A PROPOSAL FOR RESEARCH
ON
CONSERVATION OPPORTUNITY AREAS AND ECOLOGICAL INTEGRITY:
THE CAPACITY OF COMMUNITY-BASED INITIATIVES TO CONTRIBUTE TO
SUCCESSFUL ECOSYSTEM MANAGEMENT
By
Natalie Jones Mountjoy
B.A., University of Kentucky, Kentucky 2002
M.S., Western Kentucky University, Kentucky 2007
Submitted in Partial Fulfillment of the
Requirements for the degree of
Doctor of Philosophy
in
Zoology
Southern Illinois University at Carbondale
ABSTRACT
Grass-roots conservation efforts, implemented at the local level, have become
increasingly popular within the U.S. and abroad, and the conservation and natural resource
literature has touted these initiatives as more effective when compared to top-down management
efforts. As localities are given more responsibility for managing their own natural resources,
their capacity to do so effectively has become a major concern.
Thirty-two Conservation Opportunity Areas (COAs) have been designated in the state of
Illinois, providing 32 distinct community-based initiatives for study (CBIs). I will assess the
relationship between the level and various dimensions of capacity (i.e. leadership, funding, and
partnerships) in the COAs and the quality of resource management planning. I will also examine
the relationship between the quality and various dimensions of resource management plans (i.e.,
resource inventory, ownership patterns, goals and objectives) and successful conservation by
measuring ecological integrity of management areas in which adequate time has lapsed. These
analyses will illuminate the relationships between community capacity and conservation success.
I will also explore external forces that can influence capacity (i.e., network strength) and
ecological integrity (i.e., conservation easements).
My study will quantifiably evaluate community capacity using social indicators and
conservation planning using ecological indicators, providing a valuable tool for CBIs working
towards conservation goals. This information will fill a gap in the conservation literature by
evaluating the potential contribution of CBIs with data on ecological integrity. It will also
provide an opportunity for case-study analyses of one of the most pressing questions in
conservation today, namely the capacity of community-based initiatives to contribute to
successful ecosystem management.
1
INTRODUCTION
“There is no clearer illustration of the extent of human dominance of Earth than the fact
that maintaining the diversity of ‘wild’ species and the functioning of ‘wild’ ecosystems will
require increasing human involvement” (Vitousek et al., 1997). Since the Endangered Species
Act of 1973 and foundation of the discipline of conservation biology in 1978, a systematic effort
has been underway to stem the loss of biodiversity in the U.S and globally; yet, the crisis persists
and humans seem to be unable to meet the challenges ahead.
The Biodiversity Crisis and Conservation Biology
Consensus exists in the scientific community: we are experiencing a period of mass
extinction, largely due to human causes (Soulé, 1991, and references therein). Of known species,
35% of invertebrates, 70% of plants, 37% of freshwater fish, 30% of amphibians, 28% of
reptiles, 12% of birds and 21% of mammals are threatened with extinction (International Union
for the Conservation of Nature [IUCN], 2009). If current trends continue, the extinction rate is
estimated to reach 1,000 to 10,000 times higher than the background rate found in the fossil
record (Pimm, Russell, Gittleman, & Brooks, 1995), and 15-37% of all species will be
“committed to extinction” by the year 2050 (Thomas et al., 2004). By the year 2100, one-half of
all species may be extinct (Wilson, 2002).
Conservation biology is a crisis-oriented discipline created in response to the loss of
species. Its primary objective is to combat the loss of biodiversity across the globe (Soulé, 1985).
Its official foundation is marked by the First International Conference of Conservation Biology
in 1978 at the San Diego Wild Animal Park, initiated by Michael E. Soule and Bruce Wilcox
(Gibbons, 1992). The meeting drew together scientists from diverse fields including ecology,
genetics, biogeography, and natural resource management (Gibbons, 1992), and was prompted
2
by growing concerns of habitat destruction, disappearing species, and loss of genetic diversity
within species (Douglas, 1978). Founders knew the discipline would be multidisciplinary (Figure
1) and that partnerships between the biological and social sciences would be particularly
important (Soulé, 1985).
Figure 1: The Multi-disciplinary facets of conservation biology (from Soulé, 1985).
The realization that social dimensions are integral to conservation biology has been slow
to develop (Argrawal & Gibson, 1999). Instead, conservation biology has traditionally focused
on what Salafsky and Margoluis (2002) describe as the “high, hard ground.” Progress has been
made in answering vastly important biological questions such as: which species are endangered
or threatened with extinction (ICUN, 2009); what leads to shrinking population size (Caughley,
1994; Gilpin & Soulé, 1986; Johnson, 2003; Vitousek et al., 1997); which areas are the most
important to protect (Myers et al., 2000; Reld, 1998); and the appropriate size needed for parks
and reserves to best protect biodiversity (Armbruster & Lande, 1993; Burkey, 1989).
Unfortunately, gaining this basic understanding of species’ status and the causes of biodiversity
loss has not led to significant biological conservation.
3
In 2002, the International Union for the Conservation of Nature (IUCN) developed the
2010 Biodiversity Target to attain a significant reduction in the current rate of biodiversity loss
(ICUN, 2009). A 2009 report published by the International Union for Conservation of Nature
(ICUN), Wildlife in a Changing World, provides a dismal appraisal of our ability to reverse the
declining trend and shows the target will not be met.
The current biodiversity crisis coupled with our inability to halt to species decline has led
to serious questions for the practice of conservation biology. Returning to the roots of
conservation biology as outlined by Soulé (1985), Salafsky and Margoluis (2002) argue that now
is the time to ask the “messy but fundamental questions” that require a multi-disciplinary
approach from biology and sociology: “(1) What should our goals be and how do we measure
progress in reaching them? (2) How can we most effectively take action to achieve conservation?
(3) How can we do conservation better?” The answers will require an understanding of
ecological and social systems. As the new trend of community-based conservation grows, these
questions beg our attention.
From Top-down Regulation to Community-based Natural Resource Management
The traditional approach to Salafsky and Margoluis’s messy questions was simple; more
regulation equals more conservation; more regulation equals success. However, the statistics of
the continuing crisis show that approach to be insufficient at best; adversarial and detrimental at
worst.
The first federal law regulating commercial animal markets was the Lacey Act of 1900
(16 U.S.C. §§ 3371-3378), which primarily reinforced other federal, state, and foreign laws
protecting wildlife. It was followed by several Acts, including the Migratory Bird Conservation
Act of 1929 (16 U.S.C. 715-715d, 715e, 715f-715r), the Bald Eagle Protection Act of 1940 (16
4
U.S.C. 668-668d, 54 Stat. 250), and the Land and Water Conservation Fund Act of 1965 (16
U.S.C. 4601-1h). The most well-know and far-reaching legislation is The Endangered Species
Act of 1973 (16 U.S.C. 1531-1544, 87 Stat. 884), which gave the government many new powers
of regulation including authorizing the determination and listing of endangered and threatened
species, the acquisition of land for the conservation of listed species, and the assessment of
penalties for violating the Act.
There are multiple biological reasons that the Endangered Species Act is insufficient for
total biodiversity protection (Rohlf, 1991), but the social implications of the legislation are
adversarial and detrimental. The majority of habitat required by nearly 75% of the species listed
under the act is located on nonfederal lands and 37% of threatened and endangered species are
dependent on private lands for suitable habitat (Government Accountability Office, 1994).
Therefore, to effectively conserve most species on the list, cooperation is required from private
landowners. However, landowners are often fearful of the possible restrictions placed on their
property if listed species use it for habitat (Wilcove et al., 1996). In an effort to stave off
regulation, landowners have been known to destroy acceptable habitat, directly harm listed
species on their land, and/or deny researchers from investigating wildlife populations on their
property (Brook et al., 2003; Wilcove et al., 1996). The Act illustrates the distrust and tension
that exists between government regulation and private rights (Polasky & Doremus, 1995).
Another example is the 1969 National Environmental Policy Act (NEPA), which was criticized
for “promoting an adversarial context (resulting) in increased alienation, apathy and mutual
distrust between federal management agencies and citizens” (Bergman & Kemmis, 2000, as
referenced in Fleeger & Becker, 2006).
5
The failures of top-down conservation practices illustrated the limited capacity of
governments to force their populace into unpopular conservation programs (Argrawal & Gibson,
1999). The poor outcomes following years of this type of intrusive strategy have forced policy
makers and researchers to reexamine the role of the community in conservation initiatives in the
past decade. A movement away from top-down management strategies towards communitybased natural resource management has begun (Argawal & Gibson, 1999; Armitage, 2005;
Bradshaw, 2003; Chaskin, Brown, Venkatesh, & Vidal, 2001; Fleeger & Becker, 2006; Pavey,
Muth, Ostermeier, & Steiner, 2007).
Natural resource management sectors are trending away from adversarial, top-down
management approaches (Margerum, 2007) to a bottom-up, citizen-led and organized approach
(Griffin, 1999). Wells and Brandon (1992, as referenced in Argrawal & Gibson, 1999) reviewed
23 conservation initiatives and found that the limitations of top-down conservation policy have
made community-based efforts the only logical choice. These efforts are thought to: ease
tensions between governments (i.e.federal, state and local) and private landowners (Brook, Zint,
& De Young, 2003; Griffin, 1999; Habron, 2003); increase citizen participation (Foster-Fishman,
2007; Lasker, & Weiss, 2003); better attain sustainable ecological goals (Bradshaw, 2003; de
Loe & Kreutzwiser, 2005; Leigh, 2005).
It is generally accepted that community involvement in ecosystem management is a key
to success (Mendis-Millard and Reed, 2007). Non-governmental organizations, including the
World Bank, Conservation International, The Nature Conservancy (TNC), The Ford Foundation,
The MacArthur Foundation, and USAID, support this new community-based approach
(Argrawal & Gibson, 1999), forcing academics and managers to take the movement seriously.
6
Community perspectives, once neglected, are now understood to be an essential component of
successful ecosystem management (Folke et al. 2005, as referenced in Frabicious, 2007).
Grassroots or local community-based initiatives (CBIs), also referred to as
comprehensive community initiatives (Chaskin, 2001), community capacity building initiatives
(Craig, 2007), comprehensive community-building initiatives (Foster-Fishman et al., 2007),
community partnerships (Proven et al., 2005), or community coalitions (Foster-Fishman,
Berkowitz, Lounsbury, & Allen, 2001) are not unique to natural resource management. Health
services (Goodman et al., 1998; Foster-Fishman et al. 2007; Provan et al., 2005), community
development (Craig, 2007; Cotrell, 1983; Foster-Fishman et al., 2007), environmental health and
sustainability (Bonnell & Koontz, 2007; Borden et al, 2007; Gahin et al., 2003) and urban
growth and planning (Beckley et al., 2008; Chapin & Connerly, 2004) sectors are also directing
efforts to the local level to better achieve their goals. The forms of CBIs vary widely across
municipalities and disciplines, but all seek to increase “active citizenry” and view community
participation as fundamental to success, leading to more effective solutions (Foster-Fishman et
al., 2007).
The overall approach of community-based natural resource management (CBNRM), a
type of community-based initiative, seeks to foster participation from community members,
resource users, and local institutions in decision making, while relying on customary practices
and knowledge systems for enforcement and regulation to improve resource management
outcomes (Armitage, 2005 and references there in). Here the term CBNRM is used as inclusive
of other similar initiatives such as watershed councils (Borden et al., 2007; Griffin, 1999),
natural community conservation planning (Reid & Murphy, 1995), community-based watershed
management (Rhoads, Wilson, Urban, & Herricks, 1999), community-based conservation
7
(Berkes, 2004), community-based ecosystem management (Gray et al., 2001; Mendis-Millard &
Reed, 2007), collaborative natural resource management (Conley & Moote, 2003), and
community-based integrated environmental management (Rhoads et al. 1999). Although subtle
differences exist among these initiatives, Gray et al. (2001) identified four key principles that
community-based ecosystem management efforts share:
1. Stakeholders acknowledge ecosystem health and services as a critical part of the
community;
2. Resource decisions are made by collaborative processes, involving people who know the
land and are affected by management decisions;
3. Equity is sought in the distribution of ecosystem benefits (i.e., ecological services,
resource use, and processing) to sustain local capacity; and
4. Citizens and their communities are acknowledged as fundamental components of
ecosystems.
Currently, there are more than 3,000 of these initiatives operating across the country, which are
now being touted as the “new holy grail” of ecosystem conservation (Craig, 2007). The
approach, however, is not without limitations as delegating natural resource management to the
community level affords benefits and challenges (Gray et al., 2001; Bradshaw, 2003; Fleeger &
Becker, 2006; Margerum, 2007). As control over natural resources has devolved to the local
level, the question of a community’s capacity to meet conservation challenges has become
increasingly important (Beckley et al., 2008; Bradshaw, 2003; de Loe & Kreutzwiser, 2005;
Margerum, 2007; Mendis-Millard & Reed, 2007).
CAPACITY
Communities can differ in two major ways: in the resources or capital at their disposal,
and/or in their ability to use what they have to achieve their goals (Marre & Weber, 2007).
Consequently, studies of community capacity seek to determine the resources or capital available
to, and the functions or processes that can best allow, a community to meet their collective
objectives.
8
Conceptualizing Capacity
Development of a widely accepted definitional framework for capacity has been difficult.
Multiple authors have conducted literature reviews, field work, focus groups, and case studies to
define, conceptualize, and indentify the key components of capacity (Armitage, 2005; Chaskin,
2001; Cotrell, 1983; Craig, 2007; Foster-Fishman et al., 2001; Mendis-Millard & Reed, 2007).
Defining Community Capacity. Competent communities (Cottrell 1983), community
sustainability (Parkins et al. 2001), community stability (Machlis 1990) and community
collaboration (Foster-Fishman et al. 2001) are conceptually similar to community capacity
(Mendis-Millard & Reed, 2006). Goodman et al. (1998) identified two working definitions of
community capacity as “the characteristics of communities that affect their ability to identify,
mobilize, and address social and public health problems” and, “the cultivation and use of
transferable knowledge, skills, systems, and resources that affect community- and individuallevel changes consistent with public health-related goals and objectives.”
Chaskin et al. (2001) defines capacity as “the interaction of human capital, organizational
resources and social capital existing within a given community that can be leveraged to solve
collective problems and improve or maintain the well being of a given community.” Beckley et
al. (2008) developed their own definition of capacity as “the collective ability of a group to
combine various forms of capital within institutional and relational contexts to produce desired
results or outcomes.” Although Chaskin’s (2001) definition is widely accepted, no agreement on
a common definition exists (Beckley et al., 2008) and the pervasiveness of literature focused on
defining and conceptualizing capacity have led to calls for research to move past the definitional
debate into a much-needed methodological development of the constructs used to define capacity
(Donoghue & Sturtevant, 2007).
