-
Notifications
You must be signed in to change notification settings - Fork 0
/
12_plot_ecoregions.jl
340 lines (302 loc) · 10.3 KB
/
12_plot_ecoregions.jl
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
#### Ecoregion plots
# SAVE = true
# CAN = true
include("A0_required.jl");
# Load the corresponding results if dealing with CAN data or minimal example
if (@isdefined CAN) && CAN == true
ecoresults_path = joinpath("data", "results", "ecoregions");
else
ecoresults_path = joinpath("xtras", "results", "ecoregions");
end
## Basic network measures
fig_path = joinpath("figures", "ecoregions")
isdir(fig_path) || mkdir(fig_path)
# Define the network measures to use
network_measures = ["Co", "L", "Lv"]
measures = ["S", "Sv", "LCBD_species", "LCBD_networks", network_measures...]
measures_ts = [
"Richness", "Richness variance", "Relative species LCBD", "Relative network LCBD",
"Connectance", "Number of links", "Link variance",
]
summary_fs = ["median", "iqr89"]
summary_ts = ["median", "89% IQR"]
# Predefine set of options
opt = []
for m in measures, fs in summary_fs
o = (m = m, fs = fs)
push!(opt, o)
end
opt
# Load the ecoregion summary layers
ecoregion_layers = Dict{String, SimpleSDMResponse}()
for o in opt
# Load layer
path = joinpath(ecoresults_path, "ecoregion_$(o.m)_$(o.fs).tif")
ecoregion_layers["$(o.m)_$(o.fs)"] = read_geotiff(path, SimpleSDMResponse)
# Replace zero values (sites not in an ecoregion)
replace!(ecoregion_layers["$(o.m)_$(o.fs)"], 0.0 => nothing)
end
ecoregion_layers
# Put values on log scale (except for LCBD measures)
# @threads for o in opt
# if !contains(o.m, "LCBD")
# ecoregion_layers["$(o.m)_$(o.fs)"] = log(ecoregion_layers["$(o.m)_$(o.fs)"])
# end
# end
# We need to fix an issue with the network LCBN layers before we compare with species LCBD
# Some sites had no links, so their LCBD values was set to nothing to avoid NaNs everywhere
# Now we'll also set them to NaN for species LCBD to compare the rest of the two layers
if length(ecoregion_layers["LCBD_species_median"]) > length(ecoregion_layers["LCBD_networks_median"])
_nan_sites = setdiff(
keys(ecoregion_layers["LCBD_species_median"]),
keys(ecoregion_layers["LCBD_networks_median"])
)
@info "Creating a species LCBD layers without $(length(_nan_sites)) sites with missing network LCBD values"
for f in ["median", "iqr89"]
ecoregion_layers["LCBD_species_$f"][_nan_sites] = fill(nothing, length(_nan_sites))
end
end
## Make some plots!!
# Set coordinate limit for figures
lims = boundingbox(ecoregion_layers["L_median"])
# Single figures
ecoregion_plots = Dict{String, Figure}()
@showprogress "Ecoregion single figures:" for (m,t) in zip(measures, measures_ts)
begin
f = Figure(; resolution=(850,800))
p1 = background_map(f[1,1]; title="Median", titlealign=:left, lims=lims)
p2 = background_map(f[2,1]; title="89% IQR", titlealign=:left, lims=lims)
sf1 = surface!(p1, ecoregion_layers["$(m)_median"]; colormap=:inferno, shading=false)
sf2 = surface!(p2, ecoregion_layers["$(m)_iqr89"]; colormap=:inferno, shading=false)
Colorbar(p1[1,2], sf1; height=Relative(0.5), label="log($(t))")
