QUANTIFYING THE EFFECTIVENESS OF PUBLIC MEETINGS TO
GENERATE PUBLIC PARTICIPATION IN WATERSHED MANAGEMENT
by
Jennifer Kingsley
A thesis submitted in partial fulfillment of the requirements of the degree
MASTER OF SCIENCE IN NATURAL RESOURCES
Waters Emphasis
UNIVERSITY OF WISCONSIN
Stevens Point, Wisconsin
May 2008
ii
ABSTRACT
Public involvement has been identified as one of the key aspects of successful
watershed management by professionals and researches in the field and is particularly
important in the initial phases of management. In the Little Plover River Watershed,
in central Wisconsin, stakeholders expressed a need to initiate watershed management.
At this early stage in the process public involvement is seriously lacking. The goal of
this study was to assess the effectiveness of public meetings to determine if public
informational meetings increase a meeting attendee’s willingness to participate in
future watershed management activities. A series of eight public informational
meetings about the Little Plover River were hosted by several community
organizations. A survey was developed to gauge respondent knowledge, behaviors,
and demographics. At four of the meetings a survey was given to the respondent
prior to the meeting. At four other meetings, the survey was given out after the
meeting. A random sampling of the public not attending a meeting was used for a
comparison. The study found that meeting attendees had a better understanding of
watershed concepts then the public. Post-meeting respondents were better able to
identify current issues within the Little Plover River Watershed. It was also found
that pre-meeting respondents were more willing to participate in planning for future
watershed management then post-meeting respondents were. Overall the public
meetings served as a good source of information and education but were not effective
at generating increased public participation in planning for watershed management.
iii
Understanding the effectiveness of public informational meetings is critical for
planners and managers that must use public participation methods for management
but have time and budget constraints that force them to choose only the public
participation methods they feel will provide the biggest outcome.
iv
ACKNOWLEDGEMENTS
This project would not have been possible without the assistance of many
people. First and foremost I would like to thank my advisor, Dr. Katherine Clancy,
for her support, contribution, and commitment to this project. Without her, this
project would have only ever been a dream. I would also like to thank Dr. George
Kraft and Dr. Anna Haines for their continued support and interest in this project.
My husband, Matt, was with me from the beginning of this project always
providing a helping hand and much needed support whenever it was needed. Thanks
to his love and encouragement along the way. A big thank you also goes out to my
entire family for their love, encouragement, support, and editing talents on this
project.
v
TABLE OF CONTENTS
ABSTRACT.....................................................................................................................III
ACKNOWLEDGEMENTS ............................................................................................ V
LIST OF TABLES AND FIGURES...........................................................................VIII
INTRODUCTION............................................................................................................. 1
LITERATURE REVIEW ................................................................................................ 2
Watershed Management ..............................................................................................................................2
Watershed Management Strategies .............................................................................................................3
Public Participation .....................................................................................................................................5
Forms of Public Participation......................................................................................................................6
Evaluating Public Participation .................................................................................................................10
Use of Evaluation ......................................................................................................................................13
Public Participation in Wisconsin .............................................................................................................14
Conclusion.................................................................................................................................................15
METHODOLOGY ......................................................................................................... 16
Objectives..................................................................................................................................................16
Site Description .........................................................................................................................................16
Experimental Design .................................................................................................................................18
Meetings ................................................................................................................................................18
Surveys ..................................................................................................................................................20
Question Types .......................................................................................................................................21
Answer Types..........................................................................................................................................22
Survey Questions ....................................................................................................................................23
Pilot Testing ...........................................................................................................................................30
Sampling Methods.....................................................................................................................................30
ANALYSIS ...................................................................................................................... 33
Demographic Data.....................................................................................................................................33
Spearman Rank-Order Correlation.......................................................................................................34
Knowledge ................................................................................................................................................36
Chi-Square Test......................................................................................................................................37
Mann-Whitney U Test.............................................................................................................................39
Behaviors...................................................................................................................................................42
RESULTS ........................................................................................................................ 44
Section A – Background Knowledge ........................................................................................................44
Section B – Actions and Behaviors ...........................................................................................................51
Section C – Demographic Information......................................................................................................60
Survey Revisions and Results ...................................................................................................................67
vi
DISCUSSION .................................................................................................................. 71
Objective 1 ................................................................................................................................................71
Objective 2 ................................................................................................................................................78
Objective 3 ................................................................................................................................................82
Additional Data .........................................................................................................................................87
Overall Findings........................................................................................................................................91
Improvements to Study .............................................................................................................................91
Impacts on Public Participation.................................................................................................................93
LITERATURE CITED .................................................................................................. 96
APPENDICES ............................................................................................................... 100
A.
B.
C.
D.
E.
F.
G.
H.
I.
J.
K.
L.
M.
N.
O.
P.
Q.
Survey..............................................................................................................................................100
Chi-Square Test for question a-1 .....................................................................................................107
Mann-Whitney U Test for question A-2 ..........................................................................................110
Mann-Whitney U Test for question A-4..........................................................................................121
Respondent’s Rankings for question A-5........................................................................................124
Respondent’s rankings for question A-6 .........................................................................................129
Chi-Square Test for question B-3 ....................................................................................................131
Chi-Square Test for question B-4 ....................................................................................................133
Spearman Rank-Order Correlation Test for willingness to Donate
and willingness to participate ..........................................................................................................136
Spearman Rank-Order Correlation Test for respondent income and
WILLINGNESS TO PARTICipate...........................................................................................................139
Spearman Rank-Order Correlation Test for respondent income and
willingness to participate..................................................................................................................142
Spearman Rank-Order Correlation Test for respondent age and
willingness to participate..................................................................................................................145
Spearman Rank-Order Correlation Test for respondent residence and
willingness to participate..................................................................................................................148
Spearman Rank-Order Correlation Test for respondent education and
willingness to participate..................................................................................................................151
Spearman Rank-Order Correlation Test for respondent income and
willingness to donate........................................................................................................................154
Chi-Square Test for revised question A-3 .......................................................................................157
Chi-Square Test for revised question B-3........................................................................................160
vii
TABLES AND FIGURES
FIGURE
1. Ladder of public participation ..............................................................................................................7
2.
Gender demographics of survey respondents ....................................................................................61
3.
Age demographics of survey respondents .........................................................................................62
TABLE
1.
Watershed Management Unit Characteristics .....................................................................................4
2.
Community organizations sampled and size of sample.....................................................................20
3.
Example of survey codes used on each survey question ...................................................................31
4.
Example of Spearman-Rank Correlation Data and calculation.........................................................35
5.
Example of Chi-Square Test calculation...........................................................................................39
6.
Example and rank of survey responses for question A-5 and A-6.....................................................41
7.
Results of Chi-Square analysis for question A-1...............................................................................45
8.
Results of Chi-Square analysis for question A-3...............................................................................49
9.
Ranked responses of survey respondent groups for question A-5.....................................................50
10. Ranked responses of survey respondent groups for question A-6.....................................................51
11. Percentage of pre-meeting responses regarding how often respondents participated in
the listed activities ..........................................................................................................................52
12. Percentage of post-meeting responses regarding how often respondents participated in
the listed activities .............................................................................................................................53
13. Percentage of public responses regarding how often respondents participated in the
listed activities...................................................................................................................................54
14. Percentage of pre-meeting respondent’s answers to question B-2 ....................................................55
15. Percentage of post-meeting respondent’s answers to question B-2 ..................................................55
16. Percentage of public respondent’s answers to question B-2 .............................................................56
17. Survey respondent’s willingness to participate .................................................................................56
18. Results of Chi-Square analysis for question B-3...............................................................................58
19. Survey respondent’s willingness to donate money towards watershed management........................58
20. Results of Chi-Square analysis for question B-4 ...............................................................................60
viii
21. Survey respondent’s employment status ...........................................................................................63
22. Survey respondent’s occupational status ...........................................................................................63
23. Survey respondent’s annual income ..................................................................................................64
24. Survey respondent’s home ownership...............................................................................................64
25. Survey respondent’s residence within the Little Plover River watershed .........................................64
26. Survey respondent’s distance of residence from the Little Plover River watershed..........................65
27. Spearman Rank-Order Correlation between survey respondent’s demographics and willingness
to participate in future watershed management activities..................................................................66
28. Results of Chi-Square analysis for revised question A-3 ..................................................................68
29. Survey respondent’s willingness to participate with revised categories............................................69
30. Results of Chi-Square analysis for revised question B-3 ..................................................................69
31. Survey respondent’s willingness to participate in future watershed management ............................78
32. Survey respondent’s willingness to participate with revised categories............................................80
33. Age demographics of survey respondent’s and Portage County residents ........................................90
ix
INTRODUCTION
Watershed management is the management of natural resources based on
naturally occurring, hydrologically defined boundaries. This type of management
includes the consideration of a wide variety of physical and social variables,
including the public who have a vested interest in the watershed (Sabatier et al, 1999).
Past management efforts have illustrated the important role that the public plays.
Without their acceptance and active participation, management efforts often fail
(Nature, 2000). Public participation begins with knowledge and understanding of the
watershed, the water resources, and the issues that the watershed faces. If the public
has this knowledge it can in turn increases a watershed's value in the public eye
(Council of State Governments, 1999). Without establishing a watershed's value we
cannot expect voluntary cooperation from the public in management efforts.
Public participation has been recognized as such an integral part of the success
of watershed management that it is often required in order to receive funding. The
Environmental Protection Agency, one of the top watershed funding sources, requires
public participation components in both its Section 319 Grants and Targeted
Watersheds Program.
Hundreds of watersheds throughout the United States face an uncertain future
due to the lack of public participation such as the Little Plover River, in central
Wisconsin. Surface water discharges are diminishing and the public has expressed
the need for watershed management but the process has stalled due to the lack of
public involvement.
1
LITERATURE REVIEW
Watershed Management
Geographer and scientist John Wesley Powell defined a watershed as an “area
of land, a bounded hydrologic system, within which all living things are inextricably
linked by their common water course and where as humans settled, simple logic
demanded they become a part of the community” (U.S. EPA, 2002). This definition
not only serves as a definition of a watershed, but also highlights the principles of
watershed management.
Watersheds, also referred to as drainage basins, are simply an area of land that
captures water in any form and drains it to a body of water (DeBarry, 2004). They are
determined naturally by geology, soil type, and topography and therefore transcend
political and regulatory boundaries. Watersheds acknowledge the connections
between ground and surface water, upstream and downstream areas, and land and
water interface. They provide us with a unique, comprehensive scale on which to
manage our water resources.
Watershed management is the integration, coordination, and management of
human activities within the natural boundaries of a watershed to protect or improve
water quality (Reimold, 1998). The National Research Council (1999) calls
watershed management “an integrative way of thinking about all the various human
activities that occur on a given area of land (the watershed) that have effects on, or
are affected by, water.”
2
3
Managing water resources on a watershed scale is not a new concept globally.
Indo-Europeans and ancient Egyptians developed complex plans for land
management that included water management methods based on natural watershed
boundaries. In ancient Himalaya, village boundaries were determined by natural
hydrological boundaries (ICS, 1999). In the United States, the watershed concept was
first recognized and became accepted between 1880-1924. It was during this time
that John Wesley Powell urged congress to divide the west into districts that
corresponded to natural drainage patterns (Sabatier, Weible, Flicker, 2005). During
this time Theodore Roosevelt also observed that “every river system, from its
headwaters in the forests to its mouth at the coasts, is a single unit and should be
managed as such” (U.S. Inland Waterways Commission, 1908).
Throughout history, American citizens have demanded economic
development while seeking progress in environmental protection and restoration,
something that can only be accomplished through the integration of ecological,
economic, and social approaches. Watershed management has proven to be one
method for addressing these needs.
Watershed Management Strategies
The process of watershed management includes three basic steps: watershed
assessment, developing a management plan, and implementation of the plan. This
process has been described as assembling a puzzle (DeBarry, 2004). Watershed
assessment collects the biological, physiographic, hydrologic, hydraulic, political and
social puzzle pieces.
4
The watershed management plan takes all of the pieces and puts them together and
implementation of the plan preserves the puzzle and keeps the puzzle from falling
apart (DeBarry, 2004). Beyond this basic framework, there is no consensus on what
the essential components of watershed management should be (Reimold, 1998).
The strategies used in watershed management often vary from watershed to
watershed. Each watershed is unique and must be explored so that specific strategies
can be chosen to meet the management goals. Two of the most recognizable
management strategies are watershed zoning and best management practices
(Reimold, 1998). DeBarry (2004) adds source water identification and protection,
minimizing discharges, managing stormwater, land use regulations, and growth
management to the list of common strategies.
Schueler (1995) goes even further to break a watershed into five units and
outlines the management focus or strategy for each of them (Table 1).
Table 1.Characteristics that define specific watershed management units (Schueler,
1995).
Watershed
Management
Unit
Catchment
Typical area,
mi2
Influence of
impervious cover
Primary planning
authority
Management
Focus
0.05-.50
Very Strong
Subwatershed
1-10
Strong
Property Owner
(local)
Local
government
Watershed
10-100
Moderate
Subbasin
100-1000
Weak
BMP and site
design
Stream
classification and
management
Watershed based
zoning
Basin Planning
Basin
1000-10000
Very Weak
Local or multilocal government
Local, regional,
or state
State, multi-state,
or federal
Basin Planning
5
The U.S. Environmental Protection Agency developed a Watershed Approach
Framework which was “a coordinating framework for environmental management
that focuses public and private sector efforts to address the highest priority problems
within hydrologically-defined geographic areas, taking into consideration both
ground and surface water flow” (U.S. EPA, 1996) and has served as the guide for
watershed approaches throughout the U.S.
The EPA framework realizes that the individual watershed approach objectives,
priorities, elements, and resources will all be different but they should be based on
three guiding principles:
1) Strategies are conducted at a specific geographic focus;
2) Strategies utilize sound management techniques based on strong science and
data; and,
3) Strategies involve those individuals who are most affected by management
decisions.
Public Participation
Of the EPA principles, watershed managers often struggle with involving the
public who will be affected by the management (Duram and Brown, 1999.) The basis
for involving the public in the watershed management process is that it will help them
understand the problems, identify and buy into goals, select priorities, and choose and
implement the solutions (EPA, 1995; Reimold, 1998; DeBerry, 2004; Sabatier et al.,
2005).
In the past the government attempted to solve problems alone, through a topdown approach.
6
This was often met with resistance from those who lived, worked, or recreated within
the area. Private individuals who embarked on management alone often did not have
enough time or resources. It is with the combination of these parties that a successful
collaborative effort can be achieved that meets the goals and objectives of all.
Without support, trust, and participation from the public, management efforts
will not be as effective (Nature, 2000; Kerr, 1999). It is widely accepted among
professionals in the field that the public needs to be included in management efforts
(Wondolleck and Yaffee, 2000; Nature, 2000; and Webler and Tuler, 2001). Glicken
(1999) reasons that public participation enhances a decision making process because
information from the public provides a holistic view of issues, public involvement
creates legitimacy, and public involvement upholds democratic ideals. She stresses
that the public is not the decision maker, but rather there to provide input which helps
create a well-balanced, sound plan.
Over the years there has been a greater understanding of the need for public
involvement in management. Managers and planners have seen the increasing value
of the information and perspectives that the public is able to bring to the management
process.
Forms of Public Participation
Choosing exactly how to involve the public can be a difficult task. However,
before any method of participation is chosen an understanding of how citizens
become involved is necessary. There is a clear progression in the levels of
participation that the public goes through.
7
Arnstein (1969) first described a “ladder of citizen participation”(Figure 1). The
principle behind the participation ladder is that citizens start at the bottom of the
ladder in levels of “shallow participation”. At this rung managers and planners are
imparting information to the public, but there is no feedback or discussion. The
second rung of participation is described as “degrees of tokenism”, in which
managers and planners are still imparting education and information to the public, but
the public is also providing feedback and discussion. Higher rungs move into
increasing “degrees of citizen power”. This is the highest level of citizen
participation. At this level information is not only being exchanged, as well as
discussion and feedback, but citizens are also involved in the decision making process.
The ladder describes a progression of citizen participation because participants start at
the bottom and work their way through each level until they reach the top (Arnstein,
1969).
Figure 1. The ladder of citizen participation (Arnstein, 1969).
citizen control
delegated power
Degrees of
Citizen Power
partnership
placation
Degrees of
Tokenism
consultation
informing
therapy
manipulation
Shallow
Participation
8
The International Association of Public Participation (IAP2) has a similar
ladder of public participation, but it is instead called the “Spectrum of Public
Participation”. IAP2’s spectrum is laid out horizontally, instead of vertically and
citizens start at the inform level and move through consulting, involvement,
collaborating, and finally into empowering. While the levels may be different, the
principal behind each is the same (IAP2, 2007).
While the ladder and spectrum of public participation are relatively well
understood and accepted by professionals, it can be difficult to determine which
specific methods of public participation should be used at various ladder rungs or fall
within the spectrum. Methods of public participation are extremely varied in their
approaches and results. In 1998, a mail survey of 126 federally funded watershed
planning initiatives throughout the U.S. identified newsletters, public meetings, and
informational programs were being used by 75% or more of the respondents.
Pamphlets, door-to-door contact, surveys, and videos were also being widely used,
but to a lesser degree. When respondents were asked what they felt was most
effective, door-to-door contact and informational programs were identified (Duram
and Brown, 1999).
Griffin (1999) wrote a paper that outlined watershed councils as an emerging
form of public participation in western states. These councils are composed of
governmental and non-governmental stakeholders that come together to make
management decisions. Mullen and Allison (1999) outlined several public
participation efforts that were making a difference in Alabama, including the
Alabama Water Watch Initiative.
9
The Alabama Water Initiative includes a volunteer education program in water
resources management, locally led non-point source watershed re-assessments, and
continuing public meetings. Konisky and Beierle (1999) identified three very unique
public participation processes that were being used in the Great Lakes region. These
included study circles, citizen juries or meetings that bring together a statistically
representative sample of citizens to deliberate on technically complex issues, and
round tables.
In 2002, Pierce County Washington used a combination of focused discussion
groups, committees, issue workshops, and public meetings to gain the needed public
support and feedback for a watershed plan that was being developed (Smolko,
Huberd, and Tam-Davis 2002). In the Illinois River Basin, a unique new tool was
created to facilitate public participation in watershed management. A baseline impact
study was conducted and findings were integrated into a computer-based decision
support tool: an interactive, multimedia, impact visualization platform called the
Watershed Management Decision Support System. Aerial and ground photography
was obtained and combined with Geographic Information Systems base maps to
create a background for the visualizations. These backgrounds were then overlaid
with the assessments and animated to produce visual images that simulated impacts
(Meo, et al. 2002). It was also during this time that sixteen planning regions in Texas
had to develop a water plan for the needs of each individual region due to serious
drought issues.
10
In the South Central region, a large focus was placed on developing public
participation through public meetings, audience surveys, and multiple forms of
communication including brochures, newspaper articles, presentations, fact sheets,
and newsletters (Moorhouse and Elliff, 2002).
Webler and Tuler (2001) choose to take a different route. Instead of
identifying specific public participation methods they thought were effective, they
instead highlighted key characteristics that make for a “good” public participation
method. They explained that any public participation method that is credible,
legitimate, competent, information driven, fosters fair democratic deliberation, and
emphasizes constructive dialogue and education should be considered a good public
participation method. Webler and Tuler developed this list after surveying watershed
management planners and activists about what they believed constituted a good
public participation method (Webler and Tuler 2001).
