Despite the acceleration of climate change, erroneous assumptions of climate stationarity are still inculcated in the management of water resources in the United States (US). The US system for ...drought detection, which triggers billions of dollars in emergency resources, adheres to this assumption with preference towards 60-year (or longer) record lengths for drought characterization. Using observed data from 1,934 Global Historical Climate Network (GHCN) sites across the US, we show that conclusions based on long climate records can substantially bias assessment of drought severity. Bias emerges by assuming that conditions from the early and mid 20th century are as likely to occur in today's climate. Numerical simulations reveal that drought assessment error is relatively low with limited climatology lengths (~30 year) and that error increases with longer record lengths where climate is changing rapidly. We assert that non-stationarity in climate must be accounted for in contemporary assessments to more accurately portray present drought risk.
Moving crops outside of their original centers of domestication was sometimes a challenging process. Because of its substantial heat requirements, moving rice agriculture outside of its homelands of ...domestication was not an easy process for farmers in the past. Using crop niche models, we examine the constraints faced by ancient farmers and foragers as they moved rice to its most northerly extent in Ancient China: Shandong province. Contrary to previous arguments, we find that during the climatic optimum rice could have been grown in the region. Climatic cooling following this date had a clear impact on the distribution of rice, one that may have placed adaptive pressure on rice to develop a temperate phenotype. Following the development of this temperate phenotype, rice agriculture could once again become implanted in select areas of north-eastern China.
Rice (Oryza sativa) is one of the world's most important food crops, and is comprised largely of japonica and indica subspecies. Here, we reconstruct the history of rice dispersal in Asia using ...whole-genome sequences of more than 1,400 landraces, coupled with geographic, environmental, archaeobotanical and paleoclimate data. Originating around 9,000 yr ago in the Yangtze Valley, rice diversified into temperate and tropical japonica rice during a global cooling event about 4,200 yr ago. Soon after, tropical japonica rice reached Southeast Asia, where it rapidly diversified, starting about 2,500 yr BP. The history of indica rice dispersal appears more complicated, moving into China around 2,000 yr BP. We also identify extrinsic factors that influence genome diversity, with temperature being a leading abiotic factor. Reconstructing the dispersal history of rice and its climatic correlates may help identify genetic adaptations associated with the spread of a key domesticated species.
Temperature variability likely played an important role in determining the spread and productive potential of North America’s key prehispanic agricultural staple, maize. The United States Southwest ...(SWUS) also served as the gateway for maize to reach portions of North America to the north and east. Existing temperature reconstructions for the SWUS are typically low in spatial or temporal resolution, shallow in time depth, or subject to unknown degrees of insensitivity to low-frequency variability, hindering accurate determination of temperature’s role in agricultural productivity and variability in distribution and success of prehispanic farmers. Here, we develop a model-based modern analog technique (MAT) approach applied to 29 SWUS fossil pollen sites to reconstruct July temperatures from 3000 BC to AD 2000. Temperatures were generally warmer than or similar to those of the modern (1961–1990) period until the first century AD. Our reconstruction also notes rapid warming beginning in the AD 1800s; modern conditions are unprecedented in at least the last five millennia in the SWUS. Temperature minima were reached around 1800 BC, 1000 BC, AD 400 (the global minimum in this series), the mid-to-late AD 900s, and the AD 1500s. Summer temperatures were generally depressed relative to northern hemisphere norms by a dominance of El Niño-like conditions during much of the second millenium BC and the first millenium AD, but somewhat elevated relative to those same norms in other periods, including from about AD 1300 to the present, due to the dominance of La Niña-like conditions.
Humans experience, adapt to and influence climate at local scales. Paleoclimate research, however, tends to focus on continental, hemispheric or global scales, making it difficult for archaeologists ...and paleoecologists to study local effects. Here we introduce a method for high-frequency, local climate-field reconstruction from tree-rings. We reconstruct the rain-fed maize agricultural niche in two regions of the southwestern United States with dense populations of prehispanic farmers. Niche size and stability are highly variable within and between the regions. Prehispanic rain-fed maize farmers tended to live in agricultural refugia--areas most reliably in the niche. The timing and trajectory of the famous thirteenth century Pueblo migration can be understood in terms of relative niche size and stability. Local reconstructions like these illuminate the spectrum of strategies past humans used to adapt to climate change by recasting climate into the distributions of resources on which they depended.
Archaeologists increasingly use large radiocarbon databases to model prehistoric human demography (also termed paleo-demography). Numerous independent projects, funded over the past decade, have ...assembled such databases from multiple regions of the world. These data provide unprecedented potential for comparative research on human population ecology and the evolution of social-ecological systems across the Earth. However, these databases have been developed using different sample selection criteria, which has resulted in interoperability issues for global-scale, comparative paleo-demographic research and integration with paleoclimate and paleoenvironmental data. We present a synthetic, global-scale archaeological radiocarbon database composed of 180,070 radiocarbon dates that have been cleaned according to a standardized sample selection criteria. This database increases the reusability of archaeological radiocarbon data and streamlines quality control assessments for various types of paleo-demographic research. As part of an assessment of data quality, we conduct two analyses of sampling bias in the global database at multiple scales. This database is ideal for paleo-demographic research focused on dates-as-data, bayesian modeling, or summed probability distribution methodologies.