Colorbar(p2[1,2], sf2; height=Relative(0.5), label="log($(t) 89% IQR)")
ecoregion_plots[m] = f;
end;
if (@isdefined SAVE) && SAVE == true
save(joinpath(fig_path, "ecoregion_single_$m.png"), ecoregion_plots[m])
end
end
# Check results
ecoregion_plots["S"]
ecoregion_plots["Sv"]
ecoregion_plots["LCBD_species"]
ecoregion_plots["LCBD_networks"]
ecoregion_plots["Co"]
ecoregion_plots["L"]
ecoregion_plots["Lv"]
## Compare with richness
# Compare with IQR values for the ecoregion
begin
ms = ["S_median" "L_median"; "S_iqr89" "L_iqr89"]
ts = ["A) Richness" "B) Links"; "C) Richness IQR" "D) Links IQR"]
cts = ["Expected Richness" "Expected number of links";
"Richness 89% IQR" "Links 89% IQR"]
cm = [cgrad([p0, bv_pal_2[2]]), cgrad([p0, bv_pal_2[3]])]
cs = ReversibleScale(log, exp)
cticks = reshape([
[20, 40, 60, 80], # Richness
[10, 20, 30], # Richness IQR
[100, 300, 500], # Links
[100, 200, 300], # Links IQR
], (2,2))
fig = Figure(; resolution=(1275,600))
for i in 1:2, j in 1:2
m = ms[i,j]
t = ts[i,j]
ct = cts[i,j]
p = background_map(fig[i,j]; title=t, titlealign=:left, lims=lims)
s = surface!(ecoregion_layers["$(m)"]; colormap=cm[j], colorscale=cs, shading=false)
Colorbar(p[1,2], s;
height=Relative(0.5), label="$ct\n(log scale)", ticks=cticks[i,j],
minorticksvisible=true, minorticks=IntervalsBetween(2)
)
end
fig
end
if (@isdefined SAVE) && SAVE == true
save(joinpath(fig_path, "ecoregion_comparison_iqr.png"), fig)
end
# Double bivariate for median and IQR
begin
fig = Figure(; resolution=(800,850), figure_padding=20)
ga = fig[1,1] = GridLayout()
gb = fig[2,1] = GridLayout()
# Median bivariate
L1 = ecoregion_layers["S_median"]
L2 = ecoregion_layers["L_median"]
g1 = ga[1:16, 1:4] = GridLayout()
g2 = ga[2:5, 4] = GridLayout()
p1 = background_map(g1[1,1], title="A", titlealign=:left, titlesize=20, lims=lims)
sf = bivariatesurface!(p1, L1, L2; n_stops=5, bv_pal_2...)
p2 = Axis(g2[1,1];
aspect = 1, xlabel = "Richness", ylabel = "Links",
xticks=0:25:75, yticks=0:200:600
)
l2 = bivariatelegend!(p2, L1, L2; n_stops=5, bv_pal_2...,)
# IQR bivariate
L3 = ecoregion_layers["S_iqr89"]
L4 = ecoregion_layers["L_iqr89"]
g3 = gb[1:16, 1:4] = GridLayout()
g4 = gb[2:5, 4] = GridLayout()
p1 = background_map(g3[1,1], title="B", titlealign=:left, titlesize=20, lims=lims)
sf = bivariatesurface!(p1, L3, L4; n_stops=5, bv_pal_2...)
p2 = Axis(g4[1,1];
aspect = 1, xlabel = "Richness IQR", ylabel = "Links IQR",
xticks=0:15:45
)
l2 = bivariatelegend!(p2, L3, L4; n_stops=5, bv_pal_2...)
fig
end
if (@isdefined SAVE) && SAVE == true
save(joinpath(fig_path, "ecoregion_bivariates.png"), fig)
end
## Compare with LCBD
# Bivariate LCBD figure for ecoregion values
function make_bivariate_figure(L1, L2, fig = Figure(); pal=bv_pal_2, kw...)
g1 = fig[1:16, 1:4] = GridLayout()
g2 = fig[2:5, end] = GridLayout()
p1 = background_map(g1[1,1]; lims=lims)
sf = bivariatesurface!(p1, L1, L2; pal..., kw...)
p2 = Axis(g2[1,1];
aspect = 1, xlabel = "Species LCBD", ylabel = "Network LCBD",
xticks=0.2:0.3:0.8, yticks=0.3:0.2:0.7
)
l2 = bivariatelegend!(p2, L1, L2; pal..., kw...)