Evaluating Public Participation
It is important for people leading the management process to understand the
“effectiveness”, merit or worth of different participation processes (Chess, 2000).
Evaluation can help determine when and where to use public participation processes,
address criticisms, and help to refine the process and theories for future use (Conley
and Moote, 2003). However, determining what constitutes “effective” is difficult
since there have been no definitive benchmarks to compare different public
participation methods. Efforts to evaluate different methods of public participation
can be divided into categories.
11
Outcome vs. Process
There are those who evaluate public participation based on the outcome of the
method and those who evaluate the process. Process goals are evaluated based on
characteristics of the process (Chess and Purcell, 1999).
Duram and Brown (1999) evaluated public participation based on process
characteristics.
They identified five factors that can influence the effectiveness of
the public participation process. These include:
•
The approach to management: whether bureaucratic or grass-roots,
•
Fourteen different planning stages that can include public participation and
whether they include participation throughout or selectively,
•
Methods to solicit participation; either one way communication or two-way
communication,
•
The level of participation; whether participation is direct or indirect, and
•
The potential positive impacts of participation on watershed.
They claim that a process and its success can be evaluated based on these criteria.
Outcome evaluations are often done by comparing goals of a public
participation method to the success of the result. What is considered successful varies.
Some say that social outcomes such as increased understanding and improved
relationships determine success (Buckle and Thomas-Buckle 1986). Others say that
the ultimate measure of success is whether the effort leads to improved environmental
conditions (Kenney, 1999). Still others stress that it is important to evaluate all of
these outcomes (Innes, 1999).
12
The idea of evaluating based on outcomes can be problematic because there is
no way to determine if the outcome was due specifically to public participation or
other variables (Chess and Purcell 1999). For example, there may be simultaneous
events taking place that can influence the process of public participation, the group of
people involved or where the process is taking place may have an effect, or even the
type of problem that is trying to be solved could have an effect.
Theory vs. User
Some feel that criteria for evaluating public participation methods should
come from theories or from the users themselves. Webler (1995) developed a
framework for public participation based on theory. In this framework he argues that
evaluation should be based on “fairness” the ability for people to communicate,
interact, dialogue, challenge and defend; “Competence” uses the best information
available; and “right discourse” using multiple communication methods. These serve
as normative criteria that can be applied universally to public participation processes.
Others choose to evaluate based on participant’s goals and satisfaction. In this
method the goals and satisfaction of the participants are what dictate the success of
the process (Chess and Purcell 1999). Wondolleck and Yaffee (1994) used this
process in the exploration of U.S. Forest Service efforts. They asked personnel to
reflect on successful situations, decide what made them successful, and then construct
a definition of success based on that.
Blended
Still others think that evaluating public participation should combine all of the
above methods.
13
Chess and Purcell (1999) advocate for evaluation based on “methodological
pluralism”. They suggest that researchers of public participation should solicit from
participants their expectations and criteria for success, compare it to theory, and then
synthesize the outcomes.
In response to Chess and Purcell, Rowe and Frewer (2000) developed what
they consider to be a comprehensive framework for evaluation. They evaluated
multiple public participation methods based on two categories; acceptance criteria,
which evaluates the construction and implementation of the process, and process
criteria, which evaluates the public acceptance of the process. Acceptance Criteria
includes representativeness of the public, independence of the process, early
involvement of the public, influence of the procedure on policy, and transparency of
the process to the public. Process Criteria includes resource availability to public
participants, definition of tasks for public participants, structured decision-making,
and cost-effectiveness.
Use of Evaluation
Interest in evaluating public participation methods is widespread among the
different parties involved in management, but motivations for evaluation vary.
Participants want to evaluate their efforts so they can make improvements and meet
their goals. Managers and planners use evaluations as guidelines to determine which
methods of public participation may be most appropriate for them. Policymakers
want evaluations to help them formulate rules and regulations.
14
Advocates use evaluations to prove their success while critics use them to prove that
their concerns are well-founded (Innes, 1999 and Coglianese, 1999). Ultimately, we
look to evaluations to provide us with three things:
1.) The ability to determine when public participation works;
2.) The ability to address criticisms; and,
3.) The ability to refine methods.
It is through evaluation of public participation efforts that evaluators are
beginning to realize that public participation can, but does not always, work and when
it fails it comes at a potentially heavy cost (Conley and Moote, 2003).
Public Participation and Evaluation in Wisconsin
It is widely accepted that public participation is critical to watershed
management; however, the field is still extremely new.
Many researchers identify additional research into the effectiveness of public
participation as a great need (Margerum and Born 1999). This is especially true on
the local and state scales where many of the theories have not yet been tested,
including Wisconsin.
Without knowing what methods are in use, it’s impossible to determine their
effectiveness. Konisky and Beierle (2001) focused on the Great Lakes Region in
their study of “innovative” participation processes. Duram and Brown (1999), in
their survey of public participation methods in watershed planning initiatives, used a
spatial distribution that focused primarily on the Midwest but no direct focus on
Wisconsin.
15
Margerum and Born (1995) highlighted two planning processes in Wisconsin, but did
not delve deeply into what public participation methods were being used.
Conclusion
Public participation has been shown to be an integral part of the watershed
process. Not only is it desirable, but often mandated. Public participation processes
often vary as do their effectiveness. Watershed managers in Wisconsin need to have
a better understanding of how public participation processes are affecting the
watershed management process within our own state.
They need to identify what processes are being used and to what extent, as well as
evaluating how effective they have been. There is a demonstrated need for this
knowledge on state and local levels. Without this information, watershed managers
within the state may struggle to form integrative public participation processes that
represent all perspectives within a watershed.
METHODOLOGY
Objectives
This study was designed to use the Little Plover River Watershed in Plover,
Wisconsin as an example to assess the initial phase of public engagement, the public
informational meeting, as a form of public participation in watershed management.
The goal of this study was to determine if public informational meetings are an
effective form of public participation. Three objectives were identified that would
serve as a measure of the goal:
1) Determine if public informational meetings increase an attendee’s knowledge
about the Little Plover River;
2) Determine if public informational meetings increase an attendee’s willingness
to participate in future watershed management activities; and
3) Determine if there are significant differences in knowledge and actions
between those who attend the public informational meetings and those who do
not.
Site Description
The focus of the public informational meetings was on the Little Plover River
Watershed. The Little Plover River runs southeast of the city of Stevens Point, in
Portage County, Wisconsin.
16
17
Primary land uses within the watershed are irrigated vegetable farming, forested land,
and residential areas. The Little Plover River is a groundwater fed stream with cold
water that supports a Class 1 Trout fishery.
The Little Plover River gained public notice when stretches of the river ran
dry in the summers of 2005 and 2006, which is something that had never happened
before, even in extreme drought situations according to historical and anecdotal
evidence. The causes of the low-flow situations are still under investigation, but
evidence strongly suggests that agricultural and municipal groundwater withdrawal
has affected the flow regime.
Due to the river drying up, the public urged for management of the river and
the watershed. A workgroup of watershed stakeholders was assembled, which
included members of state and local government, agriculture, environmental groups,
and some concerned citizens.
During the times when stretches of the river ran dry, articles providing
information about the situation were published in the Stevens Point Journal and
Portage County Gazette, two local newspapers. These articles were meant to make
the public aware of what was happening with the Little Plover River, as well as
provide basic information and invite them to become involved.
Discussions of possible management options for the Little Plover River
Watershed have just begun. Participation from the public in the stakeholder
workgroup and management discussion has declined over the last year.
18
This river and its watershed will serve as a case study to assess the effectiveness of
public informational meetings to generate additional public participation in planning
for the management of the Little Plover River.
Experimental Design
A series of eight public informational meetings about the Little Plover River
Watershed were held throughout the Stevens Point community and surrounding area.
At four of these meetings attendees received a survey prior to the start of the meeting.
At four other meetings attendees received a survey after the meeting was completed.
The survey was also administered to a random sample of public who did not attend
any of the meetings.
Surveys conducted before and after the meeting, as well as the random
sampling of the public were compared to determine if the public informational
meeting had an effect on the knowledge, attitudes, values, and perceived future
behaviors of the meeting attendees.
Meetings
Public informational meetings were chosen for evaluation because they are
one of the most widely used forms of public participation (Duram & Brown, 1999)
and because of where they fall on the scale of public participation. Public
informational meetings fall in the category between information and education and
higher levels of involvement in public participation, indicating that they may be one
of the key methods of participation that is able to bring a participant from lower
levels of participation into higher levels, something that watershed managers and
planners strive for, but ultimately struggle with (IAP2, 2007).
19
The series of eight public informational meetings were offered in the fall and
winter of 2007. Each meeting lasted approximately 45 minutes and covered the
following information:
-
Introductory information about the water cycle, watersheds, and groundwater
-
Background information about the Little Plover River and its watershed; location,
uses, historic and current flows
-
Current issues facing the Little Plover River
-
Current research on the Little Plover River and the findings
-
Possible future scenarios for the Little Plover River
These meetings were presented to eight established community organizations
instead of hosting open public meetings. Presenting to established community
organizations guaranteed attendance at each of the eight meetings and ensured a
large enough sample size for statistical analysis. The established community
organizations also allowed control of a potential source of bias. People who attend
open public meetings may already have a vested interest in the subject matter and
usually have preconceived ideas and opinions when coming to the meeting. By
using the community organizations, individuals attending may or may not have
preconceived ideas and opinions.
Each community organization that was chosen for a presentation had meetings
that were open for the general public to attend. Each meeting was scheduled and
advertised in advance to allow people with an interest in the subject matter to attend.
20
A variety of different organizations were chosen for the meetings so that a wide array
of demographics, knowledge of the Little Plover River, and actions could be sampled.
The eight community organizations that were given a presentation and sampled are
found in Table 2.
Table 2. Community Organizations Sampled and Size of Sample.
Pre-Meeting Survey
Post-Meeting Survey
Random Survey
Soil and Water Conservation
Rotary Club of Stevens
Amherst County Fair
Society
Point
n=13
n=21
n=5
Members of the University of
Stevens Point Kiwanis
Stevens Point Harvest
Wisconsin-Stevens Point
Club
Fest
Library
n=10
Public Meeting
n=5
General Federation of
Women’s Clubs
Leadership Portage County
n=15
n=4
n=20
Downtown Stevens Point
n=6
n=17
Environmental
Educations and
Naturalists Association
n=9
Survey
Surveys were used as the method to gather information from respondents.
Surveys were an appropriate method of gathering information because the
information being collected regards a respondent’s personal knowledge, actions,
behaviors, and demographics (Fink & Kosecoff, 1998).
A written survey was given to each meeting attendee and they were asked to
complete them on site to ensure high rates of return. At four of the meetings the
survey was handed out and completed prior to the meeting starting. At four other
meetings the survey was handed out and completed following the meeting.
21
A random sampling of the public who had not attended a meeting was also required
for comparison. Random surveys were administered at three different locations; the
Amherst County Fair, downtown Stevens Point and the Stevens Point Harvest Fest.
These sample sites allowed for a wide variety of survey respondents who were able to
complete the survey at their leisure.
Convenience samples were used as the sampling method for the surveys.
Samples could only be obtained from those organizations that were willing to
participate in the informational programs and the survey. The random sample of the
public was also a convenience sample, only people who were willing to the complete
the survey did. This type of survey samples has the potential to introduce sources of
bias. Potential bias may include: public respondents who choose to fill out the survey
are more interested in the topic than others, respondents at the already established
meetings may have never chosen to attend an open public meeting on the subject, and
still other respondents may feel the need to exaggerate in the survey.
The survey design is a comparison group design. The control group is the
random sample of the public that was surveyed and the two treatment groups are the
pre-meeting and post-meeting survey respondents. This design is standard in the
social science research when two groups must be compared before and after a
treatment.
Question Types
A variety of different question types were used in the surveys.
22
Seventy-five of the seventy-seven questions asked were forced choice questions,
meaning that survey respondents are presented with a statement, question, or situation
followed by several alternative choices or solutions that they are able to choose from.
This ensures ease of use for survey respondents as well as reliable uniform data for
analysis. When using forced choice questions there are rules that must be followed.
These include:
1) Each question should pertain to the respondent’s own personal experiences,
knowledge, background etc
2) Questions were written using lay language and colloquial wording, for ease of
understanding by respondents of all backgrounds
3) Questions should be concrete
4) Avoid biased words and phrases
5) Check your own bias
6) Use caution when asking about the personal
(Fink & Kosecoff, 1998)
The two questions that are not forced choice are open-ended questions. They
both ask for a specific numeric amount that relates to them personally. These are not
answers that would be possible to bin or separate into categories.
Answer Types
When using forced choice questions there are several different forms of answers.
The first form of answer used was checklist answers. The respondent was provided
with a checklist of answers from which they must choose one or more depending on
the instructions. The other form of answer that was used was scale answers.
23
With scales, the respondent places their answer at some point along a continuum or in
an ordered series of categories. There are four basic types of scales.
These include:
1) Nominal. Nominal scales can also be referred to as categorical scales because
respondents give answers based on a group to which they belong: gender, age,
schooling, etc.
2) Ordinal. Ordinal scales require respondents to place answers in a rank order.
A measure of how strongly a person felt about a statement from strongly
agreeing to strongly disagreeing is an example of an ordinal scale.
3) Interval. In the interval scale the distance between numbers has meaning,
such as the distance between the values of annual income levels.
4) Ratio. A ratio scale has adjoining units that are equidistant from each other,
meaning that you are able to draw comparisons between two values. Surveys
rarely utilize ratio scales.
(Alreck, 1995)
Survey Questions
Survey questions were broken down into three different sections:
1) Knowledge
2) Behavior
3) Demographics
Each of these sections provides valuable insight into aspects of a respondent’s
lifestyle that may influence their willingness to participate in watershed management
activities.
24
It also provides us with data to make comparisons and draw conclusions between preand post-meeting survey respondents as well as between meeting attendees and the
public. From this data conclusions can be drawn about the effectiveness of public
informational meetings.
Background Knowledge – Section A
The first section in the survey asks questions regarding the respondent’s
background knowledge about general watershed concepts, watershed issues
throughout the state, and specific knowledge about the Little Plover River. Questions
related to background knowledge can be used to determine if public informational
meetings had an effect on the level of knowledge of meeting participants.
Question A-1 is designed to measure the respondent’s awareness of the watershed
concept, the foundation of understanding watershed issues and watershed
management. The question is a multiple-choice question with a single response
answer.
•
A-1.) Please put an “X” in front of the statement that best fits your definition
of a watershed.
Question A-2 measures the respondent’s familiarity and awareness of issues
within the Little Plover River Watershed. It uses a Linear-Numeric Scale for the
answers. Respondents must choose an answer from the scale of one to four, one
being “Not a Problem” to four being a “Serious Problem”. Respondents are also
offered a neutral choice of zero, which is “Don’t Know”.
25
•
A-2.) Please circle an estimate of how much of a problem you think each of
the following issues currently is in the Little Plover River Watershed.
Questions A-3 through A-5 are indicative of how an individual feels about the
Little Plover River. It is important to determine if the respondent has positive or
negative feeling towards the Little Plover River. The intensity of those feelings must
also be determined.
Question A-3 rates the respondent’s opinion on the perceived condition of the
Little Plover River Watershed. This question will use a multiple-choice format with a
single response from the respondent.
•
A-3.) Please put an “X” in front of the statement that best expresses your
opinion on current conditions in the Little Plover River Watershed
Question A-4 utilizes the Likert Scale to obtain the respondent’s degree of
agreement or disagreement with statements regarding the importance of the Little
Plover River. The question uses a scale of one to five, with one indicating strong
agreement, five indicating strong disagreement, and three indicating a neutral opinion.
The respondent will choose a number of one through five for each of the statements.
If the respondent is in strong agreement with the statements, they will generally place
a high value on the Little Plover River Watershed. If a respondent places a high
value on the resource, he or she is more likely to take action to protect or conserve it.
26
•
A-4.) Please pick a number from the scale to show how strongly you agree or
disagree with each statement and circle the number to the right of the item.
Questions A-5 and A-6 indicate which groups the respondent perceives as
accountable for issues and management of the rivers and streams in the state of
Wisconsin and specifically for the Little Plover River. Questions A-5 and A-6 both
utilize a rank order scale in which the respondent must rank the listed options from
one through ten, with one being the most responsible and ten being the least
responsible. If respondents list local sources or groups that they are involved in as
responsible, they may be more inclined to take action than if they listed distant groups
or organizations with no relation to themselves.
•
A-5.) Please rank the following in the order of who you think should be most
responsible for protecting Wisconsin’s stream and rivers. 1 is the most
responsible, 10 is the least responsible.
•
A-6.) Please rank the following in the order of who you think should be most
responsible for protecting the Little Plover River. 1 is the most responsible,
10 is the least responsible.
Behavior - Section B
Section B in the surveys addresses past, present, and future behaviors of the
survey respondent.
27
A respondent’s behaviors may indicate a predisposition to certain types of
involvement or participation in activities related to environmental or watershed
activities. Involvement in these activities may also influence a respondent’s
knowledge and/or attitudes toward the subject.
Questions B-1 and B-2 ask about the type, timing, and frequency of the
respondent’s behaviors and activities. Question B-1 asks about respondent’s
participation in outdoor recreational activities within the Little Plover River
Watershed. Participation in recreational activities within the Little Plover River may
indicate a greater familiarity and background knowledge of the watershed and its
issues.
Question B-2 pertains to the respondent’s participation in activities similar to
participating in watershed management. Past behavior can serve as a potential
indicator of future behavior. Questions B-1 and B-2 use a verbal frequency scale.
Respondents were asked to answer question B-1 using a scale of one through three,
one indicating one to two times a year, two indicating one to two times a month, and
three indicating one to two times a week. A score of zero was also offered, indicating
that they don’t participate in the activity at all. Question B-2 uses a scale of zero, one
to four, and five or more indicating the number of times that respondents have
participated in the activity.
•
B-1.) Please indicate how often you partake in each of the following outdoor
leisure and recreational activities in or around the Little Plover River.
28
•
B-2.) Please circle your rate of involvement for each of the following
activities.
Questions B-3 and B-4 are questions designed to gauge the respondent’s
willingness to participate. Question B-3 asks the respondents about future
participation in planning for watershed management. It goes on to ask the respondent
to estimate how many hours per month they would be willing to participate. Question
B-4 asks respondents if they would be willing to donate money towards management
and if so, how much. A measure of a respondent’s willingness to participate is
important because it provides a gauge of change between pre- and post-meeting
respondents. A higher rate of willingness in post-meeting respondents indicates that
the informational meetings may have helped to move citizens into higher rates of
participation. A respondent’s willingness to pay may help to explain a respondent’s
unwillingness to participate in watershed management.
•
B-3.) How many hours per month would you be willing to participate in
planning for the Little Plover River watershed management?
•
B-4.) How much money per year would you be willing to donate towards the
management of the Little Plover River?
Demographics – Section C
The questions in the demographics section were used to identify groups of
respondents who are distinct or who might behave in similar ways.
