Publication details
Extending the climatological concept of'Detection and Attribution' to global change ecology in the Anthropocene
| Authors | |
|---|---|
| Year of publication | 2020 |
| Type | Article in Periodical |
| Magazine / Source | Functional Ecology |
| MU Faculty or unit | |
| Citation | |
| Web | https://doi.org/10.1111/1365-2435.13647 |
| Doi | http://dx.doi.org/10.1111/1365-2435.13647 |
| Keywords | anthropogenic climate change; cyclic population dynamics; detection and attribution; global change ecology; inference-based ecological modelling; larch budmoth system |
| Description | Research 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. 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 dinianaorgriseanaGn.); the classic example of a cyclic forest defoliating insect. 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. 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. A freePlain Language Summarycan be found within the Supporting Information of this article. |