The interacting effects of forestry and climate change on the demography of a group-living bird population
Anthropogenic degradation of natural habitats is a global driver of wildlife population declines. Local population responses to such environmental perturbations are generally well understood, but in socially structured populations, interactions between environmental and social factors may influence population responses. Thus, understanding how habitat degradation affects the dynamics of these populations requires simultaneous consideration of social and environmental mechanisms underlying demographic responses. Here we investigated the effect of habitat degradation through commercial forestry on spatiotemporal dynamics of a group-living bird, the Siberian jay, Perisoreus infaustus, in boreal forests of northern Sweden. We assessed the interacting effects of forestry, climate and population density on stage-specific, seasonal life-history rates and population dynamics, using long-term, individual-based demographic data from 70 territories in natural and managed forests. Stage-specific survival and reproductive rates, and consequently population growth, were lower in managed forests than in natural forests. Population growth was most sensitive to breeder survival and was more sensitive to early dispersing juveniles than those delaying dispersal. Forestry decreased population growth in managed forests by reducing reproductive success and breeder survival. Increased snow depth improved winter survival, and warmer spring temperatures enhanced reproductive success, particularly in natural forests. Population growth was stable in natural forests but it was declining in managed forests, and this difference accelerated under forecasted climate scenarios. Thus, climatic change could exacerbate the rate of forestry-induced population decline through reduced snow cover in our study species, and in other species with similar life-history characteristics and habitat requirements.
KeywordsClimate change Forestry Demography Elasticity analysis Multi-state mark-recapture
We thank Chloe Nater for help with analysis; Folke Lindgren, Jan Ekman, Bohdan Sklepkovych, Sönke Eggers, Magdalena Nystrand, Jonathan Barnaby, Xenia Schleuning, Julian Klein and all field volunteers for collecting the field data; and Susanne Schindler, Christophe Bousquet and Agnes Olin for comments on the manuscript. NetOne provided us the much-needed internet access during the fieldwork. This study has been supported by grants from the Swiss National Science Foundation (MG: PPOOP3_123520, PP00P3_150752), ERA-Net BiodivERsA (AO, MG: 31BD30_172465), the Swedish Research Council (MG, Jan Ekman), Formas (Jan Ekman), the National Science Centre, Poland, through the European Union’s Horizon 2020 research and innovation program (Marie Sklodowska-Curie Grant 665778 (MG), and University of Zurich (AO, MG).
Author contribution statement
MG collected the data; KLM and AO analysed the data; KLM wrote the manuscript; AO and MG assisted in writing and revising the manuscript.
Compliance with ethical standards
Data used in this study will be submitted to Dryad.
- Bates, D. et al. (2014) Fitting linear mixed-effects models using lme4Google Scholar
- Brownie, C. et al. (1993) Capture-recapture studies for multiple strata including non-Markovian transitions. Biometrics, 1173–1187Google Scholar
- Burnham, K.P. (1987) Design and analysis methods for fish survival experiments based on release-recapture, American Fisheries Society Google Scholar
- Burnham KP, Anderson DR (2003) Model selection and multimodel inference: a practical information theoretic-approach. Springer Science & Business MediaGoogle Scholar
- Caswell, H. (2001) Matrix population models, John Wiley & Sons, Ltd Google Scholar
- Ekman J, Griesser M (2016) Siberian jays: delayed dispersal in the absence of cooperative breeding. Cambridge University Press 6–18:2016Google Scholar
- Esseen PA et al (1997) Boreal Forests. Ecological Bulletins 46:16–47Google Scholar
- Laake JL (2013) RMark: An R Interface for Analysis of Capture-Recapture Data with MARK. AFSC Processed Rep 2013–01. Alaska Fish. Sci. Cent., NOAA, Natl. Mar. Fish. Serv., 7600 Sand Point Way NE, Seattle WA 98115Google Scholar
- Lui, C. (2010) Survival in a population of Siberian jays. Master’s thesis. Uppsala UniversityGoogle Scholar
- R Core Team (2016) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
- Stearns SC (1992) The evolution of life histories. Oxford University Press, OxfordGoogle Scholar
- Widén, P. (1987) Goshawk predation during winter, spring and summer in a boreal forest area of central Sweden. Holarctic Ecology, 104–109Google Scholar
- Wiley, R.H. (1974) Evolution of social organization and life-history patterns among grouse. The Quarterly Review of Biology, 201–227Google Scholar
- Williams, B.K., Nichols, J.D. & Conroy, M.J. (2002) Analysis and management of animal populations. Academic Press Google Scholar