9
The dimensions of community capacity. In 1995, the CDC (Center for Disease Control)
constructed eight key aspects of community capacity: (1) participation and leadership; (2) skills,
of both participants and leaders; (3) resources (i.e., capital, technological, and social); (4) social
and interorganizational networks (i.e., structural characteristics, relationships, and benefits
received); (5) sense of community (i.e., how is it achieved and how to maintain it); (6)
understanding of community history to understand the past and improve decision-making; (7)
community power; (8) community values, clear and from a consensus; and (9) critical reflection
and critical thinking to reform communities (Goodman et al., 1998). Other authors have
highlighted the types of capacity required for successful CBIs: 1- member capacity, including
core skills and knowledge, attitudes and motivations, and access to capacity; 2- relational
capacity, focused on positive internal and external relationships and positive external
relationships; 3-building organizational capacity and 4- programming capacity (Foster-Fishman
et al., 2001).
The framework developed by Chaskin et al. (2001) is thorough and comprehensive, with
every component operationalized in full detail (Figure 2). However, there is a disconnect
between this type theoretical and an applied understanding of community capacity (Beckley et
al., 2008). Recently, in an attempt to simplify the dimensions of capacity, many have broken the
concept down into just two parts (Figure 3): community assets (as foundational or as
catalysts/mobilizers) and the outcomes desired (Beckley et al., 2008; Donoghue and Sturtevant,
2007; Mendis Millard & Reed, 2007). This simpler model allows for a more practical application
of the dimensions of capacity for problem solving and analysis.
10
(5) Conditioning Influences
Safety
Residential stability
Density of acquaintances
Structure of opportunity
Influences of migration
Race and class dynamics
Distribution of poor and resources
(1) Characteristics of Community Capacity
Sense of community
Commitment
Ability to solve problems
Access to resources
(2) Levels of social agency
Individuals
Organizations
Networks
(4) Strategies
Leadership
Organizational development
Organizing
Organizational collaborations
(3) Functions
Planning, decision-making and
governance
Production of goods and services
Information dissemination
(6) Other Outcomes
Better Services
Influencing decision-making
Economic well-being
Figure 2. Community capacity and capacity building: a relational framework (from Chaskin et al., 2001).
Assets
Foundational
Physical capital
Financial capital
Natural capital
Social capital
Human capital
Political capital
Mobilizing
Social capital
Human capital
Political capital
Actions & Outcomes
 Meet community needs
 Respond to external and
internal threats
 Create opportunities
 Take advantage of
opportunities
 Produce desired outcomes
Figure 3. A simplified conceptualization of community capacity (from Donoghue & Sturtevant, 2007).
Foundational assets. A focus on defining the foundational characteristics, capital, assets,
elements or indicators required for capacity is common in literature involving CBNRM and
conservation (Armitage, 2005; Baum, 1998; Beckley et al., 2008; Bonnell & Koontz, 2007;
Brody et al., 2004; Chaskin, 2001; Donoghue & Sturtevant, 2007; Fleeger & Becker, 2006;
Foster-Fishman et al., 2001; Frabricious, 2007; Goodman et al., 1998; Hancock, 1999; and
11
Mendis-Millard & Reed, 2007) and are often regarded as endogenous factors (Beckley et al.
2008), as they are inherent in the community itself.
There is a large amount of overlap among various models of capital (Table 1).
Researchers frequently recognize three types: (1) physical capital, including community
infrastructure and economic resources (i.g., sewer systems, open space, business parks, housing,
schools, and financial capital); (2) human capital (e.g., skills, education, and experience of
residents); (3) social capital (e.g., the ability and willingness of residents to work together for
community goals) (Donoghue & Sturtevant 2007; Kussel, 1996). Social capital is unique in that a
large amount of research has been dedicated to the subject. A well-known and broadly accepted
model was authored by Putnam (1993). His concept of social capital has three primary
components: moral obligations and norms; social values, focusing on trust; and social networks
with emphasis on voluntary associations (Putnam, 1993). Recently, authors have recognized a
fourth type of capital, ecological capital (Cosborga, 1997), which includes forest resources, soil
resources, aesthetics, mineral resources, wildlife resources, water quality and air quality
(Beckley et al., 2008).
12
Table 1. Types and capital and corresponding indicators from the literature
Beckley et al.
(2008)
Mendis-Millard
& Reed (2007)
Ecological Capital
Forest resources
Soil resources
Aesthetics
Mineral resources
Wildlife resources
Water quality
Air quality
Environmental assets
Drawbacks and threats
What needs improvement
Environmental values
Environmentally sound
practices
Perception of environment
Extant biodiversity values
Natural biodiversity in
nurseries
Economic/ Built Capital
Property tax revenue
Municipal infrastructure
Personal savings
Value of real estate
Municipal bond rating
Number of businesses
Stability and success of
businesses
Economy
Resource-based economies
Employment opportunities
Economic diversity
Economic
Viability/sustainability
Physical infrastructure
Housing concerns
Monetary resources
Financial resources
Fundraising
Financial resources
Human Capital
Education attainment
Dependency ratio
Quality of leadership
Quantity of leadership
Life skills
Trade and technical training
Entrepreneurship
Economic prosperity
Health
Education
Skills
Innovation
Creativity
Engagement
Participation
Population and demographics
Education
The biosphere reserve concept
Skills, experiences, and talents
Types of professionals in the
area
Characteristics of individuals
Willingness
Health issues
Economic uncertainty
Attitudes, values, beliefs
Knowledge
Skills
Experience
Moore et al.
(2006)
Hancock (1999)
Environmental quality
Healthy ecosystems
Sustainable resources
Conservation
Habitat
Wildlife
Biodiversity
Social Capital
Extent of barrier
Participation at events
Number of voluntary
associations
Bridging social capital
Bonding social capital
Density of acquaintanceship
Social networks
Togetherness and cooperation
Volunteerism and engagement
Communication
Gatherings and events
Youth activities
Social norms
Trust & reciprocity
Values and attitudes
Behavior
Commitment
Motivation
Sense of place
Structural Networks
Social networks
Social development programs
Social cohesion
Civic nature
Governance processes
Equitable assets
13
Mobilizing assets. The exogenous factors affecting capacity are often refered to as
mobilizers or catalysts (Armitage, 2005; Beckley et al., 2008) and comprise conditioning
influences that may encourage or impede community-based initiatives (Chaskin et al. 2001).
These factors which include safety, residential stability, density of acquaintances, degree of
opportunity, race and class dynamics, community autonomy, security, and innovative leadership,
among others, enhance community capacity under difficult circumstances (Chaskin, 2001;
Fiszbien, 1999). The social and human capital present as endogenous or foundational assets can
also serve as mobilizers or impediments to progress depending on their presence or absence in a
community (Beckley et al., 2008; Donoghue & Sturtevant 2007; and Mendis-Miller & Reed,
2007).
Adaptability and Resiliency. Many analysts focus on the various components of adaptive
capacity are important to CBIs (Table 2). CBIs must remain resilient to negative exogenous
circumstances (i.e., external political, economic, and ecological threats) while simultaneously
adapting to a changing system (Armitage, 2005; Fabricius, Folke, Cundill, & Schultz, 2007;
Olsson, Folek, & Hahn, 2004; Pavey et al., 2007; Krebs & Holley, 2005; Walker, Gunderson,
Kinzig, Folke, Carpenter, & Schultz, 2006). The resilience of a social-ecological system is built
upon its ability to adapt (Pavey et al., 2007). Adaptive capacity in CBNRM is defined as a
“critical aspect of resource management that reflects learning and ability to experiment and
foster innovative solutions in complex social and ecological circumstances” (Armitage, 2005).
Adaptability is primarily determined by the quality and quantity of all forms of capital and the
system of institutions and governance (Walker et al., 2006), and is recognized as a crucial
component in a CBI’s capacity to achieve desired outcomes (Armitage, 2005).
14
Table 2. Dimensions of adaptive capacity
Component
Learning to live with uncertainty, change
Subcomponent
Learn from crises
Expect the unexpected
Evoke disturbance
Nurture diversity for reorganization and renewal
Nurture ecological memory
Sustain social memory
Enhance socio-ecological memory
Combine different types of knowledge for learning Combine experiential and experimental knowledge
Integrate knowledge of structure and function
Incorporate process knowledge into institutions
Encourage complementarity of knowledge systems
Create opportunities for self-organization
Recognize relationship between diversity and disturbance
Deal with cross-scale dynamics
Match scales of ecosystems and governance
Account for external drivers
Source: Folke et al. (2003), as referenced in Armitage (2005).
Outcomes and goals. Chaskin et al. (2001) defines the products of capacity as
“functions” (i.e., planning, decision-making and governance, production of goods and services
and information dissemination) and as “outcomes” (e.g., better services). Donoghue and
Sturtevant (2007) further define outcomes as “responses to external and internal threats; creation
and taking advantage of opportunities; and production of desired outcomes.” Community-based
initiatives can operate protectively, to maintain the status quo, or proactively, to effect change
(Beckley et al., 2008). Some groups center on finding long-term solutions to issues while others
establish shorter-term goals (Beckley et al,. 2008). The outcomes sought are equally diverse as
the CBIs operating across the U.S. to achieve goals in various sectors.
ACHIEVING SUCCESS
Although much research is centered on defining and conceptualizing capacity in CBIs,
the best ways and means to define and measure success in CBNRM initiatives remain under
debate. Few studies have quantifiably analyzed how the amount or type of capacity in a CBNRM
organization directly affects the outputs and/or environmental outcomes produced. What defines
a successful CBNRM initiative?
15
Defining Success
There are three primary ways success is defined in CBNRM initiatives: (1) through
positive collaborative processes; (2) achieving desirable social outcomes; or (3) achieving
desirable environmental outcomes (Table 3) (Kinney, 2000; Koontz & Thomas, 2006). Research
grounded in collaborative processes and social outcomes has been extremely popular, and some
authors combine the two criteria together (compare Conley & Moote, 2003; Kinney 2000; and
Koontz & Thomas, 2006); however, researchers are now turning to measurements of the actual
environmental outcomes that CBNRM groups produce as the best way to define success.
Table 3. Typical evaluation criteria of CBNRM initiatives
Process criteria
Broadly shared vision with clear, feasible goals
Diverse, inclusive participation
Participation by local government
Linkages to individuals and groups beyond primary participants
Open, accessible, and transparent process
Clear, written plan
Consensus-based decision making regarded as just
Consistent with existing laws and policies
Social Outcome criteria
Relationships built or strengthened and increased trust
Participants gained knowledge and understanding
Increased employment
Improved capacity for dispute resolution
Changes in existing institutions or creation of new institutions
Environmental Outcome criteria Improved habitat
Land protected from development
Improved water quality
Changed land management practices
Biological diversity preserved
Soil and water resources conserved
Source: Conley & Moote (2003), referenced Blumberg (1999), Born & Genskow (2000), d’Estree & Colby (2000),
Innes (1999), KenCairn (1998) and Lead Partnership Group (2000)
Collaborative process. Evaluation research focusing on process criteria, such as
mediation, negotiation, and the building of agreements among competing stakeholders, is the
most common (Snow, 2001, as referenced in Koontz & Thomas, 2006). Numerous case studies
and analyses of such collaborative processes have been published since 1990 and include: group
dynamics (Cheng & Daniels, 2005); increasing citizen participation (Fleeger & Becker, 2006);
individual and group activism (Foster-Fishman et al., 2007); organizational challenges (Bonnell
16
& Koontz, 2007); and, participant behavior (Bauhm, 1998). Proponents argue that the
collaborative processes involved in CBIs lead to better decisions, effective and equitable
solutions, increased citizen-capacity for self-governance, and more accounting than traditional
adversarial approaches (Koontz & Thomas, 2006, and references there in). Although there are
still disagreements about the normative value of collaboration as a process, a shift towards
defining success based on outcomes is needed (Koontz & Thomas, 2006).
Social Outcomes. Kenney (2000) argued that are two different definitions of outcomebased success currently in place to evaluate CBNRM. Success can defined through social
outcomes (e.g., improved relations and trust, increased communication and commitment to
"green" goals) or achievements of specific on-the-ground goals described in terms of improved
environmental outcomes and ecological integrity, defined as “the ability of an ecological system
to support and maintain a community of organisms that has species composition, diversity, and
functional organization comparable to those of natural habitats within a region” (Kenney 2000;
Parrish et al., 2003). Research shows that collaborative CBIs lead to increased trust and social
capital (Leach & Sabatier 2005; Lubell, 2005) and proponents of CBNRM argue that these social
outcomes are important indicators of success (Conley & Moote, 2003). However, calls are being
made to shift the focus to ecological outcomes as a means to evaluate the success of CBNRN
initiatives (Kinney, 2000; Koontz & Thomas, 2006).
Environmental outcomes. A move towards measuring success via environmental
outcomes is not meant to downplay the importance of the social impacts of CBNRM initiatives,
which have obvious ramifications for society as a whole (Koontz & Thomas, 2006). The
argument that collaborative, bottom-up processes have normative merit, regardless of their
outcomes, is compelling, but ultimately the products of collaborative-based processes merit
17
current enthusiasm only if they are a means to a productive end (Kinney 2000). Any CBI,
whether it is focused on achieving goals in public health, juvenile delinquency or conservation,
must be judged by its ability to actually meet its goals and effect change in the areas of concern
(Kinney, 2000). The most crucial question in CBNRM remains unanswered and often unasked.
To what extent does collaboration lead to improved environmental outcomes? (Koontz &
Thomas, 2006). If CBNRM is to be taken seriously by conservationists and natural resource
managers, it too must judged by outcomes (Kinney 2000; Leach, Pelkey, & Sabatier, 2002).
Evaluating Successful Conservation
To better assess a CBNRM group’s success in meeting its goals, it is helpful to
distinguish between outputs and outcomes. Outputs are the activities, plans, projects, and other
tangible items generated by CBNRM initiatives (e.g., agreements, resource management plans,
education and outreach, and changes to public policy) (Donoghue & Sturtevant, 2007).
Outcomes are the effects of those outputs on environmental conditions (e.g., changes in
environmental quality and changes in land cover and biodiversity) (Koontz & Thomas, 2006).
Evaluating outputs. Concrete outputs vary widely among CBNRM initiatives, but many
efforts center on reaching agreements for partnerships, and creating natural resource
management plans (RMPs), which establish the management objectives and goals for a specified
area of land (Koontz & Thomas, 2006). CBNRM groups are encouraged to author natural RMPs
by government authorities who offer funding and assistance to do so. For example, section 319
in the Clean Water Act provides funding to local CBNRM organizations to develop management
plans for their watersheds, through the Environmental Protection Agency (Davenport et al.,
1996) and in 2003 the Department of the Interior, Bureau of Reclamation published a Resource
18
Management Plan Guidebook to provide, practical, hands-on information on how to prepare a
RMP (Department of the Interior, 2003).
