{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import xarray as xr\n",
"import pandas as pd\n",
"from salishsea_tools import viz_tools, places, visualisations\n",
"from matplotlib import pyplot as plt, dates\n",
"from datetime import datetime, timedelta\n",
"from calendar import month_name\n",
"from scipy.io import loadmat\n",
"from tqdm.notebook import tqdm\n",
"from salishsea_tools import nc_tools\n",
"from dask.diagnostics import ProgressBar\n",
"import cmocean\n",
"\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Note that all biological rates (e.g., grazing) are scaled (multiplied by 1.111) to correct for a time splitting/Roberts-Asselin filter error in hte model as reported in Olson et al. 2020"
]
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"from IPython.display import HTML\n",
"\n",
"HTML('''\n",
"\n",
"''')"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"plt.rcParams.update({'font.size': 12, 'axes.titlesize': 'medium'})"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Load files from monthly averages"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Z1 grazing on Diatoms"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"#years, months, data\n",
"monthly_array_Z1diatoms_depthint_slice = np.zeros([14,12,50,50])\n",
"# Load monthly averages\n",
"mask = xr.open_dataset('/data/eolson/results/MEOPAR/NEMO-forcing-new/grid/mesh_mask201702.nc')\n",
"slc = {'y': slice(450,500), 'x': slice(250,300)}\n",
"e3t, tmask = [mask[var].isel(z=slice(None, 27),**slc).values for var in ('e3t_0', 'tmask')]\n",
"years, variables = range(2007, 2021), ['GRMICZDIAT']\n",
"# Temporary list dict\n",
"data = {}\n",
"# Permanent aggregate dict\n",
"#aggregates = {var: {} for var in variables}\n",
"#monthlydat = {var: {} for var in variables}\n",
"\n",
"# Loop through years\n",
"for year in [2007,2008,2009,2010,2011,2012,2015,2016,2017,2018,2019,2020]:\n",
" # Initialize lists\n",
" for var in variables: data[var] = []\n",
" # Load monthly averages\n",
" for month in range(1, 13):\n",
" datestr = f'{year}{month:02d}'\n",
" prefix = f'/data/sallen/results/MEOPAR/v201905r/SalishSea_1m_{datestr}_{datestr}'\n",
" \n",
" # Load grazing variables\n",
" with xr.open_dataset(prefix + '_dia2_T.nc') as ds:\n",
" q = np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data\n",
" q2 = q[0,:,:]\n",
" monthly_array_Z1diatoms_depthint_slice[year-2007,month-1,:,:] = q2 #year2015 is index 0 along 1st dimension\n",
" for var in ['GRMICZDIAT']:\n",
" data[var].append(np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data)\n",
" \n",
" \n",
"# Loop through years for wrap files\n",
"for year in [2013,2014]:\n",
" # Initialize lists\n",
" for var in variables: data[var] = []\n",
" # Load monthly averages\n",
" for month in range(1, 13):\n",
" datestr = f'{year}{month:02d}'\n",
" prefix = f'/data/sallen/results/MEOPAR/v201905r_wrap/SalishSea_1m_{datestr}_{datestr}'\n",
" \n",
" # Load grazing variables\n",
" with xr.open_dataset(prefix + '_dia2_T.nc') as ds:\n",
" q = np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data\n",
" q2 = q[0,:,:]\n",
" monthly_array_Z1diatoms_depthint_slice[year-2007,month-1,:,:] = q2 #year2015 is index 0 along 1st dimension\n",
" for var in ['GRMICZDIAT']:\n",
" data[var].append(np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data)\n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" # Concatenate months\n",
" #for var in variables: aggregates[var][year] = np.concatenate(data[var]).mean(axis=0)\n",
"# # Calculate 5 year mean and anomalies\n",
"# for var in variables:\n",
"# aggregates[var][‘mean’] = np.concatenate([aggregates[var][year][None, ...] for year in years]).mean(axis=0)\n",
"# for year in years: aggregates[var][year] = aggregates[var][year] - aggregates[var][‘mean’]\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(14, 12)\n"
]
}
],
"source": [
"monthly_array_Z1diatoms_depthint_slice=np.where(np.isnan(monthly_array_Z1diatoms_depthint_slice), 0, monthly_array_Z1diatoms_depthint_slice)\n",
"monthly_array_Z1diatoms_depthint_slicemean = \\\n",
"np.nanmean(np.nanmean(monthly_array_Z1diatoms_depthint_slice, axis = 2),axis = 2)\n",
"print(np.shape(monthly_array_Z1diatoms_depthint_slicemean))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Select 4 warmest and 4 coldest years; leave NPGO \"neutral\" years out"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"#2008, 2010, 2011, 2012\n",
"NPGO_C_Z1diat=np.array([[monthly_array_Z1diatoms_depthint_slicemean[1,:]],[monthly_array_Z1diatoms_depthint_slicemean[3,:]],\\\n",
" [monthly_array_Z1diatoms_depthint_slicemean[4,:]],[monthly_array_Z1diatoms_depthint_slicemean[5,:]]])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_Z1diat_mean=NPGO_C_Z1diat.mean(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_Z1diat_std=NPGO_C_Z1diat.std(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"#2015, 2018, 2019, 2020\n",
"NPGO_W_Z1diat=np.array([[monthly_array_Z1diatoms_depthint_slicemean[8,:]],[monthly_array_Z1diatoms_depthint_slicemean[11,:]],\\\n",
" [monthly_array_Z1diatoms_depthint_slicemean[12,:]],[monthly_array_Z1diatoms_depthint_slicemean[13,:]]])\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_Z1diat_mean=NPGO_W_Z1diat.mean(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_Z1diat_std=NPGO_W_Z1diat.std(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"5.853982189725535"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_C_Z1diat_mean.max()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"6.757904071950235"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_W_Z1diat_mean.max()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Load files from monthly averages"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Z1 grazing on Nanoflagellates"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"\n",
"#years, months, data\n",
"monthly_array_Z1flag_depthint_slice = np.zeros([14,12,50,50])\n",
"# Load monthly averages\n",
"mask = xr.open_dataset('/data/eolson/results/MEOPAR/NEMO-forcing-new/grid/mesh_mask201702.nc')\n",
"slc = {'y': slice(450,500), 'x': slice(250,300)}\n",
"e3t, tmask = [mask[var].isel(z=slice(None, 27),**slc).values for var in ('e3t_0', 'tmask')]\n",
"years, variables = range(2007, 2021), ['GRMICZPHY']\n",
"# Temporary list dict\n",
"data = {}\n",
"# Permanent aggregate dict\n",
"#aggregates = {var: {} for var in variables}\n",
"#monthlydat = {var: {} for var in variables}\n",
"\n",
"# Loop through years\n",
"for year in [2007,2008,2009,2010,2011,2012,2015,2016,2017,2018,2019,2020]:\n",
" # Initialize lists\n",
" for var in variables: data[var] = []\n",
" # Load monthly averages\n",
" for month in range(1, 13):\n",
" datestr = f'{year}{month:02d}'\n",
" prefix = f'/data/sallen/results/MEOPAR/v201905r/SalishSea_1m_{datestr}_{datestr}'\n",
" \n",
" # Load grazing variables\n",
" with xr.open_dataset(prefix + '_dia2_T.nc') as ds:\n",
" q = np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data\n",
" q2 = q[0,:,:]\n",
" monthly_array_Z1flag_depthint_slice[year-2007,month-1,:,:] = q2 #year2015 is index 0 along 1st dimension\n",
" for var in ['GRMICZPHY']:\n",
" data[var].append(np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data)\n",
" \n",
"# Loop through years for wrap files\n",
"for year in [2013,2014]:\n",
" # Initialize lists\n",
" for var in variables: data[var] = []\n",
" # Load monthly averages\n",
" for month in range(1, 13):\n",
" datestr = f'{year}{month:02d}'\n",
" prefix = f'/data/sallen/results/MEOPAR/v201905r_wrap/SalishSea_1m_{datestr}_{datestr}'\n",
" \n",
" # Load grazing variables\n",
" with xr.open_dataset(prefix + '_dia2_T.nc') as ds:\n",
" q = np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data\n",
" q2 = q[0,:,:]\n",
" monthly_array_Z1flag_depthint_slice[year-2007,month-1,:,:] = q2 #year2015 is index 0 along 1st dimension\n",
" for var in ['GRMICZPHY']:\n",
" data[var].append(np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data)\n",
" \n",
" \n",
" \n",
" \n",
" # Concatenate months\n",
" #for var in variables: aggregates[var][year] = np.concatenate(data[var]).mean(axis=0)\n",
"# # Calculate 5 year mean and anomalies\n",
"# for var in variables:\n",
"# aggregates[var][‘mean’] = np.concatenate([aggregates[var][year][None, ...] for year in years]).mean(axis=0)\n",
"# for year in years: aggregates[var][year] = aggregates[var][year] - aggregates[var][‘mean’]\n",
"\n",
"\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(14, 12)\n"
]
}
],
"source": [
"monthly_array_Z1flag_depthint_slice[monthly_array_Z1flag_depthint_slice == 0 ] = np.nan\n",
"monthly_array_Z1flag_depthint_slicemean = \\\n",
"np.nanmean(np.nanmean(monthly_array_Z1flag_depthint_slice, axis = 2),axis = 2)\n",
"print(np.shape(monthly_array_Z1flag_depthint_slicemean))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Select 4 warmest and 4 coldest years; leave NPGO \"neutral\" years out"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"#2008, 2010, 2011, 2012\n",
"NPGO_C_Z1flag=np.array([[monthly_array_Z1flag_depthint_slicemean[1,:]],[monthly_array_Z1flag_depthint_slicemean[3,:]],\\\n",
" [monthly_array_Z1flag_depthint_slicemean[4,:]],[monthly_array_Z1flag_depthint_slicemean[5,:]]])"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_Z1flag_mean=NPGO_C_Z1flag.mean(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_Z1flag_std=NPGO_C_Z1flag.std(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"#2015, 2018, 2019, 2020\n",
"NPGO_W_Z1flag=np.array([[monthly_array_Z1flag_depthint_slicemean[8,:]],[monthly_array_Z1flag_depthint_slicemean[11,:]],\\\n",
" [monthly_array_Z1flag_depthint_slicemean[12,:]],[monthly_array_Z1flag_depthint_slicemean[13,:]]])\n"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_Z1flag_mean=NPGO_W_Z1flag.mean(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_Z1flag_std=NPGO_W_Z1flag.std(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"5.543413180928081"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_C_Z1flag_mean.max()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"6.664183563148394"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_W_Z1flag_mean.max()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Z1 Grazing on both diatoms and nanoflagelles for Cold Years"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_Z1Both=NPGO_C_Z1diat_mean+NPGO_C_Z1flag_mean"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0.10268752, 0.42718894, 1.05655672, 4.58719945, 6.87334479,\n",
" 7.61734177, 8.85194247, 6.29357942, 3.35244758, 0.56951175,\n",
" 0.11327659, 0.08977801])"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_C_Z1Both"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
"#### Z1 Grazing on both diatoms and nanoflagelles for Warm Years"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_Z1Both=NPGO_W_Z1diat_mean+NPGO_W_Z1flag_mean"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0.14284651, 0.52294073, 3.93385487, 7.52276735, 6.2666193 ,\n",
" 7.42655869, 7.66459905, 6.1478577 , 2.3778494 , 0.37108638,\n",
" 0.14533633, 0.07999317])"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_W_Z1Both"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3.3279045835973626"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_C_Z1Both.mean()"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3.5501924577589943"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_W_Z1Both.mean()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load monthly average files for Z1 biomass"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"\n",
