File:Zagoskin lake alaska selected pollen paleotemperature.svg

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Summary

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Description
English: Pollen data and paleotemperature visualuzation of Zagoskin Lake, Western Alaska coast ca, 35000-200 BP.
Date
Source Own work
Author Merikanto
Camera location63° 26′ 54″ N, 162° 06′ 18″ W Kartographer map based on OpenStreetMap.View this and other nearby images on: OpenStreetMapinfo

Location

Zagoskin Lake, St. Michael Island, Norton Sound, Alaska: 63º26.9'N, 162º06.3'W, 7 m asl, 19m depth.

Sources of data

Pollen data is "dataset 17391.csv" on Neotoma database

Ager, Zagoskin Lake (ZAGOSKIN) North American Pollen Database (Neotoma) Ager, Thomas A.Earliest Year:36790 cal yr BP * Most Recent Year:47 cal yr BP * Location Bounds - North: 63.45084 * South: 63.4461 * East: -162.10263 * West: -162.11413 *

Paleotemperature data is Kurek et al 2009:

ftp://ftp.ncdc.noaa.gov/pub/data/paleo/insecta/chironomidae/northamerica/usa/alaska/zagoskin-burial2009.txt

WDC PALEO CONTRIBUTION SERIES CITATION: Kurek, J., et al. 2009. Western Alaska 39KYr Midge-Inferred July Temperatures. IGBP PAGES/World Data Center for Paleoclimatology Data Contribution Series # 2009-113. NOAA/NCDC Paleoclimatology Program, Boulder CO, USA.

ORIGINAL REFERENCE: Kurek, J., L.C. Cwynar, T.A. Ager, M.B. Abbott, and M.E. Edwards. 2009. Late Quaternary paleoclimate of western Alaska inferred from fossil chironomids and its relation to vegetation histories. Quaternary Science Reviews, Vol. 28, pp. 799-811. doi:10.1016/j.quascirev.2008.12.001

Data is processed files, and visualized with this script

import numpy as np import matplotlib.pyplot as plt import matplotlib.patches as mpatches

basefontsize=80 xsiz=150 ysiz=50

infiili_1="zagoskin_temp3.txt" infiili_2="zagoskin_pol4.txt"

    1. temperature

indata_1 = np.genfromtxt(infiili_1, delimiter=';', dtype=None) muoto_1=np.shape(indata_1) rowis_1=muoto_1[0] colis_1=muoto_1[1] data_1=np.zeros((rowis_1, colis_1))

for i in xrange(1,rowis_1):

     for j in xrange(0,colis_1):
           data_1[i-1][j]=np.float(indata_1[i][j])

rowis_1=rowis_1-1

pdata_1=data_1.transpose() pdata_1[0][rowis_1]=pdata_1[0][rowis_1-1] pdata_1[1][rowis_1]=pdata_1[1][rowis_1-1]

    1. pollen data

indata_2 = np.genfromtxt(infiili_2, delimiter=';', dtype=None) muoto_2=np.shape(indata_2) rowis_2=muoto_2[0] colis_2=muoto_2[1] data_2=np.zeros((rowis_2, colis_2))

for i in xrange(1,rowis_2):

  1. for i in xrange(1,50):
  2. print ">",i
     for j in xrange(0,colis_2):
           data_2[i-1][j]=np.float(indata_2[i][j])
  1. print indata_2[i][j]

rowis_2=rowis_2-1

pdata_2=data_2.transpose() pdata_2[0][rowis_2]=pdata_2[0][rowis_2-1] pdata_2[1][rowis_2]=pdata_2[1][rowis_2-1]

