-
Notifications
You must be signed in to change notification settings - Fork 2
/
Copy pathnetraref.html
446 lines (368 loc) · 202 KB
/
netraref.html
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
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
<!DOCTYPE html>
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8"/>
<title>Analysis of acumulation curves for species interactions</title>
<!-- Styles for R syntax highlighter -->
<style type="text/css">
pre .operator,
pre .paren {
color: rgb(104, 118, 135)
}
pre .literal {
color: rgb(88, 72, 246)
}
pre .number {
color: rgb(0, 0, 205);
}
pre .comment {
color: rgb(76, 136, 107);
}
pre .keyword {
color: rgb(0, 0, 255);
}
pre .identifier {
color: rgb(0, 0, 0);
}
pre .string {
color: rgb(3, 106, 7);
}
</style>
<!-- R syntax highlighter -->
<script type="text/javascript">
var hljs=new function(){function m(p){return p.replace(/&/gm,"&").replace(/</gm,"<")}function f(r,q,p){return RegExp(q,"m"+(r.cI?"i":"")+(p?"g":""))}function b(r){for(var p=0;p<r.childNodes.length;p++){var q=r.childNodes[p];if(q.nodeName=="CODE"){return q}if(!(q.nodeType==3&&q.nodeValue.match(/\s+/))){break}}}function h(t,s){var p="";for(var r=0;r<t.childNodes.length;r++){if(t.childNodes[r].nodeType==3){var q=t.childNodes[r].nodeValue;if(s){q=q.replace(/\n/g,"")}p+=q}else{if(t.childNodes[r].nodeName=="BR"){p+="\n"}else{p+=h(t.childNodes[r])}}}if(/MSIE [678]/.test(navigator.userAgent)){p=p.replace(/\r/g,"\n")}return p}function a(s){var r=s.className.split(/\s+/);r=r.concat(s.parentNode.className.split(/\s+/));for(var q=0;q<r.length;q++){var p=r[q].replace(/^language-/,"");if(e[p]){return p}}}function c(q){var p=[];(function(s,t){for(var r=0;r<s.childNodes.length;r++){if(s.childNodes[r].nodeType==3){t+=s.childNodes[r].nodeValue.length}else{if(s.childNodes[r].nodeName=="BR"){t+=1}else{if(s.childNodes[r].nodeType==1){p.push({event:"start",offset:t,node:s.childNodes[r]});t=arguments.callee(s.childNodes[r],t);p.push({event:"stop",offset:t,node:s.childNodes[r]})}}}}return t})(q,0);return p}function k(y,w,x){var q=0;var z="";var s=[];function u(){if(y.length&&w.length){if(y[0].offset!=w[0].offset){return(y[0].offset<w[0].offset)?y:w}else{return w[0].event=="start"?y:w}}else{return y.length?y:w}}function t(D){var A="<"+D.nodeName.toLowerCase();for(var B=0;B<D.attributes.length;B++){var C=D.attributes[B];A+=" "+C.nodeName.toLowerCase();if(C.value!==undefined&&C.value!==false&&C.value!==null){A+='="'+m(C.value)+'"'}}return A+">"}while(y.length||w.length){var v=u().splice(0,1)[0];z+=m(x.substr(q,v.offset-q));q=v.offset;if(v.event=="start"){z+=t(v.node);s.push(v.node)}else{if(v.event=="stop"){var p,r=s.length;do{r--;p=s[r];z+=("</"+p.nodeName.toLowerCase()+">")}while(p!