publication . Article . Other literature type . 2018

Metapopulation dynamics in a changing climate: Increasing spatial synchrony in weather conditions drives metapopulation synchrony of a butterfly inhabiting a fragmented landscape

Kahilainen, Aapo; van Nouhuys, Saskya; Schulz, Torsti; Saastamoinen, Marjo;
Open Access English
  • Published: 01 Sep 2018 Journal: Global Change Biology, volume 24, issue 9, pages 4,316-4,329 (issn: 13541013, Copyright policy)
Abstract
Abstract Habitat fragmentation and climate change are both prominent manifestations of global change, but there is little knowledge on the specific mechanisms of how climate change may modify the effects of habitat fragmentation, for example, by altering dynamics of spatially structured populations. The long‐term viability of metapopulations is dependent on independent dynamics of local populations, because it mitigates fluctuations in the size of the metapopulation as a whole. Metapopulation viability will be compromised if climate change increases spatial synchrony in weather conditions associated with population growth rates. We studied a recently reported in...
Subjects
free text keywords: Ecology, Global and Planetary Change, General Environmental Science, Environmental Chemistry, Precipitation, Metapopulation, Climate change, Biological dispersal, Butterfly, Land use, Life history, Biodiversity, Biology, Primary Research Article, Primary Research Articles, dispersal, Lepidoptera, Melitaea cinxia, metapopulation dynamics, population synchrony, temperature, trophic interactions
Related Organizations
Funded by
EC| META-STRESS
Project
META-STRESS
Unravelling life-history responses and underlying mechanisms to environmental stress in wild populations
  • Funder: European Commission (EC)
  • Project Code: 637412
  • Funding stream: H2020 | ERC | ERC-STG
,
AKA| Interplay between ecology and genetics in shaping immunity in natural populations
Project
  • Funder: Academy of Finland (AKA)
  • Project Code: 273098
,
AKA| Finnish CoE in Metapopulation Research
Project
  • Funder: Academy of Finland (AKA)
  • Project Code: 213457
89 references, page 1 of 6

Aalto, J., Pirinen, P., & Jylhä, K. (2016). New gridded daily climatology of Finland: Permutation‐based uncertainty estimates and temporal trends in climate. Journal of Geophysical Research: Atmospheres, 121, 3807–3823. 10.1002/2015JD024651 [DOI]

Alexander, L., & Perkins, S. (2013). Debate heating up over changes in climate variability. Environmental Research Letters, 8, 41001 10.1088/1748-9326/8/4/041001 [OpenAIRE] [DOI]

Allstadt, A. J., Liebhold, A. M., Johnson, D. M., Davis, R. E., & Haynes, K. J. (2015). Temporal variation in the synchrony of weather and its consequences for spatiotemporal population dynamics. Ecology, 96, 2935–2946. 10.1890/14-1497.1 27070013 [OpenAIRE] [PubMed] [DOI]

Bjørnstad, O. N., Ims, R. A., & Lambin, X. (1999). Spatial population dynamics: Analyzing patterns and processes of population synchrony. Trends in Ecology and Evolution, 14, 427–432. 10.1016/S0169-5347(99)01677-8 10511718 [PubMed] [DOI]

Bonsal, B. R., Zhang, X., Vincent, L. A., & Hogg, W. D. (2001). Characteristics of daily and extreme temperatures over Canada. Journal of Climate, 14, 1959–1976. 10.1175/1520-0442(2001)014<1959:CODAET>2.0.CO;2 [DOI]

Bürkner, P.‐C. (2017). brms: An R package for Bayesian multilevel models using Stan. Journal of Statistical Software, 80, 1–28. https://doi.org/10.18637/jss.v080.i01

Carpenter, B., Gelman, A., Hoffman, M. D., Lee, D., Goodrich, B., & Betancourt, M., … Riddell, A. (2017). Stan: A probabilistic Programming Language. Journal of Statistical Software, 76, 1–32. https://doi.org/10.18637/jss.v076.i01

Chevalier, M., Laffaille, P., Ferdy, J. B., & Grenouillet, G. (2015). Measurements of spatial population synchrony: Influence of time series transformations. Oecologia, 179, 15–28. 10.1007/s00442-015-3331-5 25953116 [OpenAIRE] [PubMed] [DOI]

