Predicting bird phenology from space: Satellite-derived vegetation green-up signal uncovers spatial variation in phenological synchrony between birds and their environment

Ecology and Evolution

Volumn 5, Issue 21, 2015, Pages 5057-5074

  Cole, Ella F ^a   Long, Peter R ^a   Zelazowski, Przemyslaw ^a,b   Szulkin, Marta ^a,c   Sheldon, Ben C ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b UNIVERSITY OF WARSAW   (Poland)

^c CENTRE D ECOLOGIE FONCTIONNELLE ET EVOLUTIVE   (France)

Author keywords

Blue tit; Environmental heterogeneity; EVI; Great tit; Mismatch; MODIS; Reproductive phenology; Satellite derived; Spatial scale; Wild population

Indexed keywords

EID: 84945924607     PISSN: None     EISSN: 20457758     Source Type: Journal    
DOI: 10.1002/ece3.1745     Document Type: Article

References (60)

1. Anderson, K., and K. J. Gaston. 2013. Lightweight unmanned aerial vehicles will revolutionize spatial ecology. Front. Ecol. Environ. 11:138-146.
2. van Asch, M., and M. E. Visser. 2007. Phenology of forest caterpillars and their host trees: the importance of synchrony. Annu. Rev. Entomol. 52:37-55.
3. Bro-Jørgensen, J., M. E. Brown, and N. Pettorelli. 2008. Using the satellite-derived normalized difference vegetation index (NDVI) to explain ranging patterns in a lek-breeding antelope: the importance of scale. Oecologia 158:177-182.
4. Busetto, L., R. Colombo, M. Migliavacca, E. Cremonese, M. Meroni, M. Galvagno, et al. 2010. Remote sensing of larch phenological cycle and analysis of relationships with climate in the Alpine region. Glob. Change Biol. 16:2504-2517.
5. Chabot, D., and D. M. Bird. 2013. Small unmanned aircraft: precise and convenient new tools for surveying wetlands. J. Unmanned Vehicle Syst. 1:15-24.
6. Charmantier, A., R. H. McCleery, L. R. Cole, C. Perrins, L. E. B. Kruuk, and B. C. Sheldon. 2008. Adaptive phenotypic plasticity in response to climate change in a wild bird population. Science 320:800-803.
7. Chen, J. M., C. H. Menges, and S. G. Leblanc. 2005. Global mapping of foliage clumping index using multi-angular satellite data. Remote Sens. Environ. 97:447-457.
8. Chevin, L. M., R. Lande, and G. M. Mace. 2010. Adaptation, plasticity, and extinction in a changing environment: towards a predictive theory. PLoS Biol. 8:e1000357.
9. Cleland, E. E., I. Chuine, A. Menzel, H. A. Mooney, and M. D. Schwartz. 2007. Shifting plant phenology in response to global change. Trends Ecol. Evol. 22:357-365.
10. Crawley, M. J., and M. Akhteruzzaman. 1988. Individual variation in the phenology of oak trees and its consequences for herbivorous insects. Funct. Ecol. 2:409-415.
11. Durant, J. M., D. Ø. Hjermann, G. Ottersen, and N. C. Stenseth. 2007. Climate and the match or mismatch between predator requirements and resource availability. Clim. Res. 33:271-283.
12. Feeny, P. 1970. Seasonal changes in oak leaf tannins and nutrients as a cause of spring feeding by winter moth caterpillars. Ecology 51:565-581.
13. Fisher, J. I., J. F. Mustard, and M. A. Vadeboncoeur. 2006. Green leaf phenology at Landsat resolution: Scaling from the field to the satellite. Remote Sens. Environ. 100:265-279.
14. Gibb, J. 1954. Feeding ecology of tits, with notes on treecreeper and goldcrest. The Ibis 96:513-543.
15. Gienapp, P., C. Teplitsky, J. S. Alho, J. A. Mills, and J. Merilä. 2008. Climate change and evolution: disentangling environmental and genetic responses. Mol. Ecol. 17:167-178.
16. Hastie, T. J., and R. J. Tibshirani. 1990. Generalized additive models. Chapman and Hall, London.
17. Hinks, A. E., E. F. Cole, K. Fannon, T. A. Wilkin, S. Nakagawa, and B. C. Sheldon. 2015. Scale-dependent phenology synchrony between songbirds and their caterpillar food source. Am. Nat. doi:10.1086/681572.
18. Hoffmann, A. A., and C. M. Sgrò. 2011. Climate change and evolutionary adaptation. Nature 470:479-485.
