Abstract 2018: Arctic researchers have just witnessed another extreme summer—but in a new sense of the word. Although public interest has long been focused on general warming trends and trends towards a lower sea ice cover in the Arctic Ocean, this summer saw the realization of another predicted trend: that of increasing precipitation during the winter months and of increased year-to-year variability. In a well-studied ecosystem in Northeast Greenland, this resulted in the most complete reproductive failure encountered in the terrestrial ecosystem during more than two decades of monitoring: only a few animals and plants were able to reproduce because of abundant and late melting snow. These observations, we suggest, should open our eyes to potentially drastic consequences of predicted changes in both the mean and the variability of arctic climate.

Citation: Schmidt NM, Reneerkens J, Christensen JH, Olesen M, Roslin T (2019) An ecosystem-wide reproductive failure with more snow in the Arctic. PLoS Biol 17(10): e3000392. https://doi.org/10.1371/journal.pbio.3000392 Published: October 15, 2019 Copyright: © 2019 Schmidt et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: Climate data presented in Fig 1 are available at http://prudence.dmi.dk/data/temp/MOL/PLOS, while data presented in Figs 2 and 3 are available at https://doi.org/10.5281/zenodo.3344483. Funding: The Danish Environmental Protection Agency and the Danish Energy Agency are thanked for their financial support over the years. JR was supported by an International Polar Year grant and a Netherlands Polar Programme grant (NWO grants 851.30.008 and 866.15.207) and INTERACT grants for Transnational Access from the European Community's Seventh Framework Programme under grant agreement No 262693. JHC and MOL received funding from the European Research Council under the EU FP7 / ERC grant agreement 610055 as part of the ice2ice project. TR was funded by the Academy of Finland (grants 276909 and 285803). 'The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. Provenance: Not commissioned; externally peer reviewed.

Climate change is not just “warming” Around the world, temperatures are increasing. To predict the consequences for local ecosystems, we typically rely on the assumption that we can predict future conditions from current trends, and that with climate change, species and communities will follow their climatic envelopes in an orderly manner [1]. Yet, at least three considerations complicate this paradigm: First, current predictions involve changes in both the mean and the variance of climatic parameters [2–4]. Here, changes in the variance may have as important ecological consequences as changes in the mean. Second, although scenario analyses tend to focus on predictions regarding temperature, current predictions of climate change posit that many other parameters will change, too—most notably precipitation in many parts of the world [4,5]. Of arctic ecosystems, many are limited by snow conditions and water availability [6], and changes in precipitation may prove as crucial as changes in temperature—if not even more. Third, many current predictions are based on the idea of gradual, directional change, thus allowing for simple extrapolation of ecological effects (e.g., [7]). However, recent history includes many examples of so called tipping points [8–10], in which a relatively subtle change in conditions abruptly flips the system from one state to another. Such shifts may be hard to foresee, and their consequences impossible to assess from past experience.

The arctic extreme of 2018 The summer of 2018 underscored all three concerns. Beyond the general trend of warmer and earlier summers and a retreating snow cover [11], large parts of the Arctic, and in particular, the High Arctic, were covered by unusually large amounts of snow in 2018 (Fig 1). This pattern was particularly evident in Northeast Greenland (Fig 1) and at the research station of Zackenberg (Fig 1), where the local snow precipitation deviated from long-term mean conditions by several standard deviations. At Zackenberg, this resulted in snow melt being extraordinarily delayed. PPT PowerPoint slide