"\n",
"#years, months, data\n",
"monthly_array_microzooplankton_depthint_slice = np.zeros([14,12,50,50])\n",
"# Load monthly averages\n",
"mask = xr.open_dataset('/data/eolson/results/MEOPAR/NEMO-forcing-new/grid/mesh_mask201702.nc')\n",
"slc = {'y': slice(450,500), 'x': slice(250,300)}\n",
"e3t, tmask = [mask[var].isel(z=slice(None, 27),**slc).values for var in ('e3t_0', 'tmask')]\n",
"years, variables = range(2007, 2021), ['microzooplankton']\n",
"# Temporary list dict\n",
"data = {}\n",
"# Permanent aggregate dict\n",
"aggregates = {var: {} for var in variables}\n",
"monthlydat = {var: {} for var in variables}\n",
"\n",
"# Loop through years\n",
"for year in [2007,2008,2009,2010,2011,2012,2016,2017,2018,2019,2020]:\n",
" # Initialize lists\n",
" for var in variables: data[var] = []\n",
" # Load monthly averages\n",
" for month in range(1, 13):\n",
" datestr = f'{year}{month:02d}'\n",
" prefix = f'/data/sallen/results/MEOPAR/v201905r/SalishSea_1m_{datestr}_{datestr}'\n",
" # Load grazing variables\n",
" with xr.open_dataset(prefix + '_ptrc_T.nc') as ds:\n",
" q = np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data\n",
" q2 = q[0,:,:]\n",
" monthly_array_microzooplankton_depthint_slice[year-2007,month-1,:,:] = q2 #year2015 is index 0 along 1st dimension\n",
" for var in ['microzooplankton']:\n",
" data[var].append(np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data)\n",
" # Concatenate months\n",
" for var in variables: aggregates[var][year] = np.concatenate(data[var]).mean(axis=0)\n",
"\n",
"# Loop through years for wrap files\n",
"for year in [2013,2014,2015]:\n",
" # Initialize lists\n",
" for var in variables: data[var] = []\n",
" # Load monthly averages\n",
" for month in range(1, 13):\n",
" datestr = f'{year}{month:02d}'\n",
" prefix = f'/data/sallen/results/MEOPAR/v201905r_wrap/SalishSea_1m_{datestr}_{datestr}'\n",
" # Load grazing variables\n",
" with xr.open_dataset(prefix + '_ptrc_T.nc') as ds:\n",
" q = np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data\n",
" q2 = q[0,:,:]\n",
" monthly_array_microzooplankton_depthint_slice[year-2007,month-1,:,:] = q2 #year2015 is index 0 along 1st dimension\n",
" for var in ['microzooplankton']:\n",
" data[var].append(np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data)\n",
" # Concatenate months\n",
" for var in variables: aggregates[var][year] = np.concatenate(data[var]).mean(axis=0) \n",
" \n",
" \n",
"# # Calculate 5 year mean and anomalies\n",
"# for var in variables:\n",
"# aggregates[var][‘mean’] = np.concatenate([aggregates[var][year][None, ...] for year in years]).mean(axis=0)\n",
"# for year in years: aggregates[var][year] = aggregates[var][year] - aggregates[var][‘mean’]\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(14, 12)\n"
]
}
],
"source": [
"monthly_array_microzooplankton_depthint_slice[monthly_array_microzooplankton_depthint_slice == 0 ] = np.nan\n",
"monthly_array_microzooplankton_depthint_slicemean = \\\n",
"np.nanmean(np.nanmean(monthly_array_microzooplankton_depthint_slice, axis = 2),axis = 2)\n",
"print(np.shape(monthly_array_microzooplankton_depthint_slicemean))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Select 4 warmest and 4 coldest years; leave NPGO \"neutral\" years out"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"#2008, 2010, 2011, 2012\n",
"NPGO_C_micro=np.array([[monthly_array_microzooplankton_depthint_slicemean[1,:]],[monthly_array_microzooplankton_depthint_slicemean[3,:]],\\\n",
" [monthly_array_microzooplankton_depthint_slicemean[4,:]],[monthly_array_microzooplankton_depthint_slicemean[5,:]]])"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_micro_mean=NPGO_C_micro.mean(axis=0).flatten()*5.7*12/1000"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_micro_std=NPGO_C_micro.std(axis=0).flatten()*5.7*12/1000"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [],
"source": [
"#2015, 2018, 2019, 2020\n",
"NPGO_W_micro=np.array([[monthly_array_microzooplankton_depthint_slicemean[8,:]],[monthly_array_microzooplankton_depthint_slicemean[11,:]],\\\n",
" [monthly_array_microzooplankton_depthint_slicemean[12,:]],[monthly_array_microzooplankton_depthint_slicemean[13,:]]])\n"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_micro_mean=NPGO_W_micro.mean(axis=0).flatten()*5.7*12/1000"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_micro_std=NPGO_W_micro.std(axis=0).flatten()*5.7*12/1000"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Cold Years')"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"## Plot Figure 4a\n",
"\n",
"fig, ax = plt.subplots(figsize=(7,5))\n",
"bbox = {'boxstyle': 'round', 'facecolor': 'w', 'alpha': 0.9}\n",
"cmap = plt.get_cmap('tab10')\n",
"palette = [cmap(0), cmap(0.2), 'k', cmap(0.1), cmap(0.3)]\n",
"xticks=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov',\"Dec\"]\n",
"\n",
"ax2=ax.twinx()\n",
"\n",
"ax2.plot(xticks, NPGO_C_micro_mean,label='Z1',color='b',linestyle='--',linewidth=3)\n",
"\n",
"\n",
"ax.bar(xticks,NPGO_C_Z1diat_mean,color='grey',edgecolor='k',hatch='//',alpha=0.7,label='Diatoms')\n",
"ax.bar(xticks,NPGO_C_Z1flag_mean,color='grey',edgecolor='k',label='Nanoflagellates',alpha=0.5,bottom=NPGO_C_Z1diat_mean)\n",
"\n",
"\n",
"\n",
"ax2.set_ylim(0,5)\n",
"ax2.set_ylabel('Biomass (g C m$^{-2}$)',fontsize=14)\n",
"\n",
"ax.legend(frameon=False,loc=2)\n",
"ax2.legend(frameon=False,loc=1)\n",
"ax.set_ylim(0,12)\n",
"ax.set_ylabel('Grazing (mmol N m$^{-2}$ d$^{-1}$)',fontsize=14)\n",
"ax.set_xlabel('',fontsize=14)\n",
"#ax.tick_params(axis='x', labelrotation=0)\n",
"\n",
"ax.text(-.5, 12.5, '(a)', fontsize=15, color='k')\n",
"\n",
"ax.set_title('Cold Years',fontsize=18)\n",
"\n",
"#plt.savefig('Fig6a.png', bbox_inches='tight',dpi=1000,transparent=False)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Warm Years')"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"## Plot Figure 4b\n",
"\n",
"fig, ax = plt.subplots(figsize=(7,5))\n",
"bbox = {'boxstyle': 'round', 'facecolor': 'w', 'alpha': 0.9}\n",
"cmap = plt.get_cmap('tab10')\n",
"palette = [cmap(0), cmap(0.2), 'k', cmap(0.1), cmap(0.3)]\n",
"xticks=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov',\"Dec\"]\n",
"\n",
"ax2=ax.twinx()\n",
"\n",
"ax2.plot(xticks, NPGO_W_micro_mean,label='Z1',color='r',linestyle='--',linewidth=3)\n",
"\n",
"\n",
"ax.bar(xticks,NPGO_W_Z1diat_mean,color='grey',edgecolor='k',hatch='//',alpha=0.7,label='Diatoms')\n",
"ax.bar(xticks,NPGO_W_Z1flag_mean,color='grey',edgecolor='k',label='Nanoflagellates',alpha=0.5,bottom=NPGO_W_Z1diat_mean)\n",
"\n",
"\n",
"\n",
"ax2.set_ylim(0,5)\n",
"ax2.set_ylabel('Biomass (g C m$^{-2}$)',fontsize=14)\n",
"\n",
"ax2.legend(frameon=False,loc=1)\n",
"ax.set_ylim(0,12)\n",
"ax.set_ylabel('Grazing (mmol N m$^{-2}$ d$^{-1}$)',fontsize=14)\n",
"ax.set_xlabel('',fontsize=14)\n",
"\n",
"#ax.tick_params(axis='x', labelrotation=0)\n",
"ax.text(-.5, 12.5, '(b)', fontsize=15, color='k')\n",
"\n",
"ax.set_title('Warm Years',fontsize=18)\n",
"\n",
"#plt.savefig('Fig6b.png', bbox_inches='tight',dpi=1000,transparent=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Z2 grazing on Diatoms"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [],
"source": [
"#years, months, data\n",
"monthly_array_Z2diatoms_depthint_slice = np.zeros([14,12,50,50])\n",
"# Load monthly averages\n",
"mask = xr.open_dataset('/data/eolson/results/MEOPAR/NEMO-forcing-new/grid/mesh_mask201702.nc')\n",
"slc = {'y': slice(450,500), 'x': slice(250,300)}\n",
"e3t, tmask = [mask[var].isel(z=slice(None, 27),**slc).values for var in ('e3t_0', 'tmask')]\n",
"years, variables = range(2007, 2021), ['GRMESZDIAT']\n",
"# Temporary list dict\n",
"data = {}\n",
"# Permanent aggregate dict\n",
"#aggregates = {var: {} for var in variables}\n",
"#monthlydat = {var: {} for var in variables}\n",
"\n",
"# Loop through years\n",
"for year in [2007,2008,2009,2010,2011,2012,2015,2016,2017,2018,2019,2020]:\n",
" # Initialize lists\n",
" for var in variables: data[var] = []\n",
" # Load monthly averages\n",
" for month in range(1, 13):\n",
" datestr = f'{year}{month:02d}'\n",
" prefix = f'/data/sallen/results/MEOPAR/v201905r/SalishSea_1m_{datestr}_{datestr}'\n",
" \n",
" # Load grazing variables\n",
" with xr.open_dataset(prefix + '_dia2_T.nc') as ds:\n",
" q = np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data\n",
" q2 = q[0,:,:]\n",
" monthly_array_Z2diatoms_depthint_slice[year-2007,month-1,:,:] = q2 #year2015 is index 0 along 1st dimension\n",
" for var in ['GRMESZDIAT']:\n",
" data[var].append(np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data)\n",
" \n",
"# Loop through years for wrap files\n",
"for year in [2013,2014]:\n",
" # Initialize lists\n",
" for var in variables: data[var] = []\n",
" # Load monthly averages\n",
" for month in range(1, 13):\n",
" datestr = f'{year}{month:02d}'\n",
" prefix = f'/data/sallen/results/MEOPAR/v201905r_wrap/SalishSea_1m_{datestr}_{datestr}'\n",
" \n",
" # Load grazing variables\n",
" with xr.open_dataset(prefix + '_dia2_T.nc') as ds:\n",
" q = np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data\n",
" q2 = q[0,:,:]\n",
" monthly_array_Z2diatoms_depthint_slice[year-2007,month-1,:,:] = q2 #year2015 is index 0 along 1st dimension\n",
" for var in ['GRMESZDIAT']:\n",
" data[var].append(np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data)\n",
"\n",
" \n",
" \n",
" \n",
" \n",
" # Concatenate months\n",
" #for var in variables: aggregates[var][year] = np.concatenate(data[var]).mean(axis=0)\n",
"# # Calculate 5 year mean and anomalies\n",
"# for var in variables:\n",
"# aggregates[var][‘mean’] = np.concatenate([aggregates[var][year][None, ...] for year in years]).mean(axis=0)\n",
"# for year in years: aggregates[var][year] = aggregates[var][year] - aggregates[var][‘mean’]\n",
"\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(14, 12)\n"
]
}
],
"source": [
"monthly_array_Z2diatoms_depthint_slice[monthly_array_Z2diatoms_depthint_slice == 0 ] = np.nan\n",
"monthly_array_Z2diatoms_depthint_slicemean = \\\n",
"np.nanmean(np.nanmean(monthly_array_Z2diatoms_depthint_slice, axis = 2),axis = 2)\n",
"print(np.shape(monthly_array_Z2diatoms_depthint_slicemean))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Select 4 warmest and 4 coldest years; leave NPGO \"neutral\" years out"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [],
"source": [
"#2008, 2010, 2011, 2012\n",
"NPGO_C_Z2diat=np.array([[monthly_array_Z2diatoms_depthint_slicemean[1,:]],[monthly_array_Z2diatoms_depthint_slicemean[3,:]],\\\n",
" [monthly_array_Z2diatoms_depthint_slicemean[4,:]],[monthly_array_Z2diatoms_depthint_slicemean[5,:]]])"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_Z2diat_mean=NPGO_C_Z2diat.mean(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_Z2diat_std=NPGO_C_Z2diat.std(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [],
"source": [
"#2015, 2018, 2019, 2020\n",
"NPGO_W_Z2diat=np.array([[monthly_array_Z2diatoms_depthint_slicemean[8,:]],[monthly_array_Z2diatoms_depthint_slicemean[11,:]],\\\n",