Clark, J. S., Silman, M., Kern, R., Macklin, E., & HilleRisLambers, J. (1999). Seed dispersal near and far: Patterns across temperate and tropical forests. Ecology, 80, 1475–1949. 10.1890/0012-9658(1999)080[1475:SDNAFP]2.0.CO;2 [DOI]

Cormont, A., Malinowska, A. H., Kostenko, O., Radchuk, V., Hemerik, L., WallisDeVries, M. F., & Verboom, J. (2011). Effect of local weather on butterfly flight behaviour, movement, and colonization: Significance for dispersal under climate change. Biodiversity and Conservation, 20, 483–503. 10.1007/s10531-010-9960-4 [OpenAIRE] [DOI]

Defriez, E. J., & Reuman, D. C. (2017). A global geography of synchrony for terrestrial vegetation. Global Ecology and Biogeography, 26, 878–888. 10.1111/geb.12595 [OpenAIRE] [DOI]

Defriez, E. J., Sheppard, L. W., Reid, P. C., & Reuman, D. C. (2016). Climate change‐related regime shifts have altered spatial synchrony of plankton dynamics in the North Sea. Global Change Biology, 22, 2069–2080. 10.1111/gcb.13229 26810148 [OpenAIRE] [PubMed] [DOI]

Easterling, D. R. (2000). Climate extremes: Observations, modeling, and impacts. Science, 289, 2068–2074. 10.1126/science.289.5487.2068 11000103 [OpenAIRE] [PubMed] [DOI]

Eigenbrod, F., Gonzalez, P., Dash, J., & Steyl, I. (2015). Vulnerability of ecosystems to climate change moderated by habitat intactness. Global Change Biology, 21, 275–286. 10.1111/gcb.12669 25059822 [OpenAIRE] [PubMed] [DOI]

Fountain, T., Husby, A., Nonaka, E., DiLeo, M. F., Korhonen, J. H., Rastas, P., … Hanski, I. (2017). Inferring dispersal across a fragmented landscape using reconstructed families in the Glanville fritillary butterfly. Evolutionary Applications, 11, 287–297. 10.1111/eva.12552 [OpenAIRE] [DOI]

89 references, page 1 of 6
Abstract
Abstract Habitat fragmentation and climate change are both prominent manifestations of global change, but there is little knowledge on the specific mechanisms of how climate change may modify the effects of habitat fragmentation, for example, by altering dynamics of spatially structured populations. The long‐term viability of metapopulations is dependent on independent dynamics of local populations, because it mitigates fluctuations in the size of the metapopulation as a whole. Metapopulation viability will be compromised if climate change increases spatial synchrony in weather conditions associated with population growth rates. We studied a recently reported in...
Subjects
free text keywords: Ecology, Global and Planetary Change, General Environmental Science, Environmental Chemistry, Precipitation, Metapopulation, Climate change, Biological dispersal, Butterfly, Land use, Life history, Biodiversity, Biology, Primary Research Article, Primary Research Articles, dispersal, Lepidoptera, Melitaea cinxia, metapopulation dynamics, population synchrony, temperature, trophic interactions
Related Organizations
Funded by
EC| META-STRESS
Project
META-STRESS
Unravelling life-history responses and underlying mechanisms to environmental stress in wild populations
  • Funder: European Commission (EC)
  • Project Code: 637412
  • Funding stream: H2020 | ERC | ERC-STG
,
AKA| Interplay between ecology and genetics in shaping immunity in natural populations
Project
  • Funder: Academy of Finland (AKA)
  • Project Code: 273098
,
AKA| Finnish CoE in Metapopulation Research
Project
  • Funder: Academy of Finland (AKA)
  • Project Code: 213457
89 references, page 1 of 6

Aalto, J., Pirinen, P., & Jylhä, K. (2016). New gridded daily climatology of Finland: Permutation‐based uncertainty estimates and temporal trends in climate. Journal of Geophysical Research: Atmospheres, 121, 3807–3823. 10.1002/2015JD024651 [DOI]

Alexander, L., & Perkins, S. (2013). Debate heating up over changes in climate variability. Environmental Research Letters, 8, 41001 10.1088/1748-9326/8/4/041001 [OpenAIRE] [DOI]