29
This section of the survey was used to determine if all demographic groups from
within the watershed were represented at the public meetings. Demographic data is
the most sensitive data to obtain from a respondent.
It is placed at the end of the survey to allow the respondent to become familiar with
the survey format and to feel comfortable answering questions, before they are asked
to fill out personal information.
•
C-1.) I am Male or Female
•
C-2.) Age
•
C-3.) Formal education.______ years
(For example, High school graduate=12 years)
•
C-4.)
Employment Status:
•
C-5.)
Occupational Status:
•
C-6.)
Annual Income:
•
C-7.) Do you currently own the home you live in? Yes No
•
C-8.) If yes, how long have you lived there?
_________________________
•
C-9.) Is your residence in the Little Plover River Watershed? Yes No
•
C-10.) Please mark the approximate location of your current residence on the
map below
30
Pilot Testing
Survey questions were pilot tested for clarity of the questions, reliability of the
answers, ease of use, and ability to code and analyze. Surveys were first sent through
two reviews to edit questions and answers. Surveys were then randomly provided to
fifteen people to complete and test.
Comments about questions or answers were encouraged. These surveys were
then coded and entered into an Excel spreadsheet to test for any errors in the process.
Survey questions were further refined to meet the needs of the audience to be sampled
and analyzed.
Sampling Methods
The sample population of the survey was all attendees of the informational
meetings on the Little Plover River and the random sampling of the public. The
sample unit of the survey was the individual respondents to the survey.
Survey questions were pre-coded with response and format codes. Response
codes have a number for each alternative response to each structured question.
Questions that did not have listed responses were post-coded, or responses were given
a number after the surveys were returned. Format codes indicate the position in the
spreadsheet where data for each item was entered. The question number corresponds
to the section of the survey where the question is found followed by the question
number (Table 3).
31
Table 3. Example of survey codes used on each survey question.
Question Number
Format Code
A-1.) Please put an “X” in front of the statement that best fits your definition of a
1
watershed.
1.) ____ Low area that retains water
2.) ____ An area of land that drains water to a specific river or lake
3.) ____ A reservoir that serves a municipal water source
4.) ____ Don’t know
Response
Codes
Surveys were distributed and collected at each of the eight informational
meetings. Surveys were handed out prior to four of the meetings and after four other
meetings. In addition, a random sample of people who did not attend a meeting were
asked to complete a survey. Each survey was given a unique identification number in
the corner.
All surveys were counted and placed in an envelope with the time, date, and
location of where they were administered recorded on the outside. If the surveys
were administered at a meeting, the number of meeting participants and the number
of surveys collected from the meeting were also recorded.
Each survey was evaluated for completeness. If only two to four questions
were left unanswered, the survey was still counted as complete. If entire sections
were left unanswered the survey was not counted. Superfluous or extra data in the
survey was marked out and the survey was still counted.
32
Results from each survey were entered into an Excel spreadsheet. Each
sampling location had a separate worksheet within the spreadsheet where data was
compiled. Data was then condensed into responses from pre-meeting surveys, postmeeting surveys, all surveys from people who went to meetings (pre- and postmeeting surveys combined), and random samples of people who did not attend
meetings, for further analysis.
ANALYSIS
Surveys given before the meeting, given after the meeting, and given to the
public were all independently analyzed for statistically significant relationships of
responses between those factors. All surveys were then compared to one another to
find statistically significant relationships throughout.
Demographic Data
Demographic data (Section C) was the first section of data to be analyzed in
all of the surveys. Demographic data was condensed into three groups, pre-meeting
surveys, post-meeting surveys, and random sampling surveys (the public). Percent of
survey respondents in each gender, age, and income category were compared between
the groups and then compared to Portage County to ensure that each group of surveys
was representative of basic local demographics.
Demographic data was also analyzed to see if it could be used as a predictor
for a survey respondent’s willingness to participate in future watershed management.
A respondent’s willingness to participate was correlated to 4 different factors:
1) Age
2) Education
3) Distance of Residence from Little Plover River Watershed
4) Income
All survey respondents that attended a meeting (both pre and post) were analyzed
to determine if there were significant correlations between the factors and the
willingness to participate, using a Spearman-Rank Correlation Test.
33
34
Spearman Rank-Order Correlation
Spearman Rank-Order Correlations are used with categorical data, those that
come from nominal or ordinal scales, because it is a non-parametric test. It provides
a measure of the degree of association between two sets of ranks (Hollander and
Wolfe, 1999).
The assumptions associated with this test are as follows:
•
The two variables are ordinal or metric variables that have been reduced to an
ordinal scale of measurement,
•
The correlation between the variables is linear, and
•
If a test of significance is applied, the sample has been selected randomly
from the population.
(Hollander and Wolfe, 1999)
D = Difference between X rank and Y Rank
N = Number of data points
X and Y variables are first ranked. The differences between the X and Y
ranks are calculated for each data point. The difference for each point is squared and
all are summed. The data is then entered into the Spearman Rank-Order Correlation
Equation, which calculates an r-value (Table 4).
35
Table 4. Example of Spearman Rank-Order Correlation Data and Calculation used in the
survey.
X (Years of
Education)
X rank
18
14
18
18
12
17
14
18
17
18
16
18
18
17
26
14
9
2
9
9
1
6
2
9
6
9
5
9
9
6
16
2
Y
(Willingness
to
participate)
1
1
1
1
1
1
1
2
1
1
1
1
1
3
1
2
rs = 1- 6*(946)
16 (162-1)
x rank-y
rank
y rank
rs = 1- 5676
4080
1
1
1
1
1
1
1
14
1
1
1
1
1
16
1
14
rs = 1-1.39
8
1
8
8
0
5
1
-5
5
8
4
8
8
-10
15
-12
Sum
Difference
of
ranks^2
64
1
64
64
0
25
1
25
25
64
16
64
64
100
225
144
946
rs = 1-1.39 = -.39
An r-value of 1 is a perfect positive correlation (as one variable increases so
does the other) and an r-value of -1 is a perfect negative correlation (as one variable
increases the other decreases). A correlation of 0.5 or -0.5 or higher is considered to
be a significant correlation between a factor and the level of willingness to participate
in future watershed management activities.
It is important to note that while the Spearman Rank-Order Correlation
provides us with a degree of correlation between two variables, it in no way indicates
cause and effect relationships between the variables.
36
Questions C-7 through C-10 in the demographics section asked about the
survey respondent’s general location of residence compared to the Little Plover River
Watershed.
Survey respondents were asked to mark the approximate location of their residence
on a county map. Responses were binned into categories of distance from the Little
Plover River Watershed.
All questions in the demographic section were also analyzed using counts and
proportions of responses in the categories of pre-meeting attendees, post-meeting
attendees, meeting attendees, and random survey samples.
Knowledge
Questions in Section A evaluated a respondent’s background knowledge of
watershed concepts, awareness, and opinions about local and state watershed issues.
Questions in Section A were analyzed using tallies and frequencies of responses as
well as some specialized tests for comparison.
In question A-1 survey respondents were asked to choose the correct
definition of a watershed from three possible choices. A neutral option of “I don’t
know” was also offered but was discounted from the statistical analysis. The
responses to the question were compared between meeting attendees and the public as
well as pre-meeting survey respondents and post-meeting survey respondents using a
Chi-Square Analysis.
37
Chi-Square Test
Chi-Square analysis is a non-parametric test used to determine the probability
that an observed distribution of categorical qualitative data, based on rankings or
distribution is due to chance alone (Levine, 2005).
The Chi-Square statistic used was for two-way tables. A significance value of .05
was used because it is the standard for social science research.
The assumptions for the Chi-Square Test are:
•
Data are random
•
A sufficiently large sample size (There is no accepted cutoff. Some set the
minimum sample size at 50, while others would allow as few as 20)
•
There must be adequate cell sizes (A common rule is 5 or more in each
cell of a 2-by-2 table, and 5 or more in 80% of cells in larger tables, but no
cells with zero count)
•
Observations are independent
•
Observations must have the same distribution
•
Hypotheses are non-directional
•
Observations have finite values
•
Deviations (observed minus expected values) have a normal distribution
(Chekravert, 1967)
χ2= Σ (ƒ0-ƒe)2
ƒe
ƒ0 = Observed cell frequencies
ƒe = Expected cell frequencies
The level of significance α= 0.05
38
Hypotheses are as follows:
H0: There is no relationship between the row variable and the column variable.
Ha: There is a relationship between the row variable and the column variable.
Observed data frequencies are entered into a spreadsheet. Expected
frequencies for each row and column variable are calculated using
(row total)*(column total
Sample Size
The difference between the observed frequencies and expected frequencies is
calculated for each row and column variable. The difference is then squared and
divided by the expected frequency. These are all summed to find the Chi-Test
statistic.
The degrees of freedom for the Chi-Square Test is determined by taking the
number of rows minus one and multiplying it by the number of columns minus one
((# of rows-1)*(#of columns-1)). The critical value for the Chi-Square Test is
obtained from a Critical Value Table for x2 using the calculated degrees of freedom
and level of significance. If the Chi-Test statistic is greater then the critical value you
can reject the null hypothesis (Table 5).
39
Table 5. Example of Chi-Square Test Calculation used to compare survey data.
Row variable
Attend
Non
Total
Observed Frequencies
Column variable
1
2
3
2
52
6
17
8
69
2
5
7
Total
56
28
84
Row variable
Attend
Non
Total
Expected Frequencies
Column variable
3
1
2
5.333333
46 4.666667
2.666667
23 2.333333
8
69
7
Total
56
28
84
Calculations
fo-fe
-3.33333
3.333333
6
-6
-2.66667
2.666667
(fo-fe)^2/fe
2.083333 0.782609
1.52381
4.166667 1.565217 3.047619
The second question in the knowledge section asked a person to rate their
perceived seriousness of each of the listed watershed issues. Respondents were able
to respond on a scale of one to four, one being not a problem and four being a serious
problem. A neutral option of zero, don’t know, was also offered. A Mann-Whitney U
Test was used to determine if there was a difference between pre-meeting responses
and post-meeting responses and between meeting attendees and the public who didn’t
attend a meeting.
Mann-Whitney U Test
A Mann-Whitney U test is a non-parametric test used to assess the equality of
two population medians (Helsel, 2002). The responses of the pre-meeting survey
respondents and post-meeting survey respondents were compared as well as meeting
attendee survey respondents and the random survey sample.
40
Where samples of size n1 and n2 are pooled and Ri are ranks.
Assumptions for the Mann-Whitney U test are;
• Random samples from populations
• Independence within samples and mutual independence between samples
• Measurement scale is at least ordinal
(Helsel, 2002)
A significance level of .05 or 95% was used for each comparison. Hypotheses
for this test are as follows:
H0: There is no difference between the medians of the populations being compared.
Ha: There is a difference between the medians of the populations being compared.
Question A-3 in the background knowledge section asks respondents to mark
which statement they feel best describes the current condition of the Little Plover
River Watershed. One is excellent, two is good, three is fair, and four is poor.
Statements from pre-meeting survey respondents and post-survey respondents were
compared as well as meeting attendee survey respondents and the random survey
sample using the Chi-Square Test (See Chi-Square Test for calculation).
Question A-4 asked survey respondents how strongly they agreed or disagreed
with each statement about the Little Plover River. Survey respondents were asked to
provide answers on a scale of one to five, with one being strongly agreed, three was
neutral, and five was strongly disagreed. Responses from pre-meeting survey
respondents and post-meeting survey respondents were compared, as well as
responses from meeting attendee survey respondents and the random survey sample
using the Mann-Whitney U test (See Mann-Whitney U Test for Calculations).
41
Questions A-5 and A-6 asked a survey respondent to order the listed parties in
order of responsibility for watersheds in the state of Wisconsin and the Little Plover
River Watershed itself specifically; one is the most responsible and nine is the least
responsible. Data were condensed into answers for pre-meeting survey respondents,
post-meeting survey respondents, meeting attendee survey respondents and random
survey sample respondents.
The total number of responses for each rank of every listed party was calculated. The
listed party that received the highest number of responses for a rank received that
rank (Table 6).
Table 6. Example of Ranked Survey Responses for Questions A-5 and A-6.
Highlighted box corresponds to the rank listed for that row.
Rank
1
2
3
4
5
6
7
8
9
Fed.
Gov.
0
5
2
6
2
3
0
3
5
State
Gov.
County
Gov.
Local
Munici.
Local
Landowners
Industry/
Business
Enviro
Groups
Farm
Groups
Educators
13
4
2
3
2
0
0
1
1
4
10
7
2
1
1
1
1
0
5
4
8
4
2
1
4
0
0
4
1
2
6
4
3
5
2
0
1
3
1
4
3
5
3
1
5
1
0
3
1
8
7
4
3
0
1
1
1
3
3
2
9
5
1
1
2
1
1
2
3
0
7
10
Ranking of Parties
1 (most responsible) – State Government
6 – Environmental Groups
2 – County Government
7 – Farm Groups
3 – Local Municipalities
8 - Educators
4 – Local Landowners and Federal Government
9 (least responsible) - Educators
5 – Environmental Groups
42
Behaviors
Section B of the survey asked respondents about past, present, and future
behaviors that may indicate their predisposition towards participating in watershed
management, as well as past experiences with or knowledge of the Little Plover River.
All questions in Section B were analyzed using tallies and frequencies of responses.
Question B-1 asked respondents how often they participated in each of the
listed activities within the Little Plover River Watershed.
Responses were binned into categories of one to two times per year, one to two times
per month, one to two times per week, or not at all. This question was analyzed using
only tallies and frequencies of responses. The question was not analyzed further due
to the fact that it was found not to relate to the data that was needed for the study.
Question B-2 asked respondents how often they participated in each of the
listed activities. Responses were binned into categories of zero, one to four times, or
five or more times. The time period for the responses was indicated in each question
(ex. Over the past month or in the last five years). Responses for these questions
were condensed into pre-meeting responses, post-meeting responses, meeting
attendee responses, and random survey sample responses. Pre-meeting and postmeeting responses were compared, as well as the meeting attendee responses and
random survey sample responses using the Mann-Whitney U Test (see MannWhitney U Test for calculations).
Question B-3, which asked respondents how many hours per month they
would be willing to participate in future watershed management activities, was
analyzed using the Chi-Square Test (See Chi-Square Test for calculations).
43
Responses from pre-meeting survey respondents were compared to answers from
post-meeting survey respondents and responses from meeting attendees were
compared to the survey of the public.
Question B-4 asked respondents how much money they were willing to
donate towards the management of the Little Plover River Watershed.
Responses for each category were counted. Pre-meeting survey responses were
compared to post-meeting survey responses using the Chi-Square Test (See ChiSquare Test for calculations).
A Spearman Rank-Order Correlation test was used to determine if there was a
correlation between a respondent’s willingness to participate in watershed
management and a respondent’s willingness to donate money towards watershed
management.
RESULTS
Section A – Background Knowledge
Question A-1 asked respondents to choose the correct definition of the term
“watershed”. Ninety five percent of post-meeting survey respondents were able to
correctly identify the definition of a watershed compared to 85% of pre-meeting
survey respondents and just 59% of the public.
Answers were compared between pre-meeting survey respondents and postmeeting survey respondents, as well as the meeting attendees and the public. The
Chi-Square Test was used to determine if there were significant relationships between
when a meeting attendee filled out a survey and the definition of watershed chosen, as
well as whether a survey respondent attended a meeting or not and the definition of
watershed chosen.
Hypotheses for these tests are:
Pre-meeting respondents vs. Post-meeting respondents
Ho: There is no significant relationship between the definition of watershed chosen
and when the meeting attendee filled out the survey (pre-meeting or post-meeting).
Ha: There is a significant relationship between the definition of watershed chosen and
when the meeting attendee filled out the survey (pre-meeting or post-meeting).
Meeting attendees vs. the Public
Ho: There is no significant relationship between the definition of watershed chosen
and whether a respondent attended a meeting or not.
44
45
Ha: There is a significant relationship between the definition of watershed chosen and
whether a respondent attended a meeting or not.
At a 0.05 level of significance, the meeting attendees vs. the public had a pvalue of 0.001. Results show that there is a significant relationship between the
definition of watershed chosen and whether the respondent attended a meeting or not
(Appendix B). At the same 0.05 level of significance the comparison between the
pre-meeting and survey respondents and post-meeting survey respondents returned a
p-value of 0.561. This indicates that there is not a significant relationship between
the definition of watershed chosen and whether the respondent filled out the survey
prior to the meeting or after the meeting (Table 7 and Appendix B).
Table 7. Results of the Chi-Square analysis for question A-1
Variable 1
Variable 2
Critical Value
P-Value
Pre and Post
Definition of
watershed
chosen
Definition of
watershed
chosen
0.05
0.561
0.05
.0001
Public and
Meeting
Attendee
Question A-2 asked survey respondents how they perceived water related
issues in the Little Plover River Watershed. Survey respondent’s answers were given
on a Likert Scale of one to four. One indicated that the situation was not a problem
and four indicated that the situation was a serious problem. A neutral choice of zero
was also offered.
46
Respondents were asked to provide an opinion about 18 different situations
which included: nitrate levels in streams, rivers and lakes; nitrate levels in
groundwater; pesticide levels in streams, rivers and lakes; pesticide levels in
groundwater; soil deposition in streams, rivers and lakes; drinking water quality; soil
loss from agricultural fields; rivers and streams with eroding banks; invasive weed
growth; loss of water flows; loss of wetlands; loss of forested or wooded areas; loss
of wildlife; loss of family farms; loss of agricultural land to development; loss of
agricultural land to natural land; loss of natural land to development; and loss of
natural land to agricultural production.
Of the watershed issues listed, the loss of water flows in the Little Plover
River is arguably the largest issue that the watershed faces. Sixty two percent of postmeeting respondents felt that the loss of water flows was a serious issue compared to
50% of the pre-meeting respondents and 37% of the random public.
The Mann-Whitney U Test was used to compare all 18 proposed situations
between pre-meeting survey respondents and post-meeting survey respondents as
well as meeting attendees and the public.
The hypotheses for these tests are:
Pre-Meeting Respondents vs. Post-Meeting Respondents
Ho: There is no statistically significant difference in the responses between premeeting survey respondents and post-meeting survey respondents.
Ha: There is a statistically significant difference in responses between pre-meeting
survey respondents and post-meeting survey respondents.
47
Meeting Attendees vs. the Public
Ho: There is no statistically significant difference in responses between meeting
attendees and the public.
Ha: There is a statistically significant difference in responses between meeting
attendees and the public.
At a significance level of 0.05. all of the comparisons between pre-meeting
respondents and post-meeting respondents, as well as the comparisons between the
meeting attendees and the public all returned p-values higher than 0.05. I was able to
conclude from these results that there is not a statistically significant difference
between the population’s responses for any of the 18 listed watershed issues
(Appendix C).
Question A-3 asked respondents to choose a statement that best expressed
their opinions about the current condition of the Little Plover River Watershed.
Thirty five percent of pre-meeting respondents felt that the Little Plover River
Watershed was in poor condition versus 48% of the post-meeting respondents and
38% of the public. Conversely, 65% of the pre-meeting respondents, 52% of the
post-meeting respondents, and 62% of the public felt that the watershed was in good
or fair condition.
The Chi-Square Test was used to determine if there were significant
relationships between when a meeting attendee filled out a survey and the perceived
condition of the watershed as well as whether a respondent attended a meeting or not
and their perceived condition of the watershed.