=v.node);s.splice(r,1);while(r<s.length){z+=t(s[r]);r++}}}}return z+m(x.substr(q))}function j(){function q(x,y,v){if(x.compiled){return}var u;var s=[];if(x.k){x.lR=f(y,x.l||hljs.IR,true);for(var w in x.k){if(!x.k.hasOwnProperty(w)){continue}if(x.k[w] instanceof Object){u=x.k[w]}else{u=x.k;w="keyword"}for(var r in u){if(!u.hasOwnProperty(r)){continue}x.k[r]=[w,u[r]];s.push(r)}}}if(!v){if(x.bWK){x.b="\\b("+s.join("|")+")\\s"}x.bR=f(y,x.b?x.b:"\\B|\\b");if(!x.e&&!x.eW){x.e="\\B|\\b"}if(x.e){x.eR=f(y,x.e)}}if(x.i){x.iR=f(y,x.i)}if(x.r===undefined){x.r=1}if(!x.c){x.c=[]}x.compiled=true;for(var t=0;t<x.c.length;t++){if(x.c[t]=="self"){x.c[t]=x}q(x.c[t],y,false)}if(x.starts){q(x.starts,y,false)}}for(var p in e){if(!e.hasOwnProperty(p)){continue}q(e[p].dM,e[p],true)}}function d(B,C){if(!j.called){j();j.called=true}function q(r,M){for(var L=0;L<M.c.length;L++){if((M.c[L].bR.exec(r)||[null])[0]==r){return M.c[L]}}}function v(L,r){if(D[L].e&&D[L].eR.test(r)){return 1}if(D[L].eW){var M=v(L-1,r);return M?M+1:0}return 0}function w(r,L){return L.i&&L.iR.test(r)}function K(N,O){var M=[];for(var L=0;L<N.c.length;L++){M.push(N.c[L].b)}var r=D.length-1;do{if(D[r].e){M.push(D[r].e)}r--}while(D[r+1].eW);if(N.i){M.push(N.i)}return f(O,M.join("|"),true)}function p(M,L){var N=D[D.length-1];if(!N.t){N.t=K(N,E)}N.t.lastIndex=L;var r=N.t.exec(M);return r?[M.substr(L,r.index-L),r[0],false]:[M.substr(L),"",true]}function z(N,r){var L=E.cI?r[0].toLowerCase():r[0];var M=N.k[L];if(M&&M instanceof Array){return M}return false}function F(L,P){L=m(L);if(!P.k){return L}var r="";var O=0;P.lR.lastIndex=0;var M=P.lR.exec(L);while(M){r+=L.substr(O,M.index-O);var N=z(P,M);if(N){x+=N[1];r+='<span class="'+N[0]+'">'+M[0]+"</span>"}else{r+=M[0]}O=P.lR.lastIndex;M=P.lR.exec(L)}return r+L.substr(O,L.length-O)}function J(L,M){if(M.sL&&e[M.sL]){var r=d(M.sL,L);x+=r.keyword_count;return r.value}else{return F(L,M)}}function I(M,r){var L=M.cN?'<span class="'+M.cN+'">':"";if(M.rB){y+=L;M.buffer=""}else{if(M.eB){y+=m(r)+L;M.buffer=""}else{y+=L;M.buffer=r}}D.push(M);A+=M.r}function G(N,M,Q){var R=D[D.length-1];if(Q){y+=J(R.buffer+N,R);return false}var P=q(M,R);if(P){y+=J(R.buffer+N,R);I(P,M);return P.rB}var L=v(D.length-1,M);if(L){var O=R.cN?"</span>":"";if(R.rE){y+=J(R.buffer+N,R)+O}else{if(R.eE){y+=J(R.buffer+N,R)+O+m(M)}else{y+=J(R.buffer+N+M,R)+O}}while(L>1){O=D[D.length-2].cN?"</span>":"";y+=O;L--;D.length--}var r=D[D.length-1];D.length--;D[D.length-1].buffer="";if(r.starts){I(r.starts,"")}return R.rE}if(w(M,R)){throw"Illegal"}}var E=e[B];var D=[E.dM];var A=0;var x=0;var y="";try{var s,u=0;E.dM.buffer="";do{s=p(C,u);var t=G(s[0],s[1],s[2]);u+=s[0].length;if(!t){u+=s[1].length}}while(!s[2]);if(D.length>1){throw"Illegal"}return{r:A,keyword_count:x,value:y}}catch(H){if(H=="Illegal"){return{r:0,keyword_count:0,value:m(C)}}else{throw H}}}function g(t){var p={keyword_count:0,r:0,value:m(t)};var