fig
end
fig = make_bivariate_figure(
ecoregion_layers["LCBD_species_median"],
ecoregion_layers["LCBD_networks_median"];
# pal=bv_pal_2,
cmap=cmap2
)
## Relationship between LCBD median and IQR
# Show probability densities
function make_density_figure(fig = Figure(;resolution=(800, 400)))
ax1 = Axis(
fig[1:3,1],
# title="Median",
xlabel="Relative LCBD value",
ylabel="Probability Density"
)
ax2 = Axis(
fig[1:3,2],
# title="89% IQR",
xlabel="89% IQR",
)
p1 = density!(ax1,
unique(values(ecoregion_layers["LCBD_species_median"]));
color=(bv_pal_2[2], 0.3),
strokecolor=bv_pal_2[2],
strokewidth=3,
)
p2 = density!(ax1,
unique(values(ecoregion_layers["LCBD_networks_median"]));
color=(bv_pal_2[3], 0.3),
strokecolor=bv_pal_2[3],
strokewidth=3,
)
p3 = density!(ax2,
unique(values(ecoregion_layers["LCBD_species_iqr89"]));
color=(bv_pal_2[2], 0.3),
strokecolor=bv_pal_2[2],
strokewidth=3,
)
p4 = density!(ax2,
unique(values(ecoregion_layers["LCBD_networks_iqr89"]));
color=(bv_pal_2[3], 0.3),
strokecolor=bv_pal_2[3],
strokewidth=3,
)
Legend(fig[4,:], [p1, p2], ["Species LCBD", "Network LCBD"])
fig
end
fig = make_density_figure()
# 4 panel version
begin
fig = Figure(resolution=(1500,800))
# Define layout
g1 = fig[1:2,1] = GridLayout()
g2 = fig[1:2,2] = GridLayout()
g3 = fig[3:4,1] = GridLayout()
g4 = fig[3:4,2] = GridLayout()
# Species LCBD
p1 = background_map(g1[1,1]; lims=lims)
sf1 = surface!(
ecoregion_layers["LCBD_species_median"];
colormap=cgrad([p0, bv_pal_2[2]]),
shading=false
)
Colorbar(g1[1,2], sf1; height=Relative(0.5), label="Species LCBD")
# Network LCBD
p2 = background_map(g2[1,1]; lims=lims)
sf2 = surface!(
ecoregion_layers["LCBD_networks_median"];
colormap=cgrad([p0, bv_pal_2[3]]),
shading=false
)
Colorbar(g2[1,2], sf2; height=Relative(0.5), label="Network LCBD")
# Bivariate
p3 = make_bivariate_figure(
ecoregion_layers["LCBD_species_median"],
ecoregion_layers["LCBD_networks_median"],
g3;
cmap=cmap2
# pal=bv_pal_2
)
# Density maps
p4 = make_density_figure(g4)
# Labels
for (label, layout) in zip(["A", "B", "C", "D"], [g1, g2, g3, g4])
Label(layout[1, 1, TopLeft()], label,
fontsize = 26,
font = :bold,
# padding = (0, 5, 5, 0),
# halign = :right
)
end
fig
end
if (@isdefined SAVE) && SAVE == true
save(joinpath(fig_path, "ecoregion_LCBD_4panels.png"), fig)
end
# Side-by-side median-median and iqr-iqr relationships
_v1 = values(ecoregion_layers["LCBD_species_median"])
_v2 = values(ecoregion_layers["LCBD_networks_median"])
_pairs_med = unique(Pair.(_v1, _v2))
_lims_med = extrema([_v1 _v2]) .+ [-0.01, 0.01]
_v3 = values(ecoregion_layers["LCBD_species_iqr89"])
_v4 = values(ecoregion_layers["LCBD_networks_iqr89"])
_pairs_iqr = unique(Pair.(_v3, _v4))
_lims_iqr = extrema([_v3 _v4]) .+ [-0.01, 0.01]
begin
fig = Figure()
p1 = scatter(
fig[1,1],
first.(_pairs_med),
last.(_pairs_med),
color=:black,
axis=(;
aspect=1,
xlabel="Median species LCBD",
ylabel="Median network LCBD",
limits=(_lims_med..., _lims_med...)
)
)
p2 = scatter(
fig[1,2],
first.(_pairs_iqr),
last.(_pairs_iqr),
color=:black,
axis=(;
aspect=1,
xlabel="89% IQR species LCBD",
ylabel="89% IQR network LCBD",
limits=(_lims_iqr..., _lims_iqr...),
)
)
fig
end
if (@isdefined SAVE) && SAVE == true
save(joinpath(fig_path, "ecoregion_relation_lcbd_iqr.png"), fig)
end