48
Hypotheses for these tests are:
Pre-Meeting Respondents vs. Post Meeting Respondents
Ho: There is no significant relationship between the perceived condition of the
watershed and when the meeting attendee filled out the survey (pre-meeting or postmeeting).
Ha: There is a significant relationship between the perceived condition of the
watershed and when the meeting attendee filled out the survey (pre-meeting or postmeeting).
Meeting Attendees vs. the Public
Ho: There is no significant relationship between the perceived condition of the
watershed and whether a respondent attended a meeting or not.
Ha: There is a significant relationship between the perceived condition of the
watershed and whether a respondent attended a meeting or not.
At a 0.05 level of significance the comparison of the pre-meeting respondents
versus the post-meeting respondents had a p-value of 0.06. We can conclude that
there is not a significant relationship between the perceived condition of the
watershed and whether a meeting attendee filled out the survey prior to the meeting or
after the meeting (Appendix D). At the same level of significance, the comparison of
meeting attendees versus the public had a p-value of 0.8. We can conclude that there
is no significant relationship between the perceived condition of the watershed and
whether a respondent attended a meeting or not (Table 8 and Appendix D).
49
Table 8. Results of the Chi-Square analysis for question A-3.
Variable 1
Variable 2
Critical Value
P-Value
Pre and Post
Perceived
condition of
the watershed
Perceived
condition of
the watershed
0.05
0.06
0.05
0.8
Public and
Meeting
Attendee
Question A-4 asked respondents how strongly they agreed or disagreed with a
statement regarding the Little Plover River and its watershed. Respondents chose
their answers based on a Likert scale; one indicating that they strongly agreed with
the statement, three was neutral and five indicated they strongly disagreed with the
statement. The Mann-Whitney U-Test was used to compare the seven statements
between pre-meeting survey respondents and post-meeting survey respondents as
well as meeting attendees and the public.
The hypotheses for these tests are:
Pre-Meeting Respondents vs. Post-Meeting Respondents
Ho: There is no statistically significant difference in responses between the premeeting survey respondents and the post-meeting survey respondents.
Ha: There is a statistically significant difference in responses between the pre-meeting
survey respondents and the post-meeting survey respondents.
Meeting Attendees vs. the Public
Ho: There is no statistically significant difference in responses between the meeting
attendees and the public.
Ha: There is a statistically significant difference in responses between the meeting
attendees and the public.
50
At a 0.05 level of significance the comparison of the statement responses of
the pre-meeting survey respondents and post-meeting survey respondents and the
statement responses of the meeting attendees and the public all returned p-values
higher then 0.05 indicating that there is no statistically significant difference between
the responses of the populations (Appendix E).
Question A-5 asks survey respondents to rank nine groups in order of who
they felt should be most responsible for protecting Wisconsin’s streams and rivers,
with one being the most responsible and ten being the least responsible. Responses
were compiled into pre-meeting survey respondents, post-meeting survey respondents,
and the public. Each group received the rank that had the highest percentage of
responses (Table 9 and Appendix F).
Table 9. Ranked Responses of all survey respondent groups for question A-5.
Pre-meeting Rank
Post-Meeting Rank
Public Rank
Group
1
1
1
State Government
2
2
4
County Government
3
3&4
1
Local Municipality
4
8
3
Federal Government
2
Local Landowner
5
6
5
Environmental Groups
6
5
7&8
Industry/Business
7
7
6
Farm Groups
8&9
9
9
Educators
51
Question A-6 asks survey respondents to rank the nine groups in order of who
they thought they should be most responsible for protecting the Little Plover River,
with one was the most responsible and ten being the least responsible. Responses
were compiled into pre-meeting survey respondents, post-meeting survey respondents,
and the public. Each group received the rank that had the highest percentage of
responses (Table 10 and Appendix G).
Table 10. Ranked responses of all survey respondent groups for question A-6.
Pre-meeting rank
Post-meeting rank
1
3
2
2
2
County Government
3
1
1
Local Municipality
4
4&7
5
Federal Government
5
8
4
Environmental Groups
6
5
8
Industry/Business
7
6
6&7
Farm Groups
3
Local landowner
9
Educators
Identified as an
Self
8
9
9
Identified as an extra
Public rank
Group
State Government
extra
Section B – Actions & Behaviors
Question B-1 asked survey respondents to indicate how often they participated
in eleven different activities within the Little Plover River Watershed (Table 11, 12,
13)
52
Table 11. Percentage of pre-meeting responses regarding how often respondents
participated in listed activities within the Little Plover River Watershed.
1-2 times per
1-2 times per
1-2 times per
Not at all
year
month
week
Walking/running
37%
18%
15%
30%
Nature
41%
22%
0%
37%
Picnicking
37%
4%
0%
59%
Biking
26%
15%
11%
48%
Hiking
40%
12%
8%
40%
Hunting
7%
22%
4%
67%
Fishing
8%
19%
4%
69%
Boating
19%
7%
0%
74%
Camping
19%
7%
0%
74%
Cross-Country
19%
0%
0%
81%
9%
5%
5%
81%
Observation
Skiing
Swimming
53
Table 12. Percentage of post-meeting responses regarding how often respondents
participated in listed activities within the Little Plover River Watershed.
1-2 times per
1-2 times per
1-2 times per
Not at all
year
month
week
Walking/running
18%
18%
16%
47%
Nature
11%
34%
0%
55%
Picnicking
21%
5%
0%
74%
Biking
18%
16%
11%
55%
Hiking
24%
16%
5%
55%
Hunting
3%
3%
3%
92%
Fishing
8%
8%
3%
82%
Boating
5%
3%
5%
87%
Camping
8%
5%
3%
84%
Cross-Country
3%
5%
0%
92%
16%
5%
0%
79%
Observation
Skiing
Swimming
54
Table 13. Percentage of public responses regarding how often respondents
participated in listed activities within the Little Plover River Watershed.
1-2 times per
1-2 times per
1-2 times per
Not at all
year
month
week
Walking/running
27%
17%
23%
33%
Nature
27%
23%
17%
33%
Picnicking
27%
7%
10%
56%
Biking
27%
13%
30%
30%
Hiking
23%
13%
20%
43%
Hunting
7%
3%
7%
83%
Fishing
3%
3%
17%
77%
Boating
10%
17%
7%
66%
Camping
13%
7%
10%
70%
Cross-Country
3%
13%
7%
77%
13%
20%
7%
60%
Observation
Skiing
Swimming
Question B-2 asked survey respondents to indicate their rate of involvement
for eight activities that related to public participation, community involvement, or
environmentally related activities. Answers were grouped in categories of zero, one
to four, and five or more. The time period for involvement for each activity was
specified in the question (Table 14, 15, 16).
55
Table 14. Percentage of pre-meeting respondent’s answers to question B-2.
0
1-4
5 or more
23%
52%
25%
How many governmental meetings attended in the past year
54%
32%
14%
How many times worked to address a community problem in the
30%
63%
7%
36%
52%
11%
27%
52%
21%
50%
34%
16%
9%
61%
30%
18%
75%
7%
Hours per month participated in civic or community
organizations
last 5 years.
How many times worked with a neighbor to solve a problem in
the last 5 years.
How many conservation programs have participated in, in the
last 5 years.
How many times talked with public officials about natural
resource concerns in last 5 years.
Next year how many hours per month participating in civic or
community organizations
Next year how many conservation programs will participate in
Table 15. Percentage of post-meeting respondent’s answers to question B-2.
0
1-4
5 or more
5%
53%
42%
How many governmental meetings attended in the past year
60%
35%
5%
How many times worked to address a community problem in the
21%
57%
21%
20%
67%
13%
35%
54%
11%
73%
22%
5%
0%
46%
54%
31%
58%
11%
Hours per month participated in civic or community
organizations
last 5 years.
How many times worked with a neighbor to solve a problem in
the last 5 years.
How many conservation programs have participated in, in the
last 5 years.
How many times talked with public officials about natural
resource concerns in last 5 years.
Next year how many hours per month participating in civic or
community organizations
Next year how many conservation programs will participate in
56
Table 16. Percentage of the public’s answers to question B-2.
0
1-4
5 or more
33%
53%
13%
How many governmental meetings attended in the past year
65%
33%
2%
How many times worked to address a community problem in the
43%
46%
11%
41%
50%
9%
39%
52%
9%
62%
36%
2%
29%
53%
18%
27%
69%
4%
Hours per month participated in civic or community
organizations
last 5 years.
How many times worked with a neighbor to solve a problem in
the last 5 years.
How many conservation programs have participated in, in the
last 5 years.
How many times talked with public officials about natural
resource concerns in last 5 years.
Next year how many hours per month participating in civic or
community organizations
Next year how many conservation programs will participate in
Question B-3 asked survey respondents how many hours per month they
would be willing to participate in planning for future watershed management
activities. Answers were binned into six different categories (Table 17).
Table 17. Survey respondent’s willingness to participate in planning for future
watershed management activities.
Pre-meeting
0-5
5-10
10-15
15-20
20-25
More then
hours
hours
hours
hours
hours
25 hours
61%
25%
11%
3%
0%
0%
85%
14%
0%
0%
0%
0%
86%
14%
0%
0%
0%
0%
respondents
Post-meeting
respondent
Public
respondents
57
A Chi-Square Test was used to determine if there was a relationship between
a respondent’s willingness to participate and whether they attended a meeting or if
they did attend a meeting, whether they filled out a survey prior to the meeting or
after the meeting.
Hypotheses for these tests are:
Pre-Meeting Respondents vs. Post-Meeting Respondents
Ho: There is no significant relationship between a respondent’s willingness to
participate and whether they filled out a survey prior to or after the meeting.
Ha: There is a significant relationship between a respondent’s willingness to
participate and whether they filled out the survey prior to or after the meeting.
Meeting attendees vs. the Public
Ho: There is no significant relationship between a respondent’s willingness to
participate and whether they attended a meeting or not.
Ha: There is a significant relationship between a respondent’s willingness to
participate and whether they attended a meeting or not.
At a 0.05 level of significance the comparison of the pre-meeting respondents
versus the post-meeting survey respondents had a p-value of 0.04 indicating that there
is a significant relationship between a respondent’s willingness to participate and
whether they filled out the survey prior to or after the meeting (Appendix H). At the
same level of significance the comparison of the meeting attendees and the public had
a p-value of 0.37 indicating that there is not a significant relationship between a
respondent’s willingness to participate and whether they attended a meeting or not
(Table 18 and Appendix H).
58
Table 18. Results of Chi-Square Analysis for question B-3.
Variable 1
Variable 2
Critical Value
P-Value
Pre and Post
Willingness to
participate in
watershed
management
Willingness to
participate in
watershed
management
0.05
0.04
0.05
0.37
Public and
Meeting
Attendee
Question B-4 asked survey respondents how much money per year they would
be willing to donate towards management of the Little Plover River. Answers were
divided into categories of zero dollars, one to twenty dollars, twenty to forty dollars,
forty to sixty dollars, sixty to eighty dollars, eighty to one hundred dollars, and more
then one hundred dollars (Table 19).
Table 19. Survey respondent’s willingness to donate money towards watershed
management.
$0
$1-$20
$20-$40
$40-$60
$60-$80
$80-$100
More
then $100
Pre-
28%
40%
20%
0%
3%
6%
3%
19%
39%
19%
3%
8%
8%
3%
33%
46%
14%
5%
0%
2%
0%
meeting
Postmeeting
Public
A Chi-Square Test was used to determine if there was a significant
relationship between a respondent’s willingness to donate money and when a
respondent completed a survey or if a respondent even attended a meeting.
59
Hypotheses for these tests are:
Pre-Meeting Respondents vs. Post-Meeting Respondents
Ho: There is no significant relationship between a respondent’s willingness to pay and
whether they filled out the survey prior to or after the meeting.
Ha: There is a significant relationship between a respondent’s willingness to pay and
whether they filled out the survey prior to or after the meeting..
Meeting Attendees vs. the Public
Ho: There is no significant relationship between a respondent’s willingness to pay and
whether they attended a meeting or not.
Ha: There is a significant relationship between a respondent’s willingness to pay and
whether they attended a meeting or not.
At a 0.05 level of significance the comparison of the pre-meeting respondents
versus the post-meeting survey respondents had a p-value of 0.98 (Appendix I). This
indicates that there is not a significant relationship between a respondent’s
willingness to pay and whether they filled out the survey prior to or after the meeting.
At the same level of significance the comparison of the meeting attendees and the
public had a p-value of 0.30. This also indicates that there is not a significant
relationship between a respondent’s willingness to pay and whether they attended a
meeting or not (Table 20 and Appendix I).
60
Table 20. Results of Chi-square analysis for question B-4.
Variable 1
Variable 2
Pre and Post
Willingness to donate 0.05
money towards
watershed
managment
Willingness to donate 0.05
money towards
watershed
management
Public and
Meeting
Attendee
Critical Value
P-Value
0.98
0.30
A Spearman Rank-Order Correlation Test was conducted to determine if there
was a correlation between the amount of money a respondent was willing to donate
and the amount of a time a respondent was willing to participate in watershed
management. The Spearman Rank-Order Correlation test returned an r-value of –
0.05 indicating that there is no significant correlation between the two variables or
that a respondent’s willingness to participate is not correlated to a respondent’s
willingness to donate money towards management (Appendix J).
Section C – Demographic Information
Question C-1 asked survey respondents if they were male and female (Figure
2).
61
Figure 2. Gender demographics of survey respondents.
Gender Demographics of Pre Survey
Respondents
Gender Demographics of Post Survey
Respondents
Male
Female
Male
Female
Female
50%
Male
50%
Male
47%
Female
53%
Gender Demographics for Random Survey
Respondents
Male
Female
Female
47%
Male
53%
Question C-2 asked respondents to choose the category where their age fell.
Categories were under eighteen, eighteen to twenty five, twenty six to forty, forty one
to sixty, and older than sixty (Figure 3).
62
Figure 3. Age demographics of survey respondents.
Age Demographics of Pre Survey
Respondents
Older then 60 Under 18
0%
2%
41-60
25%
Age Demographics of Random Survey
Respondents
Older then 60
15%
18-25
46%
Under 18
17%
Under 18
Under 18
18-25
18-25
18-25
19%
26-40
41-60
Older then 60
41-60
30%
26-40
27%
26-40
41-60
Older then 60
26-40
19%
Age Demographics of Post Survey Respondents
Older then 60
26%
Under 18
0%
18-25
23%
Under 18
18-25
26-40
26-40
10%
41-60
Older then 60
41-60
41%
Question C-3 asked survey respondents their formal education in years.
Twelve years is equivalent to a high school graduate. Pre-meeting survey respondents
had an average of 16.24 years of education, post-meeting survey respondents had an
average of 16.73 years of education, and public survey respondents had an average of
17.42 years of education.
63
Question C-4 asked survey respondents to choose a response that represented
their employment status or where the majority of their work hours went (Table 21).
Table 21. Survey respondent’s employment status or where the majority of their
work hours went.
Premeeting
respondents
Postmeeting
respondents
Public
respondents
Company
Employed
Government
Employed
SelfEmployed
Seeking
Employment
Military
Retired
Student
43%
26%
0%
0%
0%
2%
29%
34%
11%
11%
2%
2%
11%
28%
38%
9%
13%
0%
2%
17%
21%
Question C-5 asked respondents to choose the option that best described their
occupational status (Table 22).
Table 22. Survey respondent’s occupational status.
Premeeting
respondent
Postmeeting
respondent
Public
respondent
Premeeting
respondent
Postmeeting
respondent
Public
respondent
Professional
Managerial
Administrative
Engineering
Marketing
7%
18%
13%
5%
7%
13%
26%
11%
3%
13%
14%
5%
2%
2%
2%
Education
Agriculture
Skilled craft
Semiskilled
Craft
Student
9%
4%
0%
0%
36%
13%
0%
0%
0%
21%
14%
0%
19%
16%
26%
Question C-6 asked respondents about their annual income (Table 23).
64
Table 23. Survey respondent’s annual income.
$0-$10,000
Pre-meeting 39%
respondents
15%
Postmeeting
respondents
41%
Public
respondents
$10,000$30,000
12%
$30,000$60,000
29%
$60,000$90,000
15%
More then
$90,000
5%
6%
26%
21%
32%
11%
33%
6%
9%
Question C-7 asked survey respondents if they lived in their own home (Table
24).
Table 24. Survey respondent’s home ownership.
Yes
Pre-meeting respondents 55%
Post-meeting respondents 71%
53%
Public respondents
No
45%
29%
47%
Question C-8 asked survey respondents on average how long they had lived in
the residence that they owned. Pre-meeting respondents indicated they lived in their
home an average of 10.14 years, post-meeting respondents lived in their homes an
average of 16.73 years, and public respondents lived in their home an average of
13.62 years.
Question C-9 asked survey respondents if their residence was within the Little
Plover River Watershed (Table 25).
Table 25. Survey respondent’s residence within the Little Plover River Watershed.
Yes
Pre-meeting respondents 12%
Post-meeting respondents 15%
6%
Public respondents
No
88%
85%
94%
65
Question C-10 asked survey respondents to indicate the approximate location
of their current residence. The first category of residences identified were those that
lived within the Little Plover River Watershed. Subsequent categories were broken
down into those who lived one mile outside of the watershed, 5 miles outside of the
watershed, ten miles outside of the watershed, fifteen miles outside of the watershed,
or greater then fifteen miles outside of the watershed. A visual map was provided so
survey respondents could either mark their residence on the map or in the box
indicating the distance from the watershed (Table 26).
Table 26. Survey Respondent’s distance of current residence from Little Plover
River Watershed.
Pre-Meeting
PostMeeting
Public
Within
Watershed
1 mile
outside
1-5 miles
outside
5-10 miles
outside
10-15 miles
outside
9%
16%
6%
9%
76%
50%
6%
22%
3%
3%
2%
14%
46%
11%
16%
More then
15 miles
outside
11%
The Spearman Rank-Order Correlation was used to determine if certain
demographic variables; age, education, income, and the distance of a respondent’s
residence from the Little Plover River Watershed, were correlated to a respondent’s
willingness to participate in future watershed management activities (Table 27 and
Appendices K, L, M, and N). Respondent’s income and willingness to participate
had a strongest correlation with an r-value of -0.93.
66
Table 27. Spearman Rank-Order Correlation of survey respondent’s demographic
variables and willingness to participate in planning for future watershed management
activities.
Variable 1
Age
Education
Income
Distance of Residence
Variable 2
Willingness to Participate
Willingness to Participate
Willingness to Participate
Willingness to Participate
R-value
-0.74
-0.77
-0.93
-0.67
67
Survey Revisions and Results
After the original data was compiled and analyzed there was a need for some
revisions and additional analysis for certain questions. The revisions were made and
the analysis was completed.
In Question A-3 respondents were asked to mark the response that best
expresses their opinion about the current condition of the Little Plover River
Watershed. Responses included the options of; Excellent, need no change in
management; Good, but could use some improved management; Fair, in need of more
management; and Poor, in need of urgent management. When the original Chi-Square
Test was conducted, the comparison between the pre-meeting respondents and the
post-meeting respondents returned a p-value of 0.06, which is very close to the 0.05
level of significance. Upon further consideration of the question and responses, it
was felt that the good and fair categories were very similar and that the test may not
have detected the small differences between the two categories. These two categories
were combined and the question was again analyzed using the Chi-square test. The
pre- and post-meeting responses as well as the meeting attendees and the public were
compared again using the same hypotheses as the original test.
