Human-induced fire regime shifts during 19th century industrialization: A robust fire regime reconstruction using northern Polish lake sediments

Fire regime shifts are driven by climate and natural vegetation changes, but can be strongly affected by human land management. Yet, it is poorly known how humans have influenced fire regimes prior to active wildfire suppression. Among the last 250 years, the human contribution to the global increase in fire occurrence during the mid-19th century is especially unclear, as data sources are limited. Here, we test the extent to which forest management has driven fire regime shifts in a temperate forest landscape. We combine multiple fire proxies (macroscopic charcoal and fire-related biomarkers) derived from highly resolved lake sediments (i.e., 3–5 years per sample), and apply a new statistical approach to classify source area- and temperature-specific fire regimes (biomass burnt, fire episodes). We compare these records with independent climate and vegetation reconstructions. We find two prominent fire regime shifts during the 19th and 20th centuries, driven by an adaptive socio-ecological cycle in human forest management. Although individual fire episodes were triggered mainly by arson (as described in historical documents) during dry summers, the biomass burnt increased unintentionally during the mid-19th century due to the plantation of flammable, fast-growing pine tree monocultures needed for industrialization. State forest management reacted with active fire management and suppression during the 20th century. However, pine cover has been increasing since the 1990s and climate projections predict increasingly dry conditions, suggesting a renewed need for adaptations to reduce the increasing fire risk. © 2019 Dietze 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

Beyond in-phase and anti-phase coordination in a model of joint action

In 1985, Haken, Kelso and Bunz proposed a system of coupled nonlinear oscillators as a model of rhythmic movement patterns in human bimanual coordination. Since then, the Haken–Kelso–Bunz (HKB) model has become a modelling paradigm applied extensively in all areas of movement science, including interpersonal motor coordination. However, all previous studies have followed a line of analysis based on slowly varying amplitudes and rotating wave approximations. These approximations lead to a reduced system, consisting of a single differential equation representing the evolution of the relative phase of the two coupled oscillators: the HKB model of the relative phase. Here we take a different approach and systematically investigate the behaviour of the HKB model in the full four-dimensional state space and for general coupling strengths. We perform detailed numerical bifurcation analyses and reveal that the HKB model supports previously unreported dynamical regimes as well as bistability between a variety of coordination patterns. Furthermore, we identify the stability boundaries of distinct coordination regimes in the model and discuss the applicability of our findings to interpersonal coordination and other joint action tasks

Regional variability in peatland burning at mid- to high-latitudes during the Holocene

Acknowledgements This work developed from the PAGES (Past Global Changes) C-PEAT (Carbon in Peat on EArth through Time) working group. PAGES has been supported by the US National Science Foundation, Swiss National Science Foundation, Swiss Academy of Sciences and Chinese Academy of Sciences. We acknowledge the following financial support: UK Natural Environment Research Council Training Grants NE/L002574/1 (T.G.S.) and NE/S007458/1 (R.E.F.); Dutch Foundation for the Conservation of Irish Bogs, Quaternary Research Association and Leverhulme Trust RPG-2021-354 (G.T.S); the Academy of Finland (M.V); PAI/SIA 80002 and FONDECYT Iniciación 11220705 - ANID, Chile (C.A.M.); R20F0002 (PATSER) ANID Chile (R.D.M.); Swedish Strategic Research Area (SRA) MERGE (ModElling the Regional and Global Earth system) (M.J.G.); Polish National Science Centre Grant number NCN 2018/29/B/ST10/00120 (K.A.); Russian Science Foundation Grant No. 19-14-00102 (Y.A.M.); University of Latvia Grant No. AAp2016/B041/Zd2016/AZ03 and the Estonian Science Council grant PRG323 (TrackLag) (N.S. and A.M.); U.S. Geological Survey Land Change Science/Climate Research & Development Program (M.J., L.A., and D.W.); German Research Foundation (DFG), grant MA 8083/2-1 (P.M.) and grant BL 563/19-1 (K.H.K.); German Academic Exchange Service (DAAD), grant no. 57044554, Faculty of Geosciences, University of Münster, and Bavarian University Centre for Latin America (BAYLAT) (K.H.K). Records from the Global Charcoal Database supplemented this work and therefore we would like to thank the contributors and managers of this open-source resource. We also thank Annica Greisman, Jennifer Shiller, Fredrik Olsson and Simon van Bellen for contributing charcoal data to our analyses. Any use of trade, firm, or product name is for descriptive purposes only and does not imply endorsement by the U.S. Government.Peer reviewedPostprin