      1. plottingi

fig = plt.figure()

ax2=plt.subplot()

x = pdata_2[0] y = np.row_stack(( pdata_2[1],pdata_2[2], pdata_2[3], pdata_2[4],pdata_2[5], pdata_2[6], pdata_2[7], pdata_2[8]))

percent = y / y.sum(axis=0).astype(float) * 100

  1. Cal_yr_BP;Alnus;Betula;Salix;Ericales;Cyperaceae;Poaceae;Artemisia;Sphagnum
  1. ax2.stackplot(x,y, colors=['#377EB8','#55BA87','#008000','#FFFF00','#FFFF80','#800000'])

ax2.stackplot(x,percent, colors=['#377EB8','#55BA87','#008000','#00F000', '#FFFF00','#FFFF80','#800000', '#8000F0'],

edgecolors=['#377EB8'], linewidth=0

)

ax2.set_ylabel('Pollen percent \n from selected datasets', color='#004000', fontsize=15) for tl in ax2.get_yticklabels():

   tl.set_color('#004000')

ax2.set_ylim([0, 100]) ax2.set_xlim([0, 25000])

  1. Shrink current axis's height by 10% on the bottom

box = ax2.get_position()

ax2.set_position([box.x0, box.y0, box.width * 0.8, box.height])

ax2.legend( [mpatches.Patch(color='#377EB8'),

            mpatches.Patch(color='#55BA87'), 
            mpatches.Patch(color='#008000'),
            mpatches.Patch(color='#00F000'), 
            mpatches.Patch(color='#FFFF00'),
            mpatches.Patch(color='#FFFF80'),
            mpatches.Patch(color='#800000'),
            mpatches.Patch(color='#8000F0')],  ['Alnus','Betula','Salix','Ericaceae', 'Cyperaceae','Poaceae', 'Artemisia', 'Sphagnum'],

loc='center left', bbox_to_anchor=(1.1, 0.75) )

    1. Cyperaceae #FFFF00
    2. Poaceae #FFFF80
    3. Artemisia #800000
    4. Brassicaceae ##008000
    5. Salix #008000

for label in (ax2.get_xticklabels() + ax2.get_yticklabels()):

   label.set_fontname('Arial')
   label.set_fontsize(15)

ax1 = ax2.twinx()

ax1.set_xlim([0, 25000])

degree_sign= u'\N{DEGREE SIGN}'

tempilabel1='TJuly ' tempilabel2=tempilabel1.encode('utf8')+degree_sign+'C';

ax1.plot(pdata_1[0], pdata_1[1], label=tempilabel2,color='#200000', linewidth=5)

box = ax1.get_position()

ax1.set_position([box.x0, box.y0, box.width * 0.8, box.height])

  1. Set the tick labels font

for label in (ax1.get_xticklabels() + ax1.get_yticklabels()):

   label.set_fontname('Arial')
   label.set_fontsize(15)

ax1.set_xlabel('Time (cal BP)', fontsize=15)

  1. ax1.get_xticklabels().set_fontsize(20)

ax1.set_ylabel(tempilabel2, color='#a00000', fontsize=15) for tl in ax1.get_yticklabels():

   tl.set_color('#400000')

kaptioni="Zagoskin Lake, Alaska \n paleotemperature and pollen diagram"

plt.title(kaptioni, fontsize=18)

ax1.legend(loc='upper left')

start, end = ax1.get_xlim() ax1.xaxis.set_ticks(np.arange(start, end, 2500))

ax1.xaxis.set_tick_params(width=4, length=10) ax1.yaxis.set_tick_params(width=4) ax2.xaxis.set_tick_params(width=4) ax2.yaxis.set_tick_params(width=4)

plt.gca().invert_xaxis()

plt.show()

fig.set_size_inches(16, 6) fig.savefig('out.svg', dpi=80)

  1. fig.savefig('test.svg')

Licensing

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I, the copyright holder of this work, hereby publish it under the following license:
w:en:Creative Commons
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This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.
You are free:
  • to share – to copy, distribute and transmit the work
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Under the following conditions:
  • attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  • share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.

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Date/TimeThumbnailDimensionsUserComment
current12:29, 3 January 2017Thumbnail for version as of 12:29, 3 January 20171,440 × 540 (118 KB)Merikanto (talk | contribs)User created page with UploadWizard

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