r=p;for(var q in e){if(!e.hasOwnProperty(q)){continue}var s=d(q,t);s.language=q;if(s.keyword_count+s.r>r.keyword_count+r.r){r=s}if(s.keyword_count+s.r>p.keyword_count+p.r){r=p;p=s}}if(r.language){p.second_best=r}return p}function i(r,q,p){if(q){r=r.replace(/^((<[^>]+>|\t)+)/gm,function(t,w,v,u){return w.replace(/\t/g,q)})}if(p){r=r.replace(/\n/g,"<br>")}return r}function n(t,w,r){var x=h(t,r);var v=a(t);var y,s;if(v){y=d(v,x)}else{return}var q=c(t);if(q.length){s=document.createElement("pre");s.innerHTML=y.value;y.value=k(q,c(s),x)}y.value=i(y.value,w,r);var u=t.className;if(!u.match("(\\s|^)(language-)?"+v+"(\\s|$)")){u=u?(u+" "+v):v}if(/MSIE [678]/.test(navigator.userAgent)&&t.tagName=="CODE"&&t.parentNode.tagName=="PRE"){s=t.parentNode;var p=document.createElement("div");p.innerHTML="<pre><code>"+y.value+"</code></pre>";t=p.firstChild.firstChild;p.firstChild.cN=s.cN;s.parentNode.replaceChild(p.firstChild,s)}else{t.innerHTML=y.value}t.className=u;t.result={language:v,kw:y.keyword_count,re:y.r};if(y.second_best){t.second_best={language:y.second_best.language,kw:y.second_best.keyword_count,re:y.second_best.r}}}function o(){if(o.called){return}o.called=true;var r=document.getElementsByTagName("pre");for(var p=0;p<r.length;p++){var q=b(r[p]);if(q){n(q,hljs.tabReplace)}}}function l(){if(window.addEventListener){window.addEventListener("DOMContentLoaded",o,false);window.addEventListener("load",o,false)}else{if(window.attachEvent){window.attachEvent("onload",o)}else{window.onload=o}}}var e={};this.LANGUAGES=e;this.highlight=d;this.highlightAuto=g;this.fixMarkup=i;this.highlightBlock=n;this.initHighlighting=o;this.initHighlightingOnLoad=l;this.IR="[a-zA-Z][a-zA-Z0-9_]*";this.UIR="[a-zA-Z_][a-zA-Z0-9_]*";this.NR="\\b\\d+(\\.\\d+)?";this.CNR="\\b(0[xX][a-fA-F0-9]+|(\\d+(\\.\\d*)?|\\.\\d+)([eE][-+]?\\d+)?)";this.BNR="\\b(0b[01]+)";this.RSR="!|!=|!==|%|%=|&|&&|&=|\\*|\\*=|\\+|\\+=|,|\\.|-|-=|/|/=|:|;|<|<<|<<=|<=|=|==|===|>|>=|>>|>>=|>>>|>>>=|\\?|\\[|\\{|\\(|\\^|\\^=|\\||\\|=|\\|\\||~";this.ER="(?![\\s\\S])";this.BE={b:"\\\\.",r:0};this.ASM={cN:"string",b:"'",e:"'",i:"\\n",c:[this.BE],r:0};this.QSM={cN:"string",b:'"',e:'"',i:"\\n",c:[this.BE],r:0};this.CLCM={cN:"comment",b:"//",e:"$"};this.CBLCLM={cN:"comment",b:"/\\*",e:"\\*/"};this.HCM={cN:"comment",b:"#",e:"$"};this.NM={cN:"number",b:this.NR,r:0};this.CNM={cN:"number",b:this.CNR,r:0};this.BNM={cN:"number",b:this.BNR,r:0};this.inherit=function(r,s){var p={};for(var q in r){p[q]=r[q]}if(s){for(var q in s){p[q]=s[q]}}return p}}();hljs.LANGUAGES.cpp=function(){var