From forest to farmland: pollen‐inferred land cover change across Europe using the pseudobiomization approach

Ecosystems on the verge of major reorganization-regime shiftmay exhibit declining resilience, which can be detected using a collection of generic statistical tests known as early warning signals (EWSs). This study explores whether EWSs anticipated human population collapse during the European Neolithic. It analyzes recent reconstructions of European Neolithic (8-4 kya) population trends that reveal regime shifts from a period of rapid growth following the introduction of agriculture to a period of instability and collapse. We find statistical support for EWSs in advance of population collapse. Seven of nine regional datasets exhibit increasing autocorrelation and variance leading up to collapse, suggesting that these societies began to recover from perturbation more slowly as resilience declined. We derive EWS statistics from a prehistoric population proxy based on summed archaeological radiocarbon date probability densities. We use simulation to validate our methods and show that sampling biases, atmospheric effects, radiocarbon calibration error, and taphonomic processes are unlikely to explain the observed EWS patterns. The implications of these results for understanding the dynamics of Neolithic ecosystems are discussed, and we present a general framework for analyzing societal regime shifts using EWS at large spatial and temporal scales. We suggest that our findings are consistent with an adaptive cycling model that highlights both the vulnerability and resilience of early European populations. We close by discussing the implications of the detection of EWS in human systems for archaeology and sustainability science.archaeology | early warning signs | human paleodemography | Neolithic Europe | resilience A 2012 Special Issue in PNAS debates how analysis of historical collapse in ancient societies can contribute to sustainability science (1). Key themes include accounting for complexity and multicausality in instances of collapse, modeling, and predicting both short-and long-term environmental change and the importance of historical and archaeological case studies. Although significant progress has been made in measuring ecosystem resilience and predicting collapse (2), quantifying the resilience of human societies presents a major challenge for social science research (3, 4). Further, the use of archaeological data and EWS methods to predict known periods of collapse in ancient human societies (i.e., retrodiction) (5) remains largely unexplored. Resilience as we use the concept here is defined as the ability of a system to absorb change and recover from disturbance while maintaining relationships between populations or state variables (6). Recent developments in ecology point to a promising new direction that follows from the observation that ecosystem resilience tends to decrease in advance of regime shifts-major transitions among qualitatively distinct ecosystem states (7). Theoretical and empirical studies of nonhuman systems reveal that decreasing resilience is detectable via time series statistics term...

Section: Implications For Understanding the Causes Of Collapse Duringsupporting

confidence: 85%

European Neolithic societies showed early warning signals of population collapse

Downey

Haas

Shennan

2016

“…Taken together, the C budget analysis at the Holocene timescale suggests that humans emerged as a driver with dominant global C-cycle impacts in the most recent three millennia. This result is in line with evidence from a wide range of paleo-ecological records documenting first significant landscape transformations in the Bronze Age in Europe (35)(36)(37). In China, archaeological evidence suggests major expansion of settlements already after 5 kyBP (38).…”

Section: Resultssupporting

confidence: 88%

Holocene peatland and ice-core data constraints on the timing and magnitude of CO₂emissions from past land use

