Linking modern pollen accumulation rates to biomass: Quantitative vegetation reconstruction in the western Klamath Mountains, NW California, USA

Quantitative reconstructions of vegetation abundance from sediment-derived pollen systems provide unique insights into past ecological conditions. Recently, the use of pollen accumulation rates (PAR, grains cm−2 year−1) has shown promise as a bioproxy for plant abundance. However, successfully reconstructing region-specific vegetation dynamics using PAR requires that accurate assessments of pollen deposition processes be quantitatively linked to spatially-explicit measures of plant abundance. Our study addressed these methodological challenges. Modern PAR and vegetation data were obtained from seven lakes in the western Klamath Mountains, California. To determine how to best calibrate our PAR-biomass model, we first calculated the spatial area of vegetation where vegetation composition and patterning is recorded by changes in the pollen signal using two metrics. These metrics were an assemblage-level relevant source area of pollen (aRSAP) derived from extended R-value analysis ( sensu Sugita, 1993) and a taxon-specific relevant source area of pollen (tRSAP) derived from PAR regression ( sensu Jackson, 1990). To the best of our knowledge, aRSAP and tRSAP have not been directly compared. We found that the tRSAP estimated a smaller area for some taxa (e.g. a circular area with a 225 m radius for Pinus) than the aRSAP (a circular area with a 625 m radius). We fit linear models to relate PAR values from modern lake sediments with empirical, distance-weighted estimates of aboveground live biomass (AGLdw) for both the aRSAP and tRSAP distances. In both cases, we found that the PARs of major tree taxa – Pseudotsuga, Pinus, Notholithocarpus, and TCT (Taxodiaceae, Cupressaceae, and Taxaceae families) – were statistically significant and reasonably precise estimators of contemporary AGLdw. However, predictions weighted by the distance defined by aRSAP tended to be more precise. The relative root-mean squared error for the aRSAP biomass estimates was 9% compared to 12% for tRSAP. Our results demonstrate that calibrated PAR-biomass relationships provide a robust method to infer changes in past plant biomass.

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Insights into pollen source area, transport and deposition from modern pollen accumulation rates in lake sediments

Quaternary Science Reviews ◽

10.1016/j.quascirev.2013.12.015 ◽

2014 ◽

Vol 87 ◽

pp. 12-23 ◽

Cited By ~ 35

Author(s):

Isabelle Matthias ◽

Thomas Giesecke

Keyword(s):

Lake Sediments ◽

Source Area ◽

Accumulation Rates ◽

Pollen Accumulation Rates ◽

Modern Pollen

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Patterns in recent and Holocene pollen accumulation rates across Europe – the Pollen Monitoring Programme Database as a tool for vegetation reconstruction

Biogeosciences ◽

10.5194/bg-18-4511-2021 ◽

2021 ◽

Vol 18 (15) ◽

pp. 4511-4534

Author(s):

Vojtěch Abraham ◽

Sheila Hicks ◽

Helena Svobodová-Svitavská ◽

Elissaveta Bozilova ◽

Sampson Panajiotidis ◽

...

Keyword(s):

Forest Cover ◽

Monitoring Network ◽

Pollen Grains ◽

Individual Species ◽

Pollen Deposition ◽

Accumulation Rates ◽

Long Distance ◽

Pollen Monitoring ◽

Pollen Accumulation Rates ◽

Long Distance Transport

Abstract. The collection of modern, spatially extensive pollen data is important for the interpretation of fossil pollen assemblages and the reconstruction of past vegetation communities in space and time. Modern datasets are readily available for percentage data but lacking for pollen accumulation rates (PARs). Filling this gap has been the motivation of the pollen monitoring network, whose contributors monitored pollen deposition in modified Tauber traps for several years or decades across Europe. Here we present this monitoring dataset consisting of 351 trap locations with a total of 2742 annual samples covering the period from 1981 to 2017. This dataset shows that total PAR is influenced by forest cover and climate parameters, which determine pollen productivity and correlate with latitude. Treeless vegetation produced PAR values of at least 140 grains cm−2 yr−1. Tree PAR increased by at least 400 grains cm−2 yr−1 with each 10 % increase in forest cover. Pollen traps situated beyond 200 km of the distribution of a given tree species still collect occasional pollen grains of that species. The threshold of this long-distance transport differs for individual species and is generally below 60 grains cm−2 yr−1. Comparisons between modern and fossil PAR from the same regions show similar values. For temperate taxa, modern analogues for fossil PARs are generally found downslope or southward of the fossil sites. While we do not find modern situations comparable to fossil PAR values of some taxa (e.g. Corylus), CO2 fertilization and land use may cause high modern PARs that are not documented in the fossil record. The modern data are now publicly available in the Neotoma Paleoecology Database and aid interpretations of fossil PAR data.