a={keyword:{"false":1,"int":1,"float":1,"while":1,"private":1,"char":1,"catch":1,"export":1,virtual:1,operator:2,sizeof:2,dynamic_cast:2,typedef:2,const_cast:2,"const":1,struct:1,"for":1,static_cast:2,union:1,namespace:1,unsigned:1,"long":1,"throw":1,"volatile":2,"static":1,"protected":1,bool:1,template:1,mutable:1,"if":1,"public":1,friend:2,"do":1,"return":1,"goto":1,auto:1,"void":2,"enum":1,"else":1,"break":1,"new":1,extern:1,using:1,"true":1,"class":1,asm:1,"case":1,typeid:1,"short":1,reinterpret_cast:2,"default":1,"double":1,register:1,explicit:1,signed:1,typename:1,"try":1,"this":1,"switch":1,"continue":1,wchar_t:1,inline:1,"delete":1,alignof:1,char16_t:1,char32_t:1,constexpr:1,decltype:1,noexcept:1,nullptr:1,static_assert:1,thread_local:1,restrict:1,_Bool:1,complex:1},built_in:{std:1,string:1,cin:1,cout:1,cerr:1,clog:1,stringstream:1,istringstream:1,ostringstream:1,auto_ptr:1,deque:1,list:1,queue:1,stack:1,vector:1,map:1,set:1,bitset:1,multiset:1,multimap:1,unordered_set:1,unordered_map:1,unordered_multiset:1,unordered_multimap:1,array:1,shared_ptr:1}};return{dM:{k:a,i:"</",c:[hljs.CLCM,hljs.CBLCLM,hljs.QSM,{cN:"string",b:"'\\\\?.",e:"'",i:"."},{cN:"number",b:"\\b(\\d+(\\.\\d*)?|\\.\\d+)(u|U|l|L|ul|UL|f|F)"},hljs.CNM,{cN:"preprocessor",b:"#",e:"$"},{cN:"stl_container",b:"\\b(deque|list|queue|stack|vector|map|set|bitset|multiset|multimap|unordered_map|unordered_set|unordered_multiset|unordered_multimap|array)\\s*<",e:">",k:a,r:10,c:["self"]}]}}}();hljs.LANGUAGES.r={dM:{c:[hljs.HCM,{cN:"number",b:"\\b0[xX][0-9a-fA-F]+[Li]?\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\b\\d+(?:[eE][+\\-]?\\d*)?L\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\b\\d+\\.(?!\\d)(?:i\\b)?",e:hljs.IMMEDIATE_RE,r:1},{cN:"number",b:"\\b\\d+(?:\\.\\d*)?(?:[eE][+\\-]?\\d*)?i?\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"number",b:"\\.\\d+(?:[eE][+\\-]?\\d*)?i?\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"keyword",b:"(?:tryCatch|library|setGeneric|setGroupGeneric)\\b",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\.\\.\\.",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\.\\.\\d+(?![\\w.])",e:hljs.IMMEDIATE_RE,r:10},{cN:"keyword",b:"\\b(?:function)",e:hljs.IMMEDIATE_RE,r:2},{cN:"keyword",b:"(?:if|in|break|next|repeat|else|for|return|switch|while|try|stop|warning|require|attach|detach|source|setMethod|setClass)\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"literal",b:"(?:NA|NA_integer_|NA_real_|NA_character_|NA_complex_)\\b",e:hljs.IMMEDIATE_RE,r:10},{cN:"literal",b:"(?:NULL|TRUE|FALSE|T|F|Inf|NaN)\\b",e:hljs.IMMEDIATE_RE,r:1},{cN:"identifier",b:"[a-zA-Z.][a-zA-Z0-9._]*\\b",e:hljs.IMMEDIATE_RE,r:0},{cN:"operator",b:"<\\-(?!\\s*\\d)",e:hljs.IMMEDIATE_RE,r:2},{cN:"operator",b:"\\->|<\\-",e:hljs.IMMEDIATE_RE,r:1},{cN:"operator",b:"%%|~",e:hljs.IMMEDIATE_RE},{cN:"operator",b:">=|<=|==|!=|\\|\\||&&|=|\\+|\\-|\\*|/|\\^|>|<|!|&|\\||\\$|:",e:hljs.IMMEDIATE_RE,r:0},{cN:"operator",b:"%",e:"%",i:"\\n",r:1},{cN:"identifier",b:"`",e:"`",r:0},{cN:"string",b:'"',e:'"',c:[hljs.BE],r:0},{cN:"string",b:"'",e:"'",c:[hljs.BE],r:0},{cN:"paren",b:"[[({\\])}]",e:hljs.IMMEDIATE_RE,r:0}]}};