Climate extremes are thought to have triggered large-scale transformations of various ancient societies, but they rarely seem to be the sole cause. It has been hypothesized that slow internal ...developments often made societies less resilient over time, setting them up for collapse. Here, we provide quantitative evidence for this idea. We use annual-resolution time series of building activity to demonstrate that repeated dramatic transformations of Pueblo cultures in the pre-Hispanic US Southwest were preceded by signals of critical slowing down, a dynamic hallmark of fragility. Declining stability of the status quo is consistent with archaeological evidence for increasing violence and in some cases, increasing wealth inequality toward the end of these periods. Our work thus supports the view that the cumulative impact of gradual processes may make societies more vulnerable through time, elevating the likelihood that a perturbation will trigger a large-scale transformation that includes radically rejecting the status quo and seeking alternative pathways.
The northern American Southwest provides one of the most well-documented cases of human population growth and decline in the world. The geographic extent of this decline in North America is unknown ...owing to the lack of high-resolution palaeodemographic data from regions across and beyond the greater Southwest, where archaeological radiocarbon data are often the only available proxy for investigating these palaeodemographic processes. Radiocarbon time series across and beyond the greater Southwest suggest widespread population collapses from AD 1300 to 1600. However, radiocarbon data have potential biases caused by variable radiocarbon sample preservation, sample collection and the nonlinearity of the radiocarbon calibration curve. In order to be confident in the wider trends seen in radiocarbon time series across and beyond the greater Southwest, here we focus on regions that have multiple palaeodemographic proxies and compare those proxies to radiocarbon time series. We develop a new method for time series analysis and comparison between dendrochronological data and radiocarbon data. Results confirm a multiple proxy decline in human populations across the Upland US Southwest, Central Mesa Verde and Northern Rio Grande from AD 1300 to 1600. These results lend confidence to single proxy radiocarbon-based reconstructions of palaeodemography outside the Southwest that suggest post-AD 1300 population declines in many parts of North America. This article is part of the theme issue 'Cross-disciplinary approaches to prehistoric demography'.
Twenty-first century approaches to ancient problems Guedes, Jade A. d’Alpoim; Crabtree, Stefani A.; Bocinsky, R. Kyle ...
Proceedings of the National Academy of Sciences - PNAS,
12/2016, Letnik:
113, Številka:
51
Journal Article
Recenzirano
Odprti dostop
By documenting how humans adapted to changes in their environment that are often much greater than those experienced in the instrumental record, archaeology provides our only deep-time laboratory for ...highlighting the circumstances under which humans managed or failed to find to adaptive solutions to changing climate, not just over a few generations but over the longue durée. Patterning between climate-mediated environmental change and change in human societies has, however, been murky because of low spatial and temporal resolution in available datasets, and because of failure to model the effects of climate change on local resources important to human societies. In this paper we review recent advances in computational modeling that, in conjunction with improving data, address these limitations. These advances include network analysis, niche and species distribution modeling, and agent-based modeling. These studies demonstrate the utility of deep-time modeling for calibrating our understanding of how climate is influencing societies today and may in the future.
Accurate drought assessments are critical for mitigating the deleterious impacts of water scarcity on communities across the world. In many regions, deficits in soil moisture represent a key driver ...of drought conditions. However, relationships between soil moisture and widely used drought indicators have not been thoroughly evaluated. In addition, there has not been an in‐depth assessment of the accuracy of operational soil moisture models used for drought monitoring. Here, we used 2,405 observed time series of soil moisture from 637 long‐term monitoring stations across the conterminous United States to test the ability of meteorological drought indices and soil moisture models to accurately characterize soil moisture drought. The optimal timescales for meteorological drought indices varied substantially by depth, but were ∼30 days for depth averaged conditions; progressively longer timescales (∼10–80 days) represent progressively deeper soil moisture (2–36 in.). However, soil moisture models (including Short‐term Prediction Research and Transition Center, Soil Moisture Active Passive L4, and Topofire) significantly outperformed the meteorological drought indices for predicting standardized soil moisture anomalies and drought conditions. Additionally, soil moisture models represent near instantaneous conditions, implicitly aggregating antecedent data thereby eliminating the need for timescales, providing a more effective and convenient method for soil moisture drought monitoring. We conclude that soil moisture models provide a straightforward and favorable alternative to meteorological drought indices that better characterize soil moisture drought.
Key Points
Optimal drought index timescales for soil moisture are relatively short (less than 100 days) and increase with increasing soil depth
The Short‐term Prediction Research and Transition Center, Topofire and Soil Moisture Active Passive L4 models are more accurate than timescale optimized drought indices for soil moisture anomaly prediction
Drought monitoring should favor the use of soil moisture models over meteorological drought indices for characterizing soil moisture drought
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