Table 4. Existing Measures of Environmental Outputs and Outcomes
Measures
Environmental Outputs
Agreements reached (e.g., management plans and
characterization reports)
Restoration or habitat improvement projects completed (e.g.,
restoration of vegetation, morphology, or biota; trash
removed)
Data-Collection Methods
Group surveys and interviews; document analysis
Group surveys and interviews; document analysis
Changes to public policy
Group surveys and interviews; government official
interviews
Changes to land management practices (e.g., best
management practices adopted)
Group surveys and interviews; landowner surveys
Education and outreach campaigns conducted
Group surveys and interviews; document analysis
Programs implemented (e.g., total maximum daily load
programs)
Group surveys and interviews; document analysis;
government official interviews
Land protected from development (e.g., new regulations,
land/easement purchases, or special designations)
Group surveys and interviews; document analysis;
government official interviews
Environmental Outcomes
Perceptions of changes in environmental quality Group
Group surveys and interviews
surveys and interviews
Changes in land cover
Remote sensing
Changes in biological diversity (at the genetic, species, or
Ecological studies
landscape levels)
Changes in environmental parameters appropriate to a
specific resource (e.g., water biochemical oxygen demand,
Ecological studies
ambient pollution levels, or contaminant discharge rates)
Source: From Koontz & Thomas 2006, referenced Born and Genskow (2000); Conley and Moote (2003); Imperial
(1999); Koontz and Johnson (2004); Koontz et al. (2004); Leach, Pelkey, & Sabatier (2002); Schweik and Thomas
(2002); Yaffee et al. (1996).
Conservation easements are outputs also generated by CBNRM groups. Conservation
easements are “restrictions placed on real property to protect its natural resource values or those
of ecologically related properties” (The Nature Conservancy [TNC], 2004). Easements are either
voluntarily sold or donated by the landowner and constitute legally binding agreements that limit
certain types of uses or development in perpetuity. Conservation easements can protect the
natural values of land for future generations while allowing owners to retain certain property
rights and to live on and use their property (TNC, 2004). Since the late 1800’s, governments and
19
non-profit organizations have relied on acquisitions like easements as their primary approach to
land conservation (Merenlander et al., 2003). Although area under conservation easement has
increased drastically since 1990, the effectiveness of such programs to lead to improved
ecological health in an area remains relatively unknown (Merenlander et al., 2003).
Evaluating conservation outcomes. Outputs must be assessed by their ability to achieve
conservation outcomes to evaluate CBNRM effectively (Koontz & Thomas, 2006). As
conservation biology is a sub-discipline of biology, the practice should theoretically be
evidenced-based, but the consequences of conservation action and outputs are rarely
documented, reviewed, or dispersed (Pullin, Knight, Stone, & Charmen, 2004). Consequently,
management decisions are not based on scientific evidence but rather anecdotal sources
(Sutherland et al., 2004). Sutherland et al. (2004) analyzed 61 management decisions made in the
UK and found that 77% of the sources consulted were anecdotal (e.g., common sense, personal
experience, and advice from other managers). Using accepted dogma instead of relying on
scientific evidence may result in negative consequences for ecosystems and species (Sutherland
et al., 2004).
Conservation actions would benefit greatly from an evidence-based approach to
determine if outputs (e.g., resource management plans and conservation easements) are working
(Sutherland, 2004). Without an evidence-based approach, how can decision makers know which
conservation action to take regarding habitat quality, population viability or the proper
functioning of an ecosystem (Pullin et al. 2004)? For conservation action to be effective,
resource managers and decision makers need to know what does and does not work. Decision
makers must know how effective a given action has been in achieving objectives (Pullin &
Knight, 2001).
20
GOALS AND OBJECTIVES
I seek to determine the capacity of Conservation Opportunity Areas (COAs) to contribute
to successful ecosystem management in the State of Illinois (Figure 4). Specifically, I will
analyze the current capacity and ecological health of COAs, evaluate the effects of various levels
of capacity on the outputs (i.e., natural resource management plans) produced by COAs, and
determine the effects of various quality outputs on the potential for COAs to achieve their
primary outcomes (i.e., improved ecological integrity). This multi-disciplinary project
necessitates reliance on the principles of both sociology and ecology, as required by explorations
of socio-ecological systems. This research is an attempt to measure the success of COAs,
operating as CBNRM initiatives, by examining changes in ecological integrity and attainment of
conservation goals. The goals of this study are to provide baseline measurements of capacity and
ecological health in COAs, a model for COAs to improve likelihood of achieving conservation
success, and a framework for evaluating other CBNRM initiatives. I will accomplish these goals
through 5 primary objectives.
Objective I: Assess the current level of capacity in each COA and determine how partnership
network size and strength affect COA capacity.
Objective II: Assess the current ecological status of each COA and examine the relationship
between conservation easement size and age with the current ecological integrity of each COA.
Objective III: Investigate the relationship between capacity in a COA and the quality of the
natural resource management plans produced.
Objective lV: Examine how the quality of a natural resource management plan is related to
trends in the ecological health of the prescribed area.
CAPACITY OF
CBNRM
INITIATIVE
+
+
Size and strength of
partnership
networks
RESOURCE
MANAGEMENT
PLAN QUALITYY
+
ECOLOGICAL
INTEGRITY OF
MANAGED AREA
Quantity, age and size of
conservation easements
+
Figure 4. General model of hypothesized relationships between CBNRM capacity and ecological integrity
21
Units of Analysis: Conservation Opportunity Areas
As part of the Illinois Wildlife Action Plan (IL-WAP) developed in 2005, 32 CBNRM
initiatives, Conservation Opportunity Areas (COAs), were recognized across the state as priority
areas for conserving Illinois’ species in greatest need of conservation (Illinois Department of
Natural Resources [IDNR], 2005). COA boundaries were developed by the Illinois Department
of Natural Resources (IDNR), based upon the presence of important habitats and fish and
wildlife resources, and guided by stakeholder participants in workshops (Appendix 1). A COA is
described as an area with wildlife and habitat resources of statewide importance, partners willing
to be involved, financial and human resources, and an agreed-upon conservation purpose and set
of objectives. COAs were established to serve as the “community arm” of the IDNR in
implementing ecosystem and conservation goals set out by the plan. The COAs comprise various
CBNRM groups (sub-groups), focusing on conservation and sustainability in each area. The
IDNR, TNC and Southern Illinois University Carbondale (SIUC) are providing communication
and coordination support to these local partners.
The IL-WAP provides general information on each COA, as it was available in 2005,
including individual CBNRM sub-groups within each COA, conservation goals, key actions,
protected lands, and priority resources (IDNR 2005). In the summer of 2009, the IDNR
commissioned SIUC to establish a general snapshot of the status of COA planning and to
provide direction for COA coordination and support efforts in the future via an online survey of
COA stakeholders. The survey provided insight into conservation needs throughout state, as
COAs serve as indicators of ecological integrity and the status of conservation efforts. The
results have informed much of development of this research proposal and revealed that the levels
22
of capacity, planning and ecological health in the COAs are highly diverse, making them
excellent units of observation for this research.
Currently the COA coordinator is traveling across the state, meeting with interested subgroups, assisting partnership formation within the COAs and with the IDNR, and is conducting
planning and partnership meetings within each COA. All attendees have a stake in the COA the
meeting pertains to, however, they represent a diverse mix of interests from sportsman and
women to agency staff and scientists and from NGO representatives to nature-lovers and birdwatchers. Every meeting-attendee provides his or her name, address and email address. Each
subgroup is instructed to send any resource management plan they have produced and their
organizational documents to the COA coordinator. These meetings also result in a list of active
subgroups within each COA, lead contacts for each group, and an initial sampling frame for
analysis. As I cannot include a COA in this analysis until collaboration efforts are underway, I
will whenever possible, assist the COA coordinator in planning and moderating these meetings.
As I reference “each” or “every” COA in the following sections, I am referring to every COA
available for analysis in which planning efforts are underway. Meetings have already begun and
by fall 2011 it is expected that the vast majority of COAs, if not all, will begin planning efforts
and be available for analysis.
Summary of Methods
In order to show the link between capacity and conservation a two- part analysis is
required involving a common CBNRM outcome- RMPs. I will determine the current capacity of
COAs using focus groups, quantitative survey instrument, and an organizational document
review. I will collect RMPs and evaluate their quality, using a rubric developed in the literature,
and determine the affects of capacity on the quality of the RMPs. Using the same rubric I will
23
evaluate 5-15 year old RMPs for other natural areas across the state. I will then determine, using
appropriate monitoring data, the ecological trends of the natural areas mange by the old plans,
and compare the variation in ecological trends data with the variation in RMP quality data. By
linking capacity to quality RMPs, then quality RMPs to ecological integrity, I will determine the
relationship between CBNRM group capacity and the likelihood of achieving positive
environmental outcomes.
OBJECTIVE I: ASSESS THE CURRENT LEVEL OF CAPACITY IN EACH COA AND
DETERMINE HOW PARTNERSHIP NETWORK SIZE AND STRENGTH AFFECT
COA CAPACITY.
Capacity can be explored at various levels of social agency: at the individual level,
operating through human capital and leadership; at the organizational level, operating through
collective bodies; or at the network level, operating through relationships between individuals,
informal groups and formal organizations (Chaskin et al., 2001). To best determine the capacity
of CBNRM initiatives, explorations at the organizational level are considered to be the most
appropriate (Agrawal & Gibson, 1999). In measuring the capacity within COAs, the focus will
be on the community of interest (Craig, 2007) in the organizations themselves, not the
community at-large.
Various methods have been employed to measure capacity, including: case studies
(Walker et al., 2006), in-depth interviews (Pavey et al., 2007), document reviews (Margerum,
2007), content analysis (Brody et al., 2004), focus groups (Pavey et al., 2007), and surveys
(Fiszbien, 1997). As capacity is a complex concept, multiple methods are often employed
(Fiszbien, 1997; Margerum, 2007; Mendis-Millard & Reed, 2007) and indicators the used vary
across community types (Fiszbien, 1997; Margerum, 2007; Mendis-Millard & Reed, 2007, Table
24
5). Although most assessments rely on a sampling of the indicators in listed Table 1 (Beckley,
2008), indicator selection must be individualized, based on the CBI under analysis, as indicators
of extreme importance in some areas may be less so in others. Assessors also vary among
professionals, sociologists, agency staff, or community residents and group members themselves
(Donoghue & Sturtevant, 2007).
Table 5. Description of assessments of capacity
Indicators
Instrument
Measure
Community 1
Physical infrastructure,
human capital, civic
responsiveness
Ratings by social scientists
and community practitioners
at workshops
Single score capacity rating
from 1-7 (low-high)
Community 2
Civic leadership, social organization,
economic structure, physical amenities and
attractiveness
Community resident questionnaires and
workshops
Community resiliency index comprised of
four components measured by quartiles as
low, medium low, medium high and high
Source: Donoghue and Sturtevant (2007) and references therein
Community 3
Physical infrastructure,
human capital and social
capital
Community and county
questionnaires and
workshops
Single score capacity
rating from 1-5 (lowhigh)
The indicators used to measure capacity vary (Table 5). Although most assessments rely
on a sampling of the indicators in table 1 (Beckley, 2008), the indicators must be conceptualized
individually, based on the community or CBI under analysis, as indicators of extreme importance
in some areas may be less so in others. Assessments also vary in who performs the assessment
(i.e. professionals, sociologists, and agency staff, or community residents and group members
themselves) (Donoghue & Sturtevant, 2007).
Methods To Assess Capacity
Selection of appropriate indicators for this analysis began first by listing indicators found
in the literature (Table 1). The list was narrowed and augmented based on data from the COA
preliminary survey. The list of indicators and measurement tools are subject to change (Table 6).
I will use focus groups, an on-line quantitative survey and organizational document review to
assess capacity within the COA subgroups and each COA as a whole.
25
Table 6. Potential indicators of capacity within COAs
Potential Indicators
Skills-Professions
Human Capital Education
Leadership
Demographics
Staff/Volunteers
Partnerships
Organization
Communication
Participation
Organizational
Capacity
Leadership
Adaptability
Civic Involvement
Community
Outreach
Funding
Attitudes
Commitment
Social
Capital
Sense of Place
Community History
Partnership
Network
Connectedness
Strength
Possible Measurement
Subjective
Diversity of professions of members
Highest education level obtained by each member
Number of members in leadership roles
Age and race
Number of staff/volunteers
Adequacy of staff/volunteers
survey
Number of official partnerships
Importance of partnerships
Attitudes regarding partnership
survey
Health of current partnerships
Number of meetings, distance traveled by participants
Opinions on organization within the group
survey
Minutes kept, announcements
Opinions on communication within the group
survey
Number of members at meetings
Perceived group participation
survey
Does the group have a mission statement with
clear goals, objectives and outcomes
Attitudes regarding group leadership
Attitudes regarding leadership of the IDNR
survey
Attitudes regarding municipal leadership
Attitudes regarding academic leadership
Perceived adaptability through scenario questions
survey
Number of group members involved in government
Number of community outreach projects
Importance of community outreach
survey
Satisfaction with community outreach
Amount of funding generated
Diversity of funding sources
Attitudes regarding funding
survey
Towards group itself, the IDNR, COAs and ecosystem management
survey
Average time served by members
Commitment on a scale
survey
Length of time in community
Attitudes regarding
survey
Knowledge of community history on a scale
survey
Number of voluntary meetings among group members survey
Number of contacts among group members
survey
Strength of group member relationships
survey
Objective
survey
survey
records
survey
records
records
records
records
records
records
records
records
records
survey
survey
Focus Groups. To refine the list of indicators further and allow for stakeholder input on
the survey design, I will conduct focus groups among subgroup members in four to six COAs,
depending on time and assistance personnel available. Focus groups are an excellent way to elicit
input from various types of stakeholders and increase the quality of survey questions (Chambliss
& Schutt, 2010). I have selected 6 potential COAs that are representative of the variation among
26
all 32 COAs, based on the preliminary survey (Table 7). Each focus group will comprise 6-8
stakeholders (Krueger & Casey, 2000) from the subgroups of each focus COA.
I will conduct purposively select participants from the lists of attendees to COA planning
meetings to ensure diversity among my focus group attendees (e.g, famers, sportsmen and
women, agency staff, conservationists, bird watchers, etc.). Potential participants will receive an
email inviting them to participate in the study (Appendix 2) and a follow-up phone call (Krueger
& Casey, 2000). Each attendee will sign a waiver (Appendix 3) and I will ask each to complete
an information form (Appendix 4). Focus groups will consist of a guided discussion of capacity
within their organizations, centering on what they believe to be important indicators of capacity
and the best ways to structure survey questions to provide a reliable measurement of those
indicators. I will tape record each focus group and an assistant will take detailed notes. Using the
computer-aided long table approach I will review the data to further augment or redact the list of
indicators already developed and to assist in development of the survey questions (Krueger &
Casey, 2000).
