Abstract:The Great Plains experienced extreme fluctuations in precipitation and temperature throughout the Holocene, but these fluctuations have been difficult to quantify systematically across the region. Pollen has long been used as a proxy for reconstructing climate changes, but its power is limited if a region is devoid of modern pollen samples to facilitate comparison with known climate conditions. Here, we present a set of pollen‐climate transfer functions developed using weighted‐averaging partial least squares … Show more
“…Our findings agree with Commerford et al (2018), who report that inclusion of Ambrosia in transfer functions drove precipitation estimates, and that precipitation appears to be a much stronger factor in Ambrosia pollen abundance than is temperature. We suggest that the strong signal of disturbance in the post‐European settlement pollen record can be adequately controlled for using a correction factor.…”
Patterns of vegetation distribution at regional to subcontinental scales can inform understanding of climate. Delineating ecoregion boundaries over geologic time is complicated by the difficulty of distinguishing between prairie types at broad spatial scales using the pollen record. Pollen ratios are sometimes employed to distinguish between vegetation types, although their applicability is often limited to a geographic range. The Neotoma Paleoecology Database offers an unparalleled opportunity to synthesize a large number of pollen datasets. Ambrosia (ragweed) is a genus of mesic-adapted species sensitive to summer moisture. Artemisia (sagebrush, wormwood, mugwort) is a genus of dry-mesic-adapted species resilient to drought. The log pollen ratio between these two common taxa was calculated across the North American midcontinent from surface pollen samples housed in the Neotoma Paleoecology Database. The relative proportion of Ambrosia has roughly doubled since European settlement, likely due to widespread disturbance, while Artemisia proportions are nearly unchanged. Correcting surface samples for the disturbance signal in modern Ambrosia proportions will allow Ambrosia, a strong indicator of summer moisture, to be more accurately represented. In surface samples where both Ambrosia and Artemisia are reported as nonzero proportions of the pollen sum, mean annual precipitation explains approximately 78% of the variation in the log Ambrosia-to-Artemisia ratio. Application of this model to Little Ice Age pollen samples produces precipitation reconstructions which generally agree with reconstructions from independent nonpollen proxies. In addition, we find that modern ecoregions within the North American midcontinent can be successfully distinguished from one another using the log Ambrosia-to-Artemisia ratio. These relationships can improve reconstructions of past climate and improve delineation of past ecoregion boundaries.
“…Our findings agree with Commerford et al (2018), who report that inclusion of Ambrosia in transfer functions drove precipitation estimates, and that precipitation appears to be a much stronger factor in Ambrosia pollen abundance than is temperature. We suggest that the strong signal of disturbance in the post‐European settlement pollen record can be adequately controlled for using a correction factor.…”
Patterns of vegetation distribution at regional to subcontinental scales can inform understanding of climate. Delineating ecoregion boundaries over geologic time is complicated by the difficulty of distinguishing between prairie types at broad spatial scales using the pollen record. Pollen ratios are sometimes employed to distinguish between vegetation types, although their applicability is often limited to a geographic range. The Neotoma Paleoecology Database offers an unparalleled opportunity to synthesize a large number of pollen datasets. Ambrosia (ragweed) is a genus of mesic-adapted species sensitive to summer moisture. Artemisia (sagebrush, wormwood, mugwort) is a genus of dry-mesic-adapted species resilient to drought. The log pollen ratio between these two common taxa was calculated across the North American midcontinent from surface pollen samples housed in the Neotoma Paleoecology Database. The relative proportion of Ambrosia has roughly doubled since European settlement, likely due to widespread disturbance, while Artemisia proportions are nearly unchanged. Correcting surface samples for the disturbance signal in modern Ambrosia proportions will allow Ambrosia, a strong indicator of summer moisture, to be more accurately represented. In surface samples where both Ambrosia and Artemisia are reported as nonzero proportions of the pollen sum, mean annual precipitation explains approximately 78% of the variation in the log Ambrosia-to-Artemisia ratio. Application of this model to Little Ice Age pollen samples produces precipitation reconstructions which generally agree with reconstructions from independent nonpollen proxies. In addition, we find that modern ecoregions within the North American midcontinent can be successfully distinguished from one another using the log Ambrosia-to-Artemisia ratio. These relationships can improve reconstructions of past climate and improve delineation of past ecoregion boundaries.
