Decomposing the spatial and temporal effects of climate on bird populations in northern European mountains

Abstract

The relationships between species abundance or occurrence versus spatial variation in climate are commonly used in species distribution models (SDMs) to forecast future distributions. Under "space-for-time-substitution", the effects of climate variation on species are assumed to be equivalent in both space and time. Two unresolved issues of space-for-time-substitution are the time period for species' responses and also the relative contributions of rapid- versus slow reactions in shaping spatial and temporal responses to climate change. To test the assumption of equivalence, we used a new approach of climate decomposition to separate variation in temperature and precipitation in Fennoscandia into spatial, temporal and spatio-temporal components over a 23-year period (1996-2018). We compiled information on land cover, topography and six components of climate for 1756 fixed route surveys and we modelled annual counts of 39 bird species breeding in the mountains of Fennoscandia. Local abundance of breeding birds was associated with the spatial components of climate as expected, but the temporal and spatio-temporal climatic variation from the current and previous breeding seasons were also important. The directions of the effects of the three climate components differed within and among species, suggesting that species can respond both rapidly and slowly to climate variation and that the responses represent different ecological processes. Thus, the assumption of equivalent species' response to spatial and temporal variation in climate was seldom met in our study system. Consequently, for the majority of our species, space-for-time substitution may only be applicable once the slow species' responses to a changing climate have occurred. Whereas forecasts for the near future need to accommodate the temporal components of climate variation. However, appropriate forecast horizons for space-for-time substitution are rarely considered and may be difficult to reliably identify. Accurately predicting change is challenging because multiple ecological processes affect species distributions at different temporal scales.