Web Survey. A web survey is an electronic survey accessed and responded to on the
internet; they are efficient, versatile, and can allow for generalizable results (Dillman, 2000).
Web surveys are becoming increasingly popular because they are also flexible and inexpensive
(Chambliss & Schutt 2010). In addition, as some of our potential respondents have already taken
the preliminary survey online, the format will be familiar to some. I will construct an online
survey, following parameters set out by Dillman (2000), to measure the capacity indicators I
have selected. The survey will comprise open- and closed-ended questions (e.g., Likert-type
(1932) questions involving scaled possible responses), both objective and subjective in nature
(Dillman, 2000). Several questions will be used to measure each indicator to allow for indexing,
27
Table 7. Highlighted COAs have been selected as potential focus COAs
COA1
Hill Prairie Corridor-South
Wisconsin Driftless Forest
N2
4
4
Priority
invasives
forests & savannas
Major Threat
invasives
invasives
structure/ infrastructure, loss of
habitat, pollutants/ sediment
L3
S
N
Natural Division
Ozark
Wisconsin Driftless
Habitat Type
forest, savanna-barren, primary
forest, savanna-barren, primary
Sinkhole Plain
1
outreach
NE
Ozark
savanna-barren, grassland, primary
Kankakee Sands
15
forests & savannas, outreach
habitat quality
NE
Grand Prairie
9
9
wetlands
forests & savannas
loss of habitat, invasives
loss of habitat
SW
N
LaRue-Pine Hills
7
forests & savannas
pollutants/ sediment
S
Eastern Shawnee
Apple River
Lower Kaskaskia Bottomlands
Upper Mississippi River
7
5
4
2
forests & savannas
wetlands
forests & savannas
forests & savannas, outreach
invasives
habitat quality, pollutants/ sediment
loss of habitat
loss of habitat, habitat quality
S
NW
SW
NW
Rock River Hills
Rock River Hills
Lwr Miss Bttmlnd, Ozark, Sawnee
Hills
Shawnee Hills
Wisconsin Driftless
Southern Till Plain
Uppr Miss Bttmland
Middle Illinois River
24
wetlands
invasives
C
Uppr Miss Bttmland
Vermilion River
Prairie Ridge Landscape
19
10
wetlands, streams
grassland & shrub
habitat quality
habitat quality
E
SC
Wabash Border
Southern Till Plain
Lake-McHenry Wetland Complex
8
wetlands
invasives
NE
Northeast Moraine
Midewin
7
wetlands
invasives
NE
Pere Marquette
7
forests & savannas
invasives
W
Kishwaukee River
Lower LaMoine River
Cache River-Cypress Creek
6
3
9
streams
forests & savannas
wetlands
pollutants/ sediment
invasives
invasives
N
E
S
Grand Prairie
Midd Miss Border, Uppr Miss
Bttmlnd, Wstrn Forest-Prairie
Northeast Moraine
Wsrtn Forest-Prairie
Coastal Plain
Mason County Sand Areas
8
wetlands
habitat quality, invasives
C
Sand Areas
Illinois Beach-Chiwaukee Prairie
5
invasives
invasives, hydrology
NE
Lake Michigan, Northeast Moraine
Upper Des Plaines River Corridor
3
wetlands
invasives
NE
Northeast Moraine
Hill Prairie Corridor-North
Siloam Springs
Middle Little Wabash
Lower Fox River
Pyramid-Arkland Landscape
3
1
2
13
2
grassland & shrub
forests & savannas
forests & savannas, wetlands
streams
invasives
invasives
invasives
loss of habitat, invasives
loss of habitat
invasives
W
W
SE
NE
S
Lost Mound
3
streams
loss of habitat
NW
Green River
Wabash River
4
4
grasslands & shrub
streams
NC
SE
Nachusa
2
forests & savannas
loss of habitat, habitat quality
hydrology, invasives
loss of habitat, habitat quality,
invasives
Grand Prairie COA?
Wsrtn Forest-Prairie
Wabash Border
Grand Prairie
Southern Till Plain
Sand Areas, Uppr. Miss Bttmlnd,
Wisconsin Driftless
Grand Prairie
Wabash Border
savanna-barren, grassland, emergent
wetland, stream
forested wetland, stream
stream
forest, savanna-barren, grassland,
forested wetland, cave, primary
forest, savanna-barren, primary
stream, primary
forest, forested wetland, stream
forested wetland, stream, lake & pond
emergent wetland, stream, lake &
pond
forest, stream
grassland, emergent wetland
savanna-barren, grassland, emergent
wetland, lake & pond
grassland
forest, savanna-barren, stream,
primary
emergent wetland, stream
forest, savanna-barren
forested wetland
savanna-barren, grassland, emergent
wetland, lake & pond
emergent wetalnd, lake and pond,
primary
savanna-barren, emergent wetland,
stream
?
forest, savanna-barren
forested wetland, stream
stream
grassland, emergent wetland
forest, savanna-barren, grassland,
forested wetland, stream, primary
grassland, emergent wetland, stream
forested wetland, stream, lake & pond
Sugar - Pecatonica
Rock River
N
Rock River Hills
forest, grassland
1
COAs are listed in order of their ability to fulfill IDNR requirements of COAs (as established by the initial survey)
Number of stakeholders who took the initial survey for that COA
3
Location: N (north) S (south) E (East) and W (West)
2
27
a composite measure based on combining responses to different questions intended to measure
the same idea, considered a more complete way to measure a concept (Chambliss & Schutt,
2010).
Using a census sampling approach, every COA subgroup member who attends a
partnership meeting will be invited to take the web survey (Appendix 5). A sampling frame will
be constructed using the list of COA subgroups and contacts made during the COA planning
meetings. As the IDNR has not completed planning meetings in all COAs, estimating a sample
size is difficult. I believe we will find well over 640 active participants among the COAs (an
average of 20 per COA) and hope for response rate of at least 50%, yielding a sample of 320,
which is sufficient for multivariate analysis. In populations where internet use is common,
response rates of 70-80% on web surveys are not uncommon (Chambliss & Schutt, 2010). The
survey will provide a measurement for each indicator of capacity on a scale from 1 (low) to 5
(high), in each COA subgroup and each COA.
Organizational document review. I will thoroughly review all pertinent documents
associated with each COA subgroup (i.e., financial statements, meeting minutes, strategic plans
and annual reviews) to measure the remaining indicators of capacity in listed in Table 6.
Documents will be obtained via contacts in the COA subgroups made at the COA planning
sessions. I will measure each indicator on a scale form 1 (low capacity) to 5 (high capacity).
Analysis. These scores will then be tallied with the measurements of indicators from the
online survey, resulting in scores for each indicator of capacity within each sub-group and COA
as a whole, and a net capacity score for each sub-group and COA.I will complete an analysis of
variance and principal components analysis on the data to investigate the variation in capacity
within the COA subgroups and across the COAs. I will also explore relationships between and
28
among the various indicators of capacity and overall capacity scores. Through factor and
reliability analysis, I will create indices of capacity indicators (i.e., leadership, human resources,
etc.) to use in later analysis. Some indicators may be more important than others, which ones to
weight will be apparent from the component loadings in the factor analysis.
Ethical issues and limitations. I will seek approval from the IRB Human Subjects
Committee for this research and will receive informed consent from all participants. Focus group
participants and survey respondents will be informed that participation is strictly voluntary and
of the confidential nature of their responses. The most limiting nature of this design is that the
survey will only be made available on-line, which means anyone without access to the internet
will not receive an invitation or be able to participate. This is a significant weakness because
CBIs greatly benefit from members with long-term community knowledge and the most
knowledgeable individuals may be elderly, and less likely to have internet access. As the list of
members and their email addresses grows, I will identify the scale of this limitation. If the
number of COA subgroup members without email addresses is too high, I may create mail
surveys to reach this particular segment in the COAs. Another key limitation is that some
indicators of capacity can only be measured subjectively, and although all the indicators
measured by the survey and document review are found in the capacity literature, the validity of
subjective measurements is somewhat restrictive.
Hypothesis Testing
Partnerships are recognized as a way for communities and organizations to address a
broad range of problems (Povan et al., 2005) and are often cited as key foundation aspects of
community capacity, specifically as collaboration, cooperation, networks and relationships
(Table 1). Collaboration can be defined as “the creation of stakeholder groups to review
29
information, share analysis, identify objectives, develop an agreed strategy, and implement
actions that also involve the public, who have a stake in management outcomes but may not
participate in intensive deliberations” (Margerum, 2007). Major issues with successful
collaboration involve the lack of clarity in systematic frameworks and issues with partners
(either community members themselves or other community organizations). All collaborators
must reach a consensus and have clear responsibilities and the means to meet those
responsibilities for the collaboration to succeed (Chaskin et al., 2001).
Within-community collaboration has become increasingly important in managing natural
resources and will be exceedingly important within the COA subgroups. Creating networks and
linkages with partners can allow communities or organizations with limited capacity in other
areas, to increase their overall capacity (de Loe & Kreutzwiser, 2005). The collaborations
between the COAs and the IDNR are equally important. Partnerships should be explored outside
the community as decoupling collaboration exclusively at the local level and extending its scale
may be more effective (Margerum, 2007). The goal of networks and partnerships is to build
capital so communities will be better able to deal with a variety of problems (Milward & Provan,
1998), and scaling-up collaborative efforts and bringing together higher-level decision makers
can offer increased opportunities for problem solving and help mitigate stumbling blocks
(Margerum, 2007).
Exploratory Analysis. I will conduct mixed participant-observation at partnership
meetings to increase my understanding of collaboration constraints, context, and social
interaction (Chambliss & Schutt, 2010). I will attend all meetings regarding the COAs at the
IDNR headquarters in Springfield, IL and I will take extensive notes. These observations will
allow me to be abreast of current agency objectives and thinking regarding the COAs. I will also
30
attend as many initial COA planning meetings as possible, and take notes at each session. These
observations will allow me to understand the collaborative process as various groups “sign-on”
to work together as a COA. Themes and comments from this qualitative research will add depth
to the network analysis completed as part of hypothesis testing.
Hypothesis: COAs in which subgroup partnerships display strong networks will have
higher capacity scores than COAs in which subgroup partnerships display weak networks.
Methods. Network analysis is a method of collecting and analyzing data from multiple
individuals or organizations that may be interacting with one another, such as the multiple
subgroups working within each COA. I plan to follow the protocol used by Milward and Provan
(1998) and expanded by Provan et al. (2005) to analyze network partnerships for each COA. As
part of the online survey I will ask respondents about their contacts and voluntary associations
with other organizations, allowing them to quantify the strength of that personal/professional
connection. I will make the network questionnaire part of the online survey used to measure
capacity. I will follow the online format for organizational network analysis on survey monkey
as developed by Bruce Hope (2006). My network questionnaire page will allow respondents to
select COA subgroups from a drop-down list, quantify the number of contacts they have in each
subgroup and the strength of each connection on a scale form 1 (very weak) to 5 (very strong).
Analysis. The partnership analysis will allow me to examine the number of COA
subgroups to which each independent subgroup is linked, the total number of links in the
network, the types of interactions between subgroups and the level and strength of the
relationships (Provan et al., 2005) within each COA. Analysis of the partnership networks will
detail the connectedness among COA subgroups. I will then assess the correlation between a
COA’s network strength and capacity score using regression techniques. I will also explore the
31
correlation between network strength and specific indicators of capacity and capital within the
COAs.
Ethical issues and limitations. I will receive SIUC IRB Human Subjects’ Committee
approval for this research. I will also gain informed consent from all meeting attendants, as I
conduct the participant observations at the IDNR and COAs.
OBJECTIVE II: ASSESS THE CURRENT ECOLOGICAL STATUS OF EACH COA
AND EXAMINE THE RELATIONSHIP BETWEEN CONSERVATION EASEMENT
SIZE AND AGE WITH THE CURRENT ECOLOGICAL INTEGRITY OF EACH COA.
Growing environmental concerns coupled with increased pressure on natural resources
have made it extremely important to closely monitor trends in ecological integrity (Vora, 1995),
or system wholeness (Karr, 1991), defined as “the ability of an ecological system to support and
maintain a community of organisms that has species composition, diversity, and functional
organization comparable to those of natural habitats within a region” (Parrish et al., 2003). A
common monitoring framework involves repeated measurements of ecological indicators over
time in areas of specific interest in which monitoring locations may be singular or consist of a
sampling network covering a particular region (Larson et al., 2001). Resource managers have not
developed a handbook describing appropriate indicators of integrity and their desirable levels for
each ecosystem type (Vora, 1997), as the most appropriate measures of environmental conditions
should be based the specific spatial and temporal requirements (Dale & Beyeler, 2001; Broden,
2003).
Critical Trends Assessment Program
The Critical Trends Assessment Program (CTAP), part of the Illinois Natural History
Survey working alongside the IDNR, assesses current and future trends in ecological conditions
32
on a statewide, regional, and site-specific basis. Assessment through CTAP began in 1997 and
continues currently.
Sample site selection. CTAP scientists use the 1,765 Illinois Public Land Survey
Townships as sampling units and sample 4 habitat types: grasslands, forests, wetlands and
streams. Sampling began in 1997. Every year 30 randomly chosen township sites are sampled for
each of the 4 habitat types (the initial 5-year course of the research resulted in 150 sampling sites
per habitat type). GIS field maps detailing landcover type are consulted to determine areas of
acceptable habitat in each township. The acceptable areas are randomly ranked and sequentially
evaluated until a site is identified that fulfills specific habitat criteria and for which landowner
access is granted. The specific habitat criteria vary for each habitat type but the primary criteria
is that all sites be “minimally to moderately managed, currently in a somewhat natural state and
undergoing successional processes such that changes in condition will be possible and
detectable” (Molano-Flores, 2002).
Indicators measured. Biological indicators are used to measure ecological integrity and
to provide early warning signs of changes in environmental conditions (Appendix 6; Dale &
Beyeler, 2001). CTAP relies on plants, birds and terrestrial insects as indicators of terrestrial
ecosystem integrity (i.e., grassland, forest and wetland habitats), and aquatic insects and water
quality indicators to assess aquatic ecosystem integrity (i.e., stream habitats) (Appendix 7)
(Molano-Flores, 2002).
To assess plant, bird, and insect populations, CTAP uses several valid indicators from the
literature. The list includes species richness and diversity (Kessler, 1993; Noss, 1990; and
Woodley, 1993), abundance of native and exotic species (Noss, 1990; Schaeffer, Herricks, &
33
Kerster, 1988), and the numbers of threatened and endangered species at each site (Noss, 1990;
Reid, McNeely, Tunstall, Bryant, & Winograd, 1993).
The Floristic Quality Index (FQI) is a plant-specific indicator used by CTAP and is
recognized as an indicator that can measure the ecological condition of a site overtime, as well as
determine the conservation value and ecological condition of an area (Lopez & Fennessy, 2002).
The FQI is a standardized index based on the coefficient of conservation (C) assigned to each
native species based on the probability a particular species is likely to found in any given area.
