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Título

Extending the climatological concept of `Detection and Attribution¿ to global change ecology in the Anthropocene

AutorBüntgen, U.; González-Rouco, J. F. CSIC ORCID; Jürg Luterbacher; Nils Christian Stenseth; Derek M. Johnson
Palabras claveAnthropogenic
Climate change
Cyclic population dynamics
Detection and attribution
Global change ecology
Inference-based ecological modelling
Larch budmoth system
Fecha de publicación2020
EditorBlackwell Publishing
CitaciónFunctional Ecology 34: 2270- 2282 (2020)
ResumenResearch into global change ecology is motivated by the need to understand the role of humans in changing biotic systems. Mechanistic understanding of ecological responses requires the separation of different climatic parameters and processes that often operate on diverse spatiotemporal scales. Yet most environmental studies do not distinguish the effects of internal climate variability from those caused by external, natural (e.g. volcanic, solar, orbital) or anthropogenic (e.g. greenhouse gases, ozone, aerosols, land-use) forcing factors. 2. We suggest extending the climatological concept of `Detection and Attribution¿ (DA) to unravel abiotic drivers of ecological dynamics in the Anthropocene. We therefore apply DA to quantify the relative roles of natural versus industrial temperature change on elevational shifts in the outbreak epicentres of the larch budmoth (LBM; Zeiraphera diniana or griseana Gn.); the classic example of a cyclic forest defoliating insect. 3. Our case study shows that anthropogenic warming shifts the epicentre of travelling LBM waves upward, which disrupts the intensity of population outbreaks that occurred regularly over the past millennium in the European Alps. Our findings demonstrate the ability of DA to detect ecological responses beyond internal system variability, to attribute them to specific external climate forcing factors and to identify climate-induced ecological tipping points. 4. In order to implement the climatological concept of `Detection and Attribution¿ successfully into modern global change ecology, future studies should combine high-resolution paleoenvironmental reconstructions and state-of-the-art climate model simulations to inform inference-based ecosystem models
Versión del editorhttp://dx.doi.org/10.1111/1365-2435.13647
URIhttp://hdl.handle.net/10261/228098
DOI10.1111/1365-2435.13647
Identificadoresdoi: 10.1111/1365-2435.13647
issn: 0269-8463
Aparece en las colecciones: (IGEO) Artículos




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