19. Hufkens, K., M. Friedl, O. Sonnentag, B. H. Braswell, T. Milliman, and A. D. Richardson. 2012. Linking near-surface and satellite remote sensing measurements of deciduous broadleaf forest phenology. Remote Sens. Environ. 117:307-321.
20. Hunter, A. F., and M. J. Lechowicz. 1992. Predicting the timing of budburst in temperate trees. J. Appl. Ecol. 29:597-604.
21. Hurley, M. A., M. Hebblewhite, J. M. Gaillard, S. Dray, K. A. Taylor, W. K. Smith, et al. 2014. Functional analysis of Normalized Difference Vegetation Index curves reveals overwinter mule deer survival is driven by both spring and autumn phenology. Philos. Trans. R. Soc. B Biol. Sci. 369:20130196.
22. Jiang, Z., A. R. Huete, K. Didan, and T. Miura. 2008. Development of a two-band enhanced vegetation index without a blue band. Remote Sens. Environ. 112:3833-3845.
23. Jönsson, P., and L. Eklundh. 2004. TIMESAT-a program for analyzing time-series of satellite sensor data. Comput. Geosci. 30:833-845.
24. Kerr, J. T., and M. Ostrovsky. 2003. From space to species: ecological applications for remote sensing. Trends Ecol. Evol. 18:299-305.
25. Levin, S. A. 1992. The problem of pattern and scale in ecology: the Robert H MacArthur award lecture. Ecology 73:1943-1967.
26. McCleery, R. H., R. A. Pettifor, P. Armbruster, K. Meyer, B. C. Sheldon, and C. M. Perrins. 2004. Components of variance underlying fitness in a natural population of the great tit Parus major. Am. Nat. 164:E62-E72.
27. Merilä, J., and A. P. Hendry. 2014. Climate change, adaptation, and phenotypic plasticity: the problem and the evidence. Evol. Appl. 7:1-14.
28. Moyes, K., D. H. Nussey, M. N. Clements, F. E. Guinness, A. Morris, S. Morris, et al. 2011. Advancing reproductive phenology in response to environmental change in a wild red deer population. Glob. Change Biol. 17:2455-2469.
29. Nager, R. G., and A. J. van Noordwijk. 1995. Proximate and ultimate aspects of phenotypic plasticity in timing of great tit breeding in a heterogeneous environment. Am. Nat. 146:454-474.
30. NASA Land Processes Distributed Active Archive Center (LP DAAC) MOD09Q1 and MYD09Q1. USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, 2008.
31. van Noordwijk, A. J., R. H. McCleery, and C. M. Perrins. 1995. Selection for the timing of great tit breeding in relation to caterpillar growth and temperature. J. Anim. Ecol. 64:451-458.
32. Packalén, P., and M. Maltamo. 2007. The k-MSN method for the prediction of species-specific stand attributes using airborne laser scanning and aerial photographs. Remote Sens. Environ. 109:328-341.
33. Parmesan, C., and G. Yohe. 2003. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421:37-42.
34. Perrins, C. M. 1965. population fluctuations and clutch-size in the great tit, Parus major L. J. Anim. Ecol. 34:601-647.
35. Pettorelli, N., J. O. Vik, A. Mysterud, J. M. Gaillard, C. J. Tucker, and N. C. Stenseth. 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends Ecol. Evol. 20:503-510.
36. Pettorelli, N., S. Ryan, T. Mueller, N. Bunnefeld, B. Jedrzejewska, M. Lima, et al. 2011. The Normalized Difference Vegetation Index (NDVI): unforeseen successes in animal ecology. Clim. Res. 46:15-27.
37. van de Pol, M., and J. Wright. 2009. A simple method for distinguishing within-versus between-subject effects using mixed models. Anim. Behav. 77:753-758.
38. Réale, D., A. G. McAdam, S. Boutin, and D. Berteaux. 2003. Genetic and plastic responses of a northern mammal to climate change. Proc. R. Soc. B Biol. Sci. 270:591-596.
39. Reed, B. C., J. F. Brown, D. Vander Zee, T. R. Loveland, J. W. Merchant, and D. O. Ohlen. 1994. Measuring phenological variability from satellite imagery. J. Veg. Sci. 5:703-714.
40. Roberts, A. M., C. Tansey, R. J. Smithers, and A. B. Phillimore. 2015. Predicting a change in the order of spring phenology in temperate forests. Glob. Chang. doi:10.1111/gcb.12896.