At a 0.05 level of significance the comparison of pre-meeting respondents and
post-meeting respondents, using the newly combined categories of excellent,
good/fair and poor, returned a p-value of 0.054, and we were able to conclude that by
combining the categories there was still not a relationship between the perceived
condition of the watershed and whether the meeting attendee had filled out the survey
prior to the meeting or after the meeting (Appendix P).
68
The comparison of the meeting attendees and the public returned a p-value of 0.25,
which was p-value lower then the original test but still did not indicate a significant
relationship between the variables (Table 28 and Appendix P).
Table 28. Results of Chi-Square analysis for revised question A-3.
Variable 1
Variable 2
Critical Value P-Value
Pre and Post
Public and
Meeting
Attendee
Perceived condition
of the watershed with
revised categories
Perceived condition
of the watershed with
revised categories
0.05
0.054
0.05
0.25
In Question B-3 the Chi-Square Test returned a p-value that was statistically
significant, indicating that there was a relationship between a respondent’s
willingness to participate in watershed management and whether the respondent filled
out the survey prior to the meeting or after the meeting.
In the analysis of the results it was discovered that there was difficulty
differentiating between the levels of participation in pre-meeting survey respondents
versus post-meeting survey respondents due to the way the responses were binned.
Responses were binned in categories of zero to five hours, five to ten hours, ten to
fifteen hours, fifteen to twenty hours, twenty to twenty five hours, and more then
twenty five hours. Because zero was included in the zero to five bin it is difficult to
distinguish between people who moved from no willingness to participate to some
level of willingness to participate. For that reason, question B-3 was revised and new
bins of zero and one were created and the zero to five bin was revised to two to five.
69
The revised survey was given to a sample of the public and a sample of pre-meeting
respondents (Table 29).
Table 29. Survey respondent’s willingness to participate in future planning for
watershed management with revised categories.
0 hours
1 hour
2-5
5-10
10-15
15-20
20-25
More
hours
hours
hours
hours
hours
then
25
hours
Pre-meeting
6%
20%
60%
7%
7%
0%
0%
0%
13%
40%
27%
13%
0%
0%
0%
7%
survey
respondents
Public
Survey
Respondents
Results from the new sample of pre-meeting respondents and public were
compared using the Chi-Square Test to determine if there was a statistically
significant relationship between the respondent’s willingness to participate (with the
new categories) and whether a respondent attended a meeting or not. The hypotheses
for this test were the same as the original test. At a 0.05 level of significance the
comparison of the meeting attendees and the public had a p-value of 0.77. This
indicates that there is not a relationship between a respondent’s willingness to pay
and whether they attended a meeting or not (Table 30 and Appendix Q).
Table 30. Results of Chi-Square analysis for revised question B-3.
Variable 1
Variable 2
Critical Value
P-Value
Pre and Public
Willingness to
participate in future
watershed
management with
revised categories
0.05
0.77
70
In section C of the survey, demographic variables were correlated with a
respondent’s willingness to participate. A question arose as to whether a
respondent’s income was correlated to the amount of money that they were willing to
donate towards watershed management. A Spearman Rank-Order Test was run to
determine if there was a correlation between the two variables. The test returned an rvalue of –0.059, which indicates that there is no correlation between respondent’s
income and their willingness to donate money towards watershed management
(Appendix O).
DISCUSSION
The goal of this study was to determine if public informational meetings were an
effective method to generate public participation in watershed management activities.
This was to be accomplished through three objectives;
1) To determine whether public informational meetings increase an attendee’s
knowledge about the Little Plover River;
2) To determine whether public informational meetings increase an attendee’s
willingness to participate in future watershed management activities; and
3) To determine whether there are significant differences in knowledge and
actions between those who attend the public informational meetings and those
who do not
Objective 1
The first objective was to determine whether informational meetings increase
an attendee’s knowledge about the Little Plover River. A survey respondent’s
background knowledge about a subject may be indicative of how familiar he or she is
with the watershed and its associated issues such as water quality, water use, and
current water levels. It can also indicate a level of advanced understanding about
watersheds in general. Often, when an individual understands an issue or subject they
are able to make informed decisions and may be inclined to take action.
71
72
The survey asked questions regarding the definition of watershed, the seriousness of
issues involving the Little Plover River, and the perceived condition of the watershed.
Responses to question A-1, asking the correct definition of a watershed, were
first to be analyzed for this objective. The results of this question indicated that 84% of
the pre-meeting respondents correctly chose the definition of a watershed compared to
95% of post-meeting respondents.
A chi-square test with a significance level of 0.05 determined that there was no
relationship between the definition of watershed chosen and whether the meeting
attendee filled out the survey prior to the meeting or after the meeting. However, the
sample sizes were so small that even the smallest change in the number of responses in
each category significantly impacts the p-value of the test.
While there was not a relationship between pre and post survey respondents who
chose the correct definition of a watershed, there was a decline from pre-meeting
attendees to post-meeting attendees who did not select a definition. Seven percent of
the pre-meeting respondents did not select a definition compared to zero in postmeeting respondents. This perhaps suggests that pre-meeting respondents were
uncomfortable choosing a definition of the concept prior to the meeting.
Results of analysis of the responses to this question indicate that all meeting
attendees, whether pre or post, are relatively familiar with the watershed concept. The
meeting itself is not making a notable difference in the understanding of the watershed
concept.
73
The change in percentage of respondents not choosing a definition of watershed
is significant to note because it may indicate that post-respondents were more familiar
or comfortable with the subject matter to try and choose a definition rather then premeeting respondents.
The second set of responses that were analyzed to address the first objective
were from question A-2. This question asked respondents to rate the seriousness of 18
different watershed issues in the Little Plover River watershed. Watershed issues
included nitrate levels in surface water and groundwater, pesticide levels in surface
water and groundwater, soil deposition in surface water, drinking water quality, soil loss
from agricultural fields, eroding banks on rivers and streams, invasive weed growth,
loss of water flows, loss of wetlands, loss of forested or wooded areas, loss of wildlife,
loss of family farms, loss of agricultural land to development, loss of agricultural land
to natural land, loss of natural land to development, and loss of natural land to
agricultural production. Although these issues are common throughout Wisconsin, not
all apply to the Little Plover River Watershed.
The responses to this question allowed analysis of a respondent’s familiarity
with the particular issues that face the Little Plover River. The familiarity with issues
gives insight into how the informational meeting may change the respondent’s
understanding of the issue. It also denotes a sense of understanding and knowledge of
the watershed that may influence a respondent’s decisions and actions in the future.
Of the 18 issues listed, the loss of water flows is arguably the most serious and
pressing issue facing the Little Plover River.
74
Fifty two percent of pre-meeting respondents identified the loss of water flows as
serious compared to 62% of the post-meeting respondents. A Mann Whitney U-Test
was used to determine if the difference in responses between the populations was
statistically significant. At a significance level of 0.05 the test returned a p-value of 0.67,
therefore it was concluded that there was not a statistically significant difference
between the responses of the two populations. In fact, there was not a statistically
significant difference in responses of pre-meeting respondents and post-meeting
respondents for any of the 18 issues.
Results of the Mann-Whitney U-Test indicates that there is not a statistically
significant difference in responses to the question that asked respondents to rate the
seriousness of the loss of water flows within the Little Plover River watershed. This is
an indication that the meeting did not increase a respondent’s awareness about the loss
of water flows. The fact that there was a not a statistically significant difference
between pre-meeting and post-meeting respondents for any of the 18 issues indicates
that the meeting did not increase awareness on any of the issues. It also serves as an
indicator that there may be potential bias among the respondents.
This is contradictory to expectations that the meetings would increase the
awareness of watershed issues from pre-meeting respondents to post-meeting
respondents. One explanation was that media exposure about Little Plover River issues
may have increased public awareness prior to the meetings. Local newspapers and
other media had covered the loss of water flows in the Little Plover River, including
memorable photos of fish kills and dry ups when they occurred the two previous
summers.
75
If a respondent had been exposed to these media sources, they may have already
been familiar with the water loss issues. However, this would not explain the
differences between the 17 other issues that were listed. Respondents may have
guessed at the answers and assumed that all of the listed issues were applicable to the
Little Plover River watershed. Some respondents also may have thought that the
question applied to watersheds throughout the entire state, not just the Little Plover
River watershed.
The responses to question A-3 were also analyzed for this section. This question
asked respondents to express their opinion about the current condition of the watershed.
Respondents were able to choose from categories that included; Excellent, needs no
change in management; Good, but could use some improved management; Fair, in need
of more management; and Poor, in need of urgent management. Twenty seven percent
of the pre-meeting respondents felt that the watershed was in poor condition and needed
urgent management compared to 48% of the post-meeting respondents. Fifty one
percent of pre-meeting respondents felt that the watershed was in fair condition and
22% felt that it was in good condition. Forty five percent of post-meeting felt that the
watershed was in fair condition and eight percent felt that it was in good condition.
A Chi-square test was used to determine if there was a significant relationship
between the perceived condition of the watershed and whether the respondent filled out
the survey prior to the meeting or after the meeting. The Chi-square test returned a pvalue of 0.06 which indicates there is no significant relationship between the perceived
condition of the watershed and when the survey was filled out. However, 0.06 is
relatively close to the 0.05 level of significance.
76
Upon closer examination of the question, the categories of good and fair were
determined to be very similar to each other in meaning.
It was felt that the important difference between categories was not between good and
fair but rather between those two categories and excellent or poor. The categories of
good and fair were grouped together. The resulting responses were that 73% of premeeting respondents felt that the watershed was in good or fair condition compared to
53% of post-meeting respondents. Twenty seven percent of pre-meeting respondents
felt that the watershed was in poor condition while 47% of post-meeting respondents
felt it was in poor condition. The Chi-Square Test was re-run with the revised
categories of good/fair and poor. The test returned a p-value of 0.054, just over the
level of significance set at 0.05. This indicates that there is a relationship even closer
then the original test to being significant between the pre-meeting respondents and postmeeting respondents and the perceived condition of the watershed.
While the relationship is technically not statistically significant, it is still
important to note. The p-value as well as the percentage of respondents in each category
suggests that post-meeting respondents are more in tune with what is happening within
the watershed. A greater percentage of respondents also indicated that there is an
urgent need for management within the Little Plover River. If the need for management
is recognized, respondents may be more inclined to participate in the management effort.
The reason that the Chi-Square test may not have found the relationship significant is
simply due to the size of samples. Larger sample sizes may have made the distinction
between the categories more dramatic.
77
These three questions indicate that there were some shifts in levels of knowledge
and awareness between pre- and post-meeting respondents.
Question one showed an increase in knowledge and understanding in the watershed
concept between pre- and post-meeting respondents, with a greater percentage of the
sample choosing the correct definition of a watershed in post-meeting respondents. A
drop in the percentage of pre-meeting respondents to post-meeting respondents who
could not choose a definition was also noted.
Question two indicated that both pre- and post-meeting respondents were
familiar with issues facing the Little Plover River watershed. Question three indicated
that there was a shift in the perceived condition of the Little Plover River Watershed.
Pre-meeting respondents felt that the Little Plover River watershed was in good or fair
condition. The majority of the post-meeting respondents felt that the Little Plover River
watershed was in poor condition.
This shift in perceived condition also noted a change in the amount of
management that respondents felt was necessary within the watershed. Pre-meeting
respondents felt that the Little Plover Watershed was in need of some more or improved
management. Post-meeting respondents felt that the watershed was in need of urgent
management. While some of these relationships may not have been as statistically
significant it is still important that shifts were noticed and it suggests that follow up
meetings may be useful in getting the message across.
78
Objective 2
The second objective was to determine if public informational meetings
increased an attendee’s willingness to participate in future watershed management
activities.
An attendee’s willingness to participate is important because it is an indication whether
the informational meetings were merely educational and informational or whether they
began to shift participants into higher levels of involvement, including participating in
management.
The first responses that were analyzed for this objective came from question B3, which asked a respondent how many hours per month they would be willing to
participate in watershed management activities. Respondents were able to choose from
six different categories of time (Table 27).
Table 31.
Survey respondent’s willingness to participate in planning for future
watershed management.
Pre-meeting
0-5
5-10
10-15
15-20
20-25
More then
hours
hours
hours
hours
hours
25 hours
61%
25%
11%
3%
0%
0%
85%
14%
0%
0%
0%
0%
respondents
Post-meeting
respondent
A chi-square test was used to determine if there was a relationship between a
survey respondent’s willingness to participate and whether they filled out the survey
prior to or after the meeting.
79
The chi-square test returned a p-value of .044 indicating that there was a significant
relationship between a respondent’s willingness to participate and when they filled out
the survey.
The respondent’s willingness to donate time shows an unexpected and different
result. A greater percentage of pre-meeting respondents were willing to volunteer more
hours then post-meeting respondents. This is opposite of what was expected. The
difference between pre-meeting respondents and post-meeting respondents may have
been due to a number of different things. As explained in the meetings, the Little Plover
River’s water quantity issues are directly related to municipal and agricultural pumping.
As people sat through the informational meeting they may have begun to feel that this
problem was not within their control or that they would not be able to do anything to
help with the issue.
While it cannot definitively determined what might have caused this difference
from the information gathered in this survey, evidence to support this theory comes
from question A-6 which asks respondents to rank listed groups in the order of who
they think should be most responsible for management on the Little Plover River. Premeeting respondents identified self as one of the groups that should be responsible
while post-meeting respondents did not.
During the analysis of the responses to question B-3 it was noted that there was
no way to determine if respondents had moved from not willing to participate at all to
willing to participate some. This was because the level of no participation or zero was
combined in the zero to five hours per month category. Using this category, there is no
way to differentiate if a respondent is choosing zero or five hours per month.
80
In order to determine if there would be a difference with the zero category separate from
the rest the question had to be re-written.
The new categories for the question were divided into categories of zero hours,
one hour, two to five hours, five to ten hours, ten to fifteen hours, fifteen to twenty
hours, and more than twenty five hours. A new survey with the revised categories for
question B-3 was given to a sample of the public and pre-meeting (Table 28).
Table 32.
Survey respondent’s willingness to participate in planning for future
watershed management with revised categories.
0 hours
1 hour
2-5
5-10
10-15
15-20
20-25
More
hours
hours
hours
hours
hours
then
25
hours
Pre-meeting
6%
20%
60%
7%
7%
0%
0%
0%
13%
40%
27%
13%
0%
0%
0%
7%
survey
respondents
Public
Survey
Respondents
The results indicate that even with the new categories of zero and one hour, over
half of the pre-meeting respondents still chose between two and five hours, which
reflects the results of the original survey. This demonstrates that the revised categories
would not have made a significant difference in the results.
It was also important to determine if any of the demographics could serve as a
predictor of a respondent’s willingness to participate. This would allow a planner or
manager to approach specific demographic groups that might be more inclined to
participate in management in the future.
81
The demographic variables that were examined included: age, education, income, and
the distance of residence from the Little Plover River Watershed. The Spearman RankOrder Test was used to determine the strength of the correlation between the
demographic variable and the respondent’s willingness to participate.
The distance of residence from the watershed had the weakest correlation with
willingness to participate, which had an r-value of -0.67. This was expected to be one
of the demographic variables with the highest correlation.
However, survey
respondents were asked to mark the approximate location of their current residence.
From this information it is clear that more then 53% of all survey respondents live
between five and ten miles outside of the Little Plover River Watershed, where both the
city of Stevens Point and the village of Plover lie. Very few of the survey respondents
actually resided within one mile of, or within, the Little Plover River Watershed.
The demographic variable with the highest correlation was income and
willingness to participate, with an r-value of -0.93. This indicates a strong negative
correlation between the two variables.
As a respondent’s income increases, the
willingness to participate decreases, which may suggest that respondents are already
occupied with things such as work or other volunteer activities and don’t have time to
participate in management.
The relationship between income and willingness to participate was expected to
follow a similar trend as income and participation. The Spearman Rank-Order test was
used to determine the correlation between a respondent’s income and their willingness
to donate money towards management.
The test returned an r-value of –0.059
indicating that there is not a correlation between the variables.
82
This result could be related to the specific nature of the Little Plover River’s problem of
water quantity, which may be viewed as a problem government should be required to
deal with directly without financial aid.
When analyzing the responses for objective two, the results were surprising. It
was found that pre-meeting respondents were more willing to participate in watershed
management activities then post-meeting participants, suggesting that the meeting was
no help in generating participation in activities and may have even been detrimental in
this effort. It was also found that income had a strong negative correlation with a
respondent’s willingness to participate.
While these outcomes were not what were originally expected, they helped show
that a respondent’s willingness to participate is extremely variable and can be difficult
to predict or even associate with other variables.
Objective 3
The purpose of objective three was to determine if there were significant
differences in meeting attendee’s knowledge and actions compared to the general public.
In this study, the public had the same opportunities for exposure and education prior to
the meetings as those who attended the meetings. The public also served as a control
group in the study, allowing us to see how people felt and acted towards the Little
Plover River and its associated issues without the information and education provided in
a meeting.
83
Question A-1, from the previous section, asked respondents for the correct
definition of a watershed. However, in this analysis comparisons were made between
meeting attendees and the public. Eighty eight percent of the meeting attendees were
able to correctly identify the definition of a watershed compared to fifty one percent of
the public.
A Chi-Square Test was used to determine if there was a statistically
significant relationship between the definition of watershed chosen and whether a
respondent had attended a meeting.
The test returned a p-value of .0001 at a
significance level of 0.05, which indicated that there is a strong relationship between the
definition chosen and meeting attendance.
It was expected that meeting attendees would have a better understanding of the
watershed concept because it was a concept that was explained in the meetings.
The second set of responses that were analyzed for this objective came from
question A-2, which asked survey respondents to rate the seriousness of 18 watershed
issues. The loss of water flows was the watershed issue that was focused on for
analysis because it is arguably the largest issue facing the Little Plover River. Thirty
one percent of the public felt that the loss of water flows was a serious issue compared
to fifty seven percent of the meeting attendees. A Mann Whitney U-Test was used to
determine if the differences between answers was statistically significant. At a 0.05
level of significance the test returned a p-value of 0.4, which indicates that the
difference between the two groups is not statistically significant. While the difference
is not statistically significant it is still important to note the difference between 31% of
the public and the 57% of the meeting attendees that felt that the loss of water flows
was serious.
84
The higher percentage of meeting attendees who felt the issues was serious indicates
that meeting respondents may have had a better idea of what was happening in the Little
Plover River Watershed. When the responses to the other 17 watershed issues were
compared between meeting attendees and the public, it was found that none of the
comparisons were statistically significant.
The lack of significant difference in responses regarding the loss of water flows
could be due to exposure on the issues of the Little Plover River, the same reason for
the non-significant difference found between pre-meeting respondents and post-meeting
respondents in objective one.
Local newspapers and other sources of media had
covered the loss of water flows in Little Plover River both summers that it took place.
