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Spatial synchrony, defined as the correlated fluctuations in abundance of spatially separated populations, can be caused by regional fluctuations in natural and anthropogenic environmental population drivers. Investigations into the geography of synchrony can provide useful insight to inform conservation planning efforts by revealing regions of common population drivers and metapopulation extinction vulnerability. We examined the geography of spatial synchrony and decadal changes in these patterns for grassland birds in the United States and Canada, which are experiencing widespread and persistent population declines. We used Bayesian hierarchical models and over 50 years of abundance data from the North American Breeding Bird Survey to generate population indices within a 2° latitude by 2° longitude grid. We computed and mapped mean local spatial synchrony for each cell (mean detrended correlation of the index among neighboring cells), along with associated uncertainty, for 19 species in 2, 26‐year periods, 1968–1993 and 1994–2019. Grassland birds were predicted to increase in spatial synchrony where agricultural intensification, climate change, or interactions between the 2 increased. We found no evidence of an overall increase in synchrony among grassland bird species. However, based on the geography of these changes, there was considerable spatial heterogeneity within species. Averaging across species, we identified clusters of increasing spatial synchrony in the Prairie Pothole and Shortgrass Prairie regions and a region of decreasing spatial synchrony in the eastern United States. Our approach has the potential to inform continental‐scale conservation planning by adding an additional layer of relevant information to species status assessments and spatial prioritization of policy and management actions. Our work adds to a growing literature suggesting that global change may result in shifting patterns of spatial synchrony in population dynamics across taxa with broad implications for biodiversity conservation. [ABSTRACT FROM AUTHOR]

Abstract: We studied hidden periodicities and trends in the temporal dynamics of soil salinity in the Canadian prairies at a field scale. Singular spectrum analysis (SSA) was applied to time series of the groundwater depth (Dgw), total precipitation, groundwater electrical conductivity (ECgw), and soil electrical conductivity (ECe). We found that the temporal variability of soil salinity is determined by its seasonal and quasi-3-yr oscillations controlled by similar cycles of Dgw and ECgw, which are controlled by the precipitation. In the seasonal cycle, the system “precipitation – groundwater depth – groundwater salinity – soil salinity” proceeds as follows: The maximal level of the precipitation is reached in late May. The water table peaks 2 months after the maximal level of precipitation was reached. The seasonal oscillation of ECgw is in phase with that of Dgw. ECe peaks 1.5 months after the maximal level of ECgw was reached. In the quasi-3-yr cycle, ECe peaks about 14 months after the maximal rise of the groundwater. Most likely, this cycle of Dgw is a response to the 3-yr periodicity of the precipitation observed in the region. SSA is the effective tool to detect hidden oscillations in soil processes handling relatively short time series with missing records. [Copyright &y& Elsevier]