“…The water balance curves, by contrast, show an early-Holocene decline, culminating in a dry period starting around 8 ka (depending on smoothing bandwidth considered), and followed by a gradual rise in water balance at around 6 ka. The early–mid Holocene maximum in aridity is consistent with numerous multi-proxy records from the Great Plains 17,18,32–34 . The strong differences in temporal pattern further suggests that both temperature and water balance signals can be separately deconvolved from mid-continental North American pollen records 16,18,32,34 .Figure 4Palaeoclimate reconstructions.…”
Section: Resultssupporting
confidence: 85%
“…These are possibly “easy” test cases, with e.g. exceptionally strong opposite trends in winter and summer temperature forcing during the LIG 19,37 and prior multiproxy evidence for major mid-Holocene aridity in the Great Plains of North America 17,18,33,34,47 as well as prior applications of pollen-based palaeoclimatic transfer functions to separately reconstruct past temperature and moisture variations 16,48,49 . Whether robust and repeatable reconstructions can be achieved for secondary or tertiary variables across a larger body of micropalaeontological data remains a question for future research.…”
Section: Discussionmentioning
confidence: 99%
“…Yet, secondary variables are important for palaeoclimatology, because they reveal diagnostic signals of the past variability in vital climate factors, forcings, feedbacks, or atmospheric-oceanic circulation mechanisms, that would otherwise be undetectable. For example, while in northern latitudes climate reconstructions from pollen and chironomids usually indicate summer temperature as a primary variable, past changes in winter temperature or precipitation may be vital to detecting and understanding past variation in sea ice extent 14 , oceanic circulation 15 , or drought regimes 16,17 . In ideal situations, palaeoclimate information is available from multiple proxies, allowing an independent validation 4 of reconstructions for hard-to-reconstruct variables such as moisture 18 or winter temperature 19 .…”
We test several quantitative algorithms as palaeoclimate reconstruction tools for North American and European fossil pollen data, using both classical methods and newer machine-learning approaches based on regression tree ensembles and artificial neural networks. We focus on the reconstruction of secondary climate variables (here, January temperature and annual water balance), as their comparatively small ecological influence compared to the primary variable (July temperature) presents special challenges to palaeo-reconstructions. We test the pollen–climate models using a novel and comprehensive cross-validation approach, running a series of h-block cross-validations using h values of 100–1500 km. Our study illustrates major benefits of this variable h-block cross-validation scheme, as the effect of spatial autocorrelation is minimized, while the cross-validations with increasing h values can reveal instabilities in the calibration model and approximate challenges faced in palaeo-reconstructions with poor modern analogues. We achieve well-performing calibration models for both primary and secondary climate variables, with boosted regression trees providing the overall most robust performance, while the palaeoclimate reconstructions from fossil datasets show major independent features for the primary and secondary variables. Our results suggest that with careful variable selection and consideration of ecological processes, robust reconstruction of both primary and secondary climate variables is possible.
“…This ratio can be used to account for the over‐representation of trees in pollen spectra due to their high pollen productivity compared with grasses/forbs. Because herbaceous species are very sensitive to climate variations, there is also an opportunity to link pollen assemblages with climatic conditions, allowing precipitation reconstructions in these areas (Commerford et al., ).…”
Grasslands are globally extensive; they exist in many different climates, at high and low elevations, on nutrient‐rich and nutrient‐poor soils. Grassland distributions today are closely linked to human activities, herbivores, and fire, but many have been converted to urban areas, forests, or agriculture fields. Roughly 80% of fires globally occur in grasslands each year, making fire a critical process in grassland dynamics. Yet, little is known about the long‐term history of fire in grasslands. Here, we analyze sedimentary archives to reconstruct grassland fire histories during the Holocene. Given that grassland locations change over time, we compare several charcoal‐based fire reconstructions based on alternative classification schemes: (a) sites from modern grassland locations; (b) sites that were likely grasslands during the mid‐Holocene; and (c) sites based on author‐derived classifications. We also compare fire histories from grassland sites, forested sites, and all sites globally over the past 12,000 years. Forested versus grassland sites show different trends: grassland burning increased from the early to mid‐Holocene, reaching a maximum about 8000–6000 years ago, and subsequently declined, reaching a minimum around 4000 years ago. In contrast, biomass burning in forests increased during the Holocene until about 2000 years ago. Continental grassland fire history reconstructions show opposing Holocene trends in North versus South America, whereas grassland burning in Australia was highly variable in the early Holocene and much more stable after the mid‐Holocene. The sharp differences in continental as well as forest versus grassland Holocene fire history trajectories have important implications for our understanding of global biomass burning and its emissions, the global carbon cycle, biodiversity, conservation, and land management.
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