" [monthly_array_Z2diatoms_depthint_slicemean[12,:]],[monthly_array_Z2diatoms_depthint_slicemean[13,:]]])\n"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_Z2diat_mean=NPGO_W_Z2diat.mean(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_Z2diat_std=NPGO_W_Z2diat.std(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"10.04984063299166"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_C_Z2diat_mean.max()"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"7.914635270032661"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_W_Z2diat_mean.max()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Z2 grazing on Nanoflagellates"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [],
"source": [
"\n",
"#years, months, data\n",
"monthly_array_Z2flag_depthint_slice = np.zeros([14,12,50,50])\n",
"# Load monthly averages\n",
"mask = xr.open_dataset('/data/eolson/results/MEOPAR/NEMO-forcing-new/grid/mesh_mask201702.nc')\n",
"slc = {'y': slice(450,500), 'x': slice(250,300)}\n",
"e3t, tmask = [mask[var].isel(z=slice(None, 27),**slc).values for var in ('e3t_0', 'tmask')]\n",
"years, variables = range(2007, 2021), ['GRMESZPHY']\n",
"# Temporary list dict\n",
"data = {}\n",
"# Permanent aggregate dict\n",
"#aggregates = {var: {} for var in variables}\n",
"#monthlydat = {var: {} for var in variables}\n",
"\n",
"# Loop through years\n",
"for year in [2007,2008,2009,2010,2011,2012,2015,2016,2017,2018,2019,2020]:\n",
" # Initialize lists\n",
" for var in variables: data[var] = []\n",
" # Load monthly averages\n",
" for month in range(1, 13):\n",
" datestr = f'{year}{month:02d}'\n",
" prefix = f'/data/sallen/results/MEOPAR/v201905r/SalishSea_1m_{datestr}_{datestr}'\n",
" \n",
" # Load grazing variables\n",
" with xr.open_dataset(prefix + '_dia2_T.nc') as ds:\n",
" q = np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data\n",
" q2 = q[0,:,:]\n",
" monthly_array_Z2flag_depthint_slice[year-2007,month-1,:,:] = q2 #year2015 is index 0 along 1st dimension\n",
" for var in ['GRMESZPHY']:\n",
" data[var].append(np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data)\n",
" \n",
"# Loop through years for wrap files\n",
"for year in [2013,2014]:\n",
" # Initialize lists\n",
" for var in variables: data[var] = []\n",
" # Load monthly averages\n",
" for month in range(1, 13):\n",
" datestr = f'{year}{month:02d}'\n",
" prefix = f'/data/sallen/results/MEOPAR/v201905r_wrap/SalishSea_1m_{datestr}_{datestr}'\n",
" \n",
" # Load grazing variables\n",
" with xr.open_dataset(prefix + '_dia2_T.nc') as ds:\n",
" q = np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data\n",
" q2 = q[0,:,:]\n",
" monthly_array_Z2flag_depthint_slice[year-2007,month-1,:,:] = q2 #year2015 is index 0 along 1st dimension\n",
" for var in ['GRMESZPHY']:\n",
" data[var].append(np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data)\n",
" \n",
" \n",
" # Concatenate months\n",
" #for var in variables: aggregates[var][year] = np.concatenate(data[var]).mean(axis=0)\n",
"# # Calculate 5 year mean and anomalies\n",
"# for var in variables:\n",
"# aggregates[var][‘mean’] = np.concatenate([aggregates[var][year][None, ...] for year in years]).mean(axis=0)\n",
"# for year in years: aggregates[var][year] = aggregates[var][year] - aggregates[var][‘mean’]\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(14, 12)\n"
]
}
],
"source": [
"monthly_array_Z2flag_depthint_slice[monthly_array_Z2flag_depthint_slice == 0 ] = np.nan\n",
"monthly_array_Z2flag_depthint_slicemean = \\\n",
"np.nanmean(np.nanmean(monthly_array_Z2flag_depthint_slice, axis = 2),axis = 2)\n",
"print(np.shape(monthly_array_Z2flag_depthint_slicemean))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Select 4 warmest and 4 coldest years; leave NPGO \"neutral\" years out"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [],
"source": [
"#2008, 2010, 2011, 2012\n",
"NPGO_C_Z2flag=np.array([[monthly_array_Z2flag_depthint_slicemean[1,:]],[monthly_array_Z2flag_depthint_slicemean[3,:]],\\\n",
" [monthly_array_Z2flag_depthint_slicemean[4,:]],[monthly_array_Z2flag_depthint_slicemean[5,:]]])"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_Z2flag_mean=NPGO_C_Z2flag.mean(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_Z2flag_std=NPGO_C_Z2flag.std(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [],
"source": [
"#2015, 2018, 2019, 2020\n",
"NPGO_W_Z2flag=np.array([[monthly_array_Z2flag_depthint_slicemean[8,:]],[monthly_array_Z2flag_depthint_slicemean[11,:]],\\\n",
" [monthly_array_Z2flag_depthint_slicemean[12,:]],[monthly_array_Z2flag_depthint_slicemean[13,:]]])\n"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_Z2flag_mean=NPGO_W_Z2flag.mean(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_Z2flag_std=NPGO_W_Z2flag.std(axis=0).flatten()*86400*1.111"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"4.57174370398066"
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_C_Z2flag_mean.max()"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"6.748131637343641"
]
},
"execution_count": 59,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_W_Z2flag_mean.max()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Z2 Grazing on both diatoms and nanoflagelles for Cold Years"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_Z2Both=NPGO_C_Z2diat_mean+NPGO_C_Z2flag_mean"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 0.40363747, 0.76335678, 1.57293094, 8.17927261, 10.74823302,\n",
" 8.98512417, 7.51202381, 7.47978546, 6.9654041 , 1.55658343,\n",
" 0.41548779, 0.29453213])"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_C_Z2Both"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Z2 Grazing on both diatoms and nanoflagelles for Warm Years"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_Z2Both=NPGO_W_Z2diat_mean+NPGO_W_Z2flag_mean"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0.4195334 , 0.81169948, 4.04578856, 7.94181399, 8.96287137,\n",
" 7.89249682, 7.91523199, 8.0897084 , 4.56273968, 1.08587646,\n",
" 0.57738917, 0.28770183])"
]
},
"execution_count": 63,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_W_Z2Both"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"4.573030975739248"
]
},
"execution_count": 64,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_C_Z2Both.mean()"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"4.382737596046964"
]
},
"execution_count": 65,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"NPGO_W_Z2Both.mean()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load monthly average files for Z2 biomass"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [],
"source": [
"\n",
"\n",
"#years, months, data\n",
"monthly_array_mesozooplankton_depthint_slice = np.zeros([14,12,50,50])\n",
"# Load monthly averages\n",
"mask = xr.open_dataset('/data/eolson/results/MEOPAR/NEMO-forcing-new/grid/mesh_mask201702.nc')\n",
"slc = {'y': slice(450,500), 'x': slice(250,300)}\n",
"e3t, tmask = [mask[var].isel(z=slice(None, 27),**slc).values for var in ('e3t_0', 'tmask')]\n",
"years, variables = range(2007, 2021), ['mesozooplankton']\n",
"# Temporary list dict\n",
"data = {}\n",
"# Permanent aggregate dict\n",
"aggregates = {var: {} for var in variables}\n",
"monthlydat = {var: {} for var in variables}\n",
"\n",
"# Loop through years\n",
"for year in [2007,2008,2009,2010,2011,2012,2016,2017,2018,2019,2020]:\n",
" # Initialize lists\n",
" for var in variables: data[var] = []\n",
" # Load monthly averages\n",
" for month in range(1, 13):\n",
" datestr = f'{year}{month:02d}'\n",
" prefix = f'/data/sallen/results/MEOPAR/v201905r/SalishSea_1m_{datestr}_{datestr}'\n",
" # Load grazing variables\n",
" with xr.open_dataset(prefix + '_ptrc_T.nc') as ds:\n",
" q = np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data\n",
" q2 = q[0,:,:]\n",
" monthly_array_mesozooplankton_depthint_slice[year-2007,month-1,:,:] = q2 #year2015 is index 0 along 1st dimension\n",
" for var in ['mesozooplankton']:\n",
" data[var].append(np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data)\n",
" # Concatenate months\n",
" for var in variables: aggregates[var][year] = np.concatenate(data[var]).mean(axis=0)\n",
"\n",
"# Loop through years for wrap files\n",
"for year in [2013,2014,2015]:\n",
" # Initialize lists\n",
" for var in variables: data[var] = []\n",
" # Load monthly averages\n",
" for month in range(1, 13):\n",
" datestr = f'{year}{month:02d}'\n",
" prefix = f'/data/sallen/results/MEOPAR/v201905r_wrap/SalishSea_1m_{datestr}_{datestr}'\n",
" # Load grazing variables\n",
" with xr.open_dataset(prefix + '_ptrc_T.nc') as ds:\n",
" q = np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data\n",
" q2 = q[0,:,:]\n",
" monthly_array_mesozooplankton_depthint_slice[year-2007,month-1,:,:] = q2 #year2015 is index 0 along 1st dimension\n",
" for var in ['mesozooplankton']:\n",
" data[var].append(np.ma.masked_where(tmask == 0, ds[var].isel(deptht=slice(None, 27), **slc).values * e3t).sum(axis=1).data)\n",
" # Concatenate months\n",
" for var in variables: aggregates[var][year] = np.concatenate(data[var]).mean(axis=0) \n",
" \n",
" \n",
"# # Calculate 5 year mean and anomalies\n",
"# for var in variables:\n",
"# aggregates[var][‘mean’] = np.concatenate([aggregates[var][year][None, ...] for year in years]).mean(axis=0)\n",
"# for year in years: aggregates[var][year] = aggregates[var][year] - aggregates[var][‘mean’]\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(14, 12)\n"
]
}
],
"source": [
"monthly_array_mesozooplankton_depthint_slice[monthly_array_mesozooplankton_depthint_slice == 0 ] = np.nan\n",
"monthly_array_mesozooplankton_depthint_slicemean = \\\n",
"np.nanmean(np.nanmean(monthly_array_mesozooplankton_depthint_slice, axis = 2),axis = 2)\n",
"print(np.shape(monthly_array_mesozooplankton_depthint_slicemean))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Select 4 warmest and 4 coldest years; leave NPGO \"neutral\" years out"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {},
"outputs": [],
"source": [
"#2008, 2010, 2011, 2012\n",
"NPGO_C_meso=np.array([[monthly_array_mesozooplankton_depthint_slicemean[1,:]],[monthly_array_mesozooplankton_depthint_slicemean[3,:]],\\\n",
" [monthly_array_mesozooplankton_depthint_slicemean[4,:]],[monthly_array_mesozooplankton_depthint_slicemean[5,:]]])"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_meso_mean=NPGO_C_meso.mean(axis=0).flatten()*5.7*12/1000"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {},
"outputs": [],
"source": [
"NPGO_C_meso_std=NPGO_C_meso.std(axis=0).flatten()*5.7*12/1000"
]
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {},
"outputs": [],
"source": [
"#2015, 2018, 2019, 2020\n",
"NPGO_W_meso=np.array([[monthly_array_mesozooplankton_depthint_slicemean[8,:]],[monthly_array_mesozooplankton_depthint_slicemean[11,:]],\\\n",
" [monthly_array_mesozooplankton_depthint_slicemean[12,:]],[monthly_array_mesozooplankton_depthint_slicemean[13,:]]])\n"
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_meso_mean=NPGO_W_meso.mean(axis=0).flatten()*5.7*12/1000"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {},
"outputs": [],
"source": [
"NPGO_W_meso_std=NPGO_W_meso.std(axis=0).flatten()*5.7*12/1000"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 1.0, '')"
]
},
"execution_count": 74,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"### Plot Figure 6C\n",
"\n",
"fig, ax = plt.subplots(figsize=(7,5))\n",
"bbox = {'boxstyle': 'round', 'facecolor': 'w', 'alpha': 0.9}\n",
"cmap = plt.get_cmap('tab10')\n",
