance can be dramatic for threatened species and low levels of ecosystem services can have adverse consequences for human well-being. When abundance fluctuate through time, the risks associated with low abundance years (extinction, shortages) are generally not offset by the benefits of high abundance years. Temporal stability is therefore a variable of great interest for the management and conservation of biodiversity and ecosystems.

The spatial scale is an essential parameter of any measure of temporal stability, and these two measurements are expected to be positively related. However, the relationship between temporal stability (invariability) and the spatial scale (area considered) had never before been made explicit and applied to the ecology of communities and ecosystems.

The article in Nature Communications establishes a Theoretical Invariability Area Relationship (IAR) and shows that its shape depends on spatial synchrony, that measures simultaneity of fluctuations. Close populations fluctuate together more than remote populations so that synchrony decreases with distance. If this decay accelerates with distance, as in an exponential relationship, the IAR presents three phases, characterized by stronger increases in invariability at small and large scales. Such triphasic IARs are observed for terrestrial primary production of the plot scale on a global scale.

When synchrony between populations decreases slowly with the geographical distance separating them, the IAR is almost linear on a log-log scale. These near-linear IARs are observed for the biomass of North American birds at both species and community levels. This quasi-linearity could come from the relatively small range of spatial scales considered.

The IAR echoes the well-known relationship between species numbers and sampled area in the Species-Area Relationship (SAR), which also has a three-phase shape from plot to globe scale. IAR offers opportunities similar to SAR, which is widely used in conservation biology to predict the consequences of habitat loss for biodiversity. For example, IAR can be used to predict the effects of habitat loss on vulnerable populations or on ecosystem services, which SAR does not consider. The authors show that IAR could also help detecting the approach of "catastrophic" transitions during ecosystem degradation. The future will tell us if this new relationship will deliver as much as the SAR has.