41. Root, T. L., J. T. Price, K. R. Hall, S. H. Schneider, C. Rosenzweig, and J. A. Pounds. 2003. Fingerprints of global warming on wild animals and plants. Nature 421:57-60.
42. Roughgarden, J., S. W. Running, P. A. Matson, and N. Dec. 1991. What does remote sensing do for ecology? Ecology 72:1918-1922.
43. Sanz, J. J., J. Potti, J. Moreno, S. Merino, and O. S. C. A. R. FRÍAs. 2003. Climate change and fitness components of a migratory bird breeding in the Mediterranean region. Glob. Change Biol. 9:461-472.
44. Scambos, T. A., T. M. Haran, M. A. Fahnestock, T. H. Painter, and J. Bohlander. 2007. MODIS-based Mosaic of Antarctica (MOA) data sets: Continent-wide surface morphology and snow grain size. Remote Sens. Environ. 111:242-257.
45. Smith, T. B., R. J. Harrigan, A. N. Kirschel, W. Buermann, S. Saatchi, D. T. Blumstein, et al. 2013. Predicting bird song from space. Evol. Appl., 6:865-874.
46. Soudani, K., G. le Maire, E. Dufrêne, C. François, N. Delpierre, E. Ulrich, et al. 2008. Evaluation of the onset of green-up in temperate deciduous broadleaf forests derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data. Remote Sens. Environ., 112:2643-2655.
47. Stauss, M. J., J. F. Burkhardt, and J. Tomiuk. 2005. Foraging flight distances as a measure of parental effort in blue tits Parus caeruleus differ with environmental conditions. J. Avian Biol. 36:47-56.
48. Svensson, L. 1994. Identification guide to European passerines. Svensson, Stockholm.
49. Szulkin, M., P. Zelazowski, P. Marrot, and A. Charmantier. 2015. Application of High Resolution Satellite Imagery to Characterize Individual-Based Environmental Heterogeneity in a Wild Blue Tit Population. Remote Sens. 7:13319-13336. doi:10.3390/rs71013319.
50. Thackeray, S. J., T. H. Sparks, M. Frederiksen, S. Burthe, P. J. Bacon, J. R. Bell, et al. 2010. Trophic level asynchrony in rates of phenological change for marine, freshwater and terrestrial environments. Glob. Change Biol. 16:3304-3313.
51. Tveraa, T., A. Stien, B. J. Bårdsen, and P. Fauchald. 2013. Population densities, vegetation green-up, and plant productivity: impacts on reproductive success and juvenile body mass in reindeer. PLoS ONE 8:e56450.
52. Verhulst, S., and J. M. Tinbergen. 1991. Experimental evidence for a causal relationship between timing and success of reproduction in the great tit Parus m. major. J. Anim. Ecol. 60:269-282.
53. Visser, M. E., A. J. van Noordwijk, J. M. Tinbergen, and C. M. Lessells. 1998. Warmer springs lead to mistimed reproduction in great tits (Parus major). Proc. R. Soc. B Biol. Sci. 265:1867-1870.
54. Wesołowski, T., and P. Rowiński. 2006. Timing of bud burst and tree-leaf development in a multispecies temperate forest. For. Ecol. Manage. 237:387-393.
55. Wilkin, T. A., and B. C. Sheldon. 2009. Sex differences in the persistence of natal environmental effects on life histories. Curr. Biol. 19:1998-2002.
56. Wilkin, T. A., D. Garant, A. G. Gosler, and B. C. Sheldon. 2007. Edge effects in the great tit: analyses of long-term data with GIS techniques. Conserv. Biol. 21:1207-1217.
57. Wint, W. 1983. The role of alternative host-plant species in the life of a polyphagous moth, Operophtera brumata (Lepidoptera: Geometridae). J. Anim. Ecol. 52:439-450.
58. Wood, S. N. 2011. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. (B) 73:3-36.
59. Wood, M. J., C. L. Cosgrove, T. A. Wilkin, S. C. Knowles, K. P. Day, and B. C. Sheldon. 2007. Within-population variation in prevalence and lineage distribution of avian malaria in blue tits, Cyanistes caeruleus. Mol. Ecol. 16:3263-3273.
60. Zhang, X., M. A. Friedl, C. B. Schaaf, A. H. Strahler, J. C. Hodges, F. Gao, et al. 2003. Monitoring vegetation phenology using MODIS. Remote Sens. Environ. 84:471-475.