Allstadt, A. J., Liebhold, A. M., Johnson, D. M., Davis, R. E., & Haynes, K. J. (2015). Temporal variation in the synchrony of weather and its consequences for spatiotemporal population dynamics. Ecology, 96, 2935–2946. 10.1890/14-1497.1 27070013 [OpenAIRE] [PubMed] [DOI]

Bjørnstad, O. N., Ims, R. A., & Lambin, X. (1999). Spatial population dynamics: Analyzing patterns and processes of population synchrony. Trends in Ecology and Evolution, 14, 427–432. 10.1016/S0169-5347(99)01677-8 10511718 [PubMed] [DOI]

Bonsal, B. R., Zhang, X., Vincent, L. A., & Hogg, W. D. (2001). Characteristics of daily and extreme temperatures over Canada. Journal of Climate, 14, 1959–1976. 10.1175/1520-0442(2001)014<1959:CODAET>2.0.CO;2 [DOI]

Bürkner, P.‐C. (2017). brms: An R package for Bayesian multilevel models using Stan. Journal of Statistical Software, 80, 1–28. https://doi.org/10.18637/jss.v080.i01

Carpenter, B., Gelman, A., Hoffman, M. D., Lee, D., Goodrich, B., & Betancourt, M., … Riddell, A. (2017). Stan: A probabilistic Programming Language. Journal of Statistical Software, 76, 1–32. https://doi.org/10.18637/jss.v076.i01

Chevalier, M., Laffaille, P., Ferdy, J. B., & Grenouillet, G. (2015). Measurements of spatial population synchrony: Influence of time series transformations. Oecologia, 179, 15–28. 10.1007/s00442-015-3331-5 25953116 [OpenAIRE] [PubMed] [DOI]

Clark, J. S., Silman, M., Kern, R., Macklin, E., & HilleRisLambers, J. (1999). Seed dispersal near and far: Patterns across temperate and tropical forests. Ecology, 80, 1475–1949. 10.1890/0012-9658(1999)080[1475:SDNAFP]2.0.CO;2 [DOI]

Cormont, A., Malinowska, A. H., Kostenko, O., Radchuk, V., Hemerik, L., WallisDeVries, M. F., & Verboom, J. (2011). Effect of local weather on butterfly flight behaviour, movement, and colonization: Significance for dispersal under climate change. Biodiversity and Conservation, 20, 483–503. 10.1007/s10531-010-9960-4 [OpenAIRE] [DOI]

Defriez, E. J., & Reuman, D. C. (2017). A global geography of synchrony for terrestrial vegetation. Global Ecology and Biogeography, 26, 878–888. 10.1111/geb.12595 [OpenAIRE] [DOI]

Defriez, E. J., Sheppard, L. W., Reid, P. C., & Reuman, D. C. (2016). Climate change‐related regime shifts have altered spatial synchrony of plankton dynamics in the North Sea. Global Change Biology, 22, 2069–2080. 10.1111/gcb.13229 26810148 [OpenAIRE] [PubMed] [DOI]

Easterling, D. R. (2000). Climate extremes: Observations, modeling, and impacts. Science, 289, 2068–2074. 10.1126/science.289.5487.2068 11000103 [OpenAIRE] [PubMed] [DOI]

Eigenbrod, F., Gonzalez, P., Dash, J., & Steyl, I. (2015). Vulnerability of ecosystems to climate change moderated by habitat intactness. Global Change Biology, 21, 275–286. 10.1111/gcb.12669 25059822 [OpenAIRE] [PubMed] [DOI]

Fountain, T., Husby, A., Nonaka, E., DiLeo, M. F., Korhonen, J. H., Rastas, P., … Hanski, I. (2017). Inferring dispersal across a fragmented landscape using reconstructed families in the Glanville fritillary butterfly. Evolutionary Applications, 11, 287–297. 10.1111/eva.12552 [OpenAIRE] [DOI]

89 references, page 1 of 6
Powered by OpenAIRE Open Research Graph
Any information missing or wrong?Report an Issue
publication . Article . Other literature type . 2018

Metapopulation dynamics in a changing climate: Increasing spatial synchrony in weather conditions drives metapopulation synchrony of a butterfly inhabiting a fragmented landscape

Kahilainen, Aapo; van Nouhuys, Saskya; Schulz, Torsti; Saastamoinen, Marjo;