"palette = [cmap(0), cmap(0.2), 'k', cmap(0.1), cmap(0.3)]\n",
"xticks=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov',\"Dec\"]\n",
"\n",
"ax2=ax.twinx()\n",
"\n",
"ax2.plot(xticks, NPGO_C_meso_mean,label='Z2',color='b',linewidth=3)\n",
"\n",
"ax.bar(xticks,NPGO_C_Z2diat_mean,color='grey',edgecolor='k',hatch='//',alpha=0.7,label='Diatoms')\n",
"ax.bar(xticks,NPGO_C_Z2flag_mean,color='grey',edgecolor='k',label='Nanoflagellates',alpha=0.5,bottom=NPGO_C_Z2diat_mean)\n",
"\n",
"\n",
"\n",
"ax2.set_ylim(0,5)\n",
"ax2.set_ylabel('Biomass (g C m$^{-2}$)',fontsize=14)\n",
"\n",
"#ax.legend(frameon=False,loc=2)\n",
"ax2.legend(frameon=False,loc=1)\n",
"ax.set_ylim(0,12)\n",
"ax.set_ylabel('Grazing (mmol N m$^{-2}$ d$^{-1}$)',fontsize=14)\n",
"ax.set_xlabel('',fontsize=14)\n",
"#ax.tick_params(axis='x', labelrotation=0)\n",
"\n",
"ax.text(-.5, 12.5, '(c)', fontsize=15, color='k')\n",
"\n",
"ax.set_title('',fontsize=18)\n",
"\n",
"#plt.savefig('Fig6c.png', bbox_inches='tight',dpi=1000,transparent=False)"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5, 1.0, '')"
]
},
"execution_count": 75,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAqQAAAHNCAYAAADIVWmmAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAA9hAAAPYQGoP6dpAACPcUlEQVR4nO3dd1hT5/sG8DsMcSBDphP3wD1bN7hRHHVX66LWaq111FG3OKnW0WFtbd2jtWqrdWBrBfdWtPrT9utCxQGCbAQZ5/fHKSMQkCQnOSfh/lxXLs2bk3OeACE3ZzyvShAEAUREREREMrGQuwAiIiIiKtoYSImIiIhIVgykRERERCQrBlIiIiIikhUDKRERERHJioGUiIiIiGTFQEpEREREsmIgJSIiIiJZMZASERERkawYSBXC398flpaWuHXrVqGWX7BgAVQqFTZv3pw1JggCGjdujAYNGiAjI8NAlRIRERFJi4FUAcLDw/HFF19gwIAB8PT01Hk9KpUK8+bNw40bN9SCKhEREZGSMZAqwNKlS5GQkICZM2fqva4+ffqgdu3amDdvHtLS0iSojoiIiMiwGEhllpSUhC1btqBBgwZo2LCh3utTqVQYOnQonjx5gt9//12CComIiIgMi4FUZrt370ZsbCyGDh2q8fETJ07Ay8sLtra2cHJywjvvvIN//vmnwHUOGTIEAPDDDz9IXi8RERGR1KzkLqCoO3jwIADAy8srz2P79+9Hv379kJ6ejlatWqFSpUq4ePEi3nrrLfTs2TPfdVatWhUVK1ZEUFAQkpOTUbx4cUOVT0RERKQ37iGV2enTp2FtbZ3ncH18fDxGjx6N9PR07Ny5E2fOnMFPP/2Ef//9F++88w527NhR4HpbtGiB169f48KFC4Ysn4iIiEhvDKQyioiIwPPnz1G5cmXY2NioPbZ7925ERkaic+fOePfdd7PGrayssHr1atja2ha47tq1awMArl+/Ln3hRERERBJiIJVRREQEAMDR0THPY6dPnwYADBw4MM9jjo6O6NKlS4HrLlOmDADgxYsX+pZJREREZFAMpDKKjY0FAJQuXTrPY0+fPgUAVKpUSeNz8xvPZGdnp7YNIiIiIqViIJWRvb09ACAuLi7PY4IgABDbOOkiM4hmboOIiIhIqRhIZeTq6goAePnyZZ7HypUrBwB4+PChxuc+evSowHVHR0cDAFxcXPQpkYiIiMjgGEhl5OrqCnd3dzx8+BCvXr1Se6xNmzYAxIubcouJicGff/5Z4Lpv374NAGjUqJE0xRIREREZCAOpzNq2bYu0tDSEhISojQ8YMABlypTBn3/+iV9++SVrPD09HZ9++ikSEhIKXO/FixdRrFgxtGjRwiB1ExEREUmFgVRmPXr0AAAEBwerjdvZ2WH9+vWwsLDAoEGD0KZNGwwZMgS1atXCnj178p3ZCQDu3buHsLAwdOjQgU3xiYiISPEYSGU2cOBA2NvbY+fOnXke69evH44ePYq2bdsiJCQEgYGB8PT0xLlz51C9evV815m5rg8++MBgdRMRERFJRSVkXs5Nspk8eTLWrFmDK1euoEmTJnqtSxAE1KlTBwkJCQgNDYWVFWeHJSIiImXjHlIFmDlzJmxtbREQEKD3uvbt24d///0XCxcuZBglIiIik8A9pAqxcOFC+Pv748aNG/D09NRpHYIgoEmTJkhLS8P169dhYcG/N4iIiEj5GEiJiIiISFbchUZEREREsmIgJSIiIiJZMZASERERkawYSImIiIhIVgykRERERCQrBlIiIiIikpVJBdL4+HhMnz4dXbp0gYuLC1QqFRYsWKC2THp6OlatWoVu3bqhQoUKKFmyJOrUqYPPPvsMMTExstRNREREZAjHjx+HSqXSeDt//rzc5RWaSQXSqKgorF+/HikpKejTp4/GZV69eoUFCxbAw8MDa9asweHDh/HBBx9g/fr1aN26NV69emXcoomIiIgMbOnSpTh37pzarV69enKXVWgmNbekh4cHoqOjoVKpEBkZiR9//DHPMiVKlMCDBw/g5OSUNebl5YVKlSphwIAB2Lt3L9577z1jlk1ERERkUDVq1MDbb78tdxk6M6lAqlKp3riMpaWlWhjN1KJFCwDA48ePJa+LiIiIiHRnUoFUH0FBQQCAunXr5rtMSkoKUlJSsu6npaXh9u3bqFixIueFJyIiIoPLyMjAo0eP4OnpCSur7JhmY2MDGxubfJ83fvx4DB48GCVLlkTLli0xd+5ctGnTxhglS6JIBNInT57gs88+Q7NmzeDr65vvcsuWLYO/v78RKyMiIiJ6s/nz5+e5kBsA7O3tMXHiRHh5ecHJyQl3797FihUr4OXlhUOHDqFr167GL1YHKkEQBLmL0EVkZCRcXFzy/QZlevnyJby9vfH8+XOcO3cOVatWzXfZ3HtIHz9+jHr16uHixYsoW7aslOUTERER5fHs2TO0aNECN2/eRMWKFbPG37SHNKeYmBjUr18fZcqUwfXr1w1VqqTMeg9pdHQ0OnfujCdPniAoKKjAMArk/Wbb29sDAMqWLYsKFSoYtFYiIiKiTPb29rCzs9PpuQ4ODvD19cV3332HV69eoUSJEhJXJz2zDaTR0dHo1KkTHjx4gGPHjqFBgwZyl0RERERkFJkHwAtzQbgSmGUgzQyj9+/fx9GjR9G4cWO5SyIiIiIyiujoaBw8eBCNGjVC8eLF5S6nUEwukAYGBiIxMRHx8fEAgFu3bmHPnj0AgO7du0OlUqFr164ICQnBmjVrkJaWpjZTgYuLC6pVqyZL7URERERSGjJkCCpVqoRmzZrB2dkZd+7cwcqVKxEeHo7NmzfLXV6hmdxFTZUrV8bDhw81PvbgwQMAQJUqVfJ9/ogRIwr9DQoLC0PFihXx+PFjnkNKREREBqdt9ggICMCuXbvw4MEDJCQkoEyZMmjTpg1mzpyJ5s2bG6FiaZhcIDUmBlIiIiIypqKaPdjtnYiIiIhkxUBKRERERLJiICUiIiIiWTGQEhEREZGsGEiJiIiISFYMpEREREQkKwZSIiIiIpIVAykRERERyYqBlIiIiIo8lUr1xtuCBQvw7NkzzJkzBy1btoSzszPs7OzQtGlTrF+/Hunp6XK/DJNlcnPZExEREUnt3LlzGsfT0tIwfPhwPHnyBN27d8eVK1ewdetWDB8+HHPnzoW1tTUCAwMxbtw4nD9/Hhs3bjRy5eaBgZSIiIi0l5EBREXJXYVmTk6AhXYHgd9++22N45988gkePHiA77//Hi1atEB0dDTu3bsHa2vrrGU6d+6M169fY+3atfD390fFihX1Kr8oYiAlIiIi7UVFAa6uclehWUQE4OKi92q2bduGr7/+Gu+//z7GjBkDAHB0dNS4bIsWLbB27dqsuehJOzyHlIiIiCiXkJAQfPjhh2jevDnWrl37xuWDgoJgZWWFmjVrGqE688NASkRERJRDZGQk3nnnHdja2mLv3r2wsbEpcPk///wT27Ztw4QJE+Dk5GSkKs0LD9kTERER/Sc9PR2DBw9GWFgYjh49+sbD71evXsXAgQPx9ttvY9myZUaq0vwwkBIREZH2nJzEczWVSI+9lNOnT8exY8fwxRdfwNvbu8BlQ0JC0LlzZ9SoUQOHDx9+455Uyh8DKREREWnPwkKSC4eU5KeffsKqVaswaNAgfPrppwUuGxISgk6dOsHDwwN//vkn7O3tjVSleeI5pERERFTk/f333xg9ejTq1auHDRs2FLjstWvX0KlTJ1SoUAFHjx7N98p7KjzuISUiIqIiLTo6Gn369EFKSgpmzJiBGzduaFzOxcUFaWlp6NSpEwBgyZIluHPnDu7cuZO1TLVq1eBiZnuOjYGBlIiIiIq069ev48GDBwCAYcOG5bvciBEj4OXlhaj/JgTo2bNnnmU2bdqEkSNHGqROc8ZASkREREWal5cXBEEo9PIMnNLjOaREREREJCsGUiIiIiKSFQMpEREREcmKgZSIiIiIZMVASkRERESyYiAlIiIiIlkxkBIRERGRrBhIiYiIiEhWDKREREREJCsGUiIiIiKSFQMpEREREcmKgZSIiIiIZMVASkRERESyYiAlIiIiIlkxkBIRERGRrBhIiYiIiEhWDKREREREJCsGUiIiIiKSFQMpEREREcmKgZSIiIiIZMVASkRERESyYiAlIiIiIlkxkBIRERGRrBhIiYiIiEhWDKREREREJCsGUiIiIiKSFQMpEREREcmKgZSIiIiIZMVASkRERESyYiAlIiIiIlmZVCCNj4/H9OnT0aVLF7i4uEClUmHBggUal7169So6deoEW1tbODg4oG/fvrh//75xCyYiIiKiNzKpQBoVFYX169cjJSUFffr0yXe5f/75B15eXnj9+jV++eUXbNy4Ef/73//Qtm1bvHjxwngFExEREdEbWcldgDY8PDwQHR0NlUqFyMhI/PjjjxqXmzdvHmxsbHDw4EHY2dkBAJo2bYoaNWrgiy++wOeff27MsomIiPInCMDLl8C9e9m3+/fFfx89AsqXB775BmjUSO5KiQzGpAKpSqV64zJpaWk4ePAghg8fnhVGATHMent747fffmMgJSIi40pLA8LCNIfOe/eAuLj8nxsaCnTtCty9C5QubbSSiYzJpAJpYdy7dw+vXr1CgwYN8jzWoEEDHD16FMnJyShevHiex1NSUpCSkpJ1Pz4+3qC1EhGRGUlMVA+ZOf8fGiqGUl1FRABffw3MmiVZuURKYnaBNCoqCgBQpkyZPI+VKVMGgiAgOjoaZcuWzfP4smXL4O/vb/AaiYjIBAkCEB6ef+gMDzfs9lesAD76CHBwMOx2iGRgdoE0U0GH9/N7bObMmZgyZUrW/SdPnsDT01Py2oiISKFevwYePtQcOu/fF/eCGoqlJeDhAVSrJt5cXIBFi7Ifj4kBVq0CFi40XA1EMjG7QOrk5AQge09pTi9fvoRKpYJDPn9d2tjYwMbGJut+XEHn9BARkel6+BC4dEnzRUQZGYbbrq1tduCsVg2oWjX7/5UqAVa5Ppb/+QfYvTv7/po1wCefAM7OhquRSAaSBNJjx44hKCgIZ8+eRVhYGCIjI1GyZEm4uLigfv36aN++PXx9feHu7i7F5gpUrVo1lChRAjdu3Mjz2I0bN1C9enWN548SEVERsW4dMH68eAjeEMqVUw+aOYOnszNQiAt0syxYAOzZk11rfLx46J4X55KZ0TmQJiQk4KuvvsIPP/yAR48eQfjvzVK8eHGUKVMGr169ws2bN/H3339jx44dsLKyQq9evTB58mS0bt1asheQm5WVFXr27Ilff/0Vy5cvR+n/rkh89OgRgoODMXnyZINtm4iIFO7wYeDjj/ULo8WKAVWqaA6dVaoAJUtKV6+nJzB0KLB9e/bY118DkycDRtjJQ2QsOgXS7777DgsWLEBERAQaNmyIMWPGoGXLlmjWrBlsbW2zlhMEAXfu3MGFCxfw559/Yv/+/fjtt9/Qu3dvrFy5ElWqVNF624GBgUhMTMy6Av7WrVvYs2cPAKB79+4oWbIk/P390bx5c/j6+uKzzz5DcnIy5s2bB2dnZ3z66ae6vGQiIjJ1t28D775buEPyjo55D6ln3i9fXjzf01jmzwd++glITxfvv3oFBASIh++JzIRKELT/M9Ha2hpDhw7FtGnTULdu3UI/79WrV/jpp5+wbNkyDBs2DPPmzdN206hcuTIePnyo8bEHDx6gcuXKAIArV65gxowZOHfuHKysrNChQwd88cUXqFatWqG3FRYWhooVK+Lx48eoUKGC1rUSEZFCREUBb70lniea09tvA3Xr5g2djo7y1Jmf0aOBDRuy7xcrJr4WfjaZnaKaPXQKpPfu3dMq2OWWnp6OsLAweHh46LwOYyiqPxRERGYlNRXo1g0IClIfHzwY2LlTu3M65fLwIVCjhvhaMo0dK54PS2alqGYPneay1yeMAoClpaXiwygREZmJyZPzhtFmzYCNG00jjAJiO6gPPlAf+/FH4MEDeeohRfvxxx+hUqnUTqNUOp0CKRERkUn47jtg7Vr1sbJlgX37gBIlZClJZ7NnAzm7xKSlqfcpJYLYQ33q1KkoV66c3KVohYGUiIjM0/HjwIQJ6mM2NmIYLV9ejor0U66cOFNTTlu2AP/7nzz1kCKNHTsW7dq1Q+fOneUuRSuSBtLo6Ghs3bpVylUSERFp7/59oF+/vPPHb9wItGghT01SmDEDKFUq+35GhtirlAjA9u3bceLECXz77bdyl6I1SQPpo0ePMGrUKClXSUREpJ24OKBnT+DlS/XxmTOBIUPkqUkqrq7iTE05/fwzcPOmPPWQwcTHxyMuLi7rlpKSUuDyERERmDRpEgICAkzyYiitAumjR48KvD19+tRQdRIREb1ZerrYSP7WLfXxXr2AxYvlqUlqU6cCdnbZ9wVB7FVKZsXT0xP29vZZt2XLlhW4/EcffYRatWph3LhxRqpQWlo1xq9cuTJUBVyRKAhCgY8TEREZ1KxZwMGD6mP16okzHVmYyWUTZcoAU6aoH6r/9Vfg6lWgSRPZyiJp3bp1C+VznOtsY2OT77J79+7FgQMHEBISYrI5TKt3p6OjI7799lvcunVL4+3XX381VJ1EZGoCA4HmzcVm5CdOyF0NFQXbtgHLl6uPOTkBv/8O/DeNtNmYNEkMpjnpMNkMKVfp0qVhZ2eXdcsvkCYkJGD8+PGYMGECypUrh5iYGMTExOD169cAgJiYGCQmJhqzdJ1otYe0adOmePHiBWrVqqXx8eTkZOjQZ5+IzM3ateLVzZm/D7p2BQ4dAjp2lLcuMl/nz4uzGeVkZQXs3SvOL29u7O2BadPE82IzHToEnDsHtGwpX11kdJGRkQgPD8fKlSuxcuXKPI87Ojqid+/e2Ldvn/GL04JWgXTcuHEFpuxKlSph06ZNehdFRCZKEMRDpgEB6uMpKUDv3sDRo/ywJOk9fgz06QP8t0coy7ffAu3by1KSUUyYAKxeDUREZI/Nmye+z6jIcHd3R3BwcJ7xgIAAnDhxAoGBgXB2dpahMu3oNHVoUVFUp+8i0snr1+Ieqm3b8l/G3l7sDdmokbGqInOXlAS0bSueP5nThAnAV1/JU5MxrV4tnk+a0/Hj5h3EzZxU2WPkyJHYs2cPEhISJKzOcMzkDG8iklV8PODrW3AYBYDYWKBLF+Cff4xTF5k3QQBGjswbRjt1AlatkqUkoxs7VmyYn9PcudmnyxCZCL0DqaWlJR49eiRFLURkip49E/fG5D5MaGkJrFsH9OihPv7ihRgYOAc36WvRImD3bvWxGjWAX34Rzx8tCkqUAObMUR87dYqH7QmbN282mb2jgASBlEf8iYqwf/4RzwkNCVEfL1kS2L9f3Huzezfg7a3++JMnYihl72LS1d69eXtv2tuLV9Q7OspTk1zefx/w8FAfmzOHe0nJpPCQPRHp5uxZoHVr4OFD9XEXF/Ectsw9oyVKiOH0rbfUl7t/XwylL14YpVwyI9euAcOHq49ZWAC7dgG1a8tSkqyKFcvb8unSpbz9WIkUjIGUiLS3b5/Ywin31IzVqolBtXlz9fHSpcW+pA0aqI/fvi22hIqNNWi5ZEbCw8VZl5KS1MdXrhR/loqq4cOB6tXVx+bOFee6JzIBDKREpJ1164B+/YDkZPXxZs3EMJr7QzGToyPw559AzZrq4yEh4t5UE2jcTDJLSQHeeUds85STnx8wcaI8NSmFlZX6zE0AcP26eGoDkQlgICWiwhEEYPZs4KOP8u516d4dCA4GXF0LXoebG/DXX3nPdztzRuwjmTvkEmUSBPGc5HPn1MfbtBH7jZrodImSGjwY8PRUH5s/H0hPl6ceIi0wkBLRm6Wmiu11li7N+9j774vniNraFm5dFSuKodTdXX38r7/ED9TUVL3LJTO0ahWwebP6WKVK4h7AAub4LlIsLQF/f/Wx27eBn36Spx4iLTCQElHBMnuMbt2a97H584EfftC+xU716mIAdXJSH9+/Xwy+3KNDOR0+DEyfrj5WqpR4Rf2b9soXNX375p14wt+ff+iR4ukdSGfPng0HBwcJSiEixXn+HPDyEs/9zMnSUgyiCxbofqi0bl3gjz/EC55y2rkTGDeOLWtIdPs28O67eU8T2bYNaNhQnpqUzMICWLhQfezuXc1/UBIpiN6BdNGiRbCzs5OiFiJSkn//FXuM5p4Fp0QJ8Sr70aP130bTpsChQ+I6c/rhB2DqVIbSoi4qCujZE4iLUx9fvFi8uIk08/UFWrRQH1u4ULwojEiheMieiPI6d07sMRoaqj7u7CxevOTrK9222rYVA26xYurjq1bl3dNDRUdqKjBwIHDvnvr44MHArFny1GQqVCoxtOf06BGwYYM89RAVgk5zq/n5+em0MZVKhQ18QxAp2/794od+7iveq1YFjhwRp2aUWpcuwM8/AwMGqJ8/umCBeEh/yhTpt0nKNnkyEBSkPtasGbBxI6+oL4xOncQ/9k6dyh5bvBgYNSrvEQkiBVAJOsz9aWGheceqSqXSOJVo5rhKpUK6CV2sEBYWhooVK+Lx48eoUKGC3OUQGd7332tu69SsmTjri5ubYbe/fbvY4Dv375HvvwfGjDHstkk5vvtOPI84p7JlxdmHypeXpyZTdPIk0L69+tiqVWLYJ8UqqtlDpz2kDx48ULufkZGBiRMn4vz585g4cSLatm0LNzc3hIeH4+TJk/jqq6/QsmVLrF69WpKiiUhigiBOPZj7MB+A5A4dEPP99xAyMoBnzwxbR8eOKBkQAPsZM9TLGzsWKltbYMgQw26f5BccDEyYoD5mYyOe1sEwqp127cQ9pX/9lT22bBnwwQeFb9NGZCQ67SHNLSAgAKtXr8a1a9dQtmzZPI8/efIEjRs3xtSpUzE9d+sOBSuqf6VQEZOaKu59zN3jEcCVhg2xo21bZFhaGrUk7ytX0Pv0abUxwdISqr17gd69jVoLGdG9e+LFOLmnpN2xg3+M6Or8efHixJyWLgVmzpSnHnqjopo9JAmkNWrUQLdu3fD111/nu8zHH3+MP/74A3fu3NF3c0ZTVH8oqAhJSAD69xfbL+USP2kS5mZkoH6DBrK0dvP8+WfU2bNHfbBYMfHUgc6djV4PGVhcnBicbt1SH585U/OEDFR4PXuK75tMjo7AgweAvb18NVG+imr20OmQfW5hYWEoXrx4gcsUL14cYWFhUmyOiKTw/Lk4h3zutk4WFsC6dUjo2RP4/HM4ODjAKXcDeyMI/+gj2AKomDOUvn4tTjH6559iFwAyD+np4h7Q3GG0Vy+Np5GQlhYuVA+k0dHA6tXiRYNECiFJ26cKFSrgt99+Q3I+81AnJSXht99+K1JJn0jR/vc/oFWr/HuMKuECIpUK9z76CA86dlQfT0oCunfPWzuZrlmzxH60OdWrJ17kls9FtKSFxo2Bfv3Ux1avFvu8EimEJO/00aNH4/79+2jdujX279+PqP9+yKOiorBv3z60adMGoaGh+OCDD6TYHBHp4/x5MYzmujgxq8doz57y1KWJSoWrY8bgas2a6uNxcWKrqNx71Mj0bN0KLF+uPubsLE4LmnsWL9Kdv796u6y4OOCLL+SrhygXSQLptGnTMGrUKISEhKBv375wdXWFtbU1XF1d0a9fP1y7dg0jR47EtGnTpNgcEenqwAGgQ4e8e0aqVAHOnAHeekueugpiaYntXbogOfd5o1FR4hXE9+/LUxfp7/x58YrvnKysgL17xZ9Jkk7duuIUrDl99RUQHi5PPUS5SBJILSwssGHDBgQHB2PEiBFo3LgxKleujMaNG2PkyJEIDg7Ghg0boGIzYyL5fP+9eP7lq1fq402bijMz5d4LqSAZlpaI/v57MUzn9OwZ0LEjwPPTTc/jx+LP4+vX6uPffiu2KyLpzZ8P5OyYkZQEfP65fPUQ5SDJRU2Z2rdvj/a5m/ASkbwEQfwgWrQo72PdugG7d5tGT8LixcVZpLp0EQN0ptBQcU/pyZOAq6ts5ZEWEhPF9l2598598knePaYknZo1xYknNm3KHvv2W+DTT9njlfI4duwYgoKCcPbsWYSFhSEyMhIlS5aEi4sL6tevj/bt28PX1xfu7u6SbI9nixOZs9RU4P33NYfRkSPF8/RMIYxmsrUFDh8GGjVSH//3XzGoRkfLUhZpQRDE6StDQtTHO3cGVq6Up6aiZN48wNo6+35KCttqUZaEhAQsXboUVapUQZcuXbBs2TKcOHECT548QalSpZCcnIybN29ix44dGDNmDCpVqoT+/fvjzJkzem+bgZTIXCUkiHuhcu4NyTRnjjgneM4PJlPh4CC