Assessing changes in global fire regimes

PAGES, Past Global Changes, is funded by the Swiss Academy of Sciences and the Chinese Academy of Sciences and supported in kind by the University of Bern, Switzerland. Financial support was provided by the U.S. National Science Foundation award numbers 1916565, EAR-2011439, and EAR-2012123. Additional support was provided by the Utah Department of Natural Resources Watershed Restoration Initiative. SSS was supported by Brigham Young University Graduate Studies. MS was supported by National Science Centre, Poland (grant no. 2018/31/B/ST10/02498 and 2021/41/B/ST10/00060). JCA was supported by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 101026211. PF contributed within the framework of the FCT-funded project no. UIDB/04033/2020. SGAF acknowledges support from Trond Mohn Stiftelse (TMS) and University of Bergen for the startup grant ‘TMS2022STG03’. JMP participation in this research was supported by the Forest Research Centre, a research unit funded by Fundação para a Ciência e a Tecnologia I.P. (FCT), Portugal (UIDB/00239/2020). A.-LD acknowledge PAGES, PICS CNRS 06484 project, CNRS-INSU, Région Nouvelle-Aquitaine, University of Bordeaux DRI and INQUA for workshop support.Background The global human footprint has fundamentally altered wildfire regimes, creating serious consequences for human health, biodiversity, and climate. However, it remains difficult to project how long-term interactions among land use, management, and climate change will affect fire behavior, representing a key knowledge gap for sustainable management. We used expert assessment to combine opinions about past and future fire regimes from 99 wildfire researchers. We asked for quantitative and qualitative assessments of the frequency, type, and implications of fire regime change from the beginning of the Holocene through the year 2300. Results Respondents indicated some direct human influence on wildfire since at least ~ 12,000 years BP, though natural climate variability remained the dominant driver of fire regime change until around 5,000 years BP, for most study regions. Responses suggested a ten-fold increase in the frequency of fire regime change during the last 250 years compared with the rest of the Holocene, corresponding first with the intensification and extensification of land use and later with anthropogenic climate change. Looking to the future, fire regimes were predicted to intensify, with increases in frequency, severity, and size in all biomes except grassland ecosystems. Fire regimes showed different climate sensitivities across biomes, but the likelihood of fire regime change increased with higher warming scenarios for all biomes. Biodiversity, carbon storage, and other ecosystem services were predicted to decrease for most biomes under higher emission scenarios. We present recommendations for adaptation and mitigation under emerging fire regimes, while recognizing that management options are constrained under higher emission scenarios. Conclusion The influence of humans on wildfire regimes has increased over the last two centuries. The perspective gained from past fires should be considered in land and fire management strategies, but novel fire behavior is likely given the unprecedented human disruption of plant communities, climate, and other factors. Future fire regimes are likely to degrade key ecosystem services, unless climate change is aggressively mitigated. Expert assessment complements empirical data and modeling, providing a broader perspective of fire science to inform decision making and future research priorities.Peer reviewe

Recent climate change has driven divergent hydrological shifts in high-latitude peatlands

High-latitude peatlands are changing rapidly in response to climate change, including permafrost thaw. Here, we reconstruct hydrological conditions since the seventeenth century using testate amoeba data from 103 high-latitude peat archives. We show that 54% of the peatlands have been drying and 32% have been wetting over this period, illustrating the complex ecohydrological dynamics of high latitude peatlands and their highly uncertain responses to a warming climate

