-
Notifications
You must be signed in to change notification settings - Fork 5
Expand file tree
/
Copy pathIndex.html
More file actions
8360 lines (7995 loc) · 660 KB
/
Index.html
File metadata and controls
8360 lines (7995 loc) · 660 KB
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
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en">
<head>
<meta charset="utf-8">
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta name="generator" content="pandoc" />
<meta name="author" content="Cory Whitney, Eike Luedeling et al." />
<meta name="progressive" content="false" />
<meta name="allow-skip" content="false" />
<meta name="learnr-version-prerender" content="0.11.5" />
<title>Decision Analysis and Forecasting for Agricultural Development </title>
<!-- header-includes START -->
<!-- HEAD_CONTENT -->
<!-- header-includes END -->
<!-- HEAD_CONTENT -->
<!-- highlightjs -->
<style type="text/css">code{white-space: pre;}</style>
<style type="text/css">
pre:not([class]) {
background-color: white;
}
</style>
<script type="text/javascript">
if (window.hljs) {
hljs.configure({languages: []});
hljs.initHighlightingOnLoad();
if (document.readyState && document.readyState === "complete") {
window.setTimeout(function() { hljs.initHighlighting(); }, 0);
}
}
</script>
<!-- taken from https://github.com/rstudio/rmarkdown/blob/de8a9c38618903627ca509f5401d50a0876079f7/inst/rmd/h/default.html#L293-L343 -->
<!-- tabsets -->
<style type="text/css">
.tabset-dropdown > .nav-tabs {
display: inline-table;
max-height: 500px;
min-height: 44px;
overflow-y: auto;
border: 1px solid #ddd;
border-radius: 4px;
}
.tabset-dropdown > .nav-tabs > li.active:before {
content: "";
font-family: 'Glyphicons Halflings';
display: inline-block;
padding: 10px;
border-right: 1px solid #ddd;
}
.tabset-dropdown > .nav-tabs.nav-tabs-open > li.active:before {
content: "";
border: none;
}
.tabset-dropdown > .nav-tabs.nav-tabs-open:before {
content: "";
font-family: 'Glyphicons Halflings';
display: inline-block;
padding: 10px;
border-right: 1px solid #ddd;
}
.tabset-dropdown > .nav-tabs > li.active {
display: block;
}
.tabset-dropdown > .nav-tabs > li > a,
.tabset-dropdown > .nav-tabs > li > a:focus,
.tabset-dropdown > .nav-tabs > li > a:hover {
border: none;
display: inline-block;
border-radius: 4px;
background-color: transparent;
}
.tabset-dropdown > .nav-tabs.nav-tabs-open > li {
display: block;
float: none;
}
.tabset-dropdown > .nav-tabs > li {
display: none;
}
</style>
<!-- end tabsets -->
</head>
<body>
<a class='sr-only sr-only-focusable visually-hidden-focusable' href='#learnr-tutorial-content'>Skip to Tutorial Content</a>
<div class="pageContent band">
<main class="bandContent page">
<article class="topics" id="learnr-tutorial-content">
<p><img src="images/decisionSupport_hex_sticker.png"
style="width:1in" />
<!-- ![]() syntax will also work but not for html --></p>
<!-- List of Lecture RMD files to be compiled -->
<div id="section-introduction" class="section level2">
<h2>Lecture 1: Introduction</h2>
<!-- use the {#introduction} syntax to create a label that can be referenced with [Introduction](#introduction) -->
<p><img src="images/INRES_Logo.png" style="width:1in" /> <img
src="images/Uni_Bonn_Picture.png" style="width:2.5in" /> <img
src="images/decisionSupport_hex_sticker.png" style="width:1in" /></p>
<p>Welcome to <strong>Decision Analysis and Forecasting for Agricultural
Development</strong>. We are excited to deliver you this course content
and to train a new generation of experts in applying these tools. We see
enormous scope for application of these methods in agriculture and the
need for more practitioners. The course has a <a
href="https://agtools.app/decision_analysis/">dedicated interactive
website</a> but if you prefer you can also look at the <a
href="http://htmlpreview.github.io/?https://github.com/CWWhitney/Decision_Analysis_Course/blob/main/Index.html">simple
html version</a>.</p>
<p>Decisions in agriculture are often risky, meaning that decision
makers have uncertainty about how their decision will influence the
intended outcomes. Farming systems are dynamic and the impact of any
intervention, policy or management decision is likely to be influenced
by many factors ranging from soil and crop dynamics to social dynamics
such as farmer and community perceptions. In order to provide scientific
support for decision making it is important that our models and
forecasts attempt to include these interactions. Decision Analysis
provides a set of approaches that are aimed at capturing what is known
and applying this knowledge to generate forecasts of decision outcomes.