Plant species that are generalized and ubiquitous are given low C-scores, whereas species with
specialized requirements and found less often are given high C-scores (Rooney & Rogers, 2002).
Habitat-dependent species (HD) are those that can only be found in a particular habitat
and is a bird-specific indicator used by CTAP. HD is recognized as a valid means to assess forest
and grassland birds (Herkert, 1993; Freemark & Collins, 1992) and wetland-dependent species
(Paine, 1997). Area-sensitive species (AS), another bird specific indicator used by CTAP, are
those species that show different levels of tolerance to habitat fragmentation. These species can
be classified as "high," "moderate," or "low." (Herkert, 1993; Freemark & Collins, 1992).
CTAP relies on three well-known measures: EPT Species, Hilsenhoff Biotic Index (HBI)
and Habitat Quality Index (HQI), along with common water quality indicators (i.e., dissolved
oxygen, fine sediment and conductivity) to assess aquatic ecosystem health. EPT is the number
of taxa of the aquatic insect orders Ephemeroptera, Plecoptera, and Trichoptera from all samples
taken at a site. EPT is recognized as a good candidate for environmental assessment studies
(Sandin & Johnson, 2000). The Hilsenhoff Biotic Index (HBI) (Hilsenhoff, 1982, 1987) is an
abundance-weight average of all species’ pollution tolerance developed to detect organic
pollution in streams. Although originally developed to assess low dissolved oxygen caused by
34
organic loading (Hilsenhoff, 1982, 1987), the HBI may also be sensitive to the effects of
impoundment, thermal pollution, and some types of chemical pollution (Hilsenhoff 1998;
Hooper, 1993). The HBI comprises a cumulative habitat quality score consisting of 12 measures
of in-stream and riparian habitat characteristics for which the scale ranges from 0-180. This
measure is a common indicator used in various U.S. EPA documents (Barbour, Gerritsen,
Snyder, & Stribling, 1999; Plafkin, Barbour, Porter, Gross, & Hughes, 1989).
Methods to Assess Ecological Integrity
I plan to utilize CTAP data to assess the current ecological status of the COAs. Using
GIS, the sampling locations have been georeferenced within the COA boundaries. Twenty-nine
of the 32 COAs contain at least one CTAP sampling location (Table 7). Illinois Beach
Chiwaukee Prairie, Wabash River and the Wisconsin Driftless Forest COAs do not contain any
CTAP sampling locations. As species and pollutants do not recognize artificial boundaries, I will
create 5, 10 and 15 mile buffer zones around each COA and include all CTAP sampling sites
within each expanded boundary for additional analyses. This strategy is to increase ecological
data available for each COA, and to provide ecological data for the Illinois Beach Chiwaukee
Prairie, Wabash River and Wisconsin Driftless Forest COAs, is
As this project unfolds, I will be assisting CTAP researchers in collecting new data
and/or analyzing current data. This will increase my understanding of each ecological indicator
and allow me to familiarize myself with their protocols (complete CTAP sampling protocol is
available at ctap.inhs.uiuc.edu/mp/monitoring.asp).
35
Table 7. Number of CTAP sites within each COA
COA
Kanakakee Sands
Lake McHenry Wetland Complex
Upper Des Plaines River Corridor
CTAP sites (n)
37
24
22
Upper Mississippi River
21
Middle Illinois River
Middle Little Wabash
Pyramid Arkland Landscape
LaRue Pine Hills
Mason County Sand Areas
Vermilion River
Midewin
Green River
Hill Prairie Corridor - North
Section
Lower Kaskaskia Bottomlands
Lower Fox River
20
17
17
13
10
10
8
7
COA
Pere Marquette
Sinkhole Plain
Lower LaMoine River
Hill Prairie Corridor - South
Section
Rock River
Siloam Springs
Lost Mound
Nachusa
Sugar Pecatonica River
Kishwaukee River
Prairie Ridge Landscape
Illinois Beach Chiwaukee Prairie
6
Wabash River
6
5
Wisconsin Driftless Forest
Total CTAP Sites
CTAP sites (n)
5
5
4
3
3
3
2
2
2
1
1
0
0
0
254
Analysis. I will perform principal components analysis on the CTAP data within each
COA and the additional buffer zones (in four separate analyses). These analyses will highlight
the primary ways the ecological integrity of COAs differ and provide a visual map of COAs
ecological indicators along the axes of variation. I will also perform an analysis of variance to
uncover any apparent trends found in the CTAP data and to evaluate significant differences
among the ecological integrity of COAs.
Limitations. Each ecological indicator is accompanied by a unique set of limitations,
which I with deal with independently. Using existing data also comes with limitations; for
example, as the CTAP sampling locations were randomly selected, some COAs have none
within their boundaries. The buffer zones help to address this limitation. Additionally, the
indicators sampled were selected by CTAP, not by myself. Consequently, some indicators I may
have used are not included in analyses, while other indicators included I may not have sampled. I
will investigate each indicator further and only use data from indicators that are widely accepted
in the literature and can be used as a valid measure of the ecological integrity of the COAs.
Hypothesis Testing
36
There are various types of conservation easements in Illinois. All are sponsored by the
United States Department of Agriculture, Natural Resource Conservation Service (NRCS) and
are outlined as follows:
1. Conservation Reserve Programs (CRP) provide technical and financial assistance to
eligible farmers and ranchers to address soil, water, and related natural resource concerns
on their lands (USDA, 2009a).
2. Wetland Reserve Programs (WRP) is a voluntary program offering landowners the
opportunity to protect, restore, and enhance wetlands on their property (USDA, 2009b).
3. Emergency Wetland Reserve Program (EWRP) was established in response to flooding
in 1993 and is targeted specifically at prior-converted wetlands damaged by flooding in
that region (USDA, 2009c).
4. Wildlife Habitat Incentives Programs (WHIP) is a voluntary program for conservationminded landowners who want to develop and improve wildlife habitat on agricultural
land, nonindustrial private forest land, and Indian land (USDA, 2009d).
5. Environmental Quality Incentives Programs (EQIP) were reauthorized in the Farm Bill to
provide a voluntary conservation program for farmers and ranchers that promotes
agricultural production and environmental quality as compatible national goals. EQIP
offers financial and technical help to assist eligible participants install or implement
structural and management practices on eligible agricultural land (USDA, 2009e).
Although many conservation-based NGOs view easements as powerful and effective tools for
the permanent conservation of private lands in the United States (TNC, 2004), the potential for
easements to contribute to ecological integrity remain unknown (Merenlender et al., 2003).
Illinois COAs vary in their current ecological integrity and in the amount of land
currently under conservation easement. To contribute to evidence-based conservation practice, it
would be useful to ascertain the relationship between conservation easements and ecological
integrity.
Hypotheses: COAs with a higher proportion of land under conservation easement will have
higher ecological integrity than COAs with a lower proportion of land under conservation
easement. COAs containing conservation easements of an older mean age will have higher
ecological integrity than COAs containing conservation easements of an younger mean age.
37
Methods. All lands under conservation easement are registered with the IDNR. Using
contacts at the IDNR and GIS analysis, I will determine the proportion of lands under the 5
easement types within each COA. I will also catalogue the date of each easement. I will use the
CTAP data, as explained earlier, to determine the current ecological integrity of each COA.
Analysis. I will use multiple regression techniques to determine the effects of easement
proportion on the current ecological integrity of each COA. I will also use multiple regression
techniques to determine the effects of easement age on the current ecological integrity of each
COA.
Limitations. The limitations for this analysis are similar to the limitations expressed for
the analysis including RMP quality and ecological integrity. Isolating the effects of conservation
easements from other factors that affect environmental conditions is impossible. However, using
a natural experiment of multiple case studies with some similarities (like the COAs) is regarded
as the optimal way to assess the effects of outputs, like conservation easements, on ecological
outcomes.
OBJECTIVE III: INVESTIGATE THE RELATIONSHIP BETWEEN CAPACITY IN A
COA AND THE QUALITY OF THE NATURAL RESOURCE MANAGEMENT PLANS
PRODUCED.
Natural RMPs are recognized as a common output of CBNRM initiatives, however,
research on their substantive content and effectiveness is surprisingly uncommon (McDonald,
McAlpine, Taylor, & Vagg, 2002). Berke et al. (1999) applied plan evaluation techniques to
local RMPs to determine if plans lead to sustainable development, and if they achieve balance
by supporting all sustainability principles or narrowly promote some principles more than others.
Berke et al. (2006) found that higher-quality RMPs led to better education, communication, and
38
policy guidelines, which affected implementation. The most relevant analysis was conducted by
Brody (2003), who compared multiple stakeholder involvement with the quality of RMPs
produced by CBNRM groups. Plan quality is increasingly used as an outcome to evaluate both
the planning process and implementation process (Brody, 2003). I propose to use plan quality as
a measurable outcome of subgroups in the COAs and as indicator of potential success. I plan to
investigate how the capacity of each COA is related to the quality of RMPs produced by the
COA or COA subgroups.
Hypothesis: Higher-capacity COAs will generate higher-quality RMPs than lower capacity
COAs.
Methods. The IDNR originally set out to have the COA subgroups produce a single plan
to manage each COA. However, as assistance with collaboration efforts began, the COA
coordinator realized asking each sub-group to negate their existing RMP and create a new one
with new partners would be combative and not well received. Some COAs will collaborate and
create a new COA-level RMP, and eventually the IDNR would prefer that outcome from each
COA. Nevertheless, the IDNR is satisfied with partnership agreements and multiple RMPs
utilized within some COAs.
I will conduct a content analysis of RMPs produced by COA subgroups and COAs. The
RMPs produced are currently provided to the COA coordinator after the initial COA planning
meetings. I will assess RMP quality using the evaluation criteria set out by Brody (2003). This
evaluation rubric (Appendix 8) was designed to assess RMPs by their abilities to represent and
apply the principles of ecosystem management (Brody, 2003). Brody conceptualized plan quality
through five components:
1. Factual basis: understanding and inventory of existing resource issues, environmental
policies, and stakeholders’ interests within the ecosystem.
2. Goals and objectives: guide the implementation of ecosystem management.
39
3. Interorganizational coordination and capabilities: the ability of a local jurisdiction to
collaborate with neighboring jurisdictions and organizations to manage what are often
transboundary natural resources.
4. Policies, tools, strategies and policies: the heart of a plan because they set forth actions to
protect critical habitats and related natural systems.
5. Implementation: must be clearly defined and specified for all affected parties.
Brody developed indicators for each plan component, measured on an ordinal scale, with 0
being not identified or mentioned, 1 being suggested or identified but not detailed, to 2 being
fully detailed. In cases where the indicators themselves have multiple manifestations (i.e., habitat
quality can be mapped, catalogued or both), Brody averaged the indicators to create an item
index. For example, if a RMP received a 1 for habitat mapping and a 1 for habitat cataloging, the
overall indicator score would be a 1. The total plan score is then determined by adding the
indicator scores for each plan component, then dividing that number by the total possible score,
and multiplying the fractional score by 10. There are five plan components; therefore, the
maximum score possible for each RMP is 50.
Analysis. For COAs with one RMP, I will compare the overall COA capacity with the
quality of the single RMP. In COAs with multiple RMPs, I will compare the COA subgroup
capacity with the quality of the RMP produced, as well as the overall COA capacity with the
average quality of the RMPs produced. I will use multiple regression and possibly structural
equation modeling to explore the relationship between capacity and RMP quality. I will also
determine which indicators of capacity are most closely correlated with overall RMP quality as
well as with individual RMP components.
Limitations. It is possible, though not probable, that no RMP exist for some COAs, in
which case the COA will have to be dropped from analysis. On the contrary, in larger COAs like
the Upper Mississippi, an exceptionally large number of RMPs may exist, making evaluation of
each plan difficult if not impossible due to time constraints. It is also possible that I may not find
40
enough variation in RMP quality among the COAs. After the first few analyses are complete, if I
find variation to be insufficient, I will re-evaluate plans with a refined rubric, possibly by
extending the scale of measure from 0-2 to 0-6 to increase variation.
OBJECTIVE LV: EXAMINE HOW THE QUALITY OF A NATURAL RESOURCE
MANAGEMENT PLAN IS RELATED TO TRENDS IN THE ECOLOGICAL HEALTH
OF THE PRESCRIBED AREA.
Conceptualizing the relationship between capacity and quality of RMPs does not equate
capacity with increased ecological integrity. To do that, another link must be investigated: how
the quality of a RMP affects the ecology of the managed area. Assessing the environmental
effects of management on ecological integrity outputs is difficult; CBNRM initiatives suffer
from a lack of funding and relevant expertise to do so completely and competently (Leach, et al.,
2002). Even with proper funding and knowledge, it is difficult to link management processes
with environmental outcomes for three primary reasons, as recognized by Koontz and Thomas
(2006). First, finding and gathering appropriate data that measure environmental outcomes is
difficult because few groups monitor the environmental conditions that result from their own
actions. Second, monitoring must begin before a group implements a management plan and
continue for decades until ecological results can be measured. Lastly, designing research studies
that can isolate the effects of particular conservation actions from the multiple interacting
variables that shape environmental change, is complicated and nearly impossible (Koontz &
Thomas, 2006).
Hypothesis: Areas managed according to higher quality RMPs will show more positive
trends in ecological integrity than areas managed according to lower quality RMPs
Methods. I propose evaluating RMPs developed for areas in Illinois 15-20 years ago
using the same evaluation rubric from Brody (2003). I will refer to these yet-to-be-determined
41
areas, “eco-interest areas.” Using the CTAP data from the first (1997- 2002) and second (20022007) rounds of sampling, I will then assess the trend in ecological integrity of each eco-interest
area. This comparison will allow me to compare the quality of old RMPs with current trends in
ecological integrity in each area.
Using contacts at the IDNR, TNC, and the Illinois Natural History Survey, I will search
for old natural resource management plans across the state. I will attempt to find RMPs written
and implemented 15-20 years ago. My search may result in RMPs developed for private lands
and/or for state or national parks. I will assess the quality of the RMPs using Brody’s (2003)
rubric and as these plans will be much older, I expect the quality to be generally lower than
current RMPs. RMPs must vary in their quality, as I will need both high-and low-quality plans
for analysis. RMPs selected must also manage lands sampled by CTAP in the first and second
rounds of sampling.
Utilizing the CTAP data as discussed earlier, I will assess trends in ecological integrity of
each eco-interest area, comparing first and second sampling schemes. I will analyze the changes
in indicator measurements from the first sampling to the second and determine if the trend is
positive or negative. This analysis will allow me to determine which eco-interest areas have the
most positive ecological trends.
Analysis. Using multiple regression techniques, and perhaps structural equation
modeling, I will assess the relationship between RMP quality and ecological trends in the ecointerest area. I will also aassess which components of a RMP are most predictive of ecological
trends.