hljs.initHighlightingOnLoad();
</script>
<!-- MathJax scripts -->
<script type="text/javascript" src="https://c328740.ssl.cf1.rackcdn.com/mathjax/2.0-latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
</script>
<style type="text/css">
/* Set the main font to Calibri, same
as My Word 2010 uses. Also set the
default font size to 11pt.
The maximum width to 35em enhances
readability through optimal line
length. Note: this setting is ignored
by Word/Libre Office*/
body {
font-family: serif;
/* font-family: Calibri; */
font-size: 13pt;
background-color: white;
padding-top: 1em;
margin: auto;
max-width: 35em;
}
/* Set the paragraph margin and
padding to 0 except for the bottom */
p {
padding: 0;
margin: 0;
margin-bottom: 10pt;
}
/* Center the table and add top/bottom margins */
table{
margin: auto;
margin-top: 1em;
margin-bottom: 1em;
border: none;
}
/* The tr padding/margin 0 is important for table
import, while the font needs to be specified as
font and not font-family/font-size due to limiations
in Libre Office */
td, tr{
font: 12pt Arial;
padding: 0px;
margin: 0px;
}
/* The cell should have a little space to easy reading
although this section is mostly ignored by the
Libre Office import */
td {
padding: 4px;
padding-bottom: 2px;
}
/* Set the headings to correspond to Word-style */
h1, h2, h3, h4, h5, h6 {
margin: 10pt 0pt 0pt 0pt;
font-family: sans-serif;
font-weight: bold;
}
/* h1 has a slightly larger top margins
so we re-set that from the other*/
h1 {
margin: 24pt 0pt 0pt 0pt;
font-size: 18pt;
color: #365F91;
}
h2 {
margin: 18pt 0pt 0pt 0pt;
font-size: 14pt;
color: #4F81BD;
}
h3 {
margin: 15pt 0pt 0pt 0pt;
font-size: 13pt;
color: #4F81BD;
}
h4 {
font-size: 12pt;
font-weight: bold;
font-style: italic;
color: #4F81BD;
}
h5 {
font-size: 11pt;
font-weight: normal;
color: #243F5D;
}
h6 {
font-size: 11pt;
font-weight: normal;
font-style: italic;
color: #243F5D;
}
/* The following sections are mostly
unrelated to Word/Libre Office imports */
tt, code, pre {
font-family: 'DejaVu Sans Mono', 'Droid Sans Mono', 'Lucida Console', Consolas, Monaco, monospace;
font-size:10pt;
}
a:visited {
color: rgb(50%, 0%, 50%);
}
pre {
margin-top: 0;
max-width: 95%;
border: 1px solid #ccc;
white-space: pre-wrap;
}
pre code {
display: block; padding: 0.5em;
}
code.r, code.cpp {
background-color: #F8F8F8;
}
blockquote {
color:#666666;
margin:0;
padding-left: 1em;
border-left: 0.5em #EEE solid;
}
hr {
height: 0px;
border-bottom: none;
border-top-width: thin;
border-top-style: dotted;
border-top-color: #999999;
}
@media print {
* {
background: transparent !important;
color: black !important;
filter: none !important;
-ms-filter: none !important;
}
body {
font-size:11pt;
max-width:100%;
}
a, a:visited {