The theoretical body of approaches have been formally applied in
business and economics for more than 50 years <span
class="citation">Howard and Abbas (2015)</span> and have been gaining
ground in agricultural development research more recently <span
class="citation">Luedeling and Shepherd (2016)</span>. Our mission is to
normalize these holistic approaches and move agricultural science from
the lab bench and field trials to real world application and decision
support for farmers and agricultural decision makers such as those in
government ministries and aid organizations.</p>
<p><strong>A student is not a vessel to be filled, but a lamp to be
lighted…</strong> - Plutarch</p>
<ul>
<li><p><strong>What?</strong> This is an experiential course. You
(participants) will be leading discussions and projects.</p></li>
<li><p><strong>So What?</strong> The aim is for you to become a critical
thinker and lead the process in generating useful forecasts for decision
makers in agricultural development.</p></li>
<li><p><strong>Now What?</strong> You will build a working model of an
agricultural development decision.</p></li>
</ul>
<p>Here is a course overview:</p>
<p><img src="images/DA-Overview.png" style="width:9in" /></p>
</div>
<div id="section-course-content" class="section level2">
<h2>Course content</h2>
<p>In this course, we will provide an overview of methods we can use to
study agricultural development decisions and generate forecasts of
decision outcomes. If you do not have a clear idea what that is you’ve
come to the right place. This course was developed for MSc. students in
<a
href="https://www.aei.uni-bonn.de/en/studies/study-programs/msc-crop-sciences/msc-npw">Crop
Sciences</a> at the <a href="https://www.uni-bonn.de/en/home">University
of Bonn</a>, but the materials are also intended for a general audience
interested in applying these tools. The main parts of the course
include:</p>
<ul>
<li><a href="#section-decision_analysis">Introduction to Decision
Analysis</a></li>
<li><a href="#section-calibration_lecture">Calibration training</a></li>
<li><a href="#section-participatory_methods">Participatory modeling
building</a></li>
<li><a href="#section-model_programming">Decision modeling in R</a></li>
<li>Group project on decision analysis</li>
</ul>
<p>See the official pages in the coursebook here <a
href="https://www.aei.uni-bonn.de/de/studium/medienpdf/modulhandbuch/mhb-msc-arts.pdf#page=72.08"><strong>Decision
Analysis and Forecasting for Agricultural Development</strong></a>.</p>
<p>After some introduction of the subject matter much of this course
will consist of practical application of the <a
href="https://cran.r-project.org/web/packages/decisionSupport/index.html"><code>decisionSupport</code></a>
package in the <a href="https://www.r-project.org/">R</a> programming
language <span class="citation">(R Core Team 2025)</span>.</p>
<div id="section-intended-learning-outcomes" class="section level3">
<h3>Intended learning outcomes</h3>
<p>In this course, we aim to provide you with the skills and experiences
in decision modeling. By the end of this course you will be able to:</p>
<ul>
<li><p>develop decision models and comprehensively evaluate the findings
using the <code>R</code> programming language with functions from the
<code>decisionSupport</code> package <span class="citation">(Luedeling
et al. 2024)</span>.</p></li>
<li><p>recognize your own biases and provide accurate range estimates
for uncertain variables.</p></li>
<li><p>analyze a decision context. You will be able to draw conclusions
from a decision model and recommend steps forward.</p></li>
<li><p>develop decision models, comprehensively evaluate your findings
and compose a report about the model you developed.</p></li>
</ul>
</div>
</div>
<div id="section-performance-assessment" class="section level2">
<h2>Performance assessment</h2>
<p>In this module, there will be no exam, but you’ll still have to put
in a bit of effort to pass and get a good grade here. Over the course of
the semester, you’ll be developing an <a
href="https://rmarkdown.rstudio.com/">Rmarkdown</a> document, where
you’ll record your learning and your coding work (<a
href="http://inresgb-lehre.iaas.uni-bonn.de/Methodology_outline.html">here
is an example from Hoa Do with an overview that includes the main
modeling procedures with the decisionSupport package in R</a>) <span
class="citation">(Luedeling et al. 2024)</span>. This document will
contain short thematic chapters on the lecture contents, as well as the
code you’ll produce and the outputs you’ll generate. The final chapters
will contain some discussion of the results you’ll have obtained. This
document will be evaluated, and it will be the major determinant of your
final grade (participation in class will also count for some of the
grade).</p>
<p>There will be about 60 hours of formal in-class time (15 ~ 4 hour <a
href="#section-lecture_schedule">lectures</a> and <a
href="#section-seminar_schedule">seminars</a>) and 120 hours of work
outside the class.</p>
<div id="section-what-we-expect-from-you" class="section level3">
<h3>What we expect from you</h3>
<p>Class participation will be about 50% of the work in this course. We
will expect you to show up in class and be an active participant in
discussions. We may also have short weekly tests for seeing how up to
speed you are and we will track your project activity (follow your <a
href="github.com">git</a> repositories etc.).</p>
<p>Group work will make up the rest of the required work for this
course. You will put together a report, build a repository with code and
a working RMarkdown file. You will also do weekly reading/listening
assignments and lead short related discussions.</p>
</div>
</div>
<div id="section-house-rules" class="section level2">
<h2>House rules</h2>
<p>In this course, we’ll gradually work our way into the
<code>decisionSupport</code> package <span class="citation">(Luedeling
et al. 2024)</span>. At the end of the semester, you should be able to