Limitations. Two of the three limitations described by Koontz and Thomas (2006) are
overcome by my research design. Using readily available CTAP data to measure ecological
42
trends in eco-interest areas keeps me from relying on data collection or monitoring completed by
groups regarding their RMP. Using old RMPs allows for analysis without waiting for long time
lines, and using ecological trends in the eco-interest areas allows for analysis without baseline
data collected prior to RMP implementation. I have not designed an experimental study with a
control group to isolate the effects of a RMP from the many other factors of environmental
change. However, using cases with similar backgrounds that vary in practice represents a natural
experiment, which has been recognized as the ideal research design in exploring environmental
outcomes (Koontz & Thomas, 2006).
Finding these old RMPs may prove more difficult than expected. Some contacts from the
IDNR seem to think it will not be a problem, while others think it will be nearly impossible. As
this component of my research may take the most time, I will start my search at the beginning of
my project.
If I cannot find enough RMPs that fit my criteria, I will expand my search to RMPs and
eco-interest areas outside Illinois. If this occurs, I will no longer be able to rely on the CTAP data
to assess ecological trends in the eco-interest areas. Instead, I will be forced to rely on
perceptions of environmental change, rather than actual measurement of ecological indicators.
Other researchers have measured perceptions of environmental improvements
( Leach & Sabatier 2005; Leach et al, 2002) which is an indirect measure of environmental
improvement. Although not as objective, I could compare the quality of RMPs with the
perception of environmental improvements in the eco-interest areas. I would contact the authors
of the RMPs located and conduct in-depth interviews (on line or over-the-phone) accompanied
with a short quantitative questionnaire (Chambliss & Schutt, 2010) to determine their perceived
changes in ecology as a result of their RMP.
43
Literature Cited
Agrawal, A., & Gibson, C.C. (1999). Enchantment and disenchantment: The role of community
in natural resource conservation. World Development, 27(4), 629-649.
Armbruster, P. & Lande R. (1993). A population viability analysis for African elephant
(Loxodonta africana): How big should reserves be? Conservation Biology, 7(3), 602-610.
Armitage, D. (2005). Adaptive capacity & community based natural resource management.
Environmental Management, 35(6), 703-715.
Bald Eagle Protection Act of 1940. 16 U.S.C. 668-668d, 54 Stat. 250, available online at
< www.fws.gov>.
Barbour, M. T., J. Gerritsen, B. d. Snyder, & J. B. Stribling. (1999). Rapid Bioassessment
Protocols for Use in Streams and Wadeable Rivers: Periphyton, Benthic
Macroinvertebrates and Fish, 2nd ed. EPA, 841-B-99-002. U.S. Environmental Protection
Agency; Office of Water; Washington, D.C.
Beckley T. M., Martz D., Nadeau S., Wall B. & Reimer E. (2008). Multiple capacities, multiple
outcomes: Delving deeper into the meaning of community capacity. Journal of Rural &
Community Development, 3(3), 56–75.
Berke, P. C., Backhurst, M., Laurine, L., Crawford, J.& Dixon, J. (2006). What makes plan
implementation successful? An evaluation of local plans & implementation practices in
New Zealand. Environment & Planning B: Planning & Design, 33, 581-600.
Berke, P. C., Dixon, J.& Ericksen, N. (1999). Do cooperative environmental planning mandates
produce good plans? Empirical results from the New Zealand experience. Environment &
Planning B: Planning & Design, 26, 643-664.
44
Berkes, F. (2004). Rethinking community-based conservation. Conservation Biology, 18(30),
621-630.
Bonnell, Joseph E. & Koontz, T. M. (2007). Stumbling forward: The organizational challenges
of building and sustaining collaborative watershed management. Society & Natural
Resources, 20(2), 153-167.
Borden, R. J., Cline, K. S., Hussey, T., Longsworth, G. & Mancinelli, I. (2007). A river runs
through it: A college-community collaboration for watershed-based regional planning
and education. Human Ecology Forum, 14(1), 90-100.
Bradshaw, B. (2003). Questioning the credibility & capacity of community-based resource
management. The Canadian Geographer, 47(2), 137-150.
Brody, S.D. (2003). Measuring the effects of stakeholder participation on the quality of local
plans based on the principles of collaborative ecosystem management. Journal of
Planning Education & Research, 22, 407-419
Brody, S., Highfield, W. & Carrasco, V. (2004). Measuring the collective planning capabilities
of local jurisdictions to manage ecological systems in southern Florida. Landscape and
Urban Planning, 69, 33-50.
Brook A., Zint, M., & De Young, R. (2003). Landowners’ response to an Endangered Species
Act Listing and implications for encouraging conservation. Conservation Biology, 17(6),
1638-1649.
Burkey, T. V. (1989). Extinction in nature reserves: The effect of fragmentation and the
importance of migration between reserves. Oikos, 55(1), 75-81.
Caughley, G. (1994). Directions in conservation biology. Journal of Animal Ecology, 63(2), 215244.
45
Chambliss, D.F. & Schutt, R.K. (2010). Making sense of the social world: Methods of
investigation. 3rd ed. Thous& Oaks, California: Pine Fords Press of Sage Publications.
Chapin, T. S. & Connerly, C. E. (2004). Attitudes towards growth management in Florida.
Journal of the American Planning Association, 70, 443–52.
Chaskin, R. J., Brown, P., Venkatesh, S., & Vidal, A. (2001). Building community capacity.
Piscataway, New Jersey: Aldine Transaction.
Cheng, A. S. & Daniels, S. A. (2005). Getting to "We" examining the relationship between
geographic scale and ingroup emergence in collaborative watershed management. Human
Ecology Review, 12(1), 30-43.
Conley, A. & Moote, M.A. (2003). Evaluating collaborative natural resource management.
Society and Natural Resources, 16, 371-386.
Cottrell Jr., L. S. (1983). The Competent Community. New Perspectives on the American
Community. Los Angeles, California: Dorsey Press.
Craig, G. (2007). Community capacity-building: Something old, something new. Critical Social
Policy Ltd, 27(3), 335-359.
Dale V. H., & Beyeler, S. C. (2001). Challenges in the development and use of ecological
indicators. Ecological Indicators, 1(1), 3-10.
Davenport , T. E., Phillips N.J., Kirschner B.A., Kirschner, L.T. (1996). The watershed
protection approach: A framework for ecosystem protection. Water, Science, and
Technology. 33(4 & 5), 23 – 26 .
de Loe, R. C. & Kreutzwiser, R. W. (2005). Closing the groundwater protection implementation
gap. Geoforum, 36, 241-256.
46
Department of the Interior, Bureau of Reclamation. (2003). Resource Management Plan
Guidebook: Planning for the future. Assessed online at <http://www.usbr.gov/pmts/planning/RMPG/RMPG.pdf>.
Dillman, D. A. (2000). Mail & Internet surveys: The tailored design method. 2nd ed. New York,
NY: John Wiley & Sons.
Donoghue, E. M. & Sturtevant, V. E. (2007). Social science constructs in ecosystem
assessments: Revisiting community capacity & community resiliency. Society & Natural
Resources, 20, 899-912.
Douglas, J. (1978). Biologists urge US endowment for conservation. Nature, 275(14).
Endangered Species Act of 1973. 16 U.S.C. 1531-1544, 87 Stat. 884. available online at
<www.fws.gov>
Fabricius, C., Folke, C., Cundill, G. & Schultz, L. (2007). Powerless spectators, coping actors,
and adaptive co-managers: A synthesis of the role of communities in ecosystem
management. Ecology and Society, 12(1).
Fiszbien, A. (1997). The emergence of local capacity: Lessons from Colombia. World
Development, 25(7), 1029-1043.
Fleeger, W. E., Becker, M. L. (2006). Creating & sustaining community capacity for ecosystembased management: Is local government the key? Journal of Environmental
Management, 88, 1396-1405.
Foster-Fishman, P .G., Berkowitz, S. L., Lounsbury, S. J. Allen, N. A. (2001). Building
collaborative capacity in community coalitions: A review and integrative framework.
American Journal of Community Psychology, 29(2), 241-261.
47
Foster-Fishman, P., Cantillon, D., Pierce, S. & Van Egeren, L. (2007). Building an active
citizenry: The role of neighborhood problems, readiness, & capacity for change.
American Journal of Community, 39, 91-106
Freemark, K.E. and B. Collins. 1992. Landscape ecology of birds breeding in temperate forest
fragments. p. 443-454 IN: J.M. Hagan and D.W. Johnston (eds.). Ecology &
Conservation of Neotropical Migrant Landbirds. Smithsonian Institution Press,
Washington, DC: Fung & Wright.
Gahin, R., Veleva, V., Hart, M.(2003). Do indicators help create sustainable communities?
Viewpoint, 8(6), 661-666.
Government Accountability Office (1994). Species protection on nonfederal lands. GAO/RCED95-16, online at < http://www.gao.gov/archive/1995/rc95016.pdf>.
Gibbons, A. (1992). Conservation Biology in the Fast Lane. Science, New Series, 255(5040), 2022.
Gilpin, M. E., Soulé, M.E. (1986). Minimum viable populations: processes of species extinction.
In Conservation biology: the science of scarcity and divers. Sunderland, Massachusetts:
Sinauer Associates.
Goodman R. M. Speers, M.A., McElroy, K., Fawecett, M., Parker, E., Smith S.R., Sterling, T.
D., Wallerstein, N. (1998). Identifying and defining the dimensions of community
capacity to provide a basis for measurement. Health Education and Behavior, 25(3), 258278.
Gray, G. J. Fisher, L. & Jungwirth, L., (2001). An introduction to community-based ecosystem
management. Journal of Sustainable Forestry, 25-34.
48
Griffin, C. B., (June 1999). Watershed councils: An emerging form of public participation in
natural resource management. Journal of the American Water Resources Association,
35(3), 505-518.
Habron, G. (2003). Role of adaptive management for watershed councils. Environmental
Management, 31(1), 29-41.
Hancock, T. (1999). People, partnership & human progress: Building community capital. Health
Promotion International, 16 (3), 275-280.
Herkert, J. R. (1993). The effects of habitat fragmentation on Midwestern grassland birds.
Ecological Applications, 4(3). 461-471
Hilsenhoff, W. L. (1982). Using the biotic index to evaluate water quality in streams. Technical
Bulletin Wisconsin Department of Natural Resources, 132.
Hilsenhoff, W.L. (1987). An improved biotic index of organic stream pollution. Great Lakes
Entomologist, 20 (1), 31-40.
Hilsenhoff, W. L. (1998). A modification of the biotic index of organic stream pollution to
remedy problems and permit its use throughout the year. The Great Lakes Entomologist,
31(1), 1 - 12.
Hooper, A. (1993). Effects of season, habitat, and an impoundment on twenty five benthic
community measures used to assess water quality. M.S. Thesis. College of Natural
Resources, University of Wisconsin-Stevens Point. 443 pp.
Hope, B. (2006). Online network survey utility for organizational network analysis. Available
online at <http://www.surveymonkey.com/s.aspx?sm=JbeN1eq4AWhuxJjDhIgY7yWG9l5N4D %2fZ8bOLGMyAMcw%3d>.
49
Illinois Department of Natural Resources (IDNR). (2005). The Illinois comprehensive wildlife
conservation plan & strategy. Version 1.0. Available online at <http://dnr.state.il.us/ORC/WildlifeResources/theplan/final/>.
International Union for the Conservation of Nature (IUCN). Vié, J.-C., Hilton-Taylor, C. &
Stuart, S.N. (eds.) (2009). Wildlife in a changing world: An analysis of the 2008 IUCN
Red List of Threatened Species. Accessed online at <http://data.iucn.org/dbtwwpd/edocs/RL-2009-001.pdf>.
Johnson, C. N. (2003). Causes of extinction of vertebrates during the Holocene of mainland
Australia: arrival of the dingo, or human impact? The Holocene, 13(6), p. 941-948.
Karr, J.R., (1991). Biological integrity: a long neglected aspect of water resource management.
Ecological Applications, 1, 66–84.
Kenney, D., 2000. Are community watershed groups effective? Confronting the thorny issue of
measuring success in: Across the Great Divide: Explorations in Conservation & the
American West, pages 188-193. Edited by Philip Brick, Donald Snow, & Sarah Van de
Wetering. Washington DC: Island Press.
Kessler, W. B. (1993). What resource inventories don't tell us about biological diversity, and
what we really need to know. The Conservation Legacy, 35.
Koontz, T.M. & Thomas, C.W. (2006). What do we know & need to know about the
environmental outcomes of collaborative management? Public Administration Review,
Special Issue: Articles on Collaborative Public Management.
Krebs, V. & Holley, J. (2005). Building adaptive communities through network weaving.
Nonprofit Quarterly, Winter, 66-72
50
Krueger, R.A. & Casey, M.A. (2000). Focus groups: A practical guide for applied research. 3rd
ed. Thousand Oaks, California: Sage Publications.
Kusel, J. (1996). Well-being in forest-dependent communities, Part I: A new approach. In Sierra
Nevada Ecosystem Project: Final report to Congress, vol. II, Assessments and scientific
basis for management options (pp. 361-374). Davis, CA: University of California,
Centers for Water and Wildland Resources.
Lacey Act of 1900. 16 U.S.C. §§ 3371-3378, available online at < www.fws.gov>.
Land and Water Conservation Fund Act of 1965. 16 U.S.C. 4601-1h, available online at <
www.fws.gov>.
Larson, D. P., Kincaid, T. M., Jacobs, S. E., & Urquart, N. S. (2001). Designs for evaluating
local and regional scale trends. BioScience, 15(12), 1069-1078.
Lasker, R. & Weiss, E. (2003). Broadening participation in community problem solving: A
multidisciplinary model to support collaborative practice and research. Journal of Urban
Health: Bulletin of the New York Academy of Medicine, 80(1), 14-47.
Leach, W. D., Pelkey, N.W. & Sabatier, P.A. (2002). Stakeholder partnerships as collaborative
policymaking: Evaluation criteria applied to watershed management in California &
Washington. Journal of Policy Analysis & Management, 21(4), 645-670.
Leach, W.D., Sabatier P. A. 2005. Are trust and social capital the keys to success? In Swimming
Upstream: Collaborative Approaches to Watershed Management, edited by P.A.
Sabatier, 233-258. Cambridge: MIT Press.
Leigh,P. (2005). The ecological crisis, the human condition and community-based restoration as
an instrument for its cure. Ethics in Science and Environmental Politics, 3-15.
51
Lopez, R.D., Fennessy M. S. (2002). Using the floristic quality assessment index (FQAI) in
wetlands as a biological indicator of landscape condition along a gradient of human
influence. Ecological Applications, 12(2), 487-497.
Margerum, R. D. (2007). Overcoming locally based collaboration constraints. Society & Natural
Resources, 20(2), 135-152.
Marre, A., Weber, B. (2007). Assessing community capacity in rural America: Some lessons
from two rural observatories. Working paper number RSP 07-02. Rural Studies Program,
Oregon State University.