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Threshold selection in univariate extreme value analysis

Extremes ◽

10.1007/s10687-021-00405-7 ◽

2021 ◽

Author(s):

Laura Fee Schneider ◽

Andrea Krajina ◽

Tatyana Krivobokova

Keyword(s):

Mean Squared Error ◽

Extreme Value ◽

Hill Estimator ◽

Small Samples ◽

Extreme Value Analysis ◽

Threshold Selection ◽

Value Analysis ◽

Wide Range ◽

Asymptotic Mean Squared Error ◽

The Hill

AbstractThreshold selection plays a key role in various aspects of statistical inference of rare events. In this work, two new threshold selection methods are introduced. The first approach measures the fit of the exponential approximation above a threshold and achieves good performance in small samples. The second method smoothly estimates the asymptotic mean squared error of the Hill estimator and performs consistently well over a wide range of processes. Both methods are analyzed theoretically, compared to existing procedures in an extensive simulation study and applied to a dataset of financial losses, where the underlying extreme value index is assumed to vary over time.

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Key parameters for landscape evolution and anthropogenisation estimation in the Kamchia River downstream region (Eastern Bulgaria)

ANNUAL JOURNAL OF TECHNICAL UNIVERSITY OF VARNA BULGARIA ◽

10.29114/ajtuv.vol5.iss1.240 ◽

2021 ◽

Vol 5 (1) ◽

pp. 86-93

Author(s):

Stoyan Ivanov Vergiev ◽

Mariana Filipova-Marinova ◽

Daniela Toneva ◽

Todorka Stankova ◽

Diyana Dimova ◽

...

Keyword(s):

Source Area ◽

Critical Parameters ◽

Vegetation Composition ◽

Pollen Data ◽

Plant Abundance ◽

Pollen Type ◽

Modern Pollen ◽

Downstream Region ◽

Pollen Productivity ◽

Gis Environment

Pollen productivity еstimate (PPE) and relevant source area of pollen (RSAP) are critical parameters for quantitative interpretations of pollen data in palaeolandscape and palaeoecological reconstructions, and for analyses of the landscapes evolution and anthropogenisation as well. In light of this, the present paper endeavours to calculate PPE of key plant taxa and to define the RSAP in the Kamchia River Downstream Region (Eastern Bulgaria) in order to use them in landscape simulations and estimations. For the purposes of this research, a dataset of pollen counts from 10 modern pollen samples together with corresponding vegetation data, measured around each sample point in concentric rings, were collected in 2020. Three submodels of the Extended R-Value (ERV) model were used to relate pollen percentages to vegetation composition. Therewith, in order to create a calibrated model, the plant abundance of each pollen type was weighed by distance in GIS environment. The findings led to the conclusion that most of the tree taxa have PPE higher than 1 (ERV3 submodel). Cichoriceae, Fabaceae and Asteraceae have lower PPE.

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Signals of tree volume and temperature in a high-resolution record of pollen accumulation rates in northern Finland

Journal of Quaternary Science ◽

10.1002/jqs.2549 ◽

2012 ◽

Vol 27 (6) ◽

pp. 564-574 ◽

Cited By ~ 25

Author(s):

F. Mazier ◽

A. B. Nielsen ◽

A. Broström ◽

S. Sugita ◽

S. Hicks

Keyword(s):

High Resolution ◽

Accumulation Rates ◽

Pollen Accumulation Rates

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On the Applicability of Extreme Value Statistics in the Prediction of Maximum Pit Depth in Heavily Corroded Non-Piggable Buried Pipelines

2010 8th International Pipeline Conference, Volume 4 ◽

10.1115/ipc2010-31321 ◽

2010 ◽

Cited By ~ 1

Author(s):

L. Alfonso ◽

F. Caleyo ◽

J. M. Hallen ◽

J. Araujo

Keyword(s):

Mean Squared Error ◽

Extreme Value ◽

Extreme Value Statistics ◽

Extreme Value Analysis ◽

Corrosion Condition ◽

Value Analysis ◽

Squared Error ◽

Different Populations ◽

Pit Depth ◽

Selection Of

There exists a large number of works aimed at the application of Extreme Value Statistics to corrosion. However, there is a lack of studies devoted to the applicability of the Gumbel method to the prediction of maximum pitting-corrosion depth. This is especially true for works considering the typical pit densities and spatial patterns in long, underground pipelines. In the presence of spatial pit clustering, estimations could deteriorate, raising the need to increase the total inspection area in order to obtain the desired accuracy for the estimated maximum pit depth. In most practical situations, pit-depth samples collected along a pipeline belong to distinguishable groups, due to differences in corrosion environments. For example, it is quite probable that samples collected from the pipeline’s upper and lower external surfaces will differ and represent different pit populations. In that case, maximum pit-depth estimations should be made separately for these two quite different populations. Therefore, a good strategy to improve maximum pit-depth estimations is critically dependent upon a careful selection of the inspection area used for the extreme value analysis. The goal should be to obtain sampling sections that contain a pit population as homogenous as possible with regard to corrosion conditions. In this study, the aforementioned strategy is carefully tested by comparing extreme-value-oriented Monte Carlo simulations of maximum pit depth with the results of inline inspections. It was found that the variance to mean ratio, a measure of randomness, and the mean squared error of the maximum pit-depth estimations were considerably reduced, compared with the errors obtained for the entire pipeline area, when the inspection areas were selected based on corrosion-condition homogeneity.

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