The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
A model quantifying global vegetation resistance and resilience to short‐term climate anomalies and their relationship with vegetation cover
Abstract
Aim: In order to mitigate the ecological, economical and social consequences of future climate change, we must understand and quantify the response of vegetation to short‐term climate anomalies. There is currently no model that quantifies vegetation resistance and resilience at a global scale while simultaneously taking climate variability into account. The goals of this study were therefore to develop a standardized indicator of short‐term vegetation resilience and resistance to drought and temperature anomalies, and to improve our understanding of vegetation resistance and resilience in drought‐sensitive areas by linking metrics of vegetation stability to the percentage of tree cover, non‐tree vegetation and bare soil. Location: Global. Methods: The deviation of vegetation behaviour from expectations was quantified using anomalies in the normalized difference vegetation index (NDVI) and modelled as a function of (1) past NDVI anomalies, (2) an instantaneous drought indicator and (3) temperature anomalies. Metrics of resistance and resilience were then extracted from the model and related to the percentages of bare soil, non‐tree vegetation and tree cover. Results: Comparisons of the globally derived resilience and resistance metrics showed low resilience and low resistance to drought in semi‐arid areas, low resistance to negative temperature anomalies in high‐latitude areas, and low resistance to positive temperature anomalies in the Sahel and A ustralia. In drought‐sensitive areas, resilience was highest for vegetation types with 3–20% bare soil and 5–15% tree cover. Main conclusions: Our ARx model is the first to simultaneously derive vegetation resistance and resilience metrics at a global scale, explicitly taking into account the spatial variability of short‐term climate anomalies and data reliability. Its results highlight the impact of tree cover, non‐tree vegetation and bare soil on vegetation resilience.
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Estimating the Dimension of a Model
Schwarz, G. (1978) · The Annals of Statistics · doi:10.1214/aos/1176344136 · Cited by 47,033
Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010) · Journal of Climate · doi:10.1175/2009jcli2909.1 · Cited by 9,493
Allen, C. D., Macalady, A. K., Chenchouni, H., Bachelet, D., McDowell, N., Vennetier, M., Kitzberger, T., Rigling, A., Breshears, D. D., Hogg, E. H. (., et al. (2010) · Forest Ecology and Management · doi:10.1016/j.foreco.2009.09.001 · Cited by 7,763
McDowell, N., Pockman, W. T., Allen, C. D., Breshears, D. D., Cobb, N., Kolb, T., Plaut, J., Sperry, J., West, A., Williams, D. G., et al. (2008) · New Phytologist · doi:10.1111/j.1469-8137.2008.02436.x · Cited by 4,472
Climate-Driven Increases in Global Terrestrial Net Primary Production from 1982 to 1999
Nemani, R. R., Keeling, C. D., Hashimoto, H., Jolly, W. M., Piper, S. C., Tucker, C. J., Myneni, R. B., & Running, S. W. (2003) · Science · doi:10.1126/science.1082750 · Cited by 3,671
Characteristics of maximum-value composite images from temporal AVHRR data
HOLBEN, B. N. (1986) · International Journal of Remote Sensing · doi:10.1080/01431168608948945 · Cited by 3,002
An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data
Tucker, C. J., Pinzon, J. E., Brown, M. E., Slayback, D. A., Pak, E. W., Mahoney, R., Vermote, E. F., & El Saleous, N. (2005) · International Journal of Remote Sensing · doi:10.1080/01431160500168686 · Cited by 2,305
New, M., Hulme, M., & Jones, P. (2000) · Journal of Climate · doi:10.1175/1520-0442(2000)013<2217:rtcstc>2.0.co;2 · Cited by 2,097
Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data
Myneni, R. B., Hoffman, S., Knyazikhin, Y., Privette, J. L., Glassy, J., Tian, Y., Wang, Y., Song, X., Zhang, Y., Smith, G. R., et al. (2002) · Remote Sensing of Environment · doi:10.1016/s0034-4257(02)00074-3 · Cited by 1,989
Response of vegetation to drought time-scales across global land biomes
Vicente-Serrano, S. M., Gouveia, C., Camarero, J. J., Beguería, S., Trigo, R., López-Moreno, J. I., Azorín-Molina, C., Pasho, E., Lorenzo-Lacruz, J., Revuelto, J., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1207068110 · Cited by 1,675
Cited by
Sensitivity of global terrestrial ecosystems to climate variability
Seddon, A. W. R., Macias-Fauria, M., Long, P. R., Benz, D., & Willis, K. J. (2016) · Nature · doi:10.1038/nature16986 · Cited by 1,373
Empirical evidence for recent global shifts in vegetation resilience
Smith, T., Traxl, D., & Boers, N. (2022) · Nature Climate Change · doi:10.1038/s41558-022-01352-2 · Cited by 298
Metadata
- Authors
- De Keersmaecker, W., Lhermitte, S., Tits, L., Honnay, O., Somers, B., & Coppin, P.
- Venue
- Global Ecology and Biogeography
- Publisher
- Wiley
- Published
- 2015-02-02
- Volume
- 24
- Issue
- 5
- Pages
- 539-548
- ISSN
- 1466-822X (ISSN-L)
- 1466-8238
- OpenAlex
- W1494272296
- Cited by
- 283
- References
- 39
- FWCI
- 10.20
- Type
- journal article
- Language
- en
- Open access
- closed
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- De Keersmaecker, W., Lhermitte, S., Tits, L., Honnay, O., Somers, B., & Coppin, P. (2015). A model quantifying global vegetation resistance and resilience to short‐term climate anomalies and their relationship with vegetation cover. Global Ecology and Biogeography. https://doi.org/10.1111/geb.12279
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