2fapdW338+nXx6vuEBFnKokJatEjcK59TjRrArl3i+aNkWJUri3+k5vTDD+KRBirSvvvuO1SvXh1z5syBg4MDFi9ejKCgIMTFxSEpKQlhYWGIiopCamoq/vnnH2zZsgWDBg3Cn3/+iXbt2qFv3755ZvLUBgMpkTkKDwe8vIDAQPVxCwtxnvBFi9SvuDU1Li7idIi5L3w5f14M4fm0oCOZ7d0rnj6Sk729eLGdo6M8NRVFs2eL07FmSk3VfBSFipQJEyagW7duuHHjBkJCQjBz5kx4eXnBNtdRNJVKhZo1a2LYsGHYtm0bwsPD8cMPP+DGjRvYtm2bzttnICUyN3fuiG2drlxRHy9RAvjtN+DDD+WpS2rly4uhtFw59fGgIGDAAPFDlpTj2jXx/MWcLCzEPaO1aslSUpFVoQIwbpz62JYt4u8OKrL++ecfbN68GXXr1tXqeSVKlICfnx/++ecfjBgxQuftM5ASmZOLF8UwmrsVkpMTcOyYOPONOalaVQylzs7q4wcPAsOGiTMAkfzCw8WfvaQk9fGVK4GuXeWpqaj77DOgZMns++npYq9SKrKqVaum1/MtLS3h4eGh8/MZSInMxcGDgLc3EBmpPl6lCnD2rDhPuDmqU0c8pzT3vNy7dol7gzMy5KmLRCkpwDvviG2ecnr/fWDiRHlqIsDNDZgwQX1s505ONkGyYSAlMgc//CCeO5l7D1STJmIYVXCPUUk0bixefZ9zjw8AbNgATJkiXtlNxicIwNix6m26AKBNG7HdkCmfx2wOpk1Tnw0rs0UcFTkZGRm4efMmnj59muex1NRUnDx50uA1MJASmbLMD5AxY/LuCezSBTh+HJCoR5zitWol9iktVkx9/Msv+SErl1WrgM2b1cc8PMSLm3J/n8j4nJyAyZPVx/bsEc/3pSLj4cOHqF+/Pho0aICKFSuiV69eWVPAA8DLly/h7e1t8Dq0DqRKSNFEBPGindGjgYUL8z42fLh4CL+ozQXeqZPYUijnbDSAeAXxihXy1FRUHT4MTJ+uPlaqlNj7lhMYKMfkyXk7HMybJ08tJIvp06ejQoUKePToEa5fv46UlBS0bt1aLecJRjjKpFUgVUqKJiryEhPFaRc3bsz72OzZ4l4pU+wxKoVevYBt2/IeDp4+XWx5RYZ3+7Y4b3ruvfbbtwMNGshTE2nm4ABMnao+duAAcOGCLOWQ8Z04cQLLly9HhQoVUK9ePRw5cgRt27ZF27Zt8ejRIwAwytTvWgVSpaRooiItMlK8eOnwYfVxCwtg3Tpg8WKem/fuu8D33+cd/+gjMRSR4URFAT17AnFx6uOLF4t/RJHyfPJJ3k4V3EtaZCQlJcEmR19alUqFH374AV26dEG7du1w7949o9ShVSBVSoomKtLGjgUuXVIfK14c+PVX8TESffCBeA5jToIgTpn622+ylGTWUlLEc5b79gVyf4ANHgzMmiVLWVQItrbAzJnqY3/+CfAUvCKhVq1auHz5cp7xdevWoXv37vD19TVKHVoFUqWkaKIi6/598YKQnMqUEXuM9u4tT01KNnkysGCB+lh6OjBoEPDHH7KUZDYyMoCrV4Hly8Veoo6O4p773CGmWTPx1BLurFC2ceOAsmXVx+bOZYeKIqBv377YuXOnxse+/fZbDBo0SHnnkColRRMVWevXq9+3txfbOrVqJU89pmDePODTT9XHUlPF3pinTslTkykSBODuXfFUiAEDxOlbmzYFZswQ96a9epX3OWXLAvv2ibOEkbKVKCGef57TyZPiH7tk1mbOnInDuU8By2HdunXIMEI/Z60CqVJSNFGRlJKS9yKmkSM57eKbqFTiFfZjxqiPv3oF9OgBaPgjm/4THg789JPYxL5KFaBGDfG0kD17gJcvC36unZ0YRsuXN0qpJIHRo4GKFdXH5szhXlIyCq0CqVJSNFGR9OuvwIsX6mM8Z7RwVCqxEfuQIerj8fHi4eabN+WpS2ni44FDh8TJBBo0EHvYDhki/iH08OGbn69SiXtNp08XZ/xp0cLwNZN0bGzyXsx04YL4M0FkYFZyF0BEhZS7ZZGXF1C7tiylmCRLS7EdVmKi2EA/08uXQOfO4uH76tVlK08Wr1+LgePYMeCvv8T/p6Vpt47q1cX+r506iT+TTk4GKZWMZMQIICBA/cK0efOA7t3FTh5UJFhaWuLBgweoVKmS0bapdyCVo+jCCAkJgb+/Py5evIiYmBhUqlQJQ4YMwdSpU1Ey9/SCREp361bei0W4d1R71tbiHPc9ewJHj2aPP38OtGsHdOwIVK6sfqtY0XxmFcrIAG7cyA6gJ0+KAV0bbm7i1ynz5uFhmFpJHtbW4sxmw4dnj4WEiJ0p+vWTry4yKjlOv9Q7kCrxnNFbt26hVatWqFWrFtasWQNnZ2ecPHkSCxcuxJUrV7A/594RIlOQu6emq6t4UQ5pz8ZG/HDt2hU4cyZ7/NkzzT1KVSqgXLnsgOrhoR5YK1US16lUoaFi+PzrLyAoKO9pH29iayvu+ezYUdwLWrcur5g3d0OGAEuXAv/8kz02f77YRzb3LGhEEjHLQ/Y7d+5EcnIy9u7di2rVqgEAOnTogGfPnmH9+vWIjo6GY+6p0oiUKjER2LJFfez9981nr50cSpUSz4vr0EFsXVQQQQCePBFvOQNsTmXLqofUnKG1UiXjXmUeGSkGz8y9oPfva/d8a2ukNW+OV61aIaVtW6Q2aqQ+69fz55KWm5+SJUvC3t7eKNuiXCwtAX9/sT1apv/7P/HoQu7zsIkkYpaB1Pq/X565f5k5ODjAwsICxfhBTqZk1y4gNjb7vkolNn0n/djbi71IO3UCrl/Xb13Pnom3c+c0P+7unnfPauZ9Dw9An9OIEhPF818zA+i1a9qvo2FD8evQsSNiGzTAinXrkJCQIAbboCDda9ODra0tpk2bxlAql/79xQvb/v47e2zBAmDgQMDKLKMDycwsf6pGjBiBNWvWYNy4cfj888/h4uKCEydO4Pvvv8f48eNRqlQpuUskKrzcFzN16ya24CH9OTsD58+LYe5//xOvJA8NFW8PHuSd/lJXz5+Lt/zmB3d11Xw6gIeHeLO1zV42LU2cqSvzMPy5c2JfVW1UqZIVQNGhg9hT9D9Jz54hISEB9evXh4ODg3brlUhMTAxu3LiBpKQkBlK5WFgAixapT7hx5w6wbRswapR8dZHZMstAWrlyZZw7dw7vvPNO1iF7APjkk0+wZs2afJ+XkpKClJSUrPvx8fGGLJPoza5cyTtN6Lhx8tRirooXF/uR9uiR97GYGPWQGhqqfj86WpoaIiLE28WLmh93dhYDqr29uIy2v5ucndUvRKpa9Y1PcXBwgBOvmC/aevYEmjdX/x3k7w8MHcpThkhyZhlIQ0ND0bNnT7i5uWHPnj1wcXHBhQsXsHjxYiQkJGDDhg0an7ds2TL4+/sbuVoqimJjY5GUlPTG5exXrULOg7np5cohonFj8fCwBHie3hs4OIi3hg01Px4bKwbU/EJrVJQ0dURGirfCKllS7BqQ2Y6pfn227CHtqVTiXtJu3bLHHj4U+9KyywdJzCwD6WeffYa4uDhcu3Yt6/B8u3bt4OzsDD8/PwwfPhzt27fP87yZM2diypQpWfefPHkCT09Po9VNRUNsbCxWrFghnqNXgOIpKfD/5Re1sT8qVcKfX3whWS1vOk8vOTkZDx8+RExMjGTb1FZsbCySk5Nl236B7O3F8+waNND8eHy8WmBN+fdfZDx4AMvHj2EZFgZLiQKrYGmJ1MaNkdK2LV63bYvXTZqo78EKD8/6L/8IIa106QK0bq1+Qd+iRWK/Uk4Ja7Zmz55t9FN29A6kchT9JteuXYOnp2eec0WbN28OALh586bGQGpjYwObHO1b4qQ6f4woh6SkpEKdo1c1MBA2OZqUZ1hYQHj/fbSVqEPEm87TS0pKwqlTpxAcHFzodaalpSEtLQ1WVlaw0vHCh9evXyMjIwM2NjZQ/ddeyMrKqsA9yoXd42xIGoNe6dJAvXpAvXrZf4hUqwb8dypRsdRUOMbFoUxcHMrEx4v/5riV1jQ//H+eOjnhfxUr4n8VK+Je+fJIsbER+4yeOCHe8sGLhUgrKhWweDHg7Z099vSp2Ipu0iTZyiLDWrRokdG3qXcglaPoNylXrhxu3ryJhIQE2Oa4GODcf1fAVqhQQa7SiLIUeI6eIKDmsWNqQ1Ft2qBU9eow5iV5Dg4OaN68eaHapN28eRPXr19HkyZNUK9ePa23lZaWhqCgIMTGxqJDhw5ZX5vo6Ghcyn0ebQ6F3eNsaG8KeoX5QyTmv1tmoybLlBSUjIxEyYgIlIyIgE1cHBLd3RFRrx5S/vueOP13KwxeLEQ6yexDm/N30rJlYrcPXiRMEjHLQ/aTJk1Cnz590LlzZ0yePBnOzs44f/48li1bBk9PT/j4+MhdIlGB7G/eRKnQULWxp716Gb0OKysrVK5cGW5ubgUud+7cOdy7dw/dunVDy5Yttd7O69evsWfPHmRkZMDPzw9ly5bNeiw8PBwhISH5Prewe5wNSZugp/XFQuXKIQ1AzuM1tv/diIxm0SL1QBoRAXzzDTBjhnw1kVFkZGQgLCwMT548QWo+HT3atWun93YkDaTGKvpNevXqhWPHjiEgIAATJ05EbGwsKlasiA8//BAzZ85kH1JSvHK//652P6l8eUQ3bixTNQU7d+4cTp8+jTZt2ugVRiMjIzFgwAC1MKoNXhVOZEAtW4rz2R8+nD22fLnY9cPOTr66yGAEQUBAQABWr16NqDec756enq739iQJpMYuujC8vb3hnfOcFyITYR0bC5dc5wA+7dVLkVdJKyWMEpERLFyoHkhfvgTWrAHmzZOtJDKcmTNnYvny5XB1dcWoUaNQtmxZna8NKAxJ1mzsoonMmXtgICxyHGHIsLZGeNeuMlakGcMoURHTtCnwzjvAb79lj61cCXz8MVCmjHx1kUFs3rwZtWrVwqVLl9SuxzEUSVKjsYsmMlsZGSh34IDaUISXF1IVdgEKwyhREeXvD+zbBwiCeD8uTgylS5bIWhZJLyEhAe+9957Rcp0kxwATEhLQo0cPhlEiPTlevYoST5+qjT3t2VOmajRjGCUqwurXBwYNUh/78kvgxQt56iGDadSoEZ7m+jwyJEkCqbGLJjJXuS9mSqhaFXE6tFAyFIZRIsKCBerntCcmAp9/Lls5ZBhz5szB/v37cfXqVaNsT5JD9nPmzEG/fv1w9epVNGnSRIpVEhU5xV68gHPO2VDw397R/5rDy41hlIgAALVqAcOGAVu2ZI+tXQtMmQKUKydfXSSpbt26YcuWLfDx8UGvXr3QsGFD2OXTUWH48OF6b0+SQGrsoonMUdnDh6HKyMi6n168OMI7d5axomwMo0SkZt48YMcOIHM2ueRkYOlSsTcpmYWUlBTs378fkZGR2LBhAwBkzZ6XSRAEqFQq5QRSYxdNZG5U6ekoe+iQ2lh4p05IV8AsKCEhIbhx44asYTQtxxSqRKQAVasC778vTiGaaf16YNo0wMNDvrpIMlOmTMGOHTvQoEED9O/f3zTaPhm7aCJTl5ycjIcPHyImJgYAUCkkBMVzXRRwsUkTRN27Z7AaYmNjkZycXOAyiYmJuHz5Mjp27ChbGI2IiEB0dLTWzyMiA5s9G9i0CXj9Wryfmipehb9xo7x1kSR2796Npk2b4ty5c0bJdJJswdhFE5mypKQknDp1CsHBwVljP4SFqS1zrVgxTNy8GTY2NnmONhSGIAhISUmBhYVFgTOTWVlZISkpKd/HExMT0aJFC9nC6LNnzxAYGMjfK0RKVLEiMHYs8NVX2WObN4uzNzVvLltZJI3k5GR4e3sb7fevJFsxdtFEps7BwQHNmzeHo6MjHF6+RNucv9AB7HF2Ru/evXWaCjMqKgpBQUFwcXFBhw4d8n1fRkdH49KlSwWuq1SpUmisw5SlUoXR3bt3w9HRkYfsiZRq5kxxj2hCgnhfEIBPPgHOnFHk7HJUeE2bNsXdu3eNtj1JEqSxiyYydVZWVqhcuTLc3NzQ8OefkXMfaJylJVwnTEBdHc7DevbsGY4cOYIqVaqgf//+Be4dDQ8PR0hISIHrK6XDOaxShlFnZ2e0a9cOBw8e1HodRGQE7u7A3LnAjBnZY+fPA9u2ASNGyFcX6W3p0qXo2LEjDh48CF9fX4NvT5JAauyiicyFRWoqqh4/rjZ2t1UruOgYRjND3JvCqKFIHUb79+/P80eJlG7iRODHH4E7d7LHZswQpxnNp+MOKd/Ro0fh5eWF3r17w9vbG40aNdLYQUmlUmHu3Ll6b0+SQGrsoonMRYVLl1A8Lk5t7FmvXlqvx1zDqByvg4i0ZGMDrFkD9OiRPRYeDixcCHzxhWxlkX4WLFiQ9f+goCAEBQVpXE5RgdTYRROZi2pHj6rdD/f0RFz58lqtQwkhjmGUqIjr3h3w9QVynl7z5ZfA6NFA7dry1VUEXLt2DbNnz8aNGzfw4sULlChRArVq1cL48ePx3nvv6bzenBfeGoMkgdTYRROZA7uwMLj/+6/a2N2OHbVahxJCHMMoEQEAVq8G/vwzuw1UWpp4OP/IEcXMOGeOYmJiULFiRbz77rsoX748EhMTsWPHDgwbNgyhoaGYM2eOTutt3769xJUWTJJAauyiiUydIAiw37VLbSzZzg5hWrRKkSLEJSYmav2cnBhGiShL9eri9KEBAdljf/4J/P470Lu3fHWZOS8vL3h5eamN+fr64sGDB1i/fr3OgdTY2JOBSAbJL1+iy9OnamP3vbyQUcjWaVKEuJCQEL0CKcMoEeUxe3be+ewnTxanFiWjcnZ2Nql2nAykRDLo/PIlSueYt15QqXC3Q4dCPVeKEHfu3DlcvnxZp7ZOAMMoEeXD1hZYsUJ97MEDYOVKeeoxYfHx8YiLi8u6paSkFLh8RkYG0tLS8OLFC3z77bf4448/MCNnOy6FYyAlksHQ+Hi1+88aNECiq+sbnydVGD19+jSaNWumiD6jDKNEZubdd4E2bdTHli4FHj+Wpx4T5enpCXt7+6zbsmXLClz+o48+grW1NVxdXTF58mR89dVX+PDDD41Urf5MZ18ukZkodvMmqmXOavKfu506vfF5UobRNm3aoGrVqggNDdXq+QyjRPRGKhXw9ddA06ZA5pGgpCRg2jTg55/lrc2E3Lp1C+VzdF2xsbEpcPlZs2Zh9OjRiIiIwIEDB/Dxxx8jMTERU6dONXSpkmAgJTIy+59+UrufWKYMnjZqVOBzpA6jLVu2RHh4uFbPZxglokJr1AgYMwb47rvssV27xHnueSF0oZQuXVpjT/f8VKpUCZUqVQIAdO/eHQAwc+ZMjBgxAi4uLgapUUo8ZE9kTLGxsD1wQG3oXocOECwt832KIcKothhGiUhrixcDjo7qYxMmiO2gyOBatGiBtLQ03L9/X6vnLVmyBLNmzUJqamq+y7x+/RqzZs1CQM6OCnpiICUypu3bYZGUlHU3w8IC9729811cCWE0NTWVYZSItOfkJIbSnG7cAL7/Xp56ipjg4GBYWFigatWqhX7OX3/9hXnz5sHJyQnW1tb5LlesWDE4Oztj9uzZ+U6GpC0GUiJjEQT1w1cAnjRtile59yD8RwlhVBAEBAYGyh5G9e2XSkQyGTMGaNBAfWzuXCAyUp56zNCYMWMwdepU/PLLLzhx4gT27t2LwYMHY9u2bfj000+1Oly/detWODo64uOPP37jsuPHj0eZMmWwadMmfcrPovM5pB999JHWz1GpVFi7dq2umyQybWfPAjdvqg3dyediJiWEUUCcAcTS0hLDhg2TLYzq2y+ViGRkZSVe4JTzvNHoaGDOnDx/oJNuWrZsiU2bNmHLli2IiYmBra0tGjZsiG3btmk9dejZs2fRqVOnN15ABYgXWXXq1Alnz57VtXQ1OgfS77T4QVLlmDKMgZSKrHXr1O5GOzsjvG7dPIspJYwCQFpaGnx9fWULo/r2SyUiBWjXDhg8WP0K+/XrgQ8/BBo3lq8uMzFq1CiMGjVKknU9ffpUq0P8VapUwf79+yXZts6BtLDz1z969AgLFy7EvXv31IIpUZESGQns3q02dKNVK8BC/awZJYVRAHB0dIRrIfqj5iZ1v1Rt21MRkcKsWCFOIZp5Dr0giBc4nTrFee4VxMLCosCLmXJLTU2FhYU0Z3/qHEjfNH99dHQ0li5dirVr1yI5ORktW7bE559/ruvmiEzb5s3A69dZd1NUKtxq3hz2ORZRWhgFoNO0c0rol0pEClOhgjit6OzZ2WNnzgA7dwJDh8pXF6kpV64cbuY6tawgN2/eVOuVqg/JL2pKTk5GQEAAqlWrhpUrV6Jy5cr49ddfcebMGbTJPXMDUVGQkZHnqtITLi5ItrXNuq/EMKoLc3kdRGQAU6YAuQ8HT5sG5Jq5juTTtm1bBAUFFWonQGhoKIKCgtCuXTtJti1ZIBUEAT/++CNq1KiBWbNmoWTJkli/fj1u3ryJPn36SLUZItNz7Bhw967a0P4c52SaS4gzl9dBRAZSvDiwerX62LNnwJIl8tRDeYwfPx6pqano378/IgvohBAVFYUBAwYgLS0N48aNk2TbkgTSffv2oW7duvjwww+RkJCApUuX4u7duxg9erRk5xYQmaxcFwCm1KyJm//NvmEuIc5cXgcRGVjPnkC3bupjq1YBd+7IUw+padKkCSZNmoSrV6/C09MT8+bNQ3BwMO7cuYM7d+7g+PHjmDt3Ljw9PXHlyhVMnjwZTZo0kWTbek0devr0acyYMQPnz59HsWLFMHnyZMyePRuO+fRVJCpynj4Fcl2BGDdkCBAUhIiICAQHB8veZ1RfDKNEVGgqFbBmDVC/PpB58UxqKjBpEnDokJyV0X9WrlyJ4sWLY8WKFViyZAmW5NqDLQgCLC0tMXPmTCzOPfGBHnQOpL169cKhQ4dgYWGBESNGYOHChahQoYJkhRGZhQ0bgPT07PulSiG+d2+k/fknAgMDUaFCBVlnYIqJidH6eTkxjBKR1mrVEgPoihXZY4cPi4G0Rw/ZyiKRSqXC0qVL8f7772PTpk04e/Ysnj9/DgBwd3dH69atMXLkSFSrVk3S7eocSA8ePAiVSoVKlSrh+fPnGDNmzBufo1KpcIh/AVFRkZYm9trLacgQCKVLIzo6Gu7u7rLOTR8YGIg0PeaUZhglIp3NmQNs2wb8F3QAiCG1UyegEE3ZyfCqVasm6R7QN9HrkL0gCHjw4AEePHhQqOXZh5SKlMOHgbAw9bGxYwGI7ZR8fHxkC6N79uxBdHS0zqfXMIwSkV7s7IDPPwdGjMgeu3tXvOjps8/kq4tko3MgLWwIJSqycs9m1qIF0KQJcO8eHBwcYG1trfUqpQqjkZGR8PHxwZkzZ7ReB8MoEUnivffE35PnzmWPLV4MDBsGSNTbkkyHzoHUw8NDyjqIzMuDB8CRI+pj/+0dBXQ7WiBlGB0wYIBOHTAYRolIMhYWwFdfiX+sZ15gmZgIzJgBbN8ub21kdOzJRGQI69dn/4IFAHt7YNAgnVcndRiVc256hlEiytKsGfD+++pjO3YAp0/LUw/JhoGUSGqvX4tX1+c0YgRQsqROq2MYJSKztnSp+Ed7ThMmqHcoIbPHQEoktd9+A168UB/LcbheG0oIoxEREbKHUSn6pRKRQrm4AAsXqo9duwb8+KMs5ZA8GEiJpLZunfr99u2BOnW0Xo0SwmhaWhoCAwNlDaNS9EslIoUbNw6oW1d9bPZs4OVLeeoho2MgJZLS7dvAiRPqYzrsHVVCGAWQ1RrKlPulEpEJsLYWL3DKKSoKmDdPnnrI6PTqQ0pEuXz/vfp9Fxegb1+tVqGUMAqYfr9UIjIhHToA/fsDe/Zkj61bB3zwAdCwoXx1FVF+fn5vXMbCwgJ2dnaoVasWfH19UV6Pdl0MpERSSUoCtmxRH3v/fUCLMKekMArApPulEpEJ+uILcQrRV6/E+xkZwCefAMePA5xcx6g2b96c1aJQ03n8KpVKbXzChAmYN28e5syZo9P2eMieSCq7dgE5z3VUqcS/7AtJaWEUUEa/VFdXV63XQUQmysMj70xNJ08Cv/wiTz1F2L179+Dr6ws3NzcsW7YMJ06cwD///IMTJ05g6dKlcHNzQ69evXDhwgWsX78e5cqVw/z587Fr1y6dtqfTHtLC7MbVRKVSYUPudjhE5iL3zExduwJVqxbqqUoMo7owxOsIDw83QKVEpFjTpgGbNgGhodljU6cCvr5AqVKylVXU7Nq1CxcvXsT169fVdgzUrFkTbdu2xciRI9GoUSMEBwdj+vTp8PHxgaenJ7799lsM0qHvtk6BdPPmzbo8jYGUzNfVq8DFi+pj48YV6qkMoyKlvA4iklmJEsCqVern34eFAcuWiVOLklFs2LChwKNU7u7uGDBgAH744QdMnz4d5cuXh6+vLw4dOqTT9nQKpJzHniiX3HtHK1QAund/49PMJcSZy+sgIoXo0wfo1An466/ssRUrgFGjgGrVZCurKAkLC4ONjU2ByxQvXhxhYWFZ9ytVqoTk5GSdtqdTIOU89kQ5xMYCO3eqj33wAWBV8NsrJCQEN27ckL3PqL4YRolIcioV8OWX4tX1mb+nXr8GpkwB9u+Xt7Yionz58ti/fz8WL16sMZimpKRg//79alfWR0RE6NwVhRc1Eelrxw4gMTH7vqUlMHp0gU9JTEzE5cuXZZ+BKTo6Wuvn5cQwSkQG4+kpTiGa0++/A0eOyFNPEfP+++/j7t27aN++PQ4dOoSX/01S8PLlSxw8eBDt2rXDvXv31K4rOnXqFBrq2KJL0rZPZ8+exebNm3Ht2jXExsbCzs4OjRs3xvDhw9GmTRspN0WkDIKQ93B9795AuXIFPi0xMREtWrSQdW76wMBAWL1hL25BGEaJyODmzxf/6I+IyB6bNAn4+2+tWuqR9qZPn47bt29j+/bt6NWrFwCx72hGRgYAsRXU0KFD8dl/XRHCw8PRo0cPdOvWTaftSRZIp06ditWrV2f1pMos+sqVK9iwYQMmTpyIVatWSbU5ImU4exa4cUN9rBAzM5UqVQqNGzfWenNShdHdu3fD0dFR50P2DKNEZBT29uLFTO+/nz3277/irE5Tp8pXVxFgaWmJrVu3YsSIEdi+fTv+/vtvxMXFwc7ODg0bNsTQoUPRsWPHrOXd3NywevVqnbcnySH7rVu3YtWqVahVqxZ++uknPHv2DGlpaXj+/Dl+/vln1K5dG19++SW2bt0qxeYK7fTp0+jevTscHR1RokQJ1KhRA4sWLTJqDWTmcu8drVYNyPEGzU8pHVqXSBlGnZ2d4ePjo4g+owyjRFSgkSOB5s3Vx/z9gWfPZCmnqOnYsSM2bdqEK1eu