Robust ordinal regression in preference learning and ranking

Multiple Criteria Decision Aiding (MCDA) offers a diversity of approaches designed for providing the decision maker (DM) with a recommendation concerning a set of alternatives (items, actions) evaluated from multiple points of view, called criteria. This paper aims at drawing attention of the Machine Learning (ML) community upon recent advances in a representative MCDA methodology, called Robust Ordinal Regression (ROR). ROR learns by examples in order to rank a set of alternatives, thus considering a similar problem as Preference Learning (ML-PL) does. However, ROR implements the interactive preference construction paradigm, which should be perceived as a mutual learning of the model and the DM. The paper clarifies the specific interpretation of the concept of preference learning adopted in ROR and MCDA, comparing it to the usual concept of preference learning considered within ML. This comparison concerns a structure of the considered problem, types of admitted preference information, a character of the employed preference models, ways of exploiting them, and techniques to arrive at a final ranking

Palaeoecological data indicates land-use changes across Europe linked to spatial heterogeneity in mortality during the Black Death pandemic

The Black Death (1347–1352 CE) is the most renowned pandemic in human history, believed by many to have killed half of Europe’s population. However, despite advances in ancient DNA research that conclusively identified the pandemic’s causative agent (bacterium Yersinia pestis), our knowledge of the Black Death remains limited, based primarily on qualitative remarks in medieval written sources available for some areas of Western Europe. Here, we remedy this situation by applying a pioneering new approach, ‘big data palaeoecology’, which, starting from palynological data, evaluates the scale of the Black Death’s mortality on a regional scale across Europe. We collected pollen data on landscape change from 261 radiocarbon-dated coring sites (lakes and wetlands) located across 19 modern-day European countries. We used two independent methods of analysis to evaluate whether the changes we see in the landscape at the time of the Black Death agree with the hypothesis that a large portion of the population, upwards of half, died within a few years in the 21 historical regions we studied. While we can confirm that the Black Death had a devastating impact in some regions, we found that it had negligible or no impact in others. These inter-regional differences in the Black Death’s mortality across Europe demonstrate the significance of cultural, ecological, economic, societal and climatic factors that mediated the dissemination and impact of the disease. The complex interplay of these factors, along with the historical ecology of plague, should be a focus of future research on historical pandemics.The authors acknowledge the following funding sources: Max Planck Independent Research Group, Palaeo-Science and History Group (A.I., A.M. and C.V.); Estonian Research Council #PRG323, PUT1173 (A.Pos., T.R., N.S. and S.V.); European Research Council #FP7 263735 (A.Bro. and A.Plu.), #MSC 655659 (A.E.); Georgetown Environmental Initiative (T.N.); Latvian Council of Science #LZP-2020/2-0060 (N.S. and N.J.); LLNL-JRNL-820941 (I.T.); NSF award #GSS-1228126 (S.M.); Polish-Swiss Research Programme #013/2010 CLIMPEAT (M.Lam.), #086/2010 CLIMPOL (A.W.); Polish Ministry of Science and Higher Education #N N306 275635 (M.K.); Polish National Science Centre #2019/03/X/ST10/00849 (M.Lam.), #2015/17/B/ST10/01656 (M.Lam.), #2015/17/B/ST10/03430 (M.Sło.), #2018/31/B/ST10/02498 (M.Sło.), #N N304 319636 (A.W.); SCIEX #12.286 (K.Mar.); Spanish Ministry of Economy and Competitiveness #REDISCO-HAR2017-88035-P (J.A.L.S.); Spanish Ministry of Education, Culture and Sports #FPU16/00676 (R.L.L.); Swedish Research Council #421-2010-1570 (P.L.), #2018-01272 (F.C.L. and A.S.); Volkswagen Foundation Freigeist Fellowship Dantean Anomaly (M.B.), Spanish Ministry of Science and Innovation #RTI2018-101714-B-I00 (F.A.S. and D.A.S.), OP RDE, MEYS project #CZ.02.1.01/0.0/0.0/16_019/0000728 (P.P.)Peer reviewe