If a respondent had been exposed to these media sources they may have already been
familiar with the issue of water loss. For the other 17 issues that were analyzed,
respondents may have guessed at the answers and assumed that all of the listed issues
were applicable to the Little Plover River watershed. Some respondents may have also
thought that the question applied to watersheds throughout the entire state, not just the
Little Plover River watershed.
The third set of responses that were analyzed for objective three were from
question A-3 regarding the perceived condition of the watershed between meeting
attendees and the public. Survey respondents were asked to indicate what condition
they felt the Little Plover River Watershed was currently in. Respondents were able to
choose excellent, good, fair or poor for their responses.
The data indicated that 31% of the public felt that the watershed was in poor
condition compared to 37% of the meeting attendees.
85
Sixty nine percent of the public felt the watershed was in good or fair condition
compared to 63% of the meeting attendees. A Chi-Square Test was used to determine if
there was a significant relationship between the perceived condition of the watershed
and whether a respondent attended a meeting. At a significance level of 0.05 the test
returned a p-value of 0.8 indicating that there is no significant relationship between the
perceived condition of the watershed and whether a meeting was attended or not. While
there was not a large difference between the percentages of respondents who ranked the
watershed in poor condition, meeting attendees still had a slightly higher percentage of
respondents who ranked the watershed in poor condition.
The fourth set of responses that were analyzed for this objective were from
question B-3, which asked survey respondents how many hours per month they would
be willing to participate in planning for future watershed management. Respondents
were able to choose from six different categories. Eighty six percent of the public were
willing to donate between zero and five hours and fourteen percent were willing to
donate between five and ten hours. Seventy five percent of meeting respondents were
willing to donate between zero and five hours, nineteen percent were willing to donate
between five and ten hours, four percent were willing to donate between ten and fifteen
hours, two percent were willing to donate between fifteen and twenty hours.
A chi-square test was conducted to determine if there was a significant
relationship between a respondent’s willingness to participate and whether a respondent
attended a meeting or not. The chi-square test returned a p-value of 0.37, indicating that
there was no significant relationship between meeting attendance and willingness to
participate.
86
While there was not a significant relationship between the two variables, meeting
attendees were overall willing to volunteer more time towards watershed management
than the public.
During the analysis of question B-3 it was noted that there was no way to
determine whether respondents were not willing to participate at all or were willing to
participate at some level, because the level of not participation or aero was included in
the zero to five hours per month category. Using that category there is no way to
differentiate whether a respondent chose zero or up to five hours per month. The
question had to be re-written to determine whether thee would be a difference with zero
separate from the rest of the category.
The revised categories of responses for the question were zero hours, one hour,
two to five hours, five to ten hours, ten to fifteen hours, fifteen to twenty hours, twenty
to twenty five hours, and more then twenty five hours a month. The percentage of
survey respondents in each revised category is found in Table 28. The new data
indicates that the majority of public respondents chose one hour per month, indicating
that the public may be less willing to participate in management activities.
The Chi-Square Test was run again using the new data from the pre-survey
respondents and the public. This time at a 0.05 level of significance the test returned a
p-value of 0.77 indicating that there is still no statistically significant relationship
between a survey respondent’s willingness to participate and whether they attended a
meeting or not. The seven percent of the public that was willing to participate more
then 25 hours per month was a response from one respondent. This is a highly unlikely
response that is not typical of the data collected.
87
The responses that were used to evaluate objective three indicate that there were
some differences in levels of knowledge, awareness, and actions between meeting
attendees and the general public. Responses to question A-1 indicated a higher level of
knowledge and understanding about the watershed concept between meeting attendees
and the public, with a greater percentage of meeting attendees choosing the correct
definition of a watershed. Responses to question A-2 indicated that both meeting
attendees and the public were familiar with issues facing the Little Plover River
watershed.
Responses to question A-3 indicated that there was not a significant relationship
between the perceived condition of the watershed and meeting attendance. The original
survey data for question B-3 indicated that there were no differences in willingness to
participate between meeting attendees and the public. When the survey was revised and
the new categories of zero and one hour per month were added, the majority of the
public chose the one hour category, indicating that there might be some difference
between the revised and original categories. However, the Chi-Square Test still
indicated that there was no relationship between the variables.
Additional Data
Additional data was collected from survey respondents, but was not used to
analyze any of the objectives. The additional data can be shared with organizations that
are interested in the available information.
Question A-2 asked respondents to rate the seriousness of 18 watershed issues.
Issue 10, the loss of water flows, was used to help determine the background knowledge
of survey respondents.
88
The other 17 issues can be used to help managers and planners determine what were
perceived as serious issues within the watershed. The issues perceived as serious by the
survey respondents had high percentages of responses that rated it as a serious problem.
Sixty three percent of post-meeting respondents identified loss of water flows and
invasive weed growth as serious problems. Fifty five percent of pre-meeting
respondents identified loss of natural land to development as one of the most serious
issues. Fifty four percent of the public identified loss of agricultural land to
development as one of the most serious problems. These issues can then be addressed as
real concerns within the watershed or something that may be perceived as a concern,
but may not be entirely founded in truth. It may also alert planners and managers to
issues within the watershed that they may not have been aware of.
Question A-4 asked respondents how strongly they agreed or disagreed with
statements regarding the Little Plover River watershed. These statements determine
how valued the Little Plover River is as a natural resource, source of economics, and
recreational opportunity. If a survey respondent values the Little Plover River then he
or she may be more inclined to take action towards it.
Question A-5 and A-6 ask respondents to rank who is the most to least
responsible for management of waters in Wisconsin and the Little Plover River. This
determines who respondents think should be in charge of resolving the issue. If
respondents feel local organizations or groups and individuals should be in charge they
may be more likely to participate in management then if they identify the federal
government as the responsible party. Data from question A-6 was also used in the
evaluating question B-3 for objective two.
89
Question B-1 asked respondents about their outdoor leisure and recreational
activities they participated in while on the Little Plover River. This question simply
identifies what activities the Little Plover River is being used for. This question turned
out not to be very influential in the survey and thus was not used in any of the analysis.
The Little Plover River is a relatively small river and is not extensively used by any of
the respondents. That’s not to say it doesn’t have other, more intrinsic values (see
question A-4). Paul Radomski, a local citizen, fondly recalls growing up in the area and
spending time during his childhood playing and exploring along the river.
Question B-2 asked respondents about their involvement in local government,
community organizations, and conservation programs. The question was used to try to
determine if there were any significant relationships between their past activities and
their willingness to participate in future activities. No relationships could be found with
the data gathered.
Question B-4 asked respondents how much money they would be willing to
donate towards management of the Little Plover River. There were no significant
differences in the amount of money that respondents were willing to donate towards
management. A Chi-Square Test was used to determine whether was a significant
relationship between a respondent’s willingness to donate and their meeting attendance,
or when meeting attendees completed the survey before or after the meeting. No
relationship was found. The majority of all respondents were willing to donate between
one and twenty dollars a year. The Chi-Square analysis of this question was not used to
meet any of the objectives of this study. However, a correlation of a respondent’s
income and their willingness to donate was used in objective two.
90
Section C asked questions regarding basic demographics of the survey
respondents. The demographics were not only used as variables to predict a
respondent’s willingness to participate or donate, but were also used to determine
whether the samples were representative of the population. The basic demographics of
gender and age of survey respondents were compared to those of Portage County.
Portage County demographics were obtained from the U.S. Census Bureau 2000 Census
Survey. Portage County gender demographics are split 50% male and 50% female. The
survey age demographics were also split 50/50 between male and female. Age
demographics for both the survey respondents and Portage County residents can be
found in Table 29.
Table 33. Age Demographics of Survey Respondents and Portage County Residents.
Survey
Under 18
18-25
26-40
41-60
Older then 60
6%
29%
19%
32%
14%
29%
11%
28%
18%
14%
Respondents
Portage County
Residents
Differences between the ages of survey respondents and residents of Portage
County can be explained by audiences that were targeted for the surveys. Surveys were
not targeted at youth or students under the age of 18. This age group is not likely to
become involved in watershed management activities. Stevens Point is also a college
town. The majority of surveys were conducted while college was in session when there
is a significant increase in college age students (ages 18-25) within the community. We
expected to see a larger number of students in this age group in the survey samples.
91
Overall, the demographics of the survey respondents do not significantly differ from the
population of Portage County.
Overall Findings
The findings of the surveys indicate that the informational public meetings are a
good source of information and education to participants. Survey respondents were
more aware of issues within the watershed and better understood the concepts related to
watershed management after the meetings. However, participants were not more
inclined to participate in future watershed management activities after attending the
meetings.
Referring back to the spectrum of public participation, informational public
meetings fell in the second category of participation, degrees of tokenism or consulting.
It was at a level where the proposed method of public participation could possibly move
participants into higher levels of participation such as degrees of citizen power or
involvement. This study was unable to determine that the informational meetings had
that impact. The surveys indicated that public meetings would be a better method of
distributing information and education, placing it in the first category of shallow
participation or informing the public.
Improvements to Study
There are some changes that should be made if this study were repeated. An
obvious change would be the revisions to the willingness to participate question.
92
Breaking out the zero category would have provided more definitive results as well as a
stronger analysis of the question.
The second improvement would have been sample sizes. While it was a
struggle to obtain the current survey samples, additional samples would have provided
an even better idea of the differences between the public, pre-meeting attendees, and
post-meeting attendees. Larger samples may have also provided more definitive
answers on some of the questions that were very close.
Another change to the study would have been a follow-up survey to meeting
attendees. The follow-up survey could have asked questions about their current
involvement in watershed management activities, how the information from the meeting
has been put to use in their lives, whether they have shared the information from the
meeting, and their current knowledge about watershed issues. The follow-up survey
could have been sent out approximately six months after the initial survey was given.
The additional follow-up survey would not have only provided additional data that
better indicates the impact of the meeting, but it would have also eliminated another
potential source of bias between pre and post meeting respondents.
While analyzing this survey, additional questions about survey respondents were
raised and could have been included in the survey. Identifying a survey respondent’s
level of previous exposure to general watershed issues, as well as specific issues within
the Little Plover River would have been extremely helpful. This information would
have helped to eliminate some speculation surrounding the non-significant differences
in responses about watershed issues. It also would have been helpful to determine what
sources of information survey respondents had utilized.
93
This could have helped determine if respondents were using reliable sources of
information. It also would provide managers and planners with some idea of what
information sources the public uses so that they could make use of those for future
management and public participation efforts.
Impacts on Public Participation
There are a number of characteristics about the watershed that could have
potentially impacted public participation efforts in this study. The Little Plover River is
a small body of water with a small watershed. People may not see a strong value
associated with such a small body of water. There is also not a very clear idea of the
economic impact of this river. Both of these factors create a sense that the river may be
somewhat disposable. In this case the issue becomes one of economic value. The Little
Plover River does not have a clear economic value associated with its dry-up.
In the case of the Little Plover River, the way people view the “worth” or the
economic impact of the river varies greatly, due in large part to a relatively distinct
generation gap. Older individuals remember and relate to the river when it had higher
water levels, more significant flow, hosted a well-known trout fishery, and was in a
more rural area. Younger individual’s have only known the river in an urban setting
and at much lower water flows that limit some uses of the river. The differences in the
perceptions of the river between the two generations impact the individual’s value of
the river and thus might impact their efforts to protect the river.
94
One of the other factors that should be considered is that the loss of water flows
on the Little Plover River is largely an intangible issue. While the diminished flows
themselves are extremely tangible, the underlying cause is not. The Little Plover River
is largely groundwater fed making it a groundwater issue. Getting the public to connect
groundwater pumping to surface water levels is a well-known difficulty. Perhaps it is
difficult for the public to become involved with something that they cannot directly see
or deal with.
Even considering the effect that these factors could have on the study, there still
remains one large issue. The informational meeting was a single event that introduced
most of the participants to the in-depth issues of the Little Plover River Watershed.
Research has shown that while a single event, like a public meeting, may be successful
at increasing short term knowledge, in order to be truly successful they should be linked
with a broader communication strategy. By becoming a part of a continuous series of
events, the same messages can be repeated multiple times (Seevers et al, 1997).
Research has also shown that the more people are familiar with a topic the more likely
they are to become involved. However, in order to become involved the knowledge
needs constant updating and reminders (Coyle, 2004).
This research helps to identify that the true threshold for moving individuals into
higher levels of participation may not lie exclusively in the method of public
participation itself but perhaps in a combination of the method or methods and the
number of times an individual hears the same message.
95
It also shows that these meetings serve as an opportunity to disseminate accurate
information and education to the public in an informal manner as well as allowing
meeting attendees to participate in a dialogue. While public meetings may not be the
key to solving watershed management issues nor the ideal public participation method,
it is certainly a powerful tool that managers and planners should continue to use.
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Appendix A
Survey
100
101
102
103
104
105
106
Appendix B
Chi-Square Test for question A-1
107
108
Chi-Square for question A-1 Meeting Attendees vs. Public
Observed Frequencies
Column variable
Row variable
1
2
Attend
4
65
Non
11
24
Total
15
89
Row variable
Attend
Non
Total
Data
Level of Significance
Number of Rows
Number of Columns
Degrees of Freedom
3
2
7
9
Total
71
42
113
Expected Frequencies
Column variable
1
2
3
9.424779 55.92035
5.654867
5.575221 33.07965
3.345133
15
89
9
Total
71
42
113
Calculations
0.05
2
3
2
Results
Critical Value
5.9915
Chi-Square Test
Statistic
18.7227
p-Value
0.0001
Reject the null hypothesis
Expected frequency assumption
is met.
fo-fe
-5.42478
5.424779
9.079646
-9.07965
-3.65487
3.654867
(fofe)^2/fe
3.122431
5.278396
1.474239
2.492166
2.362222
3.993281
109
Chi-Square for 2question A-1 Pre-meeting respondents vs. Postmeeting respondents
Observed Frequencies
Column variable
Row variable
1
2
3
Pre
3
37
Post
1
38
Total
4
75
Row variable
1
2
3
Expected Frequencies
Column variable
1
2
3
Pre
2 37.5
1.5
Post
2 37.5
1.5
Total
4
75
3
Data
Level of Significance
Number of Rows
Number of Columns
Degrees of Freedom
Total
41
41
82
Calculations
0.05
2
3
2
Results
Critical Value
5.9915
Chi-Square Test Statistic
1.3467
p-Value
0.5100
Do not reject the null hypothesis
Expected frequency assumption
is met.