4M6dO7hy5Qo2btyoFkalIEkgXbduHSpWrIgLFy5g0KBBcHNzAwC4urpi4MCBOHfuHCpUqIBvv/1Wis0Vys6dO9G+fXvY29tj69atOHz4MGbMmKFxtgEinURGArt3q4+NHQtYSH9qttRhtH///rLPwMQwSkSFYmEBfP21+lhCQt4G+mTSJDlkf/PmTXzwwQcoXbq0xsft7OzQt29f/Pjjj1Js7o2ePHmCMWPG4MMPP1QLwd7e3kbZPhURW7YAKSnZ94sVE/+Sl5ghwqicc9MzjBKR1t56S/z9mrMP+tat4k4AHX4fkfJItivnTXsedTk0qKsff/wRiYmJmDFjhtG2SUVMRkbew/UDBgDOzpJuhmGUiOg/AQGAnZ362IQJ4u9j0puvry+uXLmi03NfvXqFL774AuvWrdN5+5IE0nr16mHv3r1ISEjQ+Hh8fDz27t2LunXrSrG5Nzp58iTKlCmDf/75B40aNYKVlRVcXV0xduxYxMXF5fu8lJQUxMXFZd3i4+ONUi+ZoKAg4O5d9bFCXMykDaWE0ZCQENnDqBT9UonIxLm5iVfd53TlCrBxozz1mJnHjx+jRYsW6NixIzZv3lxgXsp0+fJlTJo0CR4eHpg3bx6c9dgpI0kgHTt2LMLCwtCyZUvs3bsXkZGRAIDIyEjs2bMHrVq1QlhYGMYVcipFfT158gRJSUkYMGAABg0ahL/++gvTpk3D1q1b0b1793z35i5btgz29vZZN09PT6PUSyYo997RevWA1q0lW71Swqi59EslIjMxYQJQp4762MyZQEyMLOWYk2vXruGHH37I6i1apkwZ1KtXD8OHD8e0adOwdOlSzJ07F+PHj0eXLl1QpkwZvPXWW1i7di06d+6MW7duYcCAATpvX5JzSEeMGIFr167hyy+/xMCBAwHk7VU1YcIEjBgxQorNvVFGRgaSk5Mxf/78rP5YXl5eKFasGCZNmoRjx46hU6dOeZ43c+ZMTJkyJev+kydPGEopr6dPgX371MfGjhVnFpGAUsIoYB79UonIjFhbizM4demSPRYZCSxYAKxZI1dVZkGlUsHPzw8jR47EoUOHsHnzZpw4cQLbt2/Ps6yFhQUaNGiAPn36YPTo0Sj3ht7bhSHZb/nVq1ejX79+2LRpE65du5bVq6px48YYMWIE2rZtK9Wm3sjJyQl37txB165d1cZ9fHwwadIkXL16VWMgtbGxUZseqzC7q6kI2rABSE/Pvl+yJPDee5KsWklhFDD9fqlEZIY6dxbnus+5Y+Cbb8QZ8urVk6sqs2FhYYGePXuiZ8+eAIDbt28jLCwMUVFRKFGiBFxcXFC3bl3Y29tLul1Jdzu0adNGETMyNWjQAOfPn88znrNpP5FO0tKA9evVx4YOFZs360lpYRRQRr/Udu3a4eDBg1qvg4jM2KpVQGBgdqeT9HRg4kTgr78kO1pFojp16qBO7tMkDMAsk1m/fv0AAIGBgWrjhw8fBgC8/fbbRq+JzERgIBAWpj724Yd6r1aJYVQXSumXSkRmrkoVYPp09bGgIODXX+Wph/Qm6R7SjIwMhIWF4cmTJ0hNTdW4TLt27aTcpEZdunRBz549sXDhQmRkZODtt9/G5cuX4e/vD19fX0XsxSUTlbulRfPmQNOmeq2SYTSbEl4HEZmIzz4T+5I+fpw9NmUK4OMjnkpFJkWSQCoIAgICArB69WpERUUVuGx6znPvDGjXrl3w9/fH+vXr4e/vj3LlymHy5MmYn7tlBFFhPXgAHDmiPqZnqydzCXHm8jqIyISULAmsXAn8dzE1AODRI2D5cvEiJzIpkgTSmTNnYvny5XB1dcWoUaNQtmxZ2a+KLVGiBAICAhAQECBrHWRGfvgByNkyzN4eGDxY59WlpqaaRYhjGCUi2fTvD3h5AcePZ499/rk4q1PlyvLURDqRJDVu3rwZtWrVwqVLl2BrayvFKomU5fVr8er6nEaM0PmwkCAICAwMxKtXr2TvM6oPhlEikpVKBXz1FdC4cXb3k+Rk4NNPgb175a2NtCLJRU0JCQno0aMHwyiZr99+AyIi1Mf0uJgpJiYG0dHRss/ApE8gZRglIkWoXx/46CP1sV9/Fa+4J5MhSSBt1KgRnj59KsWqiJQp98xM7dsDekyakJaWBh8fH1nnpr98+bJObZ0AhlEiUhh/fyD3tJWffALkc4E16U4QBNy5cwdhuTvO6EmSQDpnzhzs378fV69elWJ1RMryzz/q5ycBel/M5OjoCFdXV62fJ1UYPX36NJo1a6aIPqMMo0SkN0dHYOlS9bHbt4G1a+Wpxwzs378ffn5+alM3h4aGon79+qhduzY8PDwwdOjQrFk59SXJOaTdunXDli1b4OPjg169eqFhw4aws7PTuOzw4cOl2CSR8eTeO+riArzzjl6r1OWiPynDaJs2bVC1alWEhoZq9XyGUSJSLD8/8fd1zp1j8+cDQ4YAOuwAKOq+++47hIWFwdHRMWts0qRJuHXrFjp06ICoqCj8/PPP6NChA95//329tydJIE1JScH+/fsRGRmJDf9d+KHKNVOCIAhQqVQMpGRakpKALVvUx/z8gBxTzBqD1GG0ZcuWCA8P1+r5DKNEpGiWlsDXXwOtW2ePxcUBM2fmvSiV3uj//u//0Llz56z7sbGxOHz4MAYNGoSffvoJqampaNy4MTZs2KCcQDplyhTs2LEDDRo0QP/+/RXR9olIEr/8AsTEZN9XqYAxY4xagiHCqLYYRonIJLRqBQwbBmzblj22caN4EWqLFvLVZYJevHih9rv+9OnTSEtLw7vvvgsAsLa2RufOnbFjxw5JtidJaty9ezeaNm2Kc+fOMYiSecl9uL5rV6BqVaNtXglh1Fz6pRJREREQIHZGSUjIHvvkE+DsWcDCLGdMNwg7Ozu1yY6OHz8OCwsLtG3bNmvM2tpa7/aBmST5ziQnJ8Pb25thlMxLSAhw4YL6mJ4XM2lDCWE0s1+q3GFUql94RFQElCsHzJ2rPnbhArB1qzz1mKjatWvjwIEDePnyJWJjY/Hzzz+jSZMmaueUPnz4EG5ubpJsT5JA2rRpU9y9e1eKVREpR+69oxUqAD16GGXTSgijgHn0SyWiImjSJKBmTfWxzz4DYmNlKccUffLJJ3j69CnKly+PihUr4unTpxibY6dMeno6Tp8+jYYNG0qyPUkC6dKlS3HkyBEcPHhQitURyS8uDsh9XswHHwBGOAqglDAKmH6/VCIqoooVA9asUR8LDwcWLpSlHFPUr18/rF27FnXr1kXNmjWxbNky+Pn5ZT1+7NgxJCUloVu3bpJsT5JP16NHj8LLywu9e/eGt7c3GjVqpLHtk0qlwtzcu9GJlGj7diDnXjlLS0CCqwjfRElhFFBOv1Rt21MREcHHB/D1BXLuLPvqK2D0aKBOHfnqMiHjxo3DuHHjND7WpUsXtR6l+pIkkC5YsCDr/0FBQQgKCtK4HAMpmQRByHu4vlcvoHx5g25WaWEUMN1+qUREAIDVq4E//wRevxbvp6WJh/OPHBG7ppDWBEHA3bt3UaJECVSoUEGy9UoSSIODg6VYDZEynDsH3LihPpbPX4hSUWIY1YUS+qUSEWWpXh349FNg2bLssT//BPbvB/r0ka0sU7B//37s378fK1euzLqQKTQ0FL6+vrh9+zYAYPDgwdi2bRssJOheIEkgbd++vRSrIVKG3HtHq1UDOnY02OYYRrMp4XUQkZmZNUu8wv7Jk+yxyZPFNn4lSshXl8KZ5ExNmTIyMhAWFoYnT54gNTVV4zLt2rWTcpNE0oqKEpvh5/ThhwbrXWcuIc5cXgcRmSFbW2DFCnEK0UyWlsDDh0Dt2vLVpXAmOVOTIAgICAjA6tWr1ZqoapKeni7FJokMY/NmICUl+36xYsDIkQbZVEREBIKDg2XvM6ovhlEiUrzBg4F168R57ufMEfeQGnkKaFNjkjM1zZw5E8uXL4erqytGjRrFqUPJNGVkAN9/rz42YADg4iL5ptLS0hAYGIgKFSrIOgNTTM5pUXXAMEpEJkGlEuezL1nS4Beomgtjz9QkSWrcvHkzatWqhUuXLsHW1laKVRIZlyCIfz3fuaM+bqCZmaKjo+Hu7i7r3PSBgYFIS0vT+rmZGEaJyKTUqCF3BSYlc6amJUuWwNLS0jRmakpISECPHj0YRsk0XbkCtGkDfPyx+njdukDr1gbZpJWVFXx8fGQLo3v27EF0dLTaLxZtMIwSEZk3k5ypqVGjRnj69KkUqyIynogIcfal5s2Bs2fzPv7xxwbrU+fg4ABra2utnydVGI2MjISPj48i+owyjBIRKY9JztQ0Z84c9OvXD1evXkWTJk2kWCWR4aSmAmvXAgsW5D+v8fDhwJgxBitBpUPQlTKMDhgwQKe+cQyjRERFh8nN1NStWzds2bIFPj4+6NWrFxo2bKhx6lAAGD58uBSbJNLN0aPAxInAf01986hWTZzZw9dXUbN4SB1Gy5Ytq3XDeYZRIiIyFEkCaUpKCvbv34/IyEhs2LABQN49QIIgQKVSMZCSPO7fF2fr2LdP8+OlSim2FYghwqi2GEaJiIqu9PR0REZGIiVnW8QcKlWqpPc2JAmkU6ZMwY4dO9CgQQP079+fbZ9IORISxCnjVq5U7y+a03vvAZ9/DpQrZ9zaCkEJYdRc+qUSEZF2rly5glmzZuHkyZN4/fq1xmVUKpVeHVsySZIad+/ejaZNm+LcuXMMoqQMggD89BMwfbr6dHE5NW0KfP01oNC9dUoIo+bSL5WIyFwFBQVh+/btOHv2LB4/fgwHBwc0a9YM8+bNQ9OmTXVe77Vr19C2bVtYWVmhS5cuOHDgABo2bAh3d3dcvXoVL168gJeXFzw8PCR5HZJcZZ+cnAxvb2+GUVKGkBCgXTtg6FDNYdTFBfjxR+DiRYbRN8hsDWXK/VKJiMzZunXrEBoaiokTJ+Lw4cP48ssvERERgbfffhtBQUE6r3fRokUAgAsXLmD//v0AgHfeeQeBgYEIDQ3F2LFjcfPmTcyfP1+S1yFJgmzatCnu3r0rxaqIdPfihXge6A8/iHtIc7OyAiZMAObNAxwcjF5eYSkljAKm3y+ViMjcrV27Fq6urmpj3bp1Q/Xq1bF06VJ06NBBp/WePn0avXr1Qp06dbLGMk+fKlGiBL755hucPXsWs2bNws6dO3V/Af+RZA/p0qVLceTIERw8eFCK1RFpJzUV+OoroGZNYP16zWG0Sxfg77+BVasYRrVgyv1SiYiKgtxhFABsbW3h6emJx48f67ze2NhYVK1aNeu+tbU1EhISsu5bWFjAy8sLx44d03kbOUnyW/7o0aPw8vJC79694e3tjUaNGmls+6RSqTB37lwpNkkk+usvsY3TrVuaH69aVQyhvXopqo2TJkoLo4Dp9kslIjJ18fHxiIuLy7pvY2MDm0J2gYmNjcXVq1d13jsKiEE3Z59Rd3d33Mk1vXZycjKSkpJ03kZOkgTSBQsWZP0/KCgo33MWGEhJMg8eiG2cfvtN8+MlS2a3cSpe3Li16UCJYVQXSuiXSkRkDjw9PdXuz58/Xy1vFWT8+PFITEzE7Nmz9dr+v//+m3W/devW2LdvH86fP4+3334bt2/fxi+//ILatWvrvI2cJAmkwcHBUqyG6M0SE4GAAGDFivzbOA0dKrZxKl/euLXpiGFUpJTXQUSkBLdu3UL5HJ9jhd07OnfuXOzYsQNff/21XlfZ9+jRA5MnT8azZ89QtmxZzJgxA7/99htat26NMmXKIDo6GhkZGZg1a5bO28hJkkDavn17KVZDlD9BAHbtAqZNA8LCNC/TpIl4Lmnr1satTQ/mEuLM5XUQESlF6dKl8531Mj/+/v5YvHgxlixZgo8//liv7Y8dOxYDBw7Muqi0YcOGOHbsGJYsWYL79++jadOmmDBhAnr06KHXdjLxSgFSvpAQ8TzRU6c0P+7sDCxdCvj5AZaWxq1NDyEhIbhx44bsfUb1xTBKRCQ/f39/LFiwAAsWLJBkr6W1tTXc3NzUxlq1aoVDhw7pvW5NeLUAKVdkJDB2rNjAXlMYtbQEJk0C7twBPvjApMJoYmIiLl++LPsMTDlPWNcFwygRkfwWLVqEBQsWYM6cOZL1BTU2nfaQ+vr6wt/fX6dzE169eoW1a9eiVKlSGDdunC6bJ3OXlgasWyf2C81vhp5OnYAvvwRynfRtKhITE9GiRQtZ56YPDAzUq50SwygRkfxWrlyJefPmoVu3bujRowfOnz+v9vjbb7+t1/ozMjIQFhaGJ0+eIDU1VeMy7dq102sbgI6B9PHjx2jRogW8vLwwbNgw9O3b943nOVy+fBnbt2/Hzp07kZCQgC1btuhUMOWQkQHs3Su2NqpSBXB0VHxrozc6dkw8PP9//6f58SpVxDZOvXub9GstVaoUGjdurPXzpAqju3fvhqOjo86H7BlGiYiU4cCBAwCAI0eO4MiRI3keFzT15i4EQRAQEBCA1atXIyoqqsBl09PTddpGTjoF0mvXrmHTpk1YuHAh/Pz8MHr0aNSuXRtNmjSBm5sbHB0d8erVK7x8+RJ37tzB5cuXERsbCwsLCwwcOBBLlixB5cqV9S6+yHv6FBg4MPu+nZ0Y2HLeMsNq5cpiKySlCg0V2zj9+qvmx0uWBGbNEpcxgTZOb1KqVCmtnyNlGHV2dka7du10msyCYZSUIDY2VrL+h/ooWbIk7O3t5S6DirDjx48bZL0zZ87E8uXL4erqilGjRqFs2bIGnaREpzWrVCr4+flh5MiROHToEDZv3owTJ05g+/bteZa1sLBAgwYN0KdPH4wePRrlypXTu2j6z/376vfj4oDr18WbJm5u+QfWihXFqTWNLSkpu41TcrLmZd59F1i+HKhQwbi1KYjUYbR///46nT/KMEpKEBsbixUrVqjNGiMXW1tbTJs2jaGUzM7mzZtRq1YtXLp0Cba2tgbfnl4JxMLCAj179kTPnj0BALdv30ZYWBiioqJQokQJuLi4oG7dunyjGsqDB9otHx4u3nKdXwJAvCCoYkXNYbVKFTHMSnmIXBCAX34R2zjlN7VZo0ZiG6e2baXbrgkyRBiVc256hlHSV1JSEhISElC/fn04yDgVcExMDG7cuIGkpCR+zpHZSUhIwHvvvWeUMApI3PapTp06qFOnjpSrpIIIAuDhIQa6jAz91pWeLh42Dw0FNE10UKKEeNhfU1itUgXQ5pfx9evAJ58AJ09qftzJSWzj9P77JnXlvCEwjBLlz8HBAU5OTnKXQWSWGjVqhKdPnxpte+xDaspGjhRvqaliKH3wQLzdv5/9/wcPgIgI/bf16hVw+7Z408TRMf+9qx4e4nmfkZHA3LnA+vWaA7SlJTB+PLBggbi+Ik4pYdRc+qUSEVHhzZkzB/369cPVq1fRpEkTg2+PgdQcWFuLAbBqVc2PJyaKez41hdUHD4D4eP1riI4Wb1evan68XDmxjthYzY937Ci2capbV/9azIBSwmhmv9SOHTuadL9UIiLSTrdu3bBlyxb4+PigV69eaNiwYb4dlYYPH6739hhIi4JSpcSgpynsCQLw8mX+e1cfPgRev9a/hvx2+1euLLZx6tPHpNs4SUkpYRQwj36pRESkvZSUFOzfvx+RkZHYsGEDAPGi9pwEQYBKpWIgJQmoVOI5m05OQLNmeR/PyBDDZH57V588EUOttkqUyG7jVKKE/q/DTCgpjAKm3y+ViIh0M2XKFOzYsQMNGjRA//79ldn2iYoQCwux3VKFCpqvdk9JAR49yj+wamqmO3iw2MapYkXD129ClBZGAdPul0pERLrbvXs3mjZtinPnzhnlKBUDKenHxgaoUUO8aRIXl33+amysuBfWRKf7NCQlhlFdKKVfKhER6Sc5ORne3t5GO2WKgZQMy84OaNBAvJFGDKPZlPA6iIgIaNq0Ke7evWu07VkYbUtElIe5hDhzeR1ERCRaunQpjhw5YrRTpiTZQ+rn5/fGZSwsLGBnZ4datWrB19cX5cuXl2LTRCYrNTXVLEIcwygRkfk5evQovLy80Lt3b3h7e6NRo0Ya2z6pVCrMnTtX7+1JEkg3b96c1QpA0HDFtUqlUhufMGEC5s2bhzlz5kixeSKTIwgCAgMD8erVK9n7jOqDYZSIyDwtWLAg6/9BQUEICgrSuJyiAum9e/cwadIkXLp0CRMnTkSrVq3g5uaG8PBwnDlzBl999RVatGiB2bNn4/r161i8eDHmz5+PGjVqYNCgQVKU8EY//vgjPvjgA5QqVQoJCQlG2SZRfmJiYmBpaYlhw4bJOgOTPoGUYZSIyHwFa5pG3IAkCaS7du3CxYsXcf36dbi6umaN16xZE23btsXIkSPRqFEjBAcHY/r06fDx8YGnpye+/fZbowTSJ0+eYOrUqShXrhxi85spiMiI0tLS4OvrK+vc9JcvX9aprRPAMEpEZO7at29v1O1JEkg3bNiAAQMGqIXRnNzd3TFgwAD88MMPmD59OsqXLw9fX18cOnRIis2/0dixY9GuXTuUKVMGe/bsMco2ST6xsbFISkqStYaSJUvC3t4+38cdHR3zfb8URKowevr0aTRr1gyhoaFaP59hlIiIpCZJIA0LC4ONjU2ByxQvXhxhYWFZ9ytVqoTk5GQpNl+g7du348SJE7h16xbPWS0CYmNjsWLFCtlPy7C1tcW0adPyDaW69HWTMoy2adMGVatW1TqQMowSERUtZ8+exebNm3Ht2jXExsbCzs4OjRs3xvDhw9GmTRvJtiNJIC1fvjz279+PxYsXawymmfOh5ryyPiIiAo6OjlJsPl8RERGYNGkSAgICUKFChTcun5KSgpSUlKz78fHxhiyPDCApKQkJCQmoX78+HBwcZKkhJiYGN27cQFJSUoF7SbUhdRht2bIlwsPDtXq+ksNocnIyHj58iJiYGEnWp63Y2Fij/IFNRGRMU6dOxerVq7MuTLewsEBGRgauXLmCDRs2YOLEiVi1apUk25IkkL7//vuYPXs22rdvj7lz56Jly5YoU6YMXr58ibNnz2LRokW4d+8eFi1alPWcU6dOoWHDhlJsPl8fffQRatWqhXHjxhVq+WXLlsHf39+gNZFxODg4wMnJSe4yJGGIMKotJYfRpKQknDp1qtAn4L9+/RoZGRmwsbHJ6g6iDUEQkJKSAgsLC7XXYGVlJfupIkREUtm6dStWrVqF2rVrY/78+fDy8oKbmxsiIiJw/Phx+Pv748svv0SjRo0wfPhwvbcnSSCdPn06bt++je3bt6NXr14AslM0IP4CHzp0KD777DMAQHh4OHr06IFu3bpJsXmN9u7diwMHDiAkJKTQHzozZ87ElClTsu4/efIEnpzmkmSkhDBqCv1SHRwc0Lx58wKPuqSlpSEoKAixsbHo0KGDTn+wREVFISgoCC4uLujQoUPWqRfR0dG4dOmSzvUTESnNunXrULFiRVy4cAGlS5fOGnd1dcXAgQPRrVs31K9fH99++61yAqmlpSW2bt2KESNGYPv27fj7778RFxcHOzs7NGzYEEOHDkXHjh2zlndzc8Pq1aul2LRGCQkJGD9+PCZMmIBy5cplHcZ7/fo1APGQqrW1dZ4rjG1sbNROOYiLizNYjURvooQwair9Uq2srFC5cmW4ublpfDxzD29GRgb8/Px0fh1HjhxBlSpV8ryO8PBwhISEaL1OIiKlunnzJj744AO1MJqTnZ0d+vbtix9//FGS7Uk6l33Hjh3VgqdcIiMjER4ejpUrV2LlypV5Hnd0dETv3r2xb98+4xdHVAhKCKMA+6Vm4oVYRFQUaZrsKCddTnvKj6SBVCnc3d01nk8WEBCAEydOIDAwEM7OzjJURvRmSgmjAPulAgyjRFQ01atXD3v37sWiRYtga2ub5/H4+Hjs3bsXdevWlWR7kgXS169fY9++fbh06RJiYmKQnp6eZxmVSoUNGzZItcl8FS9eHF5eXnnGN2/eDEtLS42PESmBksIowH6pDKNEVFSNHTsWo0aNQsuWLbFgwQK0b98ezs7OiIyMzLqoKSwsDAsXLpRke5IE0ocPH6Jz5864d+9egbt3jRVIiUyR0sIowH6pDKNEVFSNGDEC165dw5dffomBAwcCyHvB+oQJEzBixAhJtidJIJ08eTLu3r2LYcOGwc/PDxUqVNDpg8zQNm/ejM2bN8tdBlEeSgyjumC/VCIi87F69Wr069cPmzZtwrVr17IuWG/cuDFGjBiBtm3bSrYtSVJjUFAQOnbsiC1btkixOqIihWE0mzn3SyUiMkVt2rSRdEam/FhIsZKMjAw0btxYilURFSlKCHFSUMLrMIV+qUREpJkke0hbtmyJ27dvS7EqoiIjIiICwcHBsvcZ1ZcSwqhS+qUSEZkqPz8/qFQqLF26FG5ubvDz8yvU86S6PkiSQBoQEIC2bdtiz5496N+/vxSrJDJraWlpCAwMRIUKFWTdo6jv3O9KCKOAMvql6tMrlYhIbps3b4ZKpcKMGTPg5uZW6GtuFBVIDxw4AG9vbwwaNAjt27dH48aNYW9vn2c5lUqFuXPnSrFJIpMWHR0Nd3d3Wc+1DAwMRFpamtbPzaSUMArI3y9V3+b9RERye/DgAQCgfPnyaveNRZJAumDBgqz/Hz9+HMePH9e4HAMpkcjKygo+Pj6yXvgTHR1d4NzvBVFSGAXk75eqT/N+IiIl8PDwKPC+oUkSSDXNikRE+XNwcIC1tbXWz5PyKnQfHx+cOXNG63UoLYwC8vdL1bV5PxERiSQJpO3bt5diNURFhi7z/0rdEsnCQvsmG0oMo7pQQvN+IiIlEgQBJ0+exIsXL9CoUSNUr14dAHD37l0EBATg6tWryMjIQLt27TB79my4ublJsl3lda8nojwM0Z9T24bzDKPZ9G3eT0SkRImJiejatSvOnTsHQNx5smLFCnTv3h0tW7ZUuxD277//xoEDB3DlyhWUKVNG723rFEjlbg1AVJSYS7N4cw2jRETmYuXKlTh79iwaN24Mb29vBAcHY86cOTh58iSsrKywYcMGtGjRAi9fvsRXX32FvXv3IiAgAMuXL9d72zoFUrlbAxAVFUoIo+yXmo1hlIjM2d69e1GlShWcP38e1tbWSE1NhaenJ37//Xfs3LkTgwYNylq2TZs2qFevHg4ePChfIJW7NQBRUaCEMMp+qdkYRonI3N27dw8jR47MuujW2toaXbt2xbp169CxY0e1ZVUqFby9vbFx40ZJtq1TIJW7NQCRuVNCGAXYLzUTwygRFQVJSUlwcXFRG3N2dlb7NycXFxekpKRIsm1J5rInIukoJYwC7JcKMIwSUdGSuwuMLl1hdCFJIN26dSv27NlT4DJ///03tm7dKsXmiMyWksIooJx+qXL3GWUYJSIyLEnaPo0cORIqlQq9evXCjh07ULJkyTzL/Pbbb1i4cCGGDx8uxSaJzI7SwijAfqkMo0RU1Gzfvh3nz5/Pun/37l0AQPfu3fMsm/mYFCTrQ1q2bFns378frVu3xsGDB7MueCKiN1NiGNUF+6USEZm2u3fvagyaR44c0bi8VIf0JQukY8aMgZOTEyZPnozmzZtj3759aNGihVSrJzJbDKMi9kslIpKXnF2TJJ2pafz48ahRowYGDhwILy8vbNiwAe+++66UmyAyK0oIcVJQwutQQr9UIiJTJmfXJMmvsu/SpQvOnz+PcuXK4b333sP8+fOl3gSRWQgJCZE9xOnTTimTEsJoZr9UU2/eT0RUVBlkLvvatWvj4sWL6Nu3LxYvXox//vkHlStXNsSmiPJITk7Gw4cP9W6mrqvY2FgkJycXuExiYiIuX76Mjh07yrpHMTo6Wuvn5aSEMArI3y9Viub9RERFmUECKQCUKVMGf/31Fz788ENs2rRJp7YtRNpKSkrCqVOnEBwcrPHx169fIyMjAzY2NjqdiC0IAlJSUmBhYVFg8LGyskJSUlK+jycmJqJFixaynmsZGBio1/tSKWEUkL9fqr7N+4mIijpJUqKHhwccHBzyrtzKChs2bEDt2rXx2WefSbEpojdycHBA8+bN1Zqpp6WlISgoCLGxsejQoQOcnJy0Xm9UVBSCgoLg4uKCDh065BvmoqOjcenSpQLXVapUKTRu3FjrGqS88MfR0VHnEKWkMArI3y9Vn+b9REQkUSB901VZ06ZNw/Dhw994GJNIClZWVqhcuTLc3NwAZIeGjIwM+Pn56Rzijhw5gipVqrzxsHB4eDhCQkIKXF+pUqW0rkHqq9DbtWuHgwcPar0OpYVRQP5+qT4+Pjhz5ozW6yAiIpHkx9HT09MRGRmpcW5TY00/RZRJKa2E9GWI16HL+aNKDKO6UELzfiIiyiZZIL1y5QpmzZqFkydP4vXr1xqXUalUPM+KjIZhNJsS+nOaaxjVpXk/ERGpkySQXrt2DW3btoWVlRW6dOmCAwcOoGHDhnB3d8fVq1fx4sULeHl5ydrfioqW1NRURYQ4fTGMSstcXgcRkbmRJJAuWrQIAHDhwgXUqVMHFhYWeOeddzBv3jy8evUKn376Kfbs2YONGzdKsTmiAgmCgMDAQLx69YphVILXERISghs3bsjeZ1RfDKNERMolyYlPp0+fRq9evVCnTp2sscwm0SVKlMA333yDcuXKYdasWVJsjqhAMTExiI6OljXEJSYmav2cnJQSRjP7pco9A5O59EslIiLNJAmksbGxqFq1atZ9a2trJCQkZG/EwgJeXl44duyYFJsjKlBaWhp8fHxk3aOoTyBVShgFxEDarFkz9ktlGCUiMihJDtm7urqq7cFwd3fHnTt31JZJTk4usFE4kVQcHR3h6uqq9fOkOtfy8uXLOrV1ApQVRgH2S2UYJSIyDkn2kHp6euLff//Nut+6dWv8+eefOH/+PADg9u3b+OWXX1C7dm0pNkdUIF32pkl54U+zZs0U0WdUinNflfA6fHx8ZO8zyjBKRGRYkgTSHj164OTJk3j27BkAYMaMGRAEAa1bt4aLiwvq16+PmJgYnkNKiiT1Vehy71E0twux5JyBiWGUiMg4JAmkY8eOxZMnT7KmY2zYsCGOHTuGbt26wdnZGZ06dcKBAwfwzjvvSLE5IsmYS0skcw2jpvr9ICIi7UhyDqm1tXXWNI2ZWrVqhUOHDkmxeiKDMJfwwzCaTQnfDyIi0p4ke0gtLS0xdOhQKVZFZBRKCD9s3p9Nqu4GDKNERKZJkj2kdnZ2qFixohSrIjI4JYRRpTTvN7d+qR07djTp5v1EREWVJIG0RYsWuH79uhSrIjIoJYRRQGzeb2lpiWHDhrFfqkT9Ulu0aGHSzfuJiIoySQ7Z+/v7IygoCFu2bJFidUQGoZQwCsjfvJ/9UkVKad5PRKSP+Ph4TJ8+HV26dIGLiwtUKhUWLFggd1lakeQ36J9//gkvLy/4+fnh66+/RosWLeDm5pand6BKpcLcuXOl2CSRVpQURgH5m/dn9ksNDQ3V+vlKC6OA/P1S9WneT0Skr6ioKKxfvx4NGzZEnz598OOPP8pdktYkCaQ5U/jVq1dx9epVjcsxkJIclBZGAfmb97dp0wZVq1bVOpAqMYzqQurX0a5dOxw8eNAAlRIRvZmHhweio6OhUqkQGRlZdANpcHCwFKshkpwSw6guDPE6wsPDtXo+w2i23K+D548SkZx0mc1OaSQJpO3bt5diNUSSYhjNpoT+nOYaRuV4HURk/uLj4xEXF5d138bGBjY2NjJWZFiSXNREpDQRERGyhzgpKCGMsl9qNiW8DiIqGjw9PWFvb591W7ZsmdwlGZRee0hfvnyJ5ORklC1bNmt38dmzZ3H69Ok8yzZo0ADdunXTZ3NEhZKWlobAwEBUqFBB1j6j+lJCGGW/1GxSvI7k5GQ8fPgQMTExWj9XCrGxsUhOTpZl20SknVu3bqF8+fJZ98157yigRyB9+fIlqlatiqZNm+LYsWNZ40ePHsXChQvzfCDb29vj3r17KFOmjO7VEhVCdHQ03N3dZd2jqG/gUEIYBdgvNZMUryMpKQnHjh3D0aNHdW4R9fr1a2RkZMDGxkanc8YEQYAgCJg2bZpO2yci4yldujTs7OzkLsNodA6k27ZtQ3x8PJYvX67x8U2bNmX9Pzo6GlOmTMH27dvxySef6LpJokKxsrKCj4+PbOdaBgYG6tUCSClhFBD3Nvv6+rJfqkSH6W1tbdG+fXs4Ojpq9by0tDQEBQUhNjYWHTp0gJOTk9bbjoqKQmBgIE8zICJF0jmQHj58GHXq1EHTpk01Pj5ixAi1+zt37sShQ4cYSMngHBwcYG1trfXzpLrwJzo6WuvAkUlJYRRgv1Spzxm1s7ND5cqV4ebmVujnZL6OjIwM+Pn56fw6jhw5gooVK7JfKhEpks4XNd24cQOtWrUq9PKNGjXCjRs3dN0cUaHpcihTyqvQfXx8FNFn1Fz6pco5A5PcFzBJ/Tp8fHzMoj0MEeUVGBiIPXv24MCBAwDEc1D37NmDPXv2ICkpSebq3kznPaRRUVEa95y0a9cOs2bNyjPu6uqKly9f6ro5IoORuiWShYX2f+cpMYzqgv1SpcN+qUSkjXHjxuHhw4dZ93fv3o3du3cDAB48eIDKlSvLVFnh6BxIixcvrjFxe3t7w9vbO894UlISz10ixTFEf05tAxTDaDb2SxWZy+sgIuPR5dQmJdH5kH2FChW0OgT/999/q7UvMKSgoCD4+fmhdu3aKFWqFMqXL4/evXvjypUrRtk+mQZzCT8MoyL2S82mhNdBRKQNnQNp27ZtcfLkyUIl8vv37+PEiRNo166drpvTyrp16xAaGoqJEyfi8OHD+PLLLxEREYG3334bQUFBRqmBlE0JYVQJzfvNrV+qqYc4hlEiKqp0PmQ/btw4rF+/HoMHD0ZgYGC+VxW/fPkSgwcPRkZGBsaOHatzodpYu3ZtnvNbu3XrhurVq2Pp0qXo0KGDUeogZVJCGFVC8372S83G5v1ERPLSOZA2bNgQU6ZMwapVq+Dp6YmxY8fCy8sL5cqVAwA8efIEwcHBWL9+PcLDwzFp0iSdrpbVhaaLrWxtbeHp6YnHjx8bpQZSJiWEUUD+5v3sl5qNzfuJiOSn19ShK1asgLW1Nb744gssXLgQCxcuVHtcEARYWFhg6tSpCAgI0KtQfcXGxuLq1asF7h1NSUlBSkpK1v34+HhjlEZGopQwCsjfvJ/9UkVs3k9EpAx6BVKVSoVly5bh/fffx6ZNm3D+/Hk8f/4cgiDAzc0NrVq1wogRI1CzZk2p6tXZ+PHjkZiYiNmzZ+e7zLJly+Dv72/EqshYlBRGAfmb92f2Sz1z5ozW61BaGAXk75dqTs37iYjkoFcgzVS9enUsWbJEilUZxNy5c7Fjxw58/fXX+c4sBQAzZ87ElClTsu4/efIEnp6exiiRDEhpYRSQv3k/+6VK+zqqVq2qdSBlGCUiyqbzVfamwt/fH4sXL8aSJUvw8ccfF7isjY0N7Ozssm6lS5c2UpVkKEoMo7pQwutgGM1mLt8PIiKlMOtA6u/vjwULFmDBggUaZ48i86aE0CAFJbwOJYQ4KSjhdZhLv1QiIilJcsheiRYtWoQFCxZgzpw5mD9/vtzlkJGFhITgxo0bDKMS9UsNDg6Wvc+ovpQQRjP7pb569YphlIgoB7MMpCtXrsS8efPQrVs39OjRA+fPn1d7/O2335apMjKGxMREXL58GR07dpS1z6i+lBBG2S81G/ulEhEZjlkG0gMHDgAAjhw5giNHjuR5XIq9LaRciYmJaNGihax7FKOjo7V+Xk5KCKMA+6VmYr9UIiLDMstAevz4cblLIBmVKlVKp0kYpDrXMjAwUKc2RJmUEkYB9ksF2C+ViMgYzPqiJiqadPnAlfLCH0dHRzg4OGj9fEBZYRRQTr9UufuMmlO/VAZSIlIiBlIq8qS+Ct3Hx0cRfUbNpV+qnHsUza0rgLGmbyYi0hYDKRVphmiJJPcexaLeFYBhNJsSXgcRUWEwkFKRZS7hh2E0mxK+H1Iwl9dBRFRYZnlRE9GbmEv4YRjNpoR+qVJQws8VEZGxMZBSkaOUMKqE5v3sl5qNzfuJiOTDQ/ZUpCgljGY275d7j6I59Ut1dHRk836GUSIyUQykVGQoJYwCYiBt1qyZrOdasl+qiM37iYjkx0P2VCQoKYwC8jfvz+yXqmuIUlIYBeTvl2pOzfuJiOTAPaRk9pQWRgH5m/ezXyqb9xMRKQn3kJJZU2IY1YUhXocu548qMYzqQurXYWGh/d/2DKNERNm4h5TMFsNoNiWEH3MNo6b6/SAiUhLuISWzlJqaqojQoC9zCT8Mo9lMoV9qcnIyHj58qHfnAF3FxsYiOTlZlm0TkTwYSMnsCIKAwMBAvHr1imGU/VKzKCGMmkK/1KSkJJw6dQrBwcEFriMlJQUWFhY6vzfS0tKQlpYGKysrjeffWllZISkpSad1E5HpYSAlsxMTEwNLS0sMGzZM1j6j+lBKGM3sl9qxY0f2S5WoX6q7u7vi+6U6ODigefPmGjsHREVFISgoCC4uLujQoYNOF3PdvHkT169fR5MmTVCvXr08j0dHR+PSpUtar5eITBcDKZmdtLQ0+Pr6yrpHUZ9AqpQwCoiBtEWLFuyXWsT6pVpZWaFy5cpwc3NTG3/27BmOHDmCKlWq6BWq7927h27duuX7OsLDwxESEqL1uonIdDGQktlxdHSEq6ur1s+T6lzLy5cv69TWCVBWGAXYL5X9UrMp4VxkIjJfvMqezI7c/SCbNWumiD6j7JeqrDAKsF8qwygR5YeBlIo8qT9s5d6jaG4XYsm5R9HcugLIeeSAYZSICsJASkWaEj5sGUazmcv3QwpKeB1K+H4QUdHAc0ipyFLCh61SQoO+lPI6lPD9kIISXocp9Es1BbGxsYpoX1WyZEnY29vLXQZRvhhIqUhSQvhh8/5s5tIvVQpKCKOm0C/VFMTGxmLFihVISEiQuxTY2tpi2rRpDKWkWAykVOQoIYwqpXk/+6WK2Lxfnan0S1W6pKQkJCQkoH79+nBwcJCtjpiYGNy4cQNJSUkMpKRYDKRUpCghjALKaN7PfqkiNu/Py1T6pZoKBwcHODk5yV0GkaLxoiYqMpQSRgFxb5qPj4+s51qyXyqb9+fHlPulEpFpYiClIkFJYRSQv3k/+6VK37xf10OySgujgOn2SyUi08VASmZPaWEUkL95P/ulsnm/lJTQL5WITBsDKZk1JYZRXSjhdTCMZmPz/mzm8jqISF4MpGS2lBDipKCE18Ewms1cvh9SMJfXQUTy40k6VGhKaPBc2ObO5tLUWwnhh/1Ss7FfajaGUSKSEgMpFYpSGjwXprmzuTT1VkIYZb/UbOyXmo1hlIikxkBKhaKEBs+Fbe5sDk29lRBGAfZLzcR+qdkYRonIEBhISSum0ODZ1Jt6KyWMAuLeNF9fX/ZLZb9UAAyjRGQ4vKiJzI4pN/VWUhgF2C+V/VKzMYwSkSExkJLZkbsfpK5NvZUWRgH2SzW3C7GKer9UIlIuBlIq8pTQ1FuJYVQXSngdDKPZ2C+ViEwFAykVaUr4sFVCiJOCEl6HUr4f+lLK61DC94OIigZe1ERFlhI+bJUQGqSghNfBfqnZ2C+VtGVKfabJPDGQUpGkhDCqhOb97JeajWE0m7n0S6XCMaU+02S+GEipyFFCGFVC8372S83G5v3qzKFfKhWeKfWZJvPFQEpFihLCKCB/8372S83G5v15mXq/VCVJTk7Gw4cP9f7jTx+xsbFITk5+43Km0GeazJd5vOOJCkEpYRSQv3k/+6WK2LxfMyX0S33TH0umEPSSkpJw6tQpBAcHa73utLQ0pKWlwcrKSudw/vr1a2RkZMDGxgbW1taynyNKVBAGUgVQwsnkgHmfUK6kMArI37w/s1/qmTNntF6H0sIoIH+/1GbNmiE0NFTr5ysxjOpC6tfRrl07HDx4MN9l8wt6Uoe4wvRstbKyKvD3t4ODA5o3b67VH383b97E9evX0aRJE9SrV6/Qz8uUlpaGoKAgxMbGokOHDrCwsMClS5e0Xg+RMTGQykwpJ5MD5ntCudLCKCB/8/4BAwbAwkL7rm9KDKO6kPp1VK1aVetAyjCaLffrKMz5o7mDntQhrjCHrqOjo98Y9KysrFC5cmW4ubkVqo5z587h3r176Natm17v84yMDPj5+aFs2bIIDw9HSEiI1usiMiYGUpkp4WRywHxPKFdiGNWFIV5HeHi4VutgGM2W+3Vo+7VkGM2m6+vIGfQMEeIKQ+qgZy6/r4h0wUCqEDyZXHrm8stdCa+DYTQb+6WKzOXniu9zImVgICWzZC5NvZXwIcV+qdnYL1WklDCqhPe5FP1SlfA+NxVKuObCnK+3kBMDKZkdc2nqrYQPKfZLzcZ+qSKlhFElvM+l6JeqhPc5IH/XgsK0plLKNRfmer2F3BhIyeyYQ1NvpXxIsV+qiP1SRUoJo4D873Mp+qUq5X2elJSEoKAgndpTAdJ1N7CyssK0adMKrFPuay7M9XoLJWAgJbNj6k29lfIhBbBfKsB+qZmUFEYB+d/nhe2Xmh8lvc8BwNnZGS1atND6vSZVd4OIiAiUKVOmUM/hNRfmiYGUzI4pNPXOj9I+pNgvlf1SAeWFUUD+93lh+qXmR2nvcwCwtrbWqj0VIG2LqgEDBuj0PifzoX0jQhORkJCASZMmoVy5cihevDgaNWqEn3/+We6ySIGk/pDy8fFRRJ9Rc+mXKuceRXPrCiD3HkVzuxBL7j/WzOmCS13e55TNHDKP2e4h7du3Ly5duoSAgADUrFkTO3fuxLvvvouMjAwMGTJE7vJIIeRq6p0bP6RE7Jeajf1SpaOU18H3uUiK9zmpM4fMY5aB9PDhwzh69GjWNwQAvL298fDhQ0ybNg2DBg2CpaWlzFWS3PghJS0lvA4lfD+koITXwX6p2ZTw/eD7nPJjLpnHLAPpb7/9BltbWwwYMEBtfNSoURgyZAguXLiAVq1ayVSd6TKFtiCFxQ8paSnhdSihX6oUlPBzxX6p2dgvNZsS3ufm9DkkFXPJPGYZSG/evIk6derkuYCgQYMGWY9r+uakpKQgJSUl635sbCwA8ReSoURERCAqKgrXr19H6dKlDbadN4mPj0dUVBSePXuG9PT0PI+Hhobi2LFjOHToEDIyMlCsWDGdzi8UBAGvX7+GhYWFTudfWVpa4r333tNYIyB+r5KTk/HgwYN8f2GlpqYiODgYsbGx8Pb2RlxcHOLi4rSqIzIyEsHBwbC3t0eDBg3w4MGDrMeio6ORnJyMZ8+ewcbGJt8ajxw5gnv37qFhw4YoU6YM/v33X61q0Pd1REdHIzEx8Y11FvS1BLKvsjXU6yjM1zMxMRG//PILXF1d83w/Ckuf1xEdHY1Xr17lW2NmnW/6ehb0cyXF63jT1zKzzoiICKSlpaFbt26Svz8KIzo6GtHR0Xr9bBr6fZ5Z55t+NqOjo/Ho0SM0bdpUlvc5ANy/fx/h4eF6fT3lfp8D4ufQH3/8gUOHDun0+QEA6enpWS2qdN1rKAhCgZ9D+srMHLGxsbCzs8sat7Gx0fi10TXzKI5ghmrUqCF07do1z/jTp08FAMLSpUs1Pm/+/PkCAN5444033njjjTdF3ebPny9p5lEas9xDChR8dXB+j82cORNTpkzJup+Wlobbt2+jYsWKsLBQbkOC+Ph4eHp64tatW7LuZX0TU6jTFGoEWKfUWKd0TKFGgHVKjXVKJyMjA48ePYKnp6faXs/89hwDumUepTHLQOrk5ISoqKg84y9fvgSAfJvvatod3rp1a+kLlFjmYY/y5cur7d5XGlOo0xRqBFin1FindEyhRoB1So11SqtSpUqFXlbXzKM0yt3tp4f69evj9u3beU7ivnHjBgDoNJsEERERkdKYS+Yxy0D6zjvvICEhAXv37lUb37JlC8qVK4e33npLpsqIiIiIpGMumccsD9n7+Pigc+fOGDduHOLi4lC9enX89NNPOHLkCLZv324S/bi0YWNjg/nz5xd4fokSmEKdplAjwDqlxjqlYwo1AqxTaqxTPuaSeVSCIAhyF2EICQkJmD17Nn755Re8fPkStWvXxsyZMzF48GC5SyMiIiKSjDlkHrMNpERERERkGszyHFIiIiIiMh0MpEREREQkKwZSIiIiIpIVA6lCbd68GSqVCpcvX5a7FI0y69N0mzp1aqHXM3LkSNja2hq8xuPHj+d5XBAEVK9eHSqVCl5eXgapQRdfffUVVCqVYnrHmerXUenvIU30qVmlUmHBggXSFwXl/UxqcuHCBbzzzjuoVKkSbGxs4ObmhpYtW+LTTz+VuzSNzp8/jwEDBqBs2bIoVqwY3N3d0b9/f5w7d07rdd26dQsLFixAaGio3nVl/gwWL14cDx8+zPO4l5eXIn4Ocn8GFS9eHO7u7vD29sayZcsQEREhd4mkJQZS0sumTZtw7tw5tdsnn3wid1lqSpcujQ0bNuQZP3HiBO7du6e46eM2btwIAPi///s/XLhwQeZqspna15Gko9SfyUyHDh1Cq1atEBcXh+XLl+PPP//El19+idatW2PXrl1yl5fH119/jdatWyMsLAzLly/HX3/9hS+++AJPnjxBmzZt8M0332i1vlu3bsHf31+SQJopJSUFc+bMkWx9hpL5GXT06FGsXbsWjRo1wueff446dergr7/+krs80gIDKemlXr16ePvtt9Vu2kx5ZgyDBg3C3r17s6aMy7Rhwwa0bNlS0npfvXql1/MvX76M69evo0ePHgCgMQDqIykpSefnGvPrSMph6J9JKSxfvhxVqlTBH3/8gcGDB6N9+/YYPHgwvvjiCzx69Eju8tScOXMGkyZNQvfu3XHq1CkMGzYM7dq1w3vvvYdTp06he/fumDhxIs6cOSNrnd26dcPOnTtx/fp1Wet4k8zPoLZt26Jfv35YvXo1/v77b5QqVQp9+/ZFeHi43CVSITGQmojLly9j8ODBqFy5MkqUKIHKlSvj3XffzXNIJfMwRnBwMMaNGwdnZ2c4OTmhb9++ePr0qVFr3rVrF1q2bIlSpUrB1tYWXbt2RUhIiMZl/+///g8dO3ZEqVKl4OLigo8//liv8JTTu+++CwD46aefssZiY2Oxd+9e+Pn55Vne398fb731FsqUKQM7Ozs0adIEGzZsQO4OaZUrV4avry9+/fVXNG7cGMWLF4e/v79etWZ+2AcEBKBVq1b4+eef1b4OoaGhUKlUWL58OZYsWYJKlSqhePHiaNasGY4dO6a2rgULFkClUuHq1avo378/HB0dUa1aNZ1rM8TX8f3330eZMmU0fq87dOiAunXr6lxvbl5eXhpPKRg5ciQqV66cdT/za/zFF19g1apVqFKlCmxtbdGyZUucP39esnoKo7A1G9KbfiaPHz+u8XSOzK/j5s2b1cZ/+OEH1KxZEzY2NvD09MTOnTv1fj1RUVFwdnaGlVXeuV4sLNQ/5grzeynzVCJD/F5atmwZVCoV1q1bl6deKysrfPvtt1CpVAgICMga/+eff/Duu+/Czc0NNjY2qFSpEoYPH46UlBRs3rwZAwYMAAB4e3tnHcLO/XXX1vTp0+Hk5IQZM2YUuFxycjJmzpyJKlWqoFixYihfvjzGjx+PmJiYrGX69OkDDw8PZGRk5Hn+W2+9hSZNmuhVa26VKlXCypUrER8fj++//z5r/PLly+jVqxfKlCmD4sWLo3Hjxvjll1/yPP/JkycYM2YMKlasiGLFiqFcuXLo378/w62BMZCaiNDQUNSqVQtr1qzBH3/8gc8//xzPnj1D8+bNERkZmWf50aNHw9raGjt37sTy5ctx/PhxvPfee5LXlZ6ejrS0NLUbACxduhTvvvsuPD098csvv2Dbtm2Ij49H27ZtcevWLbV1pKamonv37ujYsSP27duHjz/+GN9//z0GDRokSY12dnbo379/1mFHQAxVFhYWGrcRGhqKDz/8EL/88gt+/fVX9O3bFxMmTMCiRYvyLHv16lVMmzYNn3zyCY4cOYJ+/frpXOerV6/w008/oXnz5qhXrx78/PwQHx+P3bt351n2m2++wZEjR7BmzRps374dFhYW8PHx0Xj+Wd++fVG9enXs3r0b3333nc71GeLrOHHiRERHR2Pnzp1qz7116xaCg4Mxfvx4nevV19q1a3H06FGsWbMGO3bsQGJiIrp3747Y2FjZajI2bX4mC2P9+vUYM2YMGjRogF9//RVz5syBv7+/xnOTtdGyZUtcuHABn3zyCS5cuIDU1FSNy8n9eyk9PR3BwcFo1qwZKlSooHGZihUromnTpggKCkJ6ejquX7+O5s2b4/z581i4cCECAwOxbNkypKSk4PXr1+jRoweWLl0KQPyZzTx1KnOPtq5Kly6NOXPm4I8//kBQUJDGZQRBQJ8+ffDFF19g2LBhOHToEKZMmYItW7agQ4cOSElJAQD4+fnh0aNHedbzzz//4OLFixg1apRetWrSvXt3WFpa4uTJkwCA4OBgtG7dGjExMfjuu++wf/9+NGrUCIMGDVIL70+ePEHz5s3x22+/YcqUKQgMDMSaNWtgb2+P6OhoyeukHARSpE2bNgkAhEuXLml8PC0tTUhISBBKlSolfPnll3me99FHH6ktv3z5cgGA8OzZM0nr03R79OiRYGVlJUyYMEHtOfHx8YK7u7swcODArLERI0YIANRegyAIwpIlSwQAwunTp/Wu8dKlS0JwcLAAQLh586YgCILQvHlzYeTIkYIgCELdunWF9u3ba1xHenq6kJqaKixcuFBwcnISMjIysh7z8PAQLC0thX///VfnGnPaunWrAED47rvvBEEQv162trZC27Zts5Z58OCBAEAoV66c8OrVq6zxuLg4oUyZMkKnTp2yxubPny8AEObNm6dXXYb+OrZv315o1KiR2vLjxo0T7OzshPj4eEnqztyOpvpGjBgheHh4ZN3P/BrXr19fSEtLyxq/ePGiAED46aefdK7JUDULgiAAEObPny9pPYX5mcz8mQgODlZ7bubXcdOmTYIgiD8D7u7uwltvvaW23MOHDwVra+s8r0cbkZGRQps2bbJ+B1lbWwutWrUSli1blvUzpITfS8+fPxcACIMHDy5wuUGDBgkAhPDwcKFDhw6Cg4ODEBERke/yu3fv1vg90EXOn8GUlBShatWqQrNmzbLes+3btxfq1q0rCIIgHDlyRAAgLF++XG0du3btEgAI69evFwRBEFJTUwU3NzdhyJAhastNnz5dKFasmBAZGalXnflxc3MT6tSpIwiCINSuXVto3LixkJqaqraMr6+vULZsWSE9PV0QBEHw8/MTrK2thVu3bmldE+mHe0hNREJCAmbMmIHq1avDysoKVlZWsLW1RWJiIm7fvp1n+V69eqndb9CgAQBovGpSH1u3bsWlS5fUbn/88QfS0tIwfPhwtT2nxYsXR/v27TXuDRk6dKja/SFDhgAQ/6qVQvv27VGtWjVs3LgRN27cwKVLlzQeZgaAoKAgdOrUCfb29rC0tIS1tTXmzZuHqKioPFduNmjQADVr1pSkxg0bNqBEiRJZU73Z2tpiwIABOHXqFO7cuaO2bN++fVG8ePGs+6VLl0bPnj1x8uRJpKenqy2rz17b3AzxdZw4cSKuXbuWdc5cXFwctm3bhhEjRhisA0Nh9OjRQ20OaEO9h5RMm5/JN/n333/x/PlzDBw4UG28UqVKaN26tV51Ojk54dSpU7h06RICAgLQu3dv/O9//8PMmTNRv359REZGKvL3Un6E/05refXqFU6cOIGBAwfCxcXFoNvUpFixYli8eDEuX76s8dB25h7PkSNHqo0PGDAApUqVyjqNyMrKCu+99x5+/fXXrCMM6enp2LZtG3r37g0nJyeD1J/5dbx79y7++eefrO9nzu9/9+7d8ezZM/z7778AgMDAQHh7e6NOnToGqYnyx0BqIoYMGYJvvvkGo0ePxh9//IGLFy/i0qVLcHFx0XghTe43uI2NDQD9L7rJrU6dOmjWrJnaLfM8m+bNm8Pa2lrttmvXrjynGFhZWeWp193dHYB4bpgUVCoVRo0ahe3bt+O7775DzZo10bZt2zzLXbx4EV26dAEgnut25swZXLp0CbNnzwaQ9+tXtmxZSeq7e/cuTp48iR49ekAQBMTExCAmJgb9+/cHALXD5ED21yf32OvXr5GQkGCQGgHDfB179+6NypUrY+3atQDE86ATExNlPVwPGO89pFTa/ky+SeZ72c3NLc9jmsZ00axZM8yYMQO7d+/G06dPMXnyZISGhmL58uWK+L3k7OyMkiVL4sGDBwUuFxoaipIlS8LKygrp6en5Ht43hsGDB6NJkyaYPXt2nlMhoqKiYGVllScsq1QquLu7q32d/Pz8kJycjJ9//hkA8Mcff+DZs2cGOVwPAImJiYiKikK5cuWyvvdTp07N873/6KOPACDr+//ixQtZv95FWd4zwElxYmNjcfDgQcyfPx+fffZZ1nhKSgpevnwpY2WaOTs7AwD27NkDDw+PNy6flpaGqKgotV/+z58/B5A3FOhj5MiRmDdvHr777jssWbJE4zI///wzrK2tcfDgQbU9kPv27dO4vEqlkqS2jRs3QhAE7NmzB3v27Mnz+JYtW7B48eKs+5lfn5yeP3+OYsWK5dmrKFWNmaT+OlpYWGD8+PGYNWsWVq5ciW+//RYdO3ZErVq1JK27ePHiGs//1HQOtlLIWXNhfyYzv7+Z5wvmV2Pme1nThSGafp71ZW1tjfnz52P16tW4efMmevfuDUDe30uWlpbw9vbGkSNHEBYWpjH4hIWF4cqVK/Dx8UGZMmVgaWmJsLAwnbYnBZVKhc8//xydO3fG+vXr1R5zcnJCWloaXrx4oRZKBUHA8+fP0bx586wxT09PtGjRAps2bcKHH36ITZs2oVy5cll/uErt0KFDSE9Ph5eXV9Zn0syZM9G3b1+Ny2f+vnFxcZH1612UcQ+pCVCpVBAEIWsPTaYff/wxz+FZJejatSusrKxw7969PHtPM2+57dixQ+1+5kUuUjZaL1++PKZNm4aePXtixIgRGpdRqVSwsrJSO1T76tUrbNu2TbI6cktPT8eWLVtQrVo1BAcH57l9+umnePbsGQIDA7Oe8+uvvyI5OTnrfnx8PA4cOIC2bduq1W4Ihvg6jh49GsWKFcPQoUPx77//4uOPP5a87sqVK+N///ufWnCKiorC2bNnJd+WVOSqWZufycyr4//++2+1dfz+++9q92vVqgV3d/c8h34fPXqk9+t59uyZxvHM05nKlSunmN9LM2fOhCAI+Oijj/L8/k5PT8e4ceMgCAJmzpyJEiVKoH379ti9e3eBf4QYeu99p06d0LlzZyxcuFDtCEzHjh0BANu3b1dbfu/evUhMTMx6PNOoUaNw4cIFnD59GgcOHMCIESMM8vvq0aNHmDp1Kuzt7fHhhx+iVq1aqFGjBq5fv57v9z6zj7KPjw+Cg4OzDuGT8XAPqcKpVCrY2dmhXbt2WLFiBZydnVG5cmWcOHECGzZsgIODg9wl5lG5cmUsXLgQs2fPxv3799GtWzc4OjoiPDwcFy9eRKlSpdTaIxUrVgwrV65EQkICmjdvjrNnz2Lx4sXw8fFBmzZtJK0tZysVTXr06IFVq1ZhyJAhGDNmDKKiovDFF1/k+WNASoGBgXj69Ck+//xzjR909erVwzfffIMNGzZg9erVAMQ9LZ07d8aUKVOQkZGBzz//HHFxcXq3nSosqb+ODg4OGD58ONatWwcPDw/07NlTsloz9xAPGzYM33//Pd577z188MEHiIqKwvLly2FnZyfZtqQid83a/Ez6+vqiU6dOWLZsGRwdHeHh4YFjx47h119/VXuOhYUF/P398eGHH6J///7w8/NDTEwM/P39UbZs2TztmbTRtWtXVKhQAT179kTt2rWRkZGBa9euYeXKlbC1tcXEiRMV83updevWWLNmDSZNmoQ2bdrg448/RqVKlfDo0SOsXbsWFy5cwJo1a9CqVSsAwKpVq9CmTRu89dZb+Oyzz1C9enWEh4fj999/x/fff4/SpUtnzZy0fv16lC5dGsWLF0eVKlUkPcL0+eefo2nTpoiIiMhqx9a5c2d07doVM2bMQFxcHFq3bo2///4b8+fPR+PGjTFs2DC1dbz77ruYMmUK3n33XaSkpOQ591QXN2/ezDofNCIiAqdOncKmTZtgaWmJ3377LWvP7ffffw8fHx907doVI0eORPny5fHy5Uvcvn0bV69ezeockdnJoF27dpg1axbq16+PmJgYHDlyBFOmTEHt2rX1rpnyIdfVVFSwtWvXCgCEGzduCIIgCGFhYUK/fv0ER0dHoXTp0kK3bt2EmzdvCh4eHsKIESOynpfflYf5XQmrq8Jc4bhv3z7B29tbsLOzE2xsbAQPDw+hf//+wl9//ZW1zIgRI4RSpUoJf//9t+Dl5SWUKFFCKFOmjDBu3DghISHB4DUKQt6rwzdu3CjUqlVLsLGxEapWrSosW7ZM2LBhgwBAePDgQdZyHh4eQo8ePfSqURAEoU+fPkKxYsUKvIp28ODBgpWVlXD+/HkBgPD5558L/v7+QoUKFYRixYoJjRs3Fv744w+152ReZf/ixQu96jP01zHT8ePHBQBCQECAXvVmyv0eEgRB2LJli1CnTh2hePHigqenp7Br1658r7JfsWJFnnXCAFeyS1Gz1LVp8zP5/Plz4dmzZ0L//v2FMmXKCPb29sJ7770nXL58We0q+0zr168XqlevLhQrVkyoWbOmsHHjRqF3795C48aNda53165dwpAhQ4QaNWoItra2grW1tVCpUiVh2LBhea6Wlvv3UqZz584J/fv3F9zc3AQrKyvB1dVV6Nu3r3D27Nk8y966dUsYMGCA4OTkJBQrVkyoVKmSMHLkSCE5OTlrmTVr1ghVqlQRLC0tNX7dC6ug9/uQIUMEAFlX2QuCILx69UqYMWOG4OHhIVhbWwtly5YVxo0bJ0RHR2tcf+Y6WrdurVN9uevMvBUrVkxwdXUV2rdvLyxdulTjz+7169eFgQMHCq6uroK1tbXg7u4udOjQIauLRKbHjx8Lfn5+gru7u2BtbS2UK1dOGDhwoBAeHq5XzVQwlSDk6vZNijBx4kR88803iImJ4ZSMlCU0NBRVqlTBihUrMHXqVLnLkdSnn36KdevW4fHjx5Ls2THF95Ap1qyvmJgY1KxZE3369MlzjqJcRo4ciT179uS5QJCIDIeH7BXmypUruHTpEjZu3IhevXoVmQ8lKrrOnz+P//3vf/j222/x4Ycf6h1GTfE9ZIo16+L58+dYsmQJvL294eTkhIcPH2L16tWIj4/HxIkT5S6PiGTEQKow/fv3R2xsLHr16oWvvvpK7nKIDK5ly5YoWbIkfH191ToJ6MoU30OmWLMubGxsEBoaio8++ggvX75EyZIl8fbbb+O7776TdJpYIjI9PGRPRERERLJi2yciIiIikhUDKRERERHJioGUiIiIiGTFQEpEREREsmIgJSIiIiJZMZASERERkawYSImIiIhIVgykRERERCSr/wdi8et7Ie/x+wAAAABJRU5ErkJggg==\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"### Plot Figure 6d\n",
"\n",
"\n",
"fig, ax = plt.subplots(figsize=(7,5))\n",
"bbox = {'boxstyle': 'round', 'facecolor': 'w', 'alpha': 0.9}\n",
"cmap = plt.get_cmap('tab10')\n",
"palette = [cmap(0), cmap(0.2), 'k', cmap(0.1), cmap(0.3)]\n",
"xticks=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov',\"Dec\"]\n",
"\n",
"ax2=ax.twinx()\n",
"\n",
"ax2.plot(xticks, NPGO_W_meso_mean,label='Z2',color='r',linestyle='-',linewidth=3)\n",
"\n",
"\n",
"ax.bar(xticks,NPGO_W_Z2diat_mean,color='grey',edgecolor='k',hatch='//',alpha=0.7,label='Diatoms')\n",
"ax.bar(xticks,NPGO_W_Z2flag_mean,color='grey',edgecolor='k',label='Nanoflagellates',alpha=0.5,bottom=NPGO_W_Z2diat_mean)\n",
"\n",
"\n",
"\n",
"ax2.set_ylim(0,5)\n",
"ax2.set_ylabel('Biomass (g C m$^{-2}$)',fontsize=14)\n",
"\n",
"ax2.legend(frameon=False,loc=1)\n",
"ax.set_ylim(0,12)\n",
"ax.set_ylabel('Grazing (mmol N m$^{-2}$ d$^{-1}$)',fontsize=14)\n",
"ax.set_xlabel('',fontsize=14)\n",
"\n",
"#ax.tick_params(axis='x', labelrotation=0)\n",
"ax.text(-.5, 12.5, '(d)', fontsize=15, color='k')\n",
"ax.set_title('',fontsize=18)\n",
"\n",
"#plt.savefig('Fig6d.png', bbox_inches='tight',dpi=1000,transparent=False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plot all on one figure"
]
},
{
"cell_type": "code",
"execution_count": 116,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"\n",
"fig, ax = plt.subplots(2,2,figsize=(13,10))\n",
"bbox = {'boxstyle': 'round', 'facecolor': 'w', 'alpha': 0.9}\n",
"cmap = plt.get_cmap('tab10')\n",
"palette = [cmap(0), cmap(0.2), 'k', cmap(0.1), cmap(0.3)]\n",
"xticks=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov',\"Dec\"]\n",
"\n",
"fig.tight_layout(pad=4.5)\n",
"\n",
"\n",
"### PLOT FOR Z1 COLD YEARS\n",
"\n",
"ax2 = ax[0,0].twinx()\n",
"\n",
"ax2.errorbar(xticks, NPGO_C_micro_mean,label='Z1',color='b',linestyle='--',linewidth=3)\n",
"ax2.fill_between(xticks, NPGO_C_micro_mean-NPGO_C_micro_std, NPGO_C_micro_mean+NPGO_C_micro_std,\n",
" alpha=0.5, edgecolor='royalblue', facecolor='royalblue',\n",
" linewidth=0)\n",
"\n",
"ax[0,0].bar(xticks,NPGO_C_Z1diat_mean,yerr=NPGO_C_Z1diat_std,color='grey',capsize=3,edgecolor='k',hatch='//',alpha=0.7,label='Diatoms')\n",
"ax[0,0].bar(xticks,NPGO_C_Z1flag_mean,yerr=NPGO_C_Z1flag_std,color='grey',ecolor='dimgrey',capsize=3,edgecolor='k',label='Nanoflagellates',alpha=0.5,bottom=NPGO_C_Z1diat_mean)\n",
"\n",
"\n",
"\n",
"ax2.set_ylim(0,5)\n",
"ax2.set_ylabel('Biomass (g C m$^{-2}$)',fontsize=14)\n",
"\n",
"ax[0,0].legend(frameon=False,loc=2)\n",
"ax2.legend(frameon=False,loc=1)\n",
"ax[0,0].set_ylim(0,12)\n",
"ax[0,0].set_ylabel('Grazing (mmol N m$^{-2}$ d$^{-1}$)',fontsize=14)\n",
"ax[0,0].set_xlabel('',fontsize=14)\n",
"#ax.tick_params(axis='x', labelrotation=0)\n",
"\n",
"ax[0,0].text(-.5, 12.5, '(a)', fontsize=15, color='k')\n",
"\n",
"ax[0,0].set_title('Cold Years',fontsize=18)\n",
"\n",
"\n",
"### PLOT FOR Z1 WARM YEARS\n",
"ax3=ax[0,1].twinx()\n",
"\n",
"ax3.errorbar(xticks, NPGO_W_micro_mean,label='Z1',color='r',linestyle='--',linewidth=3)\n",
"ax3.fill_between(xticks, NPGO_W_micro_mean-NPGO_W_micro_std, NPGO_W_micro_mean+NPGO_W_micro_std,\n",
" alpha=0.5, edgecolor='tomato', facecolor='tomato',\n",
" linewidth=0)\n",
"\n",
"ax[0,1].bar(xticks,NPGO_W_Z1diat_mean,yerr=NPGO_W_Z1diat_std,color='grey',capsize=3,edgecolor='k',hatch='//',alpha=0.7,label='Diatoms')\n",
"ax[0,1].bar(xticks,NPGO_W_Z1flag_mean,yerr=NPGO_W_Z1flag_std,color='grey',ecolor='dimgrey',capsize=3,edgecolor='k',label='Nanoflagellates',alpha=0.5,bottom=NPGO_W_Z1diat_mean)\n",
"\n",
"\n",
"\n",
"ax3.set_ylim(0,5)\n",
"ax3.set_ylabel('Biomass (g C m$^{-2}$)',fontsize=14)\n",
"\n",
"ax3.legend(frameon=False,loc=1)\n",
"ax[0,1].set_ylim(0,12)\n",
"ax[0,1].set_ylabel('Grazing (mmol N m$^{-2}$ d$^{-1}$)',fontsize=14)\n",
"ax[0,1].set_xlabel('',fontsize=14)\n",
"\n",
"#ax.tick_params(axis='x', labelrotation=0)\n",
"ax[0,1].text(-.5, 12.5, '(b)', fontsize=15, color='k')\n",
"\n",
"ax[0,1].set_title('Warm Years',fontsize=18)\n",
"\n",
"\n",
"\n",
"### PLOT FOR Z2 COLD YEARS\n",
"ax4=ax[1,0].twinx()\n",
"\n",
"ax4.errorbar(xticks, NPGO_C_meso_mean,label='Z2',color='b',linewidth=3)\n",
"ax4.fill_between(xticks, NPGO_C_meso_mean-NPGO_C_meso_std, NPGO_C_meso_mean+NPGO_C_meso_std,\n",
" alpha=0.5, edgecolor='royalblue', facecolor='royalblue',\n",
" linewidth=0)\n",
"ax[1,0].bar(xticks,NPGO_C_Z2diat_mean,yerr=NPGO_C_Z2diat_std,color='grey',edgecolor='k',capsize=3,hatch='//',alpha=0.7,label='Diatoms')\n",
"ax[1,0].bar(xticks,NPGO_C_Z2flag_mean,yerr=NPGO_C_Z2flag_std,color='grey',edgecolor='k',ecolor='dimgrey',capsize=3,label='Nanoflagellates',alpha=0.5,bottom=NPGO_C_Z2diat_mean)\n",
"\n",
"\n",
"\n",
"ax4.set_ylim(0,5)\n",
"ax4.set_ylabel('Biomass (g C m$^{-2}$)',fontsize=14)\n",
"\n",
"#ax.legend(frameon=False,loc=2)\n",
"ax4.legend(frameon=False,loc=1)\n",
"ax[1,0].set_ylim(0,12)\n",
"ax[1,0].set_ylabel('Grazing (mmol N m$^{-2}$ d$^{-1}$)',fontsize=14)\n",
"ax[1,0].set_xlabel('',fontsize=14)\n",
"#ax.tick_params(axis='x', labelrotation=0)\n",
"\n",
"ax[1,0].text(-.5, 12.5, '(c)', fontsize=15, color='k')\n",
"\n",
"ax[1,0].set_title('',fontsize=18)\n",
"\n",
"\n",
"### PLOT FOR Z2 WARM YEARS\n",
"ax5=ax[1,1].twinx()\n",
"\n",
"ax5.errorbar(xticks, NPGO_W_meso_mean,label='Z2',color='r',linestyle='-',linewidth=3)\n",
"ax5.fill_between(xticks, NPGO_W_meso_mean-NPGO_W_meso_std, NPGO_W_meso_mean+NPGO_W_meso_std,\n",
" alpha=0.5, edgecolor='tomato', facecolor='tomato',\n",
" linewidth=0)\n",
"\n",
"ax[1,1].bar(xticks,NPGO_W_Z2diat_mean,yerr=NPGO_W_Z2diat_std,color='grey',edgecolor='k',capsize=3,hatch='//',alpha=0.7,label='Diatoms')\n",
"ax[1,1].bar(xticks,NPGO_W_Z2flag_mean,yerr=NPGO_W_Z2flag_std,color='grey',ecolor='dimgrey',capsize=3,edgecolor='k',label='Nanoflagellates',alpha=0.5,bottom=NPGO_W_Z2diat_mean)\n",
"\n",
"\n",
"\n",
"ax5.set_ylim(0,5)\n",
"ax5.set_ylabel('Biomass (g C m$^{-2}$)',fontsize=14)\n",
"\n",
"ax5.legend(frameon=False,loc=1)\n",
"ax[1,1].set_ylim(0,12)\n",
"ax[1,1].set_ylabel('Grazing (mmol N m$^{-2}$ d$^{-1}$)',fontsize=14)\n",
"ax[1,1].set_xlabel('',fontsize=14)\n",
"\n",
"#ax.tick_params(axis='x', labelrotation=0)\n",
"ax[1,1].text(-.5, 12.5, '(d)', fontsize=15, color='k')\n",
"ax[1,1].set_title('',fontsize=18)\n",
"\n",
"#plt.savefig('Figure10_ZooplanktonGrazing_revised.png', bbox_inches='tight',dpi=1000,transparent=False)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (py39)",
"language": "python",
"name": "py39"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.15"
}
},
"nbformat": 4,
"nbformat_minor": 4
}