apply state-of-the-art Decision Analysis. Yet even if it’s not your
ambition to become a decision analyst, you’ll have picked up a bunch of
useful skills along the way. We’ll try to teach you how to use some
staple programming tools and techniques that can be used for all kinds
of programming challenges. These will include the use of git and <a
href="github.com">github</a> and <a href="rmarkdown.com">Rmarkdown</a>,
as well the the ability to create, manipulate and use R functions and
packages.</p>
<p>What is expected of you is to be engaged in this class, and to
diligently complete the assignments you receive. Learning things in R
requires practice, through which many things that seem cumbersome at
first eventually become almost automatic. We are hopeful that the things
you’ll get exposed to in this class will be assets in your scientific
(or other) career. So please take the materials seriously!</p>
<div id="section-tools-we-use" class="section level3">
<h3>Tools we use</h3>
<p>This course not only aims to teach you things about Decision Analysis
and related topics - it also provides hands-on exercises to illustrate
the functions of the <code>decisionSupport</code> package <span
class="citation">Luedeling et al. (2024)</span>. For all of these
practical components, we need tools. <code>decisionSupport</code> is an
R package, so we’ll need <a href="https://www.r-project.org/">R</a>,
which we will operate through the <a
href="https://posit.co/download/rstudio-desktop/">RStudio</a>
interface.</p>
<p>We could simply start running <a
href="https://posit.co/download/rstudio-desktop/">RStudio</a> on our
local computer, save our files somewhere on our hard drive and generally
operate the way we usually work with our computer. But this is not how
real programmers work, and since this is what we’re trying to be, we
should familiarize ourselves with some code development tools that such
people use. We’ll therefore introduce you to <a
href="https://git-scm.com/">git</a> and <a
href="https://github.com/">github</a>, which are very useful for keeping
code organized and secure and for sharing with collaborators and wider
audiences.</p>
<p>Finally, we want to show you how to properly document what you do in
R, and how to compile professional-looking reports of your work. This is
what <a href="https://rmarkdown.rstudio.com/">Rmarkdown</a> helps us do.
Some of this may be a bit confusing in the beginning, but you’ll
probably learn to appreciate the value of these tools, as we keep using
them in this module.</p>
</div>
</div>
<div id="section-group-work" class="section level2">
<h2>Group Work</h2>
<p>The course will be largely based on group work. Please take some time
to choose a group to work with and begin to think about a decision. Over
the next few weeks you will be responsible for the following
milestones:</p>
<ul>
<li><p>Identify a decision</p></li>
<li><p>Frame the decision and develop a qualitative model</p></li>
<li><p>Generate and parameterize a quantitative model</p></li>
<li><p>Generate a git repo with code and documentation</p></li>
<li><p>Write a ~ 5,000 word paper in RMarkdown, see this report on <a
href="http://htmlpreview.github.io/?https://github.com/hortibonn/Plotting-High-Dimensional-Data/blob/master/HighDimensionalData.html">plotting
high-dimensional data</a> for a useful example of how this can be
done.</p></li>
</ul>
<p>In addition, each week small teams (groups of two or three) will be
responsible for presenting and leading a discussion on a short paper or
chapter. We expect everyone in the course to read the work and come
prepared for the meeting. Please contact us if you cannot find the
readings in the library or elsewhere. We will help you get a copy.</p>
<div id="section-bonus-video-from-sir-ken-robinson"
class="section level3">
<h3>Bonus video from Sir Ken Robinson</h3>
<p>Bonus: to get more background on the teaching methods that inspire
this course watch <a
href="https://www.ted.com/talks/sir_ken_robinson_do_schools_kill_creativity">Sir
Ken Robinson’s talk on Ted.com</a>. If you like it you might enjoy
reading his book ‘Out of Our Minds’ <span class="citation">(Robinson
2017)</span>.</p>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-ken-robinson" class="tutorial-question panel-body">
<div id="question-ken-robinson-answer_container" class="shiny-html-output"></div>
<div id="question-ken-robinson-message_container" class="shiny-html-output"></div>
<div id="question-ken-robinson-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<!-- ```{r child="Tools_Experiential.Rmd"} -->
<!-- ``` -->
</div>
</div>
<div id="section-lecture_schedule" class="section level2">
<h2>Lecture schedule</h2>
<table>
<colgroup>
<col width="5%" />
<col width="17%" />
<col width="22%" />
<col width="53%" />
</colgroup>
<thead>
<tr class="header">
<th align="right">Lecture</th>
<th align="left">Date</th>
<th align="left">Materials</th>
<th align="left">Reading</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td align="right">1</td>
<td align="left">Wednesday, April 9, 2025</td>
<td align="left"><a href="#section-introduction">Introduction</a></td>
<td align="left">Watch: Sir Ken Robinson / Hans Rosling (optional)</td>
</tr>
<tr class="even">
<td align="right">2</td>
<td align="left">Friday, April 11, 2025</td>
<td align="left"><a href="#section-decision_analysis">Decision Analysis
Overview</a></td>
<td align="left"><span class="citation">Luedeling and Shepherd
(2016)</span></td>
</tr>
<tr class="odd">
<td align="right">3</td>
<td align="left">Wednesday, April 16, 2025</td>
<td align="left"><a href="#section-define_decision">Defining a
Decision</a></td>
<td align="left"><span class="citation">Howard and Abbas (2015)</span>
(Chapter 1. Introduction to Quality Decision Making)</td>
</tr>
<tr class="even">
<td align="right">4</td>
<td align="left">Wednesday, April 23, 2025</td>
<td align="left"><a href="#section-case_studies">Decision Analysis Case
Studies</a></td>
<td align="left"><span class="citation">Shepherd et al.