Total
41
41
82
1
-1
0.5
0.5
fo-fe
-0.5
0.5
-0.5
0.5
(fo-fe)^2/fe
0.006667 0.166667
0.006667 0.166667
Appendix C
Mann-Whitney U Test for question A-2
110
111
Results for: Question A-2 Meeting Attendees vs. the Public
Issue A Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
8.00
3.00
Point estimate for ETA1-ETA2 is 5.00
96.3 Percent CI for ETA1-ETA2 is (-7.99,24.00)
W = 32.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.4034
The test is significant at 0.4020 (adjusted for ties)
Issue B Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
6.00
6.00
Point estimate for ETA1-ETA2 is 3.00
96.3 Percent CI for ETA1-ETA2 is (-6.00,28.01)
W = 30.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6761
The test is significant at 0.6742 (adjusted for ties)
Issue C Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
12.00
2.00
Point estimate for ETA1-ETA2 is 5.00
96.3 Percent CI for ETA1-ETA2 is (-10.00,29.00)
W = 31.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.4647
The test is significant at 0.4578 (adjusted for ties)
Issue D Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
11.00
5.00
Point estimate for ETA1-ETA2 is 6.00
96.3 Percent CI for ETA1-ETA2 is (-8.01,22.99)
W = 31.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.4647
The test is significant at 0.4633 (adjusted for ties)
112
Issue E Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
12.00
4.00
Point estimate for ETA1-ETA2 is 8.00
96.3 Percent CI for ETA1-ETA2 is (-7.00,22.99)
W = 32.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.3472
The test is significant at 0.3457 (adjusted for ties)
Issue F Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
18.00
4.00
Point estimate for ETA1-ETA2 is 7.00
96.3 Percent CI for ETA1-ETA2 is (-2.99,19.00)
W = 34.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.2101
The test is significant at 0.2059 (adjusted for ties)
Issue G Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
13.00
6.00
Point estimate for ETA1-ETA2 is 7.00
96.3 Percent CI for ETA1-ETA2 is (-8.00,20.99)
W = 34.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.2101
The test is significant at 0.2073 (adjusted for ties)
Issue H Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
17.00
5.00
Point estimate for ETA1-ETA2 is 8.00
96.3 Percent CI for ETA1-ETA2 is (-7.01,20.00)
W = 34.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.2101
The test is significant at 0.2073 (adjusted for ties)
113
Issue I Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
11.00
3.00
Point estimate for ETA1-ETA2 is 2.00
96.3 Percent CI for ETA1-ETA2 is (-7.01,33.01)
W = 32.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.4034
The test is significant at 0.4020 (adjusted for ties)
Issue J Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
7.00
6.00
Point estimate for ETA1-ETA2 is 4.00
96.3 Percent CI for ETA1-ETA2 is (-6.00,32.00)
W = 30.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6761
The test is significant at 0.6742 (adjusted for ties)
Issue K Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
9.00
3.00
Point estimate for ETA1-ETA2 is 6.00
96.3 Percent CI for ETA1-ETA2 is (-9.01,28.00)
W = 30.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6015
The test is significant at 0.6004 (adjusted for ties)
Issue L Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
10.00
8.00
Point estimate for ETA1-ETA2 is 3.00
96.3 Percent CI for ETA1-ETA2 is (-6.00,23.01)
W = 33.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.2506
The test is significant at 0.2477 (adjusted for ties)
114
Issue M Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
8.00
7.00
Point estimate for ETA1-ETA2 is 5.00
96.3 Percent CI for ETA1-ETA2 is (-4.01,23.00)
W = 33.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.2963
The test is significant at 0.2918 (adjusted for ties)
Issue N Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
12.00
5.00
Point estimate for ETA1-ETA2 is 7.00
96.3 Percent CI for ETA1-ETA2 is (-4.00,19.99)
W = 34.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.1745
The test is significant at 0.1732 (adjusted for ties)
Issue O Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
10.00
2.00
Point estimate for ETA1-ETA2 is 4.00
96.3 Percent CI for ETA1-ETA2 is (-10.00,25.00)
W = 35.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.1437
Issue P Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
10.00
7.00
Point estimate for ETA1-ETA2 is 4.00
96.3 Percent CI for ETA1-ETA2 is (-2.00,17.00)
W = 34.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.1745
The test is significant at 0.1666 (adjusted for ties)
115
Issue Q Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
7.00
3.00
Point estimate for ETA1-ETA2 is 4.00
96.3 Percent CI for ETA1-ETA2 is (-11.00,30.99)
W = 30.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6761
The test is significant at 0.6742 (adjusted for ties)
Issue R Mann-Whitney Test and CI: Meeting Attendees, Public
Meeting Attendee
Public
N
5
5
Median
11.00
7.00
Point estimate for ETA1-ETA2 is 4.00
96.3 Percent CI for ETA1-ETA2 is (-2.00,21.00)
W = 33.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.2963
The test is significant at 0.2843 (adjusted for ties)
116
Results for: Question A-2 Pre-Meeting Respondents vs. Post-Meeting
Respondents
Issue A Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
3.00
5.00
Point estimate for ETA1-ETA2 is -2.00
96.3 Percent CI for ETA1-ETA2 is (-14.00,9.00)
W = 25.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6761
The test is significant at 0.6752 (adjusted for ties)
Issue B Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
4.00
4.00
Point estimate for ETA1-ETA2 is 0.00
96.3 Percent CI for ETA1-ETA2 is (-16.00,10.01)
W = 27.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 1.0000
The test is significant at 1.0000 (adjusted for ties)
Issue C Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
3.00
9.00
Point estimate for ETA1-ETA2 is -0.00
96.3 Percent CI for ETA1-ETA2 is (-13.99,9.00)
W = 26.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.9168
The test is significant at 0.9155 (adjusted for ties)
Issue D Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
3.00
8.00
117
Point estimate for ETA1-ETA2 is -1.00
96.3 Percent CI for ETA1-ETA2 is (-14.00,10.00)
W = 25.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.7540
The test is significant at 0.7533 (adjusted for ties)
Issue E Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
7.00
5.00
Point estimate for ETA1-ETA2 is -2.00
96.3 Percent CI for ETA1-ETA2 is (-12.99,8.00)
W = 26.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.8345
Issue F Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
6.00
7.00
Point estimate for ETA1-ETA2 is -1.00
96.3 Percent CI for ETA1-ETA2 is (-10.00,6.00)
W = 25.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.7540
The test is significant at 0.7503 (adjusted for ties)
Issue G Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
5.00
8.00
Point estimate for ETA1-ETA2 is -1.00
96.3 Percent CI for ETA1-ETA2 is (-12.00,7.00)
W = 25.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.7540
The test is significant at 0.7503 (adjusted for ties)
118
Issue H Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
8.00
9.00
Point estimate for ETA1-ETA2 is -2.00
96.3 Percent CI for ETA1-ETA2 is (-10.00,8.00)
W = 24.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.5309
The test is significant at 0.5258 (adjusted for ties)
Issue I Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
6.00
5.00
Point estimate for ETA1-ETA2 is 1.00
96.3 Percent CI for ETA1-ETA2 is (-18.00,7.00)
W = 29.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.8345
The test is significant at 0.8330 (adjusted for ties)
Issue J Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
4.00
4.00
Point estimate for ETA1-ETA2 is -0.00
96.3 Percent CI for ETA1-ETA2 is (-20.00,10.00)
W = 27.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 1.0000
The test is significant at 1.0000 (adjusted for ties)
Issue K Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
5.00
4.00
Point estimate for ETA1-ETA2 is 1.00
96.3 Percent CI for ETA1-ETA2 is (-15.00,10.00)
W = 28.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 1.0000
The test is significant at 1.0000 (adjusted for ties)
119
Issue L Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
4.00
6.00
Point estimate for ETA1-ETA2 is -2.00
96.3 Percent CI for ETA1-ETA2 is (-16.00,7.00)
W = 27.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 1.0000
The test is significant at 1.0000 (adjusted for ties)
Issue M Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
4.00
6.00
Point estimate for ETA1-ETA2 is -1.00
96.3 Percent CI for ETA1-ETA2 is (-14.00,6.00)
W = 25.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6761
The test is significant at 0.6723 (adjusted for ties)
Issue N Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
3.00
9.00
Point estimate for ETA1-ETA2 is -1.00
96.3 Percent CI for ETA1-ETA2 is (-10.00,6.00)
W = 23.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.4647
The test is significant at 0.4578 (adjusted for ties)
Issue O Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
4.00
9.00
Point estimate for ETA1-ETA2 is -0.00
96.3 Percent CI for ETA1-ETA2 is (-11.01,9.00)
W = 27.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 1.0000
The test is significant at 1.0000 (adjusted for ties)
120
Issue P Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
4.00
9.00
Point estimate for ETA1-ETA2 is -3.00
96.3 Percent CI for ETA1-ETA2 is (-10.00,7.00)
W = 24.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6015
The test is significant at 0.6004 (adjusted for ties)
Issue Q Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
2.00
5.00
Point estimate for ETA1-ETA2 is -0.00
96.3 Percent CI for ETA1-ETA2 is (-17.01,10.00)
W = 26.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.9168
The test is significant at 0.9153 (adjusted for ties)
Issue R Mann-Whitney Test and CI: Pre-Meeting Respondent, Post-Meeting
Respondent
Pre-Meeting
Post-Meeting
N
5
5
Median
6.00
5.00
Point estimate for ETA1-ETA2 is -1.00
96.3 Percent CI for ETA1-ETA2 is (-10.00,7.00)
W = 25.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6761
The test is significant at 0.6733 (adjusted for ties)
Appendix D
Chi-Square Test for question A-3
121
122
Chi-Square for Question A-3 Meeting Attendees vs. Public
Row variable
Attend
Non
Total
Observed Frequencies
Column variable
Good
Fair
Poor
12
39
30
8
22
14
20
61
44
Total
81
44
125
Row variable
Attend
Non
Total
Expected Frequencies
Column variable
Good
Fair
Poor
12.96 39.528
28.512
7.04 21.472
15.488
20
61
44
Total
81
44
125
Data
Level of
Significance
Number of Rows
Number of
Columns
Degrees of
Freedom
0.05
2
Calculations
fo-fe
3
-0.96
-0.528
1.488
2
0.96
0.528
-1.488
0.007053
0.012984
0.077657
0.142959
Results
Critical Value
5.9915
Chi-Square Test
Statistic
0.4427
p-Value
0.8014
Do not reject the null
hypothesis
Expected frequency
assumption
is met.
(fo-fe)^2/fe
0.071111
0.130909
123
Chi-Square for Question A-3 Pre-Meeting Respondents vs. Post-Meeting Respondents
Row variable
Observed Frequencies
Column variable
Good
Fair
Poor
Pre
9
21
11
Post
3
18
19
Total
12
39
30
Total
41
40
81
Expected Frequencies
Column variable
Good
Fair
Poor
Pre 6.074074 19.74074
15.18519
Post 5.925926 19.25926
14.81481
Total
12
39
30
Total
41
40
81
Calculations
fo-fe
2.925926
-2.92593
1.259259
-1.25926
-4.18519
4.185185
(fo-fe)^2/fe
1.40944
1.444676
0.080328
0.082336
1.153478
1.182315
Row variable
Data
Level of Significance
Number of Rows
Number of Columns
Degrees of Freedom
0.05
2
3
2
Results
Critical Value
5.9915
Chi-Square Test Statistic
5.3526
p-Value
0.0688
Do not reject the null hypothesis
Expected frequency assumption
is met.
Appendix E
Mann-Whitney U Test for question A-4
124
125
Results for: Question A-4 Meeting Attendees vs. the Public
1.) Mann-Whitney Test and CI: Meeting Attendee, Public
Meeting Attendee
Public
N
5
5
Median
5.00
2.00
Point estimate for ETA1-ETA2 is 2.00
96.3 Percent CI for ETA1-ETA2 is (-15.99,36.01)
W = 30.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6015
The test is significant at 0.5888 (adjusted for ties)
2.) Mann-Whitney Test and CI: Meeting Attendee, Public
Meeting Attendee
Public
N
5
5
Median
7.00
2.00
Point estimate for ETA1-ETA2 is 5.00
96.3 Percent CI for ETA1-ETA2 is (-9.99,31.00)
W = 29.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.8345
The test is significant at 0.8325 (adjusted for ties)
3.) Mann-Whitney Test and CI: Meeting Attendee, Public
Meeting Attendee
Public
N
5
5
Median
20.00
8.00
Point estimate for ETA1-ETA2 is 11.00
96.3 Percent CI for ETA1-ETA2 is (-8.00,20.01)
W = 32.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.3472
The test is significant at 0.3443 (adjusted for ties)
4.) Mann-Whitney Test and CI: Meeting Attendee, Public
Meeting Attendee
Public
N
5
5
Median
16.00
4.00
Point estimate for ETA1-ETA2 is 8.00
96.3 Percent CI for ETA1-ETA2 is (-6.00,27.00)
W = 33.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.2506
The test is significant at 0.2492 (adjusted for ties)
126
5.) Mann-Whitney Test and CI: Meeting Attendee, Public
Meeting Attendee
Public
N
5
5
Median
4.00
8.00
Point estimate for ETA1-ETA2 is -4.00
96.3 Percent CI for ETA1-ETA2 is (-27.00,7.00)
W = 22.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.3472
The test is significant at 0.3443 (adjusted for ties)
6.) Mann-Whitney Test and CI: Meeting Attendee, Public
Meeting Attendee
Public
N
5
5
Median
8.00
5.00
Point estimate for ETA1-ETA2 is 3.00
96.3 Percent CI for ETA1-ETA2 is (-7.00,32.00)
W = 30.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6015
The test is significant at 0.5982 (adjusted for ties)
7.) Mann-Whitney Test and CI: Meeting Attendee, Public
Meeting Attendee
Public
N
5
5
Median
15.00
2.00
Point estimate for ETA1-ETA2 is 8.00
96.3 Percent CI for ETA1-ETA2 is (-11.01,27.00)
W = 31.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.4647
The test is significant at 0.4506 (adjusted for ties)
127
Results for: Question A-4 Pre-Meeting Respondent vs. Post-Meeting
Respondents
1.) Mann-Whitney Test and CI: Pre-Meeting, Post-Meeting
Pre-Meeting
Post-Meeting
N
5
5
Median
2.00
3.00
Point estimate for ETA1-ETA2 is -1.00
96.3 Percent CI for ETA1-ETA2 is (-19.00,13.99)
W = 24.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.5309
The test is significant at 0.5284 (adjusted for ties)
2.) Mann-Whitney Test and CI: Pre-Meeting, Post-Meeting
Pre-Meeting
Post-Meeting
N
5
5
Median
3.00
4.00
Point estimate for ETA1-ETA2 is -1.00
96.3 Percent CI for ETA1-ETA2 is (-16.00,11.01)
W = 24.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.5309
The test is significant at 0.5258 (adjusted for ties)
3.) Mann-Whitney Test and CI: Pre-Meeting, Post-Meeting
Pre-Meeting
Post-Meeting
N
5
5
Median
8.00
10.00
Point estimate for ETA1-ETA2 is -2.00
96.3 Percent CI for ETA1-ETA2 is (-12.00,8.00)
W = 23.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.4034
The test is significant at 0.3917 (adjusted for ties)
4.) Mann-Whitney Test and CI: Pre-Meeting, Post-Meeting
Pre-Meeting
Post-Meeting
N
5
5
Median
5.00
11.00
Point estimate for ETA1-ETA2 is -6.00
96.3 Percent CI for ETA1-ETA2 is (-14.00,6.01)
W = 22.5
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.3472
The test is significant at 0.3428 (adjusted for ties)
128
5.) Mann-Whitney Test and CI: Pre-Meeting, Post-Meeting
Pre-Meeting
Post-Meeting
N
5
5
Median
2.00
6.00
Point estimate for ETA1-ETA2 is -2.00
96.3 Percent CI for ETA1-ETA2 is (-14.00,11.00)
W = 25.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.6761
The test is significant at 0.6723 (adjusted for ties)
6.) Mann-Whitney Test and CI: Pre-Meeting, Post-Meeting
Pre-Meeting
Post-Meeting
N
5
5
Median
3.00
5.00
Point estimate for ETA1-ETA2 is -2.00
96.3 Percent CI for ETA1-ETA2 is (-16.00,16.00)
W = 24.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.5309
The test is significant at 0.5284 (adjusted for ties)
7.) Mann-Whitney Test and CI: Pre-Meeting, Post-Meeting
Pre-Meeting
Post-Meeting
N
5
5
Median
5.00
8.00
Point estimate for ETA1-ETA2 is -2.00
96.3 Percent CI for ETA1-ETA2 is (-14.00,6.99)
W = 24.0
Test of ETA1 = ETA2 vs ETA1 not = ETA2 is significant at 0.5309
The test is significant at 0.5258 (adjusted for ties)
Appendix F
Respondent’s rankings for question A-5
129
130
Question A-5 Pre-Meeting Respondents
Rank
Federal
Gov.
State
Gov.
County
Gov.
Local
Munic
Local
Landownders
Industry/
Business
Enviro
Groups
Farm
Groups
Educators
1
0.0
46.4
14.3
17.9
14.3
3.8
3.6
3.8
3.6
2
17.9
14.3
35.7
14.3
3.6
11.5
0.0
3.8
7.1
3
7.1
7.1
25.0
28.6
7.1
3.8
10.7
3.8
3.6
4
21.4
10.7
7.1
14.3
21.4
15.4
3.6
11.5
3.6
5
7.1
7.1
3.6
7.1
14.3
11.5
28.6
11.5
7.1
6
10.7
0.0
3.6
3.6
10.7
19.2
25.0
7.7
10.7
7
0.0
0.0
3.6
14.3
17.9
11.5
14.3
34.6
0.0
8
10.7
3.6
3.6
0.0
7.1
3.8
10.7
19.2
25.0
9
17.9
3.6
0.0
0.0
0.0
19.2
0.0
3.8
35.7
Farm
Groups
6.1
3.0
15.2
3.0
12.1
12.1
27.3
21.2
0.0
Educators
3.0
0.0
6.1
6.1
3.0
9.1
12.1
9.1
45.5
Farm
Groups
14.3
10.7
7.1
7.1
7.1
17.9
17.9
14.3
0.0
Educators
3.7
3.7
11.1
0.0
0.0
3.7
3.7
25.9
40.7
* Highlighted Box is the highest percentage of respondents for the corresponding rank
Question A-5 Post-Meeting
Respondents
Rank
1
2
3
4
5
6
7
8
9
Federal
Gov.
14.3
0.0
2.9
20.0
0.0
11.4
5.7
14.3
28.6
State
Gov.
37.8
13.5
8.1
0.0
10.8
13.5
2.7
13.5
0.0
County
Gov.
15.8
36.8
21.1
2.6
10.5
2.6
7.9
0.0
2.6
Local
Munic.
16.2
18.9
29.7
27.0
0.0
5.4
0.0
0.0
0.0
Local
Landownders
21.2
12.1
12.1
12.1
12.1
12.1
6.1
9.1
3.0
Industry/
Business
2.9
11.4
8.6
17.1
25.7
11.4
14.3
5.7
0.0
Enviro
Groups
8.8
0.0
5.9
8.8
14.7
17.6
14.7
14.7
11.8
* Highlighted Box is the highest percentage of respondents for the corresponding rank
Question A-5 Public Respondents
Rank
1
2
3
4
5
6
7
8
9
Federal
Gov.
11.1
7.4
18.5
3.7
3.7
14.8
11.1
3.7
18.5
State
Gov.
30.8
7.7
15.4
7.7
19.2
7.7
3.8
3.8
3.8
County
Gov.
10.7
17.9
14.3
25.0
14.3
7.1
3.6
7.1
0.0
Local
Munic.
31.0
6.9
13.8
10.3
10.3
6.9
17.2
0.0
3.4
Local
Landownders
17.2
31.0
13.8
13.8
10.3
10.3
0.0
3.4
0.0
Industry/
Business
6.9
10.3
3.4
17.2
6.9
13.8
17.2
20.7
3.4
Enviro
Groups
0.0
17.9
10.7
0.0
21.4
7.1
14.3
14.3
3.6
* Highlighted Box is the highest percentage of respondents for the corresponding rank
Appendix G
Respondent’s rankings for question A-6
131
132
Question A-6 Pre-Meeting Respondents
Rank
Federal
Gov.
State
Gov.
County
Gov.
Local
Munic
Local
Landownders
Industry/
Business
Enviro
Groups
Farm
Groups
Educators
1
0.0
37.5
21.7
34.8
13.6
4.3
4.3
4.3
4.2
2
8.7
8.3
47.8
13.0
0.0
8.7
0.0
4.3
4.2
3
4.3
29.2
13.0
30.4
13.6
0.0
0.0
4.3
0.0
4
39.1
8.3
8.7
4.3
13.6
4.3
8.7
8.7
0.0
5
8.7
8.3
4.3
8.7
18.2
21.7
34.8
0.0
0.0
6
8.7
0.0
4.3
4.3
13.6
21.7
17.4
8.7
16.7
7
0.0
4.2
0.0
4.3
18.2
13.0
21.7
30.4
4.2
8
8.7
4.2
0.0
0.0
4.5
17.4
13.0
30.4
16.7
9
21.7
0.0
0.0
0.0
4.5
8.7
0.0
8.7
50.0
Farm
Group
s
6.5
6.5
16.1
9.7
12.9
19.4
12.9
12.9
3.2
Educators
3.1
0.0
3.1
6.3
3.1
15.6
6.3
15.6
43.8
* Highlighted Box is the highest percentage of respondents for the corresponding rank
Question A-6 Post-Meeting Respondents
Rank
1
2
3
4
5
6
7
8
9
Federal
Gov.
3.2
0.0
3.2
22.6
0.0
9.7
16.1
16.1
25.8
State
Gov.
20.0
11.4
17.1
0.0
17.1
8.6
11.4
14.3
0.0
County
Gov.
25.7
31.4
11.4
2.9
5.7
8.6
8.6
0.0
2.9
Local
Munic
33.3
19.4
22.2
13.9
2.8
2.8
2.8
0.0
0.0
Local
Landownders
20.6
17.6
14.7
11.8
5.9
14.7
11.8
2.9
0.0
Industry/
Business
6.1
12.1
18.2
18.2
24.2
6.1
9.1
6.1
0.0
Enviro
Groups
9.1
0.0
6.1
6.1
18.2
9.1
12.1
24.2
12.1
* Highlighted Box is the highest percentage of respondents for the corresponding rank
Question A-6 Public Respondents
Rank
1
2
3
4
5
6
7
8
9
Federal
Gov.
7.4
7.4
7.4
7.4
18.5
7.4
14.8
0.0
14.8
State
Gov.
25.0
7.1
14.3
10.7
14.3
7.1
0.0
10.7
10.7
County
Gov.