text-decoration: underline;
}
hr {
visibility: hidden;
page-break-before: always;
}
pre, blockquote {
padding-right: 1em;
page-break-inside: avoid;
}
tr, img {
page-break-inside: avoid;
}
img {
max-width: 100% !important;
}
@page {
margin-top: 2cm;
margin-bottom: 1.5cm;
margin-left: 3cm;
margin-right: 3cm;
}
p, h2, h3 {
orphans: 3; widows: 3;
}
h2, h3 {
page-break-after: avoid;
}
}
</style>
</head>
<body>
<h2 style='margin: 10pt 0pt 0pt 0pt;'>Analysis of acumulation curves for species interactions</h2>
<h3 style='margin: 10pt 0pt 0pt 0pt;'>Estimating frugivore species richness. A “phytocentric” sampling</h3>
<p>We use here a dataset of direct census of animal frugivores visiting <em>Cecropia glaziovii</em> (Cecropiaceae) trees in Intervales, SP, Brazil (March 2012).
We use each tree observed as a census, and we accumulate across trees the number of frugivore species recorded visiting the plant. The idea is that as we sample additional individual trees we may get a more complete account of the actual frugivore species interacting with the plant. Eventually, for a large sample size, the number of frugivore species recorded reaches a plateu, that can be considered a robust estimate of the actual spcies richness of the frugivore assemblage.</p>
<p>Species (taxa) are in rows. Census samples are the columns.<br/>
Code variables are:<br/>
<code>cla</code> - Class: Aves, Mammalia<br/>
<code>ord</code> - Order<br/>
<code>fam</code> - Family<br/>
<code>gen</code> - Genus<br/>
<code>sp</code> - Species<br/>
<code>code</code> - species labels<br/>
<code>totvis</code> - visits recorded<br/>
<code>totbic</code> - number of fruits pecked<br/>
<code>sde</code> - effectiveness<br/>
Then columns <code>cec18</code>, <code>cec02</code>… inidicate individual plants. The adjacency matrix entries hold the number of records. </p>
<pre><code class="r"># We may eventually need these libraries.
require(vegan)
require(ade4)
# Data input. First a dataset with group codes and labels.
accum <- read.table("data/cecropia.txt", header = TRUE, sep = "\t", dec = ",",
na.strings = "NA")
# I transpose the dataset (needed for accumulation curves).
mat <- data.frame(t(accum[, 10:37])) # Just the adjacency matrix,
# and we add rownames
colnames(mat) <- accum$code
head(mat[, 1:6])
</code></pre>
<pre><code>## Thr_orna Bro_tiri Eup_chal Pyr_fron Coe_flav Cis_leve
## cec18 999 400 0 120 6 0
## cec02 1113 0 20 1 0 0
## cec03 742 0 20 4 1 1
## cec25 49 0 0 0 4 0
## cec22 315 256 4 0 0 0
## cec06 99 16 0 0 0 16
</code></pre>
<pre><code class="r">specpool(mat) # This is the species richness estimates
</code></pre>
<pre><code>## Species chao chao.se jack1 jack1.se jack2 boot boot.se n
## All 38 50.5 8.457 52.46 5.052 58.35 44.71 2.873 28
</code></pre>
<pre><code class="r"># Now, plot the species accumulation curves.