(2015)</span></td>
</tr>
<tr class="odd">
<td align="right">5</td>
<td align="left">Friday, April 25, 2025</td>
<td align="left"><a href="#section-participatory_methods">Participatory
Methods</a></td>
<td align="left">Reed et al. (2009)</td>
</tr>
<tr class="even">
<td align="right">6</td>
<td align="left">Wednesday, April 30, 2025</td>
<td align="left"><a href="#section-decision_models">Building Decision
Models</a></td>
<td align="left"><span class="citation">Do, Luedeling, and Whitney
(2020)</span></td>
</tr>
<tr class="odd">
<td align="right">7</td>
<td align="left">Friday, May 2, 2025</td>
<td align="left"><a href="#section-forecasts">Using Models to Create
Forecasts</a></td>
<td align="left"><span class="citation">Tetlock and Gardner
(2015)</span> (Chapter 1. An Optimistic Skeptic)</td>
</tr>
<tr class="even">
<td align="right">8</td>
<td align="left">Wednesday, May 7, 2025</td>
<td align="left"><a href="#section-bayes">Bayesian Thinking</a></td>
<td align="left"><span class="citation">Bertsch McGrayne (2011)</span>
(Chapter 1. Causes in the Air)</td>
</tr>
<tr class="odd">
<td align="right">9</td>
<td align="left">Friday, May 9, 2025</td>
<td align="left"><a href="#section-calibration_lecture">Calibrating
experts</a></td>
<td align="left"><span class="citation">Kahneman and Egan (2011)</span>
(Chapter 1)</td>
</tr>
<tr class="even">
<td align="right">10</td>
<td align="left">Friday, May 16, 2025</td>
<td align="left"><a href="#section-analyst_profile">Profile of a
Decision Analyst</a></td>
<td align="left"><span class="citation">Savage and Markowitz
(2009)</span> (Chapter 1)</td>
</tr>
</tbody>
</table>
</div>
<div id="section-seminar_schedule" class="section level2">
<h2>Seminar schedule</h2>
<table>
<colgroup>
<col width="4%" />
<col width="23%" />
<col width="38%" />
<col width="33%" />
</colgroup>
<thead>
<tr class="header">
<th align="right">Week</th>
<th align="left">Date</th>
<th align="left">Materials</th>
<th align="left">Assignment</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td align="right">1</td>
<td align="left">Wednesday, May 21, 2025</td>
<td align="left"><a href="#section-r_rstudio">Using R and
RStudio</a></td>
<td align="left">Install R and Rstudio</td>
</tr>
<tr class="even">
<td align="right">2</td>
<td align="left">Friday, May 23, 2025</td>
<td align="left"><a href="#section-rstudio_continued">Using R and
RStudio continued</a></td>
<td align="left">Share R scripts (part 1)</td>
</tr>
<tr class="odd">
<td align="right">3</td>
<td align="left">Wednesday, May 28, 2025</td>
<td align="left"><a href="#section-group_work_overview">Group Work
Overview</a></td>
<td align="left">Share R scripts (part 2)</td>
</tr>
<tr class="even">
<td align="right">4</td>
<td align="left">Friday, May 30, 2025</td>
<td align="left"><a href="#section-rmarkdown">Using RMarkdown</a></td>
<td align="left">Share Rmarkdown file</td>
</tr>
<tr class="odd">
<td align="right">5</td>
<td align="left">Wednesday, June 4, 2025</td>
<td align="left"><a href="#section-github_git">Using git and
Github</a></td>
<td align="left">Host your Rproj in a Github repo</td>
</tr>
<tr class="even">
<td align="right">6</td>
<td align="left">Friday, June 6, 2025</td>
<td align="left"><a href="#section-model_programming">Model
Programming</a></td>
<td align="left">Share R scripts (part 3)</td>
</tr>
<tr class="odd">
<td align="right">7</td>
<td align="left">Wednesday, June 18, 2025</td>
<td align="left"><a href="#section-calibration_seminar">Calibration
training</a></td>
<td align="left">Participate in calibration training</td>
</tr>
<tr class="even">
<td align="right">8</td>
<td align="left">Friday, June 20, 2025</td>
<td align="left"><a href="#section-model_functions">Model
functions</a></td>
<td align="left">Share updated model</td>
</tr>
<tr class="odd">
<td align="right">9</td>
<td align="left">Wednesday, June 25, 2025</td>
<td align="left"><a href="#section-voi">Value of information</a></td>
<td align="left">Share R scripts (part 4)</td>
</tr>
<tr class="even">
<td align="right">10</td>
<td align="left">Friday, June 27, 2025</td>
<td align="left"><a href="#section-communicating">Communicating Decision
Support</a></td>
<td align="left"></td>
</tr>
<tr class="odd">
<td align="right">11</td>
<td align="left">Wednesday, July 02, 2025</td>
<td align="left"><a href="#section-forecasts_seminar">Model
forecasts</a></td>
<td align="left">Share initial forecasts</td>
</tr>
<tr class="even">
<td align="right">12</td>
<td align="left">Friday, July 04, 2025</td>
<td align="left"><a href="#section-writing">Academic Writing and
Citation Management</a></td>
<td align="left">Join Zotero Group</td>
</tr>
<tr class="odd">
<td align="right">13</td>
<td align="left">Wednesday, July 09, 2025</td>
<td align="left">Consultation</td>
<td align="left"></td>
</tr>
<tr class="even">
<td align="right">14</td>
<td align="left">Friday, July 11, 2025</td>
<td align="left">Consultation</td>
<td align="left"></td>
</tr>
<tr class="odd">
<td align="right">15</td>
<td align="left">Wednesday, July 16, 2025</td>
<td align="left">Project presentation</td>
<td align="left">Present</td>
</tr>
<tr class="even">
<td align="right">16</td>
<td align="left">Friday, July 18, 2025</td>
<td align="left">Presentations continued</td>