14.3
28.6
21.4
7.1
3.6
7.1
7.1
10.7
0.0
Local
Munic
28.6
14.3
7.1
10.7
14.3
10.7
7.1
0.0
7.1
Local
Landownders
24.1
17.2
24.1
3.4
13.8
3.4
6.9
3.4
3.4
Industry/
Business
6.9
13.8
10.3
6.9
10.3
17.2
6.9
27.6
0.0
Enviro
Groups
3.4
10.3
0.0
27.6
10.3
6.9
13.8
17.2
10.3
Farm
Group
s
11.1
11.1
7.4
7.4
3.7
22.2
18.5
11.1
3.7
* Highlighted Box is the highest percentage of respondents for the corresponding rank
Educators
0.0
0.0
7.4
11.1
3.7
11.1
7.4
18.5
37.0
Appendix H
Chi-Square Test for question B-3
133
134
Chi-Square for Question B-3 Meeting Attendee vs. Public
Observed Frequencies
Column variable
Row variable
0-5
5-10
10-15
Meeting Attendee
48
12
3
Public
25
4
0
Total
73
16
3
Total
63
29
92
Expected Frequencies
Column variable
Row variable
0-5
5-10
10-15
Meeting Attendee 49.98913 10.95652
2.054348
Public 23.01087 5.043478
0.945652
Total
73
16
3
Total
63
29
92
Calculations
fo-fe
-1.98913
1.98913
1.043478
-1.04348
0.945652
-0.94565
(fo-fe)^2/fe
0.07915
0.171947
0.099379
0.215892
0.4353
0.945652
Data
Level of Significance
Number of Rows
Number of Columns
Degrees of Freedom
0.05
2
3
2
Results
Critical Value
5.9915
Chi-Square Test Statistic
1.9473
p-Value
0.3777
Do not reject the null hypothesis
135
Chi-Square for Question B-3 Pre-Meeting Respondents vs. Post-Meeting Respondents
Row variable
Observed Frequencies
Column variable
0-5
5-10
10-15
Pre
17
7
post
31
5
Total
48
12
Row variable
Data
Level of Significance
Number of Rows
Number of Columns
Degrees of Freedom
3
0
3
Total
27
36
63
Expected Frequencies
Column variable
0-5
5-10
10-15
Pre 20.57143 5.142857
1.285714
post 27.42857 6.857143
1.714286
Total
48
12
3
Total
27
36
63
0.05
2
3
2
Calculations
fo-fe
-3.57143
3.571429
1.857143
-1.85714
1.714286
-1.71429
(fo-fe)^2/fe
0.62004
0.46503
0.670635
0.502976
2.285714
1.714286
Results
Critical Value
5.9915
Chi-Square Test Statistic
6.2587
p-Value
0.0437
Reject the null hypothesis
Appendix I
Chi-Square Test for question B-4
136
137
Chi-Square for Question B-4 Meeting Attendee vs. Public
Row variable
attend
Non
Total
Observed Frequencies
Column variable
1
2
3
4
15
24
10
0
14
20
6
2
29
44
16
2
Row variable
attend
Non
Total
Expected Frequencies
Column variable
1
2
3
4
16.27551 24.69388 8.979592 1.122449
12.72449 19.30612 7.020408 0.877551
29
44
16
2
Data
Level of
Significance
Number of
Rows
Number of
Columns
Degrees of
Freedom
3
0
3
6
3
1
4
Total
55
43
98
5
1.683673
1.316327
3
6
2.244898
1.755102
4
Total
55
43
98
Calculations
fo-fe
0.05
fo-fe
2
-1.27551
-0.69388
1.020408
-1.12245
1.316327
0.755102
6
1.27551
0.693878
-1.02041
1.122449
-1.31633
-0.7551
(fo-fe)^2/fe
0.019497 0.115955
1.122449
1.029128
0.253989
1.435691
1.316327
0.324869
5
Results
Critical Value
11.0705
Chi-Square
Test Statistic
6.0190
p-Value
0.3044
Do not reject the null
hypothesis
Expected frequency
assumption
is met.
5
0.099962
0.127858
0.024939
0.148315
138
Chi-Square for Question B-4 Pre-Meeting Respondent vs. Post-Meeting Respondent
Row variable
Pre
Post
Total
Row variable
Pre
Post
Total
Data
Level of
Significance
Number of Rows
Number of
Columns
Degrees of
Freedom
Observed Frequencies
Column variable
1
2
3
7
14
7
10
14
7
17
28
14
5
1
1
2
6
3
2
5
Total
32
34
66
Expected Frequencies
Column variable
1
2
3
5
8.242424 13.57576 6.787879 0.969697
8.757576 14.42424 7.212121 1.030303
17
28
14
2
6
2.424242
2.575758
5
Total
32
34
66
Calculations
0.05
2
fo-fe
-1.24242
0.424242
0.212121
0.030303
0.575758
6
1.242424
-0.42424
-0.21212
-0.0303
-0.57576
(fofe)^2/fe
0.187277
0.013258
0.006629
0.000947
0.136742
0.176261
0.012478
0.006239
0.000891
0.128699
5
Results
Critical Value
11.0705
Chi-Square Test
Statistic
0.6694
p-Value
0.9846
Do not reject the null
hypothesis
Appendix J
Spearman-Rank Correlation Test for willingness to donate and willingness to
participate
139
140
X (Willingness to
Donate)
Y (Willingness to
Participate)
X rank
y
rank
x rank-y
rank
Dif of
ranks^2
3
50
2
48
2
4
1
1
3
60
-59
3481
1
1
1
1
0
0
2
22
2
48
-26
676
2
22
2
48
-26
676
3
50
2
48
2
4
2
22
4
63
-41
1681
3
50
1
1
49
2401
2
22
2
48
-26
676
2
22
1
1
21
441
1
1
1
1
0
0
1
1
1
1
0
0
0
1
1
1
1
0
5
58
3
60
-2
4
2
22
1
1
21
441
2
22
2
48
-26
676
2
22
1
1
21
441
2
22
1
1
21
441
1
1
1
1
0
0
2
22
1
1
21
441
1
1
1
1
0
0
1
1
1
1
0
0
1
1
1
1
0
0
1
1
1
1
0
0
6
60
1
1
59
3481
1
1
1
1
0
0
1
1
1
1
0
0
1
1
1
1
0
0
1
1
1
1
0
0
2
22
2
48
-26
676
2
22
1
1
21
441
2
22
1
1
21
441
2
22
1
1
21
441
5
58
1
1
57
3249
3
50
1
1
49
2401
2
22
1
1
21
441
6
60
2
48
12
144
1
1
1
1
0
0
2
22
1
1
21
441
2
22
2
48
-26
676
1
1
2
48
-47
2209
1
1
1
1
0
0
2
22
1
1
21
441
2
22
2
48
-26
676
2
22
1
1
21
441
141
2
22
1
1
21
441
1
1
1
1
0
0
3
50
2
48
2
4
2
22
1
1
21
441
3
50
1
1
49
2401
2
22
1
1
21
441
2
22
1
1
21
441
2
22
1
1
21
441
6
60
3
60
0
0
4
57
1
1
56
3136
2
22
1
1
21
441
6
60
1
1
59
3481
2
22
1
1
21
441
1
1
1
1
0
0
2
22
1
1
21
441
1
1
1
1
0
0
1
1
1
1
0
0
3
50
1
1
49
2401
Sum
44034
r=
-0.056883641
Appendix K
Spearman-Rank Correlation Test for respondent income and willingness to
participate
142
143
X (Income)
Y (Willingness to
participate)
X rank
1
1
1
1
1
2
1
1
1
2
1
1
1
4
1
1
1
1
0
5
4
5
5
4
5
4
5
4
3
4
5
3
3
5
5
3
2
2
1
1
1
1
1
1
3
2
2
2
2
2
23
2
2
2
23
2
2
2
42
2
2
2
2
1
51
42
51
51
42
51
42
51
42
28
42
51
28
28
51
51
28
23
23
2
2
2
2
2
2
28
x rank-y
rank
y rank
2
3
1
2
2
2
4
1
2
1
1
1
1
3
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
2
1
2
2
1
2
1
1
1
44
56
1
44
44
44
59
1
44
1
1
1
1
56
1
44
1
1
1
1
1
1
1
1
1
1
1
1
1
1
44
1
1
1
1
1
44
1
44
44
1
44
1
1
1
-42
-54
1
-42
-42
-21
-57
1
-42
22
1
1
1
-14
1
-42
1
1
0
50
41
50
50
41
50
41
50
41
27
41
7
27
27
50
50
27
-21
22
-42
-42
1
-42
1
1
27
Dif of
ranks^2
1764
2916
1
1764
1764
441
3249
1
1764
484
1
1
1
196
1
1764
1
1
0
2500
1681
2500
2500
1681
2500
1681
2500
1681
729
1681
49
729
729
2500
2500
729
441
484
1764
1764
1
1764
1
1
729
144
3
2
3
3
4
3
3
3
4
3
3
4
3
5
28
23
28
28
42
28
28
28
42
28
28
42
28
51
2
1
1
1
1
1
3
1
1
1
1
1
1
1
44
1
1
1
1
1
56
1
1
1
1
1
1
1
r=
-16
22
27
27
41
27
-28
27
41
27
27
41
27
50
Sum
256
484
729
729
1681
729
784
729
1681
729
729
1681
729
2500
66103
0.931706604
(Excel
Equation)
Appendix L
Spearman-Rank Correlation Test for respondent age and willingness to
participate
145
146
X (Age)
X rank
2
2
2
2
2
2
2
2
2
2
2
2
2
5
2
2
2
2
5
4
3
4
2
4
5
4
4
2
4
4
5
3
4
5
5
5
4
2
2
4
2
3
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
56
1
1
1
1
56
34
29
34
1
34
56
34
34
1
34
34
56
29
34
56
56
56
34
1
1
34
1
29
1
1
1
Y (Willingness to
participate)
2
3
1
2
2
2
4
1
2
1
1
1
1
3
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
1
2
1
1
2
2
1
1
2
y rank
49
61
1
49
49
49
64
1
49
1
1
1
1
61
1
49
1
1
1
1
1
1
1
1
1
1
1
1
1
1
49
1
1
1
1
1
1
49
1
1
49
49
1
1
49
x rank-y rank
-48
-60
0
-48
-48
-48
-63
0
-48
0
0
0
0
-5
0
-48
0
0
55
33
28
33
0
33
55
33
33
0
33
33
7
28
33
55
55
55
33
-48
0
33
-48
-20
0
0
-48
Dif of ranks^2
2304
3600
0
2304
2304
2304
3969
0
2304
0
0
0
0
25
0
2304
0
0
3025
1089
784
1089
0
1089
3025
1089
1089
0
1089
1089
49
784
1089
3025
3025
3025
1089
2304
0
1089
2304
400
0
0
2304
147
2
2
4
4
4
3
2
4
3
4
4
4
4
4
4
4
5
4
5
1
1
34
34
34
29
1
34
29
34
34
34
34
34
34
34
56
34
56
1
1
1
2
1
1
1
1
1
3
1
1
1
1
1
1
1
1
1
1
1
1
49
1
1
1
1
1
61
1
1
1
1
1
1
1
1
1
0
0
33
-15
33
28
0
33
28
-27
33
33
33
33
33
33
55
33
55
Sum
r=
0
0
1089
225
1089
784
0
1089
784
729
1089
1089
1089
1089
1089
1089
3025
1089
3025
75824
-0.735897436
Appendix M
Spearman-Rank Correlation Test for respondent residence and willingness to
participate
148
149
X
(Residence)
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
1
3
3
4
3
4
6
4
3
1
6
1
3
4
2
3
4
3
3
1
5
3
1
3
5
3
3
1
X rank
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
1
10
10
42
10
42
53
42
10
1
53
1
10
42
7
10
42
10
10
1
51
10
1
10
51
10
10
1
Y
(Willingness
to participate)
2
3
1
2
2
1
1
1
1
1
3
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
2
1
1
2
2
1
2
1
1
1
2
1
1
y rank
43
52
1
43
43
1
1
1
1
1
52
1
1
1
1
1
1
1
1
1
1
1
1
1
1
43
1
1
1
1
1
43
1
1
43
43
1
43
1
1
1
43
1
1
x rank-y rank
-33
-42
9
-33
-33
9
9
9
9
9
-42
9
9
9
9
9
0
9
9
41
9
41
52
41
9
-42
52
0
9
41
6
-33
41
9
-33
-42
50
-33
0
9
50
-33
9
0
Dif of
ranks^2
1089
1764
81
1089
1089
81
81
81
81
81
1764
81
81
81
81
81
0
81
81
1681
81
1681
2704
1681
81
1764
2704
0
81
1681
36
1089
1681
81
1089
1764
2500
1089
0
81
2500
1089
81
0
150
4
3
4
3
3
2
4
3
4
2
42
10
42
10
10
7
42
10
42
7
1
3
1
1
1
1
1
1
1
1
1
52
1
1
1
1
1
1
1
1
41
-42
41
9
9
6
41
9
41
6
Sum
1681
1764
1681
81
81
36
1681
81
1681
36
43870
r=
-0.672193634
Appendix N
Spearman-Rank Correlation Test for respondent education and willingness to
participate
151
152
X
(Education)
18
14
18
18
12
17
14
18
17
18
16
18
18
17
26
14
15
15
16
16
16
15
16
16
19
20
16
18
21
12
19
16
16
16
17
16
20
17
16
18
20
16
16
X rank
45
8
45
45
1
40
8
45
40
45
21
45
45
40
61
8
13
13
21
21
21
13
21
21
55
57
21
45
60
1
55
21
21
21
40
21
57
40
21
45
57
21
21
Y
(Willingness
to
participate)
y rank
1
1
1
1
1
1
1
2
1
1
1
1
1
3
1
2
1
1
2
2
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
46
1
1
1
1
1
58
1
46
1
1
46
46
1
1
46
1
1
1
1
1
1
1
1
1
1
1
1
1
46
1
1
1
1
1
1
x rank-y
rank
44
7
44
44
0
39
7
-1
39
44
20
44
44
-18
60
-38
12
12
-25
-25
20
12
-25
20
54
56
20
44
59
0
54
20
20
20
39
20
11
39
20
44
56
20
20
Dif of ranks^2
1936
49
1936
1936
0
1521
49
1
1521
1936
400
1936
1936
324
3600
1444
144
144
625
625
400
144
625
400
2916
3136
400
1936
3481
0
2916
400
400
400
1521
400
121
1521
400
1936
3136
400
400
153
18
13.5
12
15
16
15
13
15
12
14
16
12
15.5
14
16
15
16
16
45
7
1
13
21
13
6
13
1
8
21
1
20
8
21
13
21
21
3
1
2
1
1
2
3
1
2
2
2
4
1
2
1
1
1
1
58
1
46
1
1
46
58
1
46
46
46
61
1
46
1
1
1
1
-13
6
-45
12
20
-33
-52
12
-45
-38
-25
-60
19
-38
20
12
20
20
Sum
r=
169
36
2025
144
400
1089
2704
144
2025
1444
625
3600
361
1444
400
144
400
400
67006
-0.771708091
Appendix O
Spearman-Rank Correlation Test for respondent income and willingness to
donate
154
155
X (Income)
4
3
1
3
1
1
1
1
1
2
1
1
1
2
1
1
1
4
1
1
1
1
5
4
5
4
5
4
5
4
3
4
5
3
3
5
5
3
2
2
1
1
1
1
1
X rank
64
41
1
41
1
1
1
1
1
34
1
1
1
34
1
1
1
64
1
1
1
1
76
64
76
64
76
64
76
64
41
64
76
41
41
76
76
41
34
34
1
1
1
1
1
Y (Willingness to
donate)
2
2
1
2
3
1
1
2
2
3
2
3
2
2
1
1
1
5
2
2
2
2
2
1
1
1
1
6
1
1
1
1
2
2
2
2
5
3
6
1
2
1
1
2
2
y rank
36
36
1
36
73
1
1
36
36
73
36
73
36
36
1
1
1
79
36
36
36
36
36
1
1
1
1
81
1
1
1
1
36
36
36
36
79
73
81
1
36
1
1
36
36
x rank-y
rank
Dif of
ranks^2
28
5
0
5
-72
0
0
-35
-35
-39
-35
-72
-35
-2
0
0
0
-15
-35
-35
-35
-35
40
63
75
63
75
-17
75
63
40
63
40
5
5
40
-3
-32
-47
33
-35
0
0
-35
-35
784
25
0
25
5184
0
0
1225
1225
1521
1225
5184
1225
4
0
0
0
225
1225
1225
1225
1225
1600
3969
5625
3969
5625
289
5625
3969
1600
3969
1600
25
25
1600
9
1024
2209
1089
1225
0
0
1225
1225
156
1
3
3
2
3
3
4
3
3
3
4
3
3
4
5
5
4
1
1
2
1
1
1
1
1
2
3
1
3
3
3
1
3
3
4
3
1
1
3
1
41
41
34
41
41
64
41
41
41
64
41
41
64
76
76
64
1
1
34
1
1
1
1
1
34
41
1
41
41
41
1
41
41
64
41
1
1
41
2
1
3
2
3
2
2
2
6
2
6
2
1
2
2
1
2
1
1
1
2
2
1
1
2
1
1
1
2
2
1
1
1
2
1
2
1
1
1
36
1
73
36
73
36
36
36
81
36
81
36
1
36
36
1
36
1
1
1
36
36
1
1
36
1
1
1
36
36
1
1
1
36
1
36
1
1
1
-35
40
-32
-2
-32
5
28
5
-40
5
-17
5
40
28
40
75
28
0
0
33
-35
-35
0
0
-35
33
40
0
5
5
40
0
40
5
63
5
0
0
40
Sum
1225
1600
1024
4
1024
25
784
25
1600
25
289
25
1600
784
1600
5625
784
0
0
1089
1225
1225
0
0
1225
1089
1600
0
25
25
1600
0
1600
25
3969
25
0
0
1600
104613
r
0.059157639
Appendix P
Chi-Square Test for revised question A-3
157
158
Chi-Square for Revised Question A-3 Pre-Meeting Respondents vs. Post-Meeting
Respondents
Observed Frequencies
Column variable
Row variable
Good
Poor
Pre
30
11
Post
21
19
Total
51
30
Total
41
40
81
Expected Frequencies
Column variable
Row variable
Good
Poor
Pre 25.81481 15.18519
Post 25.18519 14.81481
Total
51
30
Total
41
40
81
Data
Level of Significance
Number of Rows
Number of Columns
Degrees of Freedom
0.05
2
2
1
Results
Critical Value
3.8415
Chi-Square Test Statistic
3.7098
p-Value
0.0541
Do not reject the null hypothesis
Expected frequency assumption
is met.
Calculations
fo-fe
4.185185 -4.18519
-4.18519 4.185185
(fo-fe)^2/fe
0.678516 1.153478
0.695479 1.182315
159
Chi-Square for Revised Question A-3 Meeting Attendee vs. Public
Observed Frequencies
Calculations
Column variable
fo-fe
Row variable
Good
Poor
Total
Attend
51
30
81 -2.77869 2.778689
Non
30
11
41 2.778689 -2.77869
Total
81
41 122
Expected Frequencies
Column variable
Row variable
Good
Poor
Total
Attend 53.77869 27.22131
81
Non 27.22131 13.77869
41
Total
81
41 122
Data
Level of Significance
Number of Rows
Number of Columns
Degrees of Freedom
0.05
2
2
1
Results
Critical Value
3.8415
Chi-Square Test Statistic
1.2712
p-Value
0.2595
Do not reject the null hypothesis
Expected frequency assumption
is met.
(fo-fe)^2/fe
0.143572 0.283642
0.283642 0.560366
Appendix Q
Chi-Square Test for revised question B-3
160
161
Chi-Square for Revised Question B-3 Pre-Meeting Respondents vs. The Public
Observed Frequencies
Column variable
Row variable
0
1
5-Feb
Random
2
6
4
Pre
1
3
9
Total
3
9
13
10-May
2
1
3
Total
14
14
28
Expected Frequencies
Column variable
0
1
39483
1.5
4.5
6.5
1.5
4.5
6.5
3
9
13
39578
1.5
1.5
3
Total
14
14
28
1.5
-1.5
-2.5
2.5
0.5
-0.5
0.5
0.5
0.961538
0.961538
0.166667
0.166667
Row variable
Random
Pre
Total
Data
Level of Significance
Number of Rows
Number of Columns
Degrees of Freedom
0.05
3
4
6
Calculations
fo-fe
0.5
-0.5
Results
Critical Value
12.5916
Chi-Square Test Statistic
3.2564
p-Value
0.7760
Do not reject the null hypothesis
Expected frequency assumption
is met.
(fofe)^2/fe
0
0