McDonald, G.T., McAlpine, C.A., Taylor, B.M. & Vagg, A.R. (2003). Criteria & methods for
evaluating regional natural resource management plans in tropical savanna regions.
Savannas, CRC Project 3.2.1, Darwin.
Mendis-Millard, S. & Reed, M. G. (2007). Understanding community capacity using adaptive &
reflexive research practices: Lessons from two Canadian biosphere reserves. Society &
Natural Resources, 20(6), 543-559.
Merenlander, A.M., Huntsinger, L., Guthey, G., Fairfax, S. K. (2003). Land trusts and
conservation easements: Who is conserving what for whom? Conservation Biology,
18(1), 65-75.
Migratory Bird Consevation Act of 1929. 16 U.S.C. 715-715d, 715e, 715f-715r, available online
at < www.fws.gov>.
Milward, H.B. & Provan, K.G. (1998). Measuring network Structure. Public Administration, 76,
387-407.
52
Molano-Flores, B. 2002. Critical Trends Assessment Program monitoring protocols. Illinois
Natural History Survey, Office of the Chief, Technical Report 2002-2, Champaign, IL. 38
pp, + Figures, Tables, and Appendix.
Moore, S.A., Severn R.C., Millar, R. (2006). A conceptual model of community capacity for
biodiversity conservation outcomes. Geographical Research, 44(4), 361–371.
Myers, N., Mittermeier, R. A., Mittermeier C. G., da Fonseca G. A. B., Kent, J. (2000).
Biodiversity hotspots for conservation priorities. Nature, 203, 853-858.
Noss, R. F. (1990). Indicators for monitoring biodiversity: A hierarchical approach.
Conservation Biology, 4, 355-364.
Olsson, P., Folek, C. & Hahn, T. (2004). Socio-ecological transformation for ecosystem
management: The development of adaptive co-management of a wetland landscape in
southern Sweden. Ecology and Society, 9(4).
Paine, C. R. (1997). Abundance and nesting productivity of wetland-dependent birds in
northeastern Illinois: Phase I. Methods of monitoring abundance and productivity. Final
Report. Max McGraw Wildlife Foundation. Dundee, IL
Parrish, J. D., Braun, D. P. & Unnasch, R.S. (2003). Are we conserving what we say we are?
Measuring ecological integrity within protected areas. BioScience, 53(9), 851-860.
Pavey, J. L., Muth, A. B., Ostermeier, D. & Steiner D. M. (2007). Building capacity for local
governance: An application of interactional theory to developing a community of interest.
Rural Sociology, 72(1), 90-110.
Pimm S. L., Russell G. J., Gittleman J. L., Brooks, T. M. (1995). The future of biodiversity.
Science, 269 (5222), 347-350.
53
Plafkin, J. L., M. T. Barbour, K. D. Porter, S. K. Gross, & R. M. Hughes. (1989). Rapid
bioassessment protocols: For use in streams and rivers: Benthic macroinvertebrates and
fish. EPA, 444/4-89-001. U.S. Environmental Protection Agency; Office of Water;
Washington, D.C.
Polasky, S., & Doremus, H. (1995). When the truth hurts: Endangered species policy on
private land with imperfect information. Journal of Environmental economics and
management, 35, 22-47.
Provan, K. G., Veazie, M. A., Staten, L. K. & Teufel-Shone, N. I. (2005). The use of network
analysis to strengthen community partnerships. Public Administration Review, 65(5),
603-613.
Pullin A.S., Knight T.M. (2001). Effectiveness in conservation practice: Pointers from medicine
and public health. Conservation Biology 15, 50-54.
Pullin, A.S., Knight, T.M., Stone, D.A. & Charmen, K. (2004). Do conservation managers use
scientific evidence to support their decision-making? Biological Conservation, 119, 245–
252.
Putnam, R. D. (1993). The prosperous community: social capital and public life. The American
Prospect, 4 (13).
Reid, T. S., Murphy, D. D. (1995). Providing a regional context for local conservation action.
BioScience, 45, Supplement: Science and Biodiversity Policy, S84-S90.
Reid, W. V., McNeely, J. A., Tunstall, D. B., Bryant, D. A., Winograd, M. (1993). Biodiversity
indicators for policymakers. World Resources Institute, Washington, DC.
Reld, W. V. (1998). Biodiversity hotspots. TREE, 13 (7), 275-280.
54
Rhoads, B. L., Wilson, D., Urban, M. & Herricks, E. E. (1999). Interaction between scientists
and nonscientists in community-based watershed management: Emergence of the
concepts of stream naturalization. Environmental Management, 24(3), 297-308.
Rooney, T. P., Rogers, D. A. (2002). The modified Floristic Quality Index. Natural Areas
Journal, 22 (4), 340.
Rohlf, D. J. (1991). Six biological reasons why the Endangered Species Act doesn't work-and
what to do about it. Conservation Biology, 5(3), 273-282.
Salafsky, N., Margoluis, R. (1999). Threat reduction assessment: A practical and cost effective
approach to evaluating conservation and development projects. Conservation Biology, 13,
830-841.
Schaeffer, D. J., Herricks, E. E., Kerster, H. W. (1988). Measuring ecosystem health.
Environemtnal Management, 12, 445-455.
Soulé, M.E. (1991). Conservation: tactics for a constant crisis. Science 253, 744-750.
Soulé, M. E. (1985). What is conservation biology? BioScience, 35(11), The Biological
Diversity Crisis, 727-734.
Species Preservation Act of 196. P.L. 89-669, 80 Stat. 926, available online at < www.fws.gov>.
Sutherland W. J., Pullin A. S., Dolamn, P.M. & Knight T.M. (2004). The need for evidencebased conservation. TRENDS in Ecology and Evolution, 19(6), 305-308.
Thomas, A. C., Green, R. E., Bakkenes, M., Beaumont, L. J., Collingham, Y. C., Erasmus, B. F.
N., de Siqueira, M. F., Grainger, A., Hannah, L., Hughes, L., Huntley, B., van
Jaarsveld, A. S., Midgley, G. F., Miles, L., Ortega-Huerta, M. A., Peterson, A. T.,
Phillips A. L. & Williams, S. E. (2004). Extinction risk from climate change. Nature 427,
145-148.
55
The Nature Conservancy. (2004). Conservation easements, conserving land, water and a way of
life. TNC published document, available online at http://www.nature.org/aboutus/howwework/conservationmethods/privatelands/conservationeasements/files/consrvtn_ea
semnt_sngle72.pdf.
USDA Natural Resource Conservation Service. (2009a).Conservation Reserve Programs (CRP).
Retrieved August 18, 2009, retrieved from http://www.nrcs.usda.gov/programs/CRP/.
USDA Natural Resource Conservation Service. (2009b).Wetland Reserve Programs
(WRP).Retrieved August 18, 2009 from
http://www.ncgc.nrcs.usda.gov/programs/wetlands-reserve.html.
USDA Natural Resource Conservation Service. (2009c). Emergency Wetland Reserve
Programs- (EWRP) Retrieved August 18, 2009 from
http://www.ia.nrcs.usda.gov/programs/EWRPeasements.html.
USDA Natural Resource Conservation Service. (2009d).Wildlife Habitat Incentives Programs
(WHIP). Retrieved August 18, 2009 from http://www.nrcs.usda.gov/programs/whip/.
USDA Natural Resource Conservation Service. (2009e).Environmental Quality Incentives
Programs (EQIP). Retrieved August 18, 2009 from http://www.nrcs.usda.gov/programs/eqip/.
Van Dyke, F. (2008). Conservation Biology: Foundations, Concepts, Applications, 2n ed.
Boston, MA: McGraw Hill.
Vitousek P.M., Mooney H.A., Lubchenco J. & Melillo J.M. (1997) Human domination of Earth's
ecosystems. Science, 277, 494-499.
56
Vora, R. S. (1997). Developing programs to monitor ecosystem health and effectiveness of
management practices on Lakes Sates National Forest, USA. Biological Conservation,
80, 289-302.
Walker, B., Gunderson, L., Kinzig, A., Folke, C., Carpenter, S. Schultz, L. (2006). A handful of
hueristics and some propositions for understanding resilience in social-ecological
systems. Ecology and Society, 11:1-13
Wilcove, D.S., Bean M.J., Bonnie, R. & McMillian, M. (1996). Rebuilding the ark: Toward a
more effective Endangered Species Act for private land. Washington (DC):
Environmental Defense Fund.
Wilson, E. O. (2002). The Future of Life. New York, New York: Random House Inc.
Woodley, S. (1993). Monitoring and measuring ecosystem integrity in Canadian National Parks.
In Ecological Integrity and the Management of Ecosystems, eds S. Woodley, J. Kay & G.
Francis. St Lucie Press, Delray Beach, FL, pp. 155-176.
57
Appendix 1. Map of COA boundaries
Source: IDNR, 2005
58
Appendix 2. Emailed invitation to participate in focus group
From: Natalie J. Mountjoy
Hello! Thank you for taking the time to read through the following:
I am the researcher from SIUC working alongside the Conservation Opportunity Area project manager with SIUC
and the Illinois Department of Natural Resources. I have been working with Dr. Matt Whiles, Assistant Professor in
the Department of Zoology and Center for Ecology at Southern Illinois University, Carbondale to assess the capacity
of the Conservation Opportunity Areas (COAs) that were identified in the Illinois Wildlife Action Plan.
http://dnr.state.il.us/orc/wildliferesources/theplan/outlines.pdf A map of the COAs is attached.
I would like to invite you to participate in a focus group discussion as part of a research project titled, Conservation
Opportunity Areas and Conservation Success: The capacity of community-base initiatives to contribute to successful
ecosystem management. You were contacted due to you participation in a recent meeting regarding a COA in your
area. The primary objective of this research study is to evaluate the capacity of COAs and their respective
subgroups, the quality of natural resource management plans they produce and the current ecological health of the
COA area.
You have been selected to participate in this focus group because you are a representative of an agency, nongovernmental organization or other group who may have insight about one or more Conservation Opportunity
Areas. The focus group session will last 45 ‐ 60 minutes. The primary activity will be a discussion of capacity and
collaboration within and among COA subgroups, with the primary goal of assisting in the formation of a
quantitative survey instrument. All members of COA subgroups will be invited to take the COA survey once
construction is complete.
The focus group discussion regarding COAs you may be familiar with is scheduled for (DATE AND TIME).
If you wish to have your name removed from any future mailings associated with this study, please reply to this email with the message: “remove my name from the mailing list.” If you do not return the opt-out message, I will call
within the next week to discuss your participation.
Questions about this study can be directed to
Natalie J. Mountjoy
Department of Zoology and Center for Ecology
Southern Illinois University
Carbondale, IL 62901-6501
618.453.4126 -or- 270.313.4044
mountjoy@siu.edu
Thank you for taking the time to assist me in this research.
Sincerely,
Natalie J. Mountjoy
This project has been reviewed and approved by the SIUC Human Subjects Committee. Questions concerning your
rights as a participant in this research may be addressed to the Committee Chairperson, Office of Research
Development and Administration, SIUC, Carbondale, IL 62901-4709. Phone (618) 453-4533. E-mail:
siuhsc@siu.edu
59
Appendix 3. Informed consent statement
I agree to participate in a focus group discussion as part of a research project titled, Conservation
Opportunity Areas and Conservation Success: The capacity of community-base initiatives to
contribute to successful ecosystem management. I understand the primary objective of this
research study is to evaluate the capacity of COAs and their respective, the quality of natural
resource management plans they produce and the current ecological health of the COA area.

I understand that if I agree to participate in this study, I will be asked to participate in a
focus group session that will last 45 ‐ 60 minutes. The primary activity will be a
discussion of capacity and collaboration within and among COA subgroups, with the
primary goal of assisting in the formation of a quantitative survey instrument. All
members of COA subgroup will be invited to take the COA survey once construction is
complete.

I am aware that my participation is voluntary and may be withdrawn at any time without
penalty or prejudice. If I have any additional questions concerning this study, I may
contact Natalie J. Mountjoy, Department of Zoology and Center for Ecology at Southern
Illinois University, Carbondale, IL 62901-6501, mountjoy@siu.edu -or- 618.453.4126

I understand that the intended benefits of this study center upon the development of a
model for success in COAs and the assist the IDNR in assistance efforts to COAs.

I understand that it is unlikely that I will experience risks and/or discomforts during this
study.

I understand that all information gathered during this focus group will be kept
confidential by keeping separate files of consent forms and study data. In addition, no
individual participant will be identified in any report. Only quotes and aggregate data will
be reported.

However, I also understand that when participating in a focus group, confidentiality
among the members of the group cannot be guaranteed.
I understand that my consent to participate in this project does not constitute a waiver of
any legal rights or redress I might have as a result of my participation, and I acknowledge
that I have received a copy of this consent form.


I understand this project has been reviewed and approved by the SIUC Human Subjects
Committee. Questions concerning your rights as a participant in this research may be
addressed to the Committee Chairperson, Office of Research Development and
Administration, SIUC, Carbondale, IL 62901-4709. Phone (618) 453-4533. Email: siuhsc@siu.edu
____________________________________
Signature of Subject
________________
Date
60
Appendix 4. Participant information form
Please provide us with some information about yourself. This information will be used for
reporting purposes only. If you do not wish to provide this information please disregard this
request.
Gender
What is your race/ethnicity?
ian/Non‐Hispanic
‐ Please specify __________________________________
What is your age range?
‐24 years
‐34 years
‐44 years
‐54 years
‐64 years
‐74 years
Which is the highest level of education you have completed?
Please provide the name of the COA sub-group in which you are active.
______________________________________________________________________________
Please list the COA in which your group is active (if active in multiple COAs, please all).
______________________________________________________________________________
Follow‐up contact—Optional
We would like to stay in touch with you. Kindly provide your e‐mail address if you would like to
be kept informed regarding our progress on this project.
My e‐mail address is: _______________________________________________
My name is (optional):____________________________________________
61
Appendix 5. Email invitation to participate in the web survey
From: Natalie J. Mountjoy
Hello! Thank you for taking the time to read through the following:
I am the researcher from SIUC working alongside the Conservation Opportunity Area project manager for the
Illinois Department of Natural Resources. I have been working with Dr. Matt Whiles, Assistant Professor in the
Department of Zoology and Center for Ecology at Southern Illinois University Carbondale to assess the capacity of
the Conservation Opportunity Areas (COAs) that were identified in the Illinois Wildlife Action Plan.
http://dnr.state.il.us/orc/wildliferesources/theplan/outlines.pdf A map of the COAs is attached.