<td align="left">Present</td>
</tr>
</tbody>
</table>
</div>
<div id="section-decision_analysis" class="section level2">
<h2>Lecture 2: Decision Analysis Overview</h2>
<!-- reference with [Decision Analysis](#decision_analysis) -->
<p><em>“Everything is vague to a degree you do not realize till you have
tried to make it precise.”</em></p>
<p>― <span class="citation">Whitehead and Russell (2011)</span></p>
<p><img src="images/INRES_Logo.png" style="width:1in" /> <img
src="images/Uni_Bonn_Picture.png" style="width:2in" /> <img
src="images/decisionSupport_hex_sticker.png" style="width:1in" /></p>
<p>Welcome to lecture 2 of <strong>Decision Analysis and Forecasting for
Agricultural Development</strong>. In this lecture we will use the
<code>#lecture-02-overview</code> Slack channel and in class lecture and
discussion to follow up. This will allow us all to have a chance to see
your progress, provide feedback. It will be encouraging to others to see
activity from colleagues. Feel free to bring up any questions or
concerns in the Slack or to <a
href="mailto:cory.whitney@uni-bonn.de?subject=%5BSeminar_2%5D%20Decision%20Analysis%20Lecture">Dr. Cory
Whitney</a> or the course tutor.</p>
<p>Please take a few minutes to watch the video and do the associated
exercises. The slides will be shared in the respective Slack
channels.</p>
<div id="section-introduction-1" class="section level3">
<h3>Introduction</h3>
<p>The introduction outlines the general theory and application of
Decision Analysis tools. <strong>At the end of the video please take a
moment to think about decisions that are made in agricultural
development</strong>, ideally decisions that are relevant to your
research interests. Please share these with us in the Slack channel.</p>
<p><strong>Remember to take a moment to gather your thoughts so far and
share with us in Slack. </strong></p>
<!--  -->
<iframe width="560" height="315" src="https://www.youtube.com/embed/7P2YI9-smfU" frameborder="0" allowfullscreen>
</iframe>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-1" class="tutorial-question panel-body">
<div id="question-1-answer_container" class="shiny-html-output"></div>
<div id="question-1-message_container" class="shiny-html-output"></div>
<div id="question-1-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-2" class="tutorial-question panel-body">
<div id="question-2-answer_container" class="shiny-html-output"></div>
<div id="question-2-message_container" class="shiny-html-output"></div>
<div id="question-2-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-3" class="tutorial-question panel-body">
<div id="question-3-answer_container" class="shiny-html-output"></div>
<div id="question-3-message_container" class="shiny-html-output"></div>
<div id="question-3-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
</div>
<div id="section-part-1-approaches" class="section level3">
<h3>Part 1: Approaches</h3>
<p>Part 1 gives an overview of various approaches in agricultural
research and of the Decision Analysis paradigm. At the end of the video
please take a moment to think about a situation where Decision Analysis
might be applicable. Try and identify a decision maker with a choice
between different options and with uncertainty about the outcome.</p>
<p><strong>Remember to share a specific risky decision that might be
supported with these tools. Share your ideas with us in
Slack.</strong></p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/IRZZokPD3GU" frameborder="0" allowfullscreen>
</iframe>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-DA-approaches_define" class="tutorial-question panel-body">
<div id="question-DA-approaches_define-answer_container" class="shiny-html-output"></div>
<div id="question-DA-approaches_define-message_container" class="shiny-html-output"></div>
<div id="question-DA-approaches_define-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-DA-approaches_impact-pathway" class="tutorial-question panel-body">
<div id="question-DA-approaches_impact-pathway-answer_container" class="shiny-html-output"></div>
<div id="question-DA-approaches_impact-pathway-message_container" class="shiny-html-output"></div>
<div id="question-DA-approaches_impact-pathway-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-DA-approaches_trans-research" class="tutorial-question panel-body">
<div id="question-DA-approaches_trans-research-answer_container" class="shiny-html-output"></div>
<div id="question-DA-approaches_trans-research-message_container" class="shiny-html-output"></div>
<div id="question-DA-approaches_trans-research-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
</div>
<div id="section-part-2-decision-analysis" class="section level3">
<h3>Part 2: Decision Analysis</h3>
<p>Part 2 offers some background on the theory and development of
Decision Analysis and how we apply it in agricultural decisions.</p>
<p>At the end of the video please take some time to think about a
practical application of the kinds of approaches to dealing with
uncertainty that are used in Decision Analysis. Describe a few variables
that you consider difficult to measure but for which the effects on a
decision might be possible to describe as uncertainty distributions.