Stocker

Massa

et al. 2017

CO 2 emissions from preindustrial land-use change (LUC) are subject to large uncertainties. Although atmospheric CO 2 records suggest only a small land carbon (C) source since 5,000 y before present (5 kyBP), the concurrent C sink by peat buildup could mask large early LUC emissions. Here, we combine updated continuous peat C reconstructions with the land C balance inferred from double deconvolution analyses of atmospheric CO 2 and δ 13 C at different temporal scales to investigate the terrestrial C budget of the Holocene and the last millennium and constrain LUC emissions. LUC emissions are estimated with transient model simulations for diverging published scenarios of LU area change and shifting cultivation. Our results reveal a large terrestrial nonpeatland C source after the Mid-Holocene (66 ± 25 PgC at 7-5 kyBP and 115 ± 27 PgC at 5-3 kyBP). Despite high simulated per-capita CO 2 emissions from LUC in early phases of agricultural development, humans emerge as a driver with dominant global C cycle impacts only in the most recent three millennia. Sole anthropogenic causes for particular variations in the CO 2 record (∼20 ppm rise after 7 kyBP and ∼10 ppm fall between 1500 CE and 1600 CE) are not supported. This analysis puts a strong constraint on preindustrial vs. industrial-era LUC emissions and suggests that upper-end scenarios for the extent of agricultural expansion before 1850 CE are not compatible with the C budget thereafter.carbon cycle | Anthropocene | agriculture | peatland | ice core T he Earth's functioning is now so significantly affected by human activities that their impacts will leave long-lasting fingerprints in environmental records. This has motivated the definition of a new, human-dominated geological epoch-the Anthropocene (1, 2). However, human impacts on the Earth's environmental history throughout the preindustrial Holocene are less clear. Although a causal link between anthropogenic greenhouse gas (GHG) emissions and the rapid rise in their concentrations since industrialization is unequivocal, CO 2 and CH 4 concentrations already exhibited a particular, albeit slow and not synchronous increase millennia earlier. This may give rise to the possibility of far-reaching global environmental change induced by early agriculture (3). Similarly, variations in atmospheric CO 2 during the last millennium have been linked to agricultural expansion and collapse (2). However, any association between a particular change in the GHG records and a coincidental continental or global socio-economic change hinges on a causal relationship between the two and on the plausibility of bottom-up estimates to imply a sufficient impact on atmospheric GHG concentrations.In all cases where such a connection has been claimed, causality is strongly debated (4-8). For example, the link between the particular CO 2 increase after 7 kyBP and the Neolithic Revolution is motivated by a multitude of local-scale paleoecological and archaeological archives documenting an early onset of a human influence on the landscape wit...

“…In particular, the ice core levoglucosan flux (a biomarker of fire emissions) started to slowly increase in the Holocene, reached two peaks at around 5.5 and 2.5 KY ago, and then began to decline (40), consistent with the drop in the forest clearance rate in Europe (41). It seems, therefore, that this second demographic decline was caused mainly by the contraction of habitat due to farming, which profoundly modified the genetic structure among bear populations.…”

Section: 3)mentioning

confidence: 88%

Survival and divergence in a small group: The extraordinary genomic history of the endangered Apennine brown bear stragglers

Benazzo

Trucchi

Cahill

et al. 2017

159

132

Survival and divergence in a small group: the extraordinary genomic history of the endangered Apennine brown bear stragglers 2 AbstractAbout 100 km east of Rome, in the Central Apennine mountains, a critically endangered population of approximately fifty brown bears live in complete isolation. Mating outside this population is prevented by several hundred kilometers of bear-free territories. We exploited this natural experiment to better understand the gene and genomic consequences of surviving at extremely small population size. First, we found that brown bear populations in Europe lost connectivity since Neolithic times, when farming communities expanded and forest burning was used for land clearance. In Central Italy, this resulted in a 40-fold population decline. The overall genomic impact of this decline included the complete loss of variation in the mitochondrial genome and along long stretches of the nuclear genome. Several private and deleterious amino acid changes were fixed by random drift; predicted effects include energy deficit, muscle weakness, anomalies in cranial and skeletal development, and reduced aggressiveness. Despite this extreme loss of diversity, Apennine bear genomes show non-random peaks of high variation, possibly maintained by balancing selection, at genomic regions significantly enriched for genes associated with immune and olfactory systems. Challenging the paradigm of increased extinction risk in small populations, we suggest that random fixation of deleterious alleles a) can be an important driver of divergence in isolation, b) can be tolerated when balancing selection prevents random loss of variation at important genes and c) is followed by or results directly in favorable behavioral changes. SignificanceA small and relict population of brown bears lives in complete isolation in the Italian Apennine mountains, providing a unique opportunity to study the impact of drift and selection on the genomes of a large endangered mammal and to reconstruct the phenotypic consequences and the conservation implications of such evolutionary processes. The Apennine bear is highly inbred and harbors very low genomic variation. Several deleterious mutations have been accumulated by drift. We found evidence that this is a consequence of habitat fragmentation in the Neolithic, when human expansion and land clearance shrank its habitat, and that retention of variation at immune system and olfactory receptor genes, as well as changes in diet and behavior, prevented the extinction of the Apennine bear.