all <- specaccum(mat, method = "random")
plot(all, col = "blue", lwd = 2, ci.type = "poly", ci.lty = 0, ci.col = "lightblue",
ylim = c(0, 45), main = "Cecropia glaziovii", xlab = "Number of trees",
ylab = "Number of frugivore species")
boxplot(all, col = "yellow", add = TRUE, pch = "+")
</code></pre>
<p><img src="data:image/png;base64,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" alt="plot of chunk data"/> </p>
<h3 style='margin: 10pt 0pt 0pt 0pt;'>Estimating fruit species richness. A “zoocentric” sampling</h3>
<p>Here I use a different dataset to assess how the number of interaction records increases with increasing the the number of individual samples. I use a dataset of three <em>Sylvia</em> species, whose diet was analyzed by study of faecal samples. Individual fruit species consumed by the warblers were determined by obtaining faeces from mist-netted birds and identifying seeds and pulp remains. I this way, the number of fruit ingested wa sestimated for a large number of individual birds. I am interested in assessing the robustness of the sampling, i.e., whether increasing the sample size would result in additional species recorded. This type of information can be used with all frugivore species in the community to assess the overall sampling robustnees of an empirical network.</p>
<pre><code class="r"># Reading the dataset, from a matrix of 1054 samples of three warbler
# species: Sylvia atricapilla, Sylvia borin, and Sylvia melanocephala. Data
# input. First a dataset with group codes and labels.
sylvia <- read.table("data/hr_sylvia.txt", header = TRUE, sep = "\t", dec = ".",
na.strings = "NA")
# By species
satr <- sylvia[sylvia$species == "SATR", ][, 4:20]
sbor <- sylvia[sylvia$species == "SBOR", ][, 4:20]
smel <- sylvia[sylvia$species == "SMEL", ][, 4:20]
#
specpool(satr) # Fruit species richness estimates
</code></pre>
<pre><code>## Species chao chao.se jack1 jack1.se jack2 boot boot.se n
## All 15 15 0 16 0.9984 17 15.44 0.5453 643
</code></pre>
<pre><code class="r">specpool(sbor)
</code></pre>
<pre><code>## Species chao chao.se jack1 jack1.se jack2 boot boot.se n
## All 13 13.25 0.7289 13.99 0.9942 13.02 13.71 0.7319 173
</code></pre>
<pre><code class="r">specpool(smel)
</code></pre>
<pre><code>## Species chao chao.se jack1 jack1.se jack2 boot boot.se n
## All 13 15 3.742 14.99 1.408 15.99 13.93 0.8036 238
</code></pre>
<pre><code class="r"># Now, plot the species accumulation curves. Function to estimate
# accumulation curves and plot
spacc <- function(data, thetitle) {
spaccum <- specaccum(data, method = "random")
plot(spaccum, ci.type = "poly", col = "blue", lwd = 2, ci.lty = 0, ylim = c(0,
20), ci.col = "lightblue", main = thetitle, xlab = "Number of samples",
ylab = "Number of fruit species")
# NOT RUN: boxplot(spaccum, col='yellow', add=TRUE, pch='+')
}
par(mfrow = c(3, 1))
spacc(satr, "Sylvia atricapilla")
spacc(sbor, "Sylvia borin")
spacc(smel, "Sylvia mlanocephala")
</code></pre>
<p><img src="data:image/png;base64,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" alt="plot of chunk sylvia"/> </p>
<h2 style='margin: 10pt 0pt 0pt 0pt;'>Accumulation curves for interactions</h2>
<p>Now suppose we sample an interaction network. We get data in different samples (i.e., census days) where we record pairwise species interactions. So, each sampling is our adjacency matrix filled up with just those interactions recorded in a particular day. For example, imagine we sample a communtiy with <code>A= 5</code> animal species and <code>P= 8</code> plant species:</p>
<pre><code class="r"># Create dummy datasets with pairwise interactions recorded in each
# sampling. List of the sampled matrices. Day 1- getting the pairwise
# interaction labels.
source("functions/vectorize.R")
source("functions/matfills.R") # This creates a randomly-filled matrix
M1 <- randommat(5, 8)
colnames(M1) <- c("P1", "P2", "P3", "P4", "P5", "P6", "P7", "P8")
rownames(M1) <- c("A1", "A2", "A3", "A4", "A5")
MM <- vectorize(M1)
colnames(MM) <- c("A", "P", "I")
head(MM)
</code></pre>
<pre><code>## A P I
## 1 A1 P1 0
## 2 A1 P2 0
## 3 A1 P3 0
## 4 A1 P4 0
## 5 A1 P5 0
## 6 A1 P6 0
</code></pre>
<pre><code class="r">lab <- paste(MM$A, "-", MM$P)
MM <- data.frame(lab)
# Generate the additional matrices
m <- function() {
mat <- randommat(5, 8)
colnames(mat) <- c("P1", "P2", "P3", "P4", "P5", "P6", "P7", "P8")
rownames(mat) <- c("A1", "A2", "A3", "A4", "A5")
return(mat)
}
# List of matrices (50 samples)
mlist <- list(m(), m(), m(), m(), m(), m(), m(), m(), m(), m(), m(), m(), m(),
m(), m(), m(), m(), m(), m(), m(), m(), m(), m(), m(), m(), m(), m(), m(),
m(), m(), m(), m(), m(), m(), m(), m(), m(), m(), m(), m(), m(), m(), m(),
m(), m(), m(), m(), m(), m(), m())
# mlist should be a list of observed matrices, corresponding to different
# sampling events (censuses, days, etc.)
tt <- sapply(mlist, function(m) cbind(vectorize(m)), simplify = FALSE, USE.NAMES = FALSE)
# Create a dataframe with the pairwise interactions recorded in each sample.
ttt <- as.data.frame(unlist(tt, recursive = F))
ttt <- ttt[, c(seq(from = 3, to = 150, by = 3))]
MM <- data.frame(cbind(MM, ttt))
colnames(MM) <- c("Pairwise", rep("sample", 50))
head(MM[, 1:8])
</code></pre>
<pre><code>## Pairwise sample sample.1 sample.2 sample.3 sample.4 sample.5 sample.6
## 1 A1 - P1 0 0 0 0 0 0 0
## 2 A1 - P2 1 0 1 0 0 1 1
## 3 A1 - P3 0 0 0 0 0 0 0
## 4 A1 - P4 0 0 0 0 0 0 0
## 5 A1 - P5 0 0 0 0 0 0 0
## 6 A1 - P6 0 0 0 0 1 0 0
</code></pre>
<p>Our final dataset now lists all the potential pairwise interactions and the records we got in each sampling day. Each of the columns lists the pairwise interactions recorded (value= 1) in a particular sample.
Now we can use accumulation functions to explore how increasing the sampling results in additional distinct interactions being sampled.
It is as a sampling of diversity, but instead of species we are recording pairwise interactions.</p>
<pre><code class="r"># Specify only the numerical columns!
mat <- t(MM[, 2:ncol(MM)]) # Note that I transpose the matrix to get
# samples as rows.
specpool(mat) # Statistics
</code></pre>
<pre><code>## Species chao chao.se jack1 jack1.se jack2 boot boot.se n
## All 39 39.12 0.4375 39.98 0.98 37.18 40.41 1.16 50
</code></pre>
<pre><code class="r">all <- specaccum(mat, method = "random")
plot(all, col = "blue", lwd = 2, ci.type = "poly", ci.lty = 0, ci.col = "lightblue",
ylim = c(0, 40), main = "Accumulation analysis - Interactions", xlab = "Number of censuses/samples",
ylab = "Number of distinct pairwise interactions")
boxplot(all, col = "yellow", add = TRUE, pch = "+")
</code></pre>
<p><img src="data:image/png;base64,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" alt="plot of chunk pairwise_interactions_2"/> </p>
</body>
</html>