Share with us in Slack.</p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/UvLiq85W398" frameborder="0" allowfullscreen>
</iframe>
</div>
<div id="section-part-3-model-building" class="section level3">
<h3>Part 3: Model Building</h3>
<p>Part 3 gives an overview of model building processes and
approaches.</p>
<p><strong>At the end of this video take some time to draw a decision
impact pathway.</strong> Draw a conceptual diagram of an agricultural
development decision. Include the major factors that would influence the
decision, no matter how difficult they might be to measure. Feel free to
use any program you like to make this drawing. <a
href="https://ncase.me/loopy/">Loopy</a> is a very nice interface. <a
href="https://www.google.com/slides/about/">Google Slides</a>, <a
href="https://app.biorender.com/biorender-templates">Biorender</a> are
also good options. For the more advance R users you might like the <a
href="https://igraph.org/r/">igraph library</a>. For those who prefer
analog, a photo or scan of a hand drawn diagram is also welcome. Be sure
to save your work and share it with us in Slack, a screen shot is fine,
a working link is even better.</p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/fikoVbnoNOQ" frameborder="0" allowfullscreen>
</iframe>
</div>
<div id="section-part-4-overcoming-bias" class="section level3">
<h3>Part 4: Overcoming Bias</h3>
<p>Part 4 gives an overview of various types of cognitive biases and
outlines how these can interfere with the definition of and
parameterization of models. The session ends with a number of approaches
that can be applied to help in overcoming these biases and outlines the
calibration training process whereby experts are trained to give
accurate estimates of their own uncertainty.</p>
<p><strong>At the end of the video please take some time to consider the
variables in your conceptual diagram that might benefit from calibrated
estimates.</strong> Describe variables in your model that might be
difficult to measure but the effects of which might be possible to
describe with calibrated-expert derived uncertainty distributions.</p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/dlUz5XT-u98" frameborder="0" allowfullscreen>
</iframe>
</div>
<div id="section-parts-5-and-6-case-studies-conclusions"
class="section level3">
<h3>Parts 5 and 6: Case Studies, Conclusions</h3>
<p>Parts 5 and 6 offer some brief Decision Analysis case studies and
conclusions. At the end of the video please take some time to revisit
your model and consider these approaches in practice. Feel free to
discuss in Slack about what application these approaches might have with
regard to your research.</p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/_Yq4E85a7xM" frameborder="0" allowfullscreen>
</iframe>
</div>
<div id="section-group-discussion-reading" class="section level3">
<h3>Group discussion reading:</h3>
<p>This week you will all read <span class="citation">Luedeling and
Shepherd (2016)</span>. The first group will lead a discussion on the
reading.</p>
<ul>
<li>Luedeling, Eike, and Keith Shepherd. “<a
href="https://www.thesolutionsjournal.com/article/decision-focused-agricultural-research/">Decision-Focused
Agricultural Research</a>.” Solutions 7, no. 5 (2016): 46–54.</li>
</ul>
</div>
<div id="section-bonus-video-by-professor-karl-claxton"
class="section level3">
<h3>Bonus video by Professor Karl Claxton</h3>
<p>Bonus: to get an economist’s perspective on the Decision Analysis
approaches watch ‘<a
href="https://www.youtube.com/watch?v=f1E3Iv8juC0">Lessons from applying
decision science in the public health sector</a>’ by Professor Karl
Claxton in the Constructing a Digital Environment Webinar Series. The
talk gets really interesting at around eight minutes in.</p>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-karl-claxton" class="tutorial-question panel-body">
<div id="question-karl-claxton-answer_container" class="shiny-html-output"></div>
<div id="question-karl-claxton-message_container" class="shiny-html-output"></div>
<div id="question-karl-claxton-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
</div>
</div>
<div id="section-define_decision" class="section level2">
<h2>Lecture 3: Defining a Decision</h2>
<!-- use the {#define_decision} syntax to create a label that can be referenced with [Define decision](#define_decision) -->
<p><img src="images/INRES_Logo.png" style="width:1in" /> <img
src="images/Uni_Bonn_Picture.png" style="width:3in" /> <img
src="images/decisionSupport_hex_sticker.png" style="width:1in" />
<!-- Neuman and Morgenstern etc. --></p>
<p>The following videos cover some of the challenges that researchers
and agricultural development experts face when attempting to define
decisions. Please watch the videos and answer the questions that
follow.</p>
<div id="section-defining-decisions-part-1" class="section level3">
<h3>Defining Decisions Part 1</h3>
<iframe width="560" height="315" src="https://www.youtube.com/embed/pPIs7MwgMe0" frameborder="0" allowfullscreen>
</iframe>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-define-decision-part-01-01" class="tutorial-question panel-body">
<div id="question-define-decision-part-01-01-answer_container" class="shiny-html-output"></div>
<div id="question-define-decision-part-01-01-message_container" class="shiny-html-output"></div>
<div id="question-define-decision-part-01-01-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-define-decision-part-01-02" class="tutorial-question panel-body">
<div id="question-define-decision-part-01-02-answer_container" class="shiny-html-output"></div>
<div id="question-define-decision-part-01-02-message_container" class="shiny-html-output"></div>
<div id="question-define-decision-part-01-02-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
</div>
