44 1–13 ECOGRAPHY Research Exploring timescales of predictability in species distributions Stephanie Brodie, Briana Abrahms, Steven J. Bograd, Gemma Carroll, Elliott L. Hazen, Barbara A. Muhling, Mercedes Pozo Buil, James A. Smith, Heather Welch and Michael G. Jacox S. Brodie (https://orcid.org/0000-0003-0869-9939) ✉ (
[email protected]), S. J. Bograd, E. L. Hazen, B. A. Muhling, M. Pozo Buil, J. A. Smith, H. Welch and M. G. Jacox, Inst. of Marine Science, Univ. of California Santa Cruz, Santa Cruz, CA, USA. SBr, SBo, ELH, MPB, HW and MGJ also at: Environmental Research Division, NOAA Southwest Fisheries Science Center, Monterey, CA, USA. BAM and JAS also at: Fisheries Research Division, NOAA Southwest Fisheries Science Center, San Diego, CA, USA. – B. Abrahms, Center for Ecosystem Sentinels, Dept of Biology, Univ. of Washington, Seattle, WA, USA. – G. Carroll, School of Aquatic and Fisheries Sciences, Univ. of Washington, Seattle, WA, USA, and: Resource Ecology and Ecosystem Modelling Group, NOAA Alaska Fisheries Science Center, Seattle, WA, USA. Ecography Accurate forecasts of how animals respond to climate-driven environmental change 44: 1–13, 2021 are needed to prepare for future redistributions, however, it is unclear which temporal doi: 10.1111/ecog.05504 scales of environmental variability give rise to predictability of species distributions. We examined the temporal scales of environmental variability that best predicted Subject Editor: spatial abundance of a marine predator, swordfish Xiphias gladius, in the California Christine N. Meynard Current. To understand which temporal scales of environmental variability provide Editor-in-Chief: Miguel Araújo biological predictability, we decomposed physical variables into three components: a Accepted 16 February 2021 monthly climatology (long-term average), a low frequency component representing interannual variability, and a high frequency (sub-annual) component that captures ephemeral features.