You were contacted due to you participation in a recent meeting regarding a COA in your area. I would like to invite
you to participate in an online survey as part of a research project titled, Conservation Opportunity Areas and
Conservation Success: The capacity of community-base initiatives to contribute to successful ecosystem
management. The primary objective of this research study is to evaluate the capacity of COAs and their respective
subgroups, the quality of natural resource management plans they produce and the current ecological health of the
COA area. The data collected will be used to help guide natural resources efforts such as planning and on-theground implementation of habitat improvement practices in these areas.
This survey will take an estimated 20 minutes to complete. All your responses will be kept confidential within
reasonable limits. Only people directly involved with this project will have access to the surveys. A blind copy
format will be used so that the list of recipients will not appear in the header. If you have significant knowledge
about more than one COA that you would like to share, please feel free to complete the survey up to three times.
Just follow the link from this email for each subsequent survey.
http://www.surveymonkey.com/A URL to be determined
Completion and return of this survey indicates voluntary consent to participate in this study.
If you wish to have your name removed from any future mailings associated with this survey, please reply to this email with the message: “remove my name from the mailing list.”
If you do not return the opt-out message, two (2) reminder messages will be sent during the next five (5) weeks.
Questions about this study can be directed to
Natalie J. Mountjoy
Department of Zoology and Center for Ecology
Southern Illinois University
Carbondale, IL 62901-6501
618.453.4126 -or- 270.313.4044
mountjoy@siu.edu
Thank you for taking the time to assist me in this research.
Sincerely,
Natalie J. Mountjoy
This project has been reviewed and approved by the SIUC Human Subjects Committee. Questions concerning your
rights as a participant in this research may be addressed to the Committee Chairperson, Office of Research
Development and Administration, SIUC, Carbondale, IL 62901-4709. Phone (618) 453-4533. E-mail:
siuhsc@siu.edu
62
Appendix 6. List of accepted ecological indicators from Vora (1995)
63
Appendix 7. Indicators used by CTAP as described by CTAP and augmented from the literature
INDICATOR
All Strata Total
spp
(species richness)
All Strata Native
spp
All Strata
Introduced spp
All Strata TE spp
All Strata
Sensitive spp
All Strata Mean
CC
All Strata Mean
Native CC
All Strata FQI
All Strata FQI
Native spp
Patch Size
(hectares)
# of T&E (Total)
# of T&E (State)
# of T&E
(Federal)
Species Richness
Dominant
Species
DESCRIPTION
The total number of native plant species sampled in the herbaceous layer, shrub layer, and tree
layer at a site. (=Species Richness)
The total number of plant species sampled in the herbaceous layer, shrub layer, and tree layer at
a site. (=Species Richness)
The total number of non-native plant species sampled in the herbaceous layer, shrub layer, and
tree layer at a site. (=Species Richness)
The total number of state and federally threatened or endangered plant species sampled in the
herbaceous layer, shrub layer, and tree layer at a site.
The total number of sensitive plant species sampled in the herbaceous layer, shrub layer, and
tree layer at a site. Sensitive species have a coefficient of conservatism (CC) value of 7, 8, 9, or
10.
The coefficient of conservativism (CC) summed and averaged for the all the plants sampled in
the herbaceous layer, shrub layer, and tree layer at a site. CC is a value 0-10 assigned to each
plant in the Illinois flora that reflects the plant's tolerance to disturbance, as well as varying
degrees of fidelity to specific habitat integrity.
The coefficient of conservativism (CC) summed and averaged for the all the native plants
sampled at a site. CC is a value 0-10 assigned to each plant in the Illinois flora that reflects the
plant's tolerance to disturbance, as well as varying degrees of fidelity to specific habitat
integrity.
Floristic Quality Index (FQI) value for all the plants sampled in herb layer, shrub layer, and tree
layer at a site. The Floristic Quality Assessment is a method to assess floristic integrity. Each
taxon in Illinois is assigned an integer from 0-10 termed the coefficient of conservatism (CC).
CC reflects the plant's tolerance to disturbance, as well as varying degrees of fidelity to specific
habitat integrity. FQI = meanCC * square root of N. N is the total number of plant taxa sampled
Floristic Quality Index (FQI) value for native plants sampled in herb layer, shrub layer, and tree
layer at a site. The Floristic Quality Assessment is a method to assess floristic integrity. Each
taxon in Illinois is assigned an integer from 0-10 termed the coefficient of conservatism (CC).
CC reflects the plant's tolerance to disturbance, as well as varying degrees of fidelity to specific
habitat integrity. FQI = meanCC * square root of N. N is the total number of plant taxa
sampled.
This is the area where point counts were collected. Patch size is given in hectares.
Total number of threatened and endangered species, both state and federal. State and federally
threatened species = 9. State and federally endangered species = 34. Total state threatened and
endangered species = 43
Total number of state threatened and endangered species. State threatened species = 8. State
endangered species = 26. Total state threatened and endangered species = 3
Total number of federally threatened and endangered species. Federally threatened species = 1.
Federally endangered species = 8. Total federally threatened and endangered species = 9
Total number of species in a site.
Species with the greatest number of individuals per site.
# of Habitat
Dependent
Species
Habitat dependent species (HD) are those that can only be found in that particular habitat.
Number of HD per habitat: Forest = 63, Grassland = 21, Wetland = 49. Classifications of these
species as HD is based on Herkert (1993) and Freemark and Collins (1992) grassland and forest
bird species. Wetland Dependent Species (WDS) follow Paine (1997), with additional WDS
added by the CTAP ornotologists.
Dominant Habitat
DS
Habitat dependent species with the greatest number of individuals.
64
Appendix 7. continued
# of Area
Sensitive Species
Dominant AREA
SENSITIVE
SPECIES
# of Low AREA
SENSITIVE
SPECIES
# of AREA
SENSITIVE
SPECIES (moderate)
Dominant AREA
SENSITIVE
SPECIES (mod.)
# of AREA
SENSITIVE
SPECIES (high)
Dominant AREA
SENSITIVE
SPECIES (high)
E
P
T
EPT
DOMTAXON
DOMCOUNT
EPTTOTL
DOMPERC
HBI
HBITOTL
EPTPERC
EPTQUAL
HBIPERC2
HBIQUAL
DOMPERC
HABQUAL
Area sensitive species (AS) are those species that show different levels of tolerance to
habitat fragmentation. These species can be classified as "high," "moderate," or "low."
Number of AS species per habitat: Forest = 58 total (high = 22, moderate = 23, and low =
13) and Grassland = 16 total (high = 7, moderate = 4, and low = 5). In this section we only
report high and moderate AS. Classifications of these species as AD is based on Herkert
(1993) and Freemark and Collins (1992) grassland and forest bird species.
Area sensitive species with the greatest number of individuals per site. This is based on
moderate and high.
Species with a low area-sensitivity show the least influenced by habitat fragmentation.
Number of low AS species per habitat: Forest = 13, Grassland = 5
Species with a moderate area-sensitivity show an intermediate response to habitat
fragmentation. Number of moderate AS species per habitat: Forest = 23 and Grassland = 4
Moderate area-sensitivity species with the greatest number of individuals per site.
Species with a high area-sensitivity are those to be the most influenced by habitat
fragmentation. Number of high AS species per habitat: Forest = 22 and Grassland = 7
High area-sensitivity species with the greatest number of individuals per site.
Number of taxa of Ephemeroptera (mayflies)
Number of taxa of Plecoptera (stoneflies)
Number of taxa of Trichoptera (caddisflies)
Number of taxa of the aquatic insects Ephemeroptera, Plecoptera, and Trichoptera from all
samples taken at a site.
Single most dominant taxon.
Abundance of dominant taxon.
Abundance of all EPT for a site/date visit.
Percentage abundance of the dominant taxon.
Hilsenhoff Biotic Index. An abundance-weight average of all species pollution tolerance.
This was developed in Wisconsin for use in detecting organic pollution (as from sewage
treatment plants or livestock pasturing and feedlots). Most EPT taxa in Illinois have a
tolerance value assigned by Hilsenhoff, those without were dropped from the calculation.
Using only EPT taxa, the scale runs from 0 to 9 (Hilsenhoff provided values to 10 for some
non-EPT taxa), with 9 indicating heavy organic pollution and low scores indicating a
community of sensitive taxa.
Number of specimens used in HBI calculation.
Site-date visit percentile rank for EPT richness based on statewide data.
Site-date visit tentative quality rating based on EPTPERC such that values =90 = Excellent,
75-89 = Good, 50-74 = Fair, 30 to 49 = Poor, <30 = Very Poor.
Site quality rating based on HBI scores. Due to higher values of HBI values indicating
poorer conditions, this is calculated as 1-%tile ranking in statewide data.
Site-date visit tentative quality rating based on HBIPERC2. Values <4.00 = Excellent, 4.63
to 4.00 = Good, 5.19 to 4.64 = Fair, 5.78 to 5.20 = Poor, and >5.78=Very Poor.
Site-date visit percentile rank for habitat quality based on statewide data.
Site-date visit tentative quality rating based on HABPERC such that values =130 =
Excellent, 116-129 =Good, 93-115 = Fair, 74 to 92 = Poor, <73 indicates very poor habitat
65
Appendix 7. continued
OVERALL
ALLQUAL
TEMP
DO2
PH
CONDUCT
PERFINES
HABITAT
Overall percentile score for a site-date visit, calculated as follows: Overall = (EPTPERC
*0.4)+(HBIPERC2*0.2)+ (HABPERC*0.4). HBIPERC2 was weighted as being less important
because HBI was deemed as not being as sensitive to environmental degration as EPT richness and
habitat quality.
Tentative quality designation based on the value of a composite percentile score "Overall" such that
Overall =90 = Excellent, 75-89 = Good, 50-74 = Fair, 30 to 49 = Poor, <30 = Very Poor.
Water temperature in Celsius. This is a single measure and not intended to be a comprehensive over
large time frames.
Dissolved oxygen concentration in stream water expressed in mg/l. This is a single measure and not
intended to be a comprehensive over large time frames.
Concentration of hydrogen ions in stream water expressed as pH units (ranges 0-14, <7 acidic, >7
basic). This is a single measure and not intended to be comprehensive over large time frames.
Conductivity, an indirect measure of dissolved ionic compounds in water. Urbanization (sewage,
roadway runoff, etc.) elevates this above background (usually no greater than 650 uS/cm). Some
values may be <100 in extreme southern Illinois.
Percentage of stream bottom covered by fine sediments (sand, silt, and clay). Higher values usually
indicate degradation.
A cumulative habitat quality score consisting of 12 measures of in-stream and riparian habitat
characteristics. Scale ranges from 0-180.
66
Appendix 8. Resource management plan evaluation instrument from Brody (2003)
RMP Characteristic
Factual Basis
A. Resource inventory
Ecosystem boundaries/edges
Ecological zones/habitat types
Ecological functions
Species ranges
Habitat corridors
Distributions of vertebrate species
Areas with high biodiversity/species richness
Vegetation classified
Wildlife classified
Vegetation cover mapped
Threatened and endangered species
Invasive/exotic species
Indicator/keystone species
Soils classified
Wetlands mapped
Climate described
Other water resources
Surface hydrology
Marine resources
Graphic representation of transboundary resources
Other prominent landscapes
B. Ownership patterns
Conservation lands mapped
Management status identified for Network of conservation lands
Conservation lands mapped
Distribution of species within network of conservation lands
C. Human impacts
Population growth
Road density
Fragmentation of habitat
Wetlands development
Nutrient loading
Water pollution
Loss of fisheries/marine habitat
Alteration of waterways
Other factors/impacts
Value of biodiversity identified
Existing environmental
Carrying capacity measured
Regulations described
Incorporation of gap analysis data
Factual Basis sub-total
Goals and objectives
Protect integrity of ecosystem
Protect natural processes
0 (not present)
1 (mentioned)
2 (specific)
67
Appendix 8. continued
RMP Characteristic
Maintain intact patches of native species
Establish priorities for native
Protect rare/unique landscape
Species/habitat protection elements
Protect rare/endangered species
Maintain connection among wildlife habitats protected areas
Represent native species within
Maintain intergenerational sustainability of ecosystems
Balance human use with maintaining viable wildlife populations
Restore ecosystems/critical habitat
Other goals to protect ecosystems
Goals are clearly specified
Presence of measurable objectives
Goals and objectives sub-total
Interorganization coordination and capabilities
Other organizations/stakeholders
Coordination with other identified organizations/jurisdictions
specified
Coordination within jurisdiction specified
Intergovernmental bodies specified
Joint database production
Coordination with private sector
Information sharing
Links between science and policy
Position of jurisdiction within specified bioregion specified
Intergovernmental agreements
Conflict management processes
Commitment of financial resources
Other forms of coordination
Interorganization coordination and capabilities sub-total
Policies, tools, and strategies
A. Regulatory tools
Resource use restrictions
Density restrictions
Restrictions on native vegetation removal
Removal of exotic/invasive species
Buffer requirements
Fencing controls
Public or vehicular access
Phasing of development
Controls on construction restrictions
Conservation zones/overlay districts
Performance zoning
Subdivision standards
Protected areas/sanctuaries
Urban growth boundaries to exclude habitat
0 (not present)
1 (mentioned)
2 (specific)
68
Appendix 8. continued
RMP Characteristic
Urban growth boundaries to exclude habitat
Targeted growth away from habitat
Capital improvements
Site plan review programming
Habitat restoration actions
Actions to protect resources in other jurisdictions
Other regulatory tools
B. Incentive-based tools
Density bonuses
Clustering away from habitats
Transfer of development rights
Preferential tax treatments
Mitigation banking
Other incentive-based tools
C. Land acquisition programs
Fee simple purchase
Conservation easements
Other land acquisition techniques
D. Other strategies
Designation of special taxing districts for acquisition funding
Control of public investments and projects
Monitoring of ecological health and human impacts
Public education programs
Policies, tools, and strategies sub-total
Implementation
Designation of responsibility
Provision of technical assistance
Identification of costs or funding
Provision of sanctions
Clear timetable for implementation
Regular plan updates and assessments
Enforcement specified
Monitoring for plan effectiveness and response to new
information
Implementation sub-total
RMP TOTAL
0 (not present)
1 (mentioned)
2 (specific)
69
Appendix 9. Acronyms
AS- Area-sensitive species
C- Coefficient of conservation
CBI- Community-based Initiative
CBNRM- Community-based Natural Resource Management
CRP- Conservation Reserve Programs
CTAP- Critical Trends Analysis Program
EPT- Ephemeroptera, Plecoptera, and Trichoptera
EQUIP- Environmental Quality Incentives Programs
EWRP- Emergency Wetland Reserve Program
FQI- Flouristic Quality Index
HD- Habitat-Dependent species
HBI- Hilsenhoff Biotic Index
HQI- Habitat Quality Index
IRB- Internal Review Board
NRCS- Natural Resource Conservation Service
NGO- Non-governmental Organization
RMP- Resource Management Plan
SIUC- Southern Illinois University Carbondale
USDA- United States Department of Agriculture
WHIP- Wildlife Habitat Incentives Programs
WRP- Wetland Reserve Programs
70