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larger image TIFF original image Download: Fig 1. The 2018 snow cover compared with long-term precipitation patterns in the Arctic. The three maps show the deviation (in units of standard deviations) of the 2018 season from the 1980 to 2018 normalized precipitation curve on the Pan-Arctic scale (left), the Greenland scale (top middle), and the Zackenberg region (top right), with the black circle marking Zackenberg. For each year, snow precipitation was calculated as total precipitation in November through April, obtained from a high-resolution data-assimilation system and a regional climate model (see Supporting information). The lower right panel shows the annual deviation (in units of standard deviations) from the normalized precipitation curve in the Zackenberg drainage basin from 1980 to 2018. Additional information about data and analyses can be found in S1 Data collection and analyses. Data presented here are available at http://prudence.dmi.dk/data/temp/MOL/PLOS. https://doi.org/10.1371/journal.pbio.3000392.g001 The conditions of 2018 obviously comprise only a single annual data point along a long-term, noisy trajectory. Thus, we do not want to overinterpret a single observation in one location but merely to relate the events of 2018 to a long-term, ecosystem-level perspective—pointing to what more years with more extreme snow conditions may cause, not least if they increase in frequency. Here, monitoring sites, such as Zackenberg in Northeast Greenland [12], offer crucial time series of biota over many years. Where robust, mechanistic climate predictions can be made based on the law of physics, predictions of ecological consequences of altered climatic conditions are likely to be far more inaccurate [13]. Thus, ecosystem-level monitoring sites allow us to examine trends and variability and to quantify the ecological consequences of extreme events, such as the 2018 snow situation.

Implications for the ecosystem Arctic plants and animals are well adapted to life under extreme climatic conditions [22], and their longevity and temporally dispersed reproductive bouts [23] enable them to cope with the large variability in environmental conditions, both within seasons and between years. Therefore, one nonbreeding year like the one observed in 2018 is hardly devastating for High Arctic species. The worrying perspective here is that the 2018 conditions may offer a peep into the future: Climate change has already resulted in a variety of species and ecosystem-level responses of arctic organisms [11,14]. With less sea ice in the Arctic, we can expect more and more variable amounts of snow in the future [4,24]. It is now well established that climate change includes increased variance in climatic conditions [4]. As a consequence, more extreme events like the 2018 situation in Northeast Greenland may soon be occurring more often than before. Some extreme events are unique, as for instance, the circumarctic reproductive collapse among shorebirds reported following a volcano eruption in 1992 [16]. Being unlinked to climate change, volcano eruptions will hardly increase in frequency in a changing Arctic. What may increase is the occurrence of extreme snow years like 2018, of rain-on-snow events [25,26], and of episodic snow melt events [27]. A higher incidence of such events may be a game changer for the population dynamics within High Arctic ecosystems, because frequent years with reproductive failure is an issue far more serious than a single event [18,28]. In particular, the consequences are likely to be aggravated among shorter-lived species [22] whose population dynamics is predominantly determined by reproduction [e.g. 29]. However, many arctic plant species are perennials and may reproduce over many—sometimes very many [30]—seasons. Similarly, to the extent that their life cycle is known, a majority of arctic arthropod species has a multiyear life cycle, or emerge from diapause over multiple years, thus reducing the risk of negative population impacts [31]. The overall impacts of extreme events are therefore critically dependent on their frequency and on the conditions in between them. Importantly, frequent extreme events may not only pose a threat to arctic ecosystems as we know them today but may also contribute to stabilizing population dynamics [32] and to preserving the status quo of Artic communities: With increasing temperatures, more low-latitude species are expected to move north [11], but such species may be less tolerant to the extreme conditions encountered in the Arctic. Extreme events may thus contribute to prevent them from establishing populations there, a suggestion that we should seek to monitor.

Implications for arctic research In combination with climate modelling, our unique long-term monitoring data from Zackenberg allow us to evaluate the rareness of the snow conditions in year 2018, to quantify their ecological consequences across multiple taxa and trophic levels, and to detect changes in their frequency over time. Coherent, continuous monitoring of the arctic ecosystems is thus a prerequisite for our ability to actually characterize rare or extreme events and for understanding the likely ecological consequences of such events in a future arctic climate. Our findings from 2018 have brought forth three insights: First, we need to invest equal interest in the variance as in the mean, and this concerns both abiotic and biotic parameters [33]. Second, we should supplement our interest in shifts in temperature with an added focus on shifts in precipitation. Finally, we should step up our efforts to document the dynamics of the High Arctic ecosystem, keeping in mind that sudden shifts in the state of the ecosystem are a possibility. Although our observations from a single High Arctic ecosystem may be considered scanty, they are by far the best ecosystem data available from the region. They suggest that extreme events like the one of 2018 will affect all parts of the arctic ecosystems.

Acknowledgments Data were provided by the Greenland Ecosystem Monitoring Programme. We thank Aarhus University for logistical support.