<div id="section-defining-decisions-part-2" class="section level3">
<h3>Defining Decisions Part 2</h3>
<iframe width="560" height="315" src="https://www.youtube.com/embed/4vlwELJwHYg" frameborder="0" allowfullscreen>
</iframe>
<p>Think about the following questions and jot down your thoughts.</p>
<ul>
<li><strong>Does decision analysis make sense without involving a
decision-maker?</strong></li>
<li><strong>What can this achieve, and what shouldn’t we expect from
it?</strong></li>
</ul>
</div>
<div id="section-defining-decisions-part-3" class="section level3">
<h3>Defining Decisions Part 3</h3>
<iframe width="560" height="315" src="https://www.youtube.com/embed/5ZTd73gcL-0" frameborder="0" allowfullscreen>
</iframe>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-define-decision-part-03-01" class="tutorial-question panel-body">
<div id="question-define-decision-part-03-01-answer_container" class="shiny-html-output"></div>
<div id="question-define-decision-part-03-01-message_container" class="shiny-html-output"></div>
<div id="question-define-decision-part-03-01-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-define-decision-part-03-02" class="tutorial-question panel-body">
<div id="question-define-decision-part-03-02-answer_container" class="shiny-html-output"></div>
<div id="question-define-decision-part-03-02-message_container" class="shiny-html-output"></div>
<div id="question-define-decision-part-03-02-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-define-decision-part-03-03" class="tutorial-question panel-body">
<div id="question-define-decision-part-03-03-answer_container" class="shiny-html-output"></div>
<div id="question-define-decision-part-03-03-message_container" class="shiny-html-output"></div>
<div id="question-define-decision-part-03-03-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<p>Think of challenges you may encounter when trying to do
<em>credible</em>, <em>salient</em> and <em>legitimate</em> research
(all of which decision analysts should aim to achieve).</p>
</div>
<div id="section-quality-decision-making" class="section level3">
<h3>Quality Decision Making</h3>
<p>This video outlines the background for quality decision making,
closely following <span class="citation">Howard and Abbas (2015)</span>.
At the end of the video please take some time to sketch out some
thoughts about a decision that you will be working on for the
experiential part of this course. You can find the slides for the first
three parts of the lecture here.</p>
<ul>
<li><strong>Define the decision-maker</strong>: The person, organization
or group that will be faced with choices.</li>
<li><strong>Define the decision choice and alternatives</strong>: from
which to choose</li>
<li><strong>Define the preferences</strong>: clarify how the
decision-makers consider the different possible consequences and
outcomes of the decision. These can take many forms, i.e. they can be
personal, societal or cultural values.</li>
<li><strong>Define the sources of Information</strong>: What sources of
information will you access to gather a causal understanding of the
decision impact pathway. Be explicit about where you will reach out,
i.e. specific farmers, literature etc.</li>
</ul>
<!--  -->
<iframe width="560" height="315" src="https://www.youtube.com/embed/r_BbXfMbfe0" frameborder="0" allowfullscreen>
</iframe>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-quality-decision" class="tutorial-question panel-body">
<div id="question-quality-decision-answer_container" class="shiny-html-output"></div>
<div id="question-quality-decision-message_container" class="shiny-html-output"></div>
<div id="question-quality-decision-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
</div>
<div id="section-group-discussion-reading-1" class="section level3">
<h3>Group discussion reading:</h3>
<p>This week you will all read <span class="citation">Howard and Abbas
(2015)</span> (Chapter 1. Introduction to Quality Decision Making). One
group will lead a discussion on the reading.</p>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-howard" class="tutorial-question panel-body">
<div id="question-howard-answer_container" class="shiny-html-output"></div>
<div id="question-howard-message_container" class="shiny-html-output"></div>
<div id="question-howard-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
</div>
<div id="section-reading-for-this-lecture" class="section level3">
<h3>Reading for this lecture</h3>
<p>This week you will read <span class="citation">Howard and Abbas
(2015)</span> (Chapter 1. Introduction to Quality Decision Making).</p>
<ul>
<li>Howard, Ronald A., and Ali E. Abbas. Foundations of Decision
Analysis. NY, NY: Prentice Hall, 2015.</li>
</ul>
</div>
</div>
<div id="section-case_studies" class="section level2">
<h2>Lecture 4: Decision Analysis Case Studies</h2>
<!-- reference with [Decision Analysis Case Studies](#case_studies) -->
<p>Welcome to lecture 4 of <strong>Decision Analysis and Forecasting for
Agricultural Development</strong>. In this lecture we will talk about
case studies and use the <code>#lecture-04-case-studies</code> Slack
channel and Zoom meeting to follow up. This will allow us all to have a
chance to see your progress, provide feedback. As always, your
engagement and sharing is appreciated. It will be encouraging to others
to see activity from colleagues. Feel free to bring up any questions or
concerns in the Slack or to <a
href="mailto:cory.whitney@uni-bonn.de?subject=%5BSeminar_2%5D%20Decision%20Analysis%20Lecture">Dr. Cory
Whitney</a> or the course tutor.</p>
<p>Please take a few minutes to watch these short videos and do the
associated exercises before our meeting.</p>
<div id="section-introduction-2" class="section level3">
<h3>Introduction</h3>
<p>The following videos introduce some decision analysis case studies.
Please watch the videos and answer the questions that follow.</p>
</div>
<div id="section-decision-analysis-case---water-for-wajir"
class="section level3">
<h3>Decision analysis case - Water for Wajir</h3>
<p>The city of Wajir in Northern Kenya has lacks a reliable supply of
clean drinking water and sanitation. To improve the situation, plans are
being considered to construct a water pipeline from Habaswein over 100
km away <span class="citation">(Luedeling and Leeuw 2014; Luedeling et
al. 2015)</span>. Watch the following video to learn more.</p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/imQ1Gn-E7wQ" frameborder="0" allowfullscreen>
</iframe>
<p>Now try to answer the following questions:</p>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-1-Decision-analysis-case-Water-for-Wajir" class="tutorial-question panel-body">
<div id="question-1-Decision-analysis-case-Water-for-Wajir-answer_container" class="shiny-html-output"></div>
<div id="question-1-Decision-analysis-case-Water-for-Wajir-message_container" class="shiny-html-output"></div>
<div id="question-1-Decision-analysis-case-Water-for-Wajir-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-2-Decision-analysis-case-Water-for-Wajir" class="tutorial-question panel-body">
<div id="question-2-Decision-analysis-case-Water-for-Wajir-answer_container" class="shiny-html-output"></div>
<div id="question-2-Decision-analysis-case-Water-for-Wajir-message_container" class="shiny-html-output"></div>
<div id="question-2-Decision-analysis-case-Water-for-Wajir-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-3-Decision-analysis-case-Water-for-Wajir" class="tutorial-question panel-body">
<div id="question-3-Decision-analysis-case-Water-for-Wajir-answer_container" class="shiny-html-output"></div>
<div id="question-3-Decision-analysis-case-Water-for-Wajir-message_container" class="shiny-html-output"></div>
<div id="question-3-Decision-analysis-case-Water-for-Wajir-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
</div>
<div
id="section-case-study---plastic-covers-in-sweet-cherry-orchards-in-chile"
class="section level3">
<h3>Case study - Plastic covers in sweet cherry orchards in Chile</h3>
<p>This video shows the study <span class="citation">Rojas et al.
(2021)</span> conducted in Chile for assessing the profitability of
implementing plastic covers in sweet cherry orchards to protect the
fruits from hazardous weather events.</p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/kpsqzkeg53Y" frameborder="0" allowfullscreen>
</iframe>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-sweet_cherry-1" class="tutorial-question panel-body">
<div id="question-sweet_cherry-1-answer_container" class="shiny-html-output"></div>
<div id="question-sweet_cherry-1-message_container" class="shiny-html-output"></div>
<div id="question-sweet_cherry-1-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<p>Based on the question above, think about and write down two to three
positive and negative implications of using the method we used to define
the decision.</p>
<div class="panel panel-default tutorial-question-container">
<div data-label="question-sweet_cherry-2" class="tutorial-question panel-body">
<div id="question-sweet_cherry-2-answer_container" class="shiny-html-output"></div>
<div id="question-sweet_cherry-2-message_container" class="shiny-html-output"></div>
<div id="question-sweet_cherry-2-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<div class="panel panel-default tutorial-question-container">
<div data-label="questio-sweet_cherry-3" class="tutorial-question panel-body">
<div id="questio-sweet_cherry-3-answer_container" class="shiny-html-output"></div>
<div id="questio-sweet_cherry-3-message_container" class="shiny-html-output"></div>
<div id="questio-sweet_cherry-3-action_button_container" class="shiny-html-output"></div>
<script>if (Tutorial.triggerMathJax) Tutorial.triggerMathJax()</script>
</div>
</div>
<p>The data and scripts for this study are also available online <span
class="citation">(Fernandez et al. 2021)</span>.</p>
</div>
<div id="section-group-discussion-reading-2" class="section level3">
<h3>Group discussion reading:</h3>
<p>This week you will all read <span class="citation">Shepherd et al.
(2015)</span>.</p>
<ul>
<li>Shepherd, Keith, Douglas Hubbard, Norman Fenton, Karl Claxton, Eike
Luedeling, and Jan de Leeuw. “Development Goals Should Enable
Decision-Making.” Nature 523, no. 7559 (2015): 152–54.</li>
</ul>
</div>
<div
id="section-bonus-decision-analysis-case---calluna-production-in-nrw"
class="section level3">
<h3>Bonus: Decision analysis case - Calluna production in NRW</h3>
<p>Heather growers and other stakeholders in North Rhine-Westphalia,
Germany are looking for sustainable options to manage disease outbreaks.
<span class="citation">Ruett, Whitney, and Luedeling (2020)</span>
worked with these farmers to model the impacts of changing disease
management practices and to generate comprehensive forecasts of net
returns. Watch the following video to learn more.</p>
<p><img src="https://www.youtube.com/watch?v=hvnhjrf1Ims" /></p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/hvnhjrf1Ims" frameborder="0" allowfullscreen>
</iframe>
<p>Think